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==== Front Case Rep GenetCase Rep GenetCRIGCase Reports in Genetics2090-65442090-6552Hindawi Publishing Corporation 10.1155/2016/4645716Case ReportRing Chromosome 4 in a Child with Multiple Congenital Abnormalities: A Case Report and Review of the Literature http://orcid.org/0000-0001-9214-7808Paththinige C. S. 1 http://orcid.org/0000-0003-0994-6954Sirisena N. D. 1 http://orcid.org/0000-0003-3540-8607Kariyawasam U. G. I. U. 1 Saman Kumara L. P. C. 2 http://orcid.org/0000-0002-3264-6856Dissanayake V. H. W. 1 * 1Human Genetics Unit, Faculty of Medicine, University of Colombo, 00800 Colombo, Sri Lanka2Castle Street Hospital for Women, 00800 Colombo, Sri Lanka*V. H. W. Dissanayake: vajirahwd@hotmail.comAcademic Editor: Mohnish Suri 2016 16 8 2016 2016 46457162 5 2016 20 7 2016 Copyright © 2016 C. S. Paththinige et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.A female child born preterm with intrauterine growth retardation and presenting with facial dysmorphism with clefts, microcephaly, limb deformities, and congenital abnormalities involving cardiovascular and urinary systems is described. Chromosomal analysis showed a de novo 46,XX,r(4)(p15.3q35) karyotype. The clinical features of the patient were compared with the phenotypic characteristics of 17 previously reported cases with ring chromosome 4 and those with Wolf-Hirschhorn syndrome (4p-). Clinical features observed in this case are consistent with the consensus phenotype in ring chromosome 4. Patent ductus arteriosus and bilateral talipes equinovarus observed in this baby widen the phenotypic spectrum associated with ring chromosome 4. ==== Body 1. Introduction Ring chromosome is a rare form of structural chromosomal abnormality which commonly results from the breakage of an end segment of both the short and long arms of the chromosome and subsequent end joining. The site of breakage and the amount of chromosomal material lost vary from case to case even when a single chromosome is considered. The cytogenetic variation in the presence of a ring chromosome depends on the ring size, rate of sister chromatid exchange events, and the viability of altered cell lines [1, 2]. Phenotypic variation of these individuals depends on the size of the ring chromosome, amount of genetic material lost in breakage, the stability of the ring chromosome, and the presence of secondary chromosomal aberrations including the varying degrees of mosaicism [1]. Subtelomeric or telomere-to-telomere fusion of the chromosomes resulting in formation of complete rings was also reported, usually with milder phenotypic changes due to the minimal loss of genetic material [3–5]. Advances in the cytogenetic techniques, such as high resolution molecular karyotyping, have allowed the detection of novel mechanisms of ring formation, for example, in patients with inverted duplication and terminal deletion, where ring formation was observed as an escape mechanism [6]. Ring chromosomes account for a very low percentage of structural chromosomal abnormalities [7, 8] and majority of the cases are sporadic arising de novo [9]. Ring formation is reported in all human chromosomes with nearly 50% of rings arising from acrocentric chromosomes. Among the nonacrocentric human autosomes, ring chromosome 4 was observed to be a relatively commoner occurrence [8], but only about 20 cases have so far been reported in detail. The first report of ring chromosome 4 was in 1969, in a newborn baby with growth retardation and multiple congenital abnormalities affecting many systems resulting in early neonatal death [10]. The most recent review of sixteen cases with ring chromosome 4, in 2006, highlighted low birth weight, growth retardation with retarded bone age, microcephaly, and mental retardation as the main clinical features observed in majority of cases. Cleft lip and cleft palate, abnormal facial features, and skeletal abnormalities of the hands and feet were also observed commonly while involvement of one or more of the cardiovascular, gastrointestinal, and genitourinary systems was observed in some cases [11]. It is suggested that the phenotype observed in ring chromosome 4 is a combination of clinical features due to terminal deletions of the chromosome and unspecified developmental abnormalities due to chromosomal instability in ring formation [12]. We report a baby girl who was referred for genetic evaluation due to intrauterine growth retardation and multiple congenital abnormalities and was found to have a de novo 46,XX,r(4)(p15.3q35) karyotype. Herein, her clinical findings are compared with those of the previously reported cases of ring chromosome 4. 2. Case Description Clinical information and peripheral blood samples were collected from the proband and his parents after obtaining their written informed consent. Parental written informed consent was also obtained for publication. The proband was the first child of a nonconsanguineous couple with an unremarkable family history. At the time of conception, the father was 39 years old while the mother was 33 years old. Routine prenatal scans indicated intrauterine growth retardation. The baby was delivered at 35 weeks' gestation. She was resuscitated at birth and Apgar scores were 4, 6, and 6 at 1 minute, 5 minutes, and 10 minutes, respectively. Her birth weight (1.5 kg) and head circumference (25.5 cm) were below the 3rd centile expected for a baby born at 35 weeks of gestation and the crown-to-heel length (48 cm) was above the 50th centile. The baby had microcephaly, right side ptosis, low set ears, unilateral cleft lip and cleft palate, short neck, and bilateral talipes equinovarus. A murmur was elicited during the cardiovascular examination. Examination of other systems showed no abnormality. Ductus arteriosus was found to be patent in echocardiography performed at 3 weeks and 9 weeks after birth. Abdominal ultrasonography revealed renal agenesis in the right side. No abnormalities were detected in the ultrasound scan of the brain. Radiological assessment of the chest and spine was normal. Chromosomal analysis of the proband's peripheral blood using the GTL banding technique at 525-band resolution showed ring chromosome 4 in all 20 spreads analyzed (Figure 1). The karyotype was 46,XX,r(4)(p15.3q35). Chromosomal analysis of both the mother and father was normal. The baby died of respiratory distress resulting from cardiac failure and renal impairment at 10 weeks after birth. Autopsy was not done. 3. Discussion Since the first report in 1969, over 20 cases have so far been reported describing the phenotypic spectrum associated with ring chromosome 4. The clinical signs of the present case in comparison with the phenotypic findings of 17 previously reported cases [3, 4, 10–24] are summarized in Table 1. Almost all the patients reported had both prenatal and postnatal growth retardation and microcephaly. In addition, most of them also had developmental delay and mental retardation. Abnormal facial features, which were commonly observed in these patients, included hypertelorism, epicanthal folds, micrognathia, and abnormalities of the nose and ears. Five of the 16 reported patients had cleft lip and/or cleft palate. Skeletal abnormalities were also a common finding among these patients. These abnormalities commonly involved the thumb, fifth finger, and feet. Abnormalities of feet reported among these patients include overlapping toes, hypoplasia of toes, valgus deformity, and rocker-bottom feet. In addition to these phenotypic features observed in ring chromosome 4, this baby had bilateral talipes equinovarus. Abnormalities of the heart, gastrointestinal system, kidneys, and urinary system were observed in nearly one-third of the reported patients. As reported in 4 patients, these systemic abnormalities tended to occur together [10, 11, 19, 23]. Cardiac abnormalities observed in patients with ring chromosome 4 typically involve cardiac septation and include atrial septal defects, patent foramen ovale, ventricular septal defects, and transposition of great arteries. Patent ductus arteriosus observed in this baby is not reported earlier in association with ring chromosome 4. Unilateral renal agenesis observed in this baby is also reported in one case previously, while renal hypoplasia is observed in 3 other patients. These clinical features observed in this baby are consistent with the consensus phenotype of ring chromosome 4; furthermore bilateral talipes equinovarus and patent ductus arteriosus add to the phenotypic spectrum observed in ring chromosome 4. In the reported cases of ring chromosome 4, chromosomal breakpoints were common at p16 and q35. Telomere-to-telomere fusion was suggested as the mechanism of ring formation in 2 cases, and both these cases did not show any systemic involvement [3, 4]. Mosaic genotype with ring chromosome 4 was also reported in 2 cases. One case with 46X,r(4)/46,XY mosaicism had significant renal involvement [20], while the other one had 45,XX,-4/46,XX,r(4) mosaicism which was detected prenatally and the pregnancy was terminated at 17 weeks' gestation. Abnormalities of the cardiovascular and gastrointestinal systems were identified in the fetus [23]. It is postulated that the clinical features observed in patients with ring chromosome 4 are partly due to the terminal deletion of the chromosome's p and q arms. Patients with terminal deletions of the p arm were reported to have growth failure, developmental delay, congenital cardiac defects, finger and toe anomalies, and speech delay [26]. The genes deleted in this critical region in chromosome 4 in those patients included HAND2 gene, which is expressed in the ventricular chambers of the developing heart, and SORBS2 gene, which is expressed in epithelial tissue and cardiac muscle. These genes may potentially contribute to the cardiac defects in terminal 4q deletion, hence in ring chromosome 4. Terminal deletion of the short (p) arm of chromosome 4 is a well-known clinical entity which is described as Wolf-Hirschhorn syndrome (WHS) (MIM 194190). Terminal 4p16.3 deletion is known to be necessary and sufficient to produce the classical phenotype of WHS [25]. A recent review of reported cases of WHS suggested that the characteristic facies, mental retardation, prenatal and postnatal growth retardation, microcephaly, seizures, and hypotonia were present in nearly all the reported cases irrespective of the size of the deleted chromosomal segment. Congenital heart defects, cleft palate and cleft lip, colobomas, hypospadias, and renal and skeletal abnormalities are the other commonly observed abnormalities in WHS [25]. The breakpoint on the short arm is reported to be located in the region 4p16.1 [23]. This leads to deletion of the distal portion of the short arm that includes the WHS critical region (WHSCR). Genotype-phenotype analysis of WHS has reported that haploinsufficiency of WHSC1 gene causes the characteristic facial dysmorphism and growth delay in WHS. Microcephaly is mapped to an area with its distal boundary at 2.2 Mb from the telomere, whereas the chromosomal localization of cardiac, renal, and genital anomalies is known to be further distal to the telomere [25]. This explains the more severe phenotype with systemic involvement in larger terminal deletion in WHS as well as in ring chromosome 4. The breakpoint in p arm of chromosome 4 is located proximally to MSX1 gene which is known to be associated with cleft lip and cleft palate [27]. Phenotypic features observed in the present case are comparable to the phenotype of the previously reported cases with r(4)(p16q35) karyotype and some of the phenotypic features observed in 4q terminal deletion and WHS. This suggests that the phenotypic features of ring chromosome 4 are the cumulative effect of the deletion of a number of genes located in the terminal 4p and 4q regions. Chromosomal instability in ring formation is also likely to have an additional influence on the phenotype in ring chromosome 4. In the literature cited in this paper, 5 of the 17 reviewed reports on ring chromosome 4 have presented their case as WHS [11, 12, 15, 16, 24]. Table 2 shows the clinical features of WHS which were found in common in the present case and in previously reported cases of ring chromosome 4. Although dysmorphic facial features were observed in majority of the cases, the characteristic “Greek warrior helmet” profile with prominent glabella was observed in only two cases [11, 23]. Even though seizures and hypotonia are described as customary features of WHS, seizures were reported in only two cases [11, 13] and hypotonia was reported in another two cases with ring chromosome 4 [15, 16]. These findings suggest that the phenotypic spectrum of patients with ring chromosome 4 does not always conform to the consensus phenotype of WHS. In conclusion, the phenotypic features observed in this baby add to the spectrum of clinical features observed in ring chromosome 4. Conventional karyotyping was used for cytogenetic diagnosis of the present case; however, the exact chromosomal breakpoints can only be confirmed by the use of molecular cytogenetic methods such as fluorescence in situ hybridization (FISH) and microarray, which have not yet been fully established at our centre. Such techniques will allow the precise identification of the deleted chromosomal segments and the genes involved, which will help to improve the understanding of the phenotype-genotype correlation of this relatively rare structural chromosomal abnormality. Competing Interests The authors declare that there is no conflict of interests regarding the publication of this paper. Figure 1 Karyogram of the baby showing ring chromosome 4. Table 1 Karyotype and the clinical features of the present case and previously reported cases with ring chromosome 4.   Present case 1 [10] 2 [13] 3 [14] 4 [3] 5 [15] 6 [16] 7 [17] 8 [18] Karyotype 46,XX,r(4) 46,XY,r(4) 46,XY,r(4) 46,XY,r(4) 46,XY,r(4),(p16q35) 46,XY,r(4),(p15q35) 46,XX,r(4),(p16q35) 46,XY,r(4),(p16q35) 46,XY,r(4),(p16q35) Preterm delivery +               + Low birth weight + + + + + + + + + Growth retardation + + + + + + + + + Developmental delay NA     + +     + + Mental retardation NA NA + + + NA NA   + Microcephaly + + + + +   + + + Hypertelorism −   +     + +     Epicanthal folds −   +     +       Coloboma − +       +       Ptosis +     +           Malformed ears Low set Large Low set     Low set + +   Abnormal nose − Flat, broad         Flat Broad   Cleft lip + (U/L) + (U/L)       + (B/L)       Cleft palate + +       +   +   Micrognathia −   +         + + Abnormal spine −               Mild kyphosis Transverse palmar crease − + +         +   Clinodactyly −   + + + +       Abnormal thumb − B/L hypoplasia   Hypoplasia Long slender       Adducted Feet deformity + B/L TEV Overriding toes     Valgus deformity Rocker-bottom, overriding toes Valgus deformity Overlapping toes Syndactyly, hypoplastic toes Sacral dimple −   +   +         Cardiac abnormalities PDA PFO         VSD     Intestinal anomalies − Incomplete rotation               Renal and urinary tract anomalies Unilateral agenesis Renal hypoplasia               Hypospadias NA + Epispadias +     NA +   Cryptorchidism NA   + +     NA   + Neurological abnormalities − Generalized hypoplasia of brain Seizures     Hypotonia Hypotonia abductors     Early death 10 weeks 4 weeks       2nd week 3 days     9 [12] 10 [19] 11 [4] 12 [20] 13 [21] 14 [22] 15 [23] 16 [11] 17 [24] Karyotype 46,XX,r(4),(p16q35) 46,XX,r(4),(p16q35) 46,XY,r(4) 46,XY,r(4)(p16q35)/46,XY 46,XY,r(4),(p16q35) 46,XX,r(4),(p16.3q35.2) 45,XX,-4/46,XX,r(4) 46,XY,r(4),(p16.3q35) 46,XX,r(4) Preterm delivery   +         Elective termination +   Low birth weight + + + + +   NA + + Growth retardation + + + + + + NA + + Developmental delay + +   + +   NA +   Mental retardation + +   +     NA +   Microcephaly + + + + + +   + + Hypertelorism         +   + +   Epicanthal folds   +   + + +       Coloboma               +   Ptosis               +   Malformed ears Large +   +       Large, flat Posteriorly rotated Abnormal nose   Depressed bridge   Beaked nose Short, bulbous tip   High bridge     Cleft lip             +(B/L) +   Cleft palate             + +   Micrognathia   +   + +       + Abnormal spine       Mild kyphoscoliosis           Transverse palmar crease           +       Clinodactyly     + + +         Abnormal thumb         Proximally placed     B/L hypoplasia   Feet deformity                   Sacral dimple   +               Cardiac abnormalities ASD VSD         Dextrocardia/ TGA IVS aneurysmal dilation   Intestinal anomalies   Duodenal atresia         Gallbladder hypoplasia Midgut malrotation   Renal and urinary tract anomalies   VUR   Oligomeganephronia Hypoplastic ectopic kidney     Hypoplasia Unilateral agenesis Hypospadias NA NA       NA NA + NA Cryptorchidism NA NA   +   NA NA + NA Neurological abnormalities               Seizures Cerebral atrophy   Early death             NA     NA: not applicable, U/L: unilateral, B/L: bilateral, PDA: patent ductus arteriosus, ASD: atrial septal defect, VSD: ventricular septal defect, TGA: transposition of great arteries, and IVS: interventricular septum. Table 2 The comparison of clinical features of Wolf-Hirschhorn syndrome which were found in common in the present case and in previously reported cases of ring chromosome 4. Clinical signs associated with WHS (Zollino et al., 2008 [25]) Number of reported cases of ring chromosome 4 Present case Facial dysmorphism (2 or more abnormal facial features, excluding facial clefts) 11/17 + Mental retardation 8/13 NA Seizures 2/16 − Prenatal growth retardation 15/16 + Postnatal growth retardation 16/16 + Microcephaly 15/16 + Hypotonia 2/16 − Congenital heart defects 6/17 + Cleft lip/cleft palate 5/17 + Ocular colobomas 3/17 − Hypospadias 4/11 NA Renal abnormalities 6/17 + Skeletal abnormalities 11/17 + WHS: Wolf-Hirschhorn syndrome. NA: not applicable. ==== Refs 1 Kosztolányi G. The genetics and clinical characteristics of constitutional ring chromosomes Journal of the Association of Genetic Technologists 2008 35 2 44 48 19443954 2 Sodré C. P. Guilherme R. S. Meloni V. F. A. Ring chromosome instability evaluation in six patients with autosomal rings Genetics and Molecular Research 2010 9 1 134 143 10.4238/vol9-1gmr707 2-s2.0-77649287480 20198569 3 McDermott A. Voyce M. A. Romain D. Ring chromosome 4 Journal of Medical Genetics 1977 14 3 228 232 10.1136/jmg.14.3.228 2-s2.0-0017687106 881718 4 Freyberger G. Wamsler C. Schmid M. Ring chromosome 4 in a child with mild dysmorphic signs Clinical Genetics 1991 39 2 151 155 2-s2.0-0025959476 2015696 5 Vermeesch J. R. Baten E. Fryns J.-P. Devriendt K. Ring syndrome caused by ring chromosome 7 without loss of subtelomeric sequences Clinical Genetics 2002 62 5 415 417 10.1034/j.1399-0004.2002.620511.x 2-s2.0-0344405655 12431259 6 Knijnenburg J. van Haeringen A. Hansson K. B. M. Ring chromosome formation as a novel escape mechanism in patients with inverted duplication and terminal deletion European Journal of Human Genetics 2007 15 5 548 555 10.1038/sj.ejhg.5201807 2-s2.0-34247639066 17342151 7 Nielsen J. Wohlert M. Chromosome abnormalities found among 34910 newborn children: results from a 13-year incidence study in Århus, Denmark Human Genetics 1991 87 1 81 83 10.1007/bf01213097 2-s2.0-0025921769 2037286 8 Kim H.-J. Jung S.-C. Moon H.-R. Kim S.-S. Lee J.-S. Chromosome abnormalities in a referred population for suspected chromosomal aberrations: a report of 4117 cases Journal of Korean Medical Science 1999 14 4 373 376 10.3346/jkms.1999.14.4.373 2-s2.0-0033174755 10485615 9 Kosztolányi G. Méhes K. Hook E. B. Inherited ring chromosomes: an analysis of published cases Human Genetics 1991 87 3 320 324 10.1007/BF00200912 2-s2.0-0025914051 1864607 10 Carter R. Baker E. Hayman D. Congenital malformations associated with a ring 4 chromosome Journal of Medical Genetics 1969 6 2 224 227 10.1136/jmg.6.2.224 2-s2.0-0014531889 5801472 11 Balci S. Engiz Ö. Aktaş D. Ring chromosome 4 and Wolf-Hirschhorn Syndrome (WHS) in a child with multiple anomalies American Journal of Medical Genetics 2006 140 6 628 632 10.1002/ajmg.a.31131 2-s2.0-33644864589 16470698 12 Kosztolányi G. Ring chromosome 4: Wolf syndrome and unspecific developmental anomalies Acta Paediatrica Hungarica 1985 26 2 157 165 2-s2.0-0022253558 4041283 13 Bobrow M. Joness L. F. Clarke G. A complex chromosomal rearrangement with formation of a ring 4 Journal of Medical Genetics 1971 8 2 235 239 10.1136/jmg.8.2.235 2-s2.0-0015082160 5096548 14 Niss R. Passarge E. Derivative chromosomal structures from a ring chromosome 4 Humangenetik 1975 28 1 9 23 10.1007/bf00272478 2-s2.0-0016692780 1150264 15 Pérez-Castillo A. Abrisqueta J. A. Ring chromosome 4 and wolf syndrome Human Genetics 1977 37 1 87 91 10.1007/BF00293777 2-s2.0-0017736311 881198 16 del Mazo J. Abrisqueta J. A. Pérez-Castillo A. Partial deletion of 4p16 band in a ring chromosome and Wolf syndrome Human Genetics 1978 44 1 105 108 10.1007/bf00283580 2-s2.0-0018170884 711237 17 Finley W. H. Finley S. C. Chonmaitree T. Koors J. E. Chandler W. C. Ring 4 chromosome with terminal p and q deletions The American Journal of Diseases of Children 1981 135 8 729 731 2-s2.0-0019495648 7270516 18 Gutkowska A. Krajewska-Walasek M. Wisniewski L. Ring chromosome 4: 46,XY, r (4) (p16q35) in a boy Klinische Padiatrie 1985 197 4 294 296 10.1055/s-2008-1033986 2-s2.0-0022414344 4046483 19 Halal F. Vekemans M. Ring chromosome 4 in a child with duodenal atresia American Journal of Medical Genetics 1990 37 1 79 82 10.1002/ajmg.1320370118 2-s2.0-0025074747 2240048 20 Anderson C. E. Wallerstein R. Zamerowski S. T. Ring chromosome 4 mosaicism coincidence of oligomeganephronia and signs of Seckel syndrome American Journal of Medical Genetics 1997 72 3 281 285 10.1002/(sici)1096-8628(19971031)72:360;281::aid-ajmg562;3.0.co;2-u 2-s2.0-0030768827 9332654 21 Calabrese G. Giannotti A. Mingarelli R. Di Gilio M. C. Piemontese M. R. Palka G. Two newborns with chromosome 4 imbalances: Deletion 4q33 → q35 and ring r(4)(pterq35.2-qter) Clinical Genetics 1997 51 4 264 267 2-s2.0-0030984691 9184250 22 Sigurdardottir S. Goodman B. K. Rutberg J. Thomas G. H. Jabs E. W. Geraghty M. T. Clinical, cytogenetic, and fluorescence in situ hybridization findings in two cases of 'complete ring' syndrome American Journal of Medical Genetics 1999 87 5 384 390 2-s2.0-0033455622 10594875 23 Kocks A. Endele S. Heller R. Partial deletion of 4p and 4q in a fetus with ring chromosome 4: phenotype and molecular mapping of the breakpoints Journal of Medical Genetics 2002 39 5 1 4 10.1136/jmg.39.5.e23 2-s2.0-0036580748 11826016 24 Concolino D. Rossi E. Strisciuglio P. Deletion of a 760 kb region at 4p16 determines the prenatal and postnatal growth retardation characteristic of Wolf-Hirschhorn syndrome Journal of Medical Genetics 2007 44 10 647 650 10.1136/jmg.2007.050963 2-s2.0-35348891957 17911656 25 Zollino M. Murdolo M. Marangi G. On the nosology and pathogenesis of Wolf–Hirschhorn syndrome: genotype–phenotype correlation analysis of 80 patients and literature review American Journal of Medical Genetics Part C: Seminars in Medical Genetics 2008 148 4 257 269 10.1002/ajmg.c.30190 2-s2.0-55949114508 26 Strehle E.-M. Yu L. Rosenfeld J. A. Genotype-phenotype analysis of 4q deletion syndrome: proposal of a critical region American Journal of Medical Genetics Part A 2012 158 9 2139 2151 10.1002/ajmg.a.35502 2-s2.0-84865541166 22847869 27 Dixon M. J. Marazita M. L. Beaty T. H. Murray J. C. Cleft lip and palate: understanding genetic and environmental influences Nature Reviews Genetics 2011 12 3 167 178 10.1038/nrg2933 2-s2.0-79951800135

PMC005xxxxxx/PMC5004005.txt

==== Front Evid Based Complement Alternat MedEvid Based Complement Alternat MedECAMEvidence-based Complementary and Alternative Medicine : eCAM1741-427X1741-4288Hindawi Publishing Corporation 10.1155/2016/8656740Research ArticleThe Difference of Chemical Components and Biological Activities of the Crude Products and the Salt-Processed Product from Semen Cuscutae Yang Song 1 Xu Hefang 1 Zhao Baosheng 2 Li Shasha 1 Li Tingting 1 Xu Xinfang 1 Zhang Tianjiao 2 Lin Ruichao 1 3 http://orcid.org/0000-0002-8864-0621Li Jian 2 * http://orcid.org/0000-0002-1730-5455Li Xiangri 1 3 * 1School of Chinese Materia Medica, Beijing University of Chinese Medicine, No. 6 Wangjing Zhonghuan Nan Road, Beijing 100102, China2School of Basic Medical Sciences, Beijing University of Chinese Medicine, No. 11 North Third Ring Road, Beijing 100029, China3Beijing Key Laboratory of Chinese Materia Medica Quality Evaluation, Beijing University of Chinese Medicine, No. 11 North Third Ring Road, Beijing 100029, China*Jian Li: lijiancn922@126.com and *Xiangri Li: lixiangri@sina.comAcademic Editor: Cheorl-Ho Kim 2016 16 8 2016 2016 865674028 3 2016 7 6 2016 30 6 2016 Copyright © 2016 Song Yang et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Semen Cuscutae is a well-known Chinese medicine which has been used to nourish kidney in China for thousands of years. The crude product of semen Cuscutae (CP) and its salt-processed product (SPP) are separately used in clinic for their different effects. The study was designed to investigate the influence of processing from semen Cuscutae on chemical components and biological effects. The principal component analysis and quantitative analysis were used to study the differences of the chemical components. The effects of nourishing kidney were detected to compare the differences between the CP and SPP. The PCA results showed that the obvious separation was achieved in the CP and SPP samples. The results of quantitative analysis showed that quercetin and total flavonoids had significantly increased after salt processing while hyperoside had decreased. The comparison of CP and SPP on biological activities showed that both of them could ameliorate the kidney-yang deficiency syndrome by restoring the level of sex hormone, improving the immune function and antioxidant effect. However, SPP was better in increasing the level of T and the viscera weight of testicle and epididymis, improving the antioxidant effect. The results suggested that salt processing changed its chemical profile, which in turn enhanced its biological activities. National Science Foundation of China81274081 ==== Body 1. Introduction Semen cuscutae, the dry matured seed of Cuscuta chinensis Lam. or Cuscuta australis R. Br., is an important Chinese medicine first recorded in the “Shen Nong's Herbal” as an upper grade drug. It has been used to nourish the liver and kidney, treat impotence and seminal emission, prevent miscarriage, and improve eyesight in China for thousands of years. The main constituents of semen cuscutae have been shown as various flavonoids compounds, a range of polysaccharides, a number of different alkaloids, and various other chemicals [1–4]. The flavonoids and polysaccharides are the main biologically active constituents in semen cuscutae. Modern pharmacological experiments have indicated that semen cuscutae could reverse the reduction in testosterone level and the expression of androgen receptor gene, possess immunomodulatory activities, hepatoprotective effects, antioxidation effect, anti-inflammatory action, and antiaging effects, and enhance memory by inducing PC12 cell differentiation [5–8]. In traditional Chinese medicine, the processing of traditional Chinese herbs is a common practice and usually occurs before prescription [9]. Medicinal plants sometimes require specific processing steps such as cleaning, water processing (grinding in water, steaming, and roasting), and fire processing (stir-heating with wine, vinegar, salt, or honey) [10, 11]. The main purposes of processing are to reduce toxicity and to enhance the effects of crude drugs. The chemical components of crude drugs and processed products are different: new components may be formed or the relative contents of certain components may change; other components may disappear or their contents may decrease [12]. According to the theory of traditional Chinese medicine (TCM), herbs processed with salt manifest their effects on kidney meridian [13]. Processing semen cuscutae has a long history, and salt-processed product (SPP) which is processed by stir-heating with salt solution is documented in the 2015 edition of Chinese pharmacopoeia. SPP is first documented in “Comprehensive Recording of Sage-Like Benefit” (Sheng Ji Zong Lu) in the North Song Dynasty of China and then the crude products of semen cuscutae (CP) and SPP are separately used clinically for their different effects. The CP and SPP were shown in Figure 1. SPP is better in warming and tonifying kidney-yang which was documented in “Combinations of Materia Medica” in the Qing Dynasty of China [14]. However, up to now, the differences of chemical components between CP and SPP have not been studied. Modern pharmacological researches have indicated that the semen cuscutae could tonify the kidney to secure essence and is used to treat the diseases of deficiency in the kidney such as deficiency of kidney-yang [15, 16]. However, there were no comparative studies on the biological activities between CP and SPP so far. Recently, to facilitate the experimental research, the kidney-yang deficiency animal model has been duplicated by injecting rats with a high dose of hydrocortisone, in which rats will show symptoms greatly resembling those described in TCM kidney-yang deficiency [17]. Rats with kidney-yang deficiency always have some symptoms such as raritas clothing hair, weight loss, slowed reaction, aversion cold, weakness, tendency to cluster, and decreased activity. Based on the common kidney-yang deficiency animal model, the effects of nourishing kidney were detected to compare the differences between CP and SPP and further to unveil the scientific essence of TCM processing. 2. Materials and Methods 2.1. Materials and Chemicals Hyperoside, quercetin, astragalin, kaempferol, and isorhamnetin were purchased from National Institutes for Food and Drug Control. The purities of all the standards were no less than 98%. Methanol (HPLC grade) was purchased from Thermo Fisher Scientific Inc. Deionized water was prepared by a MilliQ50 SP Reagent Water System (Bedford, MA, USA) for preparing samples and mobile solution. Other reagents were of analytical grade. SOD and MDA kits were purchased from Nanjing Jiancheng Bioengineering Institute. CD3-FITC fluorescent antibody, CD4-APC fluorescent antibody, and CD8a-PE fluorescent antibody were purchased from BD Company (USA). 2.2. Samples Collection All the crude products of semen cuscutae (CP, 6 samples) were collected by Beijing University of Chinese Medicine. The samples of the crude products were collected from Heilongjiang and Neimeng provinces, respectively, which were identified as Cuscuta australis R. Br. by Yang Yaojun, the professor of Pharmacognosy Department in Beijing University of Chinese Medicine. Voucher specimens were deposited at the School of Chinese Materia, Beijing University of Chinese Medicine. SPP samples were prepared in the lab, which means that the CP was mixed with salt solution and then stir-heated at 80–100°C in a metallic pan and dried in the air. 2.3. Principal Component Analysis (PCA) To compare the differences between CP and SPP, unsupervised principal component analysis was performed based on the relative peak areas in the HPLC fingerprints chromatography using software of Umetrics EZinfo. The main chemical markers which have the most influence on the classification among different samples were found out with the help of PCA loading Bi plots. 2.4. Sample Preparation 2.4.1. Extract Preparation for Animals The CP and SPP were selected from the samples we collected and prepared in our lab in Section 2.2. The CP was accurately weighed as 1.0 kg and soaked 8 times in 60% ethanol for one night. And then, it was extracted under reflux twice for 1 h each time. The filtrate was combined and ethanol was recovered. The total crude flavonoids extract was dried in vacuum at 60°C. The crude extract was purified by macroporous resin. Then, the flavonoids extract of CP was obtained. The flavonoids extract of SPP was obtained following the same procedure above. The flavonoids extracts of CP and SPP were mixed suspension in water, respectively, when the rats were treated orally. 2.4.2. Sample Preparation for HPLC The flavonoids extracts in Section 2.4.1 were accurately weighed as 0.15 g and extracted with 50 mL 80% methanol under reflux for 2 h. After cooling, the loss of weight was replenished with 80% methanol. All solvents and samples were filtered through 0.45 μm membrane before analysis. The contents of 2 flavonoids in CP and SPP were determined using HPLC. 2.4.3. Sample Preparation for Determining the Total Flavonoids The flavonoids extracts in Section 2.4.1 were accurately weighed as 0.05 g and extracted with 40 mL ethanol under reflux twice for 1 h each time. The filtrate was combined in 100 mL volumetric flask. 2.5. Chromatographic Condition of HPLC Fingerprints and Determining the 2 Flavonoids The chromatographic separation was performed in a Waters LC system (Waters Technologies, USA), equipped with a 1525 binary pump, a column compartment, and a 2489 double wavelength UV detector. The samples were separated on an Agilent Zorbax SB-C18 (250 mm × 4.6 mm, 5 μm) with a mobile phase that consisted of methanol (A) and 0.4% phosphoric acid solution (B) at a flow rate of 1 mL/min. The gradient elution employed was 25%–40% A at 0–60 minutes and then 40%–60% A at 60–80 minutes. The temperature was maintained at an obligatory level of 40°C. The wavelength of the detector was kept at 365 nm. The sample volume injected was 15 μL. The major constituents in the multiple extracts and fractions were identified by comparing their retention time with the flavonoid standards. The chromatographic condition which was described above had been established by our team [18]. 2.6. Determination of Contents of Total Flavonoids The condition had also been established by our team [19]. The total flavonoids contents of the CP and SPP were determined by the NaNO2-Al(NO3)3-NaOH method. 2.7. Animal Experiments 2.7.1. Animals and Housing SD male rats (purchased from Vital River Laboratories Co., Ltd.) weighing 200 ± 20 g (age: 6 weeks old) were separated into different groups by randomized procedure and acclimatized for 1 week prior to treatment. The rats were maintained under standard laboratory conditions (temperature of 21–23°C, relative humidity of 45–65%, and 12 h/12 h light/dark cycle) with food and water freely available. All animal experiments were performed according to the ethical guidelines suggested by the Institutional Animal Ethics Committee and Committee for the Purpose of Control and Supervision of Experiments on Animals, Ministry of Health, and Government of China. 2.7.2. Treatment of Animals The rats were partitioned into 4 groups (n = 10 in each group); they were given an intramuscular injection of 20 mg/kg hydrocortisone sodium succinate (purchased from Tianjin Biochem Pharmaceutical Co., Ltd., Tianjin, China) for 14 days except for group 1 (normal group, N) which were injected with an equal volume of physiological saline. After this treatment, the kidney-yang deficiency model was made. On the 15th day, 4 groups were treated as follows: group 3 (CP group, CP) were treated orally at dose of 0.14 g/kg flavonoids extract of CP, group 4 (SPP group, SPP) were treated orally with 0.15 g/kg flavonoids extract of SPP, and group 1 and group 2 (model group, M) were treated orally with equal volume distilled water. All rats were treated by gastric perfusion. After 4 weeks' treatment, the rats were denied food for 12 h before blood collection. On the next day, all rats were anesthetized and sacrificed. Blood samples were first collected from eye angular vein to EP tubes of EDTA anticoagulant and then CD4+ (%), CD8+ (%), and CD4+/CD8+ were determined by FACS2Calibur FCM (BD Company, USA). The blood samples from abdominal aorta had been centrifuged (1500 rpm, 15 min) to obtain the serum. The serum samples were stored at −80°C until the level of sex hormones, IgG and IgM, was determined. One kidney and one testicle were rapidly removed and weighed as well as epididymis, prostate gland, and seminal vesicle. The other testicle was frozen in liquid nitrogen for the determination of SOD and MDA. 2.7.3. Weight Analysis During the testing, the rats were weighed once a week for adjusting the dosage and weighed before sacrificing. 2.8. Hormone, Immunization, and Antioxidant Effect Analysis Before the rats were executed, their serum was collected. Total serum testosterone (T), estradiol (E2), IgG, and IgM level was determined in the Beijing North Biotechnology Research Institute by radioimmunity and colorimetric method. CD4+ (%), CD8+ (%), and CD4+/CD8+ were determined by FACS2Calibur FCM (BD Company, USA) in Scientific Research Center of BUCM. The frozen testicles were thawed and weighed. Then, they were mixed with cold physiological saline. The ratio of testicle and physiological saline is 1 : 9 (W/W). The testicle homogenate which was obtained by tissue homogenate in the ice bath was centrifugated to obtain the supernatant. The contents of SOD and MDA of testicle were determined by SOD and MDA kits, following the instructions. 2.9. Statistical Analysis All data was expressed as mean ± standard deviations and analyzed with one-way analysis of variance (ANOVA). Scheffe's test was used to calculate statistical significance by SPSS software 17.0. P < 0.05 was considered statistically significant. 3. Results 3.1. The Analysis of Chemical Components Change during Processing with Salt Solution from PCA According to our early work, there were no new components after processing with salt solution but the contents change occurred during the processing, and 10 components were identified [20]. In this paper, 10 chromatographic peaks were selected as characteristic peaks, the relative peak areas (RPA) of which were calculated for quantitative expression of the HPLC fingerprints. The HPLC chromatogram was shown in Figure 2. PCA analysis on the RPA of 10 components was obtained for discrimination of different samples. For the UV data set by the first two principal components, the plot of the scores (Figure 3(a)) indicated that the samples were classified into two clusters. In the scores plot obtained by PCA, CP and SPP were farther from each other. It is believed that the contents of the chemical constituents in CP and SPP are different. To find the potential chemical markers for the discrimination between CP and SPP, the extended statistical analysis was performed to generate the loading Bi plot (Figure 3(b)). Peaks 3, 6, 7, 9, 10, and 1 are the most important components to distinguish CP and SPP, which will reduce during processing. Moreover, peaks 2 and 8 are also the most important components for the differences between CP and SPP, which will increase during processing. The relative contents of peak 5 will not vary much during processing. As shown in Figure 2, peak 8 was quercetin and peak 3 was hyperoside. 3.2. The Contents of Quercetin and Total Flavonoids Had Increased after Salt Processing Next, the corresponding “loading Bi plot” analysis was used to visualize which components have changed a lot. As shown in Figure 3(b), the result showed that 8 components (2 and 8 increased and 3, 6, 7, 9, 10, and 1 decreased) had a major impact on the sample clustering which had changed significantly. Among them, quercetin and quercetin glucosides (quercetin and quercetin-3-O-β-D-gal(2-1)β-D-api) had increased the most while hyperoside decreased. So, the contents of quercetin and hyperoside were determined by HPLC. The total flavonoids in CP and SPP were determined by NaNO2-Al(NO3)3-NaOH method. As shown in Table 1, quercetin and total flavonoids in SPP had increased significantly compared with CP. Hyperoside in SPP had decreased significantly. 3.3. The Kidney-Yang Deficiency Model Was Successfully Made After 14 days' intramuscular injection, the rats showed raritas clothing hair, weight loss, slowed reaction, aversion cold, weakness, tendency to cluster, and decreased activity as in kidney-yang deficiency. Compared with normal group, the T and E2 level in the serum of the model group was lower. From what has been discussed above, the kidney-yang deficiency model was successfully made. On the other hand, the level of T and E2 in other treated groups had increased as shown in Figure 4, and the SPP group was better than CP group in the level of T. 3.4. The Average Viscera Weight and Index of CP and SPP Group During making the model of kidney-yang deficiency, some of the rats were dead. We weighed all rats and their viscera and then calculated the average viscera index. Compared with the normal group, the viscera weights of kidney, epididymis, seminal vesicle, and prostate gland were decreased in model group. The SPP group had increased weight of kidney, testicle, epididymis, and seminal vesicle. The CP group had increased weight of kidney, epididymis, seminal vesicle, and prostate gland. The SPP group was better in testicle and epididymis than CP group. The results were shown in Table 2. Compared with the normal group, the viscera indexes of testicle, epididymis, seminal vesicle, and prostate gland were decreased in model group. The SPP group had the most increase in testicle and epididymis indexes. The CP group had the greatest increase in seminal vesicle index. The SPP group was better in testicle and epididymis indexes than CP group. The results were shown in Table 3. 3.5. The Influences of CP and SPP on Immune System in Kidney-Yang Deficiency Rats T lymphocytes are active cells of immune system in the body; their activation, differentiation, and proliferation play an important role in the process of immune response. Balanced state of Th1/Th2 is the precondition of immune stable internal environment. As shown in Figure 5(a), compared with normal group, the T lymphocyte subsets were in the condition of inhibiting the expression and CD8+ (%) was increased while CD4+/CD8+ decreased significantly in model group. All treated groups had improved this condition. CP and SPP can regulate T lymphocyte subgroup level and improve the immune function. Immunoglobulin is an important immune molecule of the body, and the contents of IgG and IgM respond to the immune ability to some extent. As shown in Figure 5(b), compared with the normal group, the contents of IgG and IgM were increased in model group; the CP and SPP groups had decreased level of IgG and IgM. 3.6. SPP and CP Groups Both Showed Antioxidant Effect Malondialdehyde (MDA) is the product of lipid peroxidation which is the indicator of reflecting the degree of oxidant damage. Superoxide dismutase (SOD) is an important antioxidant enzyme. The contents of MDA and SOD respond to the extent of oxidant and antioxidant ability. As shown in Figure 6, SPP and CP both had antioxidant effect. 4. Discussion Prior to their usage in clinics, crude drugs are subjected to traditional Chinese processing techniques. SPP as one of the processing products of CP is better in terms of nourishing kidney which was documented in the 2015 edition of Chinese pharmacopoeia. In our study, the PCA results indicated that the chemical profile of CP changed after salt processing. What is more, 8 components had a major impact on the sample clustering which had changed significantly. Among them, quercetin and total flavonoids in SPP had increased most while hyperoside decreased. The findings in this study demonstrated for the first time that salt processing could change chemical constituents of crude products. Hydrolysis reaction might happen in processing, which led to the change of chemical constituents. The flavonoids in semen cuscutae could reverse the reduction in testosterone level and possess immunomodulatory activities, antioxidant effect, and anti-inflammatory action [5, 21, 22]. The quercetin, as one of the flavonoids, has antioxidation and anti-inflammatory effects [23, 24]. So, the comparison of pharmacological effects in testosterone level, immunomodulatory activities, antioxidation effect, and anti-inflammatory effect of CP and SPP was studied. In the model of kidney-yang deficiency, the endocrine was disrupted by hydrocortisone, and the level of sex hormone was changed in the blood. Hydrocortisone is also a kind of immunosuppressant and long-term injection can cause the body's immune function disorder. In our study, the sex hormone analysis results showed that both CP and SPP groups had increased level of T and E2 effectively, and SPP is better than CP. The results of the viscera indexes showed that SPP is better than CP in increasing the weights and indexes of testicle and epididymis. In the aspect of the immune system, CP and SPP both could improve the immune function through regulating T lymphocyte subgroup level and decreasing the level of IgG and IgM. In addition, semen cuscutae has a significant antioxidant effect, especially SPP. From what we discussed above, CP and SPP both could improve the kidney-yang deficiency syndrome; however, SPP is better than CP in increasing the level of T and the weights and indexes of testicle and epididymis. The results of the pharmacological effects study indicated for the first time that salt processing changed the amount of flavonoids, which in turn increased the sex hormone level, improved immune function, and enhanced antioxidant effect. 5. Conclusion The study was to discover the change of the flavonoids and the pharmacological effect in CP and SPP on the kidney-yang deficiency rat, especially on hormone level and antioxidant effect. It is important to note that this study has demonstrated that processing of traditional Chinese herbs is able to alter their chemical constituents and affect their bioactivity profile. It is also supported that crude products and processed products were prescribed differently in clinic. Acknowledgments This work was supported in part by grants from the National Science Foundation of China (Grant no. 81274081). Competing Interests The authors declare that they have no competing interests. Authors' Contributions Song Yang conceptualized the study. Song Yang and Hefang Xu reviewed the research proposal. Song Yang conducted the samples collection and preparation and data analysis. Song Yang, Xiangri Li, and Jian Li drafted the paper. All the authors participated in writing and giving feedback on the paper. All authors have read and approved the final paper. Figure 1 The crude product of semen cuscutae (CP) and the salt-processed product (SPP). Figure 2 HPLC chromatogram (3: hyperoside, 6: astragalin, 8: quercetin, 9: kaempferol, and 10: isorhamnetin). Figure 3 PCA score plot (a) and loading Bi plot (b) of CP (blue box) and SPP (red dot). CP and SPP were classified into two clusters. Peaks 3, 6, 7, 9, 10, and 1 are the most important components to distinguish CP and SPP, which will reduce during processing; peaks 2 and 8 are also the most important components for the differences between CP and SPP, which will increase during processing. Figure 4 (a) and (b) were the level of T and E2. Compared with M group, the levels of T and E2 in CP and SPP groups both had increased; however, SPP group was better than CP group. Significant differences with M group were designated as ∗ P < 0.05. Significant differences with N group were designated as # P < 0.05. Figure 5 The results of immune activity in each group of rats. (a) T cells subtype detection by FCM ((A) CD4+, (B) CD8+, and (C) CD4+/CD8+). (b) The contents of IgM and IgG in serum. Compared with M group, the percentage of CD8+ had decreased while CD4+/CD8+ increased in CP and SPP groups. The contents of IgM and IgG also decreased. Significant differences with M group were designated as ∗ P < 0.05. Significant differences with N group were designated as # P < 0.05. Figure 6 (a) and (b) were the contents of MDA and SOD. Compared with M group, the antioxidant effect in CP and SPP groups had been enhanced. Significant differences with M group were designated as ∗ P < 0.05. Significant differences with N group were designated as # P < 0.05. Table 1 The contents of total flavonoids, hyperoside, and quercetin in CP and SPP (mg/g) (x¯±s).   Total flavonoids Hyperoside Quercetin CP 19.84 ± 0.009 2.84 ± 0.021 0.09 ± 0.001 SPP 20.22 ± 0.005∗ 2.65 ± 0.007∗ 0.16 ± 0.001∗ Note: significant differences with CP were designated as ∗ P < 0.05. Table 2 The viscera weight (g) (x¯±s).   N M CP SPP Kidney 1.1941 ± 0.0500∗ 1.0494 ± 0.0377# 1.3440 ± 0.0516∗ 1.3030 ± 0.0824∗ Testicle 1.5360 ± 0.0655 1.4441 ± 0.0396 1.1320 ± 0.0346 1.8201 ± 0.0260∗ Epididymis 0.4325 ± 0.0307∗ 0.3533 ± 0.0177# 0.5409 ± 0.3200∗ 0.5534 ± 0.0174∗ Seminal vesicle 0.7724 ± 0.0420∗ 0.6434 ± 0.0719# 1.9516 ± 0.1142∗ 1.5731 ± 0.0777∗ Prostate gland 0.5919 ± 0.0258∗ 0.4022 ± 0.0599# 0.6241 ± 0.0787∗ 0.4934 ± 0.0443 Note: significant differences with M group were designated as ∗ P < 0.05. Significant differences with N group were designated as # P < 0.05. Table 3 The average viscera index (x¯±s).   N M CP SPP Kidney 0.3852 ± 0.0303 0.3656 ± 0.0310 0.3277 ± 0.0214∗ 0.3777 ± 0.0424 Testicle 0.4978 ± 0.0396∗ 0.4139 ± 0.0211# 0.4594 ± 0.0246∗ 0.4981 ± 0.0363∗ Epididymis 0.1413 ± 0.0155∗ 0.1261 ± 0.0119# 0.1317 ± 0.0213 0.1557 ± 0.0208∗ Seminal vesicle 0.4580 ± 0.0268∗ 0.4098 ± 0.0114# 0.4735 ± 0.0597∗ 0.4516 ± 0.0416∗ Prostate gland 0.1923 ± 0.0304∗ 0.1231 ± 0.0361# 0.1514 ± 0.0119∗ 0.1330 ± 0.0341 Note: significant differences with M group were designated as ∗ P < 0.05. Significant differences with N group were designated as # P < 0.05. ==== Refs 1 Ye M. Yan Y.-N. Qiao L. Ni X.-M. Studies on chemical constituents of Cuscuta chinensis China Journal of Chinese Materia Medica 2002 27 2 115 117 2-s2.0-24344453289 12774382 2 Du X.-M. Kohinata K. Kawasaki T. Guo Y.-T. Miyahara K. 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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/7830768Research ArticleMicrotubule Polymerization Functions in Hypersensitive Response and Accumulation of H2O2 in Wheat Induced by the Stripe Rust http://orcid.org/0000-0002-9905-5065Wang Juan http://orcid.org/0000-0001-9614-580XWang Yang Liu Xinjie Xu Yuanliu http://orcid.org/0000-0003-0739-2281Ma Qing * State Key Laboratory of Crop Stress Biology for Arid Areas, Northwest A&F University, Yangling 712100, China*Qing Ma: maqing@nwafu.edu.cnAcademic Editor: Xiao-Lin Chen 2016 16 8 2016 2016 783076825 4 2016 20 7 2016 Copyright © 2016 Juan Wang et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The plant cytoskeleton, including microtubules and microfilaments, is one of the important factors in determining the polarity of cell division and growth, as well as the interaction of plants with invading pathogens. In defense responses of wheat against the stripe rust (Puccinia striiformis f. sp. tritici) infection, hypersensitive response is the most crucial event to prevent the spread of pathogens. In order to reveal the effect of microtubules on the hypersensitive cell death and H2O2 accumulation in the interaction of wheat (Triticum aestivum) cv. Suwon 11 with an incompatible race, CYR23, wheat leaves were treated with microtubule inhibitor, oryzalin, before inoculation. The results showed that the frequency of infection sites with hypersensitive response occurrence was significantly reduced, and hypersensitive cell death in wheat leaves was suppressed compared to the control. In addition, the frequency and the incidence of infected cells with H2O2 accumulation were also reduced after the treatment with oryzalin. Those results indicated that microtubules are related to hypersensitive response and H2O2 accumulation in wheat induced by the stripe rust, and depolymerization of microtubules reduces the resistance of plants to pathogen infection in incompatible interaction, suggesting that microtubules play a potential role in the expression of resistance of wheat against the stripe rust fungus. National Natural Science Foundation of China3127202431571960111 Project from the Ministry of Education of ChinaB07049 ==== Body 1. Introduction In general, plants are subjected to the attack of a vast number of potential pathogens during their lifetime. As a result, they have evolved intricate defense mechanisms including hypersensitive response (HR) and the accumulation of reactive oxygen species (ROS) [1] to recognize and defend the attack of these invading pathogens. The localized hypersensitive cell death, accompanied by the restriction of pathogen growth, is an ubiquitous expression of plant resistance to pathogens [2]. Typically, HR occurs during successful defense in the host plants, usually leaving only small necrotic spots. Meanwhile, ROS plays important roles in defense response during plant-pathogen interactions [3–5]. Generation of ROS, especially hydrogen peroxide (H2O2), has been reported as one of the earliest responses of plant cells to the attack of various pathogens [3, 6, 7]. H2O2 accumulation can inhibit fungal growth [8] and is also involved in the occurrence of HR during the early infection stage [7] as well as regulates a myriad of cellular signaling pathways [9]. Understanding the resistance mechanisms of plants against the invasion of pathogens is critical to develop novel and sustainable disease control approaches. The plant cytoskeleton, including microtubules and microfilaments, is a highly dynamic subcellular structure that is associated with the plant defense response. For example, cytoskeletal elements are responsible for cytoplasmic aggregation, organelle movements, papilla formation, H2O2 production, and HR-cell death beneath the infection site [2, 10–12]. Evidence for a crucial role of the cytoskeleton in plant defense has been provided by using drugs that alter the polymerization-depolymerization dynamics of microtubules (colchicine, taxol, or oryzalin) and microfilaments (cytochalasins, latrunculin, or phalloidin). Effects of cytoskeleton inhibitors on defense response of plants during pathogen infection have been studied in several plant-microbe systems. During the interaction between cowpea and cowpea rust fungus, Uromyces vignae, cytochalasin treatment greatly delayed the generation of HR [12]. In Linum usitatissimum-Melampsora lini system, the inhibition of HR was also observed after treatment with antimicrotubule agent oryzalin [13]. Moreover, when wheat cells were attacked by nonhost pathogen Sphaerotheca fuliginea, oryzalin treatment inhibited the occurrence of HR and allowed S. fuliginea to penetrate and form haustoria in mesophyll cells of the wheat [14]. Interestingly, reorganization of microtubules during defense responses varies in different experimental systems. Microtubules were observed gathering around the infection sites upon fungal infection [12, 13, 15, 16] and even were generally disrupted upon perception of an oomycete infection signal [17, 18]. In contrast, microtubules inhibitors propyzamide and oryzalin did not affect the entry rate of fungi into barley (Hordeum vulgare) leaf epidermal cells [19]. So it is difficult to deduce common roles for microtubules during plant-microbe systems. Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), occurs worldwide and is one of the most destructive diseases of wheat in many cool and temperate regions, especially in China [20]. The attack of the rust fungus triggers HR and H2O2 accumulated in the affected leaf mesophyll cells of the resistant wheat cultivars [21, 22]. It is reasonable to assume that the more we understand the resistance mechanisms of the wheat against the stripe rust, the more likely we are able to find new ways to control the disease. In the present paper, to provide experimental evidence for a role of microtubules, we focus on the effects of oryzalin on hypersensitive cell death and H2O2 accumulation in the interaction between wheat cultivar Suwon 11 and an incompatible race CYR23 of Pst. 2. Materials and Methods 2.1. Plant Cultivars and Pathogen Wheat (Triticum aestivum L.) cultivar Suwon 11 and a Chinese race of Pst, CYR23, were used in this study. Suwon 11 is highly resistant to race CYR23. The seedlings were grown in 10 cm plastic pots in growth chamber with a 16 h : 8 h (light : dark) photoperiod (60 mmol m−2 s−1 photon flux density) at 16°C with 60% relative humidity (RH). Seven-day-old seedlings at the primary leaf stage were inoculated with fresh urediniospores of CYR23 using a fine paintbrush. After inoculation, the seedlings were kept at 100% RH in constant dark for 24 h at 12°C before being cultivated in the growth chamber. Specimens of inoculated wheat leaf tissues were taken at 12, 24, 48, 72, and 96 hours after inoculation (hai). Three independent biological replications were collected at each time point. 2.2. Treatment with Oryzalin Oryzalin (Sigma-Aldrich, St. Louis, MO, USA) was used as inhibitor of microtubules [23]. The chemical was dissolved in dimethylsulfoxide (DMSO) as a 100 mmol stock solution, stored at –20°C, and diluted with distilled water prior to use. For inhibitor treatment, 400 μg mL−1 oryzalin solution was injected into the primary leaves of seven-day-old wheat seedlings by pressure infiltration with a needleless syringe, and 1% DMSO was used as control treatment. We confirmed that 1% DMSO did not affect fungal development or the penetration efficiency of Pst (data not shown). After injection, leaves were inoculated with fresh urediniospores of CYR23. Specimens of inoculated wheat leaf tissues were taken at 12, 24, 48, 72, and 96 hai. 2.3. Detection of Inhibitor Effects on Hypersensitive Response Detection of hypersensitive cell death was carried out using a whole leaf transparent fluorescence staining method [24]. Wheat leaf segments of 3 cm long were clipped from the center of inoculated leaves. Leaf sections were fixed and decolorized in a boiling mixture of lactophenol : ethanol (1 : 2, v/v) for 1.5 min and stored overnight at room temperature (20°C). For Calcofluor staining, the cleared leaf segments were washed twice with 50% ethanol (v/v) for 15 min. The leaves were then rinsed twice with distilled water and soaked in 0.05 M NaOH twice. After washing 3 times with distilled water, the specimens were incubated in Tris-HCl buffer (0.1 M, pH 8.5) for 30 min and then stained with 0.1% (w/v) Calcofluor M2R (Sigma-Aldrich, St. Louis, MO, USA) for 5 min. After washing 4 times (10 min each) with water and once (30 min) with 25% (v/v) aqueous glycerol, cleared leaf segments were mounted on glass slides in microscopy solution and examined with fluorescent microscopy. To investigate the effects of the microtubule depolymerization on the hypersensitive cell death of wheat, the number of penetration sites displaying necrosis was calculated. The formation of substomatal vesicles was defined as a penetration site or infection site. At least 50 penetration sites on each of the four leaf segments were scored for each of the time points. All the specimens were examined under a Nikon 80i fluorescent microscope (Nikon Corporation, Japan). 2.4. Detection of Inhibitor Effects on H2O2 The detection of H2O2 was analyzed histochemically using the 3,3-diaminobenzidine (DAB; Amresco, Solon, OH, USA) staining method [7, 21]. The inoculated primary leaves were cut and the cut ends were immersed in a solution containing 1 mg mL−1 DAB dissolved in HCl-acidified (pH 3.8) distilled water. Leaves were incubated for additional 8 h to allow DAB uptake and react with H2O2. After incubation, inoculated leaves were cut into 1.5 cm long segments and then fixed and decolorized in boiling 95% ethanol for 10 min before being cleared in saturated chloral hydrate. Subsequently, leaf segments were stored in microscopy solution (50% glycerol) and examined under differential interference contrast (DIC) optics with a Nikon 80i microscope (Nikon Corporation, Japan). 3. Results 3.1. Oryzalin Treatment Had No Effect on Infectious Development of Pst Although pharmacological study generally represents a common approach to tackle the role of cytoskeleton in plant-microbe interactions, the anticytoskeletal drugs applied may also damage the microbial cytoskeleton that plays an important role during plant colonization. To determine the effects of oryzalin (400 μg mL−1) on the development of Pst, we compared the infectious development of Pst inoculated on oryzalin treated leaves with that of the control (leaves treated with 1% DMSO). Both on the control (1% DMSO) and on oryzalin treated leaves, urediniospores germinated normally, and germ tubes grew on the leaf surface until they reached stomas, where the tip of the germ tube swelled and entered into stomatal cavity through stomatal aperture. A substomatal vesicle was formed within the cavity and then developed into 1–3 infectious hyphae. Growth of the infection hyphae made them get in touch with the mesophyll cells, which induced the development of a haustorial mother cell. Our results indicated that treatment with 400 μg mL−1 oryzalin solution did not affect the infectious development of Pst on wheat leaves. 3.2. Oryzalin Treatment Increased the Susceptibility of Resistant Wheat Plants to Pst A few uredia were observed on sites with necrosis in leaves pretreated with the microtubule inhibitor oryzalin (infection type 2 or middle resistance) 15 days after inoculation. However, only some necrotic elongated spots without uredia production were found in control wheat leaves (infection type 0 or nearly immune reaction). This indicated that the resistance level of wheat cultivar Suwon 11 to CYR 23 was decreased upon microtubules depolymerization, suggesting that microtubules may play an important role in the incompatible interaction between wheat and Pst. 3.3. Oryzalin Inhibited the Hypersensitive Response in Wheat during Wheat-Pst Interaction In wheat-Pst incompatible interaction, the fungal development was remarkedly restricted in infection sites by hypersensitive response of the mesophyll cells. Microscopically, in the control leaves, the HR induced by haustorial mother cells was obvious in mesophyll cells at 24 hai (Figure 1(a)). However, only a few slight fluorescence stainings could be observed at the infection sites in oryzalin treated leaves, and, occasionally, HR could not be detected although three or more haustorial mother cells were formed at infection sites (Figure 1(b)). Although, both in the control and in the oryzalin treated leaves, the ratios of penetration sites with HR were increased significantly at 48 hai in comparison with 24 hai, the extent of HR in mesophyll cells was much less in the treated leaves than that in the control (Figures 1(c) and 1(d)). With incubation time advancing, the number of penetration sites with necrotic mesophyll cells continued to increase, and almost every infection site was necrotic in the control leaves at 96 hai (Figure 1(e)). However, in oryzalin treated leaves with advancing incubation time, 96 hai, less penetration sites with necrotic mesophyll cells were detected, and the extension of necrosis was also smaller than that of the control (Figure 1(f)). The percentage of penetration sites with mesophyll necrotic cells was significantly lower in the oryzalin treatment than in the control over the whole examination period (Figure 2). There were 36% infection sites that had necrosis in the control, but only about 11% in the oryzalin treated specimens at 24 hai. The percentage of incidence of hypersensitive cell death in the control leaves increased rapidly to 83% at 48 hai, followed by a slight increase at 72 hai, and reached approximately 100% at 96 hai. In contrast, in treatment with oryzalin, the percentage of hypersensitive cell death was only 30% at 48 hai but markedly increased to 74% at 72 hai and finally reached 77% at 96 hai. These results showed that hypersensitive response occurrence induced by Pst infection was reduced by oryzalin treatment, indicating that normal hypersensitive cell death was suppressed after depolymerization of microtubules in wheat mesophyll cells, especially in the early period of pathogen infection. 3.4. Oryzalin Treatment Suppressed H2O2 Accumulation during Wheat-Pst Interaction After Pst hyphae entering through the opening stomata, in the solvent-only control, H2O2 accumulation was first observed both in the mesophyll cells and in the guard cells as indicated by reddish-brown staining due to DAB polymerization at 24 hai (Figure 3(a)). Up to 48 hai, stronger reddish-brown DAB staining was detected and more mesophyll cells with DAB staining appeared (Figure 3(c)). At 96 hai, both mesophyll cells and adjacent cells showed strong DAB staining (Figure 3(e)). On the contrary, in oryzalin treated specimens, DAB staining was restricted mainly in the guard cells at 24 hai (Figure 3(b)), and the DAB staining in guard cells became weaker at 48 hai when haustorial mother cells were formed (Figure 3(d)). Although obvious DAB staining was detected both in mesophyll cells and in guard cells at 96 hai, the stain was much weaker than that of the control at the same time point (Figure 3(f)). During the examined time period, the oryzalin treated specimens had significantly lower percentage of penetration sites with DAB staining in the incompatible interaction between Suwon 11 and CYR23 in comparison with the control, although both of them showed similar trends (Figure 4). In the specimens treated with DMSO only, the percentage of infection sites with DAB staining was 60% at 12 hai, reached the peak of approximately 70% at 24 hai, and then decreased sharply to 20% at 48 hai, followed by an increase to 30% at 72 hai, and kept the same level to 96 hai. In contrast to the control, the numbers in the oryzalin treated specimens at the same experimental time points were 17%, 45%, 5%, and 20% (Figure 4). Those results clearly showed that the microtubules depolymerization drug oryzalin suppressed H2O2 accumulation during wheat-Pst interaction. 4. Discussion In this study we found that the microtubule polymerization inhibitor, oryzalin, caused a reduction in the occurrence of hypersensitive response and accumulation of H2O2 in wheat cultivar Suwon 11 inoculated with the incompatible Pst race CYR23, which increased the susceptibility of wheat to the rust fungus compared to normal. In our previous study, we found that cytochalasin A, an inhibitor of actin polymerization, reduced the incidence of hypersensitive cell death and delayed accumulation of H2O2 in wheat leaves infected with Pst [25]. Meanwhile, our results revealed that the cytoskeleton in mesophyll cells has a potential role in HR generation and H2O2 accumulation and was involved in plant defense responses. Moreover, depolymerizations of microtubules and microfilaments suppressed the defense reactions and promoted the infection of stripe rust fungus in wheat [14, 26], suggesting that intact microtubules and microfilaments networks are necessary for wheat defending invaded the stripe rust fungus. The microtubule inhibitor oryzalin provides an acceptable approach to study the role of microtubules in plant-pathogen interaction. Our results in this study indicated that depolymerization of microtubules inhibited HR of plant cells in response to pathogen attack. Similarly, the delay of HR after treatment with oryzalin was observed in a range of incompatible plant-pathogen interactions, including cowpea-cowpea rust fungus [12] and flax-flax rust fungus [13]. H2O2 generation and accumulation during the early infection stage were often associated with early plant defense responses [7]. H2O2 accumulation was only detected in guard cells before 48 hai in oryzalin treatment specimens instead of 24 hai in the control, which indicated that oryzalin treatment delayed the accumulation of H2O2 in wheat against rust fungus attack. Meanwhile, we also found that the burst of H2O2 was restrained after treatment with oryzalin. The data further confirmed that microtubules are necessary for H2O2 accumulation. In addition, according to the results, oryzalin also inhibited the hypersensitive response in wheat during wheat-Pst interaction. Thus, microtubules may play an essential role in resistance response of wheat against the stripe rust. Moreover, the role of microtubules in HR remains controversial. Oryzalin allowed incompatible oomycete hyphae to spread in the manner of a compatible interaction [27]. However, disruption of microtubules by oryzalin, cell death, and nuclear movements were not affected during the infection of cowpea-cowpea rust fungus [12]. Therefore, we suggest that the role of microtubules in induction of HR varies between different interaction systems. Traditionally, the plant microtubules are essential players for many different cellular events such as growth, division, cell motility, production of the ER body, vesicular sorting, signal transduction, and cell wall deposition [28]. For the cytoskeleton response to pathogen attack, the role of the microtubules has been reported in different plant-microbe interactions. In barley-Erysiphe and flax-Melampsora interactions, radial arrays of microtubules formed beneath the appressoria [15, 16]. Treatment with microtubule inhibitors delayed onset of the hypersensitive response in the flax-Melampsora system [23]. Moreover, microtubules were identified as a central component in the control of protoplast volume during the response to hyperosmotic stress [29] and the membrane fluidity in cold sensing [30]. In addition, microtubules might act as a negative regulator of ion channel activity or as stress-focusing elements that collect and convey membrane perturbations to a channel [31]. Pathogens are able to suppress the host defenses by secreting effector proteins. In turn, plants evolved resistance proteins, which allow recognition of these effectors. This leads to effector-triggered immunity (ETI) and activation of the hypersensitive response (HR) [32]. ETI or HR involves the production of reactive oxygen species (ROS) and the transcriptional activation of genes, encoding antimicrobial pathogenesis-related (PR) proteins. The signaling pathways of ETI are fine-tuned by plant signaling molecules such as salicylic acid (SA), jasmonic acid (JA), and ethylene (ET) [33, 34]. The hormone SA plays a major role in plant resistance to hemi/biotrophic pathogens [34]. Multiple regulator proteins control microtubule dynamics. Different regulators use different mechanisms to regulate microtubule dynamics. MAP65, a microtubule-associated protein conserved in higher eukaryotes, binds to microtubule to stop microtubule depolymerization [35]. In addition, mutants accumulate in Arabidopsis thaliana MAP65-3 increased levels of SA and constitutively express genes encoding PR proteins in the leaves, indicating that AtMAP65-3 exerts a role in negatively regulating plant defense responses [36]. Therefore, the focus of future work in this field should be studying the functions of microtubule-associated proteins in controlling microtubule dynamics that take part in the resistant response of wheat against Pst. Acknowledgments This research was supported by the National Natural Science Foundation of China (Grants nos. 31272024 and 31571960) and the 111 Project from the Ministry of Education of China (B07049). Competing Interests The authors declare that they have no competing interests. Authors' Contributions Juan Wang and Yang Wang contributed equally to this paper. Figure 1 Fluorescence micrographs of hypersensitive cell death localization in incompatible interaction between wheat and Pst (race CYR23) in DMSO-only (control) and oryzalin treatments. (a) In control, haustorial mother cells formed and mesophyll cells showed HR reaction, 24 hai. (b) More than two haustorial mother cells formed treated with oryzalin, 24 hai. (c) Conspicuous HR in mesophyll cells was observed in control, 48 hai. (d) The apex of the infection hypha formed a haustorial mother cell. HR was induced by HMC and the whole cells started to lose original shape treated with oryzalin, 48 hai. (e) In control, many HR cells were visualized in mesophyll cells, 96 hai. (f) Slight HR-like cells appeared in the mesophyll cells treated with oryzalin treatment, 96 hai. GT: germ tube; HMC: haustorial mother cell; HR: hypersensitive response; IH: infection hypha; SP: spore; and SV: substomatal vesicle. Scale bars = 50 μm. Figure 2 Incidence of mesophyll cells of wheat leaves at infection sites exhibiting hypersensitive cell death after inoculation with Pst (race CYR23) in DMSO-only and oryzalin treatments. Bars represent standard deviation. Replicate experiments led to similar results. Figure 3 Micrographs of differential interference contrast (DIC) of H2O2 accumulation in wheat against Pst (race CYR 23) in DMSO-only and oryzalin treatments. (a) Mesophyll cells and guard cells showing DAB staining in control, 24 hai. (b) Positive DAB staining was detected mainly in guard cells treated with oryzalin, 24 hai. (c) Guard cells showing obvious and stronger reddish-brown H2O2 accumulation and mesophyll cells exhibiting the extension of plant cell wall apposition (CWA) in control, 48 hai. (d) Weaker DAB staining detected in guard cells treated with oryzalin, 48 hai. (e) Mesophyll cells and guard cell exhibit intensive H2O2 accumulation in control, 96 hai. (f) Mesophyll cells and guard cell showed slight H2O2 accumulation in oryzalin treatment at 96 hai. GT; germ tube; HMC; haustorial mother cell; SP; spore; and SV; substomatal vesicle. Scale bars = 25 μm. Figure 4 Percentage of mesophyll cells of wheat at interaction sites exhibiting H2O2 accumulation after inoculation with Pst (race CYR23) in DMSO-only and oryzalin treatments. At least 50 infection sites of each of four leaf pieces were scored for each time point. Bars represent standard deviation. Replicate experiments led to similar results. ==== Refs 1 Heath M. C. 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==== Front AIDS Res TreatAIDS Res TreatARTAIDS Research and Treatment2090-12402090-1259Hindawi Publishing Corporation 10.1155/2016/9510172Research ArticleFeasibility and Acceptability of a Smartphone App for Daily Reports of Substance Use and Antiretroviral Therapy Adherence among HIV-Infected Adults http://orcid.org/0000-0001-9283-7307Przybyla Sarahmona M. 1 * http://orcid.org/0000-0001-6311-7597Eliseo-Arras Rebecca K. 2 http://orcid.org/0000-0002-8223-768XKrawiec Gabriela 1 http://orcid.org/0000-0001-5024-2532Gower Emily 1 http://orcid.org/0000-0003-3055-578XDermen Kurt 2 1School of Public Health and Health Professions, Department of Community Health and Health Behavior, State University of New York at Buffalo, 3435 Main Street, Buffalo, NY 14214, USA2Research Institute on Addictions, State University of New York at Buffalo, 1021 Main Street, Buffalo, NY 14203, USA*Sarahmona M. Przybyla: mona@buffalo.eduAcademic Editor: Gita Ramjee 2016 16 8 2016 2016 951017222 3 2016 6 7 2016 14 7 2016 Copyright © 2016 Sarahmona M. Przybyla et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.While substance use is one of the most consistent predictors of poor adherence to antiretroviral therapy (ART), few studies among people living with HIV (PLH) have utilized mobile phone-based assessment of these health behaviors. PLH were recruited from primary care clinics to report ART and substance use using a smartphone application (app) for 14 consecutive days. The app's feasibility as a data collection tool was evaluated quantitatively via surveys and qualitatively via in-depth interviews to assess daily report completion, compliance, and study satisfaction. Overall, 26 participants (M = 49.5 years, 76% male) completed 95.3% of time-based daily reports. Participants reported high satisfaction with the app and expressed future interest in using smartphones to report daily behaviors. High completion rates and participant acceptability suggest that smartphones are a feasible, acceptable method for collecting substance use and ART data among PLH. Potential areas of concern such as sufficient training and assistance for those with limited smartphone experience should be considered for future app-based research studies among PLH. ==== Body 1. Introduction Considering the standard of care for HIV treatment since 1996, combination antiretroviral therapy (ART) has resulted in widespread improvements in virologic outcomes for people living with HIV (PLH) and has yielded significant declines in HIV-related morbidity and mortality [1]. To achieve maximal suppression of viral replication and prevent drug resistance, consistently high adherence to prescribed regimens is critical. The most significant contributor to viral rebound is suboptimal ART adherence [2, 3] with extended treatment interruptions posing a higher risk of virologic rebound [4, 5]. Consequently, identifying modifiable barriers to ART adherence is a public health priority. Substance use is particularly prevalent among HIV-positive adults. Among PLH in medical care, 66.4% report current alcohol use with more than 25% reporting at least weekly consumption [6]. Additionally, PLH have a prevalence of alcohol use disorders that is two to three times that of the general population [7]. Heavy alcohol consumption is independently linked with earlier mortality among PLH [8] and decreased overall survival of more than three years with weekly alcohol use and more than six years with daily consumption [9]. In addition, a significant proportion of PLH use marijuana; prevalence estimates range from 10 to 24% [10, 11]. The growing trend towards the legalization of medical and recreational marijuana will likely have a continued impact on the prevalence of use among PLH. Notably, substance use is one of the most reliable predictors of poor adherence to ART [12]. Research suggests that alcohol use accelerates HIV disease progression directly through interference with ART metabolism [13] and indirectly via decreased ART adherence [14]. While previous studies have generally demonstrated a positive association between alcohol consumption and ART nonadherence [15, 16], a recent systematic review has found that the relationship may be more nuanced [17]. Findings examining the relationship between marijuana use and suboptimal adherence among PLH have been mixed. Some studies show an association [18, 19] while others have found no relationship [20, 21]. While most studies have focused on unintentional nonadherence to ART in the context of alcohol or drug use, other studies have found that substance use is linked to intentional nonadherence specifically when PLH support the belief that mixing illicit drug use with HIV medications is a harmful combination [22–24]. Consequently, the effects of alcohol and marijuana use on HIV treatment outcomes have important public health implications. In particular, behavioral interventions that address substance use may improve HIV disease management and postpone disease progression. Valid ART measures are essential to assess virologic effects of nonadherence as well as to test the efficacy of behavioral interventions to improve adherence to ART regimens [25]. Traditional tools for measuring medication adherence have inherent limitations. For example, retrospective self-reports are subject to recall errors and social desirability bias while electronic medication monitoring devices (e.g., MEMS caps) are costly and run the risk of malfunctioning [26]. Given their widespread use and convenience, the use of mobile technologies to measure both substance use and ART adherence in near real time is a promising strategy that would allow for the immediate identification of adherence challenges before the loss of viral suppression [27]. Demonstration that event-level information on the occurrence of substance use and ART adherence in one's natural environment could be collected reliably by use of a less expensive method, such as participant self-report via smartphone, would fill a known gap in the literature regarding feasibility and acceptability of such methods and may have implications for educational program development among PLH. Similar to other procedures that apply phone protocols (e.g., interactive voice response; IVR) using a smartphone-based application (app) for daily data collection minimizes recall bias, promotes ecological validity, and minimizes missing data or out-of-range responses [28–30]. Gathering data on the day-to-day experiences and behaviors of PLH has the potential to provide a unique perspective of the frequency of substance use and medication compliance in a real world setting and can reveal detailed information about social and environmental influences that may cooccur with these events. Importantly, using this participant-initiated method of data collection may be particularly appropriate for collecting data on alcohol and marijuana due to the episodic nature of substance use behaviors [31]. The emerging area of developing mobile technology for public health intervention calls for careful research among target populations to explore the acceptability of delivering such programs [32]. Questions remain about the feasibility, acceptability, and user preferences of collecting daily electronic reports of health-related behaviors among PLH. For example, stigmatization of HIV [33] may raise confidentiality concerns that may impede participation. In addition, a recent IVR study found that a significant minority of participants (20%) did not utilize the IVR system at all [34], indicating the importance of identifying preferences for engagement and utilization among potential participants. More than 90% of Americans own a cell phone with 64% owning a smartphone [35]. This increasing trend of smartphone ownership provides a potentially promising platform for delivering substance use and adherence interventions broadly and inexpensively, especially for those who may not typically access in-person interventions. While the use of mobile technologies in HIV healthcare and prevention delivery in general and ART adherence in particular is growing, previous studies using cellular phones as a technology platform most often aim to improve adherence via the use of reminders to take one's medication, most commonly in the form of text messaging [36, 37]. Few ART adherence studies assessed other behaviors that impact ART adherence, such as substance use. Therefore, the aim of the pilot study was to quantitatively and qualitatively explore the feasibility of data collection via app-based reporting of substance use and adherence to ART regimens to aid in the appropriate design and implementation of subsequent education or intervention programs tailored towards substance-using populations with ART adherence concerns. 2. Methods 2.1. Participant Recruitment and Screening Procedures Study participants were recruited from two HIV primary care clinics that provide clinical care to the majority of PLH in the Western New York region, each being Patient Centered Medical Home (PCMH) Level 3-certified clinics. The first site was a community-based clinic and the second site was a state-certified, hospital-based Designated AIDS Center (DAC). Study eligibility criteria included being at least 18 years old, English-speaking, able to read at a Grade 7 level or better, HIV-infected, and currently on a prescribed ART regimen for at least three months. Eligibility criteria also included at least two days of alcohol use and at least one day of ART nonadherence in the past week. A two-stage screening procedure was used between June 2014 and February 2015. First, potential participants were asked to complete a brief self-administered health screening survey upon arrival at the clinic for a scheduled medical appointment. Second, research staff gave a brief study overview to eligible participants; those who agreed to participate were scheduled for a study visit. 2.2. Study Procedures Eligible participants completed informed consent and a review of study instructions at the first in-person study appointment. Participants brought their ART medication in the originally prescribed bottles or pill boxes to verify and document the prescribed regimen and completed a self-administered survey. They also received a detailed training session regarding basic smartphone operation and data entry for the completion of daily reports using the DRUM app (see Figure 1) and had the opportunity to complete practice reports in the presence of study staff members. They also received a paper-based instruction manual and were advised to contact study staff in the event of technical challenges. Participants were instructed on study policies for appropriate use of the smartphone, advised that the device was for research purposes only (e.g., to complete daily reports, contact the study staff), and informed that usage records would be monitored. For the next 14 days, participants received text message reminders at 4 pm to complete their daily reports. After the 2-week reporting period, participants completed the second in-person study appointment to return smartphones (to be reused by subsequent participants) and completed a self-administered survey. With consent to be audio-recorded, an in-depth interview was also conducted with a research staff member. Participants also received an informational pamphlet regarding substance use and ART. Compensation included $10 and $30 gift cards for the first and second study visits, respectively. Participants received $1 for each submitted daily report and a $3 bonus each week for completing seven consecutive reports (maximum compensation $20 for daily reports). Total maximum compensation for the entire study was $60. All study procedures were Institutional Review Board approved. 2.3. DRUM App With the ability to operate on any smartphone platform, a mobile web application called DRUM (Daily Reports of Using Medications) was created for daily report completion. The DRUM app was developed by the principal investigator, a project coordinator, and a web-support project manager. The app was run by a browser, allowing users access as if it was a webpage. Study-issued smartphones (Motorola Droid Razr M) had the DRUM app installed on the home screen preset with a unique 5-digit passcode. While smartphone ownership was not an inclusion criterion, participants who preferred to use their own smartphone were permitted to do so and added the DRUM app on their home screen, similarly using an assigned passcode to open the app. Images of key screens and functionality are shown in Figure 1. Once text-prompted to respond, respondents were given a 2-hour window to access the DRUM app and complete the daily report (i.e., time-based reporting) to maintain fixed assessment intervals. If participants failed to complete a report by 6 pm, they had the ability to access the DRUM app and complete a make-up report the following day. The same set of closed-ended sequential questions assessed specific behaviors in the previous 24-hour period. Daily reports were designed to display one question on the screen at a time, asking participants to either check an appropriate box, fill in a number, or select responses from a drop-down menu. Navigation between questions was facilitated by the use of a “previous” and “next” button. Responses were uploaded with a time and date stamp to a secure server in real time. 2.4. Measures 2.4.1. Visit 1 Survey Participants completed a brief self-administered survey which assessed sociodemographic (e.g., age, marital status, and educational attainment) and clinical characteristics (e.g., date of ART initiation, viral load detectability). Other measures are described as follows. Alcohol Use. Alcohol use was assessed using the AUDIT, a 10-item scale used to measure alcohol consumption and identify risks for alcohol use and dependence [38]. Substance Use. Use of other drugs in the last month, including illegal drugs and prescription drugs not used as prescribed, was assessed using questions adapted from a previous study of PLH [39]. Mobile Phone Technology and Internet Utilization. Participants completed a 20-item measure that assesses mobile phone and Internet utilization. These items were adapted from a mobile phone-based HIV prevention intervention [40] and included questions regarding utilization of phones, laptop, desktop, or tablet computers for a variety of reasons including email, text messages, and app use. ART Medication Regimen and Adherence Survey. Participants completed an interviewer-administered survey that asked about one's currently prescribed ART medication regimen. Participants were queried about adherence to ART using the AIDS Clinical Trials Group (ACTG) Adherence Questionnaire, which employs a 4-day recall period [41]. Participants completed a visual analog adherence rating scale to indicate the point along a continuum showing the percentage of ART they have taken in the previous month. Standard instructions were designed to counter socially desirable response biases by acknowledging that it can be difficult to take ART [42]. 2.4.2. Daily Reports via DRUM App For 14 consecutive days, participants were asked “How many alcohol drinks did you consume in the last 24 hours?” Positive responses were followed by additional questions, including the time of first and last drink, location of alcohol consumption (e.g., bar, friend's house), and reasons for drinking (e.g., enjoy a social situation better, reduce the stress of illness). Similar items assessed marijuana use. Each daily report also asked “What time did you take your first dose?” Participants who indicated that they did not take their dose received a follow-up question to indicate the main reason why a dose was missed. A similar item queried about second dose, with an option to respond with “I only take one dose per day.” (See Figure 1.) 2.4.3. Visit 2 Survey After the two-week daily report period, a 14-item quantitative survey was completed at the second in-person study visit. The survey included items about overall satisfaction with the DRUM app, concerns about privacy/confidentiality, honesty of responses in the daily reports, and likelihood of future participation in a similar smartphone-based study. 2.4.4. Qualitative Interview A brief, semistructured qualitative interview guide was used to assess participants' general reactions to daily report completion, generate feedback on their experiences with the DRUM app, and learn about previous experiences and future interests in phone-based reporting of health behaviors. Interviewers also recorded detailed observation notes immediately after the qualitative interview which were added to interview transcripts to form complete data files. 2.5. Data Analysis As this was a pilot study, we were interested in assessing the feasibility of recruiting, enrolling, and retaining participants. Specifically, we examined the proportion of patients screened who were eligible, the proportion of eligible participants who enrolled, overall participant retention, the proportion of study participants who opted to use their own personal smartphone for reports, the compliance rate for daily reports, and the number of smartphones lost during the course of the study. Indicators of study satisfaction, study acceptability, previous experience with device-based behavioral reporting, and likelihood of participation in future smartphone-based studies were assessed. All quantitative analyses were conducted using Stata version 14.1. For the analysis of qualitative interviews, two authors independently reviewed transcriptions to develop a broad understanding of reactions to study participation and identify core concepts. A detailed thematic analysis was undertaken using a deductive approach. Transcripts were repeatedly read several times and a codebook was created to delineate precise descriptions that emerged from the data. The transcripts were coded deductively, labeling sections of text based on particular domains of interest to organize the text into categories. Discussions about the coding schema were conducted and discrepancies between coders were resolved by discussion and consensus. The descriptive codes were then systematically organized into broader themes [43]. Representative quotes were retained during analyses to illustrate key findings. 3. Results 3.1. Study Enrollment Across the two primary care clinic sites, 635 individuals completed the health screening survey and 39 met eligibility criteria. Twelve individuals declined to enroll (five were not interested, three initially expressed interest but failed to appear at the scheduled study visit, two did not have time to participate, one was moving to a different state, and one was missed at the clinic and provided no contact information). Of the 27 participants enrolled, one participant declined study continuation after completion of the first study visit. The current analysis focuses on the remaining 26 participants (see Figure 2). The mean number of days between eligibility screening and completion of the first study visit was 7.4 days (range = 1–28) and the mean number of days between the first and second study visits was 17.2 days (range = 15–32). The total study duration averaged 24.6 days (range = 16–47). 3.2. Study Participants Sociodemographic characteristics of study participants are presented in Table 1. The majority were male (76.9%) and African American (53.8%) ranging in age from 22 to 60 years. The mean time since HIV diagnosis was nearly 17 years and most reported an undetectable viral load. Most participants (80.8%) reported past month Internet use though smartphone ownership and the use of apps on a phone was minimal. The majority demonstrated hazardous alcohol use [Mean AUDIT score = 17.08, SD = 6.56]. Additionally, nearly two-thirds reported marijuana use in the previous month. 3.3. Compliance with Daily Reports There were a total of 364 possible daily reports across the 14-day period and 347 were completed (overall completion rate = 95.3%; range 21.4–100%). Forty daily reports were considered make-ups (11.4%) completed via smartphone one day after the scheduled date. Of the 347 completed reports, 92.5% were completed via smartphone. Some participants reported technical issues involving connectivity (e.g., participant was unable to access the app in a rural area) and device failure (e.g., participant temporarily misplaced the smartphone charger and was unable to complete daily reports). Upon experiencing these technical problems, participants contacted study staff resulting in 7.5% of reports being completed via telephone with a researcher. More than two-thirds of participants completed daily reports on a study-issued device. Eight participants (30.8%) opted to use personal smartphones, consistent with previous studies among PLH [44, 45]. Two devices were reported as lost and replacement phones were obtained. During the two-week reporting period, participants reported alcohol consumption on 179 days (51.6%, range 0–14 days) with an average of 5.47 (SD = 5.68) drinks per drinking day. Marijuana use was reported on 123 days (35.4%, range 0–14 days) with an average of 3.69 (SD = 2.53) joints per marijuana use day (see Table 2). Overall ART adherence was 77.5% [(number of doses taken/number of prescribed doses) × 100]. Among the nearly three-quarters of participants who had once-daily ART regimens, the adherence rate was 87.17%. The seven participants on twice-daily regimens reported a 73.17 adherence rate (93.9% adherence rate for the first dose and 52.44% for the second dose, resp.). The most common reasons for failure to take one's first ART dose were change in daily routine (35.9%), forgetting (25.6%), and substance use (18.0%). The most common reasons for missing one's second ART dose were change in daily routine (37.5%), forgetting (17.5%), and being too busy (15.0%). 3.4. Quantitative Survey Findings From a quantitative standpoint, study satisfaction was uniformly high (see Table 3). Participants had high ratings for the usefulness of the daily report training session (mean 4.64 out of 5; 92% indicating moderately/very helpful), and most (84%) indicated that the smartphone system was easy to use (mean 4.60 out of 5) despite a sizeable minority (44%) reporting limited or no previous experience with smartphones. Satisfaction with the reporting system was also high (mean 4.56 out of 5; 96% satisfied/very satisfied). Scores for accuracy regarding the level of honesty in reporting were high (mean 4.56 out of 5; 92% honest/very honest). The majority (92%) of participants indicated that they would be likely or very likely to participate in a similar daily reporting system in the future. The average time from initiation to completion of daily reports was 3.68 minutes (SD = 3.25). Most participants (80%) indicated that the survey duration was “just right,” while the remaining 20% said it was “too short” and none indicated that it was too lengthy. No participant reported prior experience with survey completion on mobile devices. Overall, participants indicated a high likelihood that they would participate in a similar daily reporting experience in the future (mean 4.48 out of 5; 92% likely/very likely). 3.5. Qualitative Interview Findings Study participants reported their experiences regarding study involvement that generated four primary themes: (a) time commitment; (b) user-friendliness of the DRUM app; (c) confidentiality and privacy; and (d) key features of the DRUM app, outlined in detail below with representative quotes supporting these themes. 3.5.1. Time Commitment Participants indicated that the daily report was not a burden on their time, stating that it typically took between 2 and 10 minutes to complete reports, corroborating quantitative findings. Most indicated that the time commitment was reasonable since the survey questions were straightforward, easy to understand, and expected given the training delivered by study staff. According to one participant, It was not a burden on my time ‘cause I had a window period, which I took that time out to make sure I'd get my daily report in. So, I put a routine into it. I got a daily report to do. So, whatever I'm doing, I'm gonna stop. I'll be doing some drinking, we'll be smoking weed, and company at the house. I say “Hey, you know, I gotta do something. … gotta stop for a minute.” (45-year-old male) 3.5.2. User-Friendliness of the DRUM App Many participants indicated that the study was engaging and the DRUM app was easy to use. Several also mentioned the usefulness of the training provided by study staff to adequately prepare them in their independent use of the DRUM app, which supports quantitative findings. As one participant shared, It's so convenient. It reminds you and then also you have in your head is what time you have to take it. So it's easier than getting a piece of paper ‘cause a piece of paper, you be like “oh, I'll do it later” And then everybody is into phones now, so it's so much easier. You have a phone with you, you can just do it. It's just simpler. (46-year-old female) Several similarly indicated that they “looked forward” (42-year-old male) to completing the reports as something to do during the day and that it was a “piece of cake” (52-year-old male) and “pretty self-explanatory” (48-year-old male). Other participants who reported visual issues (e.g., needing reading glasses to see smaller print) indicated that the DRUM app was “bright and clear and easy to read” (48-year-old male). As one participant describes, I just like it. It's more comfortable. You know, you don't have to be writing. You can just hit a screen and it goes to the answer. It's just more comfortable for me. (48-year-old female) For those participants who opted to use their personal smartphone, there were no accounts of difficulty in installing or using the DRUM app. Most expressed a preference for completing daily reports on their own smartphone rather than be asked to carry two devices for the duration of the study. Participants who reported no prior experience with a smartphone or those with limited technology experience stated that the DRUM app was easy to use to input their answers. As shared by one participant, I don't have much computer skills so it was kind of like, I feel smart. I was just scared I wouldn't know how to do it. But when you gave me the phone to take it home, I checked it, and it was more easy than I thought it was (going to be). (44-year-old female) Nonetheless, some participants shared that it took some practice to become more comfortable with the number and type of questions, particularly in the first few days of the reporting period. Others mentioned that they overestimated the level of difficulty in using the DRUM app, but found it to be relatively straightforward. As described by one participant, To be honest, the first time it took me a bit because I was still trying to get used to it. But now I breeze right through it. (51-year-old woman) 3.5.3. Confidentiality and Privacy Several participants described their comfort in knowing that the research study's procedures placed a strong emphasis on confidentiality. For example, the use of a unique 5-digit passcode to access the daily report system helped participants feel secure in sharing their personal health behaviors in the absence of any identifying information. They also positively endorsed the use of survey questions that did not overtly reveal their HIV serostatus. For example, one participant explained, Back when I was in denial (about an HIV diagnosis), I would be scared that somebody would look at my texts… Now, it didn't say “your HIV survey”. It just said, “time to do the survey”… something like that. So I felt comfortable. It didn't put me out there as an HIV-positive person but it reminded me of what I had to do. (51-year-old woman) Many participants indicated that they lived alone and often completed the reports in their own house or apartment with no apparent fears regarding privacy. In certain instances where reports were entered in the presence of others, participants commonly described curiosity expressed by others but did not indicate that their presence served as a barrier preventing them from accessing the DRUM app in the company of friends. As one participant described, Most of the time, I was at home. Only twice I wasn't. I didn't have difficulty. It was more of privacy. Like, “what are you doing?” questions from other people. It was kind of weird because I lied (about doing the report). In a sense, it was very private because the two times that it happened, the people had no understanding of what I was doing. I was just pressing numbers. (54-year-old male) 3.5.4. Key Features of the DRUM App Two important characteristics of the daily report system were commonly discussed by study participants. First, several individuals commented on the value of the daily text message reminders. This prompt established a routine notification that cued participants to open the DRUM app. Many indicated that they had kept the phone in their pocket or in a visible location (e.g., coffee table or night-stand) making it simple to complete the reporting immediately when the text prompt was received. As one participant shared, I kinda enjoyed it to be honest with you, because I would be in the middle of something and my phone would buzz. I mean, I have a certain tone for texts. And I would look down after the buzz for the text and I see that it says [university's affiliation] and I say, “oh yes, I have to do this”. And I would say to my friends or whoever, “listen, just give me 2 minutes” you know. And 2 minutes is nothing. (57-year-old male) Second, those participants who failed to complete a report and were subsequently provided a choice to complete a make-up report the next day remarked about their satisfaction with this option. The most commonly reported reason for missing a daily report included leaving one's home and forgetting to bring the smartphone. There were also instances where changes in one's routine schedule contributed to a missed report. As one participant remarked, One day I did miss, but I was able to make it up the next day. And I did miss because I had just one of those days that was just… and I had the phone with me. But it was just one of those days where I was knocked out. I was exhausted and then I was still running around in between there. And I was like… by the time I realized it was 7:00. I'm like, “Oh, crap. Let me see if it's still open for me”. And no. So, it's really good (to offer a make-up report option). (36-year-old male) 4. Discussion There is increasing interest in the use of smartphones for health behavior assessment and monitoring. Despite the growth of health-related apps available, there is limited research among PLH on user experiences and perspectives regarding the reporting of health-related behaviors using phones as the reporting platform. The results of the current study demonstrate the feasibility of reporting daily substance use and medication behaviors using mobile devices. Although no participant reported prior experience with smartphone-based health reports, after a brief training, compliance was high; more than 95% of reports were completed indicating that participants were successful at independently completing two consecutive weeks of reporting. A primary objective of the pilot study was to demonstrate feasibility of the DRUM app. Importantly, our findings suggest that (1) simple, brief daily reports were generally found to be acceptable with high interest in future study participation; (2) offering participants the choice to complete reports on a study-issued device or a personal smartphone was well accepted; and (3) additional study features (e.g., text message reminders, make-up report options, and password-protection for app entry) were considered favorable and convenient. Despite the general positive responses regarding study acceptability, certain challenges were identified. While technical difficulties were generally few, they were not absent. A modest number of daily reports (n = 26) were completed over the telephone with a research staff member rather than via the DRUM app. We listed the research study telephone number in multiple places (e.g., on the smartphone, charger, and appointment reminder card) to facilitate contact at the time of reporting in the event that a problem presented, which presumably contributed to a decreased likelihood of nonreporting as a result of technical challenges. Offering participants multiple strategies to enable communication via a variety of modalities (e.g., phone, text, or email) is strongly encouraged in subsequent studies to assist participants in adequately addressing technical difficulties when they arise. There were two instances of study-issued devices being reported as lost and replacement phones were obtained, a finding noted in previous studies [46, 47]. The use of integrated prevention techniques such as regular, consistent monitoring of device usage is recommended for future studies. Specifically, smartphone usage (e.g., telephone calls, non-research study text messages) for each device was tracked daily by the research team. In instances that indicated an inordinate amount of nonresearch related incoming and outgoing texts and phone calls, researchers immediately deactivated the devices and contacted study participants who subsequently reported the phone was missing or stolen. In neither instance was the device recovered. For future studies, it is strongly advised to remind participants to contact research staff members immediately in the instance of a device being lost or stolen. Furthermore, participants must be reminded that engagement in unauthorized activity on a study-issued smartphone may result in device deactivation, loss of compensation for daily reports, and removal from subsequent data collection. The use of a follow-up study visit offered an opportunity to conduct additional in-person data collection but also served as a financial incentive for participants to return the devices. Additionally, future studies may consider the provision of the smartphone (excluding a data plan) after study completion as an additional incentive for study participation. 4.1. Limitations Study results should be interpreted with caution given the existence of limitations. The study was conducted at two primary care clinic sites with patient screening only occurring during certain hours (i.e., 9 am–12 pm) limiting the generalizability of our findings. Our study sample was primarily middle-aged men, potentially limiting the applicability to other age groups, women, and transgendered individuals. However, the sample was representative of the HIV-positive adult population in terms of age, race, and sex for the larger geographic region from where participants were recruited. The study also had a relatively short follow-up period and daily reporting was limited to a two-hour period. Future research should weigh the potential advantages and disadvantages of the frequency and duration of reporting with careful consideration for the potential that longer reporting periods and multiple reports per day may become burdensome for participants as they experience report fatigue [47]. Additional studies should also establish the validity of reports using apps developed for research purposes. 5. Conclusions This pilot study has important implications for prevention research and program development. The use of mobile devices for health assessment and intervention will likely continue to grow as smartphone ownership increases. Results demonstrated that HIV-infected adults have the capability of and interest in successfully completing health-related electronic reports, reporting positive experiences even with minimal prior exposure to smartphones. Importantly, participant satisfaction with the study procedures was uniformly positive. This data collection approach can be a valuable resource in identifying risk behaviors leading to prompt intervention in response to substance use or adherence concerns. Acknowledgments This study was supported by a Howard T. Blane Director's Award for the Development of Innovative Research in the Addictions (University at Buffalo Research Institute on Addictions). The authors thank Evergreen Health Services and the Immunodeficiency Services of the Erie County Medical Center whose staff facilitated the implementation of this pilot study. They also thank Pamela Novello-Smith and Eric Anson for their assistance with survey programming, app development, and database management. Competing Interests The authors declare that they have no competing interests. Figure 1 Screenshots of sample DRUM daily report questions. Figure 2 Participant recruitment and enrollment. Table 1 Demographic, clinical, substance use, and mobile technology use characteristics. Measure n (%) Demographic characteristics   Age [M (SD)] 48.4 (9.49) Sex    Female 4 (15.4)  Male 20 (76.9)  Transgender 2 (7.6) Sexual identity    Straight/heterosexual 12 (46.2)  Gay/homosexual 9 (34.6)  Bisexual 3 (11.5)  Other 2 (7.7) Race    African American 14 (53.8)  White 9 (34.6)  American Indian 1 (3.8)  Other 2 (7.7) Education    High school or less 15 (57.7)  Some college or more 11 (42.3) Employment    Not employed 21 (80.8)  Full or part-time 5 (19.2) Annual income    <$20,000 22 (84.6)  ≥$20,000 4 (15.4) Clinical characteristics   Undetectable viral load 18 (69.2) Years since diagnosis [M (SD)] 16.92 (8.65) Substance use characteristics   Cigarette smoking    Daily 16 (61.5)  <Daily 5 (19.2)  None 5 (19.2) AUDIT score [M (SD)] 17.08 (6.56) Hazardous drinker (AUDIT score 8–15) 10 (38.5) Harmful drinker (AUDIT score 16–19) 3 (11.5) Probable alcohol dependence (AUDIT score ≥20) 4 (15.4) Marijuana use (past month) 16 (61.5) Crack use (past month) 7 (26.9) Mobile technology and Internet use characteristics   Mobile phone ownership 18 (69.2) Smartphone ownership 9 (34.6) Mean number of mobile phone numbers in past six months (SD) 1.50 (2.04) Average number of texts sent on a daily basisa    0–9 9 (50)  10–49 7 (38.9)  50+ 2 (11.1) Using apps on phone in past montha 11 (61.1) Using apps on phone on a daily basisb 9 (81.8) Internet use in past month 21 (80.8) Mean number of hours per day on Internet 3.30 (2.64) a n = 18 participants who indicate mobile phone ownership. b n = 11 participants who report any app use in past month. Table 2 Day-level and aggregate level substance use and ART nonadherence. Participant Day-level data Aggregate level data 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Alcohol days Marijuana days Nonadherence days 1 AMN AMN N N N N AN AMN AMN N N N N N 5 4 14 2 AM AM AM M M M M AM M AM AMN AM M AM 8 14 1 3 MN M M           M     M     0 5 1 4 AN   M   A   A A A A A     A 8 1 1 5     A A   AM   A   A A A A   8 1 0 6                             0 0 0 7   N                   A A A 3 0 1 8 A           A A A   AM       5 1 0 9 A   A   A     A A A         6 0 0 10 AM AMN AM AM AM AMN AM AMN AM AMN AM AM AM AM 14 14 4 11 AMN AM AM   M AMN AMN     A A   A A 9 6 3 12 AM M M AMN AM AM M M AM M AM AM AM AM 9 14 1 13 A A A A A A AN   A A A A A A 13 0 1 14 M             M M       A AM 2 4 0 15   AM   AM AM AM   A A A   AM M AM 9 7 0 16 AM AMN AMN A AMN AMN   AM AMN AM AMN MN AMN AMN 12 12 9 17 A   AM   AM AM AM A A AM AM   AM AM 10 8 0 18 AN AN AN AN A M M M AM   M A   A 8 5 4 19   N N N N N N N N N N N N N 0 0 13 20 AM AMN AM AMN AM AM AM AM AMN M M AM AMN AM 12 14 4 21 A               A     A A   4 0 0 22 AMN AMN M AM AM M M   AMN AMN AM AM AMN AM 10 13 5 23   N   N N A         N N N N 0 0 7 24 AN A A A A A A A A A A A A A 14 0 1 25 AMN A     AN A A   A A   AN A A 10 1 3 26 M                           1 0 0 A: alcohol; M: marijuana; cells with N indicate ART nonadherence. Table 3 Pilot study acceptability. Item Rating scale (1 to 5) M SD Study team support        How helpful was the training you received about the smartphone system? Not at all helpful–very helpful 4.64 0.76  My questions were answered in a timely manner by the research team. Strongly disagree–strongly agree 4.68 0.69 Overall reactions        Completing the daily reports interfered with my daily activities. Strongly agree–strongly disagree 3.88 1.45  We'd like to know how long it took you to do the daily report. Was it Too long–too short 2.00 0.41  How easy or difficult was it to use the smartphone system to do reports? Very difficult–very easy 4.60 0.76  How satisfied were you with the overall reporting system? Very dissatisfied–very satisfied 4.56 0.71 Reporting concerns        How concerned were you about privacy when completing your reports? Not at all concerned–extremely concerned 1.68 1.49  How concerned were you about confidentiality with your reports? Not at all concerned–extremely concerned 2.00 1.58 Willingness to participate in future studies        How likely would you participate in a similar daily report experience in the future? Very unlikely–very likely 4.48 1.12  How likely would you be to recommend this study to a friend? Very unlikely–very likely 4.32 1.11 Reporting accuracy        How honest were the answers you gave on the daily reports? Very dishonest–very honest 4.56 0.77 ==== Refs 1 Thompson M. A. Aberg J. A. Cahn P. Antiretroviral treatment of adult HIV infection: 2010 recommendations of the International AIDS Society-USA panel The Journal of the American Medical Association 2010 304 3 321 333 10.1001/jama.2010.1004 2-s2.0-77954692660 20639566 2 Haberer J. E. Musinguzi N. Boum Y. 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==== Front J Diabetes ResJ Diabetes ResJDRJournal of Diabetes Research2314-67452314-6753Hindawi Publishing Corporation 10.1155/2016/6264149Review ArticleMetainflammation in Diabetic Coronary Artery Disease: Emerging Role of Innate and Adaptive Immune Responses http://orcid.org/0000-0002-5639-4948Aravindhan Vivekanandhan 1 * Madhumitha Haridoss 2 1Department of Genetics, Dr. ALM. PG. IBMS, University of Madras, Chennai 600113, India2AU-KBC Research Centre, MIT Campus of Anna University, Chennai 600044, India*Vivekanandhan Aravindhan: cvaravindhan@gmail.comAcademic Editor: Zhenwu Zhuang 2016 16 8 2016 2016 626414919 5 2016 19 7 2016 Copyright © 2016 V. Aravindhan and H. Madhumitha.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Globally, noncommunicable chronic diseases such as Type-2 Diabetes Mellitus (T2DM) and Coronary Artery Disease (CAD) are posing a major threat to the world. T2DM is known to potentiate CAD which had led to the coining of a new clinical entity named diabetic CAD (DM-CAD), leading to excessive morbidity and mortality. The synergistic interaction between these two comorbidities is through sterile inflammation which is now being addressed as metabolic inflammation or metainflammation, which plays a pivotal role during both early and late stages of T2DM and also serves as a link between T2DM and CAD. This review summarises the current concepts on the role played by both innate and adaptive immune responses in setting up metainflammation in DM-CAD. More specifically, the role played by innate pattern recognition receptors (PRRs) like Toll-like receptors (TLRs), NOD1-like receptors (NLRs), Rig-1-like receptors (RLRs), and C-type lectin like receptors (CLRs) and metabolic endotoxemia in fuelling metainflammation in DM-CAD would be discussed. Further, the role played by adaptive immune cells (Th1, Th2, Th17, and Th9 cells) in fuelling metainflammation in DM-CAD will also be discussed. Department of Science and Technology, Ministry of Science and Technology2012/37B/11/BRNS/947SR/FT/LS-105/2009University Grants Commission ==== Body 1. Introduction In recent years, noncommunicable chronic diseases such as Type-2 Diabetes Mellitus (T2DM) and Coronary Artery Disease (CAD) are posing a major threat to the world irrespective of geographical and ethnic boundaries [1]. T2DM is known to potentiate CAD which had led to the coining of a new clinical entity named diabetic CAD (DM-CAD), leading to excessive morbidity and mortality [1]. The synergistic interaction between these two comorbidities is through sterile inflammation which is now being addressed as metabolic inflammation or metainflammation [2]. Metainflammation is due to the dysfunction of the immune system which acts like a double edged sword: at optimal level it confers protection against pathogens; at the suboptimal level it leads to immunodeficiency; at supraoptimal level it leads to inflammation. The pathogenesis of DM-CAD is complex with the involvement of multiple factors including genetic predisposition and various environmental factors like high fat diet, sedentary life style, and chronic stress [1]. Though the association of inflammation with T2DM and CAD was envisioned as early as in 1800s the mechanisms mediating these inflammatory responses were not clearly known [3]. T2DM arises due to insulin resistance (IR) during early stages, which in turn arises due to the inflammation of the insulin target organs (adipose, skeletal muscle, and liver) [4]. IR leads to increased insulin demand and thereby causes rapid exhaustion of pancreatic beta cells due to overproduction, eventually leading to insulin deficiency (ID) [4]. Thus, late stage of T2DM is characterized by combined ID and IR leading to hyperglycemia, eventually leading to endothelial dysfunction [5]. CAD is a macrovascular complication characterized by enhanced extravasation and accumulation of inflamed macrophages under the tunica intima, wherein they engulf the oxidized lipids and become foam cells, leading to the formation of atherosclerotic plaques (atherogenesis) [5]. There are 4 important mechanisms that majorly contribute to the development of hyperglycemia induced cardiovascular damage: (1) increased sorbitol production due to activation of polyol pathway, (2) increased O-GlcNAcylation of cytosolic proteins, (3) activation of protein kinase C, and (4) increased formation of Advanced Glycation End-Product (AGE) [6]. The underlying common element in all these mechanisms is the increased production of reactive oxygen species (ROS) in endothelial cells under diabetic condition [6]. Recently redox stress has also been linked to neoangiogenesis as seen in microvascular complications (HIF-1α activation) and metainflammation (NF-κB activation) [6]. DM induced hyperglycemia accelerates the process of atherosclerosis, with greater infiltration of inflammatory macrophages and T lymphocytes and increased inflammation of the coronary artery [7]. Metainflammation augments atherogenesis by directly promoting arterial lipid deposition and inducing the proliferation and migration of smooth muscle cells [7]. It also indirectly promotes atherogenesis by augmenting other risk factors of CAD including dyslipidemia, diabetes, and hypertension [6, 7]. Thus there are several immune factors involved in atherosclerosis which involve cells (endothelial cells, macrophages, and lymphocytes), cytokines, chemokines, acute phase proteins, and adhesion molecules [8–10]. Among these C-reactive protein (CRP), Interleukin-6 (IL-6), and Tumour Necrosis Factor (TNF-α) have been used as predictive markers of CAD as evidenced by various epidemiological studies [10]. Thus, metainflammation plays a pivotal role during both early and late stages of T2DM and also serves as a link between T2DM and CAD. However, the exact mechanism behind the initiation of inflammation as seen in these two conditions is not clearly known. In this review, a summary of the role played by innate and adaptive immune responses in setting up metainflammation in DM-CAD would be presented. 2. Role of Innate Metainflammation in DM-CAD The innate immune system serves as a first-line defense mechanism against invading pathogens. Unfortunately, the same system also serves as the first-line initiator of metainflammation in DM-CAD. The pattern recognition receptors (PRRs) which include Toll-like receptors (TLRs), NOD-like receptors (NLRs), Rig-1-like receptors (RLRs), and C-type lectin like receptors (CLRs) serve as the major arsenal of innate immunity in detecting unique pathogen associated molecular patterns (PAMPs) and thereby alerting the immune system [11] (Figure 1). However, apart from these well characterized receptors, new members are being added to this ever increasing list. These receptors are widely distributed in immune and nonimmune cells to enable rapid detection of pathogens and immediate activation of the immune system (danger-signal hypothesis), resulting in immunity. In fact, these receptors act as bridges between the innate and adaptive arms of the immune responses [12]. However, under certain pathogenic conditions, the same receptors, which detect the pathogens, also detect commensals and self-molecules and activate the immune system resulting in metainflammation. Metainflammation in DM-CAD is characterized by increased serum levels of proinflammatory cytokines like TNF-α, IL-6, and IL-1β [13, 14] and anti-inflammatory cytokines like IL-10 and Transforming Growth Factor-beta (TGF-β) [15]. DM associated hyperglycemia and hyperlipidemia might also fuel metainflammation. Nonenzymatic glycation of proteins and oxidised lipids can bind to innate immune receptors and can activate them. Inappropriate activation of these receptors in various organs is believed to be a major contributory factor towards the increased secretion of these cytokines. Apart from this, increased ROS production could also be an underlying cause for the increased proinflammatory cytokine secretion through enhanced NF-κB activation [16]. 3. Role of Toll-Like Receptors (TLRs) in DM-CAD Among the various PRRs, the TLRs were the earliest and thus the most well characterized group of receptors. TLRs were first identified in Drosophila, wherein they were found to confer immunity against fungal infection [17]. Later, homologs of these receptors were identified in the human genome and were found to perform similar functions. Till date, at least 10 members of TLR family have been identified and characterized in humans and have been implicated in a wide range of inflammatory conditions including cancer, infection, autoimmunity, immunodeficiency, and graft rejection [18]. However, recent studies in animals and humans have shown their involvement in metabolic diseases especially DM-CAD [19–21]. These receptors apart from recognizing the PAMPs, present in the pathogens, also detect damage associated molecular patterns (DAMPs), present in the host culminating in inflammation [22]. Immune cells like B cells, monocytes, and dendritic cells predominantly express TLRs compared to NK cells and T cells which show lesser expression. Activation of TLRs results in the increased secretion of proinflammatory cytokines such as TNF-α and IL-6 which are known to induce IR leading to T2DM [23] and promote atherogenesis leading to CAD [24] (Figure 1). Increased expression of TLR4 has been reported in the adipose tissue [25], fatty liver [26], and skeletal muscle [27] of both mice and humans. However studies carried out in our lab have shown strong downregulation of TLR2 and TLR4 in B cells and monocytes of newly diagnosed T2DM subjects which was largely due to the upregulation of immunomodulatory enzymes indoleamine-2,3-dioxygenase (IDO), arginase-1, and heme oxygenase-1, indicating that chronic hyperglycemia can impair immunity by downregulating TLR expression [28]. This opens up a susceptibility window where newly diagnosed subjects are under increased risk to infections [28]. Enhanced expression of TLR1, TLR2, and TLR4 in atherosclerotic plaques has been reported in humans [29]. During high fat diet, these receptors get activated which results in the inhibition of insulin signaling augmenting atherogenesis [30]. TLR1, TLR2, TLR4, and TLR6 which are abundantly expressed in monocytes cooperate with CD14, CD36 (scavenger receptor), and complement receptors in transforming these monocytes into foam cells [31]. Activation of TLR results in the activation of NF-κB which has been identified as a “master regulator” of inflammation [32]. NF-κB activation occurs either through Mal:MyD88 pathway (which is sometimes referred to as MyD88-dependent pathway) or through TRAM:TRIF pathway (which is sometimes referred to as MyD88-independent pathway) [32]. Activated NF-κB induces proinflammatory cytokines which when secreted reinforce the action of TLRs, setting up a positive feedback loop [32]. Interestingly, apart from NF-kB, activation of IRF3 (by TLR3 and TLR4) and IRF7 (by TLR7, TLR8, and TLR9) results in the secretion of type-1 interferons (interferon-α and interferon-β) [33]. These interferons, like the proinflammatory cytokines, act in an autocrine fashion reinforcing the TLR stimulation, via IFN-αβR-STAT1 pathway [33]. Apart from cytokines and interferons, TLR stimulation leads to the secretion of variety of chemokines which are largely under the control of NF-κB and STAT-1 regulation [34]. While TLR induced secretion of proinflammatory cytokines, type-1 interferons, and chemokines promotes inflammation, TLR induced secretion of anti-inflammatory cytokine IL-10 (and in some cases TGF-β) is the major self-limiting pathway involved in curtailing inflammation [35]. IL-10, through the JAK1-STAT3 pathway, negatively regulates TLR signaling by degrading IRAK4 and TRAF6 thereby dampening MyD88-dependent pathway (but not the MyD88-independent pathway) [36]. Apart from NF-kB, IRFs, and STAT1, AP-1 and ATF3 are the other major transcription factors involved in TLR signaling and their role in DM-CAD is yet to be deciphered [32]. While the role of proinflammatory cytokines in promoting IR and atherogenesis is well known, the involvement of type-1 interferons, chemokines, and anti-inflammatory cytokines in these pathogenic processes is less well studied. 4. Role of NOD-Like Receptors (NLRs) in DM-CAD NOD-like receptors (NLRs) are the second group of pattern recognition receptors (PRRs) which are important components of the host innate immune responses that regulate metainflammation. Though NLR and TLR pathways are mediated through different adaptors, they induce the expression of proinflammatory cytokines by activating NF-κB signaling [37]. Various cell types express NOD1 and NOD2 including epithelial cells, dendritic cells [38], keratinocytes [39], macrophages [40], and the Paneth cells [41]. Among the NLR family members, NOD1 and NOD2 recognize bacterial peptidoglycans resulting in the activation of MAPK and NF-κB signaling leading to transcriptional upregulation of proinflammatory cytokines [41]. Along with NALP3 they promote the assembly of large multiprotein complexes called “inflammasomes” [42]. These inflammasomes in turn activate the proteolytic caspase-1 which cleaves and activates the proinflammatory cytokines IL-1β and IL-18 that signal cell damage [42]. Further, like TLRs they are also capable of activating type-1 interferons, via IRF3 [43]. Since NLRs and TLRs act in a similar fashion in provoking the inflammatory response, NLRs could also play a complimentary role in the pathogenesis of DM-CAD [44] (Figure 1). NOD proteins mediated metainflammation and IR has been demonstrated in many cell types [45–47]. Monocytes from T2DM subjects have shown upregulation of NOD1 and NOD2 mRNA which also correlated with HOMA-IR, indicating its role in T2DM [48]. NOD1 mRNA was markedly upregulated in the adipose tissue of diet-induced (DIO), but not genetically susceptible (ob/ob), obese mice [45]. Stimulation of NOD1 with a synthetic ligand Tri-DAP induced proinflammatory chemokines (MCP-1, RANTES, and MIP-2) and cytokines (TNF-α and IL-6) in 3T3-L1 adipocytes [45]. A similar proinflammatory profile was also observed in human primary adipocytes stimulated with NOD1 which suppressed insulin signaling [45]. Like NOD1, activation of NOD2 in L6-myotubes induced IR within 3 h, which was characterized by a reduction in insulin-stimulated glucose uptake, GLUT4 translocation, and IRS-1 and Akt-1 phosphorylation [46]. These results showed that NOD2 alone is capable of acutely inducing metainflammation and IR in muscle cells [46]. NOD1/2 KO mice were protected from high fat diet-induced metainflammation, lipid accumulation, and IR [49]. Conversely, direct activation of NOD1 in wild type mice induced IR within 6 h [49]. Oral administration of NOD1 ligand elicited minor changes in systemic inflammation yet caused pronounced IR in adipose tissue, muscle, and liver [49]. Not limited to T2DM, the role of NLRs is also signified in CAD [50]. Bacterial peptidoglycans (PG), the natural ligands of NLRs, were observed in human atherosclerotic plaques and were associated with plaque vulnerability [51]. Oral administration of NOD1 ligands into mice induced vascular inflammation leading to coronary arteritis [52]. Activation of NOD1 in a murine model induced cardiac dysfunction and modulated cardiac fibrosis and cardiomyocyte apoptosis and other pathological processes involved in CAD [53]. Thus, both NOD1 and NOD2 play a pronounced role in setting up metainflammation in DM-CAD. 5. Role of RLRs in DM-CAD RLRs which belong to RNA helicases family have three members, namely, (1) Retinoic acid-Inducible Gene-I (RIG-I), (2) Melanoma Differentiation Associated 5 (MDA5), and (3) Laboratory of Genetics and Physiology 2 (LGP2). These receptors specifically recognize viral RNA and activate the immune system [11]. Upon activation, RIG-I and MDA5 are recruited to the IPS-1 adaptor which is localized on the outer mitochondrial membrane. IPS-1, via TRAF3-TANK-NAP1 complex, recruits TBK1-IKKε-DDX3 complex and activates IRF3 and IRF7 simultaneously. IPS-1 also recruits TRADD and forms a complex with FADD-RIP-1-TRAF6 activating NF-κB, via IKK. Activated IRFs and NF-κB in turn activate type-1 interferons and proinflammatory cytokines, respectively. In an IPS-1 independent manner, RLRs promote inflammasome assembly and processing of pro-IL-1β and pro-IL-18 cytokines [11]. Like TLRs, RIG-1 also contributes to β-cell dysfunction indicating its role in metabolic regulation [54]. Under conditions of metabolic surplus, RIG-1 induces the blocking of Src/STAT3 signaling thereby arresting the beta cells from entering into G1 phase [54]. LGP2, the third member of this family, acts as a negative regulator of RIG-1 and MDM5 and inhibits inflammation [55]. Whether LGP2 induced negative regulation of RIG-1 and MDM5 is beneficial to T2DM and CAD is not yet known. 6. Role of CLRs in DM-CAD C-type lectin like receptors (CLRs) are Ca2+ dependent glycan-binding proteins that share a unique carbohydrate-recognition domain (CRD) [56]. It includes Type-1 (DEC205 and Macrophage Mannose Receptor (MMR)) and Type-2 (Dectin-1, Dectin-2, Mincle, DC-SIGN, and DNGR-1) membrane proteins and a soluble receptor (Mannose Binding Lectin (MBL)) [57]. Generally, CLRs recognize complex carbohydrates which decorate bacterial and fungal cell wall and activate the immune system [57]. However, under pathogenic conditions like T2DM, it is highly probable that the same receptors can recognize modified host glycans and inappropriately activate the immune system resulting in metainflammation. The modified host glycans which can bind to these receptors and activate them are yet to be characterized. Upon activation, CLRs like Dectin-1 and DC-SIGN which have ITAM signaling domain can directly activate signaling by recruiting downstream effectors, while those like Dectin-2 and Mincle which lack the ITAM signaling domain associate with other receptors like FcγR and FcεR and augment their signaling capacity [57]. Unlike TLRs, NLRs, and RLRs, CLRs do not activate IRFs and induce type-1 interferon secretion. They activate proinflammatory cytokine secretion, via NF-κB, AP-1, and NF-AT [57]. It has been reported that Mincle is induced in M1 macrophages in the adipose tissue under obesity condition thereby suggesting a role in obesity-induced inflammation [58]. The role of other CLRs in metainflammation as seen in DM-CAD is yet to be deciphered. 7. Metabolic Endotoxemia in DM-CAD Even though PRR stimulation has now been identified as a major event in setting up the metainflammation (as seen in DM-CAD), the exact trigger for PRR stimulation remains largely unknown since these receptors can be triggered by both endogenous (PAMPs) and exogenous (DAMPs) ligands. Recently, metabolic endotoxemia has emerged as a major culprit in activating PRRs and setting up metainflammation. Increased gut permeability due to changes in gut microbiota has recently been described in both T2DM and CAD [59]. Because of the leaky gut effect, increased efflux of LPS into systemic circulation takes place which, in turn, is detected by the PRRs [60]. But, more than the actual endotoxin levels, the levels of endogenous anti-endotoxin antibodies (EndoCAb), LPS binding protein (LBP), and soluble CD14 (sCD14) were found to be more important in determining the activity of endotoxin [61]. These three components play an important role in conditions of acute inflammation like septicemia. Even though metabolic endotoxemia was previously reported in both T2DM and CAD [62, 63], in T2DM it is associated with significantly reduced levels of EndoCAb, with no apparent change in the levels of sCD14 and LBP (unpublished data) while in CAD it is associated with significantly elevated levels of EndoCAb and decreased levels of sCD14 with no change in LBP levels [61]. Thus, depending on the relative levels of these accessory proteins, the endotoxin can bind to different PPRs and can initiate different types of metainflammation. While engagement of TLRs predominantly promotes IL-6 and TNF-α secretion [32], engagement of NLRs is known to activate inflammasomes resulting in the enhanced processing and secretion of IL-1β and IL-18 [44]. Apart from the secretion of proinflammatory cytokines, both TLRs and NLRs are known to induce the secretion of anti-inflammatory cytokines such as IL-10 and TGF-β, which counteracts the effect of proinflammatory cytokines and maintain immune homeostasis [32, 44]. An imbalance between the activities of pro- and anti-inflammatory cytokines disrupts the immune homeostasis and would pave the way for metainflammation as seen in DM-CAD. 8. Role of Adaptive Metainflammation in DM-CAD The presence of activated T cells in human adipose tissue (in the case of T2DM) and in atherosclerotic plaque (in the case of CAD) has been identified several years ago indicating the involvement of adaptive immunity in these disease conditions [64] (Figure 2). Adaptive immune cytokines include both Th polarizing and T cell effector cytokines which together shape the adaptive arm of the immune response. While the former is largely secreted by professional antigen presenting cells (APCs) and acts on naïve T cells, the latter is predominantly secreted by polarized T cells and acts on other immune/nonimmune cells. Earlier reports, including ours, have shown significantly increased levels of proinflammatory cytokines like TNF-α, IL-6, IL-1β, and GM-CSF in T2DM and CAD [14, 15, 65–67]. However, reports documenting the levels of adaptive immune cytokines in DM-CAD are scant. Recently, several novel T cell cytokines like IL-33 [68], IL-17 [69], and IL-9 [70] have been described. While IL-12 has long been known as the master regulator of Th1 polarization, IL-33 has recently emerged as a master regulator for Th2 polarization [71]. Upon activation, T lymphocytes differentiate into T-helper 1 (Th1) and Th2 subsets secreting either Th1 (Interferon- (IFN-) γ and IL-2) or Th2 cytokines (IL-4, IL-5, and IL-13), respectively [72]. Th17 and Th9 cell types are newly discovered Th subtypes which secrete IL-17 and IL-9 and play an important role in neutrophil recruitment and mucosal immunity, respectively [72]. 9. Th1 Cytokines in DM-CAD In general, the association of Th1 cytokines with adipose inflammation is well documented in both animals and humans. Pacifico et al. showed increased frequency of Th1 cells in obese children [73]. Wegner et al. showed increased levels of serum IL-12 in T2DM subjects that was associated with IR [74]. Our studies on serum cytokine profiling on subjects with metabolic syndrome indicated strong positive correlation of both IL-12 and IFN-γ levels with fasting blood sugar, triglycerides, HOMA-IR, and hsCRP and strong negative correlation with adiponectin [75]. In the murine diet-induced obesity model, Kintscher et al. showed early recruitment of Th1 cells into adipose tissue that precedes even macrophage infiltration and IR [76]. However, the exact mechanism by which IFN-γ, the signature cytokine of Th1 cells, brings about IR is not clearly known. IFN-γ might exert its action by interfering with the insulin signaling and insulin-stimulated glucose uptake, which might eventually lead to IR and T2DM [77]. Apart from their role in IR, Th1 cells also play a critical role in the initiation, progression, and rupture of atherosclerotic plaque leading to CAD [78]. Jonasson et al. have reported that most of the cells in the atherosclerotic plaque express HLA-DR, indicating continuous activation by IFN-γ [79]. The same group has demonstrated the expression of IL-2 and IFN-γ in a large proportion of the plaque cells [80]. In apoE KO mice, IFN-γ was shown to potentiate atherosclerosis through both local and systemic effects [81]. IFN-γ has also been proposed as a component of five panel markers for the prediction of CAD in symptomatic patients referred for coronary angiography [82]. Our studies on serum cytokine profiling in DM-CAD subjects indicated strong Th1 polarization during transition from T2DM/CAD to DM-CAD signifying the importance of Th1 polarization in the disease process [83]. Thus, in the light of the available literature, it seems that Th1 cytokines might worsen IR and promote atherogenesis in DM-CAD. 10. Th2 Cytokines in DM-CAD Compared to Th1 cytokines, the role played by Th2 cytokines in IR and atherogenesis is still an enigma. In a recent study, decreased serum levels of IL-13 in T2DM subjects were reported which was implicated in impaired glucose uptake and metabolism [84]. Chang et al. have demonstrated the role of IL-4 in improving insulin sensitivity and glucose tolerance in an animal model of diet-induced obesity [85]. Winer et al. showed that adoptive transfer of Th2 cells in Rag1 KO, diet-induced obese mice reversed weight gain and IR [86]. Recently, we have reported decreased levels of serum IL-33 in T2DM subjects, while the other Th2 cytokines like IL-4 and IL-13 were significantly increased [87]. In contrast to Th1 cells, Th2 cells are rarely detected within the atherosclerotic lesions [88]. In line with these reports, we found enhanced Th1 cytokine profile in CAD subjects with significant decrease in Th2 cytokine levels [83]. Accumulating evidence suggests that an imbalance in the Th1/Th2 cytokines with enhanced Th1 immune response and suppressed Th2 response has an important role in the transition of T2DM/CAD to DM-CAD [83, 89]. Thus, in the light of the available literature the increased levels of Th2 cytokines in T2DM implicate a countermeasure to inhibit Th1 immunity and thereby IR. However, when this system fails we see enhanced Th1 polarization eventually precipitating in atherogenesis and CAD. 11. Th17 Cytokines in DM-CAD IL-17 cytokine is produced by T-helper cell subset called Th17 which has been widely associated with autoinflammatory (irritable bowel syndrome) and autoimmune (rheumatoid arthritis and multiple sclerosis) [90] diseases. Th17 polarization is mediated through IL-1β, IL-6, TNF-α, and TGF-β and is stabilized by IL-21 and IL-23 [90]. Like other T cell cytokines, IL-17 might also play a role in metabolic diseases like obesity, dyslipidemia, IR, hypertension, and cardiovascular diseases which remains largely unexplored [90]. High glucose was shown to drive the expression of IL-17 in Jurkat T cells implicating the involvement of Th17 cells in T2DM [91]. However, unlike Th1 cytokines, the reports on IL-17 levels in T2DM are highly contradictory. Previously, increased levels of IL-17 were reported in T2DM [92]. However, our studies on subjects with diabetic nephropathy have indicated decreased levels of IL-17 under diabetic conditions [93] with no major difference in IL-23 levels (unpublished data). Even in diabetic retinopathy the serum levels of IL-17 were significantly reduced compared to control group [94]. Since the synthesis of IL-17 is influenced by other cytokines such as TGF-β which induces its secretion at lower concentrations and inhibits its secretion at higher concentrations [90], more mechanistic studies are needed to decipher the mechanism behind reduced IL-17 levels in T2DM. IL-17 might also have a pathogenic role in CAD. Studies carried out on CAD-prone apoE KO mice showed significantly elevated levels of plasma IL-17 and infiltration of IL-17 producing Th17 cells into the atherosclerotic plaques [95]. Further, neutralization of IL-17 with a soluble form of IL-17A receptor significantly reduced the size and number of atherosclerotic lesions [95]. In humans, apart from IL-17, IL-21 and IL-23 were also detected in the atherosclerotic plaques and were strongly associated with venerability of plaque rapture [96]. Thus, in the light of the available literature it seems that while IL-17 might offer some protection against IR in DM, it might worsen atherogenesis in DM-CAD. 12. Th9 Cytokines in DM-CAD Th9 cells are recently discovered Th cell subset which undergoes polarization in the presence of IL-4 and TGF-β [97]. IL-9 exhibits proinflammatory activity in the experimental models of inflammation [97]. Its role in allergies has been well demonstrated [97]. But studies examining its association with metabolic disorders are limited and are contradictory [98]. Previously, significantly increased levels of plasma IL-9 were reported in T2DM subjects [98]. However, our results showed significantly reduced levels of IL-9 in T2DM subjects which correlated positively with renal parameters [93]. In CAD-prone apoE KO mice, IL-9 exerts proatherosclerotic effects by inducing VCAM-1 expression and thereby promoting macrophage infiltration and atherosclerotic plaque formation [99]. In humans, increased levels of IL-9 in atherosclerotic disorders were seen both systemically and within the lesion, suggesting a role for the IL-9/IL-9R axis in the atherosclerotic process, potentially involving IL-17 mediated mechanisms [100]. Thus, in the light of the available literature it seems that while IL-9 might offer some protection against IR, it worsens atherogenesis in DM-CAD. 13. Conclusion Metabolism and immunity are essential requirements for survival. Mounting an effective immune response requires major changes to metabolic pathways. Similarly, immune mediators (such as cytokines) also dictate changes in metabolism making the communication bidirectional [101]. Thus, the fast emerging field of immunometabolism underpins the pathogenesis of metabolic diseases like T2DM and CAD [101]. Understanding the immune-metabolic interface is daunting. One contemporary issue is characterizing the sources and mediators of metainflammation, which was first characterized in adipose tissue but is now known to be present in many different tissues including liver, muscle, and arteries. Although, the metainflammation is hypothesized to arise from chronic nutrient excess, the sensors which detect these signals are only now beginning to emerge. PRRs have now emerged as major sensors which sense nutrient excess and fuel metainflammation. Once the signal is sensed, it is then transferred to Th cells by means of APC-T cell communication fuelling metainflammation. Interestingly, changes in metabolism also affect the immune response completing the loop [101]. As can be seen in this review even though metainflammation seems to be a common denominator for T2DM and CAD distinct qualitative and quantitative differences were noted between the two conditions indicating that not all metainflammations are the same and each metabolic disease is characterized by a unique inflammatory profile with distinct cytokines and inflammatory cells. However, caution should be noted in interpreting these data since most of these studies are cross-sectional and hence the cause-effect relationship cannot be determined. The apparent disparities noted on serum cytokine profiling between populations could be either due to ethnic differences or due to small sample sizes used or due to heterogeneity of the disease condition. Only parallel studies conducted on different ethnic populations with large sample sizes can solve this issue. Compared to serum cytokine profiling, studies looking at immune cells actually secreting these cytokines are limited and hence future studies should envision identifying the immune cells secreting these cytokine and not just look at serum cytokine levels. Finally, these studies would gain translational value only when the therapeutic utility of monoclonal antibodies against these cytokines is tested in animal models and clinical trials. Acknowledgments This review was partially funded by DST FAST TRACK (SR/FT/LS-105/2009) and DAE-BRNS (2012/37B/11/BRNS/947) grants obtained by Vivekanandhan Aravindhan. The Department of Genetics, University of Madras, has received funds for infrastructural support from DST-FIST and UGC-SAP programs. Abbreviations PRRs:Pattern recognition receptors PAMPs:Pathogen associated molecular patterns DAMPs:Damage associated molecular patterns LPS:Lipopolysaccharide TLR:Toll-like receptors NLR:NOD-like receptors RLR:Rig-1-like receptors CLR:C-type lectin like receptors NOD1:Nucleotide-binding oligomerization domain-containing protein 1 RIG-1:Retinoic acid-inducible gene 1 LBP:LPS binding protein sCD14:Soluble cluster of differentiation 14 EndoCAb:Endotoxin core antibody IL:Interleukin TNF:Tumour Necrosis Factor TGF:Tumour growth factor Th:T-helper IR:Insulin resistance CAD:Coronary Artery Disease T2DM:Type-2 Diabetes Mellitus NF-κB:Nuclear factor kappa-light-chain-enhancer of activated B cells IRF:Interferon regulatory factor STAT:Signal transducer and activator of transcription AP-1:Activating protein 1. Disclosure The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the paper. Competing Interests The authors declare that they have no competing interests. Authors' Contributions Vivekanandhan Aravindhan and Haridoss Madhumitha have contributed equally towards doing literature search, formatting figures, and writing the paper. Figure 1 Role of innate immune response in triggering metainflammation associated with DM-CAD. Pattern recognition receptors (PRRs) are the well characterized innate immune receptors which trigger metainflammation following recognition of both pathogen associated molecular patterns (PAMPs) and damage associated molecular patterns (DAMPs). Viral nucleic acids, endotoxins, and peptidoglycans are some of the PAMPS which are released into the circulation following metabolic endotoxemia. Free fatty acids and self-nucleoproteins are some of the endogenous ligands which act as DAMPs. The end result is the activation of NF-κB and IRFs which in turn activate proinflammatory cytokines and type-1 interferons, respectively. These inflammatory mediators destroy pancreatic beta cells leading to insulin deficiency and induce inflammation at insulin target organs leading to insulin resistance (IR) eventually precipitating in Type-2 Diabetes. Long standing diabetes induces systemic inflammation leading to monocyte activation and endothelial dysfunction leading to the extravasation of monocytes and formation of atherosclerotic plaques. Figure 2 Role of adaptive immune response in triggering metainflammation associated with DM-CAD. CD4+T-helper cells are the most well characterized work horses of the adaptive immune system which trigger metainflammation. Inflammation triggered by PRRs is translated to T cells by the APC-T cell interaction which results in the recruitment of these activated cells into pancreases, adipose, liver, and skeletal muscle reinforcing the metainflammation set by PRRs. 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==== Front J Immunol ResJ Immunol ResJIRJournal of Immunology Research2314-88612314-7156Hindawi Publishing Corporation 10.1155/2016/7465741Research ArticleSoluble HLA-G and HLA-E Levels in Bone Marrow Plasma Samples Are Related to Disease Stage in Neuroblastoma Patients http://orcid.org/0000-0002-2849-7595Morandi Fabio 1 * Pozzi Sarah 2 Carlini Barbara 1 Amoroso Loredana 3 http://orcid.org/0000-0003-0528-9563Pistoia Vito 1 Corrias Maria Valeria 1 1Laboratorio di Oncologia, Istituto Giannina Gaslini, Via Gaslini 5, 16147 Genoa, Italy2Centro Cellule Staminali, IRCCS AOU San Martino-IST, Largo R. Benzi 10, 16132 Genoa, Italy3UOC Oncologia, Istituto Giannina Gaslini, Via Gaslini 5, 16147 Genoa, Italy*Fabio Morandi: fabiomorandi@gaslini.orgAcademic Editor: Ban-Hock Toh 2016 16 8 2016 2016 746574120 5 2016 4 7 2016 19 7 2016 Copyright © 2016 Fabio Morandi et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The role of nonclassical HLA-class Ib molecules HLA-G and HLA-E in the progression of Neuroblastoma (NB), the most common pediatric extracranial solid tumor, has been characterized in the last years. Since BM infiltration by NB cells is an adverse prognostic factor, we have here analyzed for the first time the concentration of soluble (s)HLA-G and HLA-E in bone marrow (BM) plasma samples from NB patients at diagnosis and healthy donors. sHLA-G and sHLA-E are present in BM plasma samples, and their levels were similar between NB patients and controls, thus suggesting that these molecules are physiologically released by resident or stromal BM cell populations. This hypothesis was supported by the finding that sHLA-G and sHLA-E levels did not correlate with BM infiltration and other adverse prognostic factors (MYCN amplification and age at diagnosis). In contrast, BM plasma levels of both molecules were higher in patients with metastatic disease than in patients with localized NB, thus suggesting that concentration of these molecules might be correlated with disease progression. The prognostic role of sHLA-G and sHLA-E concentration in the BM plasma for NB patients will be evaluated in future studies, by analyzing the clinical outcome of the same NB patients at follow-up. Fondazione Italiana per la Lotta al NeuroblastomaMinistero del Lavoro, della Salute e delle Politiche Sociali ==== Body 1. Introduction Neuroblastoma (NB) is the most common extracranial solid tumor in children, with an incidence of 1 case per 100.000 children per year, and causes 15% of cancer deaths in pediatric age. NB originates from the sympathetic nervous system, most frequently in the adrenal medulla or the paraspinal ganglia. The causes are unknown, although 1-2% of NB may have a hereditary basis. Different genetic alterations have been characterized in NB, that is, gain-of-function of ALK gene, losses of 11q and 1p, gain of 17q, and amplification of the MYCN gene. NB is heterogeneous, as it may undergo spontaneous remission or evolve to progressive metastatic disease, with dissemination to lymph nodes, bone, bone marrow, liver, skin, and other organs [1]. In particular, BM infiltration is an indicator of poor outcome for NB patients [2]. The International Neuroblastoma Risk Group staging system takes into account genetic alterations, DNA ploidy, histological features, and clinical data, as criteria for defining the risk classes. The prognosis of low/intermediate risk NB patients is favorable, and tumors can be cured by surgery alone or minimal chemotherapy. In contrast, high-risk NB patients' prognosis is poor, in spite of aggressive treatment based on surgery, chemotherapy, radiation therapy, hematopoietic stem cell transplantation, and adjuvant therapy with retinoic acid. In fact, survival rates of these patients at 5 years are less than 50% [3]. In the last years, the role of HLA-class Ib molecules in the progression of NB has been characterized by our group [4–7] and by others [8]. HLA-Ib family includes HLA-G, HLA-E, HLA-F, and HLA-H. In contrast with high polymorphic HLA-Ia molecules (HLA-A, HLA-B, and HLA-C) all these molecules display a limited polymorphism, with few alleles encoding a limited number of functional proteins. Moreover, although HLA-class Ib molecules can bind small peptides and present them to specific CD8+ T cell subsets (similarly to HLA-class Ia counterparts), their main function is the modulation of the immune response in both physiological and pathological conditions [9]. HLA-G and HLA-E are the best characterized among HLA-Ib molecules. HLA-G has seven different isoforms, four membrane bound (namely, HLA-G1, HLA-G2, HLA-G3, and HLA-G4) and three soluble (namely, HLA-G5, HLA-G6, and HLA-G7), that are generated by alternative splicing from the same primary transcript. HLA-G can interact with at least four receptors, namely, immunoglobulin-like transcript (ILT)2, ILT4, KIR2DL4, and CD160, thus affecting the function of different immune effector cells (T and B lymphocytes, natural killer NK cells, dendritic cells, granulocytes, and monocytes) [10]. In contrast, HLA-E can be expressed as membrane bound or soluble isoform (generated through metalloproteases cleavage) and can inhibit CD8+ T cells or NK cells though interaction with CD94/NKG2A heterodimeric receptor. However, HLA-E can also interact with the activating receptor CD94/NKG2C, thus leading to NK cell activation. These interactions are crucial during trophoblast implantation to abrogate NK cell lysis of semiallogeneic fetal tissue and, on the other hand, to activate NK cell functions in the process of tissue remodeling [11]. We have previously demonstrated that soluble (s)HLA-G concentration is higher in plasma samples from NB patients than in controls, and sHLA-G can be released by NB cells themselves, or by monocytes (stimulated by soluble factors secreted by tumor cells). Moreover, high sHLA-G plasma levels correlated with NB patients' relapse [4]. Finally, we have assessed that HLA-G is expressed by metastatic NB cells in the bone marrow from NB patients [6]. Also soluble HLA-E levels are higher in NB patients than in healthy controls. However, we have demonstrated that high plasma levels of sHLA-E at diagnosis correlated with a better overall survival (OS) of NB patients at follow-up, in contrast with sHLA-G [5]. Here, we demonstrated for the first time that sHLA-G and sHLA-E are present also in BM plasma samples derived from either NB patients at diagnosis or healthy donors. Moreover, we have assessed that sHLA-G and sHLA-E levels in BM plasma samples are related to the stage of the disease. Analysis of these patients at follow-up will reveal whether sHLA-G and sHLA-E concentration in BM plasma may predict the clinical outcome of NB patients. 2. Materials and Methods 2.1. Patients and Controls The study was approved by the Ethics Committee of the G. Gaslini Institute, Genoa, Italy. NB patients (n = 31) were diagnosed during 2016 in AIEOP centers. Bone marrow (BM) samples were collected at diagnosis and centralized at Istituto Giannina Gaslini in Genoa, Italy. BM plasma samples were obtained after centrifugation (3000g × 10′). NB patients were staged according to the International Neuroblastoma Staging System [12]. Patients' characteristics, that is, age at diagnosis, sex, MYCN amplification (single copy or amplified), BM infiltration, and stage, are summarized in Table 1. As controls, BM aspirates were obtained from 13 healthy donors, selected according to the Transplant Unit Clinical Protocol of Ematologia 2 at the IRCCS San Martino-IST in Genoa, following a written informed consent at the time of donation. Samples were processed as described in [13], and an aliquot was taken at the end of processing to perform quality control tests, such as CD34+ cell count, in vitro progenitors' cell growth, and sterility. The remaining BM blood sample from this aliquot was subjected to centrifugation (3000g × 10′) to obtain BM plasma. Donor's characteristics are summarized in Table 2. All BM plasma samples were stored at −80°C until use. 2.2. ELISA Enzyme-Linked Immunosorbent Assay (ELISA) for sHLA-G and sHLA-E was performed as previously described [14]. Briefly, MaxiSorp Nunc-Immuno 96-microwell plates (Nunc A/S, Roskilde, Denmark) were coated overnight at 4°C with 1 µg/mL of MEM-G9, specific for HLA-G HC (Exbio, Prague), that recognizes sHLA-G1/G5, or 3D12 mAb, specific for HLA-E HC (eBioscience, Science Center Drive, San Diego, CA, USA). After three washes with PBS 0.05% Tween 20 (washing buffer), plates were saturated with 200 μL/w of PBS 2% BSA (Sigma, St. Louis, MO, USA) for 30 min at RT. One hundred μL of BM plasma samples and serial dilutions of 721.221.G1 cell line supernatant (for HLA-G) or total extract from normal peripheral blood mononuclear cells (standard) were added to each well and incubated at RT for 1 hour. After three washes, 100 μL of detection reagent (HRP-conjugated anti-β2 microglobulin mAb, Exbio, Vestec, CZ) was added, and plates were incubated for 1 hour at RT. After three washes, 100 μL of TMB (substrate for HRP, Sigma) was added, and reaction was stopped after approximately 30 minutes by adding H2SO4 5 N. Absorbance at 450 nm was measured using Infinite® 200 PRO spectrometer (Tecan Group Ltd., Seestrasse, Männedorf, Switzerland). Results are expressed as ng/mL sHLA-G and arbitrary units/mL sHLA-E (1 unit = quantity of sHLA-E in 1 µg of total extract). 2.3. Statistics Normal distribution of data was tested using Kolmogorov-Smirnov test, using Prism software (GraphPad Software Inc., La Jolla, CA). Since data distribution was not normal, differences in plasma levels between (i) patients and controls or (ii) different groups of patients were compared by Mann-Whitney test, using Prism software. Correlations between plasma levels of sHLA-G and sHLA-E were calculated by Spearman's test using Prism software. A p value 0.05 was considered as statistically significant. Significance ranges are the following: ∗ p < 0.05; ∗∗ p < 0.01; and ∗∗∗ p < 0.001. 3. Results 3.1. Soluble HLA-Ib Molecules Are Physiologically Present in BM Plasma Samples First, we have tested sHLA-G and sHLA-E concentration in BM plasma samples from NB patients and healthy donors. As shown in Figure 1(a), sHLA-G concentration was similar between NB patients (median ± SE: 24.69 ± 8.45 ng/mL) and controls (25.16 ± 7.38 ng/mL). In contrast, sHLA-E levels were lower in NB patients (3.72 ± 7.89 U/mL) than in controls (48.01 ± 10.93 U/mL). However, such difference was not statistically significant, likely due to the wide distribution of the results in both groups (Figure 1(b)). Finally, sHLA-G and sHLA-E levels in BM plasma samples from NB patients (r = 0.96, p < 0.0001, Figure 1(c)) and healthy donors (r = 0.92, p < 0.0001, Figure 1(d)) strongly correlated with each other. 3.2. Soluble HLA-Ib Molecules Correlated with Disease Progression We have next analyzed possible correlation between sHLA-G and sHLA-E levels in BM plasma samples and patient's characteristics or clinical parameters. Accordingly, NB patients were divided into two groups on the basis of (i) MYCN amplification (single copy versus amplified), (ii) BM infiltration (not infiltrated versus infiltrated), (iii) age at diagnosis (<18 months versus >18 months), (iv) stage of the disease (stages 1-2 versus stages 3-4), and (v) sex (male versus female). Next, differences in sHLA-G and sHLA-E levels between these groups of NB patients have been evaluated. No significant differences in sHLA-G levels have been detected between NB patients (i) carrying amplified (29.96 ± 13.57 ng/mL) or single-copy (23.65 ± 9.6 ng/mL) MYCN gene (Figure 2(a)) and (ii) presenting (31.17 ± 11.99 ng/mL) or not (21.05 ± 9.91 ng/mL) NB cells infiltrating the BM (Figure 2(b)). In contrast, sHLA-E levels were higher in (i) patients with single-copy MYCN (7.56 ± 9.17 U/mL) than in those with amplified MYCN (1.03 ± 16.2 U/mL) (Figure 2(a)) and in (ii) patients with infiltrated BM (6.45 ± 10.29 U/mL) than in those without BM infiltration (1.86 ± 12.43 U/mL) (Figure 2(b)). However, such differences were not statistically significant. Furthermore, both sHLA-G and sHLA-E levels were similar between patients with an age below (21.05 ± 9.92 ng/mL sHLA-G and 6.45 ± 10.29 U/mL sHLA-E) or above (28.77 ± 11.36 ng/mL sHLA-G and 2.37 ± 12.81 U/mL sHLA-E) 18 months at diagnosis (Figure 3(a)). Notably, no correlation was found between age and sHLA-G or sHLA-E levels in BM plasma samples in healthy donors (data not shown). Both sHLA-G and sHLA-E levels were significantly higher in patients with disease stages 3-4 (32.34 ± 8.08 ng/mL sHLA-G and 13.87 ± 9.42 U/mL sHLA-E) than in those with disease stages 1-2 (0 ± 4.32 ng/mL sHLA-G and 0 ± 3.27 U/mL sHLA-E, p = 0.01 and 0.03, resp.) (Figure 3(b)). Surprisingly, both sHLA-G and sHLA-E levels were found to be higher in male (45.87 ± 12.5 ng/mL sHLA-G and 34.19 ± 14.83 U/mL sHLA-E) than in female (2.52 ± 8.81 ng/mL sHLA-G and 0 ± 8.18 U/mL sHLA-E, p = 0.05 and 0.03, resp.) NB patients (Figure 3(c)). In contrast, healthy donors showed higher levels of sHLA-G and sHLA-E in female (50.74 ± 14.1 ng/mL sHLA-G and 52.25 ± 14.8 U/mL sHLA-E) than in male (12.35 ± 10.98 ng/mL sHLA-G and 11.33 ± 13.25 U/mL sHLA-E) subjects. However, such differences were not statistically significant (Figure 3(d)). 4. Discussion To the best of our knowledge, this is the first demonstration of the presence of sHLA-class Ib molecules HLA-G and HLA-E in BM plasma samples. Previous studies have demonstrated that sHLA-G can be released by some cell populations that are present in the BM environment, such as erythroblasts [15] and mesenchymal stromal cells [16–19]. In contrast, no information is available regarding HLA-E expression and release in the BM. The strong correlation observed between the levels of these two molecules in BM samples either from NB patients or controls suggested that both molecules may be released by the same cell populations, or at least induced by similar stimuli. We have previously demonstrated that metastatic NB cells in the BM expressed high levels of HLA-G on their surface, in contrast with primary tumors, that tested negative for HLA-G [6]. Here, we have demonstrated that both sHLA-G and sHLA-E are present at similar levels in NB patients and healthy donors, thus suggesting that malignant metastatic NB cells are unlikely involved in their release. This observation is further confirmed by the finding that BM infiltration by metastatic NB cells did not affect sHLA-G or sHLA-E levels in BM plasma samples. Moreover, MYCN amplification and age at diagnosis that represent important prognostic factors were not related to sHLA-G and sHLA-E levels in BM, thus further suggesting that these molecules might be released by BM stromal cells or BM resident cell populations instead of NB cells themselves, and may be present in the BM environment in physiological conditions. However, the increased tumor burden might be correlated to a higher release of tumor-derived factor(s) that, in turn, can upregulate HLA-G and HLA-E production by BM stromal cells. The finding that sHLA-G and sHLA-E BM plasma levels are higher in male than in female patients is in line with a previous study on multiple sclerosis, where the authors demonstrated that sHLA-G levels in plasma samples were higher in male than in female patients [20]. However, this study has been carried out using peripheral blood plasma samples, and this is the first demonstration of this difference between male and female subjects in bone marrow plasma samples. Notably, such difference may be a prerogative of NB patients, since sHLA-G and sHLA-E levels were higher in female than in male normal subjects. The most important finding of our study is the demonstration that sHLA-G and sHLA-E levels were significantly higher in BM plasma samples from patients with metastatic disease than in patients with localized NB. This data may suggest that the levels of these molecules in the BM at diagnosis might be associated with disease progression and might be predictive of the clinical course of NB patients. However, this hypothesis can be confirmed only by analyzing the clinical parameters of these patients at follow-up. 5. Conclusions In conclusion, we demonstrated for the first time that soluble HLA-Ib molecules HLA-G and HLA-E are present in BM plasma samples in physiological and pathological conditions, and their concentration correlated with stage disease in NB patients. The prognostic value of sHLA-G and sHLA-E concentration in BM plasma samples from NB patients at diagnosis has to be confirmed in future studies. Acknowledgments This study has been supported by Fondazione Italiana per la Lotta al Neuroblastoma and Ministero del Lavoro, della Salute e delle Politiche Sociali (Progetti di Ricerca Corrente—5 per mille). The authors thank Mrs. Camilla Valentino for excellent secretarial assistance. They also thank Dr. Sebastiano Barco and Dr. Giuliana Cangemi for their collaboration. Competing Interests The authors declare that they have no competing interests. Authors' Contributions Vito Pistoia and Maria Valeria Corrias equally contributed as last author. Figure 1 Levels of soluble (s)HLA-G (a) and sHLA-E (b) have been analyzed in BM plasma samples from NB patients (grey circles) and healthy BM donors (white circles). Horizontal lines indicated medians. Results are expressed as ng/ml (sHLA-G) or arbitrary units (U)/ml (sHLA-E). Correlation between BM plasma levels of sHLA-G and sHLA-E have been analyzed in NB patients (c) and controls (d). Linear regression of data and r and p values are indicated. Figure 2 Levels of soluble (s)HLA-G and sHLA-E in BM plasma samples have been analyzed in patients presenting (grey circles) or not (white circles) MYCN amplification (a) or BM infiltration (b). Horizontal lines indicated medians. Results are expressed as ng/ml (sHLA-G) or arbitrary units (U)/ml (sHLA-E). Figure 3 Levels of soluble (s)HLA-G and sHLA-E in BM plasma samples have been analyzed in patients with age at diagnosis above (grey circles) or below (white circles) 18 months (a) and in patients with stages 3-4 (grey circles) or 1-2 (white circles) disease (b). Differences between female (grey circles) or male (white circles) subjects have been analyzed in NB patients (c) and healthy donors (d). Horizontal lines indicated medians. Results are expressed as ng/ml (sHLA-G) or arbitrary units (U)/ml (sHLA-E). p values are indicated where differences are statistically significant. Table 1 Neuroblastoma patients' characteristics. First row indicates all the variables analyzed in NB patients, second row indicates the subgroups for each variable, and third row indicates the number of subjects in each group. Age at diagnosis (months) Sex MYCN BM infiltration Stage <18 >18 M F s.c. Ampl. Neg. 1+ 2+ 3+ 1 2 3 4 4s 19 12 12 19 22 9 19 5 4 3 6 1 10 12 2 s.c.: single copy; Ampl.: amplified; Neg.: negative. Table 2 Healthy donors' characteristics. First row indicates all the variables analyzed in healthy controls, second row indicates the subgroups for each variable, and third row indicates the number of subjects in each group.  Age (years) Sex Range Mean ± SD M F 20–54 39.6 ± 13 8 5 ==== Refs 1 Pinto N. R. Applebaum M. A. Volchenboum S. L. Advances in risk classification and treatment strategies for neuroblastoma Journal of Clinical Oncology 2015 33 27 3008 3017 10.1200/JCO.2014.59.4648 2-s2.0-84942284390 26304901 2 Morandi F. Corrias M. V. Pistoia V. Evaluation of bone marrow as a metastatic site of human neuroblastoma Annals of the New York Academy of Sciences 2015 1335 1 23 31 10.1111/nyas.12554 2-s2.0-84920407549 25315505 3 Vo K. T. Matthay K. K. Neuhaus J. Clinical, biologic, and prognostic differences on the basis of primary tumor site in neuroblastoma: a report from the International Neuroblastoma Risk Group project Journal of Clinical Oncology 2014 32 28 3169 3176 10.1200/jco.2014.56.1621 2-s2.0-84907582413 25154816 4 Morandi F. Levreri I. Bocca P. Human neuroblastoma cells trigger an immunosuppressive program in monocytes by stimulating soluble HLA-G release Cancer Research 2007 67 13 6433 6441 10.1158/0008-5472.CAN-06-4588 2-s2.0-34447118827 17616704 5 Morandi F. Cangemi G. Barco S. Plasma levels of soluble HLA-E and HLA-F at diagnosis may predict overall survival of neuroblastoma patients BioMed Research International 2013 2013 9 956878 10.1155/2013/956878 2-s2.0-84890082680 6 Morandi F. Scaruffi P. Gallo F. Bone marrow-infiltrating human neuroblastoma cells express high levels of calprotectin and HLA-g proteins PLoS ONE 2012 7 1, article e29922 10.1371/journal.pone.0029922 2-s2.0-84855506127 7 Pistoia V. Morandi F. Bianchi G. Pezzolo A. Prigione I. Raffaghello L. Immunosuppressive microenvironment in neuroblastoma Frontiers in Oncology 2013 3, article 167 10.3389/fonc.2013.00167 2-s2.0-84890810756 8 Lau D. T. Norris M. D. Marshall G. M. Haber M. Ashton L. J. HLA-G polymorphisms, genetic susceptibility, and clinical outcome in childhood neuroblastoma Tissue Antigens 2011 78 6 421 427 10.1111/j.1399-0039.2011.01781.x 2-s2.0-81155144737 22115424 9 Le Bouteiller P. Lenfant F. Antigen-presenting function(s) of the non-classical HLA-E, -F and -G class I molecules: the beginning of a story Research in Immunology 1996 147 5 301 313 10.1016/0923-2494(96)89643-x 2-s2.0-0029744198 8876058 10 Pistoia V. Morandi F. Wang X. Ferrone S. Soluble HLA-G: are they clinically relevant? Seminars in Cancer Biology 2007 17 6 469 479 10.1016/j.semcancer.2007.07.004 2-s2.0-35948961915 17825579 11 Morandi F. Pistoia V. Interactions between HLA-G and HLA-E in physiological and pathological conditions Frontiers in Immunology 2014 5, article 394 10.3389/fimmu.2014.00394 2-s2.0-84918780617 12 Cohn S. L. Pearson A. D. J. London W. B. The International Neuroblastoma Risk Group (INRG) classification system: an INRG task force report Journal of Clinical Oncology 2009 27 2 289 297 10.1200/jco.2008.16.6785 2-s2.0-58249093955 19047291 13 Vicente D. Podestà M. Pitto A. Progenitor cells trapped in marrow filters can reduce GvHD and transplant mortality Bone Marrow Transplantation 2006 38 2 111 117 10.1038/sj.bmt.1705413 2-s2.0-33745752842 16751783 14 Morandi F. Venturi C. Rizzo R. Intrathecal soluble HLA-E correlates with disease activity in patients with multiple sclerosis and may cooperate with soluble HLA-G in the resolution of neuroinflammation Journal of Neuroimmune Pharmacology 2013 8 4 944 955 10.1007/s11481-013-9459-3 2-s2.0-84882246495 23625177 15 Menier C. Rabreau M. Challier J.-C. Le Discorde M. Carosella E. D. Rouas-Freiss N. Erythroblasts secrete the nonclassical HLA-G molecule from primitive to definitive hematopoiesis Blood 2004 104 10 3153 3160 10.1182/blood-2004-03-0809 2-s2.0-8644289450 15284117 16 Montespan F. Deschaseaux F. Sensébé L. Carosella E. D. Rouas-Freiss N. Osteodifferentiated mesenchymal stem cells from bone marrow and adipose tissue express HLA-G and display immunomodulatory properties in Hla-mismatched settings: implications in bone repair therapy Journal of Immunology Research 2014 2014 10 230346 10.1155/2014/230346 2-s2.0-84901022651 17 Morandi F. Raffaghello L. Bianchi G. Immunogenicity of human mesenchymal stem cells in HLA-class I-restricted T-cell responses against viral or tumor-associated antigens Stem Cells 2008 26 5 1275 1287 10.1634/stemcells.2007-0878 2-s2.0-47949099102 18292209 18 Rizzo R. Campioni D. Stignani M. A functional role for soluble HLA-G antigens in immune modulation mediated by mesenchymal stromal cells Cytotherapy 2008 10 4 364 375 10.1080/14653240802105299 2-s2.0-47249127693 18574769 19 Selmani Z. Naji A. Zidi I. Human leukocyte antigen-G5 secretion by human mesenchymal stem cells is required to suppress T lymphocyte and natural killer function and to induce CD4+ CD25highFOXP3+ regulatory T cells Stem Cells 2008 26 1 212 222 10.1634/stemcells.2007-0554 2-s2.0-38349053355 17932417 20 Alsahebfosoul F. Zavaran Hosseini A. Salehi R. Etemadifar M. Esmaeil N. Jamshidian A. Evaluation of soluble human leukocyte antigen-G (sHLA-G) isoforms and regulatory T cells in relapsing-remitting multiple sclerosis Iranian Journal of Allergy, Asthma and Immunology 2015 14 3 298 305 2-s2.0-84929663619

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==== Front ScientificWorldJournalScientificWorldJournalTSWJThe Scientific World Journal2356-61401537-744XHindawi Publishing Corporation 10.1155/2016/7370524Review ArticleHepatitis C Virus in North Africa: An Emerging Threat http://orcid.org/0000-0003-1312-5956Daw Mohamed A. 1 * El-Bouzedi Abdallah 2 http://orcid.org/0000-0001-7542-886XAhmed Mohamed O. 3 Dau Aghnyia A. 4 Agnan Mohamed M. 5 1Department of Medical Microbiology, Faculty of Medicine, Tripoli University, P.O. Box 82668, Tripoli, Libya 2Department of Laboratory Medicine, Faculty of Biotechnology, Tripoli University, P.O. Box 82668, Tripoli, Libya 3Department of Microbiology and Parasitology, Faculty of Veterinary Medicine, Tripoli University, P.O. Box 13662, Tripoli, Libya 4Department of Surgery, Tripoli Medical Centre, Faculty of Medicine, Tripoli University, P.O. Box 82668, Tripoli, Libya 5Department of Pharmacology, Faculty of Medical Technology, Algabal Algarbi University, P.O. Box 3321, Nalut, Libya*Mohamed A. Daw: mohamedadaw@gmail.comAcademic Editor: Anna Linda Zignego 2016 16 8 2016 2016 73705246 4 2016 21 6 2016 19 7 2016 Copyright © 2016 Mohamed A. Daw et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Hepatitis C virus is a major public health threat associated with serious clinical consequences worldwide. North Africa is a unique region composed of seven countries that vary considerably in the predisposing factors to microbial diseases both historically and at the present time. The dynamics of HCV in the region are not well documented. The data are both limited and controversial in most of the countries in the region. In North Africa, the epidemiology of HCV is disparate and understanding it has been hampered by regional “epidemiological homogeneity” concepts. As the dynamics of HCV vary from country to country, context-specific research is needed. In this review, we assess studies performed in each country in the general populations as well as among blood donors and groups exposed to the HCV infection. The reported prevalence of HCV ranges from 0.6% to 8.4% in the Maghreb countries and is predominated by genotype 1. In the Nile valley region, it ranges from 2.2% to 18.9% and is dominated by genotype 4. In North African countries, HCV seems to be a serious problem that is driven by different vectors even in different geographical locations within the same country. Efforts should be combined at both the national and regional levels to implement efficient preventive and treatment strategies. ==== Body 1. Introduction Hepatitis C virus (HCV) is one of the most important viruses. The dynamic nature of the virus, its transmission by various vectors, and the diversity of the subtypes are reflected in the epidemiology of hepatitis C infection. The global prevalence of anti-HCV has been estimated at 2.0% (1.7–2.3%) among adults and 1.6% (1.3–2.1%) for all ages. These percentages mean that there are about 115 million people infected with HVC, of whom about 104 million are adults [1]. The World Health Organization (WHO) recognizes viral hepatitis as a global health challenge from which no country, rich or poor, is spared. As hepatitis C virus infection is not preventable by vaccination, WHO urges member states to take action to improve surveillance, prevention, and access to screening and treatment at the national and regional levels [2]. Hepatitis C virus infection is a major public health concern particularly in African countries, which have the highest prevalence rates of HCV in the world (1–26%) [3]. In Africa over 28 million people are chronically infected with HCV and it is difficult to speculate about current and future trends [4]. The prevalence of HCV varies from one African country to another. Comparison of the epidemiological status in different countries is difficult due to variations in diagnostic procedures, multiplicity of definitions of infection, and the use of different methods, as well as the time at which the epidemiological research was done [5]. Due to the great diversity in prevalence and modes of transmission, accurate epidemiological information on HCV infections is urgently needed to guide national and regional plans for prevention, treatment, and reduction of complications of the infection [6]. Accurate data are scarce for many regions, particularly parts of sub-Saharan and North Africa, partly because the public health importance of HCV infection has been recognized only recently [7]. In North Africa, accurate assessment of the burden of hepatitis C infection is hampered by the lack of adequate surveillance and by poor resources for proper data collection and management. Despite the geographic proximity of these countries and longstanding interaction between them, the prevalence and complications of HCV are greatly different between them. According to current estimates, the lowest prevalence of the virus is in Libya (0.9–1.6%) and the highest is in adjacent Egypt (12.5–26.6%) [8]. This review aims to navigate the reported epidemiology of HCV in the region of North Africa to describe the prevalence of HCV in each country, highlight the predisposing factors, and outline the strategies needed to halt the spread of HCV and its consequences. 2. Geoepidemiological Considerations The North African region houses about 23% of the African population. It is divided into two subregions, the Maghreb (Algeria, Libya, Morocco, Tunisia, and Mauritania) and the Nile valley (Egypt and Sudan). Egypt is a transcontinental country because its Sinai Peninsula lies in western Asia. North Africa also includes a number of Spanish possessions (Ceuta and Melilla, part of coast of Morocco). Despite the similarities between these countries in environment, population genetics, social customs, and habits, they differ greatly in the infrastructure of their healthcare systems, per capita income, level of urbanization, and degree of poverty. Their populations vary from poor nomadic Bedouins scattered in the Sahara areas of Mauritania, Algeria, Morocco, and Sudan to sheltered valleys in the Atlas Mountains, the Nile Valley, and delta, up to urbanized cities on the Mediterranean coast such as Tripoli and Benghazi. Epidemiological information on HCV among these populations is fragmentary and obtaining more information is hampered by poverty, ignorance, and more recently uprisings and conflicts [9]. With the exception of Libya, Egypt, and Morocco, North African countries lack adequate surveillance studies on hepatitis C virus to enable them to take evidence-based policy decisions [10–12]. Their data are outdated, aggregated, or limited to small specific populations and affected by selection bias because most of their studies are generally based on risk groups or blood donors, and information on children and the elderly is generally not included [10, 13]. In North Africa, predisposing factors and epidemiological information on HCV vary significantly from one country to another. Moreover, there is considerable variation in the economic and demographic situations in these countries (Table 1). Therefore, the assumption of “epidemiological homogeneity” cannot be easily adopted because it may lead to inaccurate estimates of HCV seroprevalence in these countries [14]. Hence then, the epidemiological features of HCV in each country should be considered separately. The region's contribution to the global literature on HCV remains relatively small, though the number of publications from Egypt, Libya, and Morocco has increased. Figure 1 shows the prevalence of HCV and genotype distribution in all the North African countries. 3. Epidemiology of HCV in the Maghreb Region 3.1. Libya Libya is the richest country in North Africa. It is also the second largest and has a small population. HCV is well documented in this country and major studies were carried out on all aspects of HCV infection over the last 20 years [15]. The largest comprehensive national study in Asia and Africa was carried out in Libya and covered over 1% of the total population [11]. The overall prevalence rates of HCV in males and females were similar (1.1% and 1.3%, resp.). The mean age of anti-HCV-positive individuals was 31.7 ± 18.4 years in females and 35.6 + 20.9 years in males. The mean age of HCV-positive individuals was significantly higher than that of anti-HCV negative individuals for both males (almost 10-year difference) and females (7-year difference). HCV was more prevalent among single and younger individuals, and about 40% of HCV patients were less than 30 years old. The prevalence of HCV was higher among illiterate individuals (3.1%) than among literate persons (0.9–1.1%). Hepatitis C was most prevalent among intravenous drug users (7.4%) and less prevalent but still substantial in those undergoing blood transfusion (2.7%), surgical operation (2.3%) or hospital admission (1.9%). The prevalence of HCV infection in Libya varied widely between hemodialysis centers from 0% to 35.9%. Compared to seronegative patients, seropositive patients were younger and had been receiving dialysis for substantially longer. Follow-up showed that 7.1% of the dialysis patients seroconverted during the first year of dialysis [16]. A total of 20 discrete genotypes and subtypes were identified countrywide in the Libyan population, and their frequencies ranged from 11.5 to 0.3% among Libyan HCV patients. Genotype 4 was the most frequent among all regions (19.7–40.5%), reaching the highest value in eastern region (27%), followed by genotype 1 which was more prevalent in the southern (49.3%) and western (40.0%) regions. Genotype 3 was more prevalent in Tripoli area (21.3%) and the eastern regions (15.9%), while genotype 2 was common in the northern (23.6%) and southern (22.5%) regions [17, 18]. The frequencies of these genotypes were significantly associated with the demographic and risk factors involved. Transmission by intravenous drug use (IVDU) has become more frequent in Libya and is associated mostly with genotype 1 (49.2%) and genotype 3 (32.6%). 3.2. Tunisia Tunisia has the smallest area among the Maghreb countries and is bounded by the two largest countries in the region, Libya and Algeria. Different studies were carried out on HCV infection in Tunis. Two decades ago, Triki et al. studied the prevalence of hepatitis B and hepatitis C and delta virus infections in Tunis in a population of mainly male military recruits aged 20–25 years [19]. The overall prevalence of HDV/HCV coinfection was 17.7% but it was low for HCV alone (2.7%). In 2005, another study reported a prevalence of HCV of 1.7% in the general population and great heterogeneity in geographical distribution. HCV was particularly more prevalent in the northwestern region of the country than anywhere else. But there was no difference in positivity according to gender or to living in rural versus urban areas; the only significant risk factor was advanced age [20]. Similar results were reported for blood donors and diabetic patients, in whom prevalence of anti-HCV antibodies varied between 0.5% and 1.8% [21]. However, these studies suffer from lack of specificity and were confined to certain populations. They did not accurately mirror the status of HCV within the country. A recent seroprevalence study of transfusion-transmitted infections in first-time volunteer and replacement donors in Tunisia showed that HCV, according to mathematical adjusted model, reached 1.9% (95% CI = 0.9–4.1 P = 0.11) [22]. Hence, further studies are needed to assess the actual burden of CV infection in Tunisia. The prevalence of HCV infection among Tunisian dialysis patients was reported to be high, reaching up to 51%. There was a close correlation between the number of anti-HCV-positive patients and the duration of dialysis therapy [23, 24]. This indicates the nosocomial transmission of HCV in dialysis units where the number of infected patients is high and where the management of material does not take into account the patient's viral status. The reported genotype patterns among Tunisians vary substantially from one study to another. Subtype 1b was the most common (79%), whereas types 1a, 2a, 2b, 3a, and 4a occurred much less frequently. Furthermore, subtype 4k seems to have disappeared in Tunis city in conjunction with the emergence of a new subtype of HCV4 [25, 26]. 3.3. Algeria Algeria is the largest country in North Africa and its population lives a range of traditional/rural or modern/urban lifestyles. Data on the epidemiology of HCV in Algeria are scarce. Official data point to a current hepatitis C epidemic [27], and the Algerian Ministry of Health estimated that the prevalence of HCV infection had reached 2.5% [28, 29]. Seroprevalence rates of HCV reaching 53% were reported in patients undergoing hemodialysis and 31.6% among hemophilia patients in Algeria. This situation is plausibly connected with nosocomial transmission and occupational exposure to HCV among healthcare workers [29]. In a rare retrospective study, Rouabhia et al. investigated hepatitis C virus markers in 739 diabetic and 580 nondiabetic patients attending the internal medicine department of the University Hospital Center of Batna in Algeria [30]. Anti-HCV seropositivity was 17.5% in diabetic patients and 8.4% in nondiabetic patients (P < 0.01). However, after adjustment for age, this difference is statistically significant only in patients aged 40–65 years (22.2% versus 9.3%, P = 0.024). Despite the ongoing controversy being whether diabetes mellitus is a risk factor for HCV infection or HCV is a risk factor for type 2 diabetes mellitus, the prevalence of HCV among healthy Algerian in this age group is indeed high (8.4–9.3%) [30]. In Algeria, HCV genotype 1 was the most frequent (88.7%), followed by genotypes 2 (8.5%), 4 (1.1%), 3 (0.9%), and 5 (0.2%). The genotype distribution was related to age and region. Genotype 1 was significantly less frequent in the ≥ 60-year age group than in younger people (OR = 0.2; 95% CI: 0.1–0.5, P < 0.001) [27, 30]. Furthermore, genotype 1 was more frequent in the central part of the northeastern region of Algeria than elsewhere. 3.4. Morocco Morocco is the western bounding arm of the Maghreb region, facing both the Atlantic Ocean and the Mediterranean Sea. Different studies were carried out on HCV in Morocco both in the general population and on higher risk groups. Early studies estimated that the prevalence of HCV was 1.93% in the general population and 1.08% in blood donors [31]. A recent nationwide cross-sectional survey carried out in 100 major Moroccan regions over a period of six years showed that the overall prevalence of HCV infection in the general population was 1.58%, and it was lower among blood donors [10]. The prevalence was higher among males ≤ 30 years old. Factors significantly associated with HCV infection were increasing age, dental treatment, use of glass syringes, and history of surgery. Emerging data suggest that differences in anti-HCV prevalence may exist between the northern and southern regions in Morocco [32]. HCV is a major problem in hemodialysis centers in Morocco. A multicenter study covering different Moroccan dialysis centers found that the prevalence varied from 11% to 91% [33]. Practitioners of traditional medicine and barbers play an important role in the spread of HCV in Morocco. A survey of anti-HCV antibodies among barbers and their clients indicated that the prevalence rate hovered above 5%, probably because of unsanitary conditions [34]. This problem could also exist in Libya, where most of the hairdressers are Moroccans. Drug addiction is a serious problem in Morocco and has been considered to be a “male-associated habit” because the overwhelming majority of drug addicts are young males who are either single or divorced. HCV seroprevalence is high among this group, reaching up to 60% [35]. The commonly reported HCV genotypes in Morocco were genotypes 1 (46%) and 2 (40%), followed by genotypes 3 and 4. Among intravenous drug users, genotype 1 accounted for 65% of the cases, followed by genotype 3 (26%) and genotype 4 (10%) [36]. 3.5. Mauritania Mauritania is a Saharan country characterized by a very high prevalence of viral hepatitis that poses a serious public health problem. In a recent coherent study, up to 20% of consulting patients and pregnant women or blood donors have HBV, and up to 33% have HDV [37]. Despite the limited published data on HCV in Mauritania, HCV seems to be more prevalent in Mauritania than in other Maghreb countries. Mansour et al. conducted a comprehensive prospective study on 1966 individuals and showed that the overall prevalence of HBsAg was 18.3%. The prevalence was significantly higher in males (24.4%) than in females (13.8%) [P < 0.001; OR: 2.04 (1.46–2.85), P < 0.001]. It varied significantly among the different ethnic groups: 22.7% in white Moors, 19.7% in black Moors, and 12% in African ethnicities [P < 0.025, OR: 0.47 (0.26–0.82), P < 0.008] for the comparison between White Moors and other African ethnic groups [38, 39]. The characteristics of individuals positive for HBsAg strongly suggest healthcare-associated transmission, intrafamilial transmission, sexual transmission, more frequently a history of hospitalization, and transmission through iatrogenic, medical, or paramedical procedures. In 2000, 2854 healthy blood donors were screened for HCV antibodies at the National Hospital of Nouakchott, and the prevalence of HCV was found to be 2.7%, but no risk factors were studied [40, 41]. However, it has been speculated that the prevalence of HCV in Mauritania may be as high as 10.7%, similar to that in West African countries [8]. 4. Epidemiology of HCV in the Nile Valley Region HVC prevalence in the Nile Valley region has unique features and specific epidemiological characteristics that have implications for the prevention and future prospects of HCV in the region. 4.1. Egypt Egypt is confronted with a huge HCV infection problem that distinguishes it from the rest of North Africa. It has the highest prevalence of HCV in the world, and HCV infection and its complications are among the leading public health challenges in the country [40]. The epidemiological and clinical status of HCV in Egypt is well known and different studies were carried out to examine the different aspects of this epidemic [41]. Data on HCV in Egypt are diverse and vary greatly from one study to another. Nevertheless, they all reach the same conclusion that the prevalence of HCV is very high among all groups and populations [42, 43]. A major survey conducted in 2008 reported a HCV prevalence of 14.7% in a nationally representative sample of 11,126 Egyptians aged 15–59 years. The infection rate increased steadily with age. It was nearly zero in children under the age of 9 years, 5% among those aged 30–39 years, and 10% among those aged ≥ 50 years [12]. The study also showed that rural villages had a higher prevalence than urbanized cities [44]. Studies conducted in the Nile delta region, Assuit and Benha, showed a higher prevalence among all sectors studied, including pregnant women and children [45]. Overall, the average HCV prevalence among risk groups is even higher. It was reported to be 38% among schistosomiasis patients, 63.0% among intravenous drug users, and 46.1–100% among hemodialysis patients. Population groups at an intermediate risk of exposure include diabetic patients, hospital outpatient attendees, hospitalized patients, household contacts of index cases (HCV-positive cases), patients with sexually transmitted infections, patients with periodontal disease, prisoners, and healthcare workers [46, 47]. HCV genotype 4 (subtype 4a) predominates in Egypt and is responsible for > 90% of the infections; the rest of the infections are due to genotype 1 (1b, 1g) and genotype 3 (3a) [48]. Recent data show that the overall prevalence of HCV in Egypt is declining as those who were initially infected are aging and dying. However, the disease burden of HCV and associated costs will continue to grow due to the increasing number of individuals developing advanced liver disease and dying from liver pathologies related to HCV rises [49]. 4.2. Sudan Sudan is the largest country in the Nile valley with a land mass about the size of Europe. It has been engaged in an ongoing civil war for 20 years, and one of the consequences is about 4 million refugees [50]. The Sudanese community is characterized by great social and demographic diversity reflected in the epidemiology of microbial diseases in the country. Studies on HCV in Sudan are few and lack specific national goals. The few studies on HCV infection in Sudan demonstrated a seroprevalence ranging from 2.2% in the Gezira state, in which schistosomiasis is endemic, to 4.8% in patients with schistosomal periportal fibroses [51]. The prevalence of HCV infection among asymptomatic male Sudanese blood donors was 4.4%, but females do not donate blood in Sudan. Other studies reported prevalence rates of 3% and 1.5% in southern and northern regions of Sudan, respectively. Furthermore, HCV transmission was evident in healthcare settings, and occupational risk is expected to be high. In presurgery screened patients in Khartoum, central Sudan, prevalence of HCV was 2% [52]. Unprotected sexual activity (20%) was the most apparent predisposing risk factor for HCV seroreactors, followed by razor sharing (13.3%), parenteral drug injection (10%), tattooing, and surgical procedures. The highest prevalence of HCV infection in Sudan was noted in patients with end-stage renal disease who were on regular hemodialysis (seroprevalence of 66.7%) [52, 53]. Major risk factors for infection were longer duration of dialysis, dialysis in multiple centers, and an age over 30 years. Genotype 4 was the most frequently isolated genotype among HCV-positive patients in Sudan [53]. Studies on the HCV status among intravenous drug users and HIV patients in Sudan are lacking. Recently, Sudanese researchers raised the importance of this issue, particularly as Sudan borders nine African countries on the east and the south that have some of the highest HIV-1 infection rates in the world [54]. The HCV status in Sudan is not well documented, particularly for high risk groups and in healthcare settings. Further studies are urgently needed, including but not limited to population-based studies that are representative of entire communities, and a national cooperative registry system should be established. 5. Vectors of HCV Transmission in the North Africa 5.1. Drug Trafficking Drug trafficking poses specific problems for North African countries, and it is exacerbated by the geographical location and the vast area of the region. Morocco is the world's foremost producer of cannabis resin and remains the main source of the drug for the consumer markets in Western Europe; the largest seizure in 2007 was in Mauritania [55, 56]. Studies from the Middle East and North Africa regions indicate that after Iran, the largest numbers of people injecting drugs are in Egypt and Algeria [57]. Illicit drug injection is also a significant route of HIV transmission in Libya and Tunisia, as well as in Sudan. Cocaine use is reportedly increasing in these countries, but cocaine injection has not been reported. Use of noninjectable drugs has not been shown to be linked to the transmission of HIV or HCV. Information on HCV prevalence among people who inject drugs is not available for most countries in the region, but, where reported, the data reveal high levels of HCV infection [58]. Furthermore, men who have sex with men and people who inject drugs are both highly criminalized populations in region and they are more affected by HCV and HIV than the rest of the population [59]. 5.2. Urbanization Level Urbanization has contributed to an overall improvement of health status [60]. Different studies have shown that the level of urbanization could influence the prevalence of HCV in the North African region. Libya, which is considered an urbanized country, has the lowest HCV prevalence. The other countries are mainly rural and are not expected to pass the urban tipping point before 2050 [61]. Sociodemographic studies comparing rural with urban Egyptian populations have shown a higher prevalence among rural populations [62]. Blood donors and children from rural areas had a higher prevalence of HCV than those from urban areas [63]. Similar results were reported for hepatocellular carcinoma in rural and urban areas [48]. The same pattern was reported in Tunisia, Algeria, and Morocco. HCV prevalence was significantly higher in the northwestern region of Tunisia and the suburban area of Tunis than in the northern region. In Algeria, HCV infection was strongly associated with living in remote mountains or desert regions as compared to living in urbanized environments along the Mediterranean coast [27]. In Morocco, being a rural resident was found to be strongly associated with HCV infection. In Mauritania and Sudan, the vast majority of the population is composed either of rural dwellers or Bedouins even within the surroundings the capital cities. This could be attributed to the habits and economic status of this major subpopulation. Lack of sanitary services, illiteracy, traditional medicine practice, and occupational hazards and not adopting safe medical practices may contribute to higher levels of HCV infection. However, further studies are needed to verify this assumption. 5.3. Medical Practices and Personal Habits Hemodialysis, blood transfusion, and practices associated with hospital care, combined with social or personal habits and other community-associated factors, are among the most important risk factors for HCV in North African countries. Mortality and morbidity due to infections associated with such factors are expected to be high, and the adjusted hazard ratio for patient death may reach 2.3 [64]. The prevalence of HCV infections observed in blood products and dialysis patients in these countries are much higher than in the general population. This situation is worsened in areas of chronic conflict, such as Sudan and the Sahara region, as well as in regions newly gripped by war, notably Libya, in which blood supplies were safer and more secure before the 2011 uprising. Tunisia and Libya experienced stock-outs during their recent uprisings both for blood screening reagents and for access to new antiretroviral drugs. The impact of these conflicts on the healthcare system should be evaluated [65]. Healthcare workers should be sufficiently informed about the risk of acquiring HCV via sharp injuries and other nosocomial routes. Habits and cultural factors that may influence the spread of HCV in North African countries include male and female circumcision, particularly in Egypt, Sudan, Mauritania, and Morocco. Hijiama (bloodletting) done by informal practitioners, tattooing, folk body piercing and threading, sharing hygiene tools and sharp items, and the use of communal barbers may be considered as risk factors for HCV, particularly among rural dwellers [21, 34]. Education and public awareness campaigns are needed to teach the populations about the risks involved. 5.4. HCV/HIV Coinfection There is little information on HCV/HIV coinfection in North African countries. The paucity of information on injecting drug use and HIV in these countries could be attributed to the reluctance to commission research or publicize information on these two highly stigmatized issues, and such avoidance could mask the true extent to which people who inject drugs are affected by HIV [66]. The reported prevalence rates of HCV/HIV coinfection vary depending on the route of transmission. Morocco is the only country in the region that has reliable surveillance programs for HIV. Prevalence of HIV/HCV coinfections in Morocco was reported to be about 20% among injecting drug users and sex workers, but it was 10.6% among patients of different socioeconomic backgrounds [35]. Women have already overtaken men in their contribution to the HIV epidemic in Sudan, Algeria, and Tunisia, where the number of AIDS cases is higher in women than in men. In Morocco, the situation is becoming increasingly feminized [67]. A study carried on 4220 female sex workers aged 15–49 years recruited from 14 states in Sudan indicated that the prevalence of HIV ranged from 4.4 to 23.9%, with 6% coinfected with HCV [67]. In Tunisia, the prevalence rate of anti-HCV positivity was 40% among HIV-infected patients, of whom 78% were injecting drugs. In Libya, over 90% of HIV cases are attributable to injecting drugs. A population-based study in nine districts in Tripoli showed that the average prevalence rates of HIV reached 0.2%, whereas HBV and HCV rates reached 3.7% and 0.9%, respectively [68]. In Egypt, the rate of HIV infection among female sex workers was much higher (up to 36.3%) than among women who do not sell sex [69]. Furthermore, a randomized detailed survey in 2010 found that 6.8% of intravenous drug users in Cairo and 6.5% in Alexandria were infected with HIV [70]. HCV coinfection among these populations ranged from 37 to 86% in Egypt. The coemergence of HCV in HIV infected patients has become a serious problem in the North African region: effective preventive and monitoring programs have to be implemented [70]. 5.5. Miscellaneous Factors Various other factors could contribute to the epidemicity of HCV in North Africa, including imprisonment, alcoholism, and sex practices, which are stigmatized socially and culturally. The situation is exacerbated by lack of human rights, injustice, and the recent political uprisings in this region. More than a third of all prisoners and more than 80% of injecting drug users were positive for antibodies to hepatitis C virus in North African countries [13]. Libya is the only country in the region for which there is an available estimate of the number of prisoners with a history of injecting drug use (approximately 60%) [71]. Alcohol drinking and female sex work are other factors in North African countries. Alcohol consumption accelerates the course of chronic hepatitis C. In Mauritania and Libya alcohol consumption and prostitution are banned according to Islamic laws. Recorded alcohol consumption rates are variable across North Africa. Sudan has low levels of alcohol consumption. On the other hand, Morocco, Egypt, Algeria, and Tunis have higher consumption rates [56, 72]. HCV and other associated sexually transmitted diseases are rarely studied in North African countries, leaving only hypothetical speculation. The only formulated and well planned study was done in Sudan [67]. Biobehavioral surveys using respondent-driven sampling were carried out among female sex workers in the capital cities of 14 states in Sudan in 2011-2012. The findings point to a high burden of sexually transmitted diseases in female sex workers [67]. The highest prevalence of HCV was found in the western zone (2.6% and 5.1% at two sites). However, there is little information on the prevalence of HCV among injection drug users. Hence, further studies are needed. 6. Consequences of HCV in North Africa Hepatitis C infection has been implicated in the development of hepatocellular carcinoma (HCC) in North African countries. A multicenter study of the risk factors for hepatocellular carcinoma was carried out in cooperation between Morocco, Algeria, and Tunisia. The study showed that over 60% of HCC patients were positive for anti-HCV, though only 17.9% and 19% were positive for HBsAg or had diabetes, respectively [73], A33-fold higher in HCV infection comparable by just 10-fold for HBV. However, the association was mainly for HCV genotypes 1 and 2. Egypt had by far the highest burden of deaths from HCV-associated HCC, and 63.3% of all HCV-associated HCC deaths occurred in Egypt (Figure 2(a)), followed by Morocco, Sudan, and Algeria. The figures were lower for Libya and Tunisia. Mauritania and Egypt also had the highest age-standardized rates deaths (ASDR) for HCV-associated HCC in both males and females (Figure 2(b)) [74]. There is no easy and effective treatment for HCC, so preventing the transmission of hepatitis viruses is the most important step to reduce the risk of HCC in these countries. Extrahepatic diseases also cause morbidity among HCV-infected individuals. Patients with chronic hepatitis C have a higher risk of developing diabetes, thyroid disease, lichen planus, and an array of neuropsychiatric disorders [75, 76]. These conditions are rarely studied in the region of North Africa. Though the rates of HCV infection are declining, particularly in Libya and Egypt, the decline has not yet met the expectations. Forecast studies are rarely done in North Africa. In Libya, Daw and his collaborators designed a mathematical model based on data collected from blood donors to predict the future status of HCV in the country [77]. The data show a stationary phase of HCV prevalence in the coming ten years. If preventive measures are applied, the prevalence will become very low within 50 years (Figure 3(a)). In Egypt, strategies have been built to increase diagnosis and treatment. Coupled with measures to prevent transmission, the result would be to control the disease and markedly reduce the prevalence and burden of HCV in the country by 2030 (Figure 3(b)) [78]. 7. Conclusion North African countries face a serious hidden crisis of HCV infections complicated by ignorance and inefficiency of public healthcare services and coupled with lack of research studies and programs for monitoring HCV infection. Countries such as Mauritania, Algeria, and Sudan should expand their efforts to address the emerging HCV epidemic among their populations. A multifaceted approach is needed. Regional and national guidelines for screening, treating, and preventing HCV infection should be endorsed and adopted by healthcare authorities and providers. Infected individuals and those who are at a higher risk should be provided with easy access to healthcare services. Implementation of advanced research and strengthening the practices of data collection and reporting of HCV infections should be given priority in the region of North Africa [79, 80]. Acknowledgments The authors are deeply grateful to the Libyan Study Group of Hepatitis & HIV and to the Department of Medical Microbiology and Immunology, Faculty of Medicine, Tripoli, Libya, for their assistance, and particularly those who helped to analyze and critically review the data published here. Special thanks go to Dr. Amin Bredan, http://www.theeditor.be/, for his professional editing of the paper. Disclosure This research was done in association with the Libyan Study Group of Hepatitis & HIV. Competing Interests The authors declare that they have no conflict of interests. Authors' Contributions All the authors contributed substantially to the study and read and approved the final paper. Figure 1 Geographic distribution of HCV genotypes among HCV-infected individuals in North Africa. G1, G2, G3, G4, and G5 refer to the respective genotypes of HCV. Figure 2 Mortality from HCV-associated hepatocellular carcinoma in North Africa. Figure 3 The impact of prevention and treatment on future prevalence rates of HCV. Modeled prevalence of hepatitis C virus infection Libya and Egypt. A: number of HCV-infected cases. B: number of cases after prevention. C: number of cases after prevention and treatment. Table 1 Prevalence of HCV, development parameters, and genotype distribution in North African countries.   Maghreb region Nile region Countries Libya Tunis Algeria Morocco Mauritania Egypt Sudan Population (millions) 6.42 11 35 32 3.5 82.5 44.6 Population density (people/km2) 04 71 16 76 04 90 22 Literacy rate (M; F) 99.95% (99.97; 99.93) 98.06% (98.35; 97.76) 95.59% (95.65; 95.52) 83.19% (90.10; 75.87) 62.63% (70.04; 54.98) 91.12% (93.42; 88.73) 89.57% (91.29; 87.81) GNI (PPP US$) 16020 3720 4420 2770 2400 6120 2120 HDI (2010–2014) 0.849 0.712 0.736 0.628 0.453 0.644 0.408 Country classification HI LMI LMI LMI LI LMI LI Prevalence of HCV genotypes & subtypes               1 35% 67% 89% 68% ? 5% 5% 1a 1a 1a 1a 1a   — — 1b 1b 1b 1b 1b   — — 2 14.2 13% 9% 30% ? 2% 3% 2a 2a 2a 2a, 2b 2i, 2k   — — 3 15% 3% 1% — ? — — 4 29.2% 21% 1% — ? 80% 90% 4a 4a 4a 4a —   4a 4a 4k 4k 4k 4c, 4d — ? 4k —               — 5 0.2% — — — ? — — GNI, gross national income. PPP, purchasing power parity. 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Extrahepatic disease manifestations of HCV infection: some current issues Journal of Hepatology 2004 40 2 341 352 10.1016/j.jhep.2003.10.009 2-s2.0-1642491767 14739110 76 Zignego A. L. Ferri C. Pileri S. A. Caini P. Bianchi F. B. Extrahepatic manifestations of Hepatitis C Virus infection: a general overview and guidelines for a clinical approach Digestive and Liver Disease 2007 39 1 2 17 10.1016/j.dld.2006.06.008 2-s2.0-33845968066 16884964 77 Daw M. A. Shabash A. El-Bouzedi A. Dau A. A. Habas M. Libyan-Study-Group-of-Hepatitis-and-HIV Modelling the prevalence of hepatitis C virus amongst blood donors in Libya: an investigation of providing a preventive strategy World Journal of Virology 2016 5 1 14 22 10.5501/wjv.v5.i1.14 26870670 78 Waked I. Doss W. El-Sayed M. H. The current and future disease burden of chronic hepatitis C virus infection in Egypt Arab Journal of Gastroenterology 2014 15 2 45 52 10.1016/j.ajg.2014.04.003 2-s2.0-84905232893 25097045 79 Daw M. A. El-Bouzedi A. 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==== Front Case Rep UrolCase Rep UrolCRIUCase Reports in Urology2090-696X2090-6978Hindawi Publishing Corporation 10.1155/2016/5237387Case ReportSevere Hypotension, Hypoxia, and Subcutaneous Erythema Induced by Indigo Carmine Administration during Open Prostatectomy http://orcid.org/0000-0003-2665-5964Nandate Koichiro 1 * Voelzke Bryan B. 2 1Department of Anesthesiology and Pain Medicine, Harborview Medical Center, University of Washington, 325 Ninth Avenue, P.O. Box 359724, Seattle, WA 98104-2499, USA2Department of Urology, Harborview Medical Center, University of Washington, 325 Ninth Avenue, P.O. Box 359868, Seattle, WA 98104-2499, USA*Koichiro Nandate: knandate@uw.eduAcademic Editor: Giorgio Carmignani 2016 16 8 2016 2016 523738728 4 2016 4 7 2016 Copyright © 2016 K. Nandate and B. B. Voelzke.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Indigo carmine (also known as 5,5′-indigodisulfonic acid sodium salt or indigotine) is a blue dye that is administered intravenously to examine the urinary tract and usually is biologically safe and inert. Indigo carmine rarely may cause adverse reactions. We treated a 66-year-old man who had general anesthesia and radical retropubic prostatectomy for prostate cancer. He had a previous history of allergy to bee sting with nausea, vomiting, and dizziness. Within 1 minute after injection of indigo carmine for evaluation of the ureters, the patient developed hypotension to 40 mmHg, severe hypoxia (the value of SpO2 (peripheral capillary oxygen saturation) was 75% on 40% inspired oxygen concentration), poor air movement and bilateral diffuse wheezing on auscultation, and marked subcutaneous erythema at the upper extremities. After treatment with 100% oxygen, epinephrine (total, 1.5 mg), hydrocortisone (100 mg), diphenhydramine (50 mg), albuterol nebulizer (0.083%), and continuous infusion of epinephrine (0.15 μg/kg/min), the vital signs became stable, and he recovered completely. In summary, indigo carmine rarely may cause life-threatening anaphylactic or anaphylactoid reaction that may necessitate rapid treatment to stabilize cardiovascular, hemodynamic, and pulmonary function. ==== Body 1. Introduction Indigo carmine (also known as 5,5′-indigodisulfonic acid sodium salt or indigotine) is a blue dye that has been used since the early nineteenth century to localize the ureteral orifice and identify severed ureters and urinary fistulas [1]. Although usually safe for clinical use, indigo carmine occasionally may induce severe hypertension and bradycardia, possibly by stimulation of alpha receptors. Hypertension after indigo carmine injection may occur possibly because of the common chemical structure between indigo carmine and the neurotransmitter serotonin (5-hydroxytryptamine). Serotonin directly causes vasoconstriction and positive inotropic effects mediated through the alpha-adrenergic receptor. Therefore, administration of indigo carmine may increase total peripheral resistance, resulting in elevated blood pressure followed by a bradycardic reflex [2–4]. In addition, catastrophic adverse reactions after intravenous administration of indigo carmine have been reported, including critical hypotension and anaphylactic reaction, but the pathologic mechanism is unknown [5–7]. We treated a patient who had anaphylactic reaction after an intravenous injection of indigo carmine during radical retropubic prostatectomy. This reaction is not new and has been already reported. However, it is worthwhile being reported again to warn anesthesiologists, urologists, and gynecologists of life-threatening reaction by indigo carmine. 2. Case Presentation A 66-year-old man presented with prostate cancer. He did not have either any major medical problems including cardiovascular or respiratory diseases, history of surgical procedure, or exposure of indigo carmine. He had a history of allergic reaction to bee stings associated with nausea, vomiting, and dizziness, which had been treated in the emergency department. He was scheduled to undergo elective radical retropubic prostatectomy with pelvic lymph node dissection under general anesthesia. After induction of general anesthesia with midazolam, fentanyl, and propofol, muscle relaxation was achieved with rocuronium, and the trachea was intubated. An arterial line and 2 large intravenous catheters were placed, according to our routine for patients undergoing radical prostatectomy. No unusual events were noted during general anesthesia induction and preparation for the surgery. There were no issues during the operation until the surgical team requested the anesthesia team to give 5 ml of indigo carmine (0.8% sodium indigotindisulfonate USP solution, America Regent Company, Shirley, NY, USA) intravenously to ensure that neither ureter was injured during prostatectomy. By this time, estimated surgical blood loss was 1500 mL, and the patient had been given 2 units of red blood cells, 3500 mL crystalloid, and low doses of vasopressors (phenylephrine 0.1 microgram/kg/min) to stabilize the vital signs. Hematocrit was 31%. Within 1 minute after administration of indigo carmine, the vital signs deteriorated suddenly. Systolic blood pressure dropped from 110 to 40 mmHg, but the heart rate remained at 60 beats/min. The patient became hypoxic (oxygen saturation decreased from 99% to 75% on 40% inspired oxygen concentration). Auscultation showed poor air movement and bilateral diffuse wheezing. Marked cutaneous erythema was observed at the upper extremities. The anesthesia team requested the surgical team to suspend surgery temporarily until the patient became stable. The patient immediately was given 100% oxygen, epinephrine (total, 1.5 mg), hydrocortisone (100 mg), diphenhydramine (50 mg), albuterol nebulizer (0.083%), and continuous infusion of epinephrine (0.15 μg/kg/min), and the vital signs became stable. Emergency transesophageal echocardiography was performed, and there was no evidence of myocardial infarction or pulmonary embolism. The diagnosis of anaphylactic reaction due to indigo carmine was made on the basis of the sudden decrease in blood pressure, respiratory problems, and subcutaneous lesions immediately after the administration of indigo carmine. After the vital signs were stabilized, the surgery was resumed and completed uneventfully. The patient remained on a continuous infusion of epinephrine (0.1 μg/kg/min) and was transferred to the surgical critical care unit for close monitoring without emerging from general anesthesia. The patient was released from the critical care unit to the ward after 48 hours and discharged from the hospital on postoperative day 7 without any further complications. During the patient's stay in the hospital, we seriously considered investigating the serum activity of tryptase, histamine, and immunoglobulin E but could not achieve the patient and the family agreement. 3. Discussion The present patient had an anaphylactic reaction, manifested by hypotension, hypoxia, bilateral wheezing, and subcutaneous erythema, after intravenous injection of indigo carmine. In a previous report of 4 patients who were treated within 6 weeks for severe hypotension, none of the patients had a history of allergy, previous exposure to indigo carmine, or anaphylactic signs such as cutaneous erythema, laryngeal edema, or bronchospasm; the authors were unable to link the hypotensive reaction to an anaphylactic reaction and warned about the possibility of drug lot impurity [5]. We examined the lot impurity of indigo carmine which we gave to the patient but it was far before the expired date. In two other previous case reports, the marked hypotensive response noted immediately after intravenous administration of indigo carmine was due to anaphylactic reaction [6, 7]. In one of these case reports, the patient had the complete spectrum of anaphylaxis but did not have a history of allergies or previous exposure of indigo carmine, and the authors suggested that indigo carmine directly may have triggered histamine release, consistent with an anaphylactoid reaction associated with severe hypotension, bronchospasm, and urticaria [6]. In the other case report, the patient did not have a previous history of allergy or skin symptoms, but he had severe hypotension and hypoxia, with wheezing that progressed to cardiac arrest [7]. The present patient had a history of bee sting allergy, and he developed hypotension, wheezing, and subcutaneous erythema within several minutes after the administration of indigo carmine. It may be difficult to prove whether he had a life-threatening anaphylactic reaction in response to indigo carmine. The only proven method to evaluate the patient's allergic response to indigo carmine is skin testing. We seriously considered performing the skin testing, but the patient refused. Therefore, anaphylactic reaction usually may be diagnosed on the basis of a previous history of allergy and the clinical presentation. The clinical condition of the present patient satisfied the clinical criteria for a life-threatening reaction due to anaphylactic response by the World Allergy Organization [8]. In summary, indigo carmine may be used in routine clinical practice in urology or gynecology because of the safety profile of the dye compared with methylene blue [9]. However, physicians should be aware that indigo carmine rarely may cause a major life-threatening anaphylactic reaction. Competing Interests The authors declare that there are no competing interests regarding the publication of this paper. ==== Refs 1 Lacy W. W. Ugaz C. Newman E. V. The use of indigo carmine for dye dilution curves Circulation Research 1955 3 6 570 574 10.1161/01.res.3.6.570 2-s2.0-0001378393 13270370 2 Jeffords D. L. Lance P. H. Dewolf W. C. Severe hypertensive reaction to indigo carmine Urology 1977 9 2 180 181 10.1016/0090-4295(77)90192-3 2-s2.0-0017364620 841782 3 Ng T. Y. Datta T. D. Kirimli B. I. Reaction to indigo carmine Journal of Urology 1976 116 1 132 133 2-s2.0-0017163799 933277 4 Harioka T. Mori H. Mori K. Hypertensive reaction to indigo carmine during transurethral resection of a bladder tumor Anesthesia & Analgesia 1987 66 10 p. 1049 2-s2.0-0023424911 5 Shir Y. Raja S. N. Indigo carmine-induced severe hypotension in patients undergoing radical prostatectomy Anesthesiology 1993 79 2 378 381 10.1097/00000542-199308000-00024 2-s2.0-0027226114 8342846 6 Naitoh J. Fox B. M. Severe hypotension, bronchospasm,and urticaria from intravenous indigo carmine Urology 1994 44 2 271 272 10.1016/S0090-4295(94)80149-5 2-s2.0-0028094773 8048206 7 Gousse A. E. Safir M. H. Madjar S. Ziadlourad F. Raz S. Life-threatening anaphylactoid reaction associated with indigo carmine intravenous injection Urology 2000 56, article 508 2-s2.0-0343006671 8 Simons F. E. R. Ardusso L. R. F. Bilò M. B. World allergy organization guidelines for the assessment and management of anaphylaxis World Allergy Organization Journal 2011 4 2 13 37 10.1097/WOX.0b013e318211496c 2-s2.0-79954432935 23268454 9 Mahadevan M. M. Weitzman G. A. Hogan S. Breckinridge S. Miller M. M. Methylene blue but not indigo carmine is toxic to human luteal cells in vitro Reproductive Toxicology 1993 7 6 631 633 10.1016/0890-6238(93)90041-5 2-s2.0-0027692033 8118115

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==== Front Case Rep PulmonolCase Rep PulmonolCRIPUCase Reports in Pulmonology2090-68462090-6854Hindawi Publishing Corporation 10.1155/2016/3793941Case ReportPostpartum Tuberculosis: A Diagnostic and Therapeutic Challenge http://orcid.org/0000-0003-0617-9630Kodadhala Vijay 1 * Gudeta Alemeshet 1 Zerihun Aklilu 1 Lewis Odene 2 Ahmed Sohail 3 Gajjala Jhansi 3 Thomas Alicia 2 1Department of Internal Medicine, Howard University Hospital, 2041 Georgia Avenue NW, Washington, DC 20060, USA2Division of Pulmonary Medicine, Howard University Hospital, 2041 Georgia Avenue NW, Washington, DC 20060, USA3Division of Infectious Diseases, Howard University Hospital, 2041 Georgia Avenue NW, Washington, DC 20060, USA*Vijay Kodadhala: vkodadhala@gmail.comAcademic Editor: Tun-Chieh Chen 2016 16 8 2016 2016 379394123 4 2016 26 5 2016 Copyright © 2016 Vijay Kodadhala et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Tuberculosis (TB) infection in pregnant women and newborn babies is always challenging. Appropriate treatment is pivotal to curtail morbidity and mortality. TB diagnosis or exposure to active TB can be emotionally distressing to the mother. Circumstances can become more challenging for the physician if the mother's TB status is unclear. Effective management of TB during pregnancy and the postpartum period requires a multidisciplinary approach including pulmonologist, obstetrician, neonatologist, infectious disease specialist, and TB public health department. Current guidelines recommend primary Isoniazid prophylaxis in TB exposed pregnant women who are immune-suppressed and have chronic medical conditions or obstetric risk factors and close and sustained contact with a patient with infectious TB. Treatment during pregnancy is the same as for the general adult population. Infants born to mothers with active TB at delivery should undergo a complete diagnostic evaluation. Primary Isoniazid prophylaxis for at least twelve weeks is recommended for those with negative diagnostic tests and no evidence of disease. Repeated negative diagnostic tests are mandatory before interrupting prophylaxis. Separation of mother and infant is only necessary when the mother has received treatment for less than 2 weeks, is sputum smear-positive, or has drug-resistant TB. This case highlights important aspects for management of TB during the postpartum period which has a higher morbidity. We present a case of a young mother migrating from a developing nation to the USA, who was found to have a positive quantiFERON test associated with multiple cavitary lung lesions and gave birth to a healthy baby. ==== Body 1. Introduction Tuberculosis is a widespread, infectious disease caused by various strains of mycobacteria, usually Mycobacterium tuberculosis. It is an airborne infection. When patients do not have symptoms, it is known as latent tuberculosis. About ten percent of latent infections eventually progresses to active disease which, if left untreated, kills more than fifty percent of those infected [1]. Worldwide, the burden of TB disease in pregnant women is substantial. In 2011, it was estimated that more than 200,000 cases of active tuberculosis occurred among pregnant women globally; the greatest burdens were in Africa and Southeast Asia [2]. Prenatal care presents a unique opportunity for evaluation and management of latent and active tuberculosis in pregnant women. Individuals with an increased risk of tuberculosis may seek medical care only during pregnancy such as our patient. Since pregnancy has not been shown to increase the risk of TB, the epidemiology of TB in pregnancy is a reflection of the general incidence of disease [3]. 2. Case Presentation A 31-year-old woman from Columbia with medical history significant for Gestational Diabetes presented to the labor ward without prior prenatal care. She came to the United States eight months prior to presentation. She received cesarean section for fetal distress and gave birth to a healthy baby. Her medical history was negative for cough, shortness of breath, fever, night sweating or loss of appetite, incarceration or living in institution, and any contact with TB patient or chronically coughing person. She was never diagnosed with active or latent TB. At the time of presentation patient was not actively coughing. Patient did not remember if she received BCG vaccination as a child or not. Physical examination revealed young healthy looking female patient without any cardiopulmonary distress. Examination was negative for lymphadenopathy; chest was symmetrical, resonant to percussion, clear to auscultation bilaterally. Examination of other systems was within normal limits. BCG vaccination scar was not noted on either of the both upper arms. The patient's perioperative chest X-ray (Figure 1) showed a small irregular density in the right middle lung and there was a hazy increased density over the left upper lung, which was suspicious for infiltrates versus fibrotic changes. Lucency was also noted within the left upper lobe, which was suspicious for cavitary change and further evaluation with CT was recommended for possible pulmonary tuberculosis. Noncontrast CT (Figure 2) showed patchy and nodular opacity in the apical posterior segment of the left upper lobe and to a lesser extent in the superior segment of the right lower lobe and right lung base as well as a small axillary node. The differential diagnosis would include mycobacterial infection and pyogenic pneumonia. In light of positive chest X-ray and chest CT scan, TB quantiFERON gold test was requested. All other lab tests including tests for hepatitis B surface antigen, HCV, HIV, work-up for collagen vascular diseases, and sarcoidosis were negative. QuantiFERON TB gold test was positive. To address further plan of management following the positive quantiFERON TB test, a multidisciplinary approach, which included pulmonary diseases specialist, infectious diseases specialist, obstetrician, and pediatrician, was undertaken to address the following areas of concern: (1) isolation of baby from mother, (2) isolation of baby from other babies in nursery, (3) initiating LTBI (latent TB infection) treatment in baby, and (4) initiating four-drug TB regimen in the mother. The panel agreed to respiratory isolation, obtaining three sputum samples for AFB smears, bronchoalveolar lavage (BAL) for mother, starting mother on four-drug anti-TB regimen and the baby on LTBI treatment, while keeping the mother and baby together. Three induced sputum samples were obtained and were stained for Acid Fast Bacilli (AFB) which did not reveal any Acid Fast Bacilli. Patient initially refused bronchoscopy procedure, but after explaining to her the significance of the procedure, she consented for bronchoscopy. She received bronchoscopy (Figure 3) with biopsy and BAL. Bronchoscopy revealed hyperemic and friable bronchial tree mucosa. BAL was done from both left and right side and biopsy was taken from left upper lobe. Lab data are summarized in Table 1. Biopsy from left upper lobe showed predominantly bronchial mucosa with chronic inflammation and fibrosis. Special stain for Acid Fast Bacilli (Fite Stain) and fungi (GMS stain) were negative. Immunostain for CD-68 highlights few macrophages. BAL from right lower lobe was negative for malignancy and no evidence for infectious organisms and showed lympho/histiocytic infiltrate (primarily histiocytes). Left upper lobe BAL was also negative for malignancy and showed lympho/histiocytic infiltrate. Sputum and BAL sample analysis with Direct AFB probe and AFB culture was positive for AFB. Public health was notified and mother was continued on full course of TB treatment. Baby was evaluated by neonatology team, PPD was performed, and it was negative and chest X ray was normal. As per multidisciplinary team plan, baby was started on INH prophylaxis for the possible latent TB infection while awaiting gastric aspirate TB work-up results. Mom and baby are allowed to be together. 2.1. Follow-Up Patient and the baby were closely followed in pulmonary, infectious diseases, and pediatric clinics. Importance of medication compliance and adverse effects of medication were explained to the patient and she clearly understands the instructions. Two months after commencement of the treatment, patient and baby remained compliant with treatment regimen and did not experience any adverse effects of medications. Baby's growth chart was satisfactory. Patient expressed wish to travel back to her home country. We took the opportunity and once again clearly gave her the instructions about the need for regular doctor follow-up of both mother and the baby. Patient has good educational background and she promised to follow our instructions. Sadly, we lost contact with her after she left the USA. We sincerely hope that she followed our instructions and both mother and baby completed treatment and prophylaxis, respectively. 3. Discussion: Tuberculosis in Pregnancy 3.1. Introduction More than 200,000 cases of TB occur among pregnant women globally. Pregnancy has no influence on pathogenesis, disease progression, and treatment response. Pathophysiology Airborne Respiratory Droplets are inhaled and delivered to the terminal airways. Macrophages ingest the mycobacteria, which continue to multiply intracellularly and can potentially spread to other organs through the lymphatics and blood stream. LTBI means new reactivity to the tuberculin skin test (or interferon-gamma release assay). Progressive TB means primary progressive after initial infection, reactivation of LTBI. 3.2. Pathophysiology of TB Inhalation of Mycobacterium tuberculosis results in one of the four possible outcomes: (1) immediate clearance of the organism, (2) latent infection, (3) the onset of active disease (primary infection), and (4) active disease many years later (reactivation of the disease). In due course, approximately 10 percent of the infected individuals develop active disease, either primary or reactivation of LTBI. If the host defense mechanism is poor, mycobacteria proliferate within alveolar macrophages and destroy them, resulting in release of cytokines and chemokines. These in return attract other phagocytic cells including monocytes, other alveolar macrophages, and neutrophils resulting in nodular granulomatous structure formation and called the tubercle. Bacteria replication continues leading to lymph nodes involvement called primary TB, involvement of lung parenchyma along with lymph node involvement called Ghon's complex. Unchecked bacterial growth results in hematogenous spread results in disseminated TB (see Pathophysiology in Section 3.1). 3.3. Diagnosis and Treatment of Latent TB in Pregnancy Routine testing for TB is not indicated but testing is indicated on patients who need prompt treatment such as immunosupressed patients, because they are at high risk of progression to active TB. Testing for LTBI prior to pregnancy is preferred. If a patient receiving treatment gets pregnant, treatment should be continued. If there are no risks for progression of LTBI, wait three months postpartum to test and treat latent TB. Tools for diagnosis are tuberculin skin testing (TST) and interferon-gamma release assays (IGRAs). Both these tests can be safely performed in pregnancy and pregnancy does have any effect on the results. If the test results are positive further clinical evaluation including clinical features, radiological, microbiological, and immunological investigations should be performed to rule out active TB. First choice of the treatment of latent TB is Isoniazid (INH) for nine-month duration with daily pyridoxine supplement. However in one of the following circumstances four-month treatment with Rifampin is indicated. (1) INH resistance, (2) intolerance to INH, and (3) poor medication compliance. 3.4. Active Tuberculosis in Pregnancy Sugarman et al. estimated that 216 500 (95% uncertainty range 192 100–247 000) active tuberculosis cases existed in pregnant women globally in 2011. The greatest burdens were in the WHO African region with 89 400 cases and the WHO South East Asian region with 67 500 cases. Though active tuberculosis in pregnancy burden is concentrated in Africa and South East Asia, Sugarman et al.'s study reveals that active TB in pregnancy is seen worldwide in both developed and developing countries (Figure 4) [2]. 3.5. Clinical Manifestation of TB in Pregnancy Pregnant patients with active TB typically have the same clinical manifestations as nonpregnant patients which include fever, chest pain, fatigue, cough, weight loss, night sweat, and dyspnea. TB symptoms could be masked by physiological symptoms of pregnancy. Malaise and fatigue may be attributed to pregnancy and it is more difficult to recognize weight loss. 3.6. Diagnosis of TB in Pregnancy The evaluation for active TB in pregnancy should be as in nonpregnancy which includes chest X ray (with appropriate protection of the fetus), sputum for AFB and TB PCR. Evaluation for extra-pulmonary disease should be guided by clinical symptoms. Diagnosis of pregnancy should prompt the evaluation for HIV infection. Transmission of TB from Mother to Newborn Infant. It can occur by vertical transmission (very rare) of TB by transplacental transmission through umbilical veins to the fetal liver and lungs or aspiration and swallowing of infected amniotic fluid in utero- or intrapartum causing primary infection of fetal lungs and gut. Transplacental infection occurs late in pregnancy and aspiration from amniotic fluid occurs in the perinatal period. In the postpartum period a horizontal spread by droplet from mother or undiagnosed family member is most commonly suggested. Transmission of tuberculosis through breast milk does not occur [5]. Effects of Active TB on Pregnant Women and Infants. They include premature birth, low birth weight, intrauterine growth retardation, perinatal death (sixfold risk increase). 3.7. Treatment of Active TB in Pregnancy Treatment should be initiated if the suspicion of active disease is moderate to high such as persistent upper lobe infiltrate, cough in a high risk individual, and positive AFB smear/PCR as benefits of treatment overweight risks. The initial treatment regimen should consist of Isoniazid, Rifampicin, and Ethambutol. Although all of these drugs cross the placenta, they do not appear to have teratogenic effects. Streptomycin is the only antituberculosis drug documented to have harmful effects on the human fetus (congenital deafness) and should not be used. Although detailed teratogenicity data are not available, PZA can probably be used safely during pregnancy and is recommended by the World Health Organization (WHO) and the International Union against Tuberculosis and Lung Disease (IUATLD) (Table 2) [5]. Ethambutol may be discontinued after one month if the results of drug sensitivity showed the organism is susceptible to Isoniazid and Rifampin. Pyrazinamide is not used routinely for pregnant women in the United States because of limited safety data but it is recommended by WHO. 3.8. Side Effects of Anti-TB Medications in Pregnancy Drug interactions are common and need careful monitoring and appropriate action. It is near impossible to discuss all the adverse effects of anti-TB medications here. We will discuss major adverse effects of first-line anti-TB drugs and second line anti-TB medications (Table 3). INH adverse affects result anywhere from mild asymptomatic transaminitis to fatal hepatitis, peripheral neurotoxicity, and lupus like reaction. In pregnancy INH should be prescribed with pyridoxine supplementation. Rifampin adverse effects include skin reactions like pruritus, gastrointestinal reactions like nausea, anorexia, abdominal pain, flulike syndrome, hepatotoxicity, severe immunologic reactions like thrombocytopenia, hemolytic anemia, acute renal failure, and thrombotic thrombocytopenic purpura. Ethambutol can cause retrobulbar neuritis and peripheral neuritis. Pyrazinamide may result in hepatotoxicity, gastrointestinal symptoms, nongouty polyarthralgia, and asymptomatic hyperuricemia among others [4]. 3.9. Follow-Up Treatment can be administered by directly observed therapy (DOT) to improve adherence and to evaluate for drug toxicity. Expert in TB should be consulted for interruptions longer than two weeks or for sporadic adherence. Baseline liver enzymes and monthly liver enzymes should be obtained. Patient should be informed to call if any symptoms or signs of hepatitis occur. 3.10. Toxicity and Monitoring of Anti-TB Medications in Pregnancy There is increased risk of hepatotoxicity in pregnancy and postpartum. So base line Liver Function Test (LFT) and then monthly LFTs are recommended. Other investigations like HIV, HBV, HCV are also recommended. Avoidance of alcohol use and hepatotoxins exposure is advised. Mild transaminitis should prompt more frequent monitoring. Stop medication in symptomatic patients with ALT greater than three times and asymptomatic patient with ALT greater than five times. 3.11. Breast Feeding in Patient with Active TB Breastfeeding is not contraindicated if the mother is being treated for active tuberculosis or latent TB with first-line agents. The infant should receive pyridoxine if mother is receiving Isoniazid. Breast feeding is contraindicated if the mother is receiving rifabutin or fluoroquinolone. 3.12. Control of Transmission of TB in Pregnancy Mother and baby bonding is very important and breast feeding plays significant role in providing immunity to baby in the first few months. So every safe measure should be undertaken to make sure that mother and baby are allowed to be together and if separation is inevitable (Table 4), clinicians have to make the best effort to make it as short as possible. Breast feeding should be continued. It is very important for clinicians to have knowledge about special situations like that of our case where mother was diagnosed with active TB and infant does not have active or latent TB, or as a matter of fact any one of the situations mentioned in Table 4. If mother has active TB and is on treatment and baby has one of the following conditions, either active TB or LTBI or no infection, standard of care therapy should be initiated for the baby and separation is not recommended. Mother should always wear mask until she is no longer infectious. In other situations both mother and baby should be fully evaluated before they are allowed to be together. 4. Conclusion Diagnosing and treating active or latent TB in pregnancy and during postpartum period is very important as it affects both mother and baby. It can cause significant morbidity and mortality if not correctly diagnosed and treated adequately. Though our patient presented without any risk factors (except a positive travel history) and symptoms of TB, high index of suspicion lead to correct diagnosis and hence appropriate treatment. Abbreviations TB:Tuberculosis BCG:Bacille Calmette-Guerin CT:Computed tomography HIV:Human immunodeficiency virus HCV:Hepatitis C virus HBV:Hepatitis B virus LTBI:Latent TB infection AFB:Acid Fast Bacillus BAL:Bronchoalveolar Lavage GMS:Grocott's Methenamine silver CD:Cluster differentiation PCR:Polymerase chain reaction PPD:Purified protein derivative INH:Isoniazid ALT:Alanine transaminase LFT:Liver Function Test W.H.O:World Health Organization IUATLD:International Union against Tuberculosis and Lung Disease. Consent Written informed consent was obtained for the patient for the publication of this case report and accompanying images. Competing Interests The authors declare that they have no conflict of interests. Authors' Contributions Vijay Kodadhala, M.D., Alemeshet Gudeta, M.D., and Aklilu Zerihun, M.D., contributed towards an extensive review of literature as well as paper drafting. Odene Lewis, M.D., and Sohail Ahmed, M.D., also made important contributions to this paper. Jhansi Gajjala, M.D., and Alicia Thomas, M.D., primarily managed the patient and overviewed the paper. Figure 1 Chest X-ray. Increased density over the left upper lung and right middle lobe suspicious for infiltrate/fibrotic change. Figure 2 CT chest, noncontrast. Multiple cavitary lesions in left upper lobe. Figure 3 Bronchoscopy. Hyperemic and friable bronchial tree mucosa. BAL was done from both left and right side and biopsy was taken from left upper lobe. Figure 4 Epidemiology of active TB in pregnancy [2]. Table 1 Additional lab data. Connective tissue disease work-up Bronchial washing ABG on room air Summary of TB work-up ACE level: 41 (9–67) U/L: normal ESR: 30 mm/hr CRP: 1.4 (normal < 0.8) Anti-CCP: normal ANCA: negative ANA: negative Appearance: clear WBC: 8 RBC: 63 Poly: 7% Mesothelial cells: 6% Culture: normal flora Bronchial washing: AFB PCR was positive Culture was positive for mycobacterium tuberculosis Fungal stain: negative Mycobacterial PCR: positive Culture for bacteria: normal flora FiO2: 0.21  pH: 7.5  PaCO2: 30  PaO2: 106  SaO2: 99 Sputum: AFB stain (3x): negative AFB culture on broth culture: positive for AFB Mycobacterium TB complex identified by direct probe Broncho alveolar lavage (BAL): AFB stain: negative Mycobacterium tuberculosis complex identified by direct probe AFB culture on broth: positive for AFB Table 2 American Thoracic Society, CDC, Infectious Disease Society of America recommendations [4]. Medications Month 1 to month 2 Month 3 to month 9 Isoniazid ✓ ✓ Rifampin ✓ ✓ Ethambutol ✓   Table 3 Side effects of anti-TB medications in pregnancy [4]. Medications Side effects Isoniazid Category C: possible increased risk of hepatitis/peripheral neuropathy Rifampin Category C: rare cases of fetal abnormalities and hemorrhagic disease Ethambutol Category B Pyrazinamide Category C: detail teratogenicity data are not available Fluoroquinolones Category C: causes arthropathies Ethionamide Category C: teratogenic in laboratory animals Para-aminosalicylic acid Category C: adverse effects are not certain Cycloserine Category C: adverse effects are not certain Streptomycin Category D: congenital deafness Kanamycin/amikacin Category D: similar side effect with streptomycin Table 4 Control of transmission of TB in pregnancy [4]. Mother Infant   Active TB on treatment Active TB on treatment No separation Active TB on treatment Latent TB on treatment No separation Active TB on treatment No active TB or latent TB Infant should be treated for latent TB for 3 to 4 months until reevaluation Known or suspected drug resistant TB No active TB or latent TB Should be separated until mother is noninfectious Known or suspected active TB Has not been evaluated Should be separated until both have been fully evaluated ==== Refs 1 WHO Tuberculosis Fact Sheet 2010 104 World Health Organization 2 Sugarman J. Colvin C. Moran A. C. Oxlade O. Tuberculosis in pregnancy: an estimate of the global burden of disease The Lancet Global Health 2014 2 12 e710 e716 10.1016/s2214-109x(14)70330-4 2-s2.0-84918805168 25433626 3 Schaefer G. Zervoudakis I. A. Fuchs F. F. David S. Pregnancy and pulmonary tuberculosis Obstetrics & Gynecology 1975 46 6 706 715 2-s2.0-0016719141 1187077 4 American Thoracic Society Treatment of tuberculosis Morbidity and Mortality Weekly Report 2003 52 11 1 77 12549898 5 Mittal H. Das S. Faridi M. M. A. Management of newborn infant born to mother suffering from tuberculosis: current recommendations & gaps in knowledge Indian Journal of Medical Research 2014 140 32 39 2-s2.0-84906857845 25222775

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==== Front Case Rep MedCase Rep MedCRIMCase Reports in Medicine1687-96271687-9635Hindawi Publishing Corporation 10.1155/2016/6065259Case ReportClinical Evolution of Central Pontine Myelinolysis in a Patient with Alcohol Withdrawal: A Blurred Clinical Horizon http://orcid.org/0000-0003-1061-0497Mohammed Abdul S. 1 * http://orcid.org/0000-0003-4594-1704Boddu Prajwal 2 Yazdani Dina F. 3 1Department of Internal Medicine, Advocate Illinois Masonic Medical Center, 2356 N. Elston Avenue, No. 306, Chicago, IL 60614, USA2Department of Internal Medicine, Advocate Illinois Masonic Medical Center, 856 W. Nelson Street, Apartment 2002, Chicago, IL 60657, USA3Deccan College of Medical Sciences, Kanchanbagh, Hyderabad, Telangana 500058, India*Abdul S. Mohammed: mabdulsalman@gmail.comAcademic Editor: Michael S. Firstenberg 2016 16 8 2016 2016 606525929 4 2016 25 7 2016 Copyright © 2016 Abdul S. Mohammed et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Central pontine myelinolysis (CPM), a potentially fatal and debilitating neurological condition, was first described in 1959 in a study on alcoholic and malnourished patients. It is a condition most frequently related to rapid correction of hyponatremia. Chronic alcoholism associated CPM tends to be benign with a favorable prognosis compared to CPM secondary to rapid correction of hyponatremia. We describe a normonatremic, alcoholic patient who presented with CPM after a rapid rise in his sodium levels. Our case illustrates the fact that CPM can manifest even in patients who are normonatremic at baseline. Rapid rises in sodium levels should be promptly reversed before clinical symptoms manifest in patient with risk factors for CPM irrespective of their baseline sodium levels. Furthermore, clinical evolution of CPM can be difficult to discern from the natural course of alcohol withdrawal delirium, requiring astuteness and maintenance of a high degree of clinical suspicion on the part of the physician. ==== Body 1. Introduction Central pontine myelinolysis (CPM), a potentially fatal and debilitating neurological condition, was first described in 1959 in a study on alcoholic and malnourished patients [1]. It is a condition most frequently related to rapid correction of hyponatremia. Involvement of the corticospinal tracts in the pons and midbrain, resulting in spastic quadriparesis and pseudobulbar palsy, is a characteristic neurological finding and renders this condition its name [2]. Progressive lethargy, quadriparesis, dysarthria, ophthalmoplegia, and ataxia are some of the frequent manifestations of this syndrome [3]. It was later discovered that the process of osmotic demyelination was not confined exclusively to the pons but also involved various extrapontine sites, a condition referred to as extrapontine myelinolysis (EPM) [4]. EPM generally occurs along with CPM but may occur in isolation as well [5]. Extrapyramidal features and myoclonus of EPM are some of the symptoms that represent potentially treatable manifestations of the disease and should be differentiated from CPM [6]. The term osmotic demyelination syndrome encompasses both the abovementioned entities. Comorbidities associated with higher incidence of CPM include dialysis, liver failure and transplantation, advanced lymphoma, carcinoma, cachexia, severe bacterial infections, acute hemorrhagic pancreatitis, chronic alcoholism, and pellagra [2, 7]. Chronic alcoholism associated CPM tends to be benign with a favorable prognosis compared to CPM secondary to rapid correction of hyponatremia [8, 9]. Also, CPM has been documented to occur in hypokalemic patients even with a steady rise in sodium levels [10, 11]. We describe a normonatremic, alcoholic patient who presented with CPM after a rapid rise in his sodium levels. 2. Case Report A 57-year-old male with a known past medical history of squamous cell carcinoma of the oropharynx T2N0 on radiation therapy, chronic alcohol abuse, ulcerative colitis, and chronic obstructive pulmonary disease presented to the emergency department with 3 episodes of syncope and decreased oral intake over the week prior to presentation. He also reported difficulty swallowing solid foods over the past month. His last alcohol intake was 2 days prior to admission. On initial evaluation, vitals were significant for heart rate of 122 beats/min, blood pressure of 100/70 mmHg, respiratory rate of 20/min, and temperature of 37°C. Physical examination revealed a dry oral mucosa and decreased skin turgor. Laboratory studies were remarkable for sodium level of 126 mEq/L, potassium of 4.3 mEq/L, chloride of 86 mEq/L, bicarbonate of 28 mEq/L, BUN of 33 mg/dL, and creatinine of 4.2 mEq/L with a baseline of 0.6 mEq/L, platelets of 124,000/mm3, AST of 83 IU/L, ALT of 62 IU/L, ALP of 129 IU/L, and bilirubin of 1.9 mg/dL. Ammonia and albumin levels were noted to be within the normal range. Initial computerized tomography (CT) of the head was negative for acute intracranial process. The patient was started on IV fluids and admitted for further management. Over the next few days, the patient's hydration status improved and his appetite increased. His creatinine trended down and his sodium level increased to 130 mEq/L. On fourth day of admission, the patient was noted to be combative towards the medical staff. He also started showing signs of alcohol withdrawal with tachycardia, diaphoresis, tremors, anxiety, and confusion. Examination revealed progressively worsening abdominal distention. Sodium levels rose steadily to 140 mEq/L over the next four days. On the eighth day of admission, intravenous (IV) fluids were changed to D5W in light of the increasing sodium level. A CT scan of the abdomen was obtained for the increasing abdominal distention, which revealed dilatation of the small bowel (see Figure 1) extending from the proximal jejunum to the distal ileum as well as marked dilatation of the cecum extending to the proximal descending colon, suggestive of adynamic ileus. Cirrhosis of the liver and recto sigmoid diverticula were also noted. A nasogastric (NG) tube was placed and put to wall suction. Flexible sigmoidoscopy was performed but the scope had to be withdrawn prematurely due to the risk of perforation of diverticuli. He continued to be agitated and confused, requiring frequent doses of lorazepam to control his symptoms. On days 9 and 10, patient's sodium level increased steeply from 142 mEq/L to 151 and 159 mEq/L, respectively. On day 12, the patient had decreased response to verbal and physical stimuli. It was noted at this time that the patient was no longer on lorazepam. Ongoing free water losses from diarrhea, NG suction, and extensive third spacing into the bowel delayed the rapid reversal of hypernatremia despite aggressive IV fluid hydration. He became increasingly lethargic and developed worsening dysarthria and dysphagia. Neurological exam revealed disconjugate gaze with exotropia, flaccid quadriparesis, and absent deep tendon reflexes. Magnetic resonance imaging (MRI) of the brain (see Figures 2 and 3) demonstrated increased T2 and flair signals in the central basis pontis consistent with central pontine myelinolysis. On the 13th day of the hospital course, the patient started developing respiratory distress with tachypnea into the 30 s; examination revealed rapid shallow breathing and use of accessory muscles. CT scan of the chest showed significant debris in the right main stem bronchus along with collapse of the right lower lobe consistent with aspiration pneumonitis (see Figure 4). Per patient's family's wishes, comfort measures were initiated and patient passed away later that day. 3. Discussion CPM usually occurs with rapid correction of hyponatremia but may also occur in normonatremic and hypernatremic individuals [12–14]. CPM has also been described in patients with acute hypernatremia resulting from diabetes insipidus [15, 16]. Rarely, a CPM like condition developing after acute correction of hypernatremia has been described. The patient discussed in this report showed a dramatic recovery in his clinical and radiological manifestations of disease suggesting that this syndrome is probably operated by a different pathogenic mechanism [17]. The association between CPM and rapid correction of hyponatremia was first suggested by Norenberg et al. in a cohort of 12 CPM patients, the majority of whom had rapid and sustained correction of sodium levels into the hypernatremic range [18]. A subsequent study, by Ayus et al., identified rapid correction of sodium into the hypernatremic range especially in the setting of hepatic encephalopathy to be a contributing factor in the demyelinating process [19]. It is believed that rapid corrections of sodium levels create hyperosmotic stresses at regions of compact grey-white matter interdigitations leading to cellular swelling and compression induced myelinolysis of fiber tracts. Other hypotheses suggest that rapid correction may lead to endothelial injury created gaps in blood brain barrier resulting in release of unidentified myelinotoxic blood derived factors [20]. The neuropsychiatric symptoms of CPM can be similar to those seen in alcohol withdrawal. Furthermore, the ascription of subtle neurological changes to the development of CPM in a patient experiencing alcohol withdrawal can be difficult due to the confounding effects of sedative use. Alcohol delirium tremens typically lasts 1–5 days from the onset of its presentation. A prolonged encephalopathy beyond the expected duration of delirium tremens should raise concern for complicating neuropathologies and prompt further workup [21]. CPM typically presents 2–6 days after an acute rise in sodium level. Our patient continued to have neuropsychiatric symptoms for more than a week from the onset of delirium. There was a rapid rise in sodium between days 9 and 10. It was on day 12, when the patient continued to be obtunded while not being on sedatives, that the diagnosis of CPM was first entertained. Our patient did not present with active visual hallucinosis or agitated delirium to suggest alcoholic psychosis. Secondly, the CPM had to be distinguished from Wernicke encephalopathy, a condition that may occur along with it as an infrequently recognized combination [22, 23]. Our patient had eye movement abnormalities, a finding that was noted in 25% of patients with CPM in one study [24]. Our patient was treated adequately with intravenous thiamine for the duration of the hospital stay. Oculomotor dysfunction in spite of adequate thiamine administration pointed against the diagnosis of Wernicke encephalopathy [22]. Magnetic resonance imaging is the imaging sequence of choice in detecting CPM lesions. Areas affected by myelinolysis are hypoattenuating and typically involve the basis pontis with sparing of pontine tegmentum. Basal ganglia and thalamus may also be involved, indicating extrapontine myelinolysis. Lesions are typically tridentate and tend to be hyperintense on T2 and hypointense on T1 without enhancement even after administration of contrast [25, 26]. CT and MRI findings may lag behind the clinical manifestations by up to two weeks. However, diffusion weighted imaging (DWI) may be able to detect lesions as early as 24 hours from the manifestation of clinical symptoms [27]. Given the potentially severe and permanent adverse consequences of CPM, prevention is essential. The ideal management hinges upon identifying patients whose sodium levels have been corrected rapidly as high risk and pursuing rescue strategies, including the use of DDAVP to facilitate reversal of acute rise in sodium levels [28]. Prompt recognition and rapid resolution of treatment-induced hypernatremia are imperative in reversing the processes underlying demyelination before clinical symptoms manifest. Our patient had all the major risk factors of CPM including alcoholism, malnutrition, and hypokalemia [13]. Although our patient's hypernatremia was recognized promptly, he continued to have significant free water losses from large volume diarrhea, nasogastric suction, and third spacing, preventing the rapid reversal of sodium levels. Continued free water losses are the most frequent reason for miscalculation of free water deficits and appropriate correction in sodium levels. The combination of acute hypernatremia, hypokalemia, and chronic alcoholism had precipitated CPM in our patient. Although acute hypernatremia and its slow reversal may have contributed significantly to the manifestation of the disease, it can only be speculated if our patient would have developed CPM from the effects of alcoholism, malnutrition, and hypokalemia alone without the additional contribution of hypernatremia. 4. Conclusion Our case illustrates the fact that CPM can manifest even in patients who are normonatremic at baseline. Rapid rises in sodium levels should be promptly reversed before clinical symptoms manifest in patients with risk factors for CPM irrespective of their baseline sodium levels. Furthermore, clinical evolution of CPM can be difficult to discern from the natural course of alcohol withdrawal delirium, requiring astuteness and maintenance of a high degree of clinical suspicion on the part of the physician. Acknowledgments The authors would like to thank Laura Johnson, M.D., first-year family medicine resident at Advocate Illinois Masonic, for her help with editing the paper. Competing Interests The authors declare that they have no competing interests and that they have no financial or nonfinancial interests. Authors' Contributions All authors have a role in writing up this paper and have read and agreed to the content of this paper. Figure 1 CT scan of the abdomen showing small bowel dilatation. Figure 2 T2 magnetic resonance imaging demonstrating central pontine myelinolysis. Figure 3 Diffusion weighted MRI image of our patient demonstrating central pontine myelinolysis. Figure 4 CT scan of the chest showing aspiration pneumonitis. ==== Refs 1 Adams R. D. Victor M. Mancall E. L. Central pontine myelinolysis: a hitherto undescribed disease occurring in alcoholic and malnourished patients Archives of Neurology and Psychiatry 1959 81 2 154 172 10.1001/archneurpsyc.1959.02340140020004 2-s2.0-0011514906 13616772 2 Laureno R. Karp B. I. Myelinolysis after correction of hyponatremia Annals of Internal Medicine 1997 126 1 57 62 10.7326/0003-4819-126-1-199701010-00008 2-s2.0-0031034815 8992924 3 Karp B. I. Laureno R. Pontine and extrapontine myelinolysis: a neurologic disorder following rapid correction of hyponatremia Medicine 1993 72 6 359 373 2-s2.0-0027368232 8231786 4 Wright D. G. Laureno R. Victor M. Pontine and extrapontine myelinolysis Brain 1979 102 2 361 385 10.1093/brain/102.2.361 2-s2.0-0018389881 455045 5 Martin R. J. Central pontine and extrapontine myelinolysis: the osmotic demyelination syndromes Neurology in Practice 2004 75 supplement 3 iii22 iii28 10.1136/jnnp.2004.045906 2-s2.0-4344648159 6 Soupart A. Ngassa M. Decaux G. Therapeutic relowering of the serum sodium in a patient after excessive correction of hyponatremia Clinical Nephrology 1999 51 6 383 386 2-s2.0-0033024670 10404700 7 Ashrafian H. Davey P. A review of the causes of central pontine myelinosis: yet another apoptotic illness? European Journal of Neurology 2001 8 2 103 109 10.1046/j.1468-1331.2001.00176.x 2-s2.0-0035056580 11430268 8 Mochizuki H. Masaki T. Miyakawa T. Benign type of central pontine myelinolysis in alcoholism. Clinical, neuroradiological and electrophysiological findings Journal of Neurology 2003 250 9 1077 1083 10.1007/s00415-003-0157-6 2-s2.0-0141850907 14504969 9 Dujmović I. Vitas J. Zlatarić N. Drulović J. Central pontine myelinolysis in a chronic alcoholic: a clinical and brain magnetic resonance imaging follow-up Vojnosanitetski Pregled 2013 70 8 785 788 10.2298/vsp1308785d 2-s2.0-84880936442 24069831 10 Lohr J. W. Osmotic demyelination syndrome following correction of hyponatremia: association with hypokalemia The American Journal of Medicine 1994 96 5 408 413 10.1016/0002-9343(94)90166-x 2-s2.0-0028276629 8192171 11 Heng A. E. Vacher P. Aublet-Cuvelier B. Centropontine myelinolysis after correction of hyponatremia: role of associated hypokalemia Clinical Nephrology 2007 67 6 345 351 10.5414/cnp67345 2-s2.0-34250201520 17598369 12 Jha A. A. Behera V. Jairam A. Baliga K. Osmotic demyelination syndrome in a normonatremic patient of chronic kidney disease Indian Journal of Critical Care Medicine 2014 18 9 609 611 10.4103/0972-5229.140153 2-s2.0-84906997354 25249746 13 Mascalchi M. Cincotta M. Piazzini M. Case report: MRI demonstration of pontine and thalamic myelinolysis in a normonatremic alcoholic Clinical Radiology 1993 47 2 137 138 10.1016/S0009-9260(05)81191-2 2-s2.0-0027411591 8435962 14 Kelly J. Wassif W. Mitchard J. Gardner W. N. Severe hyponatraemia secondary to beer potomania complicated by central pontine myelinolysis International Journal of Clinical Practice 1998 52 8 585 587 2-s2.0-3743122755 10622059 15 Davenport C. Liew A. Vic Lau P. Central pontine myelinolysis secondary to hypokalaemic nephrogenic diabetes insipidus Annals of Clinical Biochemistry 2010 47 1 86 89 10.1258/acb.2009.009094 19940203 16 Chang L. Harrington D. W. Mlikotic A. Swerdloff R. S. Wang C. Unusual occurrence of extrapontine myelinolysis associated with acute severe hypernatraemia caused by central diabetes insipidus Clinical Endocrinology 2005 63 2 233 235 10.1111/j.1365-2265.2005.02319.x 2-s2.0-23244457144 16060921 17 Go M. Amino A. Shindo K. Tsunoda S. Shiozawa Z. A case of central pontine myelinolysis and extrapontine myelinolysis during rapid correction of hypernatremia Clinical Neurology 1994 34 11 1130 1135 2-s2.0-0028630628 7729094 18 Norenberg M. D. Leslie K. O. Robertson A. S. Association between rise in serum sodium and central pontine myelinolysis Annals of Neurology 1982 11 2 128 135 10.1002/ana.410110204 2-s2.0-0020075529 7073246 19 Ayus J. C. Krothapalli R. K. Arieff A. I. Treatment of symptomatic hyponatremia and its relation to brain damage. A prospective study The New England Journal of Medicine 1987 317 19 1190 1195 10.1056/nejm198711053171905 2-s2.0-0023162473 3309659 20 Norenberg M. D. Central pontine myelinolysis: historical and mechanistic considerations Metabolic Brain Disease 2010 25 1 97 106 10.1007/s11011-010-9175-0 2-s2.0-77954144365 20182780 21 Bakst R. L. Kasper M. E. Central Pontine Myelinolysis in a Patient Admitted for Alcohol Withdrawal 2008 Hospital Physician 22 Lopez Bernus A. Muñoz-Galindo A. Moreirobarroso M. T. Velasco-Tirado V. Carpio-Perez A. Belhassen-Garcia M. Wernicke encephalopathy and central pontine myelinolysis: an underdiagnosed combination in alcoholics Journal of Neurological Sciences 2015 32 2 418 423 2-s2.0-84935083576 23 Sutamnartpong P. Muengtaweepongsa S. Kulkantrakorn K. Wernicke′s encephalopathy and central pontine myelinolysis in hyperemesis gravidarum Journal of Neurosciences in Rural Practice 2013 4 1 39 41 10.4103/0976-3147.105608 2-s2.0-84873443053 23546346 24 Graff-Radford J. Fugate J. E. Kaufmann T. J. Mandrekar J. N. Rabinstein A. A. Clinical and radiologic correlations of central pontine myelinolysis syndrome Mayo Clinic Proceedings 2011 86 11 1063 1067 10.4065/mcp.2011.0239 2-s2.0-80055078578 21997578 25 Rippe D. J. Edwards M. K. D’Amour P. G. Holden R. W. Roos K. L. MR imaging of central pontine myelinolysis Journal of Computer Assisted Tomography 1987 11 4 724 726 10.1097/00004728-198707000-00037 2-s2.0-0023256413 3597904 26 Yuh W. T. C. Simonson T. M. D'Alessandro M. P. Smith K. S. Hunsicker L. G. 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==== Front Stem Cells IntStem Cells IntSCIStem Cells International1687-966X1687-9678Hindawi Publishing Corporation 10.1155/2016/8364382Research ArticleFibronectin and Cyclic Strain Improve Cardiac Progenitor Cell Regenerative Potential In Vitro http://orcid.org/0000-0002-1055-5689French Kristin M. 1 2 http://orcid.org/0000-0001-7389-5245Maxwell Joshua T. 2 http://orcid.org/0000-0001-6315-2990Bhutani Srishti 1 2 Ghosh-Choudhary Shohini 1 Fierro Marcos J. 1 http://orcid.org/0000-0002-8090-0134Johnson Todd D. 3 Christman Karen L. 3 Taylor W. Robert 1 2 http://orcid.org/0000-0002-9239-2886Davis Michael E. 1 2 4 * 1Wallace H. Coulter Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, GA 30322, USA2Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA3Department of Bioengineering, Sanford Consortium for Regenerative Medicine, University of California, La Jolla, San Diego, CA 92037, USA4Children's Heart Research and Outcomes Center, Emory University and Children's Healthcare of Atlanta, Atlanta, GA 30322, USA*Michael E. Davis: michael.davis@bme.emory.eduAcademic Editor: Susan Liao 2016 16 8 2016 2016 836438220 4 2016 7 7 2016 14 7 2016 Copyright © 2016 Kristin M. French et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Cardiac progenitor cells (CPCs) have rapidly advanced to clinical trials, yet little is known regarding their interaction with the microenvironment. Signaling cues present in the microenvironment change with development and disease. This work aims to assess the influence of two distinct signaling moieties on CPCs: cyclic biaxial strain and extracellular matrix. We evaluate four endpoints for improving CPC therapy: paracrine signaling, proliferation, connexin43 expression, and alignment. Vascular endothelial growth factor A (about 900 pg/mL) was secreted by CPCs cultured on fibronectin and collagen I. The application of mechanical strain increased vascular endothelial growth factor A secretion 2–4-fold for CPCs cultured on poly-L-lysine, laminin, or a naturally derived cardiac extracellular matrix. CPC proliferation was at least 25% higher on fibronectin than that on other matrices, especially for lower strain magnitudes. At 5% strain, connexin43 expression was highest on fibronectin. With increasing strain magnitude, connexin43 expression decreased by as much as 60% in CPCs cultured on collagen I and a naturally derived cardiac extracellular matrix. Cyclic mechanical strain induced the strongest CPC alignment when cultured on fibronectin or collagen I. This study demonstrates that culturing CPCs on fibronectin with 5% strain magnitude is optimal for their vascular endothelial growth factor A secretion, proliferation, connexin43 expression, and alignment. National Science Foundation Graduate Research FellowshipDGE-1148903NIHR01HL113468 ==== Body 1. Introduction The field of cardiac progenitor cells is complex and controversial. Much attention recently has been devoted to determining if c-kit positive cardiac progenitor cells (CPCs) contribute to endogenous myocardial regeneration [1–5]. While this is an important question, it does not address the full regenerative potential of CPCs. In fact, regeneration of myocardial tissue is improved by exogenous cell implantation [6–8]. CPCs as cell therapy in ischemic heart disease have a measurable cardiac benefit in the clinic [9]. The CPC regenerative potential can be improved in vivo by preconditioning CPCs before delivery or by delivering CPCs with an engineered vehicle [9, 10]. Engineered microenvironments can improve the CPC regenerative potential in vitro for applications such as lab-on-a-chip. It is of great interest to elucidate CPC-microenvironment interactions for the successful design of therapeutics. The myocardium is a complex and dynamic tissue. Two signaling cues present in the myocardium are extracellular matrix and cyclic mechanical strain. It is unknown if cyclic strain affects CPC behavior or if these potential effects are dependent on the underlying substrate. All major cardiac cell types elongate and align perpendicular to an applied strain in vitro [11]. Further, mechanical strain regulates cell proliferation, hypertrophy, differentiation, and paracrine signaling [12, 13]. Extracellular matrix components alter CPC proliferation and differentiation [14]. To test the effect of extracellular matrix protein and mechanical strain on CPC behavior, a simplified, biomimetic approach based on endogenous signaling cues was taken. Healthy myocardium is composed of collagen I, collagen III, fibronectin, laminin, collagen IV, elastin, and proteoglycans [15, 16]. Endogenous CPCs exist in niches composed of laminin and fibronectin in low strain regions of the myocardium [17]. During development and disease, the myocardial extracellular matrix and mechanical strain are altered. Myocardial infarction serves as an example herein as these structural changes are well characterized and CPC therapy is currently being evaluated in these patients [18]. After a myocardial infarction, there is an initial decrease in collagen content and organization followed by increased fibronectin and collagen deposition [15, 19–23]. Global strains of 18% in the healthy myocardium decrease to 7% following myocardial infarction [24, 25]. To systematically evaluate the influence of mechanical strain and extracellular matrix components on CPC growth factor secretion, proliferation, connexin43 expression, and alignment, this study uses culture conditions spanning a controlled range of signaling cues. 2. Materials and Methods 2.1. Cardiac Progenitor Cell Isolation and Characterization All animal work was approved by Emory University's Institutional Animal Care and Use Committee. CPCs were isolated from adult male Sprague-Dawley rats (about 250 g) by removing the heart and homogenizing the tissue. The tissue homogenate was further digested with 1 mg/mL type-2 collagenase Hank's balanced salt solution (Worthington Biochemical) and passed through a 70 μm filter. Dynabeads (Dynal) were conjugated to a c-kit antibody (Santa Cruz H-300). Cells were then incubated with beads for 2 hours at 37°C prior to magnetic sorting. Sorted cells were plated on a T-75 tissue culture flask and expanded to confluence in growth media (Ham's F-12 (Mediatech) + 10% fetal bovine serum (Atlanta Biologicals) + 0.1 μg/mL basic fibroblast growth factor (Sigma) + 10 ng/mL leukemia inhibitory factor and human recombinant (Sigma) + 1x penicillin-streptomycin-glutamine (Cellgro)). After clonal expansion, CPCs were characterized by flow cytometry of c-kit (Santa Cruz H-300). Only clones with >90% c-kit expression were used for subsequent studies. 2.2. Cardiac Extracellular Matrix Isolation and Characterization Decellularized porcine ventricular extracellular matrix was obtained and processed as previously described [26–28]. Briefly, porcine ventricular tissue was isolated and cut into small rectangular pieces, rinsed in phosphate buffered saline (PBS, Fisher), and decellularized using 1% sodium dodecyl sulfate (SDS, Fisher) for 4-5 days. The decellularized cECM was then rinsed with water overnight, frozen at −80°C overnight, lyophilized (Labconco) overnight, and milled into a fine powder. The powder was digested using pepsin at 1 mg/mL in 0.1 M HCl (Fisher) for two days, as modified from a previously published protocol, at a ratio of 10 : 1 of ECM matrix to pepsin [28, 29]. The material was then raised to a basic pH by adding 1 M NaOH (Fisher) and brought to a salt concentration of 1x PBS through the addition of 10x PBS. Then, the material was brought to physiological pH of 7.4 using HCl and NaOH and diluted to 2 mg/mL using 1x PBS. The cECM was then frozen at −80°C overnight, lyophilized for 24 hours (Labconco), and stored at −80°C prior to use. Matrix solutions were made by reconstituting cECM in sterile water and then diluted to 1 mg/mL in 100 mM acetic acid. 2.3. Silanization of Bioflex Plates Working in a fume hood, 2 mL of 1.0 M NaOH (Sigma) was added to each well of a 6-well Bioflex plate (Flexcell International) and incubated for 1 hour at room temperature. Plates were washed in ddH2O thrice for five minutes. With the lids on, each well was treated with 1 mL of 4% (v/v) aminopropyltriethoxysilane (APTES; Sigma) in acetone for 10 minutes at room temperature. Plates were washed three times, treated with 2 mL 0.5% glutaraldehyde (Sigma) in ddH2O at room temperature for 30 minutes, and washed again. Matrix proteins were diluted to 100 μg/mL, with 1 mL for each well, as follows: naturally derived cardiac extracellular matrix (cECM; porcine) in 100 mM acetic acid, collagen I (COL; rat tail, Invitrogen) in 100 mM acetic acid, fibronectin (FN; human, BD Bioscience) in 1x PBS, laminin (LN; mouse, BD Bioscience) in 1x PBS, and poly-L-lysine (Sigma) in ddH2O. Matrix proteins were added to the appropriate wells and plates were incubated for 1 hour at 37°C. Plates were then washed once for 5 minutes in 1x PBS and treated with 1 mL of 1 M ethanolamine (Sigma) in ddH2O (pH 7.0) for 20 min to quench unreacted glutaraldehyde. Plates were washed three times with 1x PBS. To sterilize, plates were kept under ultraviolet light for 1 hour prior to use. 2.4. Application of Mechanical Tension CPCs were seeded at a density of 4 × 105 cells/well on functionalized Bioflex plates and incubated in treatment media (Ham's F-12 (Mediatech) + 0.1 μg/mL basic fibroblast growth factor (Sigma) + 1x insulin transferrin selenium (Cellgro) + 1x penicillin-streptomycin-glutamine (Cellgro)) for 6 hours prior to the application of mechanical tension. Tensile strain was applied through a Flexcell 5000 (Flexcell International). For this, Bioflex plates were loaded onto 25 mm cylindrical loading posts. A cyclic sinusoidal strain regimen of 1 Hz and 0.5 duty cycle, with an elongation magnitude of 5, 10, or 15%, was applied to the plates for 24 hours. Cells were maintained in 5% CO2 at 37°C throughout. 2.5. Strain Transfer Video Microscopy Untreated StageFlexer membranes (Flexcell International) were functionalized as described above. For improved visualization, CPCs were incubated for 2 hours at 37°C with anti-c-kit antibody conjugated Dynabeads prior to being seeded at 5 × 105 cells/membrane. Following 6-hour incubation in growth media, membranes were placed in a StageFlexer (Flexcell International) attached to the Flexcell 5000. A cyclic sinusoidal strain regimen of 1 Hz and 0.5 duty cycle, with elongation magnitudes of 5, 10, or 15%, was applied and bright field video was captured on an upright microscope (Amscope) with ToupView 3.7 at 5–20 frames per second. To quantify, a single cell containing two or more beads was identified. The distance between the two beads was traced in FIJI and strain was computed. This “measured strain” is compared to the strain reported by the Flexcell 5000. 2.6. Growth Factor ELISAs After 24 hours of mechanical strain, conditioned media were immediately collected from the wells and stored at −20°C. ELISA kits were purchased from RayBiotech for stem cell factor, hepatocyte growth factor, platelet-derived growth factor, and vascular endothelial growth factor A. The insulin-like growth factor 1 ELISA was purchased from Thermo Fisher Scientific. Experiments were performed according to the manufacturer's protocol. Briefly, diluted conditioned media or standard was added to the appropriate well and incubated for 2.5 hours at room temperature. Following washing, the appropriate biotin-conjugated antibody was added to each well and incubated for 1 hour at room temperature. Following washing, a horseradish peroxidase-conjugated streptavidin solution was added to each well and incubated for 45 minutes at room temperature. After additional washing, substrate was added to each well and incubated for 30 minutes at room temperature. Finally, stop solution was added to each well. Plates were read immediately at 450 nm on a BioTek Synergy2 spectrophotometer. 2.7. Western Blot Cells were lysed in NP-40 lysis buffer with protease and phosphatase inhibitors and incubated overnight at 4°C. Lysates were spun for 5 minutes at 10,000 ×g and the supernatant was collected to remove insoluble protein. Protein quantification was performed by microBCA (Thermo Scientific) according to the manufacturer's protocol. Samples were prepared by adding 35 μg protein to appropriate amounts of 5x Laemmli buffer and water to yield a final volume of 35 μL and then boiled for 8 minutes at 95°C. Each sample was then loaded on 10% or 12% SDS-PAGE gel. Electrophoresis was performed and gels were transferred to nitrocellulose membranes. Membranes were immediately blocked with 3% milk in Tris-buffered saline with 1% Tween-20 (TBS-T) for 1 hour at room temperature. Membranes were washed 3 times in 1x TBS-T and then immersed in a 1: 1000 primary antibody (PCNA: Santa Cruz; Cnx43: Sigma; GAPDH: Santa Cruz). All antibody solutions were made in 1% milk in 1x TBS-T and incubated with membranes overnight at 4°C prior to 3 washes with 1x TBS-T. Membranes were incubated at room temperature for 1 hour in 1: 5000 dilution of secondary antibody. The secondary antibody was HRP-conjugated goat anti-rabbit or goat anti-mouse (Bio-Rad). Membranes were exposed on film and results were quantified with ImageJ. 2.8. Fluorescence Microscopy After 24 hours of mechanical strain, cells were immediately fixed in 4% paraformaldehyde (Sigma) for 20 minutes at room temperature. Following three washes in 1x PBS, the cells were permeabilized with 0.1% triton in (Sigma) 1x PBS. Cells were again washed and then blocked in 3% bovine serum albumin (Sigma) for 1 hour at room temperature. Cells were then stained with 10 μg/mL fluoresceinyl-maleimide (Sigma) for 1 hour at room temperature in the absence of light, followed by washing, and then 1 μg/mL DAPI (Invitrogen) for 10 minutes. Select wells were additionally stained for aurora B (Abcam). Cells were washed prior to imaging on an Olympus IX70 inverted fluorescent microscope. Cell characteristics were quantified by importing images into CellProfiler 2.1.0. The images were analyzed according to the following pipeline: (1) images were resized by 0.25; (2) images were converted to greyscale; (3) nuclei were identified by intensity using a global threshold, automatic smoothing, and a threshold correction factor of 1; (4) cells were identified around nuclei by intensity through propagation with per object Otsu thresholding, automatic smoothing, and a threshold correction factor of 0.8; (5) cell size, shape, and orientation were measured; (6) images were exported to spreadsheet. Exported data was compiled to calculate cell size, spread area, and alignment. Alignment scores were calculated by measuring the angle between the major axis of each cell and the horizon, taking the standard deviation of all the angles and computing 100 ∗ the percent difference of the standard deviation from a Gaussian distribution or 100∗(90/sqrt(3) − stdev)/(90/sqrt(3)). Circular math was employed to correct for the orientation of cells in orthogonal images. 2.9. Statistics All data was analyzed by one-way ANOVAs to establish specific effects of matrix or strain except where noted. All one-way ANOVA posttests are Tukey's multiple comparison tests allowing for the comparison of all groups to each other. GraphPad Prism 5 was used for all statistical analysis. 3. Results and Discussion 3.1. CPCs Strain with Underlying Membrane To determine if CPCs cultured under the same strain magnitude experienced similar strains, independent of extracellular matrix coating, live cell video microscopy was performed using a StageFlexer. A notable (p < 0.05) increase in cell strain was observed with an increase in applied strain (Figure 1). The measured strain corresponded with the strain reportedly generated by the StageFlexer. This device has a smaller volume than the Bioflex 6-well plate used in the remainder of the study, limiting the maximum achievable strain magnitude to 7%. No differences in measured strain were present between matrix groups. This suggests that regardless of the extracellular matrix coating CPCs grossly received the same applied strain. Any differences observed between matrix coating groups of the same strain magnitude will therefore be due to biochemical input from the extracellular matrix. Two other points are important for interpreting the data. First, the naturally derived cardiac extracellular matrix (cECM) contains each of the other matrix proteins evaluated in this study and represents a complex mixture. Second, the stiffness of PDMS (Bioflex plates) is an order of magnitude lower than tissue culture polystyrene and therefore even “static” conditions may not represent typical culture conditions. The effect of stiffness on CPC behavior is evaluated elsewhere [30, 31]. 3.2. Strain Induces Vascular Endothelial Growth Factor Secretion The CPC secretome may confer regenerative potential through growth factors [9]. Growth factors aid in recruitment or differentiation of endogenous progenitor cells and the survival of mature endogenous cells. Toward this end, several growth factors were examined in the conditioned media of strained CPCs. For all of the following studies, four matrix proteins (laminin: LN, fibronectin: FN, collagen I: COL, and cECM) and poly-L-lysine were evaluated at four strain magnitudes of 0, 5, 10, and 15%. Vascular endothelial growth factor A (VEGF) was detected in CPC conditioned media. There was a marked increase in VEGF (Figure 2) in conditioned media from CPCs cultured on LN in the presence of 5, 10, and 15% (730, 729, and 699 pg/mL, resp.) strain as compared to unstrained groups (159 pg/mL; p < 0.01). Similarly, conditioned media from CPCs strained at 10% (1048 pg/mL) on cECM also showed higher VEGF than in unstrained controls (420 pg/mL; p < 0.05). FN and COL induced VEGF secretion at all strain magnitudes. This suggests that strain is an important modulator of VEGF secretion by CPCs. Extracellular matrix did not change VEGF concentration at a given strain magnitude. This data suggests that static culture of CPCs is detrimental to VEGF secretion. In addition to its angiogenic effects, VEGF acts through paracrine and autocrine effects to increase Cnx43 expression in myocytes [32, 33]. Neither platelet-derived growth factor nor insulin-like growth factor or stem cell factor was detected. Hepatocyte growth factor was detected in CPC conditioned media in low quantities (<10 μg/mL, data not shown). Hepatocyte growth factor plays a role in cell proliferation, migration, survival, and angiogenesis [34]. While strain magnitude affected hepatocyte growth factor concentration, given the low absolute concentrations, these effects may not be biologically relevant. 3.3. CPC Proliferation Increased on Fibronectin An increase in CPC number via proliferation would improve their regenerative potential by increasing the number of cells available for therapy [9]. Improved proliferation would also decrease the amount of time to therapy for autologous intervention. Across all groups, as much as 2% of the CPCs were visibly dividing (Figure 3(c)). Dividing cells were identified by nuclear condensation, division, and rounded cytoplasm (Figure 3(a)). CPC division was confirmed by the presence of aurora B kinase (Figure 3(b)). A 270-fold difference was observed in CPC proliferation across these culture conditions. The highest observed number of dividing cells was on FN at 5% strain (2.7% dividing) and the lowest was on PLL at 0% strain (0.01% dividing). Unstrained CPCs seeded on FN, COL, or cECM had an increased number of dividing cells (1.2%, 1.0%, and 0.9%, resp.) as compared to CPCs cultured on PLL (p < 0.05). At 5% strain, significantly more CPCs were dividing on FN (2.7%) as compared to those on PLL (0.3%; p < 0.01) and LN (0.9%; p < 0.05). Fibronectin has been demonstrated to be essential for CPC proliferation and survival [35]. The effects of matrix coating are attenuated at 10 and 15% mechanical strains. The proliferative capacity of CPCs is likely underestimated by this method since it only captures dividing cells at a single time point. To address this shortcoming, CPC proliferation was also assessed by expression of proliferating cell nuclear antigen (PCNA). FN induces the highest PCNA expression under static culture conditions (Figure 4). At 5% strain, FN and laminin trended toward increased proliferation. Matrix did not affect the number of dividing cells at 15%, suggesting that mechanical inputs may override the effect of the matrix at higher strains. The upregulation of PCNA by matrix conditions was varied depending on the magnitude of cyclic strain. This suggests that the extracellular matrix surrounding a CPC may dictate the transmission of forces applied to the cell. Two key possibilities may explain this effect. First, the adhesion strength of CPCs may vary by extracellular matrix coating leading to varied levels of basal stress in the cell. Stress across the plasma membrane or cytoskeleton can lead to activation of molecular pathways or changes in chromatin conformation. Alternatively, as biochemical entities, different extracellular matrix proteins may activate different biochemical signaling pathways through adhesion to different cell surface receptors. For example, CPCs may adhere less tightly to LN and therefore require a greater force to induce the same stress in the plasma membrane. This would make them more sensitive to changes in strain magnitude. Future work could investigate these potential mechanisms. Together, the PCNA expression, aurora B kinase staining, and CPC phenotype suggest that CPCs are more likely to proliferate under culture conditions that mimic a niche or infarct microenvironment (i.e., low strain, high FN, and/or LN) than a healthy microenvironment [17]. Culture of CPCs on FN at 5% strain will improve CPC number in vitro. This also mimics observations that cells are more proliferative in the young heart, where FN content is high, as compared to the correlation of laminin prevalence in the adult heart with lower proliferative rates [36]. 3.4. Connexin43 Expression Decreases at Higher Strain Magnitudes Connexin43 (Cnx43) expression facilitates gap junction formation and is important for cardiomyocyte maturation and tissue integration. Alignment and mechanical strain induce Cnx43 expression in relevant cell types [37–39]. Cnx43 expressing cells better integrate when applied to the myocardium [40]. Cnx43 also improves cell survival and proliferation [41, 42]. Western blots were performed to assess Cnx43 expression in strained CPCs. Representative blots and quantification are reported in Figure 5. Unstrained CPCs cultured on FN had 40–50% more Cnx43 (1.4-fold over glyceraldehyde-3-phosphate dehydrogenase) than those cultured on PLL (1.0-fold; p < 0.05), LN (0.9-fold; p < 0.05), and cECM (1.0-fold; p < 0.05). At 5% strain, Cnx43 was maintained on FN (1.2-fold) as compared to that on PLL (0.6-fold; p < 0.05). At 10 and 15% strains, Cnx43 expression was not matrix dependent. This suggests that FN is an important signal for Cnx43 expression and that CPCs are more likely to form gap junctions when cultured on FN at low strain magnitudes. Fibronectin also induces Cnx43 expression in neonatal rat ventricular myocytes [32]. However, Cnx43 expression decreased with increasing strain for CPCs on COL (p < 0.01) and cECM (p < 0.05). This also suggests that CPCs are more likely to form gap junctions under low strain magnitudes. While expression alone is not proof of functional gap junction formation, increased Cnx43 expression suggests that the cells are better primed for functional gap junction formation and electrical propagation. Again, culture of CPCs on FN at low strain magnitudes is the optimal condition for CPC culture. 3.5. Strain Induces CPC Alignment Alignment organizes cells to be more tissue-like and has been shown to improve stem cell differentiation [37]. Representative images of CPCs from culture condition are shown in Figure 6(b) and a quantified alignment score is present in Figure 6(a). Consistent with literature, CPCs align perpendicular to the principle axis of applied strain [11]. With the application of 5% strain, more CPCs aligned on COL (58%) than on PLL (18%; p < 0.01). At 15%, CPCs aligned better on FN (42%) and COL (54%) as compared to those on PLL (15%; p < 0.001). This is expected as cells adhere to PLL through electrostatics rather than integrin binding. Within each matrix group, the application of strain had an effect on alignment. Notably, CPCs cultured on FN aligned better when strained at 10% (51%; p < 0.01) and 15% (42%; p < 0.05) strain magnitudes as compared to unstrained (12% alignment) cells. For CPCs cultured on COL, alignment was increased at 5% (58%; p < 0.05) and 10% (60%; p < 0.05) strain magnitudes as compared to unstrained (17% alignment) cells. Similarly, on cECM there was an increase in alignment at 10 (36%; p < 0.05) and 15% (35%; p < 0.01) strain magnitudes as compared to unstrained (12% alignment) CPCs. Taken together, CPCs cultured on cECM, FN, or COL had 3- to 4-fold increases in alignment with mechanical strain. This demonstrates that CPCs align with mechanical strain, but that alignment values did not differ within a matrix group with increasing magnitudes of strain above 5%. This suggests that given the appropriate matrix cues and any magnitude of cyclic strain CPCs will align. Therefore, the decrease in Cnx43 and proliferation that is observed with an increase in strain are not due to differences in cell alignment. Future work would benefit from evaluating the differentiation of CPCs under each of these culture conditions. 4. Conclusion It is of great interest to elucidate the interaction of CPCs with their microenvironment to improve engineered microenvironment and cell therapy. This study evaluates two important signaling moieties from the myocardium, extracellular matrix, and mechanical strain, in a combinatorial approach. The regenerative potential of CPCs is assessed through growth factor secretion, proliferation, Cnx43 expression, and CPC alignment. CPCs cultured on FN, COL, and cECM secreted VEGF independent of mechanical strain magnitude. Mechanical strain at a magnitude of 5% improved CPC proliferation and Cnx43 expression. These effects were most profound when the CPCs were cultured on FN. Mechanical strain of all evaluated magnitudes induced alignment of CPCs cultured on FN, COL, and cECM. CPCs have the highest regenerative potential in vitro under culture conditions of FN at 5%. These findings highlight the importance of culture condition for CPC behavior. Future work can build upon the importance of FN and low strain magnitude discussed here toward engineering a more complex microenvironment integrating additional signaling cues. Acknowledgments The authors would like to acknowledge Dr. Ashley Brown for her silanization protocol. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant no. DGE-1148903 (to Kristin M. French) and the NIH (R01HL113468 to Karen L. Christman). Abbreviations CPC:Cardiac progenitor cell PLL:Poly-L-lysine LN:Laminin FN:Fibronectin COL:Collagen I cECM:Naturally derived cardiac extracellular matrix PCNA:Proliferating cell nuclear antigen Cnx43:Connexin43 VEGF:Vascular endothelial growth factor. Disclosure Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Competing Interests Dr. Christman is a cofounder, board member, and holds equity in Ventrix, Inc. Figure 1 Cell strain. CPCs were seeded on the appropriate matrix for 6 hours. Video microscopy (19 frames per second) captured the motion of beads tethered to CPCs under cyclic 1 Hz strain. (a) Representative distance tracings from CPCs cultured on cECM; programmed strain is reported on graph. (b) Strain magnitude effects on measured strain. One-way ANOVA with Tukey's multiple comparison test; bars represent mean + SEM; # p < 0.05, ## p < 0.01, and #### p < 0.001; n = 3–10; 3.5, 7.0: strain magnitude (%), PLL (brown): poly-L-lysine, LN (green): laminin, FN (purple): fibronectin, COL (blue): collagen I, and cECM (red): naturally derived cardiac extracellular matrix. Figure 2 Strain improves VEGF secretion in CPC conditioned media. CPCs were seeded on each matrix for 6 hours and then cyclic strain was applied for 24 hours. Conditioned media were evaluated by ELISA. One-way ANOVA with Tukey's multiple comparison test; bars represent mean + SEM; ∗ p < 0.05; n = 3-4; x-axis: 0–15: strain magnitude (%) and VEGF: vascular endothelial growth factor A. Figure 3 Fibronectin increases CPC division at low strain magnitudes. CPCs were seeded on each matrix for 6 hours and then cyclic strain was applied for 24 hours. (a) Representative image showing nuclear condensation and cytokinesis. Blue: DAPI and green: FITC-maleimide. Insert shows magnification of a dividing cell. (b) Representative image of aurora B kinase staining. Blue: DAPI, green: FITC-maleimide, and red: aurora B kinase. (c) Quantified results; one-way ANOVA with Tukey's multiple comparison test; bars represent mean + SEM; ∗ p < 0.05, ∗∗ p < 0.01, and ∗∗∗ p < 0.001; n = 4–6; PLL (brown): poly-L-lysine, LN (green): laminin, FN (purple): fibronectin, COL (blue): collagen I, and cECM (red): naturally derived cardiac extracellular matrix. Figure 4 FN induces PCNA expression. CPCs were seeded on each matrix for 6 hours followed by 24 hours of cyclic strain and lysed. Cell lysate was evaluated by western blot. (a) Representative blots. (b) Quantification by densitometry; n = 4-5; PLL (brown): poly-L-lysine, LN (green): laminin, FN (purple): fibronectin, COL (blue): collagen I, cECM (red): naturally derived cardiac extracellular matrix, PCNA: proliferating cell nuclear antigen, and ∗ represents p < 0.05 by ANOVA. Figure 5 CPC connexin43 expression is highest at low strain magnitudes. CPCs were seeded on each matrix for 6 hours and then cyclic strain was applied for 24 hours. Connexin43 expression was assessed by western blot. (a) Representative blots and (b-c) densitometry quantification. One-way ANOVA with Tukey's multiple comparison test; bars represent mean + SEM; ∗ p < 0.05; n = 4–7. (b) Matrix-dependent effects. (c) Strain magnitude-dependent effects. PLL (brown): poly-L-lysine, LN (green): laminin, FN (purple): fibronectin, COL (blue): collagen I, cECM (red): naturally derived cardiac extracellular matrix, 0–15: strain magnitude (%), and Cnx43: connexin43. Figure 6 Strain induces CPC alignment. CPCs were seeded on each matrix for 6 hours and then cyclic strain was applied for 24 hours. (a) Quantification of strain-induced matrix-dependent alignment. Kruskal-Wallis one-way ANOVA with Dunn's multiple comparison tests; bars represent mean + SEM; ∗ p < 0.05 and ∗∗ p < 0.01; n = 4–7; PLL (brown): poly-L-lysine, LN (green): laminin, FN (purple): fibronectin, COL (blue): collagen I, and cECM (red): naturally derived cardiac extracellular matrix. (b) Representative cell strain images. Blue: DAPI and green: FITC-maleimide; arrow indicates principle direction of strain; 0–15: strain magnitude (%). ==== Refs 1 Beltrami A. P. Barlucchi L. Torella D. Adult cardiac stem cells are multipotent and support myocardial regeneration Cell 2003 114 6 763 776 10.1016/S0092-8674(03)00687-1 2-s2.0-10744228523 14505575 2 Ellison G. M. Vicinanza C. Smith A. J. Adult c-kitpos cardiac stem cells are necessary and sufficient for functional cardiac regeneration and repair Cell 2013 154 4 827 842 10.1016/j.cell.2013.07.039 2-s2.0-84882759023 23953114 3 van Berlo J. H. Kanisicak O. Maillet M. 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==== Front Gastroenterol Res PractGastroenterol Res PractGRPGastroenterology Research and Practice1687-61211687-630XHindawi Publishing Corporation 10.1155/2016/8454823Research ArticleGiant Serous Cystadenoma of the Pancreas (⩾10 cm): The Clinical Features and CT Findings http://orcid.org/0000-0001-7171-6346Liu Qing-Yu 1 2 * Zhou Jun 3 Zeng Yu-Rong 2 Lin Xiao-Feng 2 Min Jun 4 1Department of Radiology, Zengcheng People's Hospital, 1 Guang Ming Dong Road, Zengcheng, Guangdong 511300, China2Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yan Jiang Xi Road, Guangzhou, Guangdong 510120, China3Department of Gastrointestinal Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yan Jiang Xi Road, Guangzhou, Guangdong 510120, China4Department of Hepatobiliary Pancreatic Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yan Jiang Xi Road, Guangzhou, Guangdong 510120, China*Qing-Yu Liu: liu.qingyu@163.comAcademic Editor: Riccardo Casadei 2016 16 8 2016 2016 845482323 6 2016 20 7 2016 Copyright © 2016 Qing-Yu Liu et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Purpose. To report the clinical features and CT manifestations of giant pancreatic serous cystadenoma (≥10 cm). Methods. We retrospectively reviewed the clinical features and CT findings of 6 cases of this entity. Results. All 6 patients were symptomatic. The tumors were 10.2 cm–16.5 cm (median value, 13.0 cm). CT imaging revealed that all 6 cases showed microcystic appearances (n = 5) or mixed microcystic and macrocystic appearances (n = 1). Five patients with tumors at the distal end of the pancreas received distal pancreatectomy. Among these 5 patients, 2 patients underwent partial transverse colon resection or omentum resection due to close adhesion. One patient whose tumor was located in the pancreatic head underwent pancreaticoduodenectomy; however, due to encasement of the portal and superior mesenteric veins, the tumor was incompletely resected. One patient had abundant draining veins on the tumor surface and suffered large blood loss (700 mL). After 6–49 months of follow-up the 6 patients showed no tumor recurrence or signs of malignant transformation. Conclusions. Giant pancreatic serous cystadenoma necessitates surgical resection due to large size, symptoms, uncertain diagnosis, and adjacent organ compression. The relationship between the tumors and the neighboring organs needs to be carefully assessed before operation on CT image. ==== Body 1. Introduction Pancreatic serous cystadenoma is a common type of pancreatic cystic tumor and accounts for 10–15% of all cases of pancreatic cystic tumor and 1-2% of primary pancreatic tumors [1]. These tumors are often small at diagnosis, 31 mm (1–238 mm) on average [2]. Patients usually (61%) do not exhibit relevant clinical symptoms but may develop symptoms as the tumors grow larger [2]. Because most of these tumors display benign biological behaviors, asymptomatic patients with small tumors are often recommended for conservative treatment [2]. Giant pancreatic serous cystadenoma (diameter ≥ 10 cm) is very rare, and only sporadic cases have been reported [3–11]. In this study, we examined the clinical features and CT findings of 6 cases of giant pancreatic serous cystadenoma. To our knowledge, this is the largest series being reported. 2. Materials and Methods 2.1. Patients We searched clinical data of Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, between January 2003 and December 2015, and a total of 57 cases of pancreatic cystic tumors that were pathologically confirmed were found, including 28 cases of serous cystadenoma, of which 6 (10.5%) were giant pancreatic serous cystadenoma (diameter ≥ 10 cm). This retrospective study, which did not require consent from the patients, was approved by the ethics committee of the hospital. Before operation, all 6 patients received abdominal 64-slice spiral CT examination (Sensation 64, Siemens Medical Solutions, Erlangen, Germany), including plain scans and triphasic enhanced scans. A nonionic contrast agent (Iopromide, 370 mgI/mL, Schering, Erlangen, Germany) was administered via the antecubital vein using a pressure injector at 3.5 mL/s with a dose of 1.5 mL/kg. Using the bolus tracer function, arterial phase images were collected 10 sec after the intensification threshold of the celiac level aorta reached 100 HU. Portal phase images and delayed phase images were collected 15 and 90 sec after the completion of arterial phase scanning, respectively. The slice thickness of CT image was 3.0 mm. CT angiography (CTA) was accomplished at the CT postprocessing workstation. 2.2. The Clinical Features and CT Findings Assessment The electronic clinical data of these patients were retrospectively analyzed, including gender, age, symptoms, relevant laboratory examination results (e.g., AFP, CEA, CA125, CA199, TDIL, and DBIL), surgical approach, and prognosis. Two abdominal radiologists retrospectively evaluated the CT images using the picture archiving and communications system. The radiologists were both aware that the 6 patients were diagnosed with pancreatic tumor but did not know other information, including pathological data. Image reviews were done jointly and by consensus. The following CT findings were determined: tumor location, size, shape, capsule, calcification, morphological pattern, enhancement pattern, pancreatic or bile duct dilatation, and other relevant observations. Based on their morphological patterns, the tumors were classified as microcystic, macrocystic (or oligocystic), mixed microcystic and macrocystic, and solid type [2]. The density of pancreatic masses was compared with adjacent normal pancreatic tissue and divided into hypodensity, isodensity, or hyperdensity. 3. Results 3.1. The Clinical Properties of Giant Pancreatic Serous Cystadenoma The clinical characteristics of the 6 patients with giant pancreatic serous cystadenoma are summarized in Table 1. The patients were aged between 48 and 68 years (median age: 64 years) and included 3 females and 3 males. All patients exhibited symptoms, primarily abdominal bloating, abdominal pain, palpable mass, or vomiting. Laboratory examination (e.g., AFP, CEA, CA125, CA199, TDIL, and DBIL) showed no abnormalities except in 1 patient (case 4), who had concurrent gastric stromal tumor and rectal adenocarcinoma and presented with an elevated CEA level of 231 ng/mL (normal: 0–5 ng/mL). In this patient, the common bile duct was surrounded and compressed by the tumor and exhibited slight elevation of TBIL and DBIL levels (33.8 μmol/L and 14.16 μmol/L, resp.; normal ranges for these are 3.4–17.1 μmol/L and 0–3.4 μmol/L, resp.). All six patients were operated on due to uncertain diagnosis (n = 4), symptoms (n = 6), large size (n = 6), and adjacent organ compression (n = 1). The pancreatic tumors were 10.2–16.5 cm in size (median, 13.0 cm). In 5 patients, the tumors were located at the body-tail of the pancreas; the patients therefore received distal pancreatectomy (4 patients also underwent splenectomy). Among these 5 patients, 2 patients (case 5 and case 2) underwent concurrent partial transverse colon resection or omentum resection due to tight adhesion. One patient (case 4) whose tumor was located in the pancreatic head underwent pancreaticoduodenectomy, but the resection was incomplete because of encasement of the portal and superior mesenteric veins; this patient also underwent portal vein repair because of the intraoperative portal vein injury. One patient (case 2) had apparent draining veins on the tumor surface and suffered large blood loss (700 mL); 1 patient (case 5) received concurrent resection of colon cancer and gastric stromal tumor and had a blood loss of 3,000 mL; the other 4 patients had blood loss of 100–200 mL during operation. Among all 6 patients, there was 1 case of postoperative infection and 1 case of mild pancreatic leak. After 6–49 months of postoperative follow-up, the 6 patients showed no tumor recurrence, signs of malignant transformation, or signs of pancreatic compromise. The tumors of the 6 patients generally had clear boundaries without capsule. The gross specimens manifested as honeycomb-like shapes (n = 5) or honeycomb-like shapes with macrocysts (n = 1). The tumor was composed of numerous tiny thin-walled cysts (averaged 1–12 mm in diameter) filled with serous fluid. In addition, the tumors had stellate fibrous scars in the center (Figures 1 and 2). Serous cystadenoma was pathologically confirmed without any malignant traits. 3.2. CT Findings The tumors of all 6 patients displayed lobulated appearance without capsule. Central calcification was showed in 5 patients. The morphological pattern of the tumor was microcysts (n = 5) or mixed microcystic and macrocystic type (n = 1). The tumors were of low density with central scars on precontrast CT scanning. The septa of cysts and central scars showed early enhancement on arterial phase images and decreased enhancement on the portal phase images, manifesting rapid wash-out enhancement pattern (Figures 1 –3). Cholangiectasis (n = 1) (case 4), encasement or compression of splenic arteries and veins (n = 6), adhesion to the stomach wall (n = 2), compression of left renal vein (n = 2), and adhesion to the transverse colon (n = 1) were noted on CT image. The tumor was located at the pancreatic head in 1 case (case 4), which showed encasement of the portal vein, superior mesenteric vein, and common bile duct. The apparent feeding arteries and draining veins on the surface (n = 3) and concurrent regional portal hypertension (n = 2) were clearly revealed on CT angiography (CTA) (Table 1). The 6 patients exhibited no signs of metastasis at diagnosis. 4. Discussion As imaging technologies improve and are more widely applied, the discovery of asymptomatic cystic tumors of the pancreas has increased. Pancreatic serous cystadenoma is a common type of benign pancreatic cystic tumor and is different from other types of pancreatic cystic tumors (e.g., mucinous cystadenoma and intraductal papillary mucinous neoplasms) that have overt or potential malignancy [12]. Pancreatic serous cystadenoma is typically found in women (accounting for 74% of cases) with a mean age of 58 years (16–99 years), and the tumor is usually located at the body-tail of the pancreas [2]. Giant serous cystadenoma (diameter ≥ 10 cm) is rare and accounts for 10.5% of surgically treated cases of pancreatic cystic tumors in our hospital. We herein retrospectively analyzed cases of giant pancreatic serous cystadenoma that were treated in this hospital as well as previously reported cases in English literatures between 2005 and 2015 (Table 1). The results showed that this entity was more likely to occur in women (76.5%, 13/17) with a mean age of 65.5 years and that pancreatic head involvement (58.8%, 10/17) was slightly more common than the other pancreatic areas. Pancreatic serous cystadenomas are typically small, with a mean diameter of 31 mm [2]. During the follow-up period, the tumors maintained a stable size (57%) or grew slowly (37%, 0.4 cm/year) [2]. Due to their small size and slow growth, the tumors exerted almost no influence on neighboring tissues; therefore, the patients generally did not develop symptoms. However, giant pancreatic serous cystadenomas tend to adhere to, compress, encase, or even infiltrate into surrounding organs due to their large size. Consequently, the patients (70%) are likely to develop symptoms [2, 4], which mainly include abdominal pain, pancreatic-biliary symptoms, and other symptoms (abdominal mass, asthenia, nausea, and vomiting) (Table 1). Obstructive jaundice is very rarely reported [13]. Laboratory examination of giant pancreatic serous cystadenoma usually finds no elevated levels of tumor markers unless the tumors develop malignant transformation or the patient has concurrent malignant tumors at other sites. Morphologically, pancreatic serous cystadenoma can be classified as microcystic, macrocystic (or oligocystic), mixed microcystic and macrocystic, and solid type [2, 14]. During follow-up visits, the tumors can change morphologically (e.g., microcystic type changes to macrocystic type, macrocystic type changes to mixed type, or macrocystic type changes to microcystic type) [1]. Microcystic (45%) and macrocystic types (32%) are most common patterns; the next is mixed (18%) and solid (5%) types [2]. Giant pancreatic serous cystadenoma predominantly exhibits the microcystic type (58.8%, 10/17), followed by macrocystic (or oligocystic) type (35.3%, 6/17) and mixed type (5.9%, 1/17) (Table 1). Giant pancreatic serous cystadenoma showed clear solitary mass with lobulated appearance on CT images. The microcystic type was characterized by numerous tiny cysts (subcentimeter) and a honeycomb appearance. However, the macrocystic (or oligocystic) type featured multiple large cysts (>2 cm) or unilocular cyst. The mixed type had the characteristics of both microcystic type and macrocystic type. These cysts of serous cystadenoma were divided by fibrous septa that can coalesce into a central scar. The septa or scars may exhibit calcification [14–16]. The fibrous septa displayed a rapid wash-out enhancement pattern on enhanced CT scanning. Although calcifications with a central scar resembling sun explosions are pathognomonic for pancreatic serous cystadenoma on CT examination, this sign is not usually detected [9] and has not been found in cases of giant serous cystadenomas reported by us or others (Table 1). It is necessary to differentiate pancreatic serous cystadenoma from other cystic tumors (e.g., mucinous tumors or intraductal papillary mucinous neoplasms) on CT exam, particularly macrocystic (or oligocystic) type and mixed type [12, 14]. Pancreatic serous cystadenoma of macrocystic (or oligocystic) type manifests as lobulated polycystic (or unilocular) lesions, whereas pancreatic mucinous tumor is characterized by a smooth boundary without a lobulated contour, an enhanced thick wall, and peripheral calcification. Furthermore, intraductal papillary mucinous neoplasms manifest as either pleomorphic or a clubbed, fingerlike cystic masses that connect to the dilated pancreatic duct [12, 14]. Endoscopic ultrasonography can not only clearly reveal the internal structure of tumors, such as dense microcystic clusters but also guide fine needle aspiration biopsy; therefore, this technique is valuable for diagnosis of pancreatic serous cystadenoma [1]. Although pancreatic serous cystadenoma is generally considered a slow-growing benign tumor, symptomatic or giant serous cystadenoma has been proposed to exhibit a high risk of malignant potential [1]. Strobel et al. reported that 3% of serous cystadenoma cases were malignant [17]. However, in the multinational study which was reported by Jais et al. [2], only three serous cystadenocarcinomas (0.1%) were recorded. Most reported cases of malignant serous cystic neoplasms had tumor sizes of greater than 10.0 cm [2, 18–23]. Among 10 cases of pancreatic malignant serous cystic neoplasms reported by Matsumoto et al. [18], 8 had tumor diameters greater than 10 cm, indicating that serous cystadenomas might acquire malignant potential according to the extent of growth. Although the diameter of malignant serous cystadenoma was usually larger compared with nonmalignant group, there is no report describing the correlation between size and malignancy in serous cystadenomas due to paucity of cases. Malignant serous cystic neoplasms exhibit a low level of malignancy and indolent clinical course. The preoperative diagnosis of malignant serous cystic neoplasms remains challenging. Currently, the diagnosis of malignant serous cystic neoplasms relies pathologically on distant metastasis beyond pancreatic and peripancreatic bed [2] or apparent local filtration or lymphatic metastasis [18, 19]. Organs that are infiltrated locally by malignant serous cystic neoplasms include the spleen (8%), small intestine (4%), stomach (4%), adrenal gland (4%), and microscopic blood vessels/nerve infiltration; the organs exhibiting metastasis include (in order of frequency) the liver (35%), followed by local lymph nodes (12%), bone marrow (4%), and lung (4%) [19, 21]. Treatment for pancreatic serous cystadenoma remains controversial. It is suggested that surgery should be recommended for uncertain cystic tumor (i.e., cases without definitive diagnosis of serous cystadenoma), symptomatic serous cystadenoma (diameter ≥ 4.0 cm), or tumors with rapid growth (annual growth of greater than 4 mm). However, small or asymptomatic pancreatic serous cystadenoma should be provided with conservative treatment and close follow-up [2, 15, 24]. For cases of giant serous cystadenoma, surgery is recommended due to large size, symptoms, uncertain diagnosis, and adjacent organ compression. The relationship between a giant serous cystadenoma and the neighboring organs, blood vessels, and bile duct is critical for determining tumor resectability. Giant pancreatic serous cystadenomas may develop tight adhesion to the colon [4, 6] and omentum; thus, concurrent removal of these structures is required. Patients with the portal vein, superior mesenteric vein encasement, or adherence are subjected to vascular resection and reconstruction [7] or incomplete resection with the blood vessels preservation. Laparoscopic fenestration or dome resection with chemocautery is considered for patients with macrocystic (or oligocystic) type tumors [3, 11]. For patients who are ineligible for major operations (e.g., elderly or high-risk individuals), palliative surgery also achieves sound outcome with low mortality and low morbidity [4] (Table 1). If the tumor has abundant feeding arteries or draining veins, the patient may be at great risk of intraoperative massive hemorrhage, which can be prevented by preoperative embolization of the feeding artery [7]. 5. Conclusion Due to their large size, giant pancreatic serous cystadenomas usually are symptomatic. Although this type of tumor displays characteristic findings on CT scanning, it is necessary to differentiate this tumor from other pancreatic cystic tumor types. In general, giant pancreatic serous cystadenomas require surgical excision, and the relationship between the tumor and the neighboring organs, blood vessels, and bile duct is critical for determining tumor resectability. Ethical Approval The study was reviewed and approved by the Science and Research Office of Sun Yat-sen Memorial Hospital (Guangzhou). Consent This retrospective study did not require consent from the patients and was approved by the ethics committee of the hospital. Competing Interests There are no competing interests to report. Authors' Contributions Qing-Yu Liu designed the study and wrote the paper; Xiao-Feng Lin and Yu-Rong Zeng contributed to the analysis and interpretation of imaging data; Jun Zhou and Jun Min participated in the acquisition, analysis, and interpretation of clinical data. Figure 1 A 48-year-old male patient with a giant serous cystadenoma of the pancreas. (a) A low-density pancreatic tumor was noted on CT plain scan. (b) The tumor showed early enhancement with abundant draining vein (arrow) on arterial phase image. (c) The tumor showed honeycomb-like shapes with decreased enhancement on portal phase image. Left renal vein compression was noted (arrow). (d) The feeding splenic artery (short arrow) and draining veins (long arrow) were showed on CT angiography (CTA). (e) The tumor specimen was honeycomb-like appearance with central scars. Figure 2 A 67-year-old male patient with a giant serous cystadenoma of the pancreas. (a) A low-density, lobulated tumor with dotted calcification and isodense central scar was noted on CT plain scanning. (b) The tumor showed early enhancement on arterial phase image. (c) The honeycomb-like tumor displayed decreased enhancement on portal phase image with a hypodense central scar. (d) CTA showed the feeding splenic artery and draining veins (arrow) on the tumor surface. (e) Portal phase vascular reconstruction showed left gastric vein varices (short arrow) and splenic vein stenosis (long arrow). (f) Tumor specimens displayed a honeycomb-like appearance with abundant central scar. Figure 3 A 68-year-old female patient with a giant serous cystadenoma of the pancreatic head, concurrent colorectal cancer, and gastric stromal tumor. (a) Intrahepatic bile duct dilation and a gastric stromal tumor (arrow) were detected on CT plain scanning. (b) The pancreatic head tumor showed honeycomb-like appearance with multiple macrocysts and punctuate calcification. ((c) and (d)) Encasement of the portal and superior mesenteric veins (arrow) was noted on portal phase image. (e) The coronal CT image showed a pancreatic head tumor (short arrow) and rectal mass (long arrow). Table 1 Clinical and CT manifestations of giant pancreatic serous cystadenoma. Authors Gender/age (y) Symptoms Size (cm) Location Morphological patterns Calcification CTA or DSA Relationship with neighboring organs Surgical procedure Follow-up and outcome Sakata et al. [3] F/71 No 13.9 Head Oligocystic type No Stretching of the adjacent vessels NA Dome resection with chemocautery using 100 mg minocycline hydrochloride No postoperative complications and survived after 12 months of follow-up Schulz et al. [4] F/70 Abdominal discomfort with vomiting and lost weight 17.0 Head Microcystic type Yes NA Compression of the vena cava, the aorta, left liver lobe, and transverse colon. Involvement of the SMV and PV leading to severe portal hypertension Right-sided hemicolectomy without tumor resection Alive after 13 years of follow-up, symptoms are worsening and tumor is growing larger Salemis and Tsohataridis [5] F/83 General fatigue, epigastric pain, and weight loss 23.0 Head Macrocystic type No NA NA Roux-en-Y cystojejunostomy Alive after 13 years of follow-up, asymptomatic Vernadakis et al. [6] F/66 No 26.0 Head Microcystic type No NA Surrounding the right colonic vessels and compressing the IVC Pylorus-preserving pancreaticoduodenectomy with a right hemicolectomy Alive without postoperative complications Tajima et al. [7] F/72 No 13.0 Head Microcystic type No Feeding arteries including GDA, RGA, SA, DPA, and IPDA Enlarged draining veins on the surface (drainage into the PV and SMV) Tightly adherent to the SMV and PV Preoperative embolization of the tumor-feeding arteries, pancreaticoduodenectomy; the SMV-PV was resected and reconstructed Alive without postoperative complications Charalampoudis et al. [8] M/74 No 12.7 Body-tail Microcystic type No NA Attached to the splenic porta and the transverse mesocolon Distal pancreatectomy with splenectomy Alive without postoperative complications Dikmen et al. [9] F/64 Abdominal pain 15.5 Head Microcystic type No NA Compression of the right and left PV, inferior vena cava, left PV, and SMA Whipple procedure Alive without postoperative complications Kawaguchi et al. [10] F/58 Abdominal bloating 20.0 Body Macrocystic type No NA Compression of the middle part of the gastric body and main pancreatic duct in the tail of the pancreas Distal pancreatectomy with splenectomy NA Dokmak et al. [11] F/33–66 Pain and fullness in the right subcostal area (n = 3), palpable mass (n = 3), signs of gastric outlet obstruction (n = 1), and cholestasis without jaundice 12.0, 13.0, and 14.0 Head (n = 3) Macrocystic type (n = 3) NA (n = 3) NA (n = 3) NA (n = 3) Laparoscopic fenestration (n = 3), and one patient needed pancreatectomy Bile duct injury in one patient, pancreatic fistula in another patient At the last follow-up (13, 21, and 26 months), all 3 patients were symptom-free Liu et al. F/65 Abdominal bloating and vomiting 15.3 Body-tail Microcystic type Yes Lack of abundant feeding arteries (SA and DPA) and draining veins (drainage into the SV) Encasement or compression of the left RV, the SA and, SV and adherence to the posterior gastric wall Distal pancreatectomy with splenectomy No postoperative complications and survived after 14 months of follow-up Liu et al. M/67 Acid reflux with abdominal bloating and pain 14.8 Body-tail Microcystic type Yes Abundant feeding arteries (SA) and draining veins (drainage into the SV and the SMV) Encasement of the SA and SV; gastric vein varices, transverse mesocolon adhesions Distal pancreatectomy with splenectomy and omentum resection Postoperative infection and fluid accumulation in the surgical area; survived after 49 months of follow-up Liu et al. M/48 Abdominal pain and bloating 10.2 Body-tail Microcystic type No Abundant feeding artery (SA) and draining veins (drainage into the SMV and the SV) Compression of the left RV and the SV Distal pancreatectomy with preserving spleen Mild postoperative pancreatic fistula, survived after 45 months of follow-up Liu et al.∗ F/68 Abdominal bloating, palpable mass 16.5 Head Mix-type Yes Lack of abundant feeding artery (GDA) and draining veins (drainage into the SMV) Encasement and compression of the GDA, the PV, the SMV, and the CBD Pancreaticoduodenectomy, repair of the injured portal vein No postoperative complications and survived after 24 months of follow-up Liu et al. F/63 Abdominal pain 11.2 Body-tail Microcystic type Yes Abundant feeding artery (SA) and draining veins (drainage into the SMV and the SV) Encasement and compression of the SA and SV and adherence to the posterior gastric wall and the transverse colon Distal pancreatectomy withsplenectomy and partial resection of the transverse colon No postoperative complications and survived after 17 months of follow-up Liu et al. M/54 Abdominal bloating 10.5 Body-tail Microcystic type Yes Lack of abundant feeding artery (SA) and draining veins (drainage into the SMV and the SV) Encasement and compression of the SA and SV and gastric vein varices Distal pancreatectomy with splenectomy No postoperative complications and survived after 8 months of follow-up Note: Y, years; F, female; M, male; PV, portal vein; SMV, superior mesenteric vein; NA, not available; GDA, gastroduodenal artery; RGA, right gastric artery, SA, splenic artery; DPA, dorsal pancreatic artery; IPDA, inferior pancreaticoduodenal arteries; SMA, superior mesenteric artery; IVC, inferior vena cava; SV, splenic vein; RV, renal vein; CBD, common bile duct. ∗This patient had concurrent gastric stromal tumor and rectal adenocarcinoma. ==== Refs 1 Fukasawa M. Maguchi H. Takahashi K. Clinical features and natural history of serous cystic neoplasm of the pancreas Pancreatology 2011 10 6 695 701 10.1159/000320694 2-s2.0-78651385185 21242709 2 Jais B. 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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/6059479Research ArticleDifferential Intracochlear Sound Pressure Measurements in Human Temporal Bones with an Off-the-Shelf Sensor http://orcid.org/0000-0002-5720-0981Grossöhmichen Martin 1 2 * Salcher Rolf 1 2 Püschel Klaus 3 Lenarz Thomas 1 2 Maier Hannes 1 2 1Cluster of Excellence Hearing4all, Germany2Department of Otolaryngology and Institute of Audioneurotechnology (VIANNA), Hannover Medical School, 30625 Hannover, Germany3Department of Legal Medicine, University Medical Center Hamburg-Eppendorf, 22529 Hamburg, Germany*Martin Grossöhmichen: grossoehmichen.martin@mh-hannover.deAcademic Editor: Jun Yang 2016 16 8 2016 2016 605947929 2 2016 18 5 2016 21 7 2016 Copyright © 2016 Martin Grossöhmichen et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The standard method to determine the output level of acoustic and mechanical stimulation to the inner ear is measurement of vibration response of the stapes in human cadaveric temporal bones (TBs) by laser Doppler vibrometry. However, this method is reliable only if the intact ossicular chain is stimulated. For other stimulation modes an alternative method is needed. The differential intracochlear sound pressure between scala vestibuli (SV) and scala tympani (ST) is assumed to correlate with excitation. Using a custom-made pressure sensor it has been successfully measured and used to determine the output level of acoustic and mechanical stimulation. To make this method generally accessible, an off-the-shelf pressure sensor (Samba Preclin 420 LP, Samba Sensors) was tested here for intracochlear sound pressure measurements. During acoustic stimulation, intracochlear sound pressures were simultaneously measurable in SV and ST between 0.1 and 8 kHz with sufficient signal-to-noise ratios with this sensor. The pressure differences were comparable to results obtained with custom-made sensors. Our results demonstrated that the pressure sensor Samba Preclin 420 LP is usable for measurements of intracochlear sound pressures in SV and ST and for the determination of differential intracochlear sound pressures. CochlearDeutsche ForschungsgemeinschaftEXC 1077/1 ==== Body 1. Introduction The majority of Implantable Middle Ear Hearing Devices (IMEHDs) such as the MET® (Cochlear Ltd.) or the Vibrant Soundbridge (MED-EL) were initially developed for the treatment of sensorineural hearing loss [1, 2]. For this purpose, the implant converts external sound to vibration, which mechanically drives the ossicular chain (e.g., incus body). To quantify the IMEHD's equivalent sound pressure output level in such applications, the ASTM standard 2504-05 [3] provides an experimental method in human cadaveric temporal bones (TBs). This method is commonly used and is based on the comparison of the vibration amplitude of the stapes footplate (SFP) in response to sound and to actuator stimulation measured with a laser Doppler vibrometer (LDV). This method has been demonstrated to be reliable for applications that stimulate the ear in the physiological forward direction [2, 4–6]. More recently, the indication of IMEHDs was extended to conductive and mixed hearing loss applications where the implant vibrates the SFP or the round window (RW) [7–9]. Likewise, the direct acoustic stimulation of the cochlea by a Direct Acoustic Cochlear Implant (DACI) such as the Codacs™ (Cochlear Ltd.) has become well established for the treatment of severe to profound mixed hearing loss [10, 11]. However, quantifying the output level of these new stimulation modes by LDV measurements in TBs according to ASTM standard 2504-05 [3] is not possible. In the case where the SFP is obscured, vibration responses of the RW of the cochlea can be determined by LDV instead [12, 13]. However, due to the complex vibration pattern of the RW at frequencies >1.5 kHz, this method is reliable only within one experiment and if the measurement site on the RW is unchanged [12, 14, 15]. In the other case, where the RW is excited by an IMEHD, the ear is stimulated in reverse direction compared to the physiological sound transmission. Although SFP vibration responses are commonly measured to estimate the stimulation efficiency in such cases [16–18], it has been demonstrated that this method markedly underestimates the real output level in reverse stimulation [6]. In direct acoustic stimulation by a DACI the SFP is perforated and the cochlear fluids are stimulated by a piston. However, opening the cochlea causes strong changes in the motion pattern of the RW vibration response at frequencies >1.5 kHz making vibration measurements unreliable [15]. In conclusion, measuring vibration responses according to ASTM standard 2504-05 [3] is a reliable method to determine the output level of IMEHDs only during forward stimulation and only if the ossicular chain and cochlea are left intact. In all other stimulation modes an alternative measurement method is needed to quantify the output level of IMEHDs and DACIs in human cadaveric TBs. Measuring the sound pressure difference between the two compartments of the cochlea, scala vestibuli (SV) and scala tympani (ST), represents such a method as the pressure difference correlates with cochlear excitation [19]. Pressure differences have successfully been used to characterize the output level in forward and reverse stimulation in TB experiments [6, 20–22]. However, in these studies the sound pressure in SV and ST was measured with a custom-made pressure sensor developed by Olson [23]. This sensor is commercially not available and difficult to build. Therefore, the much-needed technique of intracochlear sound pressure measurement is currently available only for a limited group of researchers. In order to make this method accessible to a wider community, the goal of our study was to demonstrate that an off-the-shelf pressure measurement system can be successfully used for intracochlear sound pressure measurement. This may contribute to establishing intracochlear sound pressure measurements as a generally accessible and commonly used technique and a strong tool in hearing research beside vibration measurements with LDVs. 2. Materials and Methods In this study intracochlear sound pressures in response to acoustic stimulation of the tympanic membrane were measured in SV (P SV) and ST (P ST) in cadaveric human TBs with the off-the-shelf pressure transducer Samba Preclin 420 LP. 2.1. TB Preparation Nineteen human cadaveric TBs obtained from the Institute for Pathology of the Hannover Medical School and the Department of Legal Medicine of the University Medical Center Hamburg-Eppendorf [24] were used for this study. Harvesting and anonymous use of the TBs were approved by the ethics committee of the Hannover Medical School (2168-2014). All TBs were harvested within 48 h postmortem, immediately frozen at approximately −19°C, and thawed shortly before preparation at room temperature. A mastoidectomy, removal of the facial nerve, and thinning of the RW niche overhang down to approximately 0.5–1 mm were performed. This wide mastoid preparation exposed the SFP and the promontory where the pressure transducers were intended to be inserted. After preparation the TBs were stored in saline containing ~0.005‰ thimerosal at approximately −19°C until the experiments. In the beginning of each experiment the integrity of the RW membrane and the mobility of the ossicular chain were carefully checked using a surgical microscope (OPMI-1, Zeiss, Germany) and surgical tools. During experiment the TBs were kept moist with saline to avoid changes in mechanical behavior [3]. 2.2. Experimental Setup TBs were fixed in a laboratory clamp on a vibration isolated table (LW3048B, Newport, Germany). A custom-made sound application setup containing a probe microphone (ER-7C, Etymotic Research Inc., USA) and a loudspeaker (DT48, Beyerdynamic, Germany) was cemented (Paladur, Heraeus Kulzer GmbH, Germany) in the outer ear canal (OEC). The tip of the microphone's probe tube was positioned 1-2 mm from the tympanic membrane (TM). To prevent unwanted vibrations from being transferred from the loudspeaker to the TB, the TB was embedded in modelling clay (Play-Doh, Hasbro, Germany). 2.3. Intracochlear Pressure Measurement Intracochlear pressures in SV and ST were measured simultaneously with two off-the-shelf pressure fiber-optic transducers (Samba Preclin 420 LP, Samba Sensors AB, Sweden) connected to a two-channel control unit (Samba control unit 202, Samba Sensors AB, Sweden). The pressure transducer is based on the Fabry-Pérot interferometer principle, has an outer diameter of 0.42 mm, is calibrated by the manufacturer, valid for lifetime with a long term stability of <0.5% of range [25, 26], and can be reused for several measurements. In this study three sensors were used as the membrane of one sensor was damaged during experiments and two sensors are needed in each experiment for the simultaneous measurement. The pressure measurement system has a maximum measurement frequency of 40 kHz, a pressure range of −50 to +350 hPa and a sensitivity of approximately −80 dB re 1 V/Pa. Under the assumption of a middle ear amplification of 23 dB at ≤1 kHz, 0 dB at ≥7 kHz, and a decrease of −8.6 dB/octave in between [27] and depending on the conversion range of the AD/DA converter the theoretical resolution limit of the samba pressure measurement system is between 65 dB SPL and 72 dB SPL input to the TM at ≤1 kHz and between 88 dB SPL and 95 dB SPL at ≥7 kHz. The control unit provides a proportional voltage signal at each analog output channel. Each transducer was mounted to a custom-made holder attached to a 3-axis micromanipulator (M3301R, World Precision Instruments Germany GmbH, Germany), allowing the adjustment in all three spatial directions. 2.4. Vibration Measurement Stapes footplate (SFP) vibration responses were measured with a single-point LDV system (OFV 534, OFV 5000, A HLV MM 30, Polytec, Germany) attached to a surgical microscope (OPMI-1, Zeiss, Germany). The laser beam was directed at a small piece (<0.3 mm × 0.3 mm) of reflective tape on the SFP at a visually estimated incident angle of ≤45° to the SFP normal. During analysis the incident angle was considered by a cosine correction. 2.5. Experimental Procedure First, the TB preparation was checked visually using the surgical microscope. In case of damage such as a ruptured RW or broken SFP the TB was rejected. Second, the loudspeaker was driven by a custom multisine signal, having equal amplitudes of approximately −25 dB re 1V rms at 0.125, 0.25, 0.5, 1, 2, 3, 4, 6, 8, and 10 kHz. Simultaneously the vibration of the SFP was measured with the LDV and the sound pressure level (SPL) in the OEC was recorded by the probe microphone. Only if the SFP vibration response was within the modified acceptance range [4] of the ASTM standard F2504-05 [3], the experiment was continued. Third, two Samba Preclin 420 LP transducers were placed in SV and ST (Figure 1). For this purpose the promontory was first thinned where the cochleostomies were intended and then a fenestration of approximately 0.5 mm diameter was made in SV and ST using a diamond burr and a footplate perforator. When the tip of the transducer was inserted 100–300 μm (visually estimated) into the scalae, the transducer was sealed with the surrounding bone using dental impression material alginate (Alginoplast®, Heraeus Kulzer GmbH) in TB05–07 or a silicone rubber plug (Silikonkautschuk RTV, Wacker-Chemie GmbH, Germany) permanently mounted to the optical fiber in TB16, 18, and 19. If necessary, the silicone rubber could be easily removed by pulling it off the fiber. During cochleostomy, sensor insertion, and sealing, the middle ear cavity was immersed in saline to prevent air from entering the cochlear. Fourth, SFP vibrations were measured in response to the acoustic multisine stimulation similar to the second step of the experiment. With this measurement the effect of the cochleostomy and sensor insertion on the SFP vibration responses to sound stimulation was investigated. Fifth, the TM was stimulated acoustically between 0.1 and 10 kHz by a sequence of sine-wave signals with a frequency resolution of 3/octave (resulting in 23 frequencies between 0.1 and 10 kHz) at levels of 105–130 dB SPL. Simultaneously the sound pressures in SV and ST were measured by the pressure transducers, the SPL at the TM by the probe microphone and the vibration of the SFP by the LDV. Finally for the analysis single frequency results of the 23 stimulation frequencies were assembled into one frequency response for each TB. Sixth, after completing all measurements the pressure transducers were removed and the correct positioning of the cochleostomies in SV and ST was confirmed visually by dissection of the TB. In total, three out of 19 TBs were excluded due to damage of anatomical structures. Of the remaining 16 TBs, six had SFP vibration responses compliant to the modified acceptance range of ASTM F2504-05 [4] and were used for intracochlear sound pressure measurements. 2.6. Signal Generation, Acquisition, and Analysis For signal generation and acquisition a commercial 16-bit, 4-channel data acquisition system (PC-D and VIB-E-400, Polytec, Germany) with commercial software (VibSoft 4.8.1, Polytec, Germany) was used. Electric input signals to the loudspeaker were buffered by an amplifier (SA1, Tucker-Davis Technologies, USA). Electric output signals from probe microphone, LDV, and Samba pressure measurement system were acquired simultaneously as averaged complex spectra using 800 (Fast Fourier Transformation) FFT lines between 0 and 10 kHz with 12.5 Hz resolution. The signal-spectra obtained during multisine stimulation in the 2nd and 4th steps of the experiment were averaged 500 times and the signal-spectra obtained during stimulation with the sequence of sine-wave signals (5th step of experiment) were averaged 1000 times to increase the signal-to-noise ratio (SNR). At each stimulation frequency the SNR was determined using the average of the three adjacent FFT lines below and above as noise level estimate. Vibration responses with SNR < 12 dB and intracochlear sound pressure responses with SNR < 7 dB were excluded from analysis. Empirically these values have proved to be sufficient to record signals clearly above the noise floor. The differential sound pressure across the cochlear partition (ΔP = P SV − P ST) was calculated by subtracting the complex pressures in ST (P ST) and SV (P SV) in the frequency domain. 3. Results 3.1. SFP Vibration Responses before and after Cochleostomy Six TBs showed vibration responses of the SFP to sound [dB re μm/Pa] at 0.25–4 kHz (Figure 2(a)) compliant to the modified acceptance range [4] of ASTM F2504-05 [3] and were used for intracochlear sound pressure measurements. Even after the insertion of the pressure transducer, the SFP responses (Figure 2(b)) were inside the range, except TB06 at 4 kHz (5.7 dB deviation), TB16 at 1, 2, and 3 kHz (2.8 dB maximum deviation), and TB19 at 4 kHz (2.4 dB deviation). 3.2. Sound Pressures in Scala Vestibuli and Scala Tympani To compare the measurement data across all TBs independent of stimulation level, the intracochlear sound pressures P SV and P ST were normalized to the outer ear canal SPL P OEC (Figure 3) and to the stapes footplate velocity V SFP (Figure 4). In all specimens except TB05, intracochlear sound pressures were measurable in both scalae between 0.1 and 6.35 kHz with an SNR > 7 dB. Pressures at 8 kHz were measurable in two experiments (TB18, TB19) and at 10 kHz in one experiment (TB18, Figure 5). When normalized to P OEC the magnitudes of P SV (Figure 3(a)) were similar across all experiments, as well as P ST (Figure 3(c)) at frequencies ≥3 kHz. At lower frequencies the magnitudes of P ST/P OEC varied up to 42 dB across experiments. In particular, in TB19 the magnitudes were at ≤0.4 kHz up to 27 dB smaller than in all other experiments. The phases of P SV (Figure 3(b)) and P ST (Figure 3(d)) were similar across all TBs showing an increasing lag to P OEC with increasing frequency. At frequencies >4 kHz the phases of P ST decreased significantly, resulting in approximately two cycles shift at ≥5.5 kHz. The magnitudes of P SV normalized to V SFP (Figure 4(a)) were similar across all experiments; only TB07 showed a prominent peak at 2.525 kHz. In contrast, the magnitudes of P ST/V SFP (Figure 4(c)) varied at frequencies below 3 kHz significantly by up to 49 dB. Again, at frequencies ≤0.4 kHz the magnitudes in TB19 were distinctly smaller compared to the other experiments. At frequencies ≤2 kHz the P SV/V SFP and P ST/V SFP phases were mainly constant for each TB whereas at higher frequencies the phases showed a higher variation. In each experiment the normalized magnitude of P SV was higher than the normalized magnitude of P ST at frequencies above 400 Hz whereas the pressure magnitudes in both scalae were similar at lower frequencies. Only in TB07 the magnitudes of P SV and P ST were similar (differences ≤ 2 dB) up to 1.6 kHz and in TB19 the magnitude of P SV was distinctly higher than P ST at all frequencies. 3.3. Intracochlear Pressure Differences The magnitudes and phases of the complex pressure differences (ΔP = P SV − P ST) between SV and ST are plotted in Figure 6 normalized to the SPL in the OEC (P OEC). Apart from TB16, showing a sharp notch at 2525–3175 Hz, the magnitudes (Figure 6(a)) were similar across all TBs with differences ≤ 20 dB. The phases (Figure 6(b)) were also similar in all TBs showing a 1/8–2/3 cycle lead at frequencies below 1 kHz that decreased with increasing frequency to a lag of up to 1 1/3 cycle. Since in TB05 pressure differences were only measurable at ≤312.5 Hz and up to 20 dB lower than in the other experiments, it was assumed that the preparation in this TB failed and the TB was not further considered in the analysis. The magnitudes and phases of the differential pressure (ΔP = P SV − P ST) normalized to the velocity of the SFP (V SFP) (Figure 7) were almost frequency independent. Across all TBs the magnitudes varied ≤21 dB, except in TB16 at 2525–3175 Hz where a notch was present. The phases were near 0° at frequencies ≤2 kHz and varied between −180° and +180° at higher frequencies. 4. Discussion 4.1. Handling and Limitations of the Off-the-Shelf Sensor System In our study the Samba Preclin pressure measurement system was easy to handle and worked reliably. One major limitation of the Samba Preclin 420 LP pressure sensor is the fragile front membrane that can be damaged by mechanical stress or by particles drying on the membrane [25]. Therefore, the membrane had to be handled with great care (especially during sensor insertion). Although the sensor showed a strong robustness in our study as only one sensor was destroyed, an improved design with a protection of the membrane may prevent damage. The minimum bend radius of the fiber given by the manufacturer is 10 mm [25]. For intracochlear sound pressure measurements the technical specifications of the measurement system could be optimized. By increasing the numerical resolution and by adapting the pressure range to levels relevant for sound pressure measurements the resolution limit could be improved. 4.2. Effect of Transducer Insertion on SFP Vibration Responses After pressure transducer insertion most SFP vibration responses to sound (Figure 2) still fulfilled the modified ASTM criteria [4]. The difference between SFP vibration displacements before and after insertion of transducers (Δd = d post − d pre) was generally within 5 dB below 3 kHz and within 7 dB at higher frequencies (Figure 8). Only at 6 kHz the difference was higher in TB06 (11.6 dB) and TB19 (9.4 dB). These results indicate that the opening and reclosure of the cochlea by insertion of the pressure transducers have no pronounced effect on cochlear mechanics. This confirms the assumption that the inserted sensor membrane is much stiffer, has a much higher acoustic impedance than the round window membrane, and does not lead to major changes in natural cochlea acoustics. 4.3. Sealing Techniques No correlation between the sealing material used (dental impression material in TB05–07 or silicone rubber in TB16, 18, 19) and the magnitude of P SV, P ST, and ΔP (Figures 3, 4, 6, and 7) was detectable. Since silicone rubber was easier to use than alginate and it was reusable in several experiments when once applied to the transducer; it is advantageous. 4.4. Comparison to Previous Work with Custom-Made Pressure Sensors In the past it has been already demonstrated that the measurement of intracochlear pressure differences across the cochlear partition can be used to characterize the response levels from forward and reverse stimulation in human cadaveric TBs [6, 20–22]. The objective of this study was to investigate if intracochlear differential pressures are measurable in a similar manner with the off-the-shelf pressure transducer Samba Preclin 420 LP being originally intended for static pressure measurement. Thus, the intracochlear sound pressures P SV, P ST and differential sound pressures ΔP measured here were compared (Figures 3, 4, 6, and 7) to earlier measurements [6, 21, 22] performed with custom-made sensors developed by Olson [23]. Recently [28, 29] intracochlear sound pressures were measured in scala vestibuli and scala tympani with an off-the-shelf sensor different to the one used here. In these studies a detailed comparison to results measured with custom-made sensors developed by Olson [23] was not performed. Here we used results [6, 21, 22] obtained with custom-made sensors developed by Olson [23] as a comparison criterion because this sensor type has proven to provide reliable results in the past. Normalized to P OEC or by V SFP, our P SV magnitudes (Figures 3(a) and 4(a)) were largely within the minimum-maximum range of Stieger et al. [6] and Nakajima et al. [21] in the investigated frequency range. At frequencies ≥2 kHz, P ST magnitudes (Figures 3(c) and 4(c)) were also mostly comparable to these studies but differed up to approximately 20 dB at lower frequencies. Whereas we observed a maximum variation of up to 42 dB in the magnitudes of P ST/P OEC and up to 49 dB in the magnitudes of P ST/V SFP, the magnitudes of P ST/P OEC in Nakajima et al. [21] and the magnitudes of P ST/V SFP in Stieger et al. [6] varied maximally, approximately 25 dB. One potential reason for the difference between P ST magnitudes found here and in other studies performed with a custom-made sensor [6, 21] might have been the 6.3 times (approximately 16 dB) bigger sound sensitive integration area of the Samba Preclin 420 LP pressure transducer (0.1385 mm2) compared to the custom-made sensor (0.0219 mm2). Another reason for that and for the higher variation of our P ST magnitudes study might have been an imperfect sealing between pressure transducer and bone in our preparations. This would also explain why in our study the magnitudes of P SV/P OEC and P SV/V SFP were more similar (maximum variation: 20 dB and 30 dB) across the TBs than P ST magnitudes. In the experiments TB06, TB07, and TB16 where the magnitudes of P SV and P ST dropped at 8 and 10 kHz below 7 dB SNR the acoustic stimulation dropped to 70–90 dB SPL. This finding is in line with the theoretical resolution limit of the samba sensor system of 88–95 dB SPL at ≥7 kHz at the TM calculated in method, Section 2.3. The phases of P SV (Figure 3(b)) and P ST (Figure 3(d)) relative to P OEC were mostly within the range of Nakajima et al. [21]. Only at frequencies >4 kHz our P ST phases differed significantly showing an up to 1 cycle longer delay which probably might be due to different unwrapping of the phase. Relative to V SFP, P SV and P ST phases (Figures 4(b) and 4(d)) were at frequencies <2 kHz comparable to Stieger et al. [6] but mostly lower at higher frequencies. A 1/2 cycle shift in P ST phases at approximately 0.5 kHz determined by Stieger et al. [6] was not observable here. One potential reason for the lower similarity to Stieger et al. [6] might be that in their study the vibration response of the stapes was measured at the posterior crus whereas we measured it at the footplate leading to a different impact of rocking motions. However, to determine the input to the cochlea the relevant parameter is the pressure difference between SV and ST correlating to the cochlear microphonics [19]. When normalized to P OEC (Figure 6(a)), at ≥1 kHz, the magnitude of the complex pressure difference ΔP = (P SV − P ST) was within the minimum-maximum range of measurements by Nakajima et al. [21], but up to 16 dB less at lower frequencies. As mentioned before a probable reason for this discrepancy at low frequencies might have been that the sealing between pressure transducer and bone was imperfect in our experiments. On the other hand, our data was comparable in the whole frequency range (Figure 6) to two exemplary measurements of a later study [22] performed by the same researchers. This variance demonstrates that more reference data of differential intracochlear pressure measurements would be useful but is currently not available. The phases of ΔP relative to P OEC were similar to Nakajima et al. [21]. When normalized to the stapes velocity, almost all magnitudes of ΔP/V SFP (Figure 7(a)) were within the minimum-maximum range of Stieger et al. [6], except at frequencies <0.3 kHz where our results were maximally 15 dB less. Almost all phases of ΔP relative to V SFP were within the range of Stieger et al. [6]. Only TB07 and TB16 showed at approximately 0.25 kHz (TB16) and 3 kHz (TB07 and TB16) a difference of 1/2 cycle lag. Between 2525 and 3175 Hz where the normalized ΔP magnitude decreased extraordinarily in TB16 (Figures 6(a) and 7(a)), the absolute values of P SV and P ST were close in magnitude and phase in this experiment. Usually this might be an indication for placement of both pressure transducers accidently into the same scala. However, in this experiment the differential intracochlear pressure at all other frequencies was normal and a failure of preparation could be excluded based on the visual inspection during dissection. Hence, no explanation was found for this decrease in pressure difference in TB16. In consideration of nonlinear effects on the normalized intracochlear pressure magnitudes, the range of acoustical stimulation levels has to be taken into account. In our study sounds were presented at 105–130 dB SPL, whereas in Stieger et al. [6] stimulation levels between 50 and 115 dB SPL and in Nakajima et al. [21] levels between 70 and 130 dB SPL were used. In Pisano et al. [22] no information about the stimulation level was provided, but it was referred to Nakajima et al. [21]. It is known that the vibration response of the stapes in human cadaveric TBs is linear with the level of acoustic stimulation up to 124 dB SPL at 0.4–6 kHz [30] and up to 130 dB SPL at 0.1–4 kHz [31]. Therefore, it can be assumed that the normalized intracochlear pressures and pressure differences measured by Stieger et al., Nakajima et al., and Pisano et al. [6, 21, 22] and our results are not subject to significant middle ear nonlinearities although our minimum stimulation levels were higher in experiments. In one experiment we stimulated acoustically first with sound pressure levels of 110–130 dB SPL and second with levels of 90–120 dB SPL. When normalized to P OEC the magnitudes of P SV and P ST were similar within 3 dB except at 3175 Hz where a decrease in P ST by 12 dB was found for the lower simulation level. 5. Conclusion Intracochlear pressure differences obtained in this study with the off-the-shelf pressure transducer Samba Preclin 420 LP were comparable to results obtained with custom-made sensors [23] at frequencies of 1–10 kHz and differed up to 16 dB below 1 kHz. Additionally we could show that insertion of the pressure transducers had a minor effect of <5 dB on the stapes vibration response to sound. Our results demonstrate that the Samba Preclin 420 LP is usable for simultaneous measurements of intracochlear sound pressures in SV and ST in human cadaveric temporal bones with sufficient SNR and sensitivity. Acknowledgments This work was supported by a project grant from Cochlear Ltd. and by the DFG Cluster of Excellence EXC 1077/1 “Hearing4all.” Competing Interests This work is part of the doctoral thesis of Martin Grossöhmichen and was supported by a project grant from Cochlear Ltd. Martin Grossöhmichen and Hannes Maier received travel support by Cochlear Ltd. to meetings. The authors disclose no other conflict of interests. Figure 1 Temporal bone preparation for intracochlear sound pressure measurements. (a) Cochleostomies of ~0.5 mm diameter in scala vestibuli (SV) and scala tympani (ST) (picture was taken after the experiment). The reflector was placed on the stapes footplate for LDV measurement. (b) Samba Preclin 420 LP transducers placed in SV (left) and ST (right), sealed with alginate. Figure 2 SFP responses to sound stimulation at the tympanic membrane in TB preparations used for analysis. (a) Before pressure sensor insertion. (b) After cochleostomy and pressure sensor insertion. The black dashed lines depict the limits given by Rosowski et al. [4]. Figure 3 Sound pressures in scala vestibuli (P SV, (a) and (b)) and scala tympani (P ST, (c) and (d)) normalized to the outer ear canal sound pressure level (P OEC). For comparison the range of results obtained with a custom-made pressure sensor by Nakajima et al. [21] is given (grey shaded area). Data with an SNR < 7 dB were omitted. Figure 4 Sound pressures in scala vestibuli (P SV, (a) and (b)) and scala tympani (P ST, (c) and (d)) normalized to the stapes footplate velocity (V SFP). For comparison the range of results obtained with a custom-made pressure sensor by Stieger et al. [6] is given (grey shaded area). Data with an SNR < 7 dB were omitted. Figure 5 An example (TB18) of the sound pressure Psv measured in scala vestibuli and the corresponding noise floor estimated by the average of the three adjacent FFT lines below and above each stimulations frequency. Figure 6 Pressure differences (P SV − P ST) normalized to the outer ear canal sound pressure level (P OEC). For comparison the range of results (Nakajima et al. [21], grey shaded area) and two exemplary measurements (Pisano et al. [22], solid lines) obtained with a custom made pressure sensor are given. Data with an SNR < 7 dB were omitted. Figure 7 Pressure differences (P SV − P ST) normalized to the SFP velocity (V SFP). For comparison the range of results obtained with a custom made pressure sensor by Stieger et al. [6] is given (grey shaded area). Data with an SNR < 7 dB were omitted. Figure 8 Differences in SFP vibration responses to 94 dB SPL sound stimulation at the tympanic membrane in TB preparations before and after pressure transducer insertion (Δd = d post − d pre). ==== Refs 1 Kasic J. F. Fredrickson J. M. The otologics MET ossicular stimulator Otolaryngologic Clinics of North America 2001 34 2 501 513 10.1016/s0030-6665(05)70345-5 2-s2.0-0034981722 11382583 2 Mlynski R. Dalhoff E. Heyd A. Standardized active middle-ear implant coupling to the short incus process Otology and Neurotology 2015 36 8 1390 1398 10.1097/mao.0000000000000822 2-s2.0-84940107381 26247138 3 ASTM Standard practice for describing system output of implantable middle ear hearing devices ASTM 2005 F 2504-05 4 Rosowski J. J. Chien W. 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==== Front J PregnancyJ PregnancyJPJournal of Pregnancy2090-27272090-2735Hindawi Publishing Corporation 10.1155/2016/4183648Research ArticleThe Effect of the More Active MuMs in Stirling Trial on Body Composition and Psychological Well-Being among Postnatal Women http://orcid.org/0000-0002-8803-9852Lee Alyssa S. 1 http://orcid.org/0000-0003-0938-2861McInnes Rhona J. 2 * http://orcid.org/0000-0001-8602-1299Hughes Adrienne R. 3 http://orcid.org/0000-0002-4469-4011Guthrie Wendy 1 Jepson Ruth 4 1School of Health Sciences & Sport, University of Stirling, Stirling FK9 4LA, UK2School of Nursing, Midwifery and Social Care, Edinburgh Napier University, Edinburgh EH11 4BN, UK3School of Psychological Sciences and Health, University of Strathclyde, Glasgow G1 1QE, UK4Scottish Collaboration for Public Health Research & Policy, University of Edinburgh, Edinburgh EH8 9DX, UK*Rhona J. McInnes: r.j.mcinnes@stir.ac.ukAcademic Editor: Jeffrey Keelan 2016 16 8 2016 2016 418364820 3 2016 5 7 2016 14 7 2016 Copyright © 2016 Alyssa S. Lee et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction. Physical activity is important for health and well-being; however, rates of postnatal physical activity can be low. This paper reports the secondary outcomes of a trial aimed at increasing physical activity among postnatal women. Methods. More Active MuMs in Stirling (MAMMiS) was a randomised controlled trial testing the effect of physical activity consultation and pram walking group intervention among inactive postnatal women. Data were collected on postnatal weight, body composition, general well-being, and fatigue. Participants were also interviewed regarding motivations and perceived benefits of participating in the trial. Results. There was no significant effect of the intervention on any weight/body composition outcome or on general well-being at three or six months of follow-up. There was a significant but inconsistent difference in fatigue between groups. Qualitative data highlighted a number of perceived benefits to weight, body composition, and particularly well-being (including improved fatigue) which were not borne out by objective data. Discussion. The MAMMiS study found no impact of the physical activity intervention on body composition and psychological well-being and indicates that further research is required to identify successful approaches to increase physical activity and improve health and well-being among postnatal women. ==== Body 1. Introduction Recent research suggests that physical inactivity in women over 30 years is the greatest preventable risk factor for cardiovascular disease [1]. Weight retention is a clinical problem among postnatal women and may be important in terms of lifetime obesity risk [2, 3]. Regular physical activity may contribute to short-term improved weight control (during and after pregnancy), longer-term overweight and obesity management, and diabetes treatment and prevention [4–6]. Also during the postnatal period psychological well-being has been shown to be enhanced by regular physical activity [7–9]. Recommendations for postnatal physical activity are now available via clinical guidelines published in five countries [10]. All promote the safety of physical activity and the beneficial effects of following generic guidelines for adults, with variable suitable periods suggested for gradual resumption (or uptake) of physical activity after birth. Rates of postnatal physical activity participation vary considerably across studies but in general a low proportion of postnatal women report meeting physical activity guidelines [11–15]. In these studies there is considerable heterogeneity with regard to measurement approaches, the postnatal time period under study, and different definitions regarding what constitutes physical activity. Previous research suggests childbirth, pregnancy, and childrearing act as potentially negative influences on physical activity participation among women [16–18], partly due to increased caregiving responsibilities and societal and individual perceptions, particularly on how women prioritise their own needs in the context of their parental and/or working mother roles [19]. Qualitative evidence from mothers of young children lends some support to this [19, 20], as do surveys of postnatal women's self-reported PA barriers, which identify lack of time [21], lack of childcare, and low energy levels as the most frequently reported barriers [21–23]. Postnatal women reporting fewer barriers are more active [19], and self-reported self-efficacy (confidence) for overcoming barriers to PA (including setbacks to implementing PA plans) can predict positive changes to postnatal PA behaviour [22]. Our review and meta-analysis of postnatal interventions identified some evidence of a moderate positive effect on frequency of physical activity participation among postnatal women who received physical activity interventions [24]. Efficacious studies (in terms of physical activity outcomes) were generally those omitting dietary components and those utilising theoretically sound and evidence-based behavioural techniques such as goal-setting and self-monitoring. However, these studies did not report on other outcomes (e.g., weight management and indicators of postnatal well-being). Methodological flaws such as a poor sample size and lack of an objective measure of physical activity suggested further research was warranted. We designed, developed, and implemented the More Active MuMs in Stirling (MAMMiS) trial to address this underresearched area. The primary aim of MAMMiS was to investigate the effect of an intervention comprising physical activity consultations and a 10-week pram walking programme on objectively measured physical activity in healthy but insufficiently active postnatal women. Main trial results are reported elsewhere [25]. This paper reports on secondary outcomes, with a particular focus on postnatal health and well-being indicators (specifically weight management, well-being, and fatigue). Although the MAMMiS trial was not designed as a postnatal weight management intervention (weight and body composition were secondary outcomes), this together with postnatal well-being outcomes is of importance to researchers, clinicians, and postnatal women themselves. The qualitative phase (aspects of which are reported here and explored in more detail in [26]) also considered intervention feasibility and acceptability from the perspective of the postnatal women participating in the trial. 2. Materials and Methods MAMMiS study methods have been reported in detail elsewhere [27]. In this paper we present brief details of the central features of study design, participants recruited, and intervention and outcome measures of interest for this paper. 2.1. Design and Setting MAMMiS was a randomised controlled trial conducted in one region within Central Scotland. The community has approximately 3–3500 births annually [28] and is reasonably diverse in terms of socioeconomic status and urban and rural classification, although ethnic minorities are underrepresented, which can be problematic for recruitment of a diverse sample [29]. 2.2. Participants Postnatal women who had given birth between 6 weeks and one year previously were included in the study. Inclusion criteria are given in full in Gilinsky et al. [27]. In brief, postnatal women (following postnatal check-up) who were insufficiently active (defined in relation to their self-reported physical activity stage of change [30], which assessed their current physical activity in relation to physical activity guidelines [31]) were included. Postnatal women were excluded if they were pregnant/planning a pregnancy or had medical contraindications to physical activity. 2.3. Intervention and Control Procedures The intervention was delivered by a health psychologist with experience in motivational interviewing and delivery of behaviour change (plus walk leader training) and consisted of a face-to-face physical activity consultation (approximately 45 minutes in length) delivered at the start of a 10-week group pram walking programme with a second consultation (approximately 25 minutes in length) delivered at the end of the programme. The physical activity consultation approach was theoretically and evidence based (e.g., [32–34]) and was derived from models of behaviour change, in particular the Transtheoretical Model (TTM) [35]. The specific behaviour change techniques used in the physical activity consultations have been reported in detail elsewhere [27] and were chosen following a review of literature on determinants of postnatal physical activity. A workbook was used by participants to structure their activity plan (e.g., goal-setting, planning, and self-monitoring sheets). Participants also received a pedometer to monitor steps and were given information on the pram walk programme in their area. Participants could attend one session/week for 10 weeks and all women were encouraged to attend. Walks were conducted at a moderate-intensity (e.g., brisk pace) between 30 to 55 minutes per session. Four women who were unable to attend (e.g., because they had an infant and a toddler) received a 10-minute support phone call instead. The control group received a leaflet “Active Living during and after Pregnancy,” an NHS Health Scotland publication with information on physical activity guidelines and advice on implementation. 2.4. Outcome Measures The primary outcome measure for the MAMMiS study was change in physical activity (measured by accelerometry and questionnaire), which has been reported elsewhere [25, 27]. Secondary outcomes were weight, body mass, general well-being, and fatigue and these were assessed at baseline and three-month and six-month follow-up. Weight (kg) and body composition (BMI, % fat mass) were measured using the Tanita 300 MA portable bioelectrical impedance monitor in accordance with procedures specified in the technical manual [36]. Each test was conducted at the same time of day and participants were given instructions to improve the accuracy of the body composition measurements. Before each test participants were asked to avoid caffeine for four hours, eating and drinking for 4 hours, intense exercise for 12 hours, taking diuretics for 7 days, and alcohol for 48 hours; participants were also asked to empty their bladder within 30 minutes before the test. Height was measured in centimetres (to the nearest cm) using a stadiometer at baseline only. Participants were categorised as underweight, healthy weight, overweight, or obese according to their BMI (kg/m2). Psychological well-being was measured using the Adapted General Well-Being Index (AGWBI) [37]. This 22-item 5-point Likert response scale assesses well-being, self-control, anxiety and depression, vitality, and general health concerns in the past two weeks and has been validated within a GP practice in the UK [38]. Fatigue was measured using a visual analogue scale (VAS) response to one question. Visual analogue scales are a commonly used unidimensional method of assessing health status and are appropriate for measuring experience of short-term fatigue severity in general and clinical populations [39]. Participants were asked to place a mark on a 100 mm line to indicate the extent to which they had been “affected by fatigue in the past two weeks,” where no fatigue was equal to 0 and worst possible fatigue was equal to 100 on the VAS. All measurements were taken at participants' homes or at the university site, depending on participant preference. 2.5. Posttrial Interviews For the qualitative phase participants from each trial group were sought and we aimed to recruit a representative sample of at least half of all MAMMiS participants. The qualitative phase consisted of one in-depth interview (30–90 minutes in length). These took place after completion of all outcome measures at participants' homes or another suitable venue. All interviews were conducted by a separate researcher not involved in the main trial (who also led the qualitative analysis). The rationale for this was to create an open atmosphere to explore trial experiences and assess acceptability of the intervention. A topic guide was developed to guide the interview; however participants were also encouraged to raise issues important to them. All interviews were tape-recorded and transcribed verbatim. 2.6. Analysis (i) Quantitative Data. Mann-Whitney U tests were used to analyse differences between the intervention and control group for changes in weight and body composition from baseline to 3 months and from 3 to 6 months, as these outcomes were not normally distributed. Psychological well-being and fatigue were analysed using independent and paired-samples t-tests to investigate differences between the intervention and control group on changes in these outcome measures between baseline and three months (the intervention period) and between baseline and six months (follow-up period). All statistical analyses were discussed and agreed with an independent statistician. (ii) Qualitative Data. Posttrial interviews with study participants were coded using NViVO qualitative analysis software to manage the dataset. Thematic analysis based on the approach described by Braun and Clarke [40] was used to analyse, iteratively code, and build up a final set of themes and subthemes. Two people coded a sample of interviews prior to compiling a final list and then quotes were extracted to exemplify themes. For the purpose of this paper the results will report on the following areas explored during interviews: reasons for participating in the trial (i.e., motivating factors) and belief in personal health and well-being benefits acquired from taking part in the trial (from a perceived increase in physical activity or other change, e.g., in secondary outcomes or motivations for being active). 3. Results 3.1. Participant Characteristics Baseline characteristics for the sample are shown in Table 1. Postnatal women who enrolled in the MAMMiS study were on average 33 years of age with their youngest child averaging 24 weeks. Most participants were primiparous, married, degree-educated, and on maternity leave at baseline. Most study participants had given birth vaginally. Changes in weight and BMI following pregnancy were evident; average weight gain was around 4.5 kg from prepregnancy (self-reported) to enrolment in the study (measured weight). There appeared to be differences in baseline weight between the two study groups, with intervention participants being heavier and more likely to be overweight/obese (OW/OB). Control participants were more likely to be breastfeeding at baseline. None of the differences were statistically significant. Although the group of women expressing interest in joining the study were representative of postnatal women in Scotland in respect to their age, deprivation, and urban/rural classification, women actually enrolling in the study were more likely to be from affluent Scottish Index of Multiple Deprivation (SIMD) areas [40] (data not shown) and were older (only 18% were under 30 years) compared with the total number of women who expressed an interest in joining the study. Trial participants (n = 35) who completed posttrial interviews were representative of the main trial sample in terms of their number of children, postnatal stage at study onset, BMI classification at study onset, and whether they remained or dropped out of the study [26]. 3.2. Study Flow All 65 participants completed baseline assessments and were randomised to the intervention or control group. All received the intended intervention or control condition and 92% (60/65) completed assessments at three months. Twenty-nine of the 33 intervention participants attended at least one pram walk, with the average number of walks attended being five (s.d. = 3.13) out of possible ten walks. At six-month follow-up 91% (59/65) of the sample completed assessments (see Figure 1). The number of participants not completing at least one assessment period (defined as withdrawals) was similar across the groups with no evidence that withdrawals differed from nonwithdrawals on baseline physical activity “stage of change,” weight status, SIMD, or number of children at home, although withdrawals were younger and had a younger baby (data not shown). 3.3. Effect of the Intervention on Postnatal Weight and Body Composition Outcomes Table 2 shows the median and interquartile range for weight, BMI, fat mass, and % fat mass at all measurement points during the study. There was no significant effect of the intervention on any weight/body composition outcome at three- or six-month follow-up (Table 2). Both groups showed a similar small decrease in weight/body composition outcomes from baseline to three months and from three to six months; however these time effects were associated with large confidence intervals and changes were not significant (Table 2). All outcomes remained higher in the intervention group compared with controls at all measurement points. Some participants did show a clinically significant change in BMI status over the six-month study period (Figure 2); that is, 25% (n = 5) of the 20 participants in the intervention group and 50% (n = 7) of the 14 participants in the control group who were overweight or obese at baseline went from obese to overweight or overweight to normal weight. Due to the small sample of overweight/obese participants this was not tested statistically. 3.4. Effect of the Intervention on Postnatal Psychological Well-Being and Fatigue Severity Over the study period there was little evidence of an effect of the intervention on psychological well-being; that is, there were no significant between groups' differences from baseline to three- (p = 0.09; 95% CI −0.77, 10.95) and three- to six-month follow-up (p = 0.19; 95% CI −9.68, 1.97) (see Table 3). Fatigue decreased in the intervention group from baseline to three months, while among control group participants fatigue increased from baseline to 3 months; this difference between the groups was significant (p < 0.01; 95% CI −36.49, −9.14). However, this pattern was reversed from three to six months, with fatigue increasing among intervention participants and decreasing among controls (p < 0.01; 95% CI 5.20, 34.86). Note: change measures were analysed using t-tests as these were normally distributed; however the median and IQ range scores are given in Table 4 as there was evidence of skew at each measurement point. 3.5. Posttrial Interviews Personal Reasons for Participating in the Trial and Wanting to Be Active. A variety of reasons were given for joining the trial. Many mentioned weight management and the role that physical activity can play in relation to losing weight, “I put loads of weight on, and I was really inactive all through my pregnancy, and I hated it, and I really wanted to, like start doing more, like exercise,” and the possibility of increasing activity to compensate for eating habits, “I like to keep my weight down and I love to eat loads of nice things…and I find that the more activity I do, you can have these treats more.” However, motivations for joining the trial were also related to the perceived general health benefits of pursing a more active lifestyle, including relaxation/mood improvement, “the long-term reason is that I think it benefits your health. And I think it increases, in terms of, it improves your mood.” Some postnatal women mentioned using activity to manage stresses of motherhood, “I used to do yoga and stuff, that was very relaxing…I really need the time to myself,” and/or to be a role model or better mother: “it is quite important for these two to see from early – we try to go for family walks at the weekend…so they get used to it. My mum's not one for being active.” 3.6. Belief in Benefits Gained by Becoming More Active as a Result of Joining the Trial Regardless of group allocation in the trial, many participants perceived a benefit from being in the study and many felt they had become more active as a consequence of participating in the trial. When describing their personal benefits gained from increasing physical activity during the trial, one participant described feeling “fitter and less fat.” However, for many participants their perception of the value of physical activity appeared to relate to the importance of physical activity for addressing day-to-day challenges to their well-being, such as through increasing their energy levels/stamina, promoting good sleeping habits, and improving mood/releasing stress, “more energy, without a doubt, sleep better, definitely helps mood I think. Kind of feel less tense – just overall well-being.” Some participants reported unanticipated benefits related to being active since joining the trial; these also tended to focus on the benefits of activity to enable participants to cope with their life as a mother, “I think the fresh air and getting out every day walking, we had a nice structure to our day. That helped me mentally, you know, just relax, not worry. It's my first baby and you spend a lot of time worrying, in general. Lots of worrying and I think that helped.” Unanticipated benefits were also reported by one mother reflecting on her return to work, “The nature of my job is extremely stressful and so busy throughout the day, that I love the space of getting out on my own and having time – I find a lot of my best ideas come from that space and actually getting away from it all, just to be alone with your thoughts,” although both work-life and mothering presented specific challenge in terms of making time for physical activity, “I feel there's always something to be done and I find it hard, and it always will be there's never going to come a point when I find oh yes I've got a spare hour to go to the gym or something. I think women find it harder to cut off from what is needing to be done.” 4. Discussion The MAMMiS study found no impact of the physical activity intervention on secondary health outcomes for postnatal women. Changes in weight and body composition, along with general psychological well-being, were not significantly different between the postnatal women receiving a physical activity consultation and taking part in pram walking and those receiving an NHS leaflet. There was a significant positive impact on fatigue at three-month follow-up but this was not sustained at six months. 4.1. Lack of Significant Effects on Weight and Body Composition The absence of a significant impact on weight/body composition-related secondary outcomes could be explained by the lack of a significant effect on objectively measured physical activity [25]. The small changes in weight/body composition in our study groups may indicate a natural return towards prepregnancy weight or may be due to the fact that over a third of women in both groups reported engaging in dietary control strategies to manage their weight. There is evidence that physical activity trials lacking a dietary component have little effect on postnatal weight outcomes [24] and among women in more general trials [41]. While weight management or concerns about body composition motivated some participants to take part in our trial [26] this may not be a good indicator of the sustained effort required to maintain a physically active lifestyle [42]. Participants in our trial also tended to be more affluent postnatal women who are less likely to experience long-term postnatal weight retention [43, 44] and more than half were of healthy prepregnancy weight suggesting less opportunity to demonstrate effect. 4.2. Lack of Significant Effects on Psychological Well-Being MAMMiS was the first study to consider the impact of a physical activity consultation combined with group pram walking on general psychological well-being in healthy postnatal women. Although participants discussed concerns for their well-being as a motivator for taking part in the trial, psychological well-being remained stable over time in both groups with no evidence of an impact of the intervention. This may reflect the absence of change in physical activity or the relatively high psychological well-being at baseline. There is some evidence that group physical activity interventions, including pram walking, can improve well-being or postnatal depression scores in healthy postnatal women [45] and in women with postnatal depression [46, 47]. However, it is unclear whether these outcomes are attributable to changes in physical activity or to the addition of social support provided via group exercise, which is an ongoing issue in the postnatal physical activity literature [8]. There is some suggestion from our qualitative study that participating in the trial improved participants' perception of well-being despite a lack of increased objectively measured physical activity. A pilot study that used physical activity consultation only (and promoted physical activity through walking) among women with postnatal depression was underpowered to detect changes in postnatal depression and like MAMMiS did not demonstrate a significant change in physical activity behaviour at follow-up [48]. The primary outcome for our trial was an objective assessment of moderate to vigorous physical activity (MVPA) [25], and this was not improved by the intervention. However, findings from the qualitative study indicate that many participants perceived an improvement to their physical activity behaviour and related this to perceived improvements in psychological well-being. Studies comparing self-reported versus objectively measured MVPA show that people tend to overestimate the intensity and duration of MVPA, particularly activities performed as part of daily life (e.g., household and caregiving activities) [49]. Thus, the intensity of the additional activity perceived by many participants may have been “light” rather than moderate or vigorous which may explain the discrepancy between the quantitative and qualitative physical activity findings. Alternatively, many participants reported fluctuating physical activity levels (which were seen as an unavoidable consequence of having young children) and felt that accelerometer measurement at the follow-up periods was not fully representative of changes to their physical activity. The psychological gains attributed to being more active were more likely to be proximal outcomes (i.e., concurrent or day-to-day) of importance to the participants. Previous research from a successful physical activity trial has shown that endorsing statements about more immediate outcomes after physical activity (e.g., “feel energized, better overall mood, enjoyment and sense of accomplishment”) [50, page 599] is related to being more active compared to more distal outcome expectancies (e.g., weight loss, fitness change). While fatigue severity significantly improved in the intervention group compared to the control group (with the control group showing a worsening of fatigue) from baseline to three months, this pattern was reversed between 3 and 6 months. There is some evidence for a positive effect of physical activity on fatigue [9]. This trial recruited women with postnatal depression and improvements were greater among those adhering to the programme [9], highlighting the importance of having an effect on physical activity behaviour. The participants in the MAMMiS trial were a heterogeneous sample and while randomisation ensured that there were no significant differences between the control and intervention groups it is likely that some of the differences within the groups might affect outcomes. For example, the age of infant, number of siblings, and feeding methods can impact on a mother's ability to take part in physical activity and lose weight. Prepregnancy and current weight and BMI will also affect the potential of a trial to impact on body composition outcomes as suggested by a greater effect in the small number of overweigh/obese women in our trial. Recruiting a more homogenous sample, by either narrowing the inclusion criteria or targeting clinically at-risk groups (e.g., overweight, gestational diabetes, or postnatal depression), might show more benefit from increasing physical activity than in a general healthy postnatal population, although evidence is still inconclusive and to date this has not been tested using objective measures [51, 52]. Furthermore using objective measures for assessing activity levels prior to enrolment might ensure recruitment of a more inactive population. The face-to-face interaction and type of intervention in our trial are likely to appeal to more affluent women who tend to have greater access to social support and fewer environmental and economic barriers to physical activity [53] while E-health or text interventions might reach a more disadvantaged population of postnatal women [54, 55]. 4.3. Strengths and Limitations The main strengths of the MAMMiS study were the use of a randomised controlled design, inclusion of an objective measure of physical activity (i.e., accelerometers), and a three-month postintervention follow-up. Prior to the conception and implementation of the trial these methods had not previously been used in physical activity promotion research among postnatal women [24]. The intervention approach used in MAMMiS [27] was theoretically and empirically sound as it had been shown to be effective in other groups and was relevant to research on motivators and barriers to physical change in the postnatal population and the precise content of the intervention was detailed with reference to the behaviour change technique taxonomy in use at the time [56]. The main limitation of the study was that despite attempts to recruit an insufficiently active sample, baseline levels of activity were higher than expected [25]. We used a stage of change questionnaire to screen eligibility prior to baseline measures; this subjective measure is therefore susceptible to self-report bias. It is also likely that our definition of insufficient activity was too high, that is, not achieving five sessions of physical activity per week of at least thirty minutes [30]. In addition, a number of factors can affect estimation of body fat using the bioelectrical impedance method; therefore we controlled for as many of these factors as possible (as described in Section 2); however we were unable to schedule body fat measurements with participants' phase of their menstrual cycle, which may have influenced the body fat results. 5. Conclusions and Implications Although there are substantial health and well-being benefits from participating in regular physical activity during the postnatal period, results from this study (and others) suggest we still lack a definitive approach to increasing physical activity participation among this group. Competing Interests The authors declare that they have no competing interests. Figure 1 Flow of participants through the MAMMiS study. Figure 2 Proportion of overweight and obese participants at baseline and three and six months in response to a 10-week physical activity intervention. Table 1 Participant baseline sociodemographic and clinical characteristics. Characteristic∗ Intervention (n = 33) Control (n = 32) Mean age ± SD, y 33.1 ± 4.1 33.8 ± 5.4 Mean age of youngest child ± SD, weeks (range) 24.0 ± 11.0 (9–48) 24.8 ± 15.5 (7–50) Median number of children (range) 1 (1–4) 1 (1–5) Marital status, n (%)      Married/cohabiting 27 (82)/5 (15) 27 (84)/5 (16)  Single 1 (3) 0 Employment status, n (%)      Maternity leave or housewife 31 (94) 24 (74)  Working (full or part time) 2 (6) 5 (16)  Unemployed 0 3 (9) Breastfeeding status, n (%)      Breast (exclusively or incl. solids) 13 (39) 18 (56)  Bottle (exclusively or incl. solids) 16 (49) 11 (34)  Mixed (can include solids) 4 (12) 3 (9.4) Method of delivery∗∗, n (%)      Vaginal labour 24 (73) 26 (81)  Caesarean section 8 (24) 6 (19) Mean self-reported prepregnancy weight ± SD, kg 65.2 ± 9.9 63.1 ± 8.2 Mean prepregnancy BMI ± SD, kg/m2 25.1 ± 4.1 23.6 ± 3.1 Prepregnancy BMI classification, n (%)      Underweight (<18.5 kg/m2) 0 1 (3)  Healthy range (18.5–24.9 kg/m2) 14 (54) 20 (69)  Overweight (25–29.9 kg/m2) 10 (39) 7 (24)  Obese (≥30 kg/m2) 2 (8) 1 (3) Mean measured current weight ± SD, kg 72.9 ± 10.9 68.2 ± 10.4 Mean current BMI ± SD, kg/m2 27 ± 4.2 25.5 ± 3.9 Current BMI classification, n (%)      Healthy range (18.5–24.9 kg/m2) 13 (39) 18 (56)  Overweight (25–29.9 kg/m2) 11 (34) 9 (28)  Obese (≥30 kg/m2) 9 (27) 5 (16) Body mass index, BMI.  ∗At enrolment. ∗∗Missing data from one participant from the intervention group. Table 2 Weight and body composition results at baseline and three and six months of follow-up in response to a 10-week physical activity intervention.   Intervention Control   Median (IQ range) Median (IQ range) Weight (kg)      Baseline (n = 33, 32) 72 (65, 80) 68 (62, 72)  Three months∗ (n = 30) 69 (63, 79) 65 (62, 72)  Six months∗∗ (n = 30,29) 68 (61, 79) 65 (61, 71) BMI (kg/m 2)      Baseline (n = 33, 32) 27 (24, 30) 25 (22, 27)  Three months∗ (n = 30) 26 (23, 29) 24 (22, 27)  Six months∗∗ (n = 30, 29) 25 (23, 29) 24 (22, 27) Fat mass (kg)      Baseline (n = 33, 31) 26 (20, 33) 22 (18, 26)  Three months∗ (n = 30) 25 (20, 32) 20 (17, 26)  Six months∗∗ (n = 29) 25 (18, 34) 19 (17, 25) % fat mass      Baseline (n = 33, 31) 35 (32, 41) 32 (30, 36)  Three months∗ (n = 30) 35 (35, 40) 31 (29, 35)  Six months∗∗ (n = 29) 34 (29, 41) 30 (27, 35) BMI, body mass index; IQ range, interquartile range. n = numbers in intervention and control group at each measurement time period. ∗Tested with Mann-Whitney U tests not between group differences from baseline to three months for weight (p = 0.80), BMI (p = 0.80), fat mass (p = 0.55), and % fat mass (p = 0.81). ∗∗Tested with Mann-Whitney U tests not between group differences three to six months for weight (p = 0.84), BMI (p = 0.58), fat mass (p = 0.66), and % fat mass (p = 0.78). Table 3 Psychological well-being at baseline and three and six months in relation to a 10-week physical activity intervention. Measurement period Intervention group (n = 30) Control group (n = 29) Mean (s.d.) Mean (s.d.) Baseline 86 (10.6) 90 (8.1) Three months 89 (9.9) 89 (8.2) Six months 88 (10.1) 92 (7.5) Note: the Adapted General Well-Being Index (AGWBI) Likert scale range is 22–110 with higher scores representing more positive well-being. Table 4 Fatigue score at baseline and three and six months in relation to a 10-week physical activity intervention. Measurement period Intervention group Control group median (IQ range) median (IQ range) Baseline1 44 (31, 66) 28 (20, 49) Three months2 26 (15, 58) 49 (26, 61) Six months3 49 (16, 62) 27 (17, 46) N in the intervention (I) and control (C) groups: 1I = 33, C = 32, 2I = 31, C = 29, 3I = 31, and C = 28. ==== Refs 1 Brown W. J. Pavey T. Bauman A. E. 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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/9103792Review ArticlePRP Treatment Efficacy for Tendinopathy: A Review of Basic Science Studies http://orcid.org/0000-0001-8457-325XZhou Yiqin 1 2 http://orcid.org/0000-0001-7279-0679Wang James H-C. 1 * 1MechanoBiology Laboratory, Department of Orthopaedic Surgery, University of Pittsburgh School of Medicine, 210 Lothrop Street, BST, E1640, Pittsburgh, PA 15213, USA2Joint Surgery and Sports Medicine Department, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai 200003, China*James H-C. Wang: wanghc@pitt.eduAcademic Editor: Mikel Sánchez 2016 16 8 2016 2016 91037927 4 2016 8 7 2016 20 7 2016 Copyright © 2016 Y. Zhou and J. H.-C. Wang.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Platelet-Rich Plasma (PRP) has been widely used in orthopaedic surgery and sport medicine to treat tendon injuries. However, the efficacy of PRP treatment for tendinopathy is controversial. This paper focuses on reviewing the basic science studies on PRP performed under well-controlled conditions. Both in vitro and in vivo studies describe PRP's anabolic and anti-inflammatory effects on tendons. While some clinical trials support these findings, others refute them. In this review, we discuss the effectiveness of PRP to treat tendon injuries with evidence presented in basic science studies and the potential reasons for the controversial results in clinical trials. Finally, we comment on the approaches that may be required to improve the efficacy of PRP treatment for tendinopathy. National Institute of Arthritis and Musculoskeletal and Skin DiseasesAR061395AR065949 ==== Body 1. Introduction Tendons are dense connective tissues that link muscles to bones. Thus, they transmit muscular forces to bones and enable joint movements. As a consequence, tendons are subject to large mechanical loads that may cause injuries and affect tendon function. In orthopaedic clinics, tendon and ligament injuries are one of the most prevalent health problems with about 16.4 million individuals seeking medical intervention every year in the United States [1, 2]. Among the tendons, Achilles, patellar, rotator cuff, and forearm extensor tendons are the easiest to injure due to overuse [3]. Typically, tendons are hypovascular. However, histopathological observations of chronic tendon injury or tendinopathy have revealed hypervascularity and disorganization in vessel distribution, which may affect the mechanical properties of tendons and induce pain. Tendinopathic tendons also feature interstitial gaps (microtears), discontinuous collagen fibers, and a number of degenerative changes including lipid deposition, proteoglycan accumulation, and calcification [2]. They also have decreased total collagen content, increased collagen type III/collagen type I ratio, increased expression of matrix metalloproteinases (MMPs), MMP-1, MMP-3, and MMP-9, and decreased expression of the MMP inhibitors [4, 5]. Apart from changes in tendon metabolism, high inflammation has been also reported at the microinjury sites that damage the tendon tissue if left untreated [6–8]. In recent years, a popular option for treating musculoskeletal injuries including tendinopathy is Platelet-Rich Plasma (PRP) [9–11]. Currently PRP is administered to almost 86,000 athletes in the United States and Europe to treat acute and chronic tendon, ligament, and muscle injuries [12]. Because of its wide spread use, it is estimated that the market value of PRP will reach $126 million this year [13]. The key components of PRP are the platelets, which are anucleate cytoplasmic fragments produced by megakaryocytes in the bone marrow [14]. Platelets have long been recognized to maintain tissue hemostasis. But accumulating evidence indicates that platelets may have a much wider role in tissue healing because they store and release a wide range of bioactive factors including growth factors (e.g., TGF-β and HGF). These factors are secreted by the dense granules, α-granules, and lysosomes in platelets [15]. Apart from platelets, PRP also has other components such as plasma, leukocytes, neutrophils, and monocytes with some leukocyte-containing PRP (L-PRP) containing residual erythrocytes, which also contain and/or release some bioactive factors. Plasma contains proteins such as albumin, globulins, fibrinogen, complement, and clotting factors and electrolytes, hormones, and biomarkers. The key components of leukocytes are neutrophils and monocytes, which may also release many bioactive factors and proteins. Neutrophils mainly release myeloperoxidase, bactericidal phagocytins, collagenase, gelatinase, and proteases. Monocytes secrete platelet-activating factor, TGF-β, VEGF, FGF, and EGF [16]. Many of these factors have been shown to influence tendon healing [17, 18]. The main advantages of PRP that enable its wide spread use are its safety and simple preparation and administration methods. PRP is safe because it is an autologous product derived from a patients' own blood and contains platelets and bioactive factors that can modify the biological microenvironment at injury sites, thus enhancing tissue healing. More importantly, PRP is not known to have any adverse effects unlike the commonly used nonsteroid anti-inflammatory drugs (NSAIDs) that are known to affect the gastrointestinal, cardiovascular, and renal systems [19, 20]. PRP is easy to use because of the simple preparation protocols; in fact, a number of PRP preparation kits are commercially available that are widely used in orthopaedic clinics. Besides, the application of PRP in the form of injections is also noninvasive and allows easy administration in clinical settings. Thus far, numerous basic science studies have shown the beneficial effects of PRP in healing tendon injuries. Specifically, growth factors in PRP have significantly enhanced the healing of tendon injuries such as tendinopathy [21–24]. These include PDGF, TGF-β, VEGF, EGF, IGF-I, FGF, and HGF [24–26]. When platelets are activated, not only are the growth factors released, but PRP also forms a fibrin gel, which provides a conducive bioscaffold for migrating cells thus incorporating new cells for tendon healing [27]. Therefore, PRP can be regarded as a promising treatment option for tendinopathy. However, the efficacy of PRP to treat tendinopathy in clinical trials is still controversial. Therefore, in this review we discuss evidence for the use of PRP presented in basic science studies conducted in vitro and in vivo under well-controlled conditions to determine the basis of PRP applications in clinical settings. 2. Basic Science Studies on the PRP Treatment of Tendinopathy 2.1. In Vitro Studies 2.1.1. Cell Proliferation First, PRP has been reported to induce the proliferation of the two tendon cell types, tenocytes and tendon stem/progenitor cells (TSCs). Tenocytes are the predominant cells in tendons and are essential to maintain tendon homeostasis. When tendons are injured, tenocytes proliferate and help in tendon repair; however, the proliferation rate of tenocytes is limited. A number of studies have shown that PRP can promote tenocyte proliferation in vitro [28, 29]. Wang et al. demonstrated that treatment of human tenocytes with platelet-rich clot releasate (PRCR) accelerated their proliferation in a dose-dependent manner [30]. Besides tenocytes, tendons also contain TSCs, which are tendon specific adult stem cells that make up to ~5% of the tendon cell population. TSCs were discovered in recent years in the tendons of mice, rats, rabbits, and humans [31–34]. TSCs have a high proliferation rate and PRCR has been reported to enhance it further [35]. In addition, PRP is also known to accelerate the proliferation rates of circulating stem cells such as bone marrow stem cells (BMSCs) and adipose derived stem cells (ADSCs) thereby accelerating tendon healing [28, 36, 37]. Therefore, ample evidence suggests that PRP has the ability to promote tendon cell proliferation. However, the optimal platelet concentration or the PRP composition needed for an effective treatment of tendinopathy is not clear [29]. Previous studies presumed that the effect of PRP may positively correlate with its concentration [28, 36, 37]. However, the “more is better” theory is not supported by studies because PRP-induced cell proliferation increased in a dose-dependent manner only up to a certain concentration. Specifically, the concentration of platelets from human PRP strongly induced tenocyte proliferation and migration only up to 1 × 106 platelet/μL concentration but above that cell proliferation and migration were reduced [38]. Moreover, the effect of rabbit PRP on cell proliferation in vitro also diminished when the concentration of PRP was 20% or more than the amount of the culture medium [39]. Interestingly, leukocytes in PRP, widely known for their deleterious effects, did not inhibit tendon cell proliferation but increased it in comparison to PRP containing no leukocytes [39]. 2.1.2. Tenocyte Differentiation A number of studies have demonstrated the ability of PRP to induce TSCs differentiation into tenocytes. PRCR was shown to induce rabbit TSCs to differentiate into tenocytes in vitro, and the newly formed tenocytes were α-SMA positive indicating that they were active tenocytes [35, 39]. One study specifically showed that PDGF in PRP promoted tenogenic differentiation of ADSCs [36]. It should be noted that currently there are no known tenocyte specific markers, and tenocyte differentiation is assessed by using a panel of markers including collagen types I and III and tenomodulin. Therefore, there is uncertainty regarding whether these differentiated cells are true tenocytes or tendon progenitor cells that have differentiated from TSCs to a certain extent. More importantly, PRCR treatment of TSCs did not induce the expression of non-tenocyte-related genes (PPARγ, Sox-9, and Runx-2) suggesting their safety in tendon injury treatments [35]. Autologous PRCR was also shown to inhibit the differentiation of rat TSCs towards nontenocyte lineages in a PRP dose-dependent manner [21]. Along these lines, an important finding was made by Zhang and Wang who reported that PRCR could only induce TSCs to differentiate into tenocytes but cannot reverse nontenocyte differentiation that is well underway in advanced stage tendinopathic tendons [40]. This finding may explain why PRP injection to treat advanced stage tendinopathy, where nontendinous tissues are predominant in the lesion sites, may not be effective in clinics. Such advanced stage tendinopathy may be effectively repaired by removing the tendon lesions by tissue debridement followed by PRP treatments. In this case, removal of the nontenogenic materials in the tendon that may negatively impact PRP effects may result in an improvement in the PRP treatment efficacy. 2.1.3. Anabolic Effects A number of in vitro studies have shown that PRP can influence the metabolism of tendon cells involved in the wound healing process. PRP was shown to increase total collagen synthesis in both tenocytes and TSCs [35, 39] and specifically enhance the gene expression of collagen types I and III [41]. An in vitro study on tendon tissues used PRP to treat horse flexor digitorum superficialis tendon and found that PRP treatment increased the expression of collagen types I and III and collagen type I/collagen type III ratio. However, in another cell culture study, PRP treatment did not significantly change the ratio of collagen type I/collagen type III although the gene expression of collagen types I and III significantly increased [42]. PRP not only affects collagen but also affects the expression of other tendon related genes and proteins. For example, PRP treatment increased the mRNA and protein expression of tenocyte-related genes (scleraxis (SCX) and tenascin-C) by activating the focal adhesion kinase (FAK) and extracellular-regulated kinase (ERK) 1/2 signaling pathways [43]. Furthermore, PRP treatment has been shown to enhance the expression of COMP, decorin, and tenascin-C [35, 42–46]. COMP is a tendon healing related glycoprotein, which is abundant in the normal tendon but is depleted in fibrous scar tissue. Decorin is a matrix proteoglycan and is also abundant in the tendon and plays a role in matrix assembly by binding to collagen type I fibrils. Tenascin-C is also a glycoprotein abundant in developing tendons. These noncollagenous matrix markers are the indicators of matrix synthesis, and an increase in their expression by PRP treatment also signifies the beneficial anabolic effects of PRP on tendons. However, PRP's positive influence on the anabolism of tendon cells has not been consistent in studies. One reason for this is the presence or absence of leukocytes in PRP. Based on the amounts of leukocytes, PRP may be classified as pure-PRP (P-PRP) containing a few or no leukocytes and L-PRP that contains more leukocytes. Since the protocols for preparing PRP vary in basic science studies and clinical trials, variations in PRP treatment effects should be expected. An in vitro study showed that PRP could stimulate human tenocyte proliferation and total collagen production, but it decreased the gene expression of collagen types I and III without affecting the collagen I/collagen III ratio. It should be noted that in this study PRP contained high levels of leukocytes [44]. In another study, increasing the platelet concentration in L-PRP significantly reduced collagen type 1A1 and collagen type IIIA1 synthesis in tendons, despite the delivery of more anabolic growth factors [47]. In yet another in vitro study, both L-PRP and P-PRP without leukocytes were found to enhance the gene and protein expression of collagen types I and III but L-PRP induced higher collagen type III and lower collagen type 1 expression than P-PRP [39]. Since a high collagen type III/collagen type I ratio indicates fibrosis that reduces the mechanical strength of tendons, it appears that administering L-PRP, especially when leukocyte levels are high, may lead to inferior outcomes in tendon healing. However, platelets and leukocytes had differential effects on the collagen ratio. While platelets positively influenced collagen type I and thereby increased collagen type I/collagen type III ratio, leukocytes increased the amount of collagen type III thereby negatively influencing the collagen type I/collagen type III ratio [45]. Furthermore, platelets decreased collagen type III levels but increased COMP and decorin while leukocytes had the opposite effects [45]. Together, these studies indicate clearly that leukocytes in PRP may negatively affect the anabolic effects of PRP and may lead to scar formation by increasing the collagen type III/collagen type I ratio [48]. 2.1.4. Catabolic Effects Pure-PRP has not been implicated in much catabolic activities while L-PRP is known to induce catabolic effects. Treatment of tenocytes with PRP, likely P-PRP, did not influence the catabolic molecules, MMP-3 and MMP-13 [41]. In fact, the expression of MMP-13 in tenocytes decreased after PRP treatment in vitro, and the platelet concentration negatively correlated with MMP-3 and MMP-13 levels [46]. However, PRCR upregulated MMP-1 and MMP-3 expression [44] likely because of the presence of large amounts of leukocytes in PRCR. In a recent study, we showed that L-PRP significantly induced the expression of MMP-1 and MMP-13 while P-PRP only slightly increased the expression of MMP-1 when compared to the control [39]. These studies clearly indicate that leukocytes in PRP are the key factors that induce catabolic actions in tendons/tendon cells. 2.1.5. Anti-Inflammation PRP also plays an active role in the inflammatory aspects of tissue healing. It was shown that PRP treatment of tendon cells in vitro could induce the release of HGF, which is a major anti-inflammatory growth factor [49]. Results from a recent study were also consistent with these findings and reported that PRP treatment increased VEGF and HGF expression in tendinopathic tendons [50]. Furthermore, the anti-inflammatory effect of HGF was shown by the reduction in the levels of COX-1, COX-2, and PGE2, the proinflammatory mediators in tendon cells treated with PRP or HGF. However, addition of HGF antibodies to the in vitro culture overruled this suppression suggesting that HGF plays a crucial role as an anti-inflammatory mediator in PRP preparations [49]. Similarly, injection of HGF antibodies into wounded mouse Achilles tendons reversed the reduction in PGE2, COX-1, and COX-2 protein levels caused by PRP or HGF injections [49]. Additionally, HGF in PRP increased the expression of IκBα, which is an inhibitor of NFκB [51] and a well-known regulator of immune response to infection. This is highly relevant in tendinopathy treatments because NFκB expression is upregulated in the tenocytes of tendons with inflammation [52] and therefore can be reduced after PRP treatment. Potentially, IGF-1 or PDGF in PRP can also inhibit IκB kinase α (IKKα) and suppress the production of NFκB thereby inhibiting inflammation [53]. In addition, it was shown that PRP treatment could decrease the expression of the proinflammatory cytokine, IL-6, and its ligand, CXCL-6, and IL-8 along with its ligand, CXCL-8, in tendon cells isolated from tendinopathic tendons [50]. Such reduction was shown to be effected specifically by HGF treatment that decreased the production of IL-6 and increased the anti-inflammatory cytokine, IL-10, levels [54]. TGF-β, also an anti-inflammatory cytokine present in PRP, has been also shown to control local inflammation [55]. However, leukocytes in PRP could potentially increase inflammation because they significantly increased the gene and protein expression of IL-1β, IL-6, and TNF-α in tendon cells [39]. This demonstrates that leukocytes can exacerbate inflammation in tendon cells but P-PRP without leukocytes can be anti-inflammatory because it decreased the gene expression of IL-6 when compared to untreated controls [39]. Similarly, PRP also reduced the gene expression and production of IL-6 in tendon cells when compared to cells treated with IL-1β [50]. It should be noted that IL-6 levels in tendon cells cultured in 2D and 3D hydrogels were increased by P-PRP [56]; therefore, future study may be still needed to determine the precise effects of P-PRP on IL-6. McCarrel et al. [45, 57] also showed that high concentration of leukocytes in PRP could induce higher expression of IL-1β and TNF-α when compared to P-PRP. Because platelets recruit leukocytes and progenitor cells to the sites of vascular injury and inflammation, they induce changes in cell permeability and promote chemotaxis and cell proliferation, which are essential steps in tissue repair. Macrophage, a kind of leukocyte, was reported to be involved in the maintenance of inflammatory state or innate immune response. It also induced tenocytes to synthesize relevant amounts of MCP-1/CCL2 and RANTES/CCL5, which could mediate migration of more monocytes/macrophages that can trigger inflammatory and angiogenic mechanisms [56, 58]. L-PRP can be directly involved in the inflammatory response by producing and releasing inflammatory mediators such as the cytokines, IL-1β and CD40L, and chemokines, CXCL1 and CCL2. Besides, PRP induces the expression of chemokine receptors, particularly CCR1, CCR3, CCR4, and CXCR4, thus regulating the inflammatory response associated with the healing process [55]. 2.1.6. Antibiotic Effects Furthermore, platelets are a source of active metabolites and proteins that promote heterotypic cell interactions, provide a surface together with cell-derived microparticles that promote coagulation and protease activation, and play an active role in sepsis and fighting infection (including promoting the innate immune response). Intravia et al. [59] compared the antibiotic effect of two different PRP preparations: PRPLP with lower leukocyte and platelet concentrations and PRPHP with higher leukocyte and platelet concentrations. The results showed that both PRP preparations significantly decreased bacterial (MRSA, P. acnes, S. epidermidis, and S. aureus) growth compared to whole blood but no difference in antibacterial activity was observed between the two products. This indicates not only the antibiotic effect of PRP but also that the leukocyte and platelet concentrations may not influence the antibiotic effects of PRP. Based on these in vitro studies, it is evident that PRP can enhance cell proliferation and also induce the tenocyte differentiation of stem cells thus replenishing cell resources for effective tendon healing. PRP also induces anabolic effects and increases collagen production thereby helping extracellular matrix restoration and tissue remodeling in healing tendons. In addition to platelets, plasma in PRP has been found to positively influence cell attachment and spreading on the fibrin scaffold, as well as promoting cell proliferation [60]. However, as shown above, platelet and leukocyte concentrations could significantly affect PRP function. Too high or too low platelet concentration is not advisable for the clinical treatment of tendinopathy with PRP. As discussed, L-PRP may cause higher catabolic and inflammatory actions than P-PRP indicating that leukocytes play a major role in reducing the efficacy of PRP. PRP versus Steroids. Lastly, current clinical practices commonly use corticosteroids to treat tendinopathy although they are known to cause multiple side effects. Application of dexamethasone, a corticosteroid, to hTSCs in culture induced nontenocyte differentiation visualized by a change in the cell shape, a near-complete suppression of collagen type I expression, and upregulation of non-tenocyte-related genes (PPARγ and Sox-9) especially at higher concentrations (>10 nM) [61]. Another study showed that dexamethasone reduced cell viability and increased the number of senescent cells. However, after cotreatment with 10% PRP, dexamethasone-induced senescence was markedly reduced [62]. Similarly, exposure to methylprednisolone alone decreased human tenocyte viability, but the addition of PRP partially reversed this negative effect [63]. Moreover, incorporation of corticosteroids with PRP injection was shown to compromise the potential beneficial effects of PRP on tendon cells with reduced cell viability at the site of tendon injury [64]. Thus, PRP may be a better alternative to treat tendinopathy than steroid treatments. 2.2. In Vivo Studies PRP has been shown to treat tendinopathy and promote tendon healing positively in in vivo animal studies. Intratendinous injections of PRP to treat tendinopathy in rat patellar and Achilles tendons increased joint mobilization and improved tendon fiber organization 25 days after treatment [65]. In this study, the authors also tested the toxicity of PRP by injecting it into normal tendons and found no difference in tested parameters between the control and PRP treated normal tendon thus showing that PRP poses no threats for its use in vivo [65]. Spang et al. [66] compared the effect of platelet concentrate and saline in a rat tendon healing model in vivo and found that at 14 days after treatment ultimate tensile load and energy absorbed to failure increased significantly in the platelet concentrates treated rats when compared to the saline treated rats. Histological results also showed more elongated cells indicating the presence of tenocytes and the absence of chondrocytes in the platelet concentrate treated group thus confirming the safety of PRP use in vivo. Lyras et al. [67] observed the effect of PRP gel in the early phase of patellar tendon healing and found that after 2 weeks PRP treatment increased load at failure by 72.2%, ultimate stress by 39.1%, and stiffness by 53.1% compared to untreated controls. Immunohistochemical analysis during the first two weeks of healing after PRP treatment further showed significant increase in blood vessel density in comparison with the control. Moreover, angiogenesis also significantly decreased in the PRP group 3 and 4 weeks after treatment [68]. PRP treatment also induced better cell orientation and tissue maturation. These results indicated that PRP could accelerate the tendon wound healing process. After a longer healing period, another study reported fewer neovessels in tendons after PRP treatment [65]. Lastly, PRP was also found to increase the expression of growth factors (IGF-I) in healed tendons [69]. Recent biologics approaches have also combined PRP with other tissue engineering modalities to enhance tendon healing. Particularly, stem cells in conjunction with PRP have shown promising results in the treatment of tendinopathy. PRP + BMSC treatment of tendon wounds in dogs significantly increased the strength and stiffness of healing tendons compared to the groups that used either of them separately [37]. Carvalho et al. performed an animal RCT (Randomized Controlled Trial) and found that, after 16 weeks, the combination of ADMSCs and platelet concentrate prevented the progression of lesion, induced a greater organization of collagen fibers, and decreased inflammatory infiltrates [70]. Furthermore, the combined use of TSCs and PRP showed synergistic effects (higher collagen I mRNA level) on tendon healing [43, 71]. However, injection of PB-MSCs (Peripheral Blood-Derived Mesenchymal Stromal Cells) and PRP together into injured sheep digital flexor tendons did not provide an additional benefit when compared to treatment with PB-MSCs alone [72]. Other modalities have also been used along with PRP to treat tendon injuries. Moshiri et al. reported that the use of platelet gel embedded within a 3D collagen implant in an Achilles tendon defect in rabbits was effective in healing, modeling, and remodeling the tendon [73]. Besides, Barbosa et al. reported that low-level laser therapy combined with PRP increased the deposition of collagen type I and enhanced regeneration of the tendon tissue [74]. Thus, with an exception of a few, most in vivo animal studies demonstrated that PRP treatment can enhance the healing of tendinopathic tendons. 3. Concluding Remarks Tendinopathy is a highly prevalent tendon disorder and plagues a range of individuals from the common person to elite athletes. It may cause extreme pain and affect tendon function, which can impair normal life activities. Because the mechanisms of tendinopathy are not completely understood, the current treatment options for this tendon disease remain largely palliative. PRP is a popular cell-free therapy that is used worldwide to treat tendinopathy. Basic science studies have consistently shown the beneficial effects of PRP on tendons including increased tendon cell proliferation, increased expression of anabolic genes and proteins, and reduced tendon inflammation. However, the efficacy of PRP in clinical trials is not consistent leading to the controversies regarding the PRP treatment efficacy. Among clinical studies, RCTs are considered to be the gold standard in assessing the efficacy of PRP treatments in clinical settings. However, when an RCT study yields negative results on PRP treatment of tendinopathy, the reasons for the negative results should be carefully analyzed. A number of factors could cause the negative results in RCTs. The most common is the relatively small sample size. Considering the fact that the extremely variable responses of humans to any treatment are unavoidable, the use of a small number of subjects in an RCT study will surely reduce the statistical power to detect the treatment effects by PRP. Another major factor in RCTs is the undefined PRP composition in the preparations used in RCT studies. Most clinical studies use PRP, prepared from a commercial kit, and a predetermined dose is administered for all types of tendon injuries and all patients irrespective of age, gender, disease history, and so forth. Basic science studies on the other hand indicate that stem cells could be used to promote tendon wound healing only in early stages but not so effectively in later stages that may be dominated by the presence of degenerative tissues. Therefore, the so-called “one-size-fits-all” approach may be the main reason for the conflicting results observed in the PRP treatment of tendinopathy in clinical studies. Instead of this, we propose the use of an individualized approach based on the conditions of individual patients. Such efforts may improve the efficacy of PRP for the treatment of tendon injuries and may effectively address the controversies on the PRP treatment efficacy in clinical trials. Acknowledgments The funding support from NIH/NIAMS (AR061395 and AR065949) for this work is gratefully acknowledged (James H-C. Wang). The authors thank Dr. Nirmala Xavier for her assistance in preparing this paper. Competing Interests The authors declare that they do not have any competing interests in this study. ==== Refs 1 James R. Kesturu G. Balian G. Chhabra A. B. Tendon: biology, biomechanics, repair, growth factors, and evolving treatment options Journal of Hand Surgery 2008 33 1 102 112 10.1016/j.jhsa.2007.09.007 2-s2.0-38849090654 18261674 2 Wang J. H.-C. Guo Q. Li B. Tendon biomechanics and mechanobiology—a minireview of basic concepts and recent advancements Journal of Hand Therapy 2012 25 2 133 141 10.1016/j.jht.2011.07.004 2-s2.0-84859832733 21925835 3 Bass E. 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==== Front J BiomarkJ BiomarkJBMJournal of Biomarkers2090-86602090-7699Hindawi Publishing Corporation 10.1155/2016/2198745Research ArticleThe Diagnostic Value of Serum C-Reactive Protein for Identifying Pneumonia in Hospitalized Patients with Acute Respiratory Symptoms http://orcid.org/0000-0003-1705-0875Ruiz-González Agustín * Utrillo Laia Bielsa Silvia Falguera Miquel Porcel José M. Department of Internal Medicine, Arnau de Vilanova University Hospital, Biomedical Research Institute of Lleida Foundation Dr. Pifarré (IRBLleida), 25198 Lleida, Spain*Agustín Ruiz-González: agustinruiz@saludalia.comAcademic Editor: Mark Duncan 2016 16 8 2016 2016 219874510 5 2016 25 7 2016 Copyright © 2016 Agustín Ruiz-González et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. The clinical diagnosis of pneumonia is sometimes difficult since chest radiographs are often indeterminate. In this study, we aimed to assess whether serum C-reactive protein (CRP) could assist in identifying patients with pneumonia. Methods. For one winter, all consecutive patients with acute respiratory symptoms admitted to the emergency ward of a single center were prospectively enrolled. In addition to chest radiographs, basic laboratory tests, and microbiology, serum levels of CRP were measured at entry. Results. A total of 923 (62.3%) of 1473 patients hospitalized for acute respiratory symptoms were included. Subjects with a final diagnosis of pneumonia had higher serum CRP levels (median 187 mg/L) than those with exacerbations of chronic obstructive pulmonary disease (63 mg/L) or acute bronchitis (54 mg/L, p < 0.01). CRP was accurate in identifying pneumonia (area under the curve 0.84, 95% CI 0.82–0.87). The multilevel likelihood ratio (LR) for intervals of CRP provided useful information on the posttest probability of having pneumonia. CRP intervals above 200 mg/L were associated with LR+ > 5, for which pneumonia is likely, whereas CRP intervals below 75 mg/L were associated with LR < 0.2, for which pneumonia is unlikely. Conclusion. Serum CRP may be a useful addition for diagnosing pneumonia in hospitalized patients with acute respiratory symptoms. ==== Body 1. Introduction Pneumonia is a leading cause of hospitalization and death in developed countries [1]. However, the discrimination of pneumonia from other lower respiratory tract infections (LRTI), where antibiotics are not required, is sometimes challenging, particularly in its early stages. In elderly patients, the clinical presentation is often nonspecific and interpreting chest radiographs can be difficult in patients with severe or previous pulmonary disease [2, 3]. Recent guidelines and review studies have suggested that serum C-reactive protein (CRP) may be helpful in distinguishing pneumonia from other acute respiratory illnesses [4, 5]. Nevertheless, the strength of this assertion is moderate as it is based on just a few previous studies whose designs were mainly retrospective and only included a small number of selected patients (e.g., chronic obstructive pulmonary disease (COPD) was sometimes excluded) [6–8]. A prospective study was therefore conducted in a large and unselected population with the goal of clarifying whether serum CRP could identify patients with pneumonia. 2. Patients and Methods 2.1. Subjects A prospective study was performed in a 500-bed university hospital, and patients with the following inclusion criteria were recruited during one winter season (2013-14): (1) adults > 18 years old admitted to the emergency ward, (2) respiratory symptoms (cough, sputum production, dyspnea, tachypnea, and pleuritic pain) as the main complaint, with or without fever, and (3) disease duration of less than two weeks. The exclusion criteria were (1) a final diagnosis of acute decompensated heart failure, pulmonary embolism, lung cancer, or an upper respiratory infection (e.g., acute pharyngitis, rhinitis, and sinusitis), (2) severe immunosuppression (e.g., human immunodeficiency virus infection and hematological diseases) or receiving immunosuppressive therapy (i.e., prednisone or an equivalent dose of 15 mg daily for 2 weeks or other immunosuppressant drugs), and (3) no hospitalization required. Hospitalization was considered necessary if patients met one of the following: (1) need for either respiratory support (Sa 02 < 90% or Pa 02/Fi 02 < 300), mechanical ventilation (respiratory acidosis with pH < 7.30), or vasopressor drugs, (2) worsening of associated comorbidities (e.g., decompensated heart failure), (3) inability to take oral drugs, or (4) no response to an initial adequate treatment in the emergency department. The local ethics committee approved this study and written informed consent was obtained from each patient. 2.2. Measurements At the initial visit to the emergency department, demographic and basic clinical information was collected from each patient. In addition to routine blood tests, a serum sample was obtained to measure CRP. Microbiological studies included sputum sampling for Gram staining and culture in all patients with LRTI, when possible, as well as blood cultures, and Streptococcus pneumoniae and Legionella pneumophila antigen detection tests in urine samples from those with pneumonia. Serology was ordered according to the criterion of the attending physician. To stratify severity in pneumonia patients, a validated prediction rule was used, namely, the CRB65 Severity Index [9]. Antibiotic therapy was administered in the emergency department based on the clinician's judgment. Blood samples for CRP were analyzed by a particle-enhanced turbidimetric assay following the manufacturer's instructions (Beckman Coulter, USA). The range of detection for this CRP assay is from 0.2 to 480 mg/L. 2.3. Disease Criteria LRTI was defined by the presence of at least one respiratory symptom (e.g., cough, sputum production, dyspnea, tachypnea, and pleuritic pain) plus at least one finding during auscultation (i.e., crackles) or one sign of infection (temperature > 38°C, shivering, leukocyte count >10, or <4 × 109 cells), regardless of antibiotic use. For pneumonia, a new infiltrate on the chest radiograph was also required. COPD was defined by postbronchodilator spirometric criteria, according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines, as FEV1/FVC ratio < 70%. Acute bronchitis was defined as LRTI in the absence of an underlying lung disease (COPD) or focal chest infiltrates on chest X-rays [10, 11]. The chest X-rays were reviewed by two clinicians with expertise in chest infections. The diagnosis of heart failure was made on clinical grounds (history, physical examination, chest radiograph, electrocardiogram, echocardiogram, and response to diuretic treatment), according to the American College of Cardiology/American Heart Association guidelines [12]. Pulmonary embolism was the final diagnosis when intraluminal filling defects were observed in computed tomographic pulmonary angiography. 2.4. Statistical Analysis Results are reported as means (SD) or medians (quartiles) as appropriate. Comparisons between groups were performed with χ 2 and Fisher's exact tests for categorical variables and the nonparametric Kruskal-Wallis and Mann-Whitney U tests for continuous variables. Sensitivity, specificity, and positive and negative likelihood ratios (LR), with confidence intervals based on exact binomial distribution, were calculated using standard methods. The area under the receiver operating characteristic curve (AUC) was used to establish the optimum cut-off points for CRP and leukocyte counts. Multilevel LRs were calculated as previously described with the use of equally spaced cut-off points [13]. Statistical significance was established at p ≤ 0.05. Calculations were performed with statistical software SPSS version 22.0 (Chicago, IL, USA). 3. Results and Discussion 3.1. Results A total of 1473 consecutive patients admitted to the emergency ward with acute respiratory symptoms were initially recruited, of whom 550 were excluded because of diagnoses other than LRTI (309), immunosuppressive condition or therapy (52), or no hospitalization requirement (189). Therefore, 923 patients with the final diagnoses of pneumonia (557) or other LRTI (366), namely, acute bronchitis and acute exacerbation of COPD, were included (Table 1). Patients with pneumonia had a median CRB65 score of 2 (IQR, 1–5) and microorganisms were found in 171 (30.7%), as follows: Streptococcus pneumoniae (118), Haemophilus influenzae (23), Chlamydophila pneumoniae (7), Legionella pneumophila (5), influenza A (5), Pseudomonas aeruginosa (4), Mycobacterium tuberculosis (4), Mycoplasma pneumoniae (2), and one for each of Moraxella catarrhalis, Staphylococcus aureus, Escherichia coli, and Enterococcus faecium. In comparison with other LRTI, patients with pneumonia were younger and had fewer comorbid conditions, higher temperatures, and both higher blood leukocyte counts and serum CRP levels. Additionally, more patients with pneumonia required admission to the intensive care unit, although in-hospital mortality was similar between groups (Table 1). In a logistic regression model, only 4 variables were independently related to pneumonia diagnosis: under 70 years of age (OR 2.83; 95% CI 1.95–4.09), temperature > 38°C (OR 2.51, 95% CI 1.65–3.81), leukocyte count > 15 × 109/L (OR 2.21, 95% CI 1.5–3.25), and serum CRP > 150 mg/L (OR 10.44, 95% CI 7.24–15.05). Serum CRP levels according to disease etiologies are shown in Figure 1. Subjects with pneumonia had higher serum CRP concentrations (median 187 mg/L) than those with exacerbations of COPD (63 mg/L) or acute bronchitis (54 mg/L, p < 0.01). The CRP reached AUC of 0.84 (95% CI 0.82–0.87) to distinguish pneumonia from other LRTI. The operating characteristics of different cut-off serum CRP values are shown in Table 2. For example, a serum CRP > 200 mg/L identified pneumonia with a sensitivity, specificity, and positive and negative LR of 44.8%, 95.6%, and 10.2 and 0.5, respectively. Moreover, the positive LR for several CRP intervals was calculated (Table 3). Thus, CRP intervals above 200 mg/L were associated with LR positive greater than 5 (for which pneumonia is likely), whereas CRP intervals below 75 mg/L were associated with LR lower than 0.2 (for which pneumonia is unlikely). It was also observed that CRP levels were not related to the variable “days of symptoms.” Indeed, median CRP values in patients with ≤2, 3–5, and ≥6 days of symptoms were 107 mg/L (45–196), 127 mg/L (45–214), and 123 mg/L (43–222), respectively (p = 0.70). 3.2. Discussion This study showed that serum CRP measurements upon admission to the hospital are useful for distinguishing patients with pneumonia from those with other LRTI. Previous studies have investigated the utility of serum CRP in identifying pneumonia. In a retrospective analysis of 60 patients with LRTI, 75% of patients with pneumonia had serum CRP levels > 100 mg/L, although no information was reported on specificity [6]. In a prospective study of 97 patients with pneumonia, it was found that only 5% had serum CRP levels below 50 mg/L [7]. In another prospective study of 284 patients with LRTI, a serum CRP > 100 mg/L had a specificity of 96% for labeling pneumonia [8], even though patients with acute exacerbation of COPD were excluded from the analysis. Based on these studies, the British Thoracic Society stated that the measurement of serum CRP on admission may be helpful in distinguishing pneumonia from other LRTI, with moderate weight being placed on this recommendation [4]. More recently, in a post hoc analysis of 545 patients with LRTI, Müller et al. [14] found that serum CRP had AUC of 0.76 in identifying patients with pneumonia. However, only 11% of patients included had acute exacerbation of COPD, and the technique used (a highly sensitive CRP) is not widely available in clinical practice. Finally, Bafadhel et al. [15] studied 158 patients with LRTI and concluded that a cut-off point for serum CRP of >48 mg/L had a sensitivity and specificity of 91% and 93% for pneumonia, respectively. Even so, patients with acute exacerbations of COPD were also excluded from this analysis. Previous studies usually recommended a single CRP cut-off point to dichotomize respiratory infections into either pneumonia or nonpneumonia categories. This approach eliminates much of the diagnostic information contained in laboratory tests that have continuous integer values. An alternative strategy for improving the discriminative properties of diagnostic tests is to generate multilevel LRs using various cut-off points and then apply them to convert the pretest probabilities into posttest probabilities of having pneumonia [16]. This new strategy, when applied to laboratory results in the borderline pneumonia range with the use of single cut-off points, generates low LRs that will not misclassify patients if the pretest suspicion for pneumonia is low. Medical literature commonly describes the operating characteristics of a diagnostic test by dichotomizing test results into normal and abnormal values and calculating their sensitivity and specificity. Unfortunately, this knowledge offers little clinical utility when evaluating individual patients because these indexes do not describe the probability of disease if the result is positive or negative, as LR does. Moreover, the rationale behind the use of multilevel LRs is that the dichotomization of test results does not assist in assessing to what degree a test result alters a clinician's estimation of the pretest probability of disease [13]. In our study, we sought to improve upon the shortcomings of the previous ones. First, this is the largest study performed on this issue to date. Second, the population was derived from unselected patients admitted to the emergency department with acute respiratory symptoms, including those with acute exacerbations of COPD. Third, the design of the study was prospective. Finally, the multilevel LRs for several intervals of serum CRP provided useful information on the posttest probability of having pneumonia. Thus, serum CRP intervals above 200 mg/L were associated with LR positive > 5 (for which pneumonia is likely), whereas CRP intervals below 75 mg/L were associated with LR < 0.2 (for which pneumonia is unlikely). Between these intervals, the serum CRP did not provide useful clinical information. One drawback of the study was that detailed information on physical signs was not provided. However, previous studies have shown that there are no findings from the history or physical examination capable of confidently ruling in or out the diagnosis of pneumonia [2]. Also, other potentially useful biomarkers of infection were not tested. For instance, procalcitonin has been reported to have high discriminative power in identifying pneumonia [17] although it is not widely available in emergency settings. 4. Conclusion The results of our study suggest that the routine use of serum CRP levels in hospitalized patients with acute respiratory symptoms can help clinicians to differentiate pneumonia from other respiratory infections. Indeed, serum CRP levels above 200 mg/L or below 75 mg/L make the diagnosis of pneumonia likely or unlikely, respectively. A further prospective validation of CRP ranges in an independent population is warranted. Competing Interests The authors state that they have no competing interests including any financial, personal, or other relationships with other people or organizations with the submitted work that could inappropriately influence or be perceived to influence their work. Figure 1 C-reactive protein levels in the study population. ∗ represents extreme values. Table 1 Baseline characteristics of patients admitted with lower respiratory tract infections.   Pneumonia (n = 557) Other lower respiratory tract infections∗  (n = 366) p value Demographics       Age, years 72 (56–80) 79 (71–85) <0.01 Gender, male 349 (63) 232 (54) 0.84 Comorbidity (Charlson index) 4 (2–6) 6 (4–7) <0.01 Clinical variables       Days of symptoms 4 (2–7) 4 (2–7) 0.27 Previous antibiotic treatment 164 (33) 100 (30) 0.40 Heart rate (bpm) 98 (84–110) 97 (84–110) 0.56 Respiratory rate (rpm) 28 (24–32) 28 (24–32) 0.79 Systolic blood pressure (mmHg) 123 (109–140) 133 (116–146) <0.01 Diastolic blood pressure (mmHg) 69 (60–78) 71 (63–82) <0.01 Temperature (°C)        No fever (<37°C) 197 (35) 219 (60) <0.01  Low-grade fever (37-38°C) 163 (29) 87 (24)  High-grade fever (>38°C) 197 (35) 60 (16) Laboratory findings       Basal pO2(mmHg) 61 (55–70) 62 (55–72) 0.19 C-reactive protein (mg/L) 187 (123–278) 59 (24–108) <0.01 Leukocyte count (×109/L) 13.3 (9.27–17.65) 10.8 (7.97–13.30) <0.01 Creatinine (mg/dL) 1.0 (0.8–1.3) 0.9 (0.7–1.2) 0.01 Microbiology findings       Microorganism found 169 (30.3%) 30 (8.9%) <0.01 Follow-up       Days in hospital 6 (4–10) 6 (4–9) 0.05 Intensive care unit transfers 37 (7) 4 (1) <0.01 In-hospital mortality 31 (6) 16 (4) 0.45 Quantitative variables are shown as medians (IQR 25–75) and qualitative variables as absolute numbers (percentages). ∗Other lower respiratory tract infections included acute bronchitis and acute exacerbations of COPD. Table 2 Operating characteristics of C-reactive protein for identifying pneumonia according to different serum values. Serum CRP (mg/L) Sensitivity, % (95% CI) Specificity, % (95% CI) LR+ LR− ≥50 91.3 (88.7–93.4) 43.9 (38.9–49.1) 1.6 (1.4–1.7) 0.2 (0.1–0.2) ≥100 82.4 (79.0–85.3) 72.3 (67.6–76.7) 3 (2.5–3.5) 0.2 (0.2-0.2) ≥150 65.1 (61.1–69.0) 87.16 (83.2–90.2) 5.0 (3.8–6.6) 0.4 (0.3–0.4) ≥200 44.8 (40.8–49.0) 95.6 (93.0–97.2) 10.2 (6.3–16.6) 0.5 (0.5–0.6) CRP, C-reactive protein; LR, likelihood ratio. Table 3 Multilevel likelihood ratios for different serum C-reactive protein intervals. Serum CRP (mg/L) Pneumonia (n = 557) Other lower respiratory tract infections∗  (n = 366) LR+ >250 171 7 16.3 (7.7–34.4) 225–250 40 5 5.3 (2.1–13.4) 200–225 32 4 5.3 (1.9–15.0) 175–200 53 17 2.0 (1.2–3.5) 150–175 58 13 2.9 (1.6–5.3) 125–150 46 23 1.3 (0.8–2.1) 100–125 49 30 1.1 (0.7–1.6) 75–100 31 42 0.5 (0.3–0.7) 50–75 19 60 0.2 (0.1–0.3) 25–50 27 67 0.2 (0.1–0.4) <25 20 98 0.1 (0.0–0.2) CRP, C-reactive protein; LR, likelihood ratio. ∗Other lower respiratory tract infections included acute bronchitis and acute exacerbations of COPD. ==== Refs 1 Jain S. Self W. H. Wunderink R. G. Community-acquired pneumonia requiring hospitalization The New England Journal of Medicine 2015 373 24 415 427 10.1056/nejmc1511751 2-s2.0-84953343700 26172429 2 Metlay J. P. Kapoor W. N. Fine M. J. Does this patient have community-acquired pneumonia? 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C-reactive protein: a clinical marker in community-acquired pneumonia Chest 1995 108 5 1288 1291 10.1378/chest.108.5.1288 2-s2.0-0028876117 7587431 7 Hansson L.-O. Hedlund J. U. Ortqvist A. B. Sequential changes of inflammatory and nutritional markers in patients with community-acquired pneumonia Scandinavian Journal of Clinical and Laboratory Investigation 1997 57 2 111 118 10.1080/00365519709056378 2-s2.0-0030941399 9200269 8 Castro-Guardiola A. Armengou-Arxé A. Viejo-Rodríguez A.-L. Peñarroja-Matutano G. Garcia-Bragado F. Differential diagnosis between community-acquired pneumonia and non-pneumonia diseases of the chest in the emergency ward European Journal of Internal Medicine 2000 11 6 334 339 10.1016/S0953-6205(00)00118-7 2-s2.0-0033675231 11113658 9 Chalmers J. D. Singanayagam A. Akram A. R. Severity assessment tools for predicting mortality in hospitalised patients with community-acquired pneumonia. Systematic review and meta-analysis Thorax 2010 65 10 878 883 10.1136/thx.2009.133280 2-s2.0-77957192940 20729231 10 Global Initiative for Chronic Obstructive Lung Disease Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease 2015 Global Initiative for Chronic Obstructive Lung Disease http://www.goldcopd.it/materiale/2015/GOLD_Report_2015.pdf 11 Woodhead M. Blasi F. Ewig S. Joint Taskforce of the European Respiratory Society and European Society for Clinical Microbiology and Infectious Diseases. Guidelines for the management of adult lower respiratory tract infections Clinical Microbiology and Infection 2011 17 supplement 6 e1 e59 21951385 12 Yancy C. W. Jessup M. Bozkurt B. J. 2013 ACCF/AHA Guideline for the management of heart failure. A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines Circulation 2013 128 16 e240 e327 10.1161/cir.0b013e31829e8776 23741058 13 Jaeschke R. Guyatt G. Sackett D. User's guides to the medical literature: III: how to use an article about a diagnostic test Journal of the American Medical Association 1994 271 703 707 8309035 14 Müller B. Harbarth S. Stolz D. Diagnostic and prognostic accuracy of clinical and laboratory parameters in community-acquired pneumonia BMC Infectious Diseases 2007 7, article 10 10.1186/1471-2334-7-10 2-s2.0-33947592780 15 Bafadhel M. Clark T. W. Reid C. Procalcitonin and C-reactive protein in hospitalized adult patients with community-acquired pneumonia or exacerbation of asthma or COPD Chest 2011 139 6 1410 1418 10.1378/chest.10-1747 2-s2.0-79958731375 21030489 16 Heffner J. E. Sahn S. A. Brown L. K. Multilevel likelihood ratios for identifying exudative pleural effusions Chest 2002 121 6 1916 1920 10.1378/chest.121.6.1916 2-s2.0-0036282641 12065357 17 Alba G. A. Truong Q. A. Gaggin H. K. Diagnostic and prognostic utility of procalcitonin in patients presenting to the emergency department with dyspnea American Journal of Medicine 2016 129 96 110 10.1016/j.amjmed.2015.06.037 2-s2.0-84940704627 26169892

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==== Front Can Respir JCan. Respir. JCRJCanadian Respiratory Journal1198-22411916-7245Hindawi Publishing Corporation 10.1155/2016/9795739Research ArticleThe Development of a Critical Care Resident Research Curriculum: A Needs Assessment Jain Sangeeta 1 http://orcid.org/0000-0003-0932-9243Menon Kusum 2 http://orcid.org/0000-0001-5008-2815Piquette Dominique 3 http://orcid.org/0000-0002-9488-3320Gottesman Ronald 4 Hutchison James 5 http://orcid.org/0000-0002-2939-8716Gilfoyle Elaine 6 * Group Canadian Critical Care Trials 7 1Department of Pediatrics, 2888 Shaganappi Trail NW, Calgary, AB, Canada T3B 6A82Children's Hospital of Eastern Ontario, 401 Smyth Road, Room 3446, Ottawa, ON, Canada K1H 8L13Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Room D108, Toronto, ON, Canada M4N 3M54Division of Critical Care, Department of Pediatrics, Montreal Children's Hospital, 1001 Decarie Boulevard, Room B06.3834.2, Montreal, QC, Canada H4A 3J15Neuroscience and Mental Health Research Program, Hospital for Sick Children Research Institute, 555 University Avenue, Toronto, ON, Canada M5G 1X86Section of Critical Care, Department of Pediatrics, Alberta Children's Hospital, 2888 Shaganappi Trail NW, Calgary, AB, Canada T3B 6A87Centre de Recherche du CHUM, Tour Viger, 900 rue Saint-Denis, Room R04-470, Montreal, QC, Canada H2X 0A9*Elaine Gilfoyle: elaine.gilfoyle@albertahealthservices.caAcademic Editor: Jack Kastelik 2016 16 8 2016 2016 979573919 10 2015 13 4 2016 19 5 2016 Copyright © 2016 Sangeeta Jain et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Conducting research is expected from many clinicians' professional profile, yet many do not have advanced research degrees. Research training during residency is variable amongst institutions and research education needs of trainees are not well understood. Objective. To understand needs of critical care trainees regarding research education. Methods. Canadian critical care trainees, new critical care faculty, program directors, and research coordinators were surveyed regarding research training, research expectations, and support within their programs. Results. Critical care trainees and junior faculty members highlighted many gaps in research knowledge and skills. In contrast, critical care program directors felt that trainees were prepared to undertake research careers. Major differences in opinion amongst program directors and other respondent groups exist regarding preparation for designing a study, navigating research ethics board applications, and managing a research budget. Conclusion. We demonstrated that Canadian critical care trainees and junior faculty reported gaps in knowledge in all areas of research. There was disagreement amongst trainees, junior faculty, research coordinators, and program directors regarding learning needs. Results from this needs assessment will be used to help redesign the education program of the Canadian Critical Care Trials Group to complement local research training offered for critical care trainees. ==== Body 1. Introduction Research is a mandatory activity for all Royal College of Physician and Surgeons of Canada (RCPSC) training programs, including the field of critical care. Trainees in critical care “are expected to participate in a basic or clinical research project” and must “demonstrate a basic understanding of biostatistics, study design, protocol writing, and manuscript preparation…under the direction of a scientist or Critical Care Medicine specialist” [1, 2]. This has become an integral part of training programs since we know that a better understanding of reported studies is linked to improved patient care and improvement in the academic mind of the physician [3]. In addition and on a more practical level, having published research is an advantage when applying for further training or employment [4]. Various barriers to successful research amongst trainees have been described in the literature, including lack of interest, lack of time, and poor understanding of research methods [3, 5]. In Canada, some individual residency programs organize a departmental-specific research course or have trainees who participate in university-wide research courses. These experiences are variable due to lack of resources of each individual program or courses not specific to critical care. Organizations that are not directly affiliated with official training programs may also be tasked to provide research training. The Canadian Critical Care Trials Group (CCCTG) is an internationally recognized group of critical care clinicians and researchers who collaborate to conduct high-quality critical care-based research. The CCCTG currently offers a “Resident Research Day,” where CCCTG members teach about various aspects of research (such as ethics in critical care research) followed by critical care residents and other critical care research trainees presenting their research projects for feedback from their peers and members of the CCCTG and Canadian Critical Care Translational Biology Group. This research day was designed for critical care trainees based on data from a focus group conducted with CCCTG faculty and trainee members (unpublished data). However, it has been several years since the implementation of this training curriculum; it is unknown whether there has been a change in local resources available to trainees or whether the needs of trainees have evolved. One aspect of the mission of the CCCTG is to “mentor and support aspiring investigators and future leaders in critical care research” (http://www.ccctg.ca/About-Us/Strategic-Directions.aspx). When developing a new curriculum (or revising an existing one), performing a needs assessment is the necessary first step [6]. Without a needs assessment, any curriculum developed risks devoting unnecessary resources to areas already mastered by the learner and/or paying insufficient attention to areas of particular weakness. Through a needs assessment, we aim to identify and describe what the learning needs are for research education in critical care in Canada. We plan to target both perceived needs (from the learners themselves) and unperceived needs (from program directors, new faculty researchers, and research coordinators) regarding trainees' needs. Specifically, we aim to gain insight into (1) perceived and unperceived knowledge gaps about the research process, (2) barriers to successful research during residency training, and (3) tools and skills that would be useful for trainees before they take on faculty positions with research requirements. The ultimate aim of this project is to obtain information useful for the development of a research curriculum targeting trainees currently involved in research, with the objective to encourage participation in research as part of their future careers. We hypothesize that there will be differences between the perceived and unperceived needs related to critical care research education, which will be highlighted when comparing responses amongst trainees, program directors, new faculty, and research coordinators. 2. Methods We surveyed various stakeholders including adult and pediatric critical care residents, new academic critical care faculty, critical care research coordinators, and critical care residency program directors during the July 2012 to June 2013 training year. A voluntary, confidential, self-administered online survey in English (via Survey Monkey®) was sent to eligible participants. Critical care residents were recruited by gathering their contact information from their program directors. We also contacted the Critical Care Department Heads across the country to identify new academic faculty (within 5 years of their appointment). Research coordinators were contacted via the Canadian Critical Care Research Coordinators Group. The research team contacted potential subjects by sending out an electronic letter explaining our research goals with a link to the survey attached. In order to maximize response rate, we emailed participants ahead of the survey and also sent two follow-up reminders after the initial survey was sent out, for a total study period of six months. The questionnaire for trainees (see Appendix A in Supplementary Material available online at http://dx.doi.org/10.1155/2016/9795739 for the full document) consisted of 4 domains: demographic information, current research activities, previous research training (including the CCCTG research day), and a self-assessment of knowledge with various aspects of research (e.g., developing a research question). A similar survey was sent out to university-affiliated critical care faculty who are within 5 years of completing their critical care fellowship. Questionnaires were also distributed to program directors and research coordinators. Data from Survey Monkey were downloaded to and analyzed in Microsoft Excel®. Quantitative data were analyzed with descriptive statistics (mean and median). For descriptive analyses, we used actual number of respondents for the denominator. We collapsed categories where appropriate to summarize responses in a meaningful manner. Comparisons were made between different respondents; however statistical comparisons were not pursued due to low numbers. Written comments were summarized and grouped into themes. Ethics approval was obtained from the Conjoint Health Research Ethics Board of the University of Calgary. 3. Results 3.1. Demographics Surveys were sent to a total of 235 potential participants with 86 completed surveys returned, yielding an overall response rate of 37%. Table 1 describes the summary of survey responses within each category of respondent. Table 2 describes the demographics of the critical care trainees who responded to the survey. 3.2. Trainee Responses Of the trainees who responded, 60.7% identified an interest in doing research as a part of their future careers in critical care. At the time of the survey, 86% of trainees were currently involved in a research project. Of the 28 respondents, the majority (75%) had projects representing clinical research, whereas a much smaller percentage was pursuing medical education-based projects or translational medicine projects (7% and 4%, resp.). Trainees noted that formal research training during their critical care fellowships provided them with a good overview of study design and ethics in research but did not give them the skills to be proficient in the specific areas of database management and managing a research team (Figure 1). Overall, trainees felt that, in order to assume future professional and research responsibilities, they would benefit from more training in most areas of research, but especially in statistics and writing grant proposals (Figure 2). Trainees felt most comfortable with their ability to navigate ethics in research. 3.3. Faculty Member Responses Faculty members who responded to the survey had all been trained in Canadian critical care programs. Of faculty members surveyed, 36% had advanced degrees in areas such as epidemiology, public health, and health administration. Eighteen percent of respondents spent a majority of their nonclinical time on research and had protected time to do so. Forty percent of faculty participated in formal research education outside of the CCCTG Research Day. In these research education programs, faculty identified areas of research not generally touched upon: managing a database management, developing budgets, and writing grant proposals. After formal training, faculty members still did not feel proficient in database management, creating a research budget or managing a research team (Figure 3). 3.4. Program Director Responses Program directors who responded to the survey represented nine of 21 (43%) adult and pediatric critical care residency programs from across Canada. Fifty-six percent of respondents represented medium-sized programs (six to eight critical care trainees), 22% of respondents represented smaller programs (three to five trainees), and 22% represented larger programs (greater than eight trainees). All program directors noted that more than 50% of their residents were involved in scholarly work and benefited from protected time during residency to pursue research. This protected time ranged from four weeks to over four months throughout the duration of the 2-year training program. The expectation at the end of residency for all but one program for which information was available is that critical care trainees would have completed a study and/or presented a poster/abstract at a meeting. Program directors generally had a positive perception of critical care trainees' readiness to perform various aspects of research by the end of their training but also identified managing a research team and database management as areas of relative weakness (Figure 4). 3.5. Research Coordinator Responses Forty-two percent of surveyed research coordinators stated that they work with critical care trainees and junior faculty. Research coordinators echoed that trainees and junior faculty were least proficient in the areas of managing a research team, developing a budget, and managing a database (Figure 5). Contrary to the feeling of program directors, research coordinators felt that trainees and junior faculty needed to develop proficiency in study design and setting up a research budget. Contrary to the feelings of both program directors and trainees, research coordinators felt that trainees and junior faculty also required more training on ethics in research (Figures 6, 7, and 8). 3.6. CCCTG Research Course Thirty percent of program directors felt that the CCCTG research course was valuable or very valuable, with an additional 20% feeling that it was somewhat valuable. Eighteen percent of faculty surveyed had participated in the CCCTG education program in the past; nonparticipants cited unawareness of the program or inability to get time off clinical work to attend the program as reasons for not attending the course. Trainees felt that the CCCTG would be a valuable resource in terms of research training, especially for research career mentorship as well as critiquing of research proposals. In terms of information delivery, 40% of program directors and previous attendees felt that longitudinal in-person seminars with a web-based component, such as access to online statistics teaching, would be the most beneficial. However, they recognized the challenge of obtaining time away from clinical duties and monetary perspective. One theme that came out from many of the qualitative comments was mentorship. Most of the respondents who are involved in research identified having a research supervisor. The level of involvement of the supervisor varied significantly and the amount of support the trainee felt he/she had also varied. Program directors most commonly cited increased availability of mentorship and easier access to statistical support as needed resources for trainees. 4. Discussion Our study demonstrated that trainees and junior faculty members still felt inadequately trained in several research-related areas following their critical care fellowships. This was in contrast with the expressed views of program directors who felt that trainees were generally well prepared for undertaking research. In addition, we found that there were some discrepancies between the areas of perceived need for further training between the trainees/junior faculty and the research coordinators surveyed. The discrepancy between program directors and research coordinators may be due to program directors trying to ensure that trainees learn general skills as a scholar whereas research coordinators are focused specifically upon research. Although almost half of coordinators who responded indicated they worked with trainees and/or junior faculty, the extent to which they worked with them was likely variable. Further work would have to be done to clarify this relationship and its possible link to the opinions of coordinators regarding research educational needs of trainees and junior faculty. The specific areas of need identified by trainees and junior faculty included database and research team management, how to manage a research team, and how to prepare a research budget, statistical analysis, and grant writing. In addition, research coordinators identified study design and research ethics as further areas in which research training was necessary for critical care trainees and junior faculty. Further study is required to more thoroughly understand why this difference of opinion exists. For example, what are the gaps that the research coordinators perceive trainees have with research ethics? This may prove to be an opportunity for research-focused organizations, such as the CCCTG, which could focus on areas of research training that are not well addressed currently by formal research education. The CCCTG could develop a longitudinal or rotating seminar series based upon these perceived gaps, adding value to the current CCCTG research curriculum. In addition, given their detailed knowledge about the research process, research coordinators may be recruited by the CCCTG as a valuable resource in educating trainees about real-life operational issues related to conducting research. To date, there are no studies describing critical care research education. Studies related to research education in general have suggested that factors that were most predictive of positive research experiences during training and continuation of a research career included intellectual satisfaction and training grants [7]. With this in mind, the CCCTG could take a role in announcing available grant opportunities and helping trainees with their applications. Another theme that has become prominent in the literature regarding research education is one of mentorship. Mentors are important not only in the undertaking of a research project, but also in helping trainees shape research careers [7]. Our finding of the importance of mentorship was echoed in the results of a recent survey of critical care medicine trainees. These authors found that trainees expressed a need for more mentorship of nonclinical activities, including research [8]. The CCCTG, along with critical care programs, could consider developing a network of researchers who would be interested in mentoring fellows with various parts of their research and who could also be helpful in research career mentorship. Currently, the CCCTG identifies mentors for junior faculty, but there is a clear need to extend this partnership to trainees and to further formalize the mentorship process. Because a majority of trainees were identified as having a research supervisor, the role of this mentor may not need to be in helping with the finer details of the research project, but more focusing on ways to construct a meaningful research career. It can be assumed that many research skills are honed through experience rather than via formal education, such as managing a research team and creating a budget. This makes longitudinal mentorship even more important as trainees are transitioning from primary work in designing a study to more challenging and managerial aspects of research. Another role for CCCTG mentors would be to expose trainees to researchers who excel in various different styles of research, such as Knowledge Translation, to give trainees a wide example of types of research available. Even though a majority of trainees were involved in a research project during their critical care residencies, only 60% were interested in pursuing research in their future career. A similar trend was found amongst junior faculty members, with only 20% of those surveyed currently in a research-based position. It is unclear whether this represents the whole group of trainees and junior faculty members, but it would be important to pursue so as to understand better the barriers to a successful research career. It is unclear whether this is due to waning interests, lack of protected time, competing clinical careers, or other barriers. In order to gain a deeper understanding about the data gathered above, hosting focus groups of trainees at their respective sites or via teleconference would be a good adjuvant. As a majority of respondents felt that a longitudinal research training program would be the most beneficial to improving research knowledge and skills, further work needs to be done to identify how curriculum content could be best disseminated (e.g., online seminars and live webinars) in spite of workload and monetary constraints. Consideration must be given to time available for these opportunities, given all the other responsibilities that critical care trainees have. Currently in Canada, this training is 2 years in length; for people interested in a research career, training beyond these 2 years may be required. This study's major limitation is the fact that there were differences in representation within the respondent groups. In particular, research coordinators were better represented than critical care trainees. In addition, our absolute number of respondents was small, especially in the trainee and junior faculty categories, yielding a response rate less than the 50–75% desired [9, 10]. Having robust data representing the opinions of junior faculty members would have been valuable as we felt that they would have the most insight into what their needs were transitioning from training to being a clinician and researcher. Future studies are needed to target input from these groups. Further, we do not know to what extent respondents and nonrespondents differ, introducing a potential source of bias into our results. Another limitation would be that faculty in nonacademic centres and community critical care physicians were not included in this study. These physicians may argue that intensive research training during fellowship would not have been necessary or valuable for their career progression. This information would be important to determine whether a dedicated CCCTG research course would be appropriate or necessary for all trainees. Finally, further engagement with program directors is planned regarding how they envision the CCCTG research curriculum complementing their locally available educational opportunities. We plan to create a summary of all the available research educational opportunities from around the country so that individual trainees could potentially access the resources they need to prepare them for a future research career. 5. Conclusion Research education is an important part of training for all critical care physicians. With the information from our survey, we envision a research curriculum that complements training provided locally so that all research education goals are met by the end of training. Although we focused on the needs of critical care trainees in Canada, these data may be more widely applicable to trainees of all postgraduate programs in Canada or internationally. As it has in the past, the CCCTG can continue to be a valuable resource for the education of current and future critical care trainees to help prepare them for a career in research. Supplementary Material Items contained within the online research education questionnaire sent to critical care residents during this study. Acknowledgments The authors would like to thank the CCCTG Grants and Manuscripts Committee for the coordination of the review of the paper. The authors would also like to thank the trainees, faculty members, research coordinators, and program directors who completed the survey. Appendix The Canadian Critical Care Trials Group Neill Adhikari, M.D. (Sunnybrook Health Sciences Centre), Eyad Althenayan, M.D. (Western University), Patrick Archambault, M.D. (CSSS Alphonse-Desjardins-CHAU Hôtel-Dieu de Lévis), Sean Bagshaw, M.D. (University of Alberta), Andrew Baker, M.D. (St. Michael's Hospital), Ian Ball, M.D. (Western University), Jane Batt, M.D. and Ph.D. (St. Michael's Hospital), Karen Bosma, M.D. (London Health Sciences Centre), Gordon Boyd, M.D. and Ph.D. (Kingston General Hospital), Laurent Brochard, M.D. and H.D.R. (St. Michael's Hospital), Karen Burns, M.D. (St. Michael's Hospital), Jeff Burzynski, M.D. (University of Manitoba Health Sciences Center), François-Martin Carrier (Centre Hospitalier de l'Université de Montréal), Emmanuel Charbonney, M.D. and Ph.D. (CSSSTR (Trois-Rivières) Centre Hospitalier Affilié Universitaire), Michaël Chassé, M.D. and Ph.D. (Centre de Recherche du CHU de Québec), Karen Choong, M.B. (McMaster University), Bryan Coburn, M.D. and Ph.D. (University Health Network-Toronto General Hospital), Deborah Cook, M.D. (McMaster University), Nick Daneman, M.D. (Sunnybrook Health Sciences Centre), Frederick D'Aragon, M.D. and Ph.D. (Centre Hospitalier Universitaire de Sherbrooke), Sonny Dhanani, M.D. (Children's Hospital of Eastern Ontario), Peter Dodek, M.D. (Center for Health Evaluation & Outcome Sciences), John Drover, M.D. (Queen's University), Guillaume Emeriaud, M.D. and Ph.D. (CHU Sainte-Justine), Shane English, M.D. (Ottawa Health Research Institute), and Eddy Fan, M.D. and Ph.D. (Mount Sinai Hospital). Catherine Farrell, M.D. (CHU Sainte-Justine), Niall Ferguson, M.D. (Mount Sinai Hospital), Patricia Fontela, M.D. and Ph.D. (McGill University Health Center), Jennifer Foster, M.D. (London Health Sciences Centre), Rob Fowler, M.D. (Sunnybrook Health Sciences Centre), Alison Fox-Robichaud, M.D. (Hamilton Health Sciences), Charles Francoeur, M.D. (CHU de Québec-Hôpital Enfant-Jésus), Elaine Gilfoyle, M.D. (Alberta Children's Hospital), Martin Girard, M.D. (Centre Hospitalier de l'Université de Montréal), Ronald Gottesman, M.D. (McGill University Health Center), Robert Green, M.D. (Dalhousie University), Donald Griesdale, M.D. (Vancouver General Hospital), Anne-Marie Guerguerian, M.D. and Ph.D. (Hospital for Sick Children), Richard Hall, M.D. (Dalhousie University), Betty Jane Hancock, M.D. (Children's Hospital), Paul Hébert, M.D. (Centre Hospitalier de l'Université de Montréal), Ahmed Hegazy, M.B. (University of Western Ontario), Margaret Herridge, M.D. (University Health Network-Toronto General Hospital), Jamie Hutchison, M.D. (Hospital of Sick Children), Tim Karachi, M.D. (McMaster University), Constantine Karvellas, M.D. (University of Alberta), Brian Kavanagh, M.D. (The Hospital for Sick Children), Michelle Kho, Ph.D. (McMaster University), Niranjan Kissoon, M.D. (British Columbia Children's Hospital), Karen Koo, M.D. (McMaster University), Andreas Kramer, M.D. (Foothills Medical Centre), Arnold Kristoff, M.D. (McGill University Health Center), Jim Kutsogiannis, M.D. (Royal Alexandra Hospital), Jacques Lacroix, M.D. (CHU Sainte-Justine), François Lamontagne, M.D. (Centre Hospitalier de l'Université de Sherbrooke), François Lauzier, M.D. (CHU de Québec, Hôpital de l'Enfant-Jésus), Osama Loubani, M.D. (Dalhousie University), Sheldon Magder, M.D. (McGill University Health Center), John Marshall, M.D. (St. Michael's Hospital), Claudio Martin, M.D. (London Health Sciences Centre), Victoria McCredie, M.D. and Ph.D. (Sunnybrook Health Sciences Centre), Lauralyn McIntyre, M.D. (Ottawa Health Research Institute), James McNally, M.D. (Children's Hospital of Eastern Ontario), Maureen Meade, M.D. (McMaster University), Nav Mehta, M.D. (Health Sciences North), Sangeeta Mehta, M.D. (Mount Sinai Hospital), Tina Mele, M.D. and Ph.D. (London Health Sciences Centre), Kusum Menon, M.D. (Children's Hospital of Eastern Ontario), Srinivas Murthy, M.D. (British Columbia Children's Hospital), John Muscedere, M.D. (Kingston General Hospital), Simon Oczkowski, M.D. (McMaster University), Joe Pagliarello, M.D. (Ottawa Hospital), Melissa Parker, M.D. (McMaster University), Dominique Piquette, M.D. and Ph.D. (Sunnybrook Health Sciences Centre), Bram Rochwerg, M.D. (Juravinski Hospital), Aimee Sarti, M.D. (Ottawa Hospital), Damon Scales, M.D. and Ph.D. (Sunnybrook Health Sciences Centre), Andrew Seely, M.D. (Ottawa Health Research Institute), Jason Shahin, M.D. (McGill University Health Center), Michael Sharpe, M.D. (London Health Sciences Centre), Jeffrey Singh, M.D. (University Health Network-Toronto Western Hospital), Tasnim Sinuff, M.D. and Ph.D. (Sunnybrook Health Sciences Centre), Yoanna Skrobik, M.D. (McGill University Health Center), Maude St-Onge, M.D. and Ph.D. (CHU de Québec, Centre Antipoison du Québec), Asumi Sugiura, M.D. (The Hospital for Sick Children), Eric Sy, M.D. (Regina General Hospital), Jennifer Tsang, M.D. (St. Catharines General Hospital), Marisa Tucci, M.D. (CHU Sainte-Justine), Alexis Turgeon, M.D. (CHU de Québec, Hôpital de l'Enfant-Jésus), Keith Walley, M.D. (St. Paul's Hospital), Matthew Weiss, M.D. (Université Laval), Dave Wensley, M.B. (British Columbia Children's Hospital), David Williamson, Ph.D. (Hôpital du Sacré-Coeur de Montréal), Brent Winston, M.D. (University of Calgary), Davinia Withington, B.M. (McGill University Health Center), Hannah Wunsch, M.D. (Sunnybrook Health Sciences Centre), Ryan Zarychanski, M.D. (Cancer Care Manitoba), and David Zygun, M.D. (University of Alberta). Competing Interests The authors declare that they have no competing interests. Figure 1 Response of critical care trainees to the question: “Formal research training during my fellowship in Critical Care has provided me with the skills to be proficient in the following areas of research.” Figure 2 Response of critical care trainees to the survey question: “I feel that, in order to assume my future professional responsibilities, I would benefit from more training in the following areas of research.” Figure 3 Junior faculty members' response to the question: “Formal research training during my fellowship in Critical Care provided me with the skills to be proficient in the following areas of research.” Figure 4 Response by program directors to the survey question: “I believe that graduates of our fellowship are comfortable with performing the following research activities.” Figure 5 Response of research coordinators to the question: “Within my institution, Critical Care fellows and junior faculty members are well trained in the following areas of research.” Figure 6 Comparing responses of program directors and research coordinators regarding trainees' abilities in applying appropriate study design when developing a research project. Figure 7 Comparing responses of program directors and research coordinators regarding trainees' abilities in navigating ethics in research. Figure 8 Comparing responses of program directors and research coordinators regarding trainees' abilities in creating and managing a research budget. Table 1 Number of survey respondents, response rate, and total response rate based on identified position. Title Number of surveys sent Number of respondents Response rate Research coordinators 60 38 63% Program directors 21 9 43% Junior faculty 40 11 27% Trainees 114 28 25% Total 235 86 37% Table 2 Demographics of critical care trainees who responded to the survey. Description of trainee Percentage of respondents Program stream    (i) Royal College stream 86%  (ii) Clinical Fellow stream1 14% Training program    (i) Adult 71%  (ii) Pediatric 29% Specialty prior to critical care    (i) Anesthesia 18%  (ii) General surgery 7%  (iii) Internal medicine 39%  (iv) Pediatrics 25%  (v) Other (cardiac surgery, emergency) 11% Prior advanced degree (master's, Ph.D.)    (i) Yes 14%  (ii) No 86% 1Clinical Fellows are generally trainees who come from other countries with the sole purpose of education. ==== Refs 1 The Royal College of Physicians and Surgeons of Canada Objectives of Training of Adult Critical Care Medicine, http://www.royalcollege.ca/cs/groups/public/documents/document/y2vk/mdaw/~edisp/tztest3rcpsced000888.pdf 2 The Royal College of Physicians and Surgeons of Canada Objectives of Training in Pediatric Critical Care Medicine, http://www.royalcollege.ca/cs/groups/public/documents/document/y2vk/mdaw/~edisp/tztest3rcpsced000891.pdf 3 Rothberg M. B. Overcoming the obstacles to research during residency: what does it take? The Journal of the American Medical Association 2012 308 21 2191 2192 10.1001/jama.2012.14587 2-s2.0-84870547006 23212493 4 Souba W. W. Tanabe K. K. Gadd M. A. Smith B. L. Bushman M. S. Attitudes and opinions toward surgical research: a survey of surgical residents and their chairpersons Annals of Surgery 1996 223 4 377 383 10.1097/00000658-199604000-00006 2-s2.0-0029868437 8633916 5 Takahashi O. Ohde S. Jacobs J. L. Tokuda Y. Omata F. Fukui T. Residents' experience of scholarly activities is associated with higher satisfaction with residency training Journal of General Internal Medicine 2009 24 6 716 720 10.1007/s11606-009-0970-4 2-s2.0-67349166629 19396500 6 Grant J. Learning needs assessment: assessing the need British Medical Journal 2002 324 7330 156 159 10.1136/bmj.324.7330.156 2-s2.0-0037132827 11799035 7 Zahtz G. Vambutas A. Hussey H. M. Rosen L. Resident research experience and career path association: a national survey of recent otolaryngology graduates Otolaryngology—Head and Neck Surgery 2014 151 1 46 51 10.1177/0194599814529408 2-s2.0-84930708692 24705222 8 St-Onge M. Mandelzweig K. Marshall J. C. Scales D. C. Granton J. Critical care trainees' career goals and needs: a Canadian survey Canadian Respiratory Journal 2014 21 2 93 95 10.1155/2014/520237 2-s2.0-84898466983 24724149 9 Draugalis J. R. Coons S. J. Plaza C. M. Best practices for survey research reports: a synopsis for authors and reviewers The American Journal of Pharmaceutical Education 2008 72 1, article 11 2-s2.0-39449084102 10 Burns K. E. A. Duffett M. Kho M. E. A guide for the design and conduct of self-administered surveys of clinicians Canadian Medical Association Journal 2008 179 3 245 252 10.1503/cmaj.080372 2-s2.0-48349095136 18663204

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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/9027489Research ArticleGamma-Ray Treatment of Echinococcus Protoscoleces prior to Implantation in Mice Reduces Echinococcosis Yuan Qing 1 http://orcid.org/0000-0002-3640-6526Li Bo 2 * Jiang Shiping 1 Zhao Qiang 1 Duo Ji 3 Huang Xiang 3 1Department of General Surgery, Ya'an People's Hospital, Ya'an, China2Hepatobiliary Surgery, The Affiliated Hospital of Luzhou Medical College, Luzhou, China3Ganzi State Hospital, Kangding, China*Bo Li: liboer2002@126.comAcademic Editor: Anna K. Walduck 2016 16 8 2016 2016 90274892 2 2016 20 4 2016 30 5 2016 Copyright © 2016 Qing Yuan et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Echinococcosis is a serious parasitic disease caused by Echinococcus tapeworms. Protoscoleces are sometimes released during surgical treatment for hydatid cysts, causing the recurrence of echinococcosis. Protoscoleces may be susceptible to radiation therapy. In this study Echinococcus protoscoleces were cultured in vitro and then divided into four different γ-ray irradiation dose groups (10 Gy, 20 Gy, 40 Gy, and 80 Gy) and a blank group. The protoscoleces were then implanted into the abdominal cavity of mice. Four months later, we observed that the incidence and weight of cysts declined with the increase of irradiation dose. γ-ray irradiation can suppress the generation of Echinococcus originated from protoscolex, the reason of which is due to the damaging to the structure of Echinococcus. Irradiation may prevent echinococcosis recurrence after surgical removal of hydatid cysts. ==== Body 1. Introduction Echinococcosis or hydatidosis is a parasitic disease in humans and animals that may cause serious problems. This type of zoonosis is characterized by growth of hydatid cysts in hosts. The two major infective species in humans are Echinococcus granulosus and E. multilocularis, which cause cystic echinococcosis and alveolar echinococcosis [1]. In addition E. vogeli and E. oligarthrus cause polycystic echinococcosis [2]. It is thought that 58% of the total population in Central Asia are at risk of cystic echinococcosis and surgical incidence for echinococcosis is as high as 10% in some Tibetan communities in western China [3]. Alveolar echinococcosis is also endemic in Central Asia with up to 6% of some village communities infected [3]. The major infective site for the two most common forms is the liver and occurs in approximately 75% of cases [2]. Hepatic echinococcosis can involve hepatic enlargement, epigastric pain, nausea, and vomiting. The sudden rupture of a cyst can cause allergic reactions including fatal anaphylaxis. The lungs are also commonly infected; ruptured cyst membranes in the lungs can sometimes be retained and act as a site for bacterial or fungal infection [4]. Prevention of infection is an important basis for control of echinococcosis; monthly deworming of dogs with praziquantel, as a key measure to control the Echinococcus parasites, has been used in western China while education and vaccination of livestock are also important [3]. Once infection has occurred the main treatment options are surgery to remove the cysts and drug therapy with benzimidazole compounds as well as other methods such as cyst puncture, aspiration, injection of chemicals, and reaspiration [4]. For E. granulosus the Echinococcus protoscolex is an important part of the tapeworm's life cycle and a central link for onset of hydatidosis in humans; protoscoleces attach to the intestinal mucosa of the dog and develop into the adult tapeworm after 30 to 80 days [2]. Since no drugs can effectively kill a protoscolex [5], it is an important factor that also affects the prognosis of surgical treatment [6, 7]. Implantation of protoscoleces caused by operative egress of hydatid cyst fluids during surgery is a serious issue for recurrence [8]. So an effective mechanism of killing the protoscoleces during surgery should assist with the treatment of echinococcosis by preventing recurrence. Radiation therapy has been considered as a method of treating alveolar echinococcosis that cannot be treated surgically [9, 10]. But the benefits of this method remain under debate [11]. The ionizing radiation of γ-rays can cause DNA damage, leading to structural and functional changes to DNA and metabolic changes in cells and in some circumstances cell death [12]. Radiation therapy with γ-rays is commonly used as a therapy in cancer to kill tumor cells [13]. An alternative method of using the killing potential of radiation therapy is to treat protoscoleces that may be released during surgery, in a similar way to the drug therapy during surgery and thus help prevent recurrence of the infection. Previous experimental results show that γ-ray irradiation kills protoscoleces in vitro [14, 15] but is less effective at killing protoscoleces in vivo [15]. The aim of this investigation was to evaluate whether γ-ray irradiation at different doses would effectively prevent Echinococcus protoscoleces from infecting mice. This information should provide details on whether radiation therapy could be used during surgery to prevent recurrence of echinococcosis. By simulation of γ-ray irradiation of E. granulosus cyst fluid during intraoperative spillover, we found that radiation treatment of protoscoleces decreased the incidence of echinococcosis and the weight of the resulting echinococci, while increasing the level of calcification. This study suggests that radiation therapy with γ-rays may be a useful method of reducing the recurrence of echinococcosis by killing protoscoleces in cyst spillover. 2. Materials and Methods 2.1. Echinococcus Protoscoleces Echinococcus granulosus protoscoleces were collected from a hydatid liver surgery in Sichuan Provincial People's Hospital (China). External capsule complete resection was performed and the specimen was maintained at lower than 4°C in an ice box and sent to the laboratory. The harvested liver hydatid cyst was placed on a laminar flow cabinet and its surface was disinfected with 75% alcohol. Cyst fluid was extracted with a 50 mL syringe, with repeated filling and emptying to ensure that the protoscoleces that had adhered to the endocyst were completely collected. After the cyst fluid was completely extracted, the sac wall was cut open, and the surface of the internal capsule was rinsed using physiological saline. The flushing fluid and the hydatid cyst fluid were collected and reserved. Then the sample was centrifuged at 3000 r/min for 5 minutes to obtain the yellow-white hydatid sands. After removing the supernatant, the hydatid sands were rinsed with flushing fluid (physiological saline containing 1500 μ/mL penicillin, 1000 μ/mL streptomycin) (penicillin-streptomycin solution: ThermoFisher Biochemicals (Beijing), Co., Ltd., China) 3 times. 1 mL of 20% trypsin solution (ThermoFisher Biochemicals (Beijing), Co., Ltd.) was added to the hydatid sands and left for 20 mins to digest the tissue debris. The hydatid sands were then again rinsed with flushing fluid and centrifuged, the supernatant was removed, and finally the protoscoleces were obtained and reserved. 2.2. Animals Specific-pathogen-free level female Kunming mice (n = 75), 6 weeks old and mean weight of 20 ± 4 g, were provided by the Animal Laboratory of Luzhou Medical College (Sichuan, China). The mice were housed at 20–25°C and 50 ± 5% humidity with ad libitum access to food and water and 12 : 12 h light/dark cycle. All procedures and animal experiments were approved by the Animal Care and Use Committee of Luzhou Medical College. 2.3. Incubation of Protoscoleces Ten mL RPMI-1640 medium (ThermoFisher Biochemicals (Beijing) Co., Ltd.) containing 20% fetal bovine serum (ThermoFisher Biochemicals (Beijing) Co., Ltd.) was added to the cuvette in which the protoscoleces were stored. After agitation, 0.2 mL of the solution was placed on a glass slide and the protoscoleces were counted under a BX50 inverted microscope (Olympus, Japan). The count was repeated for 5 times, and the average value was obtained. Then 20% methylene solution (ThermoFisher Biochemicals (Beijing) Co., Ltd.) was added to the collected solution to observe the survival rate of the protoscoleces (live protoscoleces were not dyed, while dead protoscoleces were dyed blue), which was required to be greater than 90% for this study. Finally the protoscoleces were cultured at a density of 2000/mL in RPMI-1640 medium containing 20% fetal bovine serum and incubated at 37°C in a CO2 incubator (ThermoFisher Biochemicals (Beijing) Co., Ltd.). 2.4. γ-Ray Irradiation The protoscoleces were cultured and allowed to grow and adapt to the media until evagination, and then they were γ-ray-irradiated. During the experiments, the medium containing the protoscoleces was evenly divided into 5 groups, of which one was the control group, and the other 4 groups were the experimental groups. The experimental groups were placed into a Cobalt-60 therapy unit (GWXJ80 type 60 Co teleradiation apparatus: Nuclear Power Institute of China) for irradiation. The exposure dose was controlled in a mediate-and-low range after referring to earlier experimental results [14] to avoid invalid implantation of the protoscoleces due to rapid death after the irradiation. The exposure doses of the 4 groups were 10 Gy, 20 Gy, 40 Gy, and 80 Gy, respectively. 2.5. Inoculation After irradiation, the protoscoleces were inoculated into mice that had been fasted for 1 day. The 75 female mice were randomly divided into 5 groups, 15 in each group, and the abdominal puncture inoculation method was adopted. The puncture site was selected from the left lower abdominal inguinal region towards the right upper abdomen. 1 mL protoscolex medium (about 400–600 protoscoleces) was injected, for each mouse. The mice resumed feeding 12 hours after this procedure. 2.6. Detection of Echinococcosis in Mice Four months after the implantation of protoscoleces, blood samples were collected from the mouse hearts to detect Echinococcus antibodies. To observe the occurrence of false positives, blood was also collected from 10 healthy mice. The detection methods were in accordance with the instruction of the kits (Diagnostic Kit for Antibodies to Echinococcus: Guangzhou Jianlun Biotechnology Co., Ltd., China). The absorbance value (optical density, OD) was read on Multiskan FC microplate reader (Thermo Fisher Scientific, USA) at 450 nm as a test wavelength (620 nm as a reference wavelength). According to the kit instructions, the OD of the negative control group should be less than 0.15, and the OD of the positive control group should be greater than 0.5, indicating that the operation is correct and the experiment is valid. The cut-off value (COV) was calculated according to COV = mean OD of negative control × 3.1. So the IgG positive response was defined as sample in the experiment group OD value ≥ COV value, and IgG negative response was defined as sample OD value < COV value. 2.7. Development of Echinococcus The mice were killed by cervical dislocation method. After echinococcosis was confirmed by antibodies against Echinococcus, abdominal laparotomy was performed. Intra-abdominal cysts were harvested, and after removing the outside tissues, they were dried using clean, dry gauzes and weighed. The suppression capsule rate (suppression capsule rate (%) = [1 − (mean weight of cyst in the experimental group/mean weight of cyst in the control group)] × 100%) and incidence of Echinococcus (incidence of Echinococcus (%) = number of inoculated mice with hydatid cysts/total number of inoculated mice × 100%) of each group were analyzed. 2.8. HE Staining Hematoxylin and eosin (HE) staining of thin sections of the intra-abdominal cysts was performed according to standard techniques. 2.9. Calcium Alizarin Red Staining Calcium alizarin red staining was performed according to the recommended procedure of the kit (GENMED Paraffin section calcium alizarin red staining kit: Shanghai Jiemei Genetic Pharmaceutical Technology Co., Ltd., China). 2.10. Statistical Analysis All statistical analyses were conducted using SPSS version 17.0 (SPSS Inc., Chicago, IL, USA). Data were expressed as median (quartile) and analyzed by Kruskal-Wallis H test. Mann-Whitney U was applied to adjust data in pairwise comparisons according to the characteristics of the data. Proportions were analyzed by Chi-square analysis. A P value of <0.05 was considered statistically significant. 3. Results 3.1. Model Development After abdominal cavity implantation of γ-ray irradiated protoscoleces, the mice were in good condition and none of the mice died. Three months after implantation, soft bumps were palpable at the abdomen wall in individual mice. 3.2. Echinococcosis Rate Estimated by Antibody Detection By referring to a COV = mean OD of negative control group × 3.1, we obtained the COV = 0.43 for our testing. Our results showed that serum detection was positive in all mice that had incubation of protoscoleces, and serum detection was negative in mice without incubation of protoscoleces. 3.3. Visual Observation of Cysts Cysts were found in the abdominal cavity of the mice, and most of them were located in the abdominal wall and mesentery (Figure 1). Through observation and comparison, we found that the cysts in the abdominal cavity in the control group had a larger volume and were lightly adhesive to the surrounding tissues. The cysts were of rounded shape, white, pale yellow, or transparent, and the cystic wall was elastic and contained clear fluids. On the other hand, the cyst volumes in the experimental groups were relatively smaller and more adhesive to the surrounding tissues. The cystic wall was thickened and some of them presented as a degraded morphology (Figure 2). In some mice in the experimental groups, no cysts were found in the abdominal cavity. 3.4. Incidence of Echinococcus by Abdominal Cavity Examination In some mice in the experimental groups, we did not find any cysts in the abdominal cavity. Analyses found that incidence of cysts in each of the experimental groups reduced with increasing radiation dose (χ 2 = 7.82, P = 0.005) (Table 1), indicating that the incidence of cysts is suppressed with increasing exposure dose. 3.5. Weight of Isolated Cysts The median weight of cysts decreased with radiation treatment (Z = 32.729; P < 0.001), from 157.80 (0.15) mg (median (Quartile)) in the control group to 35.80 (0.07) mg in the 10 Gy group, 0.00 (0.08) mg in the 20 Gy group, 0.00 (0.09) mg in the 40 Gy group, and 0.00 (0.00) mg in the 80 Gy group (Table 2). In view of the data distribution of the cysts weights in the experimental groups, we used the median weight of each group to calculate the average weight of the hydatid cysts and the suppression capsule rate (Table 2). At 80 Gy, this was 99.61% capsule suppression. 3.6. Analysis of Cyst Morphology In the control group, HE staining of cysts showed that the cyst wall structure was uniform and clear, in which we could observe the germinal layer (Gl), cuticle layer (Cl), and fibrous tissue (Ft). Therefore we confirmed that the cyst was Echinococcus, and we did not find any asci or protoscoleces in the Gl (Figure 3). Comparing the Gl, Cl, and Ft in Echinococcus slices from each group showed that, in the control group, the Echinococcus cyst wall had uniform thickness. Cells were completely distributed in the Gl with consistent thickness, and no protoscoleces or brood capsules were found. The Cl showed good morphology and was transparent. The Ft was closely textured and tightly adhered to the Cl and tissues (Figure 3). On the contrary, we found a variety of structural damage in the Echinococcus cyst walls in the experimental groups (Figure 4). In the 10 Gy group the hydatid cysts' germinal layers were coarse and in some cases had disappeared; the germinal layer and cuticle had separated and formed vacuoles. In the 20 Gy group the hydatid cyst cuticle occurred at separation. In the 40 Gy group the hydatid cyst cuticle and fiber layer occurred at separation and formed vacuoles. In the 40 Gy group the Echinococcus fiber layer was isolated. While in the 80 Gy group the hydatid cysts' cuticles ruptured. 3.7. Calcification of Echinococcus Alizarin red staining was uniform without calcium staining phenomenon in the control group. Meanwhile, we found intermittent calcareous infarct phenomenon in the CI in the experimental groups, and this phenomenon becomes more significant with increasing exposure dose (Figure 5). In the 10 Gy group 1/3 of the inner surface of the cuticle had apparent calcium deposits, in the 20 Gy group the whole cuticle had calcium deposits and inside the cuticle appeared wave-like, in the 40 Gy group the cuticle and the hydatid cyst layers had calcium deposits, and in the 80 Gy group the hydatid cyst cuticles collapsed and formed calcified lesions and the cuticle fractured. 4. Discussion During surgery to remove hydatid cysts, cyst fluid spillover may cause protoscoleces to attach and the echinococcosis recurs. Drug therapy is generally used to try and kill protoscoleces to prevent this from happening but is often ineffective [6, 7]. The aim of this study was to see if irradiation of cultured protoscoleces using γ-rays could prevent echinococcosis in mice when the protoscoleces were implanted into the abdominal cavity, as a model for the human surgical situation. The results showed that the incidence of echinococcosis was decreased with irradiation of protoscoleces. Previous studies have investigated different methods of preventing recurrent echinococcosis after surgical resection of hydatid cysts; these include drug therapy with recommended drugs such as albendazole [16] and other methods such as inhibition of larval growth with essential oils [17], the use of high-intensity focused ultrasound alone [18] and in combination with a superabsorbent polymer [19, 20], and the use of fungal chitosan [21]. The results of this study suggest that irradiation with γ-rays is another method that should be seriously considered as at low doses it was at least as effective as the other methods tested. Irradiation has previously been used to treat hydatid cysts that cannot be removed surgically [22], but irradiation is apparently more successful at killing protoscoleces in vitro than in vivo [15]. In this study, after abdominal cavity implantation of γ-ray irradiated protoscoleces in mice, Echinococcus were found in the control group, while the incidence of Echinococcus in the experimental groups reduced with increased irradiation dose. This result indicated that the DNA damage in proscolex cells caused by these doses of γ-rays was repairable because there was Echinococcus formation in the experimental groups. However, with increased exposure dose, the ability to repair appears to decrease, and the incidence of the Echinococcus reduces, suggesting a dose-effect relationship between the exposure dose and incidence. In the exposure dose range of 10 Gy to 20 Gy, the weight of the Echinococcus produced by protoscoleces reduced with increasing exposure dose, indicating that the structural damage to DNA in the cells of a protoscolex may lead to its biological dysfunction and result in different degrees of Echinococcus development. However, in the range of 20 Gy to 80 Gy, the increase of exposure dose no longer induced variations in Echinococcus weight. Combined with the variation of incidence of Echinococcus, we may consider that in the early irradiation with different doses, the common effect of the damage of protoscolex cells DNA and the body's immune reaction leads to different incidence of the Echinococcus. However, once the Echinococcus is generated, the body's immune reaction no longer impacts on the Echinococcus, which is consistent with Smyth and Heath's opinion [23]. Our subsequent studies found that though the irradiated protoscolex can still generate Echinococcus, the effects of the γ-ray are sustained, and its targets are mostly focused on the germinal layer of the generated Echinococcus. The germinal layer is the material basis of the cuticle layer, while the cuticle layer in turn plays a protective role in the structural function of the germinal layer. In HE staining results, we found that part of the cuticle layers in the experimental groups appeared to show nonuniform growth, as well as detachment, collapse, and even fracture of the fibrous layer, indicating that the normal physiological functions of the germinal layer of the Echinococcus generated by an irradiated protoscolex were damaged. Alizarin red staining results showed that Echinococcus in the experimental groups contained a large amount of calcification, indicating that the necrotic calcification process of the Echinococcus generated by an irradiated protoscolex was accelerated. This study has some limitations, as the results are preliminary; the mechanisms involved in protoscoleces damage were not investigated. Using a mouse model to investigate the implantation of irradiated protoscoleces into the abdominal cavity may not give the same results as preoperative irradiation in a clinical situation, so these results need to be investigated further in other models and eventually in a clinical study in humans. 5. Conclusion In conclusion, we believe that irradiation with γ-rays can kill protoscoleces [14] and reduce the incidence of echinococcosis. Its effects can reduce the generation of Echinococcus. If this function of γ-rays can be applied to laparoscopic treatment of echinococcosis or other preoperative treatments, postoperative recurrence caused by implantation of echinococcosis may be significantly reduced. However, the full details of any effective method of γ-ray therapy remain to be investigated in further studies. Competing Interests The authors declare that they have no conflict of interests. Figure 1 Visual observation of cysts. (a) Rounded hydatid cysts (circled with a dotted line) in the intraperitoneal space of mice in the control group. (b) Rounded hydatid cysts (circled with a dotted line) present the cyst and surrounding tissue dense adhesions in the intraperitoneal space of mice in the 40 Gy group. (c and d) Rounded hydatid cysts (circled with a dotted line) present the degraded morphology in the intraperitoneal space of mice in the 80 Gy group. Figure 2 Visual observation of cysts. Control group (a, c) Echinococcus granulosus volume is larger, the wall is transparent, and the cystic fluid is clear, compared to the experimental group ((b) at 40 Gy and (d) at 80 Gy) where Echinococcus granulosus volume is smaller, the wall is consolidated, and the cystic fluid is turbid. Figure 3 Hematoxylin and eosin (HE) staining to show the structures of the hydatid cysts. HE staining to show the structures of the hydatid cysts typical Echinococcus structures that can clearly be seen in the germinal layer (Gl), the cuticle Layer (Cl), and fibrous tissue (Ft) (×200). Figure 4 H&E staining to show the structures of the hydatid cysts in the irradiated groups. (a) The hydatid cyst germinal layer (Gl) cells were coarse in the 10 Gy group (×200). (b) The hydatid cyst germinal layer disappeared in the 10 Gy group (×200). (c) The hydatid cyst germinal layer and cuticle separated and formed vacuoles in the 10 Gy group (×200). (d) The hydatid cyst cuticle occurred at separation in the 20 Gy group (×200). (e) The hydatid cyst cuticle occurred at separation in the 20 Gy group (×200). (f) The hydatid cyst cuticle and fiber layer occurred at separation and formed vacuoles in the 40 Gy group (×100). (g) Echinococcus fiber layer tissue isolation in the 40 Gy group (×400). (h) Echinococcus fiber layer tissue isolation in the 40 Gy group (×400). (i) Hydatid cyst cuticle rupture (×200). (j) Hydatid cyst cuticle rupture in the 80 Gy group (×200). Figure 5 Calcium alizarin red staining of hydatid cysts. (a) Echinococcus granulosus stained uniformly and had no calcium deposition in the control group (×200). (b) (×50). (c) Echinococcus granulosus with 1/3 of the inner surface of the cuticle appearing to have calcium deposition in the 10 Gy group (×200). (d) (×400). (e) Whole Echinococcus granulosus cuticles had calcium salt deposits in the 20 Gy group (×50). (f) 20 Gy group hydatid cyst cuticle layer had calcium deposition, while inside the cuticle showed wave-like erosion (×400). (g) 40 Gy group Echinococcus granulosus cuticles had calcium salt deposits (×200). (h) 40 Gy group hydatid cyst layers had calcium deposition (×400). (i) 80 Gy group hydatid cyst cuticles collapsed and formed calcified lesions (×100). (j) Echinococcus cuticles collapsed and showed calcification in the 80 Gy group (×400). (k) Hydatid cyst cuticle fracture in the 80 Gy group (×50). (l) (×200). Gl: germinal layer; Cl: cuticle layer; and Ft: fibrous tissue. Table 1 Analysis of the incidence of cysts in each experimental group. Group Number of inoculated mice with cysts Total number of inoculated mice Incidence of cysts (%) P value∗ Control 15 15 100.0 0.005 10 Gy 12 15 80.0   20 Gy 5 15 33.3   40 Gy 5 15 33.3   80 Gy 4 15 26.7   Note. ∗Chi-square test. Table 2 Cysts weight and suppression capsule rate. Group n Median (mg) Quartile (mg) Mean (mg)Δ Suppression capsule rate (%) Control 15 157.80 0.15 15.90 — 10 Gy 15 35.80∗ 0.07 4.20 73.55 20 Gy 15 0.00∗ 0.08 1.92 87.92 40 Gy 15 0.00∗ 0.09 1.92 91.48 80 Gy 15 0.00∗# 0.00 0.06 99.61 Note. Suppression capsule rate (%) = [1 − (mean weight of cyst in the experimental group/mean weight of cyst in the control group)] × 100%. IQR: interquartile range; ∗ P < 0.005 (0.05/10, adjusted P value) versus control group; # P < 0.005 (0.05/10, adjusted P value) versus 10 Gy. 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Use of albendazole sulfoxide, albendazole sulfone, and combined solutions as scolicidal agents on hydatid cysts (in vitro study) World Journal of Gastroenterology 2009 15 1 112 116 10.3748/wjg.15.112 2-s2.0-59249094088 19115476 6 Gollackner B. Längle F. Auer H. Radical surgical therapy of abdominal cystic hydatid disease: factors of recurrence World Journal of Surgery 2000 24 6 717 721 10.1007/s002689910115 2-s2.0-0343729924 10773125 7 Uhl W. Löffler H. Zimmermann A. Tcholakov O. Gloor B. Büchler M. Surgical treatment of echinococcosis of the liver Swiss Surgery 1998 5 3 126 132 10414184 8 Skuhala T. Trkulja V. Runje M. Vukelić D. Desnica B. Albendazolesulphoxide concentrations in plasma and hydatid cyst and prediction of parasitological and clinical outcomes in patients with liver hydatidosis caused by Echinococcus granulosus Croatian Medical Journal 2014 55 2 146 155 10.3325/cmj.2014.55.146 2-s2.0-84901350690 24778101 9 Ulger S. Barut H. Tunc M. Radiation therapy for resistant sternal hydatid disease Strahlentherapie und Onkologie 2013 189 6 508 509 10.1007/s00066-013-0322-5 2-s2.0-84878279101 23604185 10 Schmid M. Pendl G. Samonigg H. Ranner G. Eustacchio S. Reisinger E. C. Gamma knife radiosurgery and albendazole for cerebral alveolar hydatid disease Clinical Infectious Diseases 1998 26 6 1379 1382 10.1086/516351 2-s2.0-0031811352 9636867 11 Gripp S. Ernst R. Pohle S. Is radiation an effective therapy in Echinococcus multilocularis? Strahlentherapie und Onkologie 2014 190 6, article 591 10.1007/s00066-014-0653-x 2-s2.0-84901608979 12 Von Stechow L. Van De Water B. Danen E. H. J. Unraveling DNA damage response-signaling networks through systems approaches Archives of Toxicology 2013 87 9 1635 1648 10.1007/s00204-013-1106-5 2-s2.0-84883559012 23943208 13 Niranjan A. Flickinger J. C. 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==== Front Evid Based Complement Alternat MedEvid Based Complement Alternat MedECAMEvidence-based Complementary and Alternative Medicine : eCAM1741-427X1741-4288Hindawi Publishing Corporation 10.1155/2016/6012761Research ArticleA Novel Method for Evaluating the Cardiotoxicity of Traditional Chinese Medicine Compatibility by Using Support Vector Machine Model Combined with Metabonomics Li Yubo 1 Zhou Haonan 1 Xie Jiabin 1 Ally Mayassa Salum 1 Hou Zhiguo 1 Xu Yanyan 1 http://orcid.org/0000-0002-9702-1128Zhang Yanjun 2 * 1Tianjin State Key Laboratory of Modern Chinese Medicine, School of Traditional Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, 312 Anshan West Road, Tianjin 300193, China2Tianjin State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 312 Anshan West Road, Tianjin 300193, China*Yanjun Zhang: tianjin_tcm001@sina.comAcademic Editor: Jian-Li Gao 2016 23 8 2016 2016 601276120 5 2016 21 6 2016 29 6 2016 Copyright © 2016 Yubo Li et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Traditional biochemical and histopathological tests have been used to evaluate the safety of traditional Chinese medicine (TCM) compatibility for a long time. But these methods lack high sensitivity and specificity. In the previous study, we have found ten biomarkers related to cardiotoxicity and established a support vector machine (SVM) prediction model. Results showed a good sensitivity and specificity. Therefore, in this study, we used SVM model combined with metabonomics UPLC/Q-TOF-MS technology to build a rapid and sensitivity and specificity method to predict the cardiotoxicity of TCM compatibility. This study firstly applied SVM model to the prediction of cardiotoxicity in TCM compatibility containing Aconiti Lateralis Radix Praeparata and further identified whether the cardiotoxicity increased after Aconiti Lateralis Radix Praeparata combined with other TCM. This study provides a new idea for studying the evaluation of the cardiotoxicity caused by compatibility of TCM. Program for Changjiang Scholars and Innovative Research Team in UniversityIRT 14R41National Basic Research Program of China9732011CB5053002011CB505302National Natural Science foundation of China81273998China Postdoctoral Science Foundation funded project133806 ==== Body 1. Introduction In the early research, Li et al. have found 10 highly specific early cardiac toxicity biomarkers and established a support vector machine (SVM) prediction model [1]. And they used the SVM model to predict the cardiotoxicity of drugs and traditional Chinese medicine (TCM); results showed that the SVM prediction model had a better sensitivity and specificity. However, currently there is no effective method for evaluating the cardiotoxicity of TCM compatibility. And it is still not known how the SVM model can be applied to predict cardiotoxicity of TCM compatibility. So we hope to develop a new approach with high specificity and accuracy for prediction of TCM compatibility. For thousands of years, ancient Chinese people gradually formed the medical theory system of traditional Chinese medicine (TCM), in the process of struggling with the diseases [2]. Compatibility of TCM is the main form of clinical treatment; we always used two or more TCM to produce synergies effect or improve therapeutic effect [3]. Aconiti Lateralis Radix Praeparata (fuzi in Chinese) is one of the commonly traditional Chinese medicines used in clinical treatment; modern research has shown that fuzi has lots of efficacy, such as cardiotonic, anti-inflammatory, analgesic, antimyocardial ischemia, and hypoxia effect. The alkaloid components of fuzi may cause toxic reactions, especially the cardiotoxicity, so it has been always used in the combination with other Chinese herbs to reduce its toxicity in clinical treatment [4, 5]. Research has shown that fuzi combined with Zingiberis rhizoma (ganjiang in Chinese) can enhance the effect of the treatment of acute heart failure [6]. Other studies have found that, for fuzi and Rhei Radix Et Rhizoma (dahuang in Chinese), these kinds of combinations can reduce the toxicity of fuzi and produce other synergistic effects at the same time [7]. However, if TCM compatibility is improper, it will produce toxic effects and even cause damage to the human body; we called this phenomenon “incompatibility” [8]. With the development of times and people growing awareness of drug safety, incompatibility of TCM increasingly received widespread attention. In recent years, medical workers conducted series of studies on the toxicity of TCM incompatibility; it aimed to provide the basis for clinical application. Currently, researchers commonly used biochemical and histopathological tests to evaluate the safety of TCM incompatibility in clinical treatment [9]. But due to the complex material composition of TCM, variety of metabolic pathways, and different targets, traditional evaluation methods have some limitations. Many biological indicators are lack of high sensitivity and specificity, small and weak elaboration of toxicity mechanisms, and slowness of research. In addition, traditional methods require significant time, energy, and laboratory animals [10, 11]. Thus, we need a detection method with less damage, strong specificity, and high accuracy to study the incompatibility of TCM. Metabonomics is a new research method with comprehensive analysis. We can explore variation and characteristics of drug metabolism in the body by analyzing metabolites information in various biological samples and further on to evaluate drug efficacy, predict drug toxicity, and diagnose disease [12]. Metabonomics technology also can monitor the changes process of drug metabolism in the body, observe the changes of endogenous metabolites at the same time, and then infer the mechanism of TCM. Moreover, we can look for or clarify the drugs target or receptor of toxic effects through the terminal information of metabolites. However, metabonomics technologies produce large and multidimensional data with diversity formats; this leads to a heavy workload and time-consuming data preprocessing [13]. Support vector machine (SVM) as a method with good generalization ability has obvious advantages in application of metabonomics data processing. Because the final decision function of SVM only determined by few support vectors and few support vectors determines the final result, so it helps us seize the key sample and exclude a large number of redundant sample [14, 15]. This method is simple and convenient and it can make the research results more reliable. Thus, we used SVM to analyze experimental data combined with metabonomics. In this study, based on the preestablished cardiac toxicity SVM model, we apply it to predict cardiotoxicity of TCM compatibility containing fuzi; then we combine biochemical and pathology tests to evaluate the cardiotoxicity and analyze whether the cardiotoxicity increased or not. The novel method is effective in rapidly and precisely predicting the cardiotoxicity of TCM compatibility. In addition, this study also provides a new way for the evaluation of toxicity in TCM compatibility. 2. Materials and Methods 2.1. Extraction of Traditional Chinese Medicine In this study, single herb groups, processed Aconiti Lateralis Radix Praeparata (heishunpian in Chinese, HSP), Trichosanthis Fructus (gualou in Chinese, GL), Fritillariae Thunbergii Bulbus (zhebeimu in Chinese, ZBM), Ampelopsis Radix (bailian in Chinese, BL), and Bletillae Rhizoma (baiji in Chinese, BJ), respectively, take 200 g. Compatibility groups take 200 g heishunpian, respectively, combined with the same amount of gualou, zhebeimu, bailian, and baiji. All of these were extracted twice with 10 and 8 times the amount of pure water under reflux for 60 minutes, respectively. Then the extracting solutions were filtrated, combined, and concentrated to 1 g/mL (amount of crude drug) aqueous extract samples. 2.2. Animal Treatment The experimental animals were supplied by the Academy of Military Medical Sciences Experimental Animal Centre (Beijing). 110 male Wistar rats, with body weight of 200 ± 20 g, were housed in Tianjin Institute of Radiation Laboratory Animal Center of SPF Animal Laboratory for one week. All of the rats were randomly divided into 10 groups; the control group has twenty rats and each of the model groups has ten rats. The growth environment was as follows: 12-hour day and night turnover, ambient temperature of 23 ± 2°C, and humidity of 35 ± 5%. To reduce the pain of animals, all experiments were carried out in accordance with Chinese national laws and local guidelines. The animal study was approved by the Animal Ethics Committee of Tianjin University of Traditional Chinese Medicine under approval number TCM-2012-078F01. 2.3. Sample Collection and Preparation All animals were only given water without food for 12 h before sample collection. After each group was intragastrically given corresponding water extract of single herbal medicine (10 g/kg), water extract of compatible TCM (10 g/kg), and the normal saline (10 mL/kg) for seven days [16, 17], we took 10 mL of abdominal aorta blood and heart tissue in rats. 5 mL of whole blood was centrifuged at 3500 rpm for 8 minutes. The obtained supernatant is plasma, and it was stored in −80°C refrigerator for metabonomics research. Another 5 mL of whole blood was placed in normal tubes and then handled and stored in the same conditions for biochemical parameters test. The heart tissue was immersed in 10% formaldehyde solution for pathological examination by haematoxylin and eosin (H&E) staining. For H&E staining, the heart tissues were trimmed and embedded in paraffin wax. Then, 5 μm thick slices were cut and affixed to glass slides. The slices were deparaffinized with xylene, hydrated, stained with haematoxylin for 10 mins, differentiated with hydrochloric alcohol, stained with eosin, and dehydrated in a graded alcohol series and then cleaned with xylene. Finally, the histopathological changes were observed by a light microscopy at 100x and 200x magnification. 2.4. Chromatographic and Mass Spectrometric Conditions In this study, ACQUITY UPLC HSS C18 column (2.1 × 100 mm, 1.7 μm, Waters) was used for analysis of plasma samples. The volume of plasma injection is 5 μL, the column temperature was 40°C, and the flow rate was 0.3 mL/min. Mobile phase A (0.1% formic acid in water) and mobile phase B (0.1% formic acid in acetonitrile) were used for gradient elution, and the specific conditions were as follows: 0–0.5 min, 99% A; 0.5–2 min, 99% A–50% A; 2–9 min, 50% A–1% A; 9-10 min, 1% A; 10–10.5 min, 1% A–99% A; 10.5–12 min, 99% A. Mass spectrometry analysis was conducted by electrospray ionisation in positive mode. High-purity N2 was used as auxiliary ionization and desolvation gas, and the MS parameters were as follows: drying gas flow rate was set to 10 mL/min, temperature of N2 was set to 325°C, pressure of atomized gas was 350 psi, flow rate of desolvation gas was 600 L/h, capillary voltage was 3.5 kv, and quadrupole scan range was m/z 50–1000. All samples were randomly injected. In addition, we singled out the plasma samples from each group and mixed them together to make quality control (QC) samples. Then we injected blank and QC samples every 10 samples to test system precision, method precision, and sample stability. 2.5. Data Process Independent sample t-test was used to calculate the difference between the control group and the models group. The process of the calculation is as follows. First, we ensured that the two populations obeyed the normal distribution, and the samples were independent mutually. Then the t-test was used to test whether there is a significant difference between the two populations. All the calculation was completed by SPSS software. The retention time and the relative content of the metabolites differed within the spectrum. Twenty of them were randomly selected to evaluate the relative standard deviations (RSD) of precision and reproducibility. The raw data of the control and model groups were collected and exported by MarkerLynx Version 4.1 (Waters Corp., Manchester, USA). Then according to the retention time, m/z values, and corresponding MS2 information [1], we found out ten predetermined cardiac toxicity biomarkers in the exported data. The variation trends of cardiac toxicity biomarkers were investigated. Finally, we used the preestablished SVM model to predict the cardiac toxicity in both single herb groups and compatibility groups. 3. Results and Discussion 3.1. Biochemical Analysis and Histopathological Assessment In this study, creatine kinase (CK) and lactate dehydrogenase (LDH) were selected as biochemical indices to evaluate whether the drug caused damage to the heart [18–22]. Biochemical results are shown in Figure 1. From the result, we can see that CK and LDH were significantly increased in heishunpian group compared with the control group. It means heishunpian shows significant cardiac toxicity. And there was no significant difference of CK and LDH in other single herb groups; it means zhebeimu, gualou, bailian, and baiji did not show the cardiac toxicity. Furthermore, compared with single herb groups, CK and LDH were increased in various degrees in compatibility groups. But they were not higher than heishunpian group when compared with it. Compared with the control group, LDH was significantly increased in heishunpian-baiji group, but CK did not show significant difference. It is not enough to suggest that there was cardiac toxicity after combination. In addition, CK and LDH did not show significant difference in other compatibility groups. This indicated that there was no cardiac toxicity after heishunpian, respectively, combined with zhebeimu, gualou, bailian, and baiji. We used histopathological examination to evaluate the extent of heart damage. The histopathological results were shown in Figure 2. Compared with the NS group, all the single herb groups and compatibility groups exhibited normal basic structure of rat heart tissue and arranged regular cardiac muscle fibers. In heishunpian group, muscle fibers were seen scattered with small lymphocytes, myocardial stripes existing, and part of the heart cytoplasm staining shades. In other single herb groups, the arrangement of cell nuclear was irregular, and endochylema staining was uneven. In the compatibility groups, a small amount of the dilated blood vessels could be seen under myocardial tunica, striated muscle fibers were visible, myocardial cytoplasmic staining was slightly uneven, and cell nuclear showed a mild shift with different sizes. 3.2. Biomarkers for the Early Prediction of Cardiotoxicity The RSD of peak areas and retention times of 20 randomly selected chromatographic peaks were less than 15%, which indicates that the sample detection method meets metabolomics requirements. And the QC results of this study were shown in Table 1. At present, myocardial enzymes were commonly used as indicators of heart disease. But these indicators always show significant changes when heart tissue pathological damage occurred. This method showed a lag nature and lack of sensitivity and specificity [23, 24]. Based on the early study, combined with retention time, m/z values, and corresponding MS2 information, we found out ten early cardiac toxicity biomarkers from metabolomic data; the information of those biomarkers was shown in Table 2. Then compared with NS group, we analyzed the variation trends of ten early cardiac toxicity biomarkers in model groups. Results showed that the content of L-carnitine in heishunpian, zhebeimu, bailian, and compatibility groups was higher than NS group and the content of other biomarkers in those groups was lower than NS group. The variation trends of these biomarkers were consistent with the results of early experiment [1]; detailed information is shown in Table 3. 3.3. Prediction Results of SVM Model Analysis The obtained metabonomics data were analyzed by using the preestablished cardiac toxicity SVM model. First, the data of control group were used as training set, and the data of single herb groups were used as test set; then the SVM model was run to predict if there is cardiac toxicity in single herb groups. Next, we replaced the control group with heishunpian group; that is, the data of heishunpian group were used as training set, and the data of compatibility groups were used as test set. Then we ran SVM model to predict if there is cardiac toxicity in compatibility groups. 3D views and parameters of SVM model were shown in Figures 3 and 4. SVM prediction results were described in Table 4. From the results, it can be seen that all the single herb groups did not show cardiac toxicity except heishunpian group. It indicated that the bodies were exposed to cardiac toxicity in heishunpian group, and this was consistent with biochemical results. In addition, all the compatibility groups showed cardiac toxicity when heishunpian group was used as control group; it means that there is cardiac toxicity, and the cardiac toxicity was increased after heishunpian combined with zhebeimu, gualou, bailian, and baiji. This was consistent with early reports. Huang et al. have reported that when heishunpian combined with gualou, zhebeimu, bailian, and baiji, the content of diester alkaloids was obviously increased [25]. Ma et al. have found that the codecoctions of fuzi combined with gualou increased the cardiotoxicity [26]. Moreover, Bian et al. reported that the the content of toxic components was increased after fuzi combined with zhebeimu [27]. 4. Conclusions In this study, we used UPLC-Q-TOF-MS metabolomics analysis, combined with preestablished SVM model to predict the cardiac toxicity of heishunpian, gualou, zhebeimu, bailian, and baiji and determine whether the cardiac toxicity increased after heishunpian combined with gualou, zhebeimu, bailian, and baiji. According to biochemical and pathological results, we found that heishunpian group showed obvious cardiac toxicity, and compatibility groups did not show significant cardiac toxicity. But SVM model prediction results revealed that the cardiac toxicity were increased in all compatibility groups compared with heishunpian group. It indicates that traditional testing methods have not yet showed cardiac toxicity. This may be due to lack of time, so the cardiac toxicity was not exposed enough. Therefore, compared with traditional detection methods, early cardiac toxicity biomarkers, and the preestablished cardiac toxicity SVM model can rapidly and accurately predict toxicity when heart tissue damage has not yet appeared. The discovery of early cardiac toxicity biomarkers has great significance for early predicting toxicity. Moreover, SVM model based on early cardiac toxicity biomarkers offers a new research direction for the prediction of cardiac toxicity in TCM compatibility. This study makes a theoretical support for cardiac toxicity studies and the application of cardiac toxicity biomarkers. It also provides a more reliable guidance for clinical application in early diagnosis of cardiac toxicity. Acknowledgments This project was supported by the Program for Changjiang Scholars and Innovative Research Team in University (no. IRT 14R41), the National Basic Research Program of China (973 Program) (2011CB505300 and 2011CB505302), the National Natural Science foundation of China (no. 81273998), and China Postdoctoral Science Foundation funded project (no. 133806). Competing Interests The authors declare that they have no competing interests. Figure 1 Content changes of biochemical indices (CK, LDH) in rats, respectively, comparing model groups with NS group (∗ p < 0.05, ∗∗ p < 0.01). Figure 2 Histopathological results of the heart by H&E staining. Control group: no necrotic lesions; HSP: heishunpian group, infiltration of lymphocytes; GL: gualou group, irregular arrangement of cell nuclear; BM: beimu group, inhomogeneous staining of cytoplasm; BL: bailian group, cytoplasm discoloration and uneven staining; BJ: baiji group, overflow of red blood cells in muscle fibers; HSP + GL: heishunpian-gualou group, uneven staining of cytoplasm; HSP + BM: heishunpian-beimu group, mild hyperchromatic of cell nuclear; HSP + BL: heishunpian-bailian group, loss of muscle fibers and irregular arrangement of cell nuclear; HSP + BJ: heishunpian-baiji group, atrophy of striated muscle. Figure 3 Three-dimensional view of the SVM model of ten biomarkers: comparing single herb groups with NS group (the parameters are described in the following: Best c = 0.25, Best g = 1.3195, and CV accuracy = 100%). Figure 4 Three-dimensional view of the SVM model of ten biomarkers: comparing compatibility groups with HSP group (the parameters are described in the following: Best c = 0.25, Best g = 0.75786, and CV accuracy = 100%). Table 1 The results of experimental methodology. Experiment name RSD (retention time) RSD (peak area) Precision instrument <0.48% <11.0% Method repeatability <0.36% <4.0% Sample stability <1.2% <9.6% Table 2 Ion information of early cardiotoxicity biomarkers [1]. T R (min) Obsd m/z Calcd m/z Error (ppm) Metabolite Formula MS/MS 0.76 162.1123 162.1130 4.32 L-carnitine C7H15NO3 162.1, 103.0 4.19 190.0863           4.19 172.0755           4.19 130.065           4.67 347.2214 347.2222 2.30 19-Hydroxydeoxycorticosterone C21H30O4 385.3, 369.2, 347.2, 329.2, 109.1, 97.1 5.45 432.3107           5.87 299.2002           7.30 468.3467           7.85 548.3715 548.3716 0.18 LPC (20:2) C28H54NO7P 570.3, 548.3, 184.1, 104.1 6.48 490.2913 490.2910 −0.61 LPC (14:0) C22H46NO7PNa 490.2, 468.3, 184.1, 104.1 Table 3 Content change trend of early cardiac toxicity biomarkers. T R (min) m/z Metabolite Content change Identified HSP GL ZBM BL BJ HSP + GL HSP + ZBM HSP + BL HSP + BJ 0.76 162.1123 L-carnitine ↑ ↑ ↓ ↑ ↑ ↓ ↑ ↑ ↑ ↑ 4.19 190.0863   ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 4.19 172.0755   ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 4.19 130.065   ↓ ↓ ↑ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 4.67 347.2214 19-Hydroxydeoxycorticosterone ↓ ↓ ↑ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 5.45 432.3107   ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 5.87 299.2002   ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 7.30 468.3467   ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 7.85 548.3715 LPC (20:2) ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 6.48 490.2913 LPC (14:0) ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ Table 4 SVM cardiac toxicity prediction results. Single herb group Prediction result Compatibility group Prediction result HSP 1 — — GL 0 HSP + GL 1 ZBM 0 HSP + ZBM 1 BL 0 HSP + BL 1 BJ 0 HSP + BJ 1 “0” indicated that the TCM did not induce the cardiac toxicity; “1” indicated that the TCM induced cardiac toxicity. ==== Refs 1 Li Y. B. Ju L. Hou Z. G. 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Compatibility art of traditional Chinese medicine: from the perspective of herb pairs Journal of Ethnopharmacology 2012 143 2 412 423 10.1016/j.jep.2012.07.033 2-s2.0-84866005625 22871585 9 Tan Y. Ko J. Liu X. R. Serum metabolomics reveals betaine and phosphatidylcholine as potential biomarkers for the toxic responses of processed Aconitum carmichaelii Debx Molecular BioSystems 2014 10 9 2305 2316 10.1039/c4mb00072b 2-s2.0-84905274906 24949573 10 Sun D.-Z. Li S.-D. Liu Y. Zhang Y. Mei R. Yang M.-H. Differences in the origin of philosophy between Chinese medicine and western medicine: exploration of the holistic advantages of Chinese medicine Chinese Journal of Integrative Medicine 2013 19 9 706 711 10.1007/s11655-013-1435-5 2-s2.0-84883302822 23975136 11 Liang X. J. Li H. Y. Li S. 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==== Front Rehabil Res PractRehabil Res PractRERPRehabilitation Research and Practice2090-28672090-2875Hindawi Publishing Corporation 10.1155/2016/7621690Research ArticleAddressing Work-Related Issues in Medical Rehabilitation: Revision of an Online Information Tool for Healthcare Professionals http://orcid.org/0000-0003-2933-076XLukasczik Matthias 1 * Wolf Hans-Dieter 1 Gerlich Christian 1 http://orcid.org/0000-0002-9538-1787Küffner Roland 1 Vogel Heiner 1 Neuderth Silke 2 1Department of Medical Psychology, Medical Sociology and Rehabilitation Sciences, University of Würzburg, 97070 Würzburg, Germany2Faculty of Applied Social Sciences, Würzburg University of Applied Sciences, 97070 Würzburg, Germany*Matthias Lukasczik: matthias.lukasczik@uni-wuerzburg.deAcademic Editor: Jae-Young Lim 2016 16 8 2016 2016 76216901 4 2016 24 6 2016 4 7 2016 Copyright © 2016 Matthias Lukasczik et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Medical rehabilitation increasingly considers occupational issues as determinants of health and work ability. Information on work-related rehabilitation concepts should therefore be made available to healthcare professionals. Objective. To revise a website providing healthcare professionals in medical rehabilitation facilities with information on work-related concepts in terms of updating existing information and including new topics, based on recommendations from implementation research. Method. The modification process included a questionnaire survey of medical rehabilitation centers (n = 28); two workshops with experts from rehabilitation centers, health payers, and research institutions (n = 14); the selection of new topics and revision of existing text modules based on expert consensus; and an update of good practice descriptions of work-related measures. Results. Health payers' requirements, workplace descriptions, and practical implementation aids were added as new topics. The database of good practice examples was extended to 63 descriptions. Information on introductory concepts was rewritten and supplemented by current data. Diagnostic tools were updated by including additional assessments. Conclusions. Recommendations from implementation research such as assessing user needs and including expert knowledge may serve as a useful starting point for the dissemination of information on work-related medical rehabilitation into practice. Web-based information tools such as the website presented here can be quickly adapted to current evidence and changes in medicolegal regulations. German Federal Pension Insurance0421/40-64-50-38Open Access Publication Fund of the University of Würzburg ==== Body 1. Introduction Adverse working conditions and occupational stressors may impair work ability and complicate return to work after sickness or injury [1–6]. They may be associated with mental and somatic health problems, for instance, regarding stress-related somatic symptoms [7], depression [8], cardiovascular disease [9], or musculoskeletal disorders [10]. Addressing occupational issues in healthcare is therefore of great importance. Rehabilitation is a particularly suited and relevant setting: in many countries, its focus is on improving health status, treating chronic conditions, and/or altering their detrimental effects on activities and participation, in terms of the International Classification of Functioning, Disability, and Health (ICF) [11], which includes participation in working life. Internationally, a growing number of vocational and/or medical rehabilitation concepts put a special emphasis on the interrelations of work-related variables, health, and work ability with return to work as a central rehabilitative outcome. These concepts vary in scope, target group(s), setting, or treatment elements (e.g., inpatient versus outpatient programs; workplace-related versus clinical interventions; coordination with actors involved such as healthcare providers and employers) [12–16]. For example, work-related programs have been introduced in inpatient medical rehabilitation centers in Germany that target patients with severe restrictions of work ability [17]. In view of current requirements specified by public healthcare payers (in Germany, e.g., by the statutory pension insurance as the main funding agency of work-related medical rehabilitation [18]), information on work-related rehabilitation concepts (including the available evidence) should be easily accessible to institutions and healthcare professionals working in this field, especially to those not (or less) familiar with this approach. The information provided should include resources and recommendations on how to implement vocationally oriented elements in medical rehabilitation. Generally, information websites can be regarded as a widespread and useful educational strategy of dissemination [19]. Although less common than internet information tools that address patients [20], a web-based approach directed at healthcare professionals seems suitable to realize these elements. It is a low-threshold tool that is easy to adapt and can be accessed by a large number of users. A German study with general practitioners showed that physicians rate this format favorably [21]. However, online tools that support this implementation are largely lacking in rehabilitation, especially with respect to work-related programs. Currently, very few web-based information devices exist that offer information on rehabilitation topics (general information on rehabilitation [22]; preparation for rehabilitation; and follow-up/aftercare directed at patients [23, 24]). Against this background, a website informing healthcare professionals in rehabilitation centers on work-related rehabilitation in the specific context of the German medical rehabilitation system had been developed between 2009 and 2010 [17, 25], with subsequent minor revisions following in 2011 and 2012. In this initial phase, standardized descriptions of major work-related treatment components had been developed in a consensus process using Delphi techniques with 50 experts from different professions working in work-related medical rehabilitation (medicine, psychology, social work, occupational therapy, physiotherapy, administration, and sports science). Descriptions of work-related rehabilitation programs and concepts already implemented in rehabilitation centers had been obtained to establish a database of good practice examples. These included the following descriptive features: indication(s); main content and treatment elements; target group(s) (including inclusion/exclusion criteria); therapeutic goals; therapeutic staff/professions involved; required equipment. General information on work-related medical rehabilitation and its translation into practice had also been made available to users. This paper describes a major revision and update of the website (which can be accessed at http://www.medizinisch-berufliche-orientierung.de/; content currently available in German only) carried out between October 2013 and December 2014. Its purpose was (a) to enhance the practical value of the website to healthcare professionals by adding new topics and resources based on user needs and expert input, including practical implementation aids and resources and additional good practice examples and (b) to update the information provided on the website, referring to the current state of knowledge relevant to the setting. In this context, we referred to recommendations from implementation research: consideration of user needs; incorporation of expert knowledge; inclusion of good practice examples and practical implementation resources and recommendations; user-friendly presentation of the current state of knowledge [26]. The interprofessional character of work-related rehabilitation was also addressed [27]. 2. Methods To realize these objectives, the following steps were carried out. To update the current state of knowledge presented on the website, a systematic literature search was conducted, comprising the period from 2011 to 2014. It focused on German publications referring to the specific healthcare setting and target group of the website. The websites and publications of relevant institutions in the German healthcare system (statutory pension insurance scheme, statutory accident insurance scheme, and vocational rehabilitation providers) as well as German scientific journals that regularly publish papers on medical rehabilitation were searched. Additionally, English-language studies by German researchers published in international journals and overviews of topics relevant to the context of work-related medical rehabilitation were reviewed, using the following databases: MEDLINE; PUBMED; Cochrane Database of Systematic Reviews; PSYCINFO. As search terms, the following headings (representing the main topics from the previous version of the website) were used: work-related medical rehabilitation (basics/development); screening for vocational problems; functional capacity evaluation instruments; self-rating instruments; motivation to deal with vocational issues; core interventions in work-related medical rehabilitation (work hardening; occupational training/therapy; patient education groups with vocational focus; social work counseling; cooperation with external institutions). All rehabilitation centers already providing good practice examples on the website were contacted (n = 28 inpatient medical rehabilitation centers of various indications located throughout Germany). They were asked to indicate via a short questionnaire (6 items) whether they preferred (a) refined search criteria in the database including all good practice examples; (b) changes of the website structure or certain sections; (c) the addition of any new topics; (d) a regular newsletter; (e) a version for mobile devices; and (f) other issues of importance that could be specified in a free-text field as needed. The questionnaire had been developed specifically for this project. It was designed to assess to what extent several potential usage options and changes on the website would be of interest to (current and/or potential) users (see above). Its content and items were discussed and consented by the research team. Questionnaire data were analyzed using descriptive statistics. Clinics were also asked to provide an updated description of their work-related measures in case there were any changes in their programs. In addition, an online form corresponding to the questionnaire was implemented on the website to give users the opportunity to propose modifications. The results of the questionnaire survey were discussed at two expert workshops held in February and March 2014 with n = 14 representatives from rehabilitation centers, health payers, and research institutions. The following institutions/actors were included (number of participants in parentheses): German statutory pension insurance (1); German statutory accident insurance (1); vocational rehabilitation centers (1); medical rehabilitation centers (indications: orthopedics; psychosomatics; neurology; cardiology; metabolic diseases (9)); universities (rehabilitation research; sports sciences (2)). The following professions were represented: medicine; psychology; sports science; social work; occupational therapy; physical therapy; rehabilitation education/sciences. The experts compiled proposals to revise the structure and contents of the website. Moreover, they participated in the revision of text modules on the website. The expert workshops followed focus group techniques with several predefined key topics guiding the workshops (revision/modification needs; workplace descriptions; website structure/outline). Based on the literature search, the results from the questionnaire survey of rehabilitation centers and the expert workshops, several new topics to be included in the modified website were identified (see Section 3). As a basis for the preparation of corresponding new text modules, a complementary national literature search was conducted. Publications referring to these topics within the context of the German healthcare setting were reviewed that were published between 2011 and 2014. To ensure comprehensibility, accuracy, and topicality of the information presented, all existing text modules were also reviewed. During this process, several parts of the website were extensively restructured, rewritten, and updated (based on the literature search described above). In order to extend the existing database of good practice examples (which included n = 52 descriptions on the “old” website; see above), n = 12 medical rehabilitation facilities from different indications were contacted and asked to make their work-related treatment concepts available as additional good practice examples, using a form to describe the respective measure. 3. Results In the questionnaire survey, 19 of 28 rehabilitation centers (67.9%) indicated they preferred one or several changes on the website (Table 1). Results were discussed during the expert workshops. Here, it was eventually decided not to launch a newsletter (as suggested by the majority of institutions) in favor of a regularly updated overview of training and further education activities in areas/specialties relevant to work-related medical rehabilitation. Also, the suggestion of a version for mobile devices was not pursued due to limited technological resources. The following additions to the website in terms of new topics were consented in the expert workshops: information on requirements of health payers and social security schemes regarding work-related medical rehabilitation; information on workplace/job descriptions; glossary; practical implementation aids; and resources (including material available for download provided by rehabilitation facilities, e.g., team briefing checklists). The latter comprise information on how to prepare patients for rehabilitation (e.g., importance of patient motivation, screening for vocational problems), the actual implementation of work-related rehabilitation programs (e.g., qualification of therapeutic staff), and potential risks and pitfalls. Since the information provided on the website addresses clinicians and therapists, a separate brief section was added that informs patients on the objectives of the website. In this section, a link to another website that specifically targets rehabilitation patients was supplemented. This website (which had been developed in an unrelated research project [24]) informs patients (i.e., laypersons) on all aspects of medical rehabilitation (including work-related programs) in plain words. The section on diagnostic tools used in work-related medical rehabilitation assessment was updated and extended. It comprises short descriptions of 28 standardized instruments available in German with links providing further information and resources and download options for those instruments that are license-free (Table 2). Other (minor) modifications and restructuring made during the revision are listed in Table 3, which summarizes the structure and sections of the modified website. Feedback regarding the modification of existing good practice examples was obtained for 50 descriptions. Clinics indicated modification needs in 29 of these examples, which were revised accordingly. The database including good practice examples was extended to 63 examples from seven indications (plus generic examples) including 11 new descriptions obtained from rehabilitation facilities throughout the revision process (Figure 1). As mentioned above, all examples comprise detailed descriptions of the respective measure (e.g., target group; therapeutic goals; therapeutic professions involved). The revised website was launched in January 2015. 4. Discussion In this paper, we described the process of revising a website serving as an information tool for healthcare professionals in work-related medical rehabilitation (in Germany). The steps in this process followed recommendations for disseminating knowledge into practice, such as user involvement and the incorporation of expert knowledge [26]. These elements were realized by means of a survey of rehabilitation centers and the inclusion of an expert panel involved in the modification of contents. In doing so, we were able to specify topics regarded as essential by rehabilitation experts for the updated website. Available evidence to be implemented into healthcare practice may cover varying types and levels of information, which may range from high-level research evidence to (good) clinical practice [38]. For the specific field of work-related medical rehabilitation in Germany, there is a lack of efficacy or effectiveness trials that can be regarded as steps or phases in the translation of research into practice [39]. Therefore, the aim of this project was to design a practical guide for clinicians and therapists in rehabilitation facilities and to provide them with information and “proven practice” specific to the German healthcare system, rather than presenting a systematic review of (international) evidence regarding vocationally oriented rehabilitation programs. Web-based tools such as the website presented here offer several advantages. Their content and structure can be quickly revised and extended and is thus less prone to become obsolete. The specific information provided can be adapted to the respective healthcare setting and legal context. Moreover, users can easily access them. They also correspond to user expectations and preferences since clinicians themselves favor web-based information on rehabilitation-related contents [21]. As noted above, however, these tools are still uncommon in rehabilitation, especially with respect to work-related programs and are rarely accompanied by evaluation research. Several limitations should be pointed out. First, there has been no user evaluation of the website so far. The revision process did not include a systematic quantitative assessment of the website by rehabilitation facilities or healthcare professionals. It is, however, important to examine whether the website actually reaches its target group as intended and to what extent users rate it as useful and informative. Therefore, future research should document the website's actual benefit to the targeted user groups and its suitability to transfer relevant information into rehabilitation practice. This should also include a larger number (and wider range) of rehabilitation facilities to allow a more detailed assessment, given that the revision of the website included only institutions already involved by providing good practice examples or practical implementation aids. Second, as mentioned above, the website cannot (and does not claim to) provide a systematic and critical review of the international evidence, given its more “informational” focus including the requirements of national health payers and social security schemes. This fact in conjunction with the lack of higher-level evidence in the field of work-related medical rehabilitation (at least in Germany) limits the informative value of the website. With regard to the clinics providing good practice examples and implementation resources, the centers took part on a voluntary basis. It cannot be ruled out that there is a “positive selection” of facilities with extensive expertise and a wide range of work-related rehabilitation programs (as compared to centers providing only basic programs or not yet offering work-related programs). Given the aim of the website to provide healthcare professionals with practical and field-tested information on how to establish and run work-related programs, we would not regard this as a major drawback. Several clinics that took part in the survey on modification needs did not specify any needs. This leaves open the question whether these facilities were content with the status quo of the website or if they would prefer modifications other than those given in the questionnaire. As the free-text field was not used by these clinics to propose other suggestions, we can assume that they actually did not recognize a need for modification. Finally, the long-term practical relevance of web-based information media depends on whether strategies to create a sustainable platform for this tool can be established (e.g., regarding personnel, financial resources). Implementation research has made rather few statements regarding this aspect [26, 40]. The website presented here was developed and revised in the context of several related research projects. This raises the question to what extent the resources necessary for the continuation of the platform can be ensured. This issue might be less problematic in other contexts, if, for instance, the tool is developed and maintained by a private company, social security agency, or health payer organization. Research on the dissemination of evidence to professionals in medical rehabilitative practice is still relatively scarce. The development of information tools such as the website presented here may serve as a useful step to further establish work-related concepts in medical rehabilitation. This, however, must be accompanied and sustained by research that evaluates the respective programs and their effectiveness as well as the usefulness of associated information tools. Acknowledgments This project was funded by the German Federal Pension Insurance (DRV Bund), Reference no. 0421/40-64-50-38 (date: 28.10.2013). This publication was supported by the Open Access Publication Fund of the University of Würzburg. Part of this research was presented at the 13th Congress of European Forum for Research in Rehabilitation (EFRR), Helsinki (Finland), May 6–9, 2015. The authors would like to thank all participating rehabilitation facilities and experts for their invaluable support. Moreover, the authors would like to thank Patrizia Driesel for her dedication and support in the revision of the website. Competing Interests The authors report no competing interests. Figure 1 Indications represented in the database of good practice examples. Note: given is the number of examples per indication. The number of examples does not equal n = 63 as some examples relate to more than one indication. Table 1 Feedback from rehabilitation centers regarding potential website modifications. Newsletter 12 Refined search functions 7 Modified structure 5 New topics 5 Version for mobile devices 4 Other 0 Note: multiple answers possible. Table 2 Assessments/diagnostic tools illustrated on the website with examples. Type of assessment Number of assessments described on the website Examples Screenings to identify patients with severe work-related problems/limitations 3 Screening-Instrument to identify the need for work-related medical rehabilitation (SIMBO) [28]; Würzburger Screening [29] Functional capacity evaluation instruments (including profile comparison procedures that evaluate and compare work-related demands and functional capacities) 5 Isernhagen Work Systems FCE [30, 31] Self-rating instruments (including the assessment of limitations of activities and participation and person-related context factors in terms of the ICF) 19 Disabilities of the Arm, Shoulder, and Hand Questionnaire (DASH) [32, 33]; Work Ability Index (WAI) [34, 35]; Effort-Reward Imbalance Questionnaire (ERI) [36, 37] Note: screenings given as examples are currently available in German only. Table 3 Overview of website structure and content.     Content revised and extended New content/topic Background Introduction to work-related medical rehabilitation ✓   Health payers' requirements/conceptual frameworks   ✓ Cooperation with external institutions (e.g., company physicians; vocational training institutes; career development centers) ✓   Promoting motivation in work-related medical rehabilitation ✓   Components Diagnostic tools/assessments ✓   Information on workplace/job descriptions   ✓ Work-related treatment components (as specified by the German pension insurance's profile of requirements [18]; e.g., work hardening; patient education groups with vocational focus) ✓   Implementation Good practice examples (database) ✓   Practical implementation aids and recommendations   ✓ Service Terms and definitions (glossary) ✓   Links and literature (cited literature, recommendations) ✓   Information in English   ✓ Information for patients   ✓ Feedback section (i) Submit a good practice example (ii) Submit information on workplace descriptions (iii) Recommend training/further education (iv) General feedback ✓   Further education and training (calendar of events) ✓   ==== Refs 1 Yong M. 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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/9343417Review ArticleRoles of Peroxisomes in the Rice Blast Fungus http://orcid.org/0000-0002-5492-516XChen Xiao-Lin * http://orcid.org/0000-0003-2677-3207Wang Zhao Liu Caiyun State Key Laboratory of Agricultural Microbiology, The Provincial Key Lab of Plant Pathology of Hubei Province, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China*Xiao-Lin Chen: chenxiaolin@mail.hzau.edu.cnAcademic Editor: Frederick D. Quinn 2016 16 8 2016 2016 93434173 6 2016 25 7 2016 Copyright © 2016 Xiao-Lin Chen et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The rice blast fungus, Magnaporthe oryzae, is a model plant pathogenic fungus and is a severe threat to global rice production. Over the past two decades, it has been found that the peroxisomes play indispensable roles during M. oryzae infection. Given the importance of the peroxisomes for virulence, we review recent advances of the peroxisomes roles during M. oryzae infection processes. We firstly introduce the molecular mechanisms and life cycles of the peroxisomes. And then, metabolic functions related to the peroxisomes are also discussed. Finally, we provide an overview of the relationship between peroxisomes and pathogenicity. National Natural Science Foundation of China31571952Fundamental Research Funds for the Central Universities09002063062662015PY085 ==== Body 1. Introduction Peroxisomes are single membrane-bound microbodies which existed in all eukaryotic cells. In different organisms and environmental conditions, their abundance can be changed rapidly, and functions could be different. The abundance of peroxisomes is coordinated by several cellular processes, including peroxisome biogenesis, peroxisome proliferation, and peroxisome degradation [1]. In budding yeast, the genes involved in those cellular processes include a set of PEX genes, which encode peroxins [2]. Up to now, over 30 PEX genes have been found in different organisms [2]. There are several important metabolic processes that take place in peroxisomes, which involve fatty acids β-oxidation, glyoxylate cycle, hydrogen peroxide detoxification and secondary metabolite biosynthesis, and so forth [1]. The roles of peroxisomes have been extensively uncovered in yeast, filamentous fungi, plant, and human [3]. Some peroxisome functions are species specific, such as the methanol assimilation in yeast [4], the glyoxylate cycle in plant seeds [5], and the plasmalogens biosynthesis in mammal [6]. In filamentous fungi, they can develop a special compartment, the peroxisome-derived woronin body, to seal the septal pore when suffered cellular wounding [7]. The molecular mechanisms of peroxisome life cycle have been extensively studied in yeast [2]. Peroxisome studies in the filamentous fungi are also increased rapidly, especially in the model filamentous fungi Aspergillus nidulans [8, 9] and Neurospora crassa [10–12], the plant pathogens Colletotrichum orbiculare [13–15] and Magnaporthe oryzae [16–20], and the human pathogens Candida albicans [21, 22], Aspergillus fumigatus [23, 24], and Cryptococcus neoformans [25, 26]. An important aspect is that the peroxisomes are found to play key roles in fungal pathogenicity towards their host, including plants and human. In all these pathogenic fungi, the roles of peroxisomes in M. oryzae have received extensive concern. Over the past two decades, many components involving roles of peroxisomes have been identified in M. oryzae (Table 1). This review focuses on recent advances in our understanding of peroxisomes in M. oryzae, including a description of the peroxisome life cycle during fungal infection, and an overview of their remarkable functions relevant to pathogenesis. 2. Life Cycle of the Peroxisomes The peroxisome life cycle mainly includes peroxisome biogenesis, peroxisome proliferation, and peroxisome degradation [27]. The peroxisomes are thought to be born originally from the endoplasmic reticulum (ER) [27]. Basically, the biogenesis process contains peroxisomal membrane proteins (PMPs) acquisition and peroxisomal matrix proteins import. Peroxisome proliferation can be achieved by either de novo formation from ER or/and peroxisome fission. When the peroxisomes have finished their mission, they can be degraded by pexophagy, an autophagic process [27]. In M. oryzae, there are several PEX genes involving peroxisome life cycle that have been characterized, including MoPEX5, MoPEX6, MoPEX7, MoPEX14, MoPEX19, and MoPEX11 family genes. MoPEX5 and MoPEX7 are involved in matrix proteins import [17, 18], MoPEX6 participates in receptors import for recycling [28], MoPex14 functions as a matrix docking protein [19], MoPEX19 functions as chaperone and receptor for importing of both matrix proteins and PMPs [16], and MoPEX11 family genes are involved in peroxisomal fission processes [20]. 2.1. Peroxisome Biogenesis In yeast, during peroxisome biogenesis, peroxisome membrane proteins (PMPs) should firstly be inserted into membranes, which are mediated by PEX3, PEX16, and PEX19 [29–31]. Then the peroxisomal matrix proteins, which are synthesized in the cytoplasm, are translocated into the peroxisomes by peroxisome membrane docking complex [32]. Most of the peroxisomal matrix proteins contain either PTS1 (type I peroxisomal targeting signal) at the C-terminus or PTS2 (type II peroxisomal targeting signal) at the N-terminal and can be recognized by shuttle receptors Pex5 or Pex7-mediated complex, respectively. The cargos on the PTS1 and PTS2 receptors are accepted by the Pex13/Pex14/Pex17 docking complex, and then the receptors are recycled by the ubiquitin system. The ubiquitinated receptors can be extracted into cytoplasm by AAA+ ATPases Pex1 and Pex6 [27]. In M. oryzae, MoPex19 is the ortholog of yeast PMPs receptor Pex19. Pex19 protein is located in the cytoplasm and newly formed peroxisomes, which is consistent with its PMPs receptor function that shuttles the PMPs between the cytosol and peroxisomal membrane [30]. Deletion of MoPEX19 will lead to PMPs mislocalization. PMP47 is a representative PMP which is normally distributed in the peroxisomes in the wild type strain, while in the MoPEX19 deletion mutants, its localization pattern is changed, which is distributed in the cytoplasm [16]. This demonstrated that the PMP47 cannot be imported into the peroxisomes. Moreover, in the Δmopex19 mutants, peroxisomal structures and peroxisome-derived woronin bodies are both absent [16], indicating that the MoPex19 is essential for biogenesis of peroxisomes and woronin bodies. M. oryzae MoPex5 and MoPex7 are also proved to function as receptors of peroxisomal matrix proteins, which are involved in importing of the matrix proteins into peroxisomes [17, 18]. Disruption of MoPEX5 and MoPEX7 will block the PTS1 and PTS2 peroxisomal import pathways, respectively. In the wild type strain, RFP-PTS1 and GFP-PTS2 are normally distributed in the punctuate peroxisomes, while in the Δmopex5 mutants, RFP-PTS1 is dispersed in cytoplasm but GFP-PTS2 is still located in peroxisomes. In contrast, in the Δmopex7 mutants, RFP-PTS1 is still located in peroxisomes but GFP-PTS2 is dispersed in cytoplasm. These results demonstrated the MoPex5-mediated PTS1 peroxisomal import pathway and MoPex7-mediated PTS2 peroxisomal import pathway separately function in the rice blast fungus [17, 18]. The thiolase MoThl1 is a candidate PTS2 protein; it is failed to be located at the peroxisomes in the Δmopex7 mutants [17], which further supports the role of MoPex7 in the PTS2 peroxisomal protein import pathway. The function of Pex6 ortholog in M. oryzae, MoPex6, was also evaluated [28]. In MoPEX6 disruption mutants, the GFP-SRL protein is diffused in the cytoplasm, failed to be localized in the punctuate peroxisomes in mycelia, conidia, germ tubes, and appressoria [28], indicating the PTS peroxisomal import pathway is blocked. This result is consistent with the cellular function of Pex6, which is involved in recycling of matrix protein receptors (Pex5 and Pex7) during peroxisome biogenesis. In the MoPEX14 disruption mutants, the GFP-SRL protein is also mislocalized to the cytoplasm, while when the PEX14 61-361 or PEX14 1-258 is expressed in the Δmopex14 mutants, the punctate localization of GFP-SRL can be restored [19]. These data confirmed the functions of MoPex14, which act as a matrix docking protein to facilitate peroxisomal protein import and peroxisome biogenesis. 2.2. Peroxisome Proliferation Peroxisomes can proliferate rapidly according to suitable environment stimulation. The proliferation processes can be achieved by de novo biogenesis from the ER, or by fission from the preexisting peroxisomes. In yeast, the peroxisome fission processes mainly consist of several steps. At the beginning, the mature peroxisomes are elongated by the functions of the peroxisomal membrane protein Pex11. Then the matrix proteins can be imported into the elongated peroxisomes, and the fission machinery can also be imported into appropriate place for fission. The dynamin-like protein Dnm1 is located at the constriction sites and leads to membrane fission processes by GTP hydrolysis. At last, the daughter peroxisomes can be produced from the fission processes, which is achieved by cooperation of several proteins, including Fis1, Dnm1, and the adaptors Mdv1 or Caf4 [27]. The peroxisome fission process in M. oryzae is identified recently, by several independent studies. There are three members of PEX11 family genes in M. oryzae genome, named MoPEX11A, MoPEX11B, and MoPEX11C, respectively [20]. However, it seems that only MoPEX11A plays vital role in peroxisome fission. The MoPEX11A deletion mutant exhibits decreased but enlarged peroxisomes compared to the wild type, which demonstrated the MoPEX11A is important for peroxisome elongation and proliferation. In contrast, the MoPEX11B and MoPEX11C deletion mutants are normal in both number and size of the peroxisomes [20], indicating they could not be key regulators during peroxisomal proliferation. There is only one counterpart of Mdv1/Caf4 protein in M. oryzae, named PEF1 [peroxisome fission protein 1] [33]. This gene may play dual roles of Mdv1 and Caf4, because deletion of PEF1 will lead to evident peroxisomal fission defect during the fission inducing conditions. The Δpef1 mutant forms string-linked peroxisomes, in contrast to the punctuate structures in normal cells [33]. Similar situation can be found in the Δmdv1Δcaf4 double mutant or the Δfis1 and Δdnm1 mutants in yeast [34]. The phenotypic defect indicates that the daughter peroxisomes cannot be cut from the elongated peroxisomes in Δpef1. Pef1 can bind to Fis1 with its N-terminal extension (NTE) region and to Dnm1 with its C-terminal WD40 repeat region. With the help of adaptors Mdv1 or Caf4, the outer membrane protein Fis1 can recruit Dnm1 to peroxisomes for fission [35]. Pef1 can be well colocalized with MoFis1, which is recently reported to play important roles in mitochondria fission in M. oryzae [36]. This is intelligible, because in S. cerevisiae, the peroxisome fission machinery can be also used to facilitate mitochondria fission process. 2.3. Peroxisome Degradation Peroxisome abundance can be rapidly cleared by a selective autophagic process, which is known as the pexophagy. In yeast, there are two different peroxisome degradation modes, macropexophagy and micropexophagy [37]. The macropexophagy sequesters peroxisomes to form a pexophagosome, which leads the peroxisomes to vacuole for degradation. The micropexophagy encloses peroxisomes by vacuolar membrane protrusions and the micropexophagy specific membrane apparatus (MIPA) to vacuole for degradation [37]. There are several ATG and PEX genes reported to be involved in perophagy [37]. In Pichia pastoris, ATG30 is required for both of macropexophagy and micropexophagy [38], but no ATG30 homolog gene can be found in M. oryzae. In P. pastoris and C. orbiculare, ATG26 plays key roles in pexophagy, and the CoATG26 is essential for infection process [13, 39]. However, In M. oryzae, MoATG26 is not involved in pexophagy and is dispensable for virulence [19]. In S. cerevisiae, the pexophagy process can be mediated by Atg20/Snx42 [40]. By the assistance of sorting nexins Snx41 and Atg24/Snx4, Atg20/Snx42 can be also involved in endosomal retrieval trafficking [40]. However, only one protein [MoSnx41] with high similarity to Snx41 and Snx42/Atg20 can be found in M. oryzae. Studies have found that the MoSNX41 plays key roles in conidiation and pathogenesis. Deletion of MoSNX41 leads to pexophagy deficiency, demonstrating this gene is involved in pexophagy in M. oryzae. The yeast ScSnx42 can restore the pexophagy deficiency of the Δmosnx41 mutant but failed to recover the defects of conidiation and pathogenesis, indicating the pexophagy process is dispensable for development and pathogenicity in M. oryzae. The function of MoSnx41 in conidiation and pathogenesis is mediated by Snx41-dependent retrieval trafficking, but not pexophagy [19]. As a peroxisomal membrane protein, PEX14 is also involved in pexophagy of Hansenula polymorpha [41]. In M. oryzae, the MoPex14 has also been proved to be essential for pexophagy, but dispensable for pathogenicity. 2.4. Peroxisome Differentiation Filamentous fungi can form a special structure, called woronin body (WB), which is differentiated from the peroxisomes [42]. It is accepted that the peroxisome-related woronin bodies are used to seal the septal pore when suffering cellular wounding [43]. The formation mechanism of woronin bodies has been well studied in Neurospora crassa [44]. Hexagonal peroxisome Hex1 is the major structural protein in woronin body, which can be imported into the peroxisome matrix and assembled to form a woronin body core structure. This core structure can recruit WB sorting complex protein [WSC] into the peroxisome membrane. Then the nascent WB can be budded from the mother peroxisomes. In M. oryzae, the HEX1 homolog gene has been cloned and the roles of the woronin bodies have also been uncovered by analyses of the MoHEX1 functions. The woronin body is proved to be required for development, appressoria formation, and infection hyphae growth and therefore is essential for pathogenicity in M. oryzae [45]. Ultrastructural analyses proved that the woronin bodies are located adjacent to septa of mycelia, germ tubes, and infection hyphae, but they are less observed in conidia. The HEX1 deletion mutant is lack of woronin bodies, and when the cells are damaged, the cellular materials will bleed out through the septal pores. The M. oryzae Hex1 protein contains the PTS1 peroxisome targeting signal, which can help it locate into the peroxisomes. For the woronin bodies being formed from the peroxisomes, defects in peroxisome formation cycles could lead to defect in woronin body formation. Consistent to this hypothesis, nearly all disruption of the genes involving in peroxisome life cycle can result in woronin body deficiency [45]. 2.5. Regulation of Peroxisome Dynamics The peroxisomes in the cell are dynamics according to environmental conditions and development stages. Occupancy of the peroxisomes in a cell is determined by several processes, including peroxisome biogenesis, peroxisome proliferation [de novo formation and fission], and peroxisome degradation (pexophagy). De novo biogenesis and fission process are both used to increase peroxisomes numbers. However, how to coordinate de novo formation and peroxisomal fission remains unclear. It is possible that both of the ER formation and fission of the preexisting peroxisomes might exist in normal conditions. It is supposed that, upon the peroxisome fission inducing conditions, such as in fatty acids condition, the peroxisomes are needed to be largely produced in a short time and the de novo formation process may be not enough or effective. In contrast, the peroxisome fission cycles would fulfill peroxisome demands in a limited time. During infection of M. oryzae, the lipid stores should be utilized less than 12 h. The rapid lipolysis of lipid bodies produced mass fatty acids, which in turn induces peroxisome fission process (de novo biogenesis efficiency could also be elevated), and massive peroxisomes are produced in short time, thus promoting fatty acids utilization and facilitating infection. When fatty acids are utilized, the peroxisomes should be decreased in a short time, and then they can be degraded by pexophagy. In C. orbiculare, the CoAtg26-dependent pexophagy is used to recycle cellular amino acids of the appressoria for infection [13]. How the peroxisome fission and pexophagy are activated and suspended remains obscure. The Snf1/AMPK pathway plays central role in response to nutrient stress in M. oryzae. A recent study demonstrated that the MoSnf1 pathway can regulate peroxisomal maintenance and lipid metabolism by responding to nutrient-free environment [46]. In Δmosnf1 mutant, the peroxisomes are significantly decreased during appressoria formation. Accordingly, the Δmosnf1 mutant is also defect in lipid droplet mobilization, fails to generate enormous turgor, and loses its virulence [46]. Other regulatory mechanisms should also be uncovered in the future. 3. Metabolic Functions of Peroxisomes Multiple metabolic processes occur in the peroxisomes, which makes the peroxisomes play crucial role in fungal development and pathogenesis. Peroxisomal β-oxidation of fatty acids ubiquitously existed for all eukaryotes. The reactive oxygen species [ROS] homeostasis can be also mediated by peroxisomes. Peroxisomes can be involved in many other metabolic pathways, including glyoxylate cycle in plants and fungi [52], penicillin biosynthesis in Penicillium chrysogenum [53], and melanin biogenesis in filamentous fungi [54]. 3.1. Fatty Acid β-Oxidation The β-oxidation metabolism is mainly used to degrade fatty acids for nutrient and energy utilization [55]. This metabolic process involves four major enzymes, acyl-CoA oxidase, 2-enoyl-CoA hydratase, 3-hydroxyacyl-CoA dehydrogenase, and 3-ketoacyl-CoA thiolase. Through a four-step pathway mediated by these enzymes, the acetyl-CoA is produced [55]. The acetyl-CoA can be fed to the glyoxylate cycle and gluconeogenesis to produce nutrient or metabolites. In M. oryzae, the Mfp1/Fox2 protein has been shown to play an important role in fatty acid metabolism and pathogenesis [47]. The Δmfp1 mutants cannot grow on olive oil or oleic acid as sole carbon sources, indicating its roles in fatty acids metabolism. The expression level of MFP1 is significantly induced in the olive oil condition. The Mfp1GFP fusion protein is well colocalized with FoxA-RFP in the peroxisome-like punctuate structures [47]. Because the A. nidulans FoxA has been proved to be a β-oxidation enzyme and can be located in the peroxisomes, the M. oryzae Mfp1 should also be located in the peroxisomes and is required for fatty acid β-oxidation. In the past, β-oxidation is thought to occur exclusively in peroxisomes in the filamentous fungi, while it can occur in both peroxisomes and mitochondria in mammal. However, recent studies demonstrated that the mitochondrial β-oxidation is also functional and important for the infection of the fungal pathogens [56]. In M. oryzae, Enoyl-CoA hydratase Ech1 is an important mitochondrial β-oxidation enzyme, which is important for conidial germination, appressoria penetration, and host colonization. The Δech1 mutant cannot utilize C14 fatty acid and also cannot well utilize C16 and C18 fatty acids. Consequently, Δech1 is reduced in melanization and sensitive to oxidative stress. Generally, the short- and medium-chain fatty acids (less than 20C) can be oxidized in mitochondria, while long-chain fatty acids (over 20C) should be degraded in peroxisomes to shorter chain fatty acids for full oxidation in mitochondria [56]. Thus, the mitochondrial β-oxidation and peroxisomal β-oxidation can collaborate with each other for different length fatty acid oxidation in M. oryzae. Acetyl CoA is the main product of fatty acid β-oxidation in the appressorium of M. oryzae, which must be transported into different cellular compartments for consumption. The acetyl CoA transportation is catalysed by carnitine acetyl transferases (CATs). In budding yeast S. cerevisiae, Cat2 is involved in transferring acetyl CoA to the cytoplasm, while Cat1 is used to transfer acetyl CoA into mitochondria for utilization by the tricarboxylic acid cycle [57]. Two CAT genes, PTH2 and CRAT2, have been studied in M. oryzae [48]. The results demonstrated that PTH2 plays major role in acetyl CoA transfer. Pth2-GFP protein is colocalized with the peroxisome marker protein and is abundant in appressoria. The Δpth2 is reduced in melanin deposition, defect in host penetration, and essential for pathogenesis [48]. Further analysis found that the Δpth2 mutant cannot utilize some lipid substrates. In contrast, the Δcrat2 displays no evident defect in those mentioned phenotypes [48]. The carnitine-acylcarnitine carrier protein Crc1 functions in transferring the acetyl CoA cross the mitochondrial membrane. The M. oryzae MoCRC1 deletion mutant is severely reduced in appressorial penetration and invasive growth. MoCRC1 is also needed for utilization of olive oil [49]. 3.2. Glyoxylate Cycle The glyoxylate cycle is a metabolic pathway which can be normally found in plants and fungi [52]. This pathway can assimilate acetyl CoA for gluconeogenesis and eventually generate glucose. The glyoxylate cycle is mainly induced when the fatty acids and acetate should be used [52]. The fatty acid β-oxidation pathway produces massive acetyl CoA, which will be processed by glyoxylate cycle. In this pathway, the acetyl CoA can be converted to glyoxylate by isocitrate lyase, and then the glyoxylate can be further converted to malate by malate synthase. The malate can be further metabolized to hexoses by gluconeogenesis. The isocitrate lyase (Icl1) and malate synthase (Mls1) are two of principal enzymes involving glyoxylate cycle [52]. In M. oryzae, ICL1 is highly expressed during appressoria formation and penetration stages, indicating that the glyoxylate cycle should be induced in these stages [50]. Defect in peroxisome biogenesis will lead to loss functions of glyoxylate cycle. For example, disruption of MoPEX19 will result in failure in acetate utilization [16]. 3.3. Redox Homeostasis Oxidative reactions are theme of the peroxisome metabolism, which generates massive reactive oxidative species (ROS), especially the hydrogen peroxide (H2O2) [58]. In order to eliminate harmful ROS, ROS scavenging becomes an important peroxisomal metabolism. To detoxification, the hydrogen peroxide can be scavenged by catalases and peroxidases, which are abundant in peroxisomes. A number of catalases and peroxidases are predicted in genome of M. oryzae, and some of which (such as CATB and CPXB) have been reported to function in host ROS detoxification [59, 60]. However, no catalase or peroxidase has been revealed to take part in intracellular peroxisome ROS detoxification. Glutathione S-transferases (GSTs) and peroxiredoxins (PRXs) are other antioxidant enzymes existing in peroxisomes [61]. There is also no GST or PRX protein reported to play roles in peroxisome ROS detoxification. In Alternaria brassicicola and A. fumigatus, a transmembrane protein TmpL has been identified and proved to be important for reduction of intracellular ROS and detoxification of external ROS and thus is important for fungal infection. TmpL can be located in the woronin body, and its expression level is evidently elevated in conidiation and initial invasive growth stages [62]. During peroxisome β-oxidation process, acetyl-CoA formation will accompany mass formation of FADH2 and NADH. To keep peroxisome redox homeostasis, the FADH2 and NADH should be eliminated. For the NADH, it can be reoxidated to NAD+. This reaction can be catalyzed by the peroxisomal lactate dehydrogenase, which can mediate production of lactate from pyruvate. In M. oryzae, the pyruvate is generated by the alanine: glyoxylate aminotransferase 1 (AGT1), which transfers the alanine amino group to glyoxylate and results in formation of the pyruvate. AGT1GFP is colocalized with RFP-MTS1 fusion protein, demonstrating that AGT1 is located in the peroxisomes [51]. The Δagt1 mutant cannot form appressoria on artificial inductive surface. When the NAD+ and pyruvate were added during conidia germination on artificial inductive surface, the appressorium formation can be restored [51]. Thus, the AGT-mediated pyruvate generation can function as one of factors to maintain redox homeostasis during appressoria formation. 3.4. Melanin Biosynthesis In filamentous fungi, peroxisomes not only are crucial for the primary metabolism, but also play important roles in the biosynthesis of secondary metabolites. Many plant pathogenic fungi can produce melanin to protect the conidia to survive in different environment and to facilitate host penetration during infection. The dihydroxy naphthalene (DHN) melanin is well studied and found to be essential for appressorial mediated penetration in M. oryzae. The fungal appressorium contains a distinct melanin layer located between the cell wall and the membrane, which can be used to generate turgor for penetration. The DHN melanin is synthesized by the polyketide pathway, through which the peroxisomes-derived acetyl-CoA can be used to produce the 1,3,6,8-tetrahydroxynaphthalene (1,3,6,8-THN). The 1,3,6,8-THN is then used to synthesize the DHN melanin, catalyzed by a series of enzymes, including Alb1, Rsy1, and Buf1 [63]. Because the acetyl-CoA is mainly produced in peroxisomes, defects in peroxisome formation would lead to block in melanin synthesis. Consistent with this prediction, all disruptions of the peroxisome biogenesis-related genes can result in melanin deficiency. 3.5. Cell Wall Biosynthesis The fungal cell wall mainly consists of chitin, β-1,3-glucan, β-1,6-glucan, and mannoproteins [64]. This rigid structure can protect fungal from extracellular stresses and is flexible for adaptation to development and environment [64]. It is believed that fungal cell wall chitin and glucan are derived from acetyl-CoA, and the defects in peroxisomes will lead to deficiency in cell wall integrity. Consistent with this hypothesis, the M. oryzae MoPEX5, MoPEX6, and MoPEX19 deletion mutants are all sensitive to the cell wall-perturbing agents, such as Congo Red and Calcofluor White [16, 18, 28]. 4. Peroxisome and Pathogenicity Functions of peroxisomes have been studied in kinds of organisms, including the filamentous fungi. In fungal pathogens, an intriguing feature is their roles in pathogenicity. It is reported that peroxisomes are required for virulence of almost all fungal pathogens, such as the plant pathogens C. orbiculare and M. oryzae, the insect pathogen M. robertsii, and the human pathogens C. albicans, A. fumigatus and C. neoformans. During infection, M. oryzae can form a specialized structure known as appressorium. Along with the formation and maturation of appressoria, the lipid stores are mobilized and utilized. The lipid stores are firstly coupled to lipolysis, resulting in triglycerides and glycerol; the latter can accumulate enormous turgor pressure. Meanwhile, the triglycerides can be adopted by the peroxisomes for subsequent fatty acids β-oxidation to produce acetyl CoA and ATP. The acetyl CoA can be utilized by the glyoxylate cycle and gluconeogenesis pathway for glucan and chitin biosynthesis; they can also be utilized for melanin biosynthesis. Therefore, the peroxisomes mediated cellular processes and metabolisms can provide key factors, such as melanin and cell wall integrity, and play key roles during M. oryzae infection (Figure 1). Detailed peroxisome-related roles during M. oryzae infection will be described below. 4.1. Peroxisome Biogenesis and Pathogenesis Defects in peroxisomal biogenesis will lead to severe disorder of peroxisomal metabolisms, including fatty acids β-oxidation, glyoxylate cycle, melanin, and cell wall biosynthesis. Consequently, the fungal development and pathogenicity will be severely affected. During germination and appressorial development, the expression of MoPEX19 was evidently elevated. Deletion of this gene will lead to deficiency in glyoxylate cycle and severe defects in development and complete loss of pathogenicity [16]. The Δmopex7 mutant is reduced in utilization of short-chain fatty acids and reduced its capacity in conidiation [17]. The MoPEX5 seems to play more important role than MoPEX7, because the Δmopex5 mutant exhibits more severe defects than Δmopex7, such as failure to utilize some fatty acids, generation of less turgor, and more sensitivity to H2O2 pressure. Moreover, distinct defects in developments are also detected in Δmopex5. This phenomenon demonstrated that the PEX5-mediated PTS1 peroxisomal import pathway could be more important than the PEX7-mediated PTS2 peroxisomal import pathway [18]. However, both of the Δmopex5 and Δmopex7 mutants lose their pathogenicity. MoPEX6 is also required for long-chain fatty acids utilization and is essential for pathogenicity. The Δmopex6 mutant forms nonmelanized appressoria; as a result, it cannot form the penetration peg and infection hyphae. Additionally, mycelia of Δmopex6 are more sensitive to Calcofluor White, suggesting the cell wall of the mutant is defect [28]. 4.2. Peroxisome Fission and Pathogenesis Block in peroxisome proliferation can result in failure to increase peroxisome number and impact the peroxisomal metabolism. In M. oryzae, deletion of MoPEX11A and PEF1 can both severely reduce the fatty acids utilization and virulence capacity [20]. However, in contrast to totally loss of virulence in Δmopex5, Δmopex6, Δmopex7, or Δmopex19, the reduction of the virulence in Δmopex11A and Δpef1 is evidently slighter [20, 33]. Other phenotypic defects, such as the melanin layer formation, turgor generation, cell wall integrity, and ROS tolerance, are also slighter in Δmopex11A and Δpef1 [20, 33]. These indicate that the de novo formation, another way for peroxisome proliferation, can still function or compensate the defects of the peroxisome fission in the Δmopex11A and Δpef1 mutants. 4.3. Pexophagy and Pathogenesis In C. orbiculare, the Atg26-mediated pexophagy has been proved to be essential for pathogenicity, by rapidly removing redundant peroxisomes after appressoria maturation [13]. The recycling of cellular components required for invasive growth could be the primary cause. However, it seems that the pexophagy process could be dispensable for pathogenicity in M oryzae. It has been proved that the Magnaporthe MoATG26 gene is not involved in pexophagy and is dispensable for virulence [19]. Another gene, MoSNX41, obtains the ability to regulate pexophagy in M. oryzae, and it plays important roles in pathogenesis. However, its pathogenicity-related function is not relevant to roles in pexophagy, because the yeast ScSnx42 (homolog of MoSnx41) can restore the pexophagy deficiency of Δmosnx41, but cannot recover the defects of pathogenesis [19]. The function of MoSnx41 in conidiation and pathogenesis could be related to Snx41-dependent retrieval trafficking pathway, which may function in gamma-glutamyl cycle and GSH antioxidant production. 4.4. Woronin Body and Pathogenesis Failing to form woronin body would result in multiple phenotypic defects in M. oryzae. The Δhex1 mutant is normal in mycelial growth, conidiation, and mating processes, but it forms abnormal appressoria, delayed in host penetration and severely blocked in infection hyphae growth [45]. As a result, Δhex1 is severely reduced in virulence. Besides, lack of HEX1 will also result in failure to survive in nitrogen starvation condition, which could explain why the mutant cannot survive in host cells with kinds of cellular damage. The peroxisome β-oxidation is not affected in Δhex1, indicating the function of woronin body is distinct from the peroxisomes, although it is derived from the latter [45]. 4.5. Fatty Acid β-Oxidation and Pathogenesis Peroxisomal β-oxidation is one of the chief catabolic processes during fungal infection, which can produce acetyl CoA and energy, as well as glycerol. The glycerol is used to form appressoria turgor, and the acetyl CoA can be used by the glyoxylate cycle to produce nutrient; it also can be used to synthesize melanin and cell wall contents, or other purposes. All of the mentioned products are critical for fungal infection. In M. oryzae, the Mfp1 protein involving in peroxisomal β-oxidation is proved to play important roles in fatty acid metabolism and pathogenesis [47]. Defects in peroxisome biogenesis will severely block fatty acids β-oxidation, and all peroxisome biogenesis and peroxisome fission-related genes are important for fatty acids β-oxidation. For example, the PEX6 disruption mutant is defect in olive oil utilization, cell wall integrity, and appressorial melanization and is lost in penetration capacity [28]. Block in acetyl CoA transportation will lead to similar defect in those mentioned cellular processes. The Δpth2 mutant produces less melanin than the wild type and fails to penetrate the host cells and thus is essential for pathogenesis [48]. It cannot grow on lipid substrates. MoCRC1 is also required for olive oil utilization. The Δmocrc1 deletion mutant is severely reduced in penetration and invasive growth. The β-oxidation can also occur in mitochondria [49]. However, it seems like that the peroxisomal β-oxidation is important for appressoria-mediated penetration, while the mitochondrial β-oxidation functions in conidial viability and keeping redox homeostasis during host colonization. 4.6. Glyoxylate Cycle and Pathogenesis The peroxisomal β-oxidation produced acetyl CoA should be used by the glyoxylate cycle to provide a mechanism for glucose generation. Glyoxylate cycle enzymes, such as Icl1, are required for full virulence of M. oryzae. The expression of ICL1 is significantly elevated during conidial germination, appressorium formation, and penetration peg formation stages. Correspondingly, the Δicl1 mutant is delayed in conidial germination and appressorium formation and retards in cuticle penetration [50]. 4.7. Redox Homeostasis and Pathogenesis Accompanied with the degradation of fatty acids, redox homeostasis will be broken, where it is harmful to the fungi and must be rebalanced quickly. Failure in removing redundant oxides may lead to reducing of infection. For example, acetyl-CoA formation resulted in mass NADH, which can be eliminated by reoxidating it to NAD+. This reaction is catalyzed by peroxisomal lactate dehydrogenase and needs pyruvate. The pyruvate is generated by the alanine: glyoxylate aminotransferase 1 (Agt1) in M. oryzae. The Δagt1 mutant fails to penetration via appressoria and totally lost its pathogenicity [51]. 5. Conclusions and Perspective As a model plant pathogen, the rice blast fungus M. oryzae gains more attention on role of peroxisomes than other pathogens. Considerable progress has been made for us to understand life cycle and functions of the peroxisomes in the filamentous fungi. Knowledge gained from past studies will provide comprehensive understanding in the peroxisomes and may lead to develop novel targets for new drugs against pathogenic fungi. The mechanistic details the peroxisome life cycle and functions are developing rapidly, but how these processes can be well tuned according to the developmental stages and environmental conditions is largely unknown. In the future, efforts should be done to elucidate these regulatory mechanisms. A large number of PEX genes can be found in the genome of M. oryzae; the precise roles of these should be further characterized in the future. Another challenge is to reveal the mechanism of de novo synthesis and uncover its roles during appressorium formation. The connections between the peroxisomes and other cellular processes or structures should also be addressed. Genome-wide screening of peroxisome-related genes and global analysis of the PEX genes can help us to systematically investigate functions and mechanisms of the peroxisomes. The omics approaches can help us to establish the peroxisomal regulatory networks. Acknowledgments The work of Xiao-Lin Chen was supported by the National Natural Science Foundation of China (Grant 31571952) and Fundamental Research Funds for the Central Universities (Program nos. 0900206306 and 2662015PY085). Competing Interests The authors declare that there is no conflict of interests regarding the publication of this paper. Figure 1 Life cycle and functions of the peroxisomes in M. oryzae. (a) Model of life cycle of the peroxisomes. The peroxisomes are synthesized from the ER and then mature through peroxisome biogenesis process. During the fission inducing condition, the matured peroxisomes can be elongated, and then the daughter peroxisomes can be produced by the fission process, the newly formed peroxisomes will mature through the biogenesis process, and the matured peroxisomes can be elongated again for another fission cycle. When the fission inducing condition is removed, the redundant peroxisomes can be eliminated through pexophagy process. (b) Function of the peroxisomes during fungal infection. When the conidia attach the host surface, the cAMP/PKA signaling pathway is activated, leading to mobilization of the lipid stores by lipolysis, and produces the fatty acids and glycerol. The glycerol will be used to generate turgor. The fatty acids will be taken by the peroxisomes for β-oxidation, which can produce mass of acetyl CoA. Acetyl CoA can be used by the glyoxylate cycle and gluconeogenesis to produce glucose for infection or be used to synthesize melanin and cell wall components. Together with the glycerol generated turgor, these products can help the fungus to penetrate the cuticle and colonize in the host cells. Table 1 Peroxisome-related genes identified in M. oryzae. Gene Functions References Peroxisome biogenesis       MoPEX5 Receptor of PTS1 peroxisomal matrix proteins [18]   MoPEX6 Peroxisomal matrix protein import [28]   MoPEX7 Receptor of PTS2 peroxisomal matrix proteins [17, 18]   MoPEX19 Peroxisomal membrane proteins import [16] Peroxisome fission       MoPEX11A/11B/11C Peroxisome elongation [20]   PEF1 Peroxisome division [33]   MoFis1 Peroxisome division [36] Pexophagy       MoSNX41 Pexophagy and retrieval trafficking [19]   MoPEX14 Pexophagy [19] Woronin body       HEX1 Seal the septal pore [45] β-oxidation       MFP1 Peroxisome β-oxidation [47]   PTH2 Acetyl CoA transportation [48]   CRAT2 Acetyl CoA transportation [48]   MoCRC1 Carnitine-acylcarnitine carrier [49] Glyoxylate cycle       ICL1 Isocitrate lyase/glyoxylate cycle [50] Redox homeostasis       AGT1 Synthesis of the pyruvate [51] ==== Refs 1 Smith J. J. Aitchison J. D. 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A central role for the peroxisomal membrane in glyoxylate cycle function Biochimica et Biophysica Acta—Molecular Cell Research 2006 1763 12 1441 1452 10.1016/j.bbamcr.2006.09.009 2-s2.0-33845368338 53 Opaliński L. Bartoszewska M. Fekken S. De novo peroxisome biogenesis in Penicillium chrysogenum is not dependent on the Pex11 family members or Pex16 PLoS ONE 2012 7 4 e35490 10.1371/journal.pone.0035490 2-s2.0-84859811841 54 Langfelder K. Streibel M. Jahn B. Haase G. Brakhage A. A. Biosynthesis of fungal melanins and their importance for human pathogenic fungi Fungal Genetics and Biology 2003 38 2 143 158 10.1016/s1087-1845(02)00526-1 2-s2.0-0037373742 12620252 55 Poirier Y. Antonenkov V. D. Glumoff T. Hiltunen J. K. Peroxisomal β -oxidation—a metabolic pathway with multiple functions Biochimica et Biophysica Acta—Molecular Cell Research 2006 1763 12 1413 1426 10.1016/j.bbamcr.2006.08.034 2-s2.0-33845326985 56 Patkar R. N. Ramos-Pamplona M. Gupta A. P. Fan Y. Naqvi N. I. 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==== Front Case Rep OtolaryngolCase Rep OtolaryngolCRIOTCase Reports in Otolaryngology2090-67652090-6773Hindawi Publishing Corporation 10.1155/2016/6971491Case ReportPrimary Neuroendocrine Tumor of the Parotid Gland: A Case Report and a Comprehensive Review of a Rare Entity http://orcid.org/0000-0001-8686-0236Martínez-Sáez Olga 1 * Molina-Cerrillo Javier 1 Moreno García del Real Carmen 2 http://orcid.org/0000-0002-0551-5180Barberá Durban Rafael 3 Díez Juan J. 4 Alonso-Gordoa Teresa 1 Pulido Enrique Grande 1 1Department of Medical Oncology, Ramón y Cajal Hospital, University of Alcalá de Henares, Carretera Colmenar Viejo, Km 9.1, 28034 Madrid, Spain2Department of Pathology, Ramón y Cajal Hospital, University of Alcalá de Henares, Carretera Colmenar Viejo, Km 9.1, 28034 Madrid, Spain3Department of Otorhinolaryngology, Ramón y Cajal Hospital, University of Alcalá de Henares, Carretera Colmenar Viejo, Km 9.1, 28034 Madrid, Spain4Department of Endocrinology, Ramón y Cajal Hospital, University of Alcalá de Henares, Carretera Colmenar Viejo, Km 9.1, 28034 Madrid, Spain*Olga Martínez-Sáez: olgamarsa@hotmail.comAcademic Editor: Yorihisa Orita 2016 16 8 2016 2016 69714911 5 2016 25 7 2016 Copyright © 2016 Olga Martínez-Sáez et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Neuroendocrine tumors (NETs) comprise a heterogeneous group of malignancies from cells derived from the neural crest with neuroendocrine differentiation. Despite the differences in the site of origin, nomenclature, biological behavior, and functional status, NETs share certain ultrastructural and immunohistochemical features. NETs are relative rare tumors with an annual incidence of 5.76 new cases per 100.000 inhabitants and they usually appear in the gastrointestinal tract or in the pulmonary system. Head and neck NETs are uncommon with limited information regarding frequency, most of them showing small cell carcinoma features. NETs that arise from the salivary glands are exceedingly rare. Regardless of their low frequency, it is imperative to accurately differentiate these tumors from the much more common squamous cell carcinomas and from metastasis from another primary tumor due to the completely different therapeutic approaches and prognosis. The diagnosis is based on the recognition of the typical neuroendocrine architecture and immunohistochemical staining and on an exhaustive work-up. Hereby, we report a case of a moderately differentiated NET of the parotid gland that was treated with a complete parotidectomy. We summarize the clues that led to the final diagnosis and major strategies that were employed to manage the patient. We also perform a comprehensive review of the scarce available literature on this topic. ==== Body 1. Introduction As an exceedingly rare entity, NETs of the head and neck region represent a diagnostic and therapeutic challenge in the routine practice. A complete work-up is necessary to rule out a metastatic origin of the tumor, since NETs are much more common in other parts of the body [1, 2]. An adequate subclassification of NETs in the head and neck area regarding the degree of differentiation is required to predict the clinical behavior and to support the treatment decision-making. Clinical-morphological correlations in large series of cases are necessary to provide clear diagnostic categories and to define the best therapeutic options [3]. 2. Case Report A 67-year-old woman was referred to our institution's maxillofacial surgery department with a 3-month history of asymptomatic growing mass in the left parotid area. The patient's medical history included hypertension, dyslipidaemia, and chronic bronchitis. Physical examination revealed a nodule of 1.5 cm of diameter in the parotid gland. There were no cervical palpable lymphadenopathies and no intraoral lesions, and the facial nerve was preserved. A fine-needle aspiration biopsy was subsequently performed. The cellular extensions showed abundant cellularity with basaloid appearance with scant cytoplasm. Neither necrosis nor mitosis was observed at the tumor sample. A complete parotidectomy was then performed. The macroscopic examination showed a well-circumscribed elastic white mass located in the superficial parotid lobe that measured 1.6 cm in its greatest dimension. Under the light microscopy it consisted of an epithelial infiltrating neoplasm with an organoid pattern of growth. It showed monomorphous round cells with salt-and-pepper chromatin arranged mostly in nests with a solid or cribriform pattern that formed frequent rosette-like structures (Figure 1). Vascular embolization and perineural infiltration were observed. The immunohistochemical study supported the neuroendocrine origin with positivity for CD56 (Figure 2). CK AE1/AE3 was also positive. Staining was negative for CK 5/6, CK7, CK20, calponin, synaptophysin, and chromogranin. The mitotic index was around 10%. These features were compatible with atypical carcinoid according to the World Health Organization (WHO) classification of head and neck NETs and with a well differentiated, grade 2, NET, according to the European Neuroendocrine Tumour Society (ENETS) and WHO classification of gastroenteropancreatic NETs. The pathological stage was pT1Nx according to TNM/AJCC classification. A clinical and radiographic work-up was performed after surgery. Computed tomography (CT) of the neck, chest, abdomen, and pelvis, positron-emission tomography (PET)/CT, and octreoscan were all negative. The absence of any other tumor confirmed the diagnosis of a primary neuroendocrine tumor of the salivary gland. No further treatment was offered to the patient after surgery. No recurrent disease has been observed after 7 months of following up. 3. Discussion Primary NETs of the head and neck are exceedingly rare and there is a considerable debate regarding the best practical approach for their management. The current WHO classification for lung NETs recognizes four major types based on mitotic rate and extent of necrosis: carcinoid, atypical carcinoid, small cell carcinoma, and large cell neuroendocrine carcinoma [3, 4]. However, some clinicians have argued that the term atypical carcinoid implies a close relationship with the more indolent typical carcinoid, while atypical carcinoids are more aggressive and highly metastatic malignancies. Meacham et al. proposed the terms well differentiated, moderately differentiated, and poorly differentiated to best classify these tumors [2]. Recently, the WHO recommended a new classification system for gastrointestinal NETs regardless of the primary tumor origin. This classification splits tumors in grades based on tumor proliferation: well differentiated NETs and poorly differentiated neuroendocrine carcinomas (NECs). Well differentiated NETs were further separated into 2 subgroups: grade 1, which are tumors having a proliferative index of <2% (or mitotic counts of ≤2 per 10 high power fields) and are equivalent to carcinoid tumor, and grade 2, with proliferative indices ranging from 2 to 20% (or mitotic counts of 3–20 per 10 high power fields); the grade 3 NEC has proliferative indices of >20% (or mitotic counts >20 per 10 high power fields) and was subclassified as large cell or small cell types. We are going to use this last classification in our paper, although its proper application to head and neck NETs has not been determined yet [1]. Primary NETs of the head and neck are more frequently derived from the larynx but only account for 0.5–1% of all tumors at this location [5]. In the salivary glands, most reported NETs are small cell carcinomas (SmCC), constituting around 2% of all tumors, with some cases of large cell NECs and well differentiated, grade 1, NETs, but only few previously reported well (moderately) differentiated, grade 2, NETs [1, 2, 4, 6, 7]. The reported male-to-female ratio for well differentiated, grade 2, NETs of the larynx is 3-to-1, and most patients have been heavy smokers [6]. Poorly differentiated NECs seem to have a strong male predominance and correlation with a smoking habit. This association has not been seen in well differentiated tumors [8]. The pathological diagnosis of the NET in the head and neck area may be difficult just because of the low frequency of these tumors in that location. The diagnosis is based on histological, ultrastructural, and immunohistochemical criteria, which may be overlooked or misdiagnosed especially in small biopsy samples. For that reason, a large core needle biopsy, rather than a fine-needle aspiration, is preferred for the diagnosis. Due to its rarity, an adequate metastatic work-up is also imperative for the diagnosis of a primary tumor. The morphological characteristics of NETs are the organoid pattern of growth (nests, cords, trabeculae, glands, or rosette-like structures), the presence of neurosecretory cytoplasmatic granules and finely granular chromatin, and the absence of keratinization [4]. The differentiation between well and poorly differentiated tumors is essential to adequately predict the clinical behavior. Unlike NETs, NECs usually appear with a solid growth pattern, a less frequent gland formation, and a marked cellular pleomorphism, with abundant mitosis and necrosis. Vascular and perineural invasions are also common findings in poorly differentiated NECs [1, 4]. The immunodiagnostic is based on immunohistochemical proof of a simultaneous epithelial and neuroendocrine differentiation. The tumor cells stain positively with broad-spectrum cytokeratin and they often display the characteristic punctate paranuclear dot staining [9]. Some tumors will also react with cytokeratins 7 and 20 (CK-7 and CK-20 positivity). NETs are staining for at least one of the most known neuroendocrine markers [synaptophysin, chromogranin, and CD56 neural cell adhesion molecule (NCAM), CD57 (Leu-7), and neuron specific enolase (NSE)] [1, 4, 7]. Immunohistochemical staining is helpful to rule out the differential diagnosis of a primary NET at the parotid gland from a distant metastasis from a NET with another primary origin. For example, thyroid transcription factor-1 (TTF-1) is a sensitive marker for lung SmCC (positive in 80%–100%), so its absence in tumor cells is of value to exclude a metastatic NEC of the lung. TTF-1 also helps to rule out Merkel cell carcinoma, where it is consistently negative. CK20 positive staining observed in primary salivary carcinomas may help to exclude metastatic small cell carcinoma of pulmonary origin, which typically does not stain with CK20. On the other hand, CK20 negativity practically rules out Merkel cell carcinoma (Table 1) [3, 9, 10]. Immunohistochemical study is also useful to distinguish other malignant small round cell neoplasms that may be considered in the differential diagnosis, as olfactory neuroblastoma, sinonasal undifferentiated carcinoma, basaloid squamous carcinoma, non-Hodgkin lymphoma, and paraganglioma (Table 2) [1, 2, 9, 11, 12]. Besides the immunohistological analysis, the clinical exam and radiologic imaging with CT, PET/CT, and octreoscan are basic to rule out an alternative primary tumor [13]. Moreover, octreoscan may demonstrate the presence of somatostatin receptors in tumor cells that can be amenable to radiometabolic treatment [4, 14]. As in other primary origin NETs, prognosis will depend on the histological subtype and the stage at diagnosis. Well differentiated NETs of head and neck have been classically thought to be indolent; however, recent data have shown that their biologic behavior is significantly worse than other NETs in the body and locoregional metastasis reported rates are around 30% [2, 8, 14]. Woodruff and Senie found that well differentiated, grade 2, NETs of the larynx had an aggressive nature with metastasis to neck nodes in 43% of cases and to distant sites in 44% and five-year survival of 48% [6]. Poorly differentiated NECs are highly malignant tumors [2]. Metastases were most often found in cervical nodes, liver, bone, skin, and lung. Survival rates were similar to those for pulmonary SmCC, with 2- and 5-year survival rates of only 16% and 5%, respectively [2, 15]. The therapeutic approaches to NETs of the head and neck area vary according to the histological type and disease stage [4]. The mainstay of treatment to well differentiated NET is surgical resection. There is a lack of agreement about the need of elective neck dissection in these cases. Some authors recommend further lymphadenectomy mostly in well differentiated, grade 2, NETs due to the high likelihood of nodal metastasis, while others do not [16]. In addition, some authors advocate that adjuvant radiation conferred no benefit in the treatment of (moderately) well differentiated NETs of the larynx despite the established role of radiotherapy in more frequent tumors of the head and neck area [6]. This fact emphasizes the need to distinguish these tumors from more radiation-sensitive squamous cell carcinomas. Chemotherapy seems to be ineffective as well, although the responsiveness of these lesions to the different chemotherapy regimens has not been well documented. By contrast, chemoradiotherapy is the treatment of choice of poorly differentiated NECs [6, 12]. The chemotherapeutic regimens usually included platinum in combination with other agents (mostly etoposide, but also 5-fluorouracil, ifosfamide, paclitaxel, methotrexate, gemcitabine, vincristine, vinblastine, or bleomycin). In our patient, no further treatment was offered after surgery due to the lack of evidence behind the realization of a neck dissection and the use of radiation or chemotherapy in the adjuvant context of well differentiated NETs. The extensive work-up did not show any evidence of disease, neither local or regional nor distant, which supported the decision of not adding any treatment. Expression of somatostatin receptors through a high uptake of octreotide in scintigraphy could be useful to select tumors that could benefit from the systemic use of somatostatin analogues [17]. Due to the low incidence of these tumors in the head and neck location there is a lack of prospective evidence behind the use of everolimus, peptide receptor radionuclides therapy (PRRT), multikinase inhibitors, or novel chemotherapeutic agents like temozolomide and/or capecitabine. In conclusion, the present case report emphasizes that the proper pathologic identification of primary NET in the head and neck area and their differentiation from squamous cell carcinoma or a metastatic tumor is necessary because prognosis and management of these patients are not the same. It is also imperative to correctly distinguish between NET subtypes, due to the fact that well and poorly differentiated NECs present different clinical behavior and require different treatment approaches. Because of the rarity of this entity, an appropriate registry of the cases is highly needed to gather experience in its management. Competing Interests The authors declare that they have no competing interests. Figure 1 Light microscopy shows monomorphous round cells with salt-and-pepper chromatin arranged mostly in nests with a cribriform pattern that formed rosette-like structures (hematoxylin and eosin stain, original magnification ×20). Figure 2 Further immunohistochemical analysis shows strong positive staining for CD56 (original magnification ×20). Table 1 Immunohistochemical features that help in the differential diagnosis between NEC from the parotid, SmCC of the lung, and Merkel cell carcinoma.   NEC parotid origin SmCC lung Merkel cell carcinoma TTF-1 − + − CK20 +/− − + CK7 +/− + − Table 2 Immunohistochemical staining of some malignant round cell tumors. SmCC: small cell carcinoma, NB: neuroblastoma, SYP: synaptophysin, CgA: chromogranin A, EMA: epithelial membrane antigen, CK: cytokeratin, TTF-1: thyroid transcription factor-1, NSE: neuron specific enolase.   SmCC Melanoma NB Sinonasal undifferentiated carcinoma Lymphoma Paraganglioma Basaloid squamous carcinoma EMA + − − +   − + CK + − +/− +   − + CD99 +/− − − + +/−   − TTF-1 +/− − − −   − − CD45 − − − − + − − S100 − + − +/−   +/− − HBM45 − + − − − − − CD56 + − + +/−   + − CD57 + − + +/−   + − SYP + − + +/−     − CgA + − + +/−   + − NSE + − + +/−   + − ==== Refs 1 Said-Al-Naief N. Sciandra K. Gnepp D. R. Moderately differentiated neuroendocrine carcinoma (atypical carcinoid) of the parotid gland: report of three cases with contemporary review of salivary neuroendocrine carcinomas Head and Neck Pathology 2013 7 3 295 303 10.1007/s12105-013-0431-6 2-s2.0-84883779338 23456649 2 Meacham R. Matrka L. Ozer E. Ozer H. G. Wakely P. Shah M. Neuroendocrine carcinoma of the head and neck: a 20-year case series Ear, Nose and Throat Journal 2012 91 3 E20 E24 2-s2.0-84861507825 3 Capelli M. Bertino G. Morbini P. Villa C. Zorzi S. Benazzo M. Neuroendocrine carcinomas of the upper airways: a small case series with histopathological considerations Tumori 2007 93 5 499 503 2-s2.0-36749006078 18038886 4 Procopio G. Ricotta R. Fusi A. Neuroendocrine tumors of the larynx: a clinical report and literature review Tumori 2006 92 1 72 75 2-s2.0-33645972913 16683387 5 Ferlito A. Devaney K. O. Rinaldo A. Neuroendocrine neoplasms of the larynx: advances in identification, understanding, and management Oral Oncology 2006 42 8 770 788 10.1016/j.oraloncology.2006.01.002 2-s2.0-33748111106 16815077 6 Woodruff J. M. Senie R. T. Atypical carcinoid tumor of the larynx. A critical review of the literature Journal for Oto-Rhino-laryngology and Its Related Specialties 1991 53 4 194 209 10.1159/000276219 2-s2.0-0025915120 1891252 7 Wenig B. M. 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==== Front Adv MedAdv MedAMEDAdvances in Medicine2356-67522314-758XHindawi Publishing Corporation 10.1155/2016/4985745Research ArticleEvaluation of HLA-G 14 bp Ins/Del and +3142G>C Polymorphism with Susceptibility and Early Disease Activity in Rheumatoid Arthritis http://orcid.org/0000-0002-6074-7101Hashemi Mohammad 1 2 Sandoughi Mahnaz 3 Fazeli Seyed Amirhossein 3 Bahari Gholamreza 2 Rezaei Maryam 2 http://orcid.org/0000-0002-8449-7709Zakeri Zahra 4 * 1Cellular and Molecular Research Center, Zahedan University of Medical Sciences, Zahedan 98167-43181, Iran2Department of Clinical Biochemistry, School of Medicine, Zahedan University of Medical Sciences, Zahedan 98167-43181, Iran3Department of Internal Medicine, School of Medicine, Zahedan University of Medical Sciences, Zahedan 98167-43181, Iran4Department of Internal Medicine, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 19857-17443, Iran*Zahra Zakeri: zah_zakeri@yahoo.comAcademic Editor: Maja Krajinovic 2016 16 8 2016 2016 49857451 4 2016 27 6 2016 20 7 2016 Copyright © 2016 Mohammad Hashemi et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Purpose/Background. Mounting evidence designates that HLA-G plays a role in the regulation of inflammatory processes and autoimmune diseases. There are controversial reports concerning the impact of HLA-G gene polymorphism on rheumatoid arthritis (RA). This study was aimed at examining the impact of 14 bp ins/del and +3142G>C polymorphism with susceptibility and early disease activity in RA patients in a sample of the Iranian population. Methods. This case-control study was done on 194 patients with RA and 158 healthy subjects. The HLA-G rs1063320 (+3142G>C) and rs66554220 (14 bp ins/del) variants were genotype by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFP) and PCR method, respectively. Results. The HLA-G +3142G>C polymorphism significantly decreased the risk of RA in codominant (OR = 0.61, 95% CI = 0.38–0.97, p = 0.038, GC versus GG; OR = 0.36, 95% CI = 0.14–0.92, p = 0.034, CC versus GG), dominant (OR = 0.56, 95% CI = 0.36–0.87, p = 0.011, GC + CC versus GG), and allele (OR = 0.58, 95% CI = 0.41–0.84, p = 0.004, C versus G) inheritance models tested. Our finding did not support an association between HLA-G 14 bp ins/del variant and risk/protection of RA. In addition, no significant association was found between the polymorphism and early disease activity. Conclusion. In summary, our results showed that HLA-G +3142G>C gene polymorphism significantly decreased the risk of RA in a sample of the Iranian population. Zahedan University of Medical Sciences6840 ==== Body 1. Introduction Rheumatoid arthritis (RA) is the most common autoimmune disease of unknown etiology affecting approximately 0.5–1% of the human population worldwide [1, 2]. The disease is 2-3 times more common in females than in males. It has been proposed that both genetic and environmental factors are involved in the expression and complications of the disease [3–8]. Genetic factors are assumed to contribute to up to 60% of the risk of developing RA [2]. Human leucocyte antigen-G (HLA-G), a nonclassical major HLA class Ib molecule, may suppress functions of natural killer (NK) cells, CD4+, CD8+ lymphocytes, and dendritic cell [9–11]. HLA-G protein potentially exists as seven isoforms including four membrane-bound (HLA-G1, -G2, -G3, and -G4) as well as three secreted soluble (HLA-G5, -G6, and -G7) proteins [12]. HLA-G gene, which is located on chromosome 6 (6p21.31), contains a 14 bp insertion (ins)/deletion (del) and a +3142G>C (rs1063320) polymorphism in 3′-untranslated region (3′UTR) of HLA-G. HLA-G expression rate and plasma level are influenced by polymorphism in the promoter region as well as 3′-untranslated region (UTR) variants [13–15]. A 14 bp ins/del polymorphism in exon 8 in the 3′UTR of HLA-G was found to be associated with the stability and splicing patterns of HLA-G mRNA isoforms. The homozygous deletion of 14 bp confers a more stable mRNA as compared to the homozygous insertion genotype [13, 14, 16]. Low levels of membrane bound and sHLA-G levels are associated with the ins allele [13]. +3142G>C polymorphism influences the affinity of HLA-G mRNA targeted by different microRNAs as demonstrated by an in silico study [17]. +3142G allele has a binding site with higher affinity for miR-148a, miR-148b, and miR-152 downregulating the expression of HLA-G [15, 18]. The common polymorphism of the HLA-G seems to affect its level of expression and may have an impact on disease susceptibility in autoimmune disorders. It has been reported that plasma soluble HLA-G (sHLA-G) levels were lower in RA patients than in controls [19]. Several studies investigated the impact of common polymorphism of HLA-G (+3142G>C and 14 bp ins/del) on RA risk in various population, but the findings have been controversial [20–24]. Therefore, the present study was aimed at examining whether rs1063320 (+3142G>C) and rs66554220 (14 bp ins/del) polymorphism in the HLA-G gene were associated with susceptibility to RA in a sample of Iranian population. 2. Material and Methods 2.1. Patients A total of 352 subjects including 194 patients with RA fulfilling the 2010 American College of Rheumatology/European League Against Rheumatism for RA [25] and 158 unrelated healthy subjects were enrolled in the study. The cases were selected from RA patients admitted to the Rheumatology Clinic of university-affiliated hospital (Ali-Ebne-Abitaleb Hospital, Zahedan, Iran). The control group consisted of 158 whose age and sex matched healthy individuals with no clinical symptoms or family histories of RA, and they were unrelated to RA patients, had no known autoimmune diseases, and were from the same geographical origin as the patients with RA (Zahedan, Iran). The project was approved by local ethics committee of Zahedan University of Medical Sciences and informed consent was obtained from all participants. Genomic DNA was extracted from peripheral blood samples using salting out method as described previously [26]. Among all the participant patients, 30 early RA subjects who were symptomatic for ≤1 year enrolled for subsequent follow-up study. All the patients were on standard therapeutic regimen. The disease activity was determined by disease activity score 28 (DAS-28) at the beginning and the end of the follow-up study (at least 18 months) by the same specialist rheumatologist. At the end of the study, the patients were stratified into remitting (DAS-28 < 2.6) and nonremitting (DAS-28 ≥ 2.6) patients. Genotyping of HLA-G rs1063320 (+3142G>C) variant was performed by PCR-RFLP methods. The set of forward and reverse primers were 5′-CATGCTGAACTGCATTCCTTCC-3′ and 5′-CTGGTGGGACAAGGTTCTACTG-3′ [27]. Amplification was done with an initial denaturation step at 95°C for 5 min, followed by 30 cycles of 30 s at 95°C, 30 s at 65°C, and 30 s at 72°C with a final step at 72°C for 10 min. 10 μL of PCR products was digested with BaeGI restriction enzyme (Fermentas). G allele digested and produced 316 bp and 90 bp (digested), while C allele undigested and produced 406 bp (Figure 1). Genotyping of HLA-G rs66554220 (14 bp ins/del) variant was done by polymerase chain reaction [28]. The forward and reverse primers were 5′-TCACCCCTCACTGTGACTGATA-3′ and 5′-GCACAAAGAGGAGTCAGGGTT-3′, respectively. In each 0.20 mL PCR reaction tube, 1 μL of genomic DNA (~100 ng/mL), 1 μL of each primer (10 μM), 10 μL of 2x Prime Taq Premix (Genet Bio, Korea), and 5 μL ddH2O were added. The PCR cycling conditions were as follows: an initial denaturation step of 5 min at 95°C followed by 30 cycles of 30 s at 95°C, annealing at 56°C for 30 s, and extension at 72°C for 30 s, with final extension at 72°C for 5 min. The PCR products were separated by electrophoresis in 2% agarose gels and observed under ultraviolet light. Product sizes were 127 bp for del and 141 bp for ins allele (Figure 2). 2.2. Statistical Analysis Statistical analysis of the data was done using statistical software package SPSS 20 software. Independent sample t-test for continuous data and χ 2 test for categorical data were used. The associations between genotypes of HLA-G gene and RA were assessed by computing the odds ratio (OR) and 95% confidence intervals (95% CI) from logistic regression analyses. Haplotype analysis was performed using SNPStats software (a web tool for the analysis of association studies). p value less than 0.05 was considered statistically significant. The Bonferroni correction was applied by multiplying p values by the number of SNPs analyzed. 3. Results In this study, we recruited 194 RA patients (180 female and 14 male; mean age 45.3 ± 14.1 years) and 158 unrelated healthy subjects (140 female and 18 male; mean age: 46.1 ± 12.3 years). There was no significant difference between the groups concerning sex and age (p = 0.815 and p = 0.465, resp.). The genotype and allele frequencies of HLA-G polymorphism in RA patients and in controls are shown in Table 1. HLA-G rs1063320 (+3142G>C) variant decreased the risk of RA in codominant (OR = 0.61, 95% CI = 0.38–0.97, p = 0.038, GC versus GG; OR = 0.36, 95% CI = 0.14–0.92, p = 0.034, CC versus GG) and dominant (OR = 0.56, 95% CI = 0.36–0.87, p = 0.011, GC + CC versus GG) tested inheritance models. HLA-G rs1063320 C allele significantly decreased the risk of RA (OR = 0.58, 95% CI = 0.41–0.84, p = 0.004) compared to G allele. Overall, both chi-square comparison and logistic regression analysis (which was calculated in each model of inheritance) did not reveal an association between HLA-G rs66554220 polymorphism and RA risk (Table 1). In the combined analysis of two HLA-G variants, subjects carrying deldel/GG genotypes had significantly higher risk of RA than 14 bp deldel/+3142GG (Table 2). Haplotype analysis is shown in Table 3. Haplotype +3142G/14 bp del significantly increased the risk of RA (OR = 1.77, 95% CI = 1.14–2.75, p = 0.012), while +3142C/14 bp del decreased the risk of RA (OR = 0.52, 95% CI = 0.30–0.90, p = 0.019) compared to +3142G/14 bp ins. Baseline demographic and clinical characteristics of total follow-up cohort and the remitting and nonremitting subgroups are shown in Table 4. We determined the association of HLA-G polymorphism with early disease activity. Our results revealed no significant association between HLA-G +3142G>C and HLA-G 14 bp ins/del variant and early disease activity (Table 5). The genotype frequency of the HLA-G polymorphism was examined for Hardy-Weinberg equilibrium (HWE). +3142G>C polymorphism in cases and controls was in HWE (χ 2 = 0.50, p = 0.480 and χ 2 = 0.96, p = 0.328, resp.), while the 14 bp I/D variant in cases and controls was not in HWE (χ 2 = 13.94, p = 0.0002 and χ 2 = 8.38, p = 0.004, resp.). 4. Discussion HLA-G is a nonclassical HLA class I molecule that can bind to immune cells and inhibit their function [29, 30]. It is involved in several immunoregulatory processes and may potentially be involved in the pathogenesis of RA. Genetic variants in coding and noncoding regions of the HLA-G may affect biological features of the molecule. Expression rate of HLA-G gene and plasma level are affected by variants in the promoter region as well as 3′UTR [12]. In the present study, we investigated the impact of HLA-G 14 bp ins/del and +3142G>C polymorphism on risk of RA in a sample of Iranian population. The findings of our study showed an association between HLA-G +3142G>C polymorphism and RA in our population. The GC as well as C allele decreased the risk of RA in our population. Regarding HLA-G 14 bp ins/del variant, we did not find any statistically significant difference in either genotype or allele distribution between patients and controls. The deldel/GG genotypes significantly increased the risk of RA compared to insins/GG. In addition, we did not find an association between HLA-G variants and disease activity. In contrast to our findings, Rizzo et al. [31] investigated 23 early rheumatoid arthritis (ERA) patients during a 12-month follow-up disease treatment period. They found that the frequency of 14 bp del allele was associated with disease remission. They concluded that HLA-G may be a candidate biomarker to evaluate early prognosis and disease activity in ERA patients. A meta-analysis performed by Lee et al. [32] revealed no significant association between HLA-G 14 bp I/D and +3142G/C polymorphism and RA risk. Similar negative findings have been reported in Brazilian [24] and Indian population [22]. Although Veit et al. [23] have observed no differences in allelic and genotypic frequencies of the HLA-G 14 bp ins/del polymorphism between RA patients and controls, the 14 bp ins/del polymorphism was associated with juvenile idiopathic arthritis in Brazilian population. In another study, Veit et al. [33] reported that +3142GG genotype significantly increased the risk of RA (odds ratio (OR) = 1.45, 95% confidence interval (CI) = 1.075–1.95, p = 0.030). Kim et al. [20] investigated the impact of rs1736936 (-1202T/C) and rs2735022 (-586C/T) promoter polymorphism of HLA-G gene on RA in Korean population. They found no significant differences in distributions of genotypes and haplotypes between RA patients and control subjects. Verbruggen et al. [19] found that the levels of sHLA-G in patients with RA were significantly lower than healthy controls. They suggested that patients with low sHLA-G levels were unable to suppress self-reactive cells leading to development of autoimmunity. The 3′-untranslated region (UTR) has a major role in HLA-G regulation [17, 34]. It has been proposed that polymorphism exerts a significant effect in the HLA-G function and may have an impact on the expression of sHLA-G [35–37]. The HLA-G expression is influenced by 14 bp ins/del as well as +3142G/C polymorphism in the 3′-untranslated region (3′UTR) of HLA-G gene and may have possible implications of clinical significance [37]. The discrepancy in findings among studies may be due to genetic and environmental differences between the different populations being investigated. The limitation of our study is that we have no data regarding anti-CCP antibodies, RF antibody, HLA-DRB1 shared epitope, and smoking history. Consequently, we could not evaluate the association between HLA-G variants and these factors. However, we believe that our findings provide an important input into the debate concerning the clinical relevance of studied variants. There is no clear explanation for deviation from HWE in our population. The possible reason is that the HLA-G gene is under balancing selection [34]. In summary, we found a significant association between HLA-G +3142G>C variant and susceptibility to RA in a sample of Iranian population. Further association studies with large sample size and different ethnicities are required to verify our findings. Acknowledgments This work was supported by a dissertation grant (MD thesis of SAF no. 6840) from Zahedan University of Medical Sciences. Competing Interests No competing financial interests exist. Figure 1 Photograph of the PCR products of HLA-G +3142G>C polymorphism by polymerase chain reaction-restriction fragment length polymorphism method (PCR-RFLP). G allele digested by BaeGI restriction enzyme and produced 316 bp and 90 bp while C allele undigested 406 bp. M: DNA Marker; Lanes 1 and 4: GC; Lanes 2 and 5: GG; Lane 3: CC. Figure 2 Photograph of the PCR products of HLA-G 14 bp ins/del polymorphism by polymerase chain reaction (PCR). Product sizes were 127 bp for del and 141 bp for ins allele. M: DNA Marker; Lanes 1, 4, and 7: ins/ins; Lanes 2 and 5: ins/del; Lanes 3 and 6: del/del. Table 1 Association of HLA-G polymorphisms and the risk of RA. HLA-G polymorphisms Case n (%) Control n (%) OR (95% CI) p p c 14-bp ins/del (rs66554220)           Codominant            Ins/ins 36 (18.6) 34 (21.5) 1.00 —    Ins/del 123 (63.4) 97 (61.4) 1.20 (0.70–2.05) 0.582 1.00  Del/del 35 (18.0) 27 (17.1) 1.22 (0.62–2.43) 0.603 1.00 Dominant            Ins/ins 36 (18.6) 34 (21.5) 1.00      Ins/del + del/del 158 (81.4) 124 (78.5) 1.20 (0.71–2.03) 0.505 1.00 Recessive            Ins/ins + ins/del 159 (82.0) 131 (82.9) 1.00      Del/del 35 (18.0) 27 (17.1) 1.07 (0.61–1.86) 0.888 1.00 Allele            Ins 195 (50.3) 165 (52.2) 1.00 —    Del 193 (49.7) 151 (47.8) 1.08 (0.80–1.46) 0.649 1.00 +3142G>C (rs1063320)           Codominant            GG 135 (69.6) 89 (56.3) 1.00 —    GC 52 (26.8) 56 (35.4) 0.61 (0.38–0.97) 0.038 0.076  CC 7 (3.6) 13 (8.2) 0.36 (0.14–0.92) 0.034 0.068 Dominant            GG 135 (69.6) 89 (56.3) 1.00      GC + CC 59 (30.4) 69 (43.7) 0.56 (0.36–0.87) 0.011 0.022 Recessive            GG + GC 187 (96.4) 145 (91.8) 1.00      CC 7 (3.6) 13 (8.2) 0.42 (0.16–1.07) 0.068 1.00 Allele            G 322 (83.0) 234 (74.0) 1.00 —    C 66 (17.0) 82 (26.0) 0.58 (0.41–0.84) 0.004 0.005 p c: Bonferroni-corrected p. Table 2 Interaction of 14 bp ins/del and +3142G>C polymorphism of HLA-G gene on rheumatoid arthritis (RA) risk. 14 bp ins/del +3142G>C RA cases n (%) Controls n (%) OR (95% CI) p p c Ins/ins GG 27 (13.9) 27 (17.1) 1.00 — — Ins/del GG 84 (43.3) 56 (35.4) 1.50 (0.79–2.82) 0.257 1.000 Del/del GG 24 (12.4) 6 (3.8) 4.00 (1.41–11.34) 0.010 0.039 Ins/del GC 34 (17.5) 35 (22.2) 0.97 (0.48–1.98) 0.890 1.000 Del/del GC 10 (5.2) 14 (8.9) 0.71 (0.27–1.89) 0.624 0.992 Ins/ins GC 8 (4.1) 7 (4.4) 1.14 (0.36–3.60) 0.922 1.000 Del/del CC 1 (0.5) 7 (4.4) 0.14 (0.02–1.24) 0.063 0.240 Ins/del CC 5 (2.6) 6 (3.8) 0.83 (0.23–3.06) 0.927 1.000 Ins/ins CC 1 (0.5) 0 (0.0) — — — p c: Bonferroni-corrected p. Table 3 Haplotype association of HLA-G +3142G>C and 14 bp ins/del variants with rheumatoid arthritis (RA) risk. +3142G>C 14 bp ins/del RA cases (frequency) Controls (frequency) OR (95% CI) p G Ins 0.4250 0.4652 1.00 — G Del 0.4049 0.2753 1.77 (1.14–2.75) 0.012 C Del 0.0925 0.2026 0.52 (0.30–0.90) 0.019 C Ins 0.0776 0.0569 1.74 (0.75–4.05) 0.200 Table 4 Baseline demographic and clinical characteristics of total follow-up cohort and the remitting and nonremitting subgroups. Parameters Total patients (n = 30) Remitting patients (n = 15) Nonremitting patients (n = 15) p Age (mean ± SD) 45.56 ± 16.99 46.26 ± 17.22 44.86 ± 17.34 NS∗ Gender (%)          Male 2 (6.7) 2 (13.3) 0 (0.0) NS  Female 28 (93.3) 13 (86.6) 15 (100.0)   BMI (Kg/m 2) (mean ± SD) 25.18 ± 5.24 24.87 ± 3.34 25.52 ± 6.84 NS Cigarette (pack/years; mean ± SD) 0.33 ± 1.82 0.00 ± 0.00 0.66 ± 2.58   Hookah (%) 4 (13.3) 1 (6.6) 3 (20) NS Education       NS  Illiterate (%) 12 (40.0) 6 (40.0) 6 (40.0)    Less than diploma (%) 5 (16.7) 1 (6.6) 4 (26.7)    Diploma (%) 8 (26.6) 4 (26.7) 4 (26.7)    Higher education (%) 5 (16.7) 4 (26.7) 1 (6.6)   Length of symptom prior to study (months; mean ± SD) 8.20 ± 4.22 8.20 ± 4.63 8.20 ± 3.94 NS Positive rheumatoid factor (%) 26 (86.7) 12 (80) 14 (93.3) NS Comorbidity       NS  No comorbidity (%) 17 (56.6) 7 (80.0) 10 (66.6)    Type 2 diabetes mellitus (%) 3 (10.0) 1 (6.6) 2 (13.3)    Hypertension (%) 6 (20.0) 5 (33.3) 1 (6.6)    Dyslipidemia (%) 6 (20) 2 (13.3) 4 (26.6)    Other factors (%) 5 (16.6) 4 (26.6) 1 (6.6)   ∗Nonsignificant. Table 5 Association of HLA-G polymorphism in remitting and nonremitting RA patients. Genotypes Remitting patients n (%) Nonremitting patients n (%) OR (95% CI) p 14-bp ins/del         Genotype          Ins/ins 1 (50.0) 1 (50.0) 1.00 —  Ins/del 10 (43.5) 13 (56.5) 0.76 (0.04–13.88) 0.897  Del/del 4 (80.0) 1 (20.0) 4.00 (0.12–137.10) 0.912 Allele          Ins 12 (40.0) 15 (50.0) 1.00 —  Del 18 (60.0) 15 (50.0) 1.50 (0.54–4.17) 0.602 +3142G>C         Genotype          GG 11 (45.8) 13 (54.2) 1.00 —  CG 4 (66.7) 2 (33.3) 2.36 (0.36–15.46) 0.651  CC 0 (0.0) 0 (0.0) — — Allele          G 26 (63.4) 28 (65.1) 1.00 —  C 15 (36.6) 15 (34.9) 0.90 (0.38–2.14) 0.826 ==== Refs 1 Hochberg M. C. Spector T. D. Epidemiology of rheumatoid arthritis: update Epidemiologic Reviews 1990 12 1 247 252 2-s2.0-0025697332 2286222 2 Turesson C. Matteson E. L. Genetics of rheumatoid arthritis Mayo Clinic Proceedings 2006 81 1 94 101 10.4065/81.1.94 2-s2.0-30344465333 16438485 3 Ghelani A. M. Samanta A. Jones A. C. 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==== Front Mediators InflammMediators InflammMIMediators of Inflammation0962-93511466-1861Hindawi Publishing Corporation 10.1155/2016/9856538Research ArticleIdentification of a Novel lincRNA-p21-miR-181b-PTEN Signaling Cascade in Liver Fibrosis Yu Fujun 1 2 3 Lu Zhongqiu 4 Chen Bicheng 5 http://orcid.org/0000-0002-5600-775XDong Peihong 1 * http://orcid.org/0000-0003-0563-2229Zheng Jianjian 5 * 1Department of Infectious Diseases, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China2Department of Gastroenterology, Songjiang Hospital Affiliated Shanghai First People's Hospital, Shanghai Jiao Tong University, Shanghai 201600, China3Department of Gastroenterology, Shanghai Songjiang Hospital Affiliated to Nanjing Medical University, Nanjing 210029, China4Emergency Department, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China5Key Laboratory of Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China*Peihong Dong: dongpeihong111@163.com and *Jianjian Zheng: 120378196@qq.comAcademic Editor: Fumio Tsuji 2016 16 8 2016 2016 98565387 4 2016 21 6 2016 3 7 2016 Copyright © 2016 Fujun Yu et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Previously, we found that long intergenic noncoding RNA-p21 (lincRNA-p21) inhibits hepatic stellate cell (HSC) activation and liver fibrosis via p21. However, the underlying mechanism of the antifibrotic role of lincRNA-p21 in liver fibrosis remains largely unknown. Here, we found that lincRNA-p21 expression was significantly downregulated during liver fibrosis. In LX-2 cells, the reduction of lincRNA-p21 induced by TGF-β1 was in a dose- and time-dependent manner. lincRNA-p21 expression was reduced in liver tissues from patients with liver cirrhosis when compared with that of healthy controls. Notably, lincRNA-p21 overexpression contributed to the suppression of HSC activation. lincRNA-p21 suppressed HSC proliferation and induced a significant reduction in α-SMA and type I collagen. All these effects induced by lincRNA-p21 were blocked down by the loss of PTEN, suggesting that lincRNA-p21 suppressed HSC activation via PTEN. Further study demonstrated that microRNA-181b (miR-181b) was involved in the effects of lincRNA-p21 on HSC activation. The effects of lincRNA-p21 on PTEN expression and HSC activation were inhibited by miR-181b mimics. We demonstrated that lincRNA-p21 enhanced PTEN expression by competitively binding miR-181b. In conclusion, our results disclose a novel lincRNA-p21-miR-181b-PTEN signaling cascade in liver fibrosis and suggest lincRNA-p21 as a promising molecular target for antifibrosis therapy. National Natural Science Foundation of China81000176/H031781100292/H031781500458/H0317Natural Science Foundation of Zhejiang ProvinceY2090326Y2110634LY16H030012Wenzhou Municipal Science and Technology BureauY20110033Y20120127Y20150091Wang Bao-En Liver Fibrosis Foundation20120127 ==== Body 1. Introduction Liver fibrosis, characterized by enhanced extracellular matrix (ECM), represents the common responses of the liver to various chronic injuries. It is well known that hepatic stellate cells (HSCs) are crucial mediators of liver fibrosis [1, 2]. In normal liver tissue, HSCs with abundant vitamin A stores are quiescent. Once activated, they will lose their vitamin A stores and become proliferative and fibrogenic. Currently, efficiently abrogating HSC activation is considered as a potential therapeutic strategy for treating liver fibrosis. MicroRNAs (miRNAs) are highly conserved noncoding RNAs of ~22 nucleotides that regulate gene expression by binding to the 3′-untranslated region (3′-UTR) of the target gene mRNAs to repress protein translation or induce mRNA degradation [3]. Numerous studies have shown that miRNAs participate in the regulation of diverse biological processes including development and differentiation, immune response, metabolism, cell proliferation, and apoptosis [4]. Notably, miRNAs are involved in the pathogenesis and progression of liver fibrosis [5–7]. For instance, miR-29b overexpression upregulates phosphatase and tensin homologue deleted on chromosome 10 (PTEN) expression via inhibiting PTEN hypermethylation, leading to the suppression of HSC activation [7]. Long noncoding RNAs (lncRNAs) are transcribed RNA molecules (>200 nucleotides in length) that structurally resemble mRNAs but do not encode proteins [8]. Emerging data have reported that lncRNAs are involved in a wide range of biological processes, such as proliferation, apoptosis, and differentiation [9]. Recently, lncRNAs are reported to be involved in the progression of liver fibrosis [10, 11]. For example, we previously found that long intergenic noncoding RNA-p21 (lincRNA-p21) can act as an antifibrotic factor in liver fibrosis via p21 [11]. However, the underlying mechanism of the antifibrotic role of lincRNA-p21 in liver fibrosis remains largely unknown. Bian et al. found that DNA methyltransferase1- (DNMT1-) mediated PTEN hypermethylation contributes to HSC activation and liver fibrogenesis, suggesting that PTEN is a negative regulator of liver fibrosis [12]. However, the roles of PTEN in the effects of lincRNA-p21 on HSC activation had never been studied. In this study, we aimed to investigate whether PTEN plays a crucial role in the effects of lincRNA-p21 on liver fibrosis. 2. Materials and Methods 2.1. Materials Transforming growth factor-β1 (TGF-β1) was purchased from R&D Systems (Shanghai, China). Adenoviral vectors expressing a control scrambled sequence (Ad-Ctrl) and adenoviral vectors expressing lincRNA-p21 (Ad-lincRNA-p21) were purchased from GenePharma biotechnology (Shanghai, China). Antibodies against type I collagen, α-smooth muscle actin (α-SMA), PTEN, and GAPDH were obtained from Abcam (Cambridge, MA, USA). Chemically synthesized RNAs including negative control (miR-NC), miR-181b mimics, and miR-181b inhibitor were obtained from GenePharma biotechnology. For transfection, cells were transfected with 1 μg of the chemically synthesized RNA using Lipofectamine 2000 (Invitrogen, USA). 2.2. Human Specimens Written informed consent was received from all patients prior to liver tissues. In this study, 15 healthy controls and 15 liver cirrhosis patients undergoing partial liver resection or liver biopsy were selected from the First Affiliated Hospital of Wenzhou Medical University. Liver cirrhosis was diagnosed by liver biopsy and/or a typical appearance of the liver on abdominal ultrasound and/or computed tomography scan. This study was performed in compliance with the Declaration of Helsinki and approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University. 2.3. Cell Culture Human LX-2 cell strain was obtained from JENNIO Biological Technology (Guangdong, China). It was cultured in DMEM containing 10% fetal bovine serum, 100 U/mL penicillin G sodium salt, and 100 U/mL streptomycin sulfate (Gibco, Carlsbad, CA). The cells were grown in a 37°C incubator with 5% CO2. Exponentially growing cells were seeded in a six-well plate at a density of 1 × 106 cells/well; then the cells were transduced with the Ad-lincARNA-p21 or Ad-Ctrl for 48 h. Cells were also treated with TGF-β1 for different experiment purposes. Cells were harvested for RNA/miRNA isolation, and whole cell extracts were subjected to western blot analysis. 2.4. RNA Interference Analysis RNA interference experiments were performed using Lipofectamine 2000 (Invitrogen) in accordance with the manufacturer's instructions. PTEN siRNA1 (sense 5′-UCUCAAACUUCCAUCAUGGCU-3′; antisense 5′-CCAUGAUGGAAGUUUGAGAGU-3′), PTEN siRNA2 (sense 5′-UGAUAUCUCCUUUUGUUUCUG-3′; antisense 5′-GAAACAAAAGGAGAUAUCAAG-3′), and scrambled siRNA (negative control) were designed and synthesized by GenePharma biotechnology. siRNAs were transfected into cells at a final concentration of 100 nM. 2.5. Quantitative Real-Time PCR Total RNA was extracted from human liver tissues and LX-2 cells using miRNeasy Mini kit (Qiagen, Valencia, CA, USA) according to manufacturer's instructions. Fifty nanograms of total RNA was reverse-transcribed to cDNA using the ReverTra Ace qPCR RT Kit (Toyobo, Osaka, Japan). Gene expression was measured by real-time PCR using cDNA, SYBR Green real-time PCR Master Mix (Toyobo, Osaka, Japan). The primers of lincRNA-p21, alpha-1 (I) collagen (Col1A1), α-SMA, GAPDH, and U6 were designed as described previously [13, 14]. The primers used for PTEN were 5′-CAGGATACGCGCTCGGC-3′ and 5′-ACAGCGGCTCAACTCTCAAA-3′. To detect the expressions of miR-21, miR-24, miR-32, miR-93, miR-153, miR-181b, miR-205, and miR-214, the RT reaction was performed using the TaqMan MicroRNA Assay (Applied Biosystems, Foster City, CA) according to the manufacturer's instructions. The GAPDH (Applied Biosystems, Foster City, CA) level was used to normalize the relative abundance of lincRNA-p21 and mRNAs. U6 snRNA (Applied Biosystems, Foster City, CA) was used to normalize the relative abundance of miRNAs. The expression levels (2−ΔΔCt) of lincRNA-p21, mRNAs, and miRNAs were calculated as described previously [15]. 2.6. Protein Extraction and Western Blot Assay The protein concentration of samples was determined by a BCA protein assay kit (Beyotime Biotechnology, Jiangsu, China). Total proteins (30–50 μg) were separated by SDS-PAGE and blotted onto a PVDF membrane (Millipore Corp, Billerica, MA, USA). After blocking, nitrocellulose blots were incubated for 1 h with primary antibodies diluted in TBS/Tween20 (0.075%) containing 3% Marvel. Rabbit polyclonal antibodies against type I collagen and PTEN were diluted 1 : 1000, and mouse monoclonal antibodies against α-SMA and GAPDH were used at 1 : 2000. The membranes were washed 3 times with TBS/Tween20 (0.075%) containing 3% Marvel, followed by incubation with HRP-conjugated secondary antibodies (1 : 5000) at 37°C for 1 h. The antigen-antibody complex was developed by enhanced chemiluminescence, exposed in the dark room and analyzed for integral absorbance (IA) of the protein bands using quantitative software, Quantity One 4.4. 2.7. Cell Proliferation Assay Cells were seeded in 96-well plates at a density of 1 × 103 cells per well and cultured for 24 h. Cell were transduced with Ad-lincRNA-p21 for 48 h and treated with PTEN siRNA or miR-181b mimics for additional 48 h. Then, cell proliferation was assessed using CCK-8 (Dojindo, Kumamoto, Japan) according to manufacturer's instructions. Absorbance values for each well were determined at 450 nm using a microplate reader (Molecular Devices, Sunnyvale, CA, USA). All experiments were performed in triplicate and repeated at least three times. 2.8. Luciferase Activity Assay According to RNA22 analysis, oligonucleotides containing human lincRNA-p21 3′UTR target sequence were annealed and cloned into the pmirGLO plasmids (Promega, Madison, WI, USA) to generate the pmioGLO-lincRNA-p21 vector: lincRNA-p21-3′UTR for miR-181b (position of 1296–1318) forward, 5′-CCCTCCGACAGGAGTCTCA-3′, and reverse, 5′-TTGAGAGAGATGCACAGCCAG-3′. Empty plasmid pmirGLO was regarded as a negative control. Luciferase reporter plasmids plus miR-181b mimics or miR-NC were cotransfected into LX-2 cells using Lipofectamine 2000 (Invitrogen). Forty-eight hours after transfection, relative luciferase activity was examined in a luminometer using a Dual-Luciferase Reporter Assay System (Promega). 2.9. Statistical Analysis Data from at least three independent experiments were expressed as the mean ± SD. Comparisons between two groups and multiple groups were made using Student's t-test and one-way analysis of variance, respectively. Correlation between the expressions of miR-181b and lincRNA-p21 in liver tissues was examined by Pearson's correlation coefficient. P < 0.05 was considered significant. All statistical analyses were performed with SPSS software (version 13; SPSS, Chicago, IL). 3. Results 3.1. lincRNA-p21 Is Downregulated in TGF-β1-Treated HSCs and Human Liver Cirrhosis In the initiation and progression of liver fibrosis, HSC activation is considered as a vital event [16]. HSC activation can be triggered by various inflammatory cytokines, of which TGF-β1 is recognized as the main profibrogenic mediator [17]. In our experiments, immortalized human stellate cells, LX-2, were treated with different concentrations of TGF-β1, and the expression of lincRNA-p21 was detected. There was a significant reduction in lincRNA-p21 level as the increased concentrations of TGF-β1 (from 0 to 15 ng/mL), suggesting that lincRNA-p21 was reduced by TGF-β1 in a dose-dependent manner (Figure 1(a)). Next, lincRNA-p21 expression was detected at 0, 24, 48, and 72 h in TGF-β1-treated HSCs. Expression was significantly decreased with time, with the lowest level observed at 72 h (Figure 1(b)), clearly indicating lincRNA-p21 expression was reduced by TGF-β1 in a time-dependent manner. lincRNA-p21 expression was additionally detected in human normal liver tissues and cirrhotic tissues. Compared with the control, lincRNA-p21 expression was reduced in the cirrhotic samples (Figure 1(c)). These data collectively suggest that lincRNA-p21 is downregulated during liver fibrosis. 3.2. The Effects of lincRNA-p21 Overexpression on HSC Activation HSC activation is characterized by enhanced cell proliferation, overproduction of ECM, and de novo synthesis of α-SMA [18]. To investigate whether lincRNA-p21 overexpression inhibits HSC activation, LX-2 cells were transduced with Ad-lincRNA-p21 to increase lincRNA-p21 level. Compared with the control, the delivery of Ad-lincRNA-p21 effectively induced the elevation of lincRNA-p21 level (Figure 2(a)). Next, the effects of lincRNA-p21 on cell proliferation were examined in HSCs transduced with Ad-lincRNA-p21. As indicated by the results of CCK-8 assay, lincRNA-p21 overexpression resulted in a significant reduction in HSC proliferation (Figure 2(b)). To confirm the effects of lincRNA-p21 overexpression on HSC transdifferentiation, the mRNA and protein levels of α-SMA in LX-2 cells were detected by real-time PCR and immunoblot analysis, respectively. The results of real-time PCR showed that overexpression of lincRNA-p21 induced a significant reduction in α-SMA mRNA expression (Figure 2(c)). Consistent with the mRNA data, immunoblot assays revealed that lincRNA-p21 inhibited α-SMA protein expression (Figure 2(d)). Then, the effects of lincRNA-p21 on collagen expression were examined. Ad-lincRNA-p21 caused a significant reduction in Col1A1 mRNA expression (Figure 2(e)). In addition, immunoblot assays demonstrated that type I collagen was suppressed by Ad-lincRNA-p21 (Figure 2(f)). These data suggest that HSC activation can be suppressed by lincRNA-p21. 3.3. lincRNA-p21 Inhibits HSC Activation via PTEN PTEN has been reported to function as a “fibrotic suppressor” gene in liver fibrosis [12]. To investigate whether PTEN was involved in the effects of lincRNA-p21 on HSC activation, PTEN expression was detected in HSCs transduced with Ad-lincRNA-p21. Notably, the mRNA and protein expressions of PTEN were enhanced by overexpression of lincRNA-p21 (Figures 2(g) and 2(h)), indicating that PTEN may play a role in the effects of lincRNA-p21 on liver fibrosis. To further confirm whether PTEN was responsible for the antifibrotic effects induced by lincRNA-p21, lincRNA-p21-overexpressing cells were treated with PTEN siRNA. The suppressive effect of PTEN siRNA on PTEN level was examined. As shown in Figure S1A (in Supplementary Material available online at http://dx.doi.org/10.1155/2016/9856538), both PTEN siRNA1 and PTEN siRNA2 caused a significant reduction in PTEN protein level. Then, the expressions of α-SMA and collagen were examined in lincRNA-p21-overexpressing cells with PTEN siRNA. It was found that reduced HSC proliferation caused by lincRNA-p21 was blocked down by PTEN siRNA (Figure 2(b)). In addition, the reduced α-SMA and type I collagen caused by lincRNA-p21 were restored by the silencing of PTEN (Figures 2(c)–2(f)). These results suggest that HSC activation is suppressed by lincRNA-p21, at least in part, via PTEN. 3.4. miR-181b Is Involved in the Effects of lincRNA-p21 on HSC Activation Using bioinformatic analysis (TargetScan), PTEN is predicted as a target of miRNAs. In theory, PTEN can be regulated by them. Many studies have demonstrated that miRNAs including miR-21, miR-24, miR-32, miR-93, miR-153, miR-205, and miR-214 can regulate PTEN expression as a target in human diseases [19–25]. Our previous study found that miR-181b promotes HSC activation via PTEN/Akt pathway [26]. Recently, lncRNAs have been reported to act as competing endogenous RNAs (ceRNAs) to sponge miRNAs, consequently modulating the derepression of miRNA targets [9]. We hypothesized that lincRNA-p21-mediated PTEN expression may be through a ceRNA mechanism. Next, these miRNAs were detected in lincRNA-p21-overexpressing cells. It was found that miR-181b level was reduced by lincRNA-p21, whereas others were not (Figure 3(a)). Compared with the healthy controls, miR-181b level was enhanced in the cirrhotic samples (Figure 3(b)), indicating that miR-181b may be inversely correlated with lincRNA-p21 expression in liver fibrosis. To confirm whether miR-181b was involved in the effects of lincRNA-p21 on PTEN level and HSC activation, lincRNA-p21-overexpressing cells were transfected with miR-181b mimics. Compared with the control, there was a significant increase in miR-181b level in miR-181b mimics group (Figure 3(c)). Interestingly, increased PTEN protein level induced by lincRNA-p21 was inhibited by miR-181b mimics (Figure 3(d)). By contrast, as shown in Fig.S1B, lincRNA-p21-induced PTEN protein level was further enhanced by miR-181b inhibitor. Moreover, lincRNA-p21 overexpression resulted in a significant reduction in HSC proliferation, α-SMA, and type I collagen expressions, which were all blocked down by miR-181b mimics (Figures 3(e)–3(g)). All the data suggest that miR-181b is involved in the antifibrotic effects of lincRNA-p21. 3.5. lincRNA-p21 Is a Target of miR-181b In the liver tissue samples from cirrhotic patients, there was a strong negative correlation between lincRNA-p21 level and miR-181b expression (r = −0.961, P < 0.001) (Figure 4(a)). There might be a relation between lincRNA-p21 and miR-181b, and this hypothesis was confirmed by luciferase reporter assays. Using bioinformatic analysis (RNA22), it was found that lincRNA-p21 contains one target site for miR-181b (Figure 4(b)). Using pmirGLO construct, we generated a lincRNA-p21 luciferase reporter containing the miR-181b-binding sites (pmirGLO-lincRNA-p21) or mutated sites (pmirGLO-lincRNA-p21-Mu) (Figure 4(b)). miR-181b mimics induced a reduction in luciferase activity of pmirGLO-lincRNA-p21 without affecting that of pmirGLO-lincRNA-p21-Mu (Figure 4(c)). lincRNA-p21 is confirmed as a target of miR-181b. All the data suggest that lincRNA-p21 enhances PTEN expression through competitively binding miR-181b. 4. Discussion The results of the present study showed that PTEN expression was enhanced by lincRNA-p21 via the regulation of miR-181b. HSC activation was significantly suppressed by overexpression of lincRNA-p21, including the reduction in HSC proliferation, ECM protein, and α-SMA expression. Without the enhanced PTEN caused by lincRNA-p21, all these effects were blocked down, suggesting that lincRNA-p21 suppresses liver fibrosis, at least in part, via PTEN. Notably, further studies showed that enhanced PTEN protein level and the antifibrotic effects induced by lincRNA-p21 were blocked down by miR-181b. As confirmed by luciferase activity assays, lincRNA-p21 was confirmed as a target of miR-181b. Combined with the data above, we demonstrated that lincRNA-p21 contributes to the suppression of liver fibrosis via miR-181b-mediated PTEN. LncRNAs, lacking significant protein-coding capacity, can regulate a wide range of biological processes through diverse molecular mechanisms including chromatin modification, transcriptional regulation, and posttranscriptional regulation [9, 27, 28]. Moreover, lncRNAs can regulate miRNAs-mediated cellular processes by sponging miRNAs via a ceRNA mechanism. For instance, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) contributes to liver fibrosis via the regulation of RAS-related C3 botulinum substrate 1 (Rac1) and miR-101b [29]. In the past few years, the roles and functions of lncRNAs in human diseases have been widely explored. For example, the G1/S checkpoint is reported to be regulated by lincRNA-p21 via p21 in cis [30]. miRNA-regulated delivery of lincRNA-p21 suppresses β-catenin signaling and tumorigenicity of colorectal cancer stem cells [31]. Our previous study showed that lincRNA-p21 inhibits HSC activation and liver fibrosis via p21 [11]. In our previous study, the roles of lincRNA-p21 in liver fibrosis were explored in mouse primary HSCs and mice. But the present study focused on the roles of lincRNA-p21 in immortalized human stellate cells, LX-2. Interestingly, a novel antifibrosis signaling pathway was identified in the effects of lincRNA-p21 in liver fibrosis. Our data demonstrated that lincRNA-p21 inhibits liver fibrosis through sponging miR-181b in LX-2 cells. PTEN, as a tumor suppressor, is often deregulated in various cancers. Both phosphatidylinositol 3-kinase (PI3K)/Akt and extracellular signal-regulated kinase (ERK) pathways can be regulated by PTEN through its lipid phosphatase and protein tyrosine phosphatase activity, respectively [32, 33]. The loss of PTEN results in the activation of PI3K/Akt and ERK pathways, leading to a reduction in cellular apoptosis and an increase in mitogen signaling [34, 35]. Recent study shows that PTEN is downregulated during liver fibrosis and considered as a negative regulator of liver fibrosis [12]. Overexpression of PTEN leads to the suppression of HSC activation and liver fibrosis [36]. Recently, miR-181b has been reported to contribute to the activation of HSCs through its targets such as p27 [37]. Therefore, miR-181b may play a profibrotic role in liver fibrosis. Our previous study demonstrated that PTEN is a target of miR-181b and HSCs can be activated by miR-181b via PTEN/Akt pathway [26]. Based on our previous study and the role of PTEN in liver fibrosis, whether miR-181b-mediated PTEN was involved in the effects of lincRNA-p21 in liver fibrosis was further explored. At the present study, our results showed that lincRNA-p21 inhibits HSC activation, at least in part, via miR-181b-mediated PTEN. Our data identify a novel lincRNA-p21/miR-181b/PTEN signaling cascade in liver fibrosis. However, the functions of lincRNA-p21 in HSC may be more complex than what we imagine, and further functional analysis should be performed to determine the precise role of lincRNA-p21 in HSC. In conclusion, our results provide new insights that lincRNA-p21 inhibits the progression of liver fibrosis via PTEN. Moreover, our data disclose a novel lincRNA-p21/miR-181b/PTEN signaling cascade in liver fibrosis. The downregulation of lincRNA-p21 in patients with cirrhosis suggests that it may be potential diagnostic biomarkers for cirrhosis. Supplementary Material Fig.S1 The effects of PTEN siRNA, Ad-lincRNA-p21 or miR-181b inhibitor on the protein expression of PTEN. (A) PTEN protein was reduced by PTEN siRNA1 or siRNA2. Cells were transfected with PTEN siRNA for 48 h. (B) PTEN protein was increased by Ad-lincRNA-p21, which was further enhanced by miR-181b inhibitor. Cells were transduced with Ad-lincRNA-p21 for 48 h and treated with miR-181b inhibitor for additional 48 h. GAPDH was used as internal control. Each value is the mean ± SD of three experiments. ∗P<0.05 compared with the control and #P<0.05 compared with Ad-lincRNA-p21 group. Acknowledgments The project was supported by the National Natural Science Foundation of China (nos. 81000176/H0317, 81100292/H0317, and 81500458/H0317), Zhejiang Provincial Natural Science Foundation of China (nos. Y2090326, Y2110634, and LY16H030012), Wenzhou Municipal Science and technology Bureau (nos. Y20110033, Y20120127, and Y20150091), the Wang Bao-En Liver Fibrosis Foundation (no. 20120127), and the key disciplines in Colleges and Universities of Zhejiang Province. Competing Interests The authors declare that they have no competing interests. Figure 1 lincRNA-p21 is downregulated in TGF-β1-treated HSCs and human liver fibrosis. (a) The downregulation of lincRNA-p21 expression was dose-dependently induced by TGF-β1. LX-2 cells were treated with TGF-β1 (0, 5, 10, and 15 ng/mL) for 24 h. (b) The downregulation of lincRNA-p21 expression was time-dependently induced by TGF-β1. LX-2 cells were treated with TGF-β1 (5 ng/mL) for 0, 24, 48, and 72 h. (c) Expression of lincRNA-p21 in liver tissues of healthy controls (n = 15) and cirrhotic patients (n = 15). Each value is the mean ± SD of three experiments. ∗ P < 0.05 compared with the control. Figure 2 Effects of lincRNA-p21 overexpression on cell proliferation, α-SMA, type I collagen, and PTEN in LX-2 cells. Cells were transduced with Ad-lincRNA-p21 for 48 h and treated with PTEN siRNA for additional 48 h. (a) lincRNA-p21 was detected in cells transduced with Ad-lincRNA-p21. Overexpression of lincRNA-p21 suppressed cell proliferation (b), α-SMA mRNA (c), α-SMA protein (d), Col1A1 mRNA (e), and type I collagen (f), which were almost blocked down by PTEN siRNA. Cell proliferation was assessed by CCK-8 assay. PTEN mRNA (g) and protein (h) expressions were upregulated by Ad-lincRNA-p21. GAPDH was used as internal control. Each value is the mean ± SD of three experiments. ∗ P < 0.05 compared with the control and # P < 0.05 compared with Ad-lincRNA-p21 group. Figure 3 miR-181b is involved in the effects of lincRNA-p21 on PTEN expression and HSC activation. Cells were transduced with Ad-lincRNA-p21 for 48 h and treated with miR-181b mimics for additional 48 h. (a) Expressions of miR-21, miR-24, miR-32, miR-93, miR-153, miR-181b, miR-205, and miR-214 were detected in cells transduced with lincRNA-p21. (b) Expression of miR-181b in liver tissues of healthy controls (n = 15) and cirrhotic patients (n = 15). (c) Expression of miR-181b in miR-181b mimics group. (d) lincRNA-p21-induced PTEN was inhibited by miR-181b. (e) The effect of Ad-lincRNA-p21 on cell proliferation was suppressed by miR-181b. (f) The reduced mRNA expressions of α-SMA and Col1A1 by Ad-lincRNA-p21 were inhibited by miR-181b. (g) The reduced protein expressions of α-SMA and type I collagen by Ad-lincRNA-p21 were inhibited by miR-181b. GAPDH was used as internal control. Each value is the mean ± SD of three experiments. ∗ P < 0.05 compared with the control and # P < 0.05 compared with Ad-lincRNA-p21 group. Figure 4 The effect of lincRNA-p21 on PTEN expression is through competitively binding miR-181b. (a) Correlation between lincRNA-p21 level and miR-181b expression in liver tissue samples from cirrhotic patients (n = 15) was subjected to Pearson correlation analysis. (b) Schematic diagram of the miR-181b binding site in the lincRNA-p21 based on RNA22 software. (c) Relative luciferase activities of luciferase reporters bearing wild-type or mutant lincRNA-p21 were analyzed 48 h following transfection with the indicated miR-181b mimics or miR-NC in LX-2 cells. Each value is the mean ± SD of three experiments. ∗ P < 0.05. ==== Refs 1 Friedman S. L. Mechanisms of hepatic fibrogenesis Gastroenterology 2008 134 6 1655 1669 10.1053/j.gastro.2008.03.003 2-s2.0-42949163491 18471545 2 Friedman S. L. 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==== Front Anesthesiol Res PractAnesthesiol Res PractARPAnesthesiology Research and Practice1687-69621687-6970Hindawi Publishing Corporation 10.1155/2016/9425936Research ArticleLength of Stay in Ambulatory Surgical Oncology Patients at High Risk for Sleep Apnea as Predicted by STOP-BANG Questionnaire http://orcid.org/0000-0002-7427-9388Balachandran Diwakar D. 1 * Faiz Saadia A. 1 Hernandez Mike 2 http://orcid.org/0000-0003-0775-3868Kowalski Alicia M. 3 Bashoura Lara 1 http://orcid.org/0000-0002-6134-9308Goravanchi Farzin 3 Cherian Sujith V. 4 http://orcid.org/0000-0003-3443-7078Rebello Elizabeth 3 http://orcid.org/0000-0003-2090-5141Kee Spencer S. 3 French Katy E. 3 1Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA2Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA3Department of Anesthesia and Perioperative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA4Divisions of Pulmonary, Critical Care and Sleep Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA*Diwakar D. Balachandran: dbalachandran@mdanderson.orgAcademic Editor: Enrico Camporesi 2016 16 8 2016 2016 942593616 5 2016 21 7 2016 Copyright © 2016 Diwakar D. Balachandran et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. The STOP-BANG questionnaire has been used to identify surgical patients at risk for undiagnosed obstructive sleep apnea (OSA) by classifying patients as low risk (LR) if STOP-BANG score < 3 or high risk (HR) if STOP-BANG score ≥ 3. Few studies have examined whether postoperative complications are increased in HR patients and none have been described in oncologic patients. Objective. This retrospective study examined if HR patients experience increased complications evidenced by an increased length of stay (LOS) in the postanesthesia care unit (PACU). Methods. We retrospectively measured LOS and the frequency of oxygen desaturation (<93%) in cancer patients who were given the STOP-BANG questionnaire prior to cystoscopy for urologic disease in an ambulatory surgery center. Results. The majority of patients in our study were men (77.7%), over the age of 50 (90.1%), and had BMI < 30 kg/m2 (88.4%). STOP-BANG results were obtained on 404 patients. Cumulative incidence of the time to discharge between HR and the LR groups was plotted. By 8 hours, LR patients showed a higher cumulative probability of being discharged early (80% versus 74%, P = 0.008). Conclusions. Urologic oncology patients at HR for OSA based on the STOP-BANG questionnaire were less likely to be discharged early from the PACU compared to LR patients. National Institutes of HealthCA016672 ==== Body 1. Introduction Obstructive sleep apnea (OSA) is characterized by repetitive episodes of apnea or reduced inspiratory airflow due to upper airway obstruction, resulting in increased respiratory effort, oxyhemoglobin desaturation, and frequent neuronal arousals during sleep. General anesthesia and perioperative analgesia may often exacerbate this pathophysiology; thus, OSA patients may suffer from postoperative respiratory, cardiovascular, and neurological complications [1–6]. OSA can further complicate perioperative care by impacting recovery time and increasing hospital length of stay (LOS). Surprisingly, up to 70% of patients undergoing surgery may have undiagnosed OSA, thus increasing the need to develop strategies to identify patients at risk [7, 8]. The STOP-BANG is a simple patient-administered questionnaire developed by Chung and associates with screen for OSA in the perioperative setting, and it has a high sensitivity for detecting OSA in this setting [9]. The STOP-BANG consists of 8 items producing a numerical score that can be used to classify patients as low risk (LR, score < 3), intermediate risk (IR, score of 3 or 4), and high risk (HR, score ≥ 5) for OSA. Several studies have demonstrated that patients with higher preoperative STOP-BANG scores have increased postoperative complications, including increased difficulty with intubations and unanticipated critical care admissions [10–12]. Although the American Society of Anesthesiologists (ASA) and the Society for Ambulatory Anesthesia have issued guidelines for the perioperative management of OSA, standardized data addressing the appropriate duration and setting for monitoring patients undergoing ambulatory procedures is lacking [13–15]. Furthermore, the optimal management strategy for mitigating the risk of complications in patients with OSA remains unclear. No previous study has examined the incidence and risk of perioperative OSA in an oncologic population. The purpose of our study was to use the STOP-BANG questionnaire to classify patients as LR or HR for OSA and determine if HR patients were less likely to be discharged early from the PACU when compared to LR patients. 2. Methods This study is a retrospective review of the medical records of 1666 consecutive patients with urologic cancer who underwent cystoscopy in the ambulatory surgical center at University of Texas MD Anderson Cancer Center in Houston, Texas, from March 2013 to February 2015. The study was conducted with the approval of our institution's institutional review board. Due to the retrospective nature of this study and adherence to the established standard of care, a waiver of informed consent was obtained. Patients and clinical characteristics included basic demographics: (i) age, (ii) sex, and (iii) body mass index (BMI). The STOP-BANG questionnaire was administered to 404 patients as part of the standard of care while in the perioperative anesthesia assessment center to determine risk of OSA. The STOP-BANG survey consists of the following 8 items: (i) loud snoring; (ii) being tired, fatigued, or sleepy; (iii) observed stop of breathing; (iv) high blood pressure; (v) body mass index (BMI) > 35 kg/m2; (vi) age older than 50; (vii) neck size > 17 inches (40 cm); and (viii) male gender. Patients were assigned a value of “1” if the response was affirmative with each item and a “0” if negative. STOP-BANG scores range from 0 to 8. We utilized a dichotomous framework with HR patients defined as those with a STOP-Bang score ≥ 3 and LR patients defined as those with a STOP-Bang score < 3 [9]. Complete STOP-BANG scores were acquired on 404 patients. If a patient had more than one cystoscopy during the course of the study period, the STOP-BANG score and other parameters were gathered from the first procedure. Medical information from the time spent in the postanesthesia care unit (PACU) was obtained from an integrated perioperative electronic medical record (PICIS, Westfield, MA). Parameters recorded while in the PACU included the following: (i) vital signs during observation, (ii) time of admission to PACU, (iii) time of discharge from PACU, and (iv) procedure time. Length of stay (LOS) was defined as the duration of time in PACU, and it was calculated as the time from admission to the PACU to the time the patient met established discharge criteria such as adequate pain control, voiding, and tolerance of oral intake. All patients were kept for a minimum of 2 hours in the PACU. Oxygen desaturation was defined as oxygen saturation less than 93% with or without supplemental oxygen for 10 seconds, as recorded by pulse oximetry. 2.1. Statistical Analysis Descriptive statistics were used to summarize patients' demographic and clinical characteristics by LR and HR status established by the STOP-BANG questionnaire. Histograms, box plots, and one-way scatter plots were used to visually assess the distributions of continuous characteristics of interest. Independent samples t-tests, or Wilcoxon rank-sum tests if more appropriate, were used to compare continuous characteristics between the LR and HR patients. In cases where the data was categorical, comparisons were made using Chi-square tests. Our primary hypothesis was that HR patients would have longer discharge times relative to LR patients. Cumulative incidence plots were generated to illustrate the cumulative probability of patient discharge at any time during the postoperative follow-up period. The distributions of discharge times were compared between HR and LR patients using a log-rank test. Secondary aims included the assessment of LOS and more frequent episodes of oxygen desaturation where a correlation coefficient was estimated. All statistical tests were two-sided, and a P value < 0.05 was used to signify statistical significance. All analyses were performed using Stata version 12.0 (Stata, College Station, TX). 3. Results Four hundred and four consecutive cancer patients provided complete information to obtain a STOP-BANG score. Patient characteristics are summarized in Table 1. The majority of patients surveyed were men (77.7%), over 50 years of age (90.1%), and had BMI < 30 kg/m2 (88.4%). Anesthesia duration between the two groups was similar with a mean of 63 minutes in the LR group and 61.3 minutes in the HR group (P = 0.560, Table 2). The patients were categorized into HR and LR categories on the basis of the patients' STOP-BANG scores (Table 2). The average PACU LOS, procedure time, and frequency of oxygen saturation <93% during the PACU stay are also shown in Table 2 for both the HR and LR categories. Overall, the mean PACU LOS was 372.4 minutes. Figure 1 shows the cumulative incidence plots which illustrate the time to discharge between HR and the LR groups. By 8 hours, LR patients showed a higher cumulative probability of being discharged early (80% versus 74%, P = 0.008). The separation of the curves does not persist beyond 20 hours, although, by then, most patients were discharged. All patients were discharged home, and there were no patients admitted overnight. Figure 2 demonstrates that the mean duration of anesthesia in LR and HR patients was similar. Oxygen desaturation was examined as a potential etiology for increased LOS (Figure 3), but there was no statistical difference in the frequency of oxygen desaturation between the LR and HR groups (P = 0.131). However, there was a statistically significant positive correlation between LOS and frequency of oxygen desaturation (r = 0.30, P < 0.001). 4. Discussion Our study demonstrates a longer LOS for those stratified as HR patients based on the STOP-BANG questionnaire in an ambulatory oncologic setting. Although more frequent oxygen desaturations were not observed, an increased time to discharge between the LR and HR groups was noted. Our data further corroborates other published works using this screening tool for postoperative outcome in general surgery patients. It is the first study to utilize the STOP-BANG and assess outcomes in a purely oncologic and ambulatory population. Many oncologic patients require general anesthesia and surgery multiple times throughout the treatment of their cancer. Although little is known about the clinical impact of OSA in surgical oncology patients, undiagnosed OSA in the perioperative setting has been shown to have more complications, especially cardiac or respiratory in origin [16]. The nature of anesthesia places patients with sleep apnea at higher risk due to multiple factors including medications (sedation, analgesics), alterations in upper airway patency, and positioning [17]. The supine position required in many surgeries may create dead space thus reducing lung volumes and oxygen saturations. Atelectasis as a result of pain induced splinting or sedation may further contribute to hypoventilation and respiratory insufficiency [18]. Sedation, neuromuscular blockade, and postsurgical opioid pain medications decrease arousal and may elicit sleep apnea symptoms postoperatively by decreasing neuromuscular tone in the upper airway [19, 20]. Finally, sleep fragmentation after surgery can reduce rapid eye movement (REM) sleep stage, immediately postoperatively, following which REM sleep rebound can occur. REM sleep rebound is associated with muscle atonia and may promote sleep apnea and cardiac dysrhythmia days after surgery [7, 21]. We did not observe any new onset atrial fibrillation, ICU admissions, or respiratory distress in our cohort, and we suspect the selection of an ambulatory population with short procedure times likely influenced the lack of these complications. In general, however, complications related to OSA in the perioperative setting may result in longer length of stay and consequent increased resource utilization. The application of the STOP-BANG questionnaire in an oncologic setting is novel. Intuitively, one may question the use of this tool since most assume that cancer patients will be fatigued or tired, thus potentially reducing the specificity of the survey. Interestingly, in our study, only 43.8% of cancer patients affirmed feeling “tired.” It is unclear if that fatigue is due to undiagnosed OSA or cancer, but regardless the nonuniform response shows promise for this tool in surgical cancer patients. Given the success of this tool in the perioperative setting, the application to our cancer population seems logical. It is important to recognize however that the use of the STOP-BANG or any screening tools to diagnose sleep apnea and predict outcomes has limitations, for OSA shares common symptoms with many other diseases, thus lowering their specificity [22]. The score, itself, contains elements such as obesity, age, hypertension, gender, and fatigue. Each of these factors might be associated with increased postoperative stay, regardless of the presence or absence of OSA. Disentangling these contributors to sleep apnea from the disease itself, therefore, is challenging [23]. Finally, the discovery of an early discharge in LR patients despite short procedure duration in an outpatient setting further demonstrates the potential robustness of the STOP-BANG questionnaire. Our study establishes areas of application for the STOP-BANG questionnaire in cancer patients. Our study has limitations inherent to most retrospective studies. We tried to use an adequate sample size and had controls for many of the variables. An electronic medical record and an integrated perioperative medical record were used so loss of patient data was marginal. The procedures for each patient, including the anesthetic agents, process of care, monitoring, and standardized criteria for discharge from the PACU, were the same. Although discharge criteria were standardized, variability due to factors, related to the delivery of care and unrelated to the risk for sleep apnea, such as patient transportation needs, nursing shift changes, and provider implementation, may have affected LOS. We attempted to minimize this variability by evaluating a large number of consecutive patients. All our patients were ambulatory and procedure times were similar and brief, so there may be selection bias since these procedures were not extensive or prolonged. In our study, the difference in time to discharge did not persist beyond 20 hours, although, by then, most patients were discharged. This finding may signify that factors other than risk for sleep apnea may be responsible for prolonged time to discharge from the PACU for some patients. Expansion of our study to include the nonambulatory setting and longer surgery times may identify patients at increased risk of respiratory or cardiovascular complications. Evaluation of these patients may also magnify the difference found between the HR and LR groups. Our findings support the recommendations of the ASA guidelines, which call for more intensive monitoring of patients with OSA [13]. Further delineation of the patient population and surgical procedures which are less prone to complications and lower risk, respectively, may help guide escalation of care for OSA. This would be especially beneficial for anesthesiologists, given the advent of the Affordable Care Act. As in other medical specialties, anesthesiologists will be asked to focus on cost containment by increasing the number of procedures performed in the ambulatory setting, without compromising patient safety. Alternatively, monitoring for complications beyond the PACU may also be considered, for it is known that the effects of anesthesia on respiratory and sleep patterns reach their peak approximately 72 hours postoperatively [24]. Further prospective studies in the oncologic population undergoing longer and more complex surgeries in hospitalized patients with the STOP-BANG score could also better define the role of this screening tool and correlate with more intensive and prolonged monitoring. To date, this study represents the largest group of cancer patients screened preoperatively with the validated STOP-BANG. This study demonstrates that cancer patients undergoing a relatively minor procedure with less known cardiorespiratory morbidity may benefit from screening for OSA with the STOP-BANG questionnaire. Knowing the average duration of LOS for HR patients may assist healthcare providers in selecting an appropriate duration of monitoring. If the LOS is higher for ambulatory patients with suspected OSA, then guidelines that recommend an increase in the duration of observation are justifiable and worth the increased resources that such monitoring entails. Systematically designed studies to better define which patient may undergo higher risk surgery in ambulatory centers safely are needed. The potential role for the STOP-BANG survey in cancer patients may be greater than previously anticipated. Acknowledgments This research is supported in part by the National Institutes of Health through MD Anderson's Cancer Center Support Grant (CA016672). Competing Interests The authors declare that there is no conflict of interests regarding the publication of this paper. Figure 1 Cumulative incidence of discharge over time in the PACU. Figure 2 Procedure time by low and high risk patients based on STOP-BANG questionnaire. Figure 3 Oxygen saturation by low and high risk patients based on STOP-BANG questionnaire. Table 1 Patient characteristics.   N = 404∗ Percentage BMI (kg/m2)      Mean ± SD 28.5 ± 5.7    Median (min to max) 27.3 (16.5 to 51)   Neck circumference (cm)      Mean ± SD 39.8 ± 4.6    Median (min to max) 40 (28 to 54)   PACU LOS (minutes)      Mean ± SD 372.4 ± 433.0    Median (min to max) 137.5 (39 to 1667)   Procedure time (minutes)      Mean ± SD 61.7 ± 24.2    Median (min to max) 55 (26 to 256)   Oxygen saturation below 93% (count)      Mean ± SD 3.7 ± 3.8    Median (min to max) 2 (1 to 18)   STOP-BANG items      Snoring       No 305 75.5   Yes 99 24.5  Tiredness       No 227 56.2   Yes 177 43.8  Observed apneas       No 361 89.4   Yes 43 10.6  High blood pressure       No 169 41.8   Yes 235 58.2  BMI > 35 kg/m2       No 357 88.4   Yes 47 11.6  Age > 50 years       No 40 9.9   Yes 364 90.1  Neck > 40 cm       No 234 57.9   Yes 170 42.1  Gender       Female 90 22.3   Male 314 77.7 STOP-BANG criteria      Low risk (<3) 100 24.8  High risk (≥3) 304 75.2 Bicarbonate ≥ 28 mmol/L      No 194 48  Yes 210 52 BMI, body mass index; SD, standard deviation; PACU, postanesthesia care unit. ∗404 patients provided complete STOP-BANG information to derive a total score. Table 2 Patient characteristics based on STOP-BANG questionnaire.   STOP-BANG   STOP-BANG < 3 (LR) N = 100 STOP-BANG ≥ 3 (HR) N = 304 P value BMI (kg/m2)        Mean ± SD 25.7 ± 3.9 29.4 ± 5.9 —  Median (min to max) 25.4 (18.4 to 36.8) 28 (16.5 to 51)   Neck circumference (cm)        Mean ± SD 36.0 ± 3.3 41.1 ± 4.2 —  Median (min to max) 36 (28 to 46) 41 (29 to 54)   PACU LOS (minutes)        Mean ± SD 278.6 ± 358.6 403.2 ± 451.1 —#  Median (min to max) 117.5 (39 to 1492) 146 (44 to 1667)   Anesthesia duration (minutes)        Mean ± SD 63.0 ± 32.1 61.3 ± 20.9 0.560∗  Median (min to max) 52 (30 to 256) 55.5 (26 to 147) 0.277∗∗ Oxygen sat below 93% (count)        Mean ± SD 2.7 ± 2.6 3.9 ± 3.9 0.131∗  Median (min to max) 2 (1 to 12) 3 (1 to 18)   LR, low risk; HR, high risk; SD, standard deviation. —: BMI and neck circumference were used to create the STOP-BANG score. # P value is not provided; PACU LOS has a bimodal distribution. ∗ P value is based on independent samples t-test. ∗∗ P value is based on Wilcoxon rank-sum test. ==== Refs 1 Riley R. 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==== Front Case Rep HematolCase Rep HematolCRIHEMCase Reports in Hematology2090-65602090-6579Hindawi Publishing Corporation 10.1155/2016/4231276Case ReportAcute Monocytic Leukemia Masquerading Behçet's Disease-Like Illness at Onset in an Elderly Female Koba Shigeru 1 Sekioka Toshio 1 Takeda Sorou 1 Miyagawa-Hayashino Aya 2 Nishimura Keisuke 3 http://orcid.org/0000-0001-9795-0819Imashuku Shinsaku 4 * 1Department of Internal Medicine, Uji-Tokushukai Medical Center, Uji 611-0042, Japan 2Department of Diagnostic Pathology, Kyoto University Hospital, Kyoto 606-8507, Japan 3Division of Pathology, Uji-Tokushukai Medical Center, Uji 611-0042, Japan 4Department of Laboratory Medicine, Uji-Tokushukai Medical Center, Uji 611-0042, Japan*Shinsaku Imashuku: shinim95@mbox.kyoto-inet.or.jpAcademic Editor: Kazunori Nakase 2016 16 8 2016 2016 423127631 5 2016 25 7 2016 Copyright © 2016 Shigeru Koba et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.A previously healthy 74-year-old Japanese female was hospitalized with fever and high C-reactive protein. She developed palatal herpangina-like aphthous ulcers, localized intestinal wall thickening, terminal ileum ulcers, and an erythematous acneiform rash; thus Behçet's disease-like illness was suspected. Significant peripheral blood acute monocytosis developed during her hospitalization and acute monocytic leukemia (FAB M5b) with normal karyotype was diagnosed. By immunostaining, the infiltrating cells in the skin and the terminal ileum were identified as monocytic leukemic cells. This case exhibited a unique initial presentation of Behçet's disease-like illness associated with acute monocytic leukemia. ==== Body 1. Introduction Autoimmune diseases like Behçet's disease (BD) develop in as many as 10% of patients with myelodysplastic syndromes (MDS) or myeloproliferative neoplasms (MPN) [1]. In particular, a link between BD or BD-like illness and chronic myelomonocytic leukemia (CMML) with a trisomy 8 chromosome abnormality has been well recognized [2–4]. However, the association of BD or BD-like illness and acute myeloid leukemia has rarely been reported [5]. In patients with CMML showing cutaneous lesions as a sign of BD or BD-like illness, skin tissues were shown to contain abnormal monocytes, that is, leukemia cutis [6–8]. We report here an elderly Japanese female who initially presented with BD-like illness including cutaneous lesions and thereafter was diagnosed as having acute monocytic leukemia (AMoL; FAB M5b). In this case, we identified leukemic cells in the tissues of skin and ileum. 2. Case Report A previously healthy 74-year-old Japanese female was hospitalized with unknown fever and high C-reactive protein (CRP) values in December 2015. On admission, she was 155 cm in height and 59.2 kg in weight and had temperature of 37.6°C, blood pressure of 118/64 mmHg, pulse rate of 71/min, respiration rate of 18/min, and SpO2 of 94% at room temperature. Physical examination revealed no specific findings. After admission, she developed herpangina-like aphthous ulcers at the palate, when significant monocytosis (absolute monocyte counts >5,000/μL) was first noted; however, monocytosis fluctuated (Figure 1). Thereafter, a CT scan of the abdomen showed localized thickening of the intestinal wall (Figure 2(a)) and colonofiberscopy (CF) revealed the presence of multiple ovoid punched-out ulcers at the terminal ileum and aphthous lesions at the ascending colon (Figure 2(b)). In addition, the patient also developed multiple erythematous rashes on her right thigh (Figure 3(a)). Given the diagnostic criteria of BD [9], the rash was not typical erythema nodosum but was thought rather to be acneiform eruption. Ophthalmological studies showed no evidence of BD signs. Taken together, BD was suspected in this patient from fulfilling 2 major and 1 minor clinical features required in the diagnosis of BD [9]. Thereafter, from the second week of admission, the patient again developed a significant monocytosis (from 15% to >70% in PB, with absolute monocyte counts to a maximum of 23,900/μL) associated with urinary infection at the 5th week of admission (Figure 1). These findings with subsequent bone marrow study confirmed a diagnosis of AMoL (Figures 4(a) and 4(b)). Blood results at the 5th week of admission, when AMoL was diagnosed, were as follows: white blood cells (33,200/μL) containing 15% blasts, 21% promonocytes, 19% mature monocytes, 1% myelocytes, 10% neutrophils, and 33% lymphocytes (Figure 4(a)). Flow cytometric data of a major cell population in PB were as follows: CD13+ (86.4%), CD14+ (80.0%), CD33+ (97.4%), CD34+ (0.8%), CD41+ (44.8%), CD56+ (32.4%), and HLA-DR+ (97.0%). Mature lymphocytes in PB consisted of mostly T cells (approximately 90%), whose markers were CD4+ (59.2%) and CD8+ (27.4%), respectively. By contrast, the hypercellular BM consisted of 33.2% blasts, 15.0% promonocytes, 33.6% mature monocytes, 6.8% granulocytes, 1.4% lymphocytes, 2.0% plasma cells, and 8.0% erythroblasts with an M/E ratio of 0.85 (Figure 4(b)). No significant abnormalities indicating MDS were noted. Flow cytometric results of the major cell population in BM were as follows: CD13+ (38.3%), CD14+ (26.0%), CD33+ (97.5%), CD41+ (45.5%), CD34+ (2.3%), CD56+ (38.0%), and HLADR+ (80.9%). Mature lymphocytes in BM were mostly T cells (approximately 90%) with a CD4/CD8 ratio of 0.54. Myeloperoxidase positive cells accounted for 10% of the mononuclear cells present in both the PB and BM, while alpha-naphthyl butyrate esterase (inhibited by sodium fluoride) positive cells comprised more than 60% of cells in both the PB and BM. These findings were compatible with the diagnostic criteria of AMoL (FAB M5b) [10]. In addition, the karyotypes of PB and BM cells were both 46, XX [20/20]. The other blood chemistry was uneventful except for high levels of CRP (15.75 mg/dL), with aspartate aminotransferase 13 U/L, alanine aminotransferase 14 U/L, lactate dehydrogenase 205 U/L, total bilirubin 0.76 mg/dL, total protein 6.9 g/dL, albumin 2.9 g/dL, blood urea nitrogen 23.4 mg/dL, creatinine 1.61 mg/dL, sodium 135 mmol/L, potassium 3.6 mmol/L, chlorine 97 mmol/L, and calcium 8.0 mg/dL. Since the diagnosis of AMoL (FAB M5b) was confirmed, the biopsied tissues showing BD-like illness were reevaluated with immunostaining except for stomatitis lesions and were proved to have leukemic cell infiltrations. The intestinal ulcer-associated granulation tissues with vascularization and infiltration of cells were positive for lysozyme, CD13, CD14, and CD33 (Figures 2(c) and 2(d)). Also the histopathology of skin rash showed that the infiltrating cells were positive for lysozyme, CD13, CD14, and CD33 (Figures 3(b) and 3(c)). These findings confirmed that the lesions primarily thought due to BD-like illness were in fact AMoL-related. In addition, HLA-typing, performed to ascertain whether the patient had BD-related HLA types, detected the presence of A2/A24 and B52/B55 but not the BD-related HLA-B51 or B5 alleles [11, 12]. As shown in Figure 1, the patient was initially treated with adalimumab for BD-like illness, following the successful report for a case of intestinal BD with trisomy 8 MDS by Kimura et al. [13]; however, after AMoL was confirmed, she was transferred to another hospital for intensive chemotherapy as a very high-risk patient. 3. Discussion This case is not a classic autoimmune case of BD, nor is AMoL that developed during the treatment for BD. AMoL masquerading BD-like illness acutely developed. We had no evidence that this case progressed from CMML, because blood count records for the past 5 years prior to admission showed no increase of monocytes (which remained <10%) in the PB. Clinical features of BD, aphthous stomatitis, skin lesions, and ulcers in the terminal ileum were present, but genital ulcers, vascular, or ocular involvements were absent; thus, it was considered to be an incomplete BD or BD-like illness. The HLA-B51 allele was also absent. To date, the association of BD or BD-like illness with MDS has been well characterized, particularly in those patients with CMML [2–4, 14–16], but rarely characterized in patients with acute myeloid leukemia [5]. The precise causes developing BD or BD-like illness in cases of MDS/CMML are unknown [17]. In immunostaining studies in a classic autoimmune case of BD, Yamana et al. [18] showed that the lymphocytes infiltrating the terminal ileum were high CD4 (Leu 3a)+ cells and low CD8 (Leu 2a)+ cells. On the other hand, Tada et al. [14] previously reviewed the clinical characteristics of MDS-associated BD or BD-like illness in Japan but did not mention the characteristics of infiltrating cells in the tissues. In CMML cases, leukemic cells were reported to infiltrate cutaneous tissues as leukemia cutis [6–8]. We confirmed that both the skin rash and ileal tissues were infiltrated with monocytic leukemic cells in the case presented here. It remains unknown however how these findings explain the development of BD or BD-like illness in a case of AMoL. In a classic autoimmune case of BD cytokine-producing dysfunctional T cells play a major role [19]. In our case, infiltrating monocytic leukemic cells or T cells responding to monocytic leukemic cells or both might have played a similar role by producing various cytokines. As another interesting issue, a literature survey indicates a correlation of BD or BD-like illness and MDS/CMML with the presence of chromosomal trisomy 8 [2–4, 15, 16]. The present case, in contrast, had no trisomy 8. In summary, although rare, caution must be exercised if BD or BD-like illness is associated with any hematological diseases, such as MDS/CMML, or rarely AMoL. We presented here the unique clinical course of an elderly patient whose disease initiated with the clinical features mimicking BD and was followed by the diagnosis of AMoL (FAB M5b) with normal karyotype. Acknowledgments The authors thank Dr. Taro Sakamaki, Department of Hematology and Oncology, Graduate School of Medicine, Kyoto University, for his helpful discussion and advice on this case. Competing Interests The authors declare no competing interests. Figure 1 Clinical course of the patient: the patient first developed aphthous stomatitis (inserted photo), followed by intestinal BD-like lesions detected by CF and then skin rash. Significant monocytosis triggered by urinary tract infection was noted at the 5th week of admission and the eventual diagnosis of AMoL was made. WBC: white cell counts, AMoC: absolute monocyte counts, ADL: adalimumab, CT: computerized tomography, CF: colonofiberscopy, GIF = gastrointestinal fiberscopy. Figure 2 Intestinal findings. Abdominal CT scan showed localized thickening of the intestinal wall (arrows) (a). Endoscopic study revealed multiple ovoid punched-out ulcers at the terminal ileum (b). HE staining of a biopsy of the terminal ileum showed the presence of ulcer-associated granulation tissues with vascularization and infiltration of cells (original magnification ×100) (c), which were strongly positive for lysozyme (d) (original magnification ×100). Positive stains for CD13, CD14, and CD33 are not shown. Figure 3 Findings of cutaneous lesions: photo of the rash on the right thigh (a). The biopsy shows the dense perivascular and periadnexal infiltration of mononuclear cells in the dermis extending into the subcutaneous tissue (b) (HE staining, original magnification ×100). The mononuclear cells were strongly lysozyme-positive (c) (original magnification ×100). Positive stains for CD13, CD14, and CD33 are not shown. Figure 4 May-Grünwald-Giemsa stained smears of peripheral blood and bone marrow show mature monocytes and promonocytoid cells with folded nuclei in the peripheral blood (a) and immature blast and promonocytoid cells in the bone marrow (b) (original magnification ×1,000). ==== Refs 1 Castro M. Conn D. L. Su W. P. D. Garton J. P. Rheumatic manifestations in myelodysplastic syndromes The Journal of Rheumatology 1991 18 5 721 727 2-s2.0-0025784748 1865418 2 Lin Y.-C. Liang T.-H. Chang H.-N. Lin J.-S. Lin H.-Y. Behçet disease associated with myelodysplastic syndrome Journal of Clinical Rheumatology 2008 14 3 169 174 10.1097/RHU.0b013e3181776bde 2-s2.0-48249103136 18525438 3 Mantzourani M. G. Chantziara K. Thanopoulou I. Variami H. Vaiopoulos G. Pangalis G. A. Coexistence of Behcet's disease and chronic myelomonocyte leukemia with trisomy 8: a case report and review of the literature Clinical and Experimental Rheumatology 2009 27 2 S85 S87 2-s2.0-70350156457 19796540 4 Muñoz-Grajales C. 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Cutaneous manifestations in CMML: indication of disease acceleration or transformation to AML and review of the literature Leukemia Research 2012 36 1 72 80 10.1016/j.leukres.2011.05.003 2-s2.0-83555173389 21782240 9 Kurokawa M. S. Suzuki N. Behcet's disease Clinical and Experimental Medicine 2004 4 1 10 20 10.1007/s10238-004-0033-4 2-s2.0-4644352596 15598081 10 Bennett J. M. Catovsky D. Daniel M. T. Proposed revised criteria for the classification of acute myeloid leukemia. A report of the French-American-British Cooperative Group Annals of Internal Medicine 1985 103 4 620 625 10.7326/0003-4819-103-4-620 2-s2.0-0022135739 3862359 11 Sakly K. Lahmar R. Nefzi F. Phenotypic abnormalities of peripheral blood mononuclear cells in patients with Behçet's disease and association with HLA-B51 expression Immunological Investigations 2014 43 5 463 478 10.3109/08820139.2014.886260 2-s2.0-84901593880 24661088 12 Maldini C. Lavalley M. P. Cheminant M. de Menthon M. Mahr A. Relationships of HLA-B51 or B5 genotype with Behçet's disease clinical characteristics: systematic review and meta-analyses of observational studies Rheumatology 2012 51 5 887 900 ker428 10.1093/rheumatology/ker428 2-s2.0-84860231111 22240504 13 Kimura M. Tsuji Y. Iwai M. Usefulness of adalimumab for treating a case of intestinal Behçet's disease with trisomy 8 myelodysplastic syndrome Intestinal Research 2015 13 2 166 169 25932002 14 Tada Y. Koarada S. Haruta Y. Mitamura M. Ohta A. Nagasawa K. The association of Behçet's disease with myelodysplastic syndrome in Japan: a review of the literature Clinical and Experimental Rheumatology 2006 24 5, supplement 42 S115 S119 2-s2.0-33750733946 17067441 15 Ogawa H. Kuroda T. Inada M. Intestinal Behçet's disease associated with myelodysplastic syndrome with chromosomal trisomy 8—a report of two cases and a review of the literature Hepato-Gastroenterology 2001 48 38 416 420 2-s2.0-0035037182 11379321 16 Eder L. Rozenbaum M. Boulman N. Behçet's disease, myelodysplastic syndrome, trisomy 8, gastroenterological involvement—an association Clinical and Experimental Rheumatology 2005 23 4, supplement 38 S91 S95 2-s2.0-33644803393 16273773 17 Braun T. Fenaux P. Myelodysplastic Syndromes (MDS) and autoimmune disorders (AD): cause or consequence? Best Practice and Research: Clinical Haematology 2013 26 4 327 336 10.1016/j.beha.2013.09.0033 2-s2.0-84893811075 24507810 18 Yamana S. Jones S. L. Shimamoto T. Immunohistological analysis of lymphocytes infiltrating the terminal ileum in a patient with intestinal Behçet's disease Ryumachi 1986 26 1 10 14 2-s2.0-0022665806 3487125 19 Sugi-Ikai N. Nakazawa M. Nakamura S. Ohno S. Minami M. Increased frequencies of interleukin-2- and interferon-γ -producing T cells in patients with active Behcet's disease Investigative Ophthalmology & Visual Science 1998 39 6 996 1004 2-s2.0-0031965818 9579479

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==== Front Stem Cells IntStem Cells IntSCIStem Cells International1687-966X1687-9678Hindawi Publishing Corporation 10.1155/2016/8414715Research ArticleComparison of Osteogenesis between Adipose-Derived Mesenchymal Stem Cells and Their Sheets on Poly-ε-Caprolactone/β-Tricalcium Phosphate Composite Scaffolds in Canine Bone Defects Kim Yongsun 1 Lee Seung Hoon 1 Kang Byung-jae 2 Kim Wan Hee 1 Yun Hui-suk 3 http://orcid.org/0000-0003-2670-7322Kweon Oh-kyeong 1 * 1BK21 PLUS Program for Creative Veterinary Science Research, Research Institute for Veterinary Science and College of Veterinary Medicine, Seoul National University, Seoul 08826, Republic of Korea2College of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University, Chuncheon 24341, Republic of Korea3Powder & Ceramics Division, Korea Institute of Materials Science, Changwon 51508, Republic of Korea*Oh-kyeong Kweon: ohkweon@snu.ac.krAcademic Editor: Marco Tatullo 2016 16 8 2016 2016 841471516 5 2016 1 7 2016 5 7 2016 Copyright © 2016 Yongsun Kim et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Multipotent mesenchymal stem cells (MSCs) and MSC sheets have effective potentials of bone regeneration. Composite polymer/ceramic scaffolds such as poly-ε-caprolactone (PCL)/β-tricalcium phosphate (β-TCP) are widely used to repair large bone defects. The present study investigated the in vitro osteogenic potential of canine adipose-derived MSCs (Ad-MSCs) and Ad-MSC sheets. Composite PCL/β-TCP scaffolds seeded with Ad-MSCs or wrapped with osteogenic Ad-MSC sheets (OCS) were also fabricated and their osteogenic potential was assessed following transplantation into critical-sized bone defects in dogs. The alkaline phosphatase (ALP) activity of osteogenic Ad-MSCs (O-MSCs) and OCS was significantly higher than that of undifferentiated Ad-MSCs (U-MSCs). The ALP, runt-related transcription factor 2, osteopontin, and bone morphogenetic protein 7 mRNA levels were upregulated in O-MSCs and OCS as compared to U-MSCs. In a segmental bone defect, the amount of newly formed bone was greater in PCL/β-TCP/OCS and PCL/β-TCP/O-MSCs/OCS than in the other groups. The OCS exhibit strong osteogenic capacity, and OCS combined with a PCL/β-TCP composite scaffold stimulated new bone formation in a critical-sized bone defect. These results suggest that the PCL/β-TCP/OCS composite has potential clinical applications in bone regeneration and can be used as an alternative treatment modality in bone tissue engineering. ==== Body 1. Introduction Synthetic bone substitutes such as collagen, hydroxyapatite (HA), β-tricalcium phosphate (β-TCP), and synthetic polymers are currently available for bone tissue regeneration. Ceramic scaffolds that consist of HA and β-TCP have been widely used to repair bone defects in clinical applications, since they have good biocompatibility and a microstructure similar to the mineral component of natural bone [1, 2]. Poly-ε-caprolactone (PCL), a type of polymer-based composite, has also been used for bone tissue engineering owing to its biodegradability, biocompatibility, and low inflammatory response [3, 4]. Some recent studies have examined the feasibility of using composite polymer/ceramic scaffolds such as PCL/β-TCP so as to combine the advantages of each material [4–6]. Cell-based tissue engineering is a promising alternative approach to bone regeneration. In particular, mesenchymal stem cells (MSCs) show great potential for therapeutic use in bone tissue engineering due to their capacity for osteogenic differentiation and regeneration [7]. However, transplanted single-cell suspensions do not attach, survive, or proliferate on target tissues [8]. To overcome this limitation, cell sheet technology has been developed to enhance the regenerative capacity of tissue-engineered products [9, 10]. Cell sheets are beneficial for cell transplantation because they preserve cell-cell junctions as well as endogenous extracellular matrix (ECM), thereby ensuring homeostasis of the cellular microenvironment for the delivery of growth factors and cytokines that promote tissue repair over a prolonged period of time. We hypothesized that combining polymer and ceramic scaffolds and MSCs or MSC sheets could accelerate and enhance bone regeneration in large bone defects. In this study, canine adipose-derived MSC (Ad-MSC) sheets were generated by cell sheet technology, and the osteogenic potential of Ad-MSCs and Ad-MSC sheets was investigated in vitro. In addition, composite PCL/β-TCP scaffolds seeded with Ad-MSCs or wrapped with osteogenic cell sheets were constructed and assessed for their osteogenic potential after transplantation into critical-sized bone defects in dogs. 2. Materials and Methods 2.1. Isolation and Culture of Canine Ad-MSCs The study protocol was approved by the Institutional Animal Care and Use Committee of Seoul National University (SNU-140801-1). MSCs derived from canine hip adipose tissue were isolated and characterized [11]. The tissue was collected aseptically from the subcutaneous fat of a 2-year-old beagle dog under anesthesia, washed with Dulbecco's phosphate-buffered saline (DPBS; Thermo Fisher Scientific Inc., USA), minced, and then digested with collagenase type I (1 mg/mL; Sigma-Aldrich) at 37°C for 30–60 min with intermittent shaking. The suspension was filtered through a 100 μm nylon mesh and centrifuged to separate floating adipocytes from stromal cells. Preadipocytes in the stromal vascular fraction were plated at 8,000–10,000 cells/cm2 in T175 culture flasks containing Dulbecco's modified Eagle's medium (Thermo Fisher Scientific Inc., USA) supplemented with 3.7 g/L sodium bicarbonate, 1% penicillin and streptomycin, 1.7 mM l-glutamine, and 10% fetal bovine serum (Thermo Fisher Scientific Inc., USA). Cells were incubated in a humidified atmosphere at 37°C and 5% CO2. Unattached cells and residual nonadherent red blood cells were removed after 24 h by washing with PBS, and the culture medium was replaced every 2 days. Cells were used for experiments after the third passage. 2.2. Preparation of Osteogenic Cell Sheet (OCS) and Ad-MSC Cultures OCS was prepared as previously described [9]. Briefly, Ad-MSCs were seeded at a density of 1 × 104 cells/cm2 in a 100 mm culture dish and cultured in growth medium containing 0.1 μM dexamethasone (Sigma-Aldrich, USA) and 82 μg/mL l-ascorbic acid 2-phosphate (A2-P, Sigma-Aldrich, USA) for 10 days. As a positive control for Ad-MSCs induced to undergo osteogenic differentiation (O-MSCs), cells were seeded at the same density and cultured in growth medium containing 0.1 μM dexamethasone, 15 μg/mL A2-P, and 10 mM β-glycerophosphate (Sigma-Aldrich, USA) [12, 13]. Undifferentiated Ad-MSCs (U-MSCs, negative control) were cultured in unsupplemented growth medium for 10 days. Morphological changes in cells during culture were monitored under an inverted light microscope (Olympus Corp., Japan). The OCS was fixed in 4% paraformaldehyde, embedded in paraffin, sectioned at a thickness of 4 μm, and stained with hematoxylin and eosin (H&E). 2.3. Alkaline Phosphatase (ALP) Activity Measurement Cells cultured in 100 mm dishes were used for measurement of ALP activity using an ALP assay kit (Takara Bio Inc., Japan) according to the manufacturer's instructions. Briefly, p-nitrophenyl phosphate (pNPP) solution was prepared by dissolving 24 mg pNPP substrate in 5 mL ALP buffer. Cells were scraped into 200 μL extraction solution, homogenized, and sonicated. The cleared supernatant was collected after centrifugation at 13,000 ×g and 4°C for 10 min. A 50 μL volume of cell lysate supernatant was mixed with 50 μL pNPP substrate solution and incubated at 37°C for 30 min. After adding 50 μL stop solution (0.5 N NaOH), absorbance was measured at 405 nm with a spectrophotometer. 2.4. Quantification of Mineralization Alizarin Red S (ARS) staining was used to detect calcium mineralization. Cells cultured in 100 mm dishes for 10 days were washed twice with DPBS and fixed with 4% paraformaldehyde (Wako, Japan) at room temperature for 10 min. Cells were then washed three times with distilled water, and 3 mL of 40 mM ARS (Sigma-Aldrich, USA, pH 4.1–4.3) was added to each dish, followed by incubation at room temperature for 20 min with gentle shaking. Excess dye was removed by aspiration and cells were washed three times with distilled water. For quantification of staining, the ARS was solubilized in 2 mL cetylpyridinium chloride (Sigma-Aldrich, USA) for 1 h [14], and the absorbance at 570 nm was measured with a spectrophotometer. 2.5. Gene Expression Analysis Total RNA was isolated from cells using the Hybrid-RTM RNA extraction kit (GeneAll Bio, Korea) according to the manufacturer's protocol. RNA concentration was determined by measuring optical density at 260 nm with a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, USA). cDNA was synthesized from RNA using a commercially available cDNA synthesis kit (Takara Bio, Japan). Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was carried out on an ABI 7300 Real-Time PCR system (Applied Biosystems, USA) and SYBR Premix Ex Taq (Takara Bio, Japan). Primer sequences are listed in Table 1. Expression levels of target genes were normalized to the level of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and quantitated with the ΔΔCt method [15]. 2.6. Fabrication of PCL/β-TCP Scaffolds PCL was dissolved in chloroform at 40°C. NaCl and β-TCP were ground and sieved, and granules between 25 and 33 μm were selected. β-TCP was prepared by calcination of nano-TCP (Merck, USA) at 1,000°C for 4 h. Selected NaCl granules were mixed with predetermined amounts of ceramic particles (1 : 1 = NaCl : PCL, 1.5 : 1 = ceramic : PCL, weight ratios). Combined powders were mixed with the PCL suspension to produce a homogeneous paste. Sheet-type porous scaffolds (50 × 25 mm, five layers) were constructed by extruding the gel paste onto a substrate using a three-dimensional (3D) printing system (Figure 1). The shapes and sizes of the PCL/β-TCP scaffold were designed using a computer system. NaCl was removed by immersing the scaffold in deionized water to produce macrosized pores in strut and the water was replaced every 2 h with fresh water at 30°C after sufficient drying of the scaffold. 2.7. Preparation of Scaffold with Ad-MSCs and Cell Sheet Scaffolds were immersed in DPBS for 24 h. Ad-MSCs (~1 × 106) were seeded on the scaffolds in a 100 mm dish for the PCL/β-TCP/U-MSCs group. After 24 h of incubation, the medium was replaced with osteoinductive medium for the PCL/β-TCP/O-MSCs group. The culture was maintained for 10 days at 37°C and 5% CO2, and the medium was changed every 48 h. For the PCL/β-TCP/OCS group, the scaffold was wrapped with four OCS after 10 days of culture. Cell-free scaffolds cultured in growth medium under the same conditions were used as controls. 2.8. Animal Experiments Beagle dogs (n = 20, 2-3-year-old) weighing 8.7 ± 1.4 kg were used in the study. Dogs were handled in accordance with the animal care guidelines of the Institute of Laboratory Animal Resources, Seoul National University, Korea. The dogs were assigned to one of five groups (n = 4 in each): PCL/β-TCP (control), PCL/β-TCP/U-MSCs, PCL/β-TCP/O-MSCs, PCL/β-TCP/OCS, and PCL/β-TCP/O-MSCs/OCS. The Institutional Animal Care and Use Committee of Seoul National University approved the experimental design. Dogs were medicated and anesthetized with tramadol (4 mg/kg by intravenous (i.v.) injection; Toranzin; Samsung Pharmaceutical Co., Korea), propofol (6 mg/kg i.v.; Provive; Claris Lifesciences, Indonesia), and atropine sulfate (0.05 mg/kg by subcutaneous injection; Jeil Pharmaceutical Co., Korea). Anesthesia was maintained with isoflurane (Forane solution, Choongwae Pharmaceutical Co., Korea) at 1.5 minimum alveolar concentration throughout the procedure. Electrocardiography, pulse oximetry, respiratory gas analysis, and rectal temperature measurement were carried out using an anesthetic monitoring system (Datex-Ohmeda S/5; GE Healthcare, UK). Under sterile conditions, a craniomedial incision was made to the skin to expose the diaphysis of the left radius. To create a critical-sized segmental defect in the radial diaphysis, a 15 mm long segmental defect was made to the middle portion of the diaphysis using an oscillating saw (Stryker, USA) as previously described [16, 17]. Overlying periosteum was also resected from the defect area. Defects were surrounded by the experimental scaffold. A nine-hole, 2.7 mm dynamic compression plate (DePuy Synthes, Switzerland) was placed on the cranial aspect of the radius. The soft tissue was closed with 3-0 polydioxanone sutures (Ethicon, USA), and the skin was closed with 4-0 nylon sutures. All the animals were bandaged for 2 days after operation. 2.9. Microcomputed Tomography (CT) Bone Imaging Dogs were sacrificed 12 weeks after implantation. The radius segment was excised, trimmed, and fixed in 10% formaldehyde. Samples were scanned using a micro-CT system (Skyscan; Bruker Corp., Belgium) and 3D images were reconstructed; the volume of newly formed bone within bone defects was calculated using the auxiliary software (Bruker Corp., Belgium). 2.10. Histological Analysis After micro-CT measurement, specimens were decalcified in 10% ethylenediaminetetraacetic acid for 4 weeks at room temperature and then dehydrated through a graded series of alcohol, embedded in paraffin, sectioned at a thickness of 5 or 8 μm, and stained with H&E or Masson's trichrome according to standard protocols. 2.11. Statistical Analysis Results are expressed as mean ± standard deviation. Statistical analysis was performed using SPSS v.21.0 software (IBM Corp., USA). Group means were compared with the Kruskal-Wallis tests followed by Mann-Whitney U tests. A P value of less than 0.05 was considered statistically significant. 3. Results 3.1. Cell Sheet Formation and Osteogenic Differentiation U-MSCs and O-MSCs cultured for 10 days exhibited a spindle-shaped, fibroblast-like morphology with clearly delineated cell margins (Figures 2(a)(A) and 2(a)(B)). However, OCS appeared to overlap and were stacked on top of one another, with indistinguishable cell-cell boundaries (Figure 2(a)(C)). The OCS was composed of two to four layers of cells surrounded by ECM (Figure 2(b)), and it was easily detached by cell scraper (Figure 2(c)). ALP activity was higher in the O-MSCs and OCS than in the U-MSCs group (P < 0.05; Figure 3). After staining with ARS, calcium-rich granules were clearly visible in the O-MSCs group (Figure 4(a)(B)), whereas no nodules were observed in the U-MSCs and OCS groups (Figures 4(a)(A) and 4(a)(C)). The degree of ARS staining was also greater in the O-MSCs group (Figure 4(b)). 3.2. Expression of Osteogenic Differentiation Markers in Ad-MSCs and Matrix Cell Sheets The expression of runt-related transcription factor 2 (RUNX2), ALP, osteopontin, bone morphogenetic protein 7 (BMP7), and transforming growth factor beta (TGF-β) mRNA was significantly upregulated in O-MSCs and OCS compared to the U-MSCs control (P < 0.05; Figure 5). RUNX2 and TGF-β transcript levels were higher in OCS than in the O-MSCs group (P < 0.05). The involvement of the Wnt/β-catenin signaling pathway was investigated by evaluating axis inhibition protein 2 (AXIN2) and β-catenin expression. Both transcripts were upregulated in O-MSCs and OCS relative to U-MSCs (P < 0.05). The mRNA level of vascular endothelial growth factor (VEGF) tends to be downregulated in O-MSCs and OCS as compared to the U-MSCs group. 3.3. In Vivo Bone Regeneration in Canine Radial Defects New bone was detected within defects at the bone margin. In the 3D reconstructed image, the cone-shaped newly formed bone was visible (Figure 6(a)). From the sagittal view, the bone volume was discernible (Figure 6(b)), and a quantitative 3D micro-CT analysis revealed the following values for newly formed bone mass: PCL/β-TCP, 1.89 ± 1.27 cm3; PCL/β-TCP/U-MSC, 8.10 ± 1.46 cm3; PCL/β-TCP/O-MSC, 16.81 ± 3.15 cm3; PCL/β-TCP/OCS, 26.53 ± 6.02 cm3; and PCL/β-TCP/O-MSC/OCS, 28.11 ± 5.5 cm3 (Figure 6(c)). The amount of new bone formed was greater in all experimental groups than in the PCL/β-TCP group (P < 0.05). Moreover, groups with cell sheets (with or without O-MSCs) showed a greater volume of newly formed bone than the other groups (P < 0.05). 3.4. Histological Evaluation At 12 weeks after implantation, decalcified paraffin sections were stained with H&E and Masson's trichrome to identify regenerated bone in defect areas. In all experimental groups, new bone was observed in longitudinal sections throughout the segmental defect and there was no obvious inflammation. Most of the defect areas were filled with fibrous connective tissue and newly formed bone tissue had a woven, trabecular appearance (Figure 7(a)). Masson's trichrome staining revealed abundant collagenous tissue around the regenerated tissue (Figure 7(b)(A)). In addition, vasculatures were observed inside and around the new bone (Figure 7(b)(B)). 4. Discussion The present study investigated the osteogenic potential of Ad-MSCs and Ad-MSC sheets, as well as that of composite PCL/β-TCP scaffolds seeded with Ad-MSCs or wrapped with OCS after their transplantation into critical-sized bone defects in dogs. MSCs have been reported to promote fracture repair; however, injection of single-cell suspensions leads to uneven distribution and weak adhesion of cells, which may ultimately result in cell death [8]. Additionally, the transplantation of isolated cells is impractical for bone regeneration in large-sized defects, which would require an adequate supply of cells. This is provided by cell sheets, which have intact cell-cell junctions and ECM that confer mechanical support and thereby maintain the integrity of the transplant [18]. In this study, we create a cell sheet using A2-P; the OCS had multiple layers of proliferating cells with ECM formation. A2-P is a stable form of ascorbic acid that plays a role in collagen biosynthesis and ECM deposition [19]. The OCS was readily detached from the culture dish using a scraper rather than a proteolytic agent such as trypsin, which preserved critical cell surface proteins such as ion channels, growth factor receptors, and cell-to-cell junction proteins. MSCs are capable of producing multiple mesenchymal cell lineages under specific culture conditions [7, 12]. Differentiation into the osteoblastic lineage is induced by culturing in osteoinductive medium containing dexamethasone, vitamin C, and β-glycerophosphate. In this study, the O-MSCs and OCS showed strong osteogenic potential, as evidenced by upregulation of the osteogenic differentiation markers such as RUNX2, ALP, and osteopontin as well as the increase in ALP activity relative to undifferentiated Ad-MSCs. These osteogenic effects of O-MSCs and OCS correspond well with those previously reported [20, 21]. In our in vivo study, the PCL/β-TCP/O-MSC group showed more extensive bone regeneration than the PCL/β-TCP/U-MSC group, likely due to the higher osteogenic potential of O-MSCs relative to U-MSCs. Moreover, there was more newly formed bone in the PCL/β-TCP/OCS and PCL/β-TCP/O-MSC/OCS groups than in those without OCS. The enhanced bone formation might be due to the delivery of osteogenic cells and ECM to the defect sites by MSC sheets. As for the role of MSCs in bone tissue engineering, besides osteogenic differentiation, MSCs are thought to exert therapeutic effects via secretion of trophic factors that provide a supportive microenvironment for cell survival, renewal, and differentiation [22]. It has been suggested that wrapped cell sheets function as a tissue-engineered periosteum at bone defect sites. A biomimetic periosteum can maintain homeostasis of the cellular microenvironment by delivering growth factors. A previous study showed that paracrine factors of MSCs play a positive role in bone repair [23, 24]. During bone healing, the proliferation and osteoblastic differentiation of endogenous or exogenous MSCs are influenced by various growth factors, among which TGF-β and BMPs play a major role. Both are members of the TGF-β superfamily, a group of dimeric proteins, acting as growth and differentiation factors. The BMP/TGF-β signaling induces MSCs differentiation into osteoblast via activation of intracellular pathways such as SMAD and mitogen-activated protein kinase signaling [25, 26]. Wnt signaling is also crucial in bone regeneration. Wnt/β-catenin signaling pathway promotes osteoblastogenesis, activation of osteoblast activity, inhibition of osteoclast activity, and increase in bone mass [1, 27]. In the present study, OCS showed higher expression of RUNX2, BMP7, TGF-β, AXIN2, and β-catenin, suggesting that the induction of bone regeneration by OCS occurs via activation of the BMP/TGF-β and Wnt signal pathways. Osteogenesis requires a well-developed vascular supply. It has been proposed that MSCs and cell sheets stimulate bone formation by inducing vascularization [7, 9, 21]. Neovascularization helps to overcome the hypoxic environment and facilitate bone formation. VEGF promotes angiogenesis and indirectly stimulates bone formation by inducing the ingress of osteoprogenitor cells. In the present study, U-MSCs, O-MSCs, and OCS expressed VEGF, which corresponded to the formation of a vascular network around newly formed bone tissue following transplantation of scaffolds into bone defects. This neovascularization may also have positive effects on the bone tissue regeneration. In this study, we used a PCL/β-TCP composite as a scaffold for bone regeneration. PCL is a biodegradable polymer with a porous 3D structure [28]. This scaffold has approximately 500 µm sized pores and 70% of porosity; thus, it has large surface area. Ceramic powders such as β-TCP, which is an inorganic component of bone, may enhance the mechanical properties of the PCL scaffolds. Recent studies have shown that β-TCP has good osteoconductivity and biocompatibility and promotes MSCs adherence, survival, and osteogenic differentiation [29, 30]. Thus, in large bone defects, the PCL/β-TCP composite may provide structural and mechanical support and enhance interactions between scaffold and cells or cell sheets in a manner that is conducive to bone regeneration. 5. Conclusion Our results demonstrate that osteogenic Ad-MSC sheets have strong osteogenic potential. Moreover, OCS combined with a PCL/β-TCP composite scaffold stimulated new bone formation to repair critical-sized bone defects in dogs. Ad-MSC sheets not only deliver osteogenic cells along with ECM, but also secrete trophic factors at defect sites for the bone regeneration. Our findings indicate that the PCL/β-TCP/OCS composite has a therapeutic potential for the treatment of bone defects and could be used to enhance current treatment practices. Acknowledgments This work was supported by the National Research Foundation of Korea (NRF-2013R1A1A2004506, 2011-0017572). Competing Interests The authors state that there are no competing interests. Figure 1 Photograph of a fabricated composite PCL/β-TCP scaffold. Sheet-type porous scaffolds (50 × 25 mm, five layers) were constructed by extruding the gel paste onto a substrate using a three-dimensional printing system. Figure 2 Morphological characteristics of the adipose-derived mesenchymal stem cells (Ad-MSCs) and Ad-MSC sheets. (a) (A) undifferentiated Ad-MSCs, (B) osteogenic Ad-MSCs, and (C) osteogenic Ad-MSC sheets observed under a phase contrast microscope. (b) OCS was composed of multiple layers of cells surrounded by ECM. (c) OCS was easily detached by cell scraper. Scale bars = 25 μm. Figure 3 Quantification of alkaline phosphatase (ALP) activity. ALP activity was significantly higher in the O-MSCs and OCS than in the U-MSCs group (∗ P < 0.05). Figure 4 Alizarin Red S (ARS) staining. (a) (A) U-MSCs, (B) O-MSCs, and (C) OCS were stained using ARS solution. Calcium-rich granules were clearly visible in the O-MSCs group. (b) The degree of mineralization was greater in the O-MSCs group (∗ P < 0.05). Figure 5 Expression of osteogenic differentiation markers. The expression of RUNX2, ALP, osteopontin, BMP7, and TGF-β mRNA was significantly upregulated in O-MSCs and OCS (∗ P < 0.05). RUNX2 and TGF-β transcript levels were higher in OCS than in the O-MSCs group (# P < 0.05). AXIN2 and β-catenin mRNA expression was upregulated in O-MSCs and OCS (∗ P < 0.05). ∗: compared to the U-MSCs group, #: compared to the O-MSCs group. Figure 6 Bone regeneration in canine radial defects. (a) 3D reconstructed image and (b) sagittal view image showed that new bone formation was detected within defects at the bone margin. (c) Quantitative 3D micro-CT analysis revealed that groups with cell sheets (with or without O-MSCs) showed a greater volume of newly formed bone than the other groups (∗, #, $ P < 0.05). ∗: compared to the PCL/β-TCP group, #: compared to the PCL/β-TCP/U-MSCs group, and $: compared to the PCL/β-TCP/O-MSCs group. Figure 7 Histological analysis. (a) In hematoxylin and eosin staining, most of the defect areas were filled with fibrous connective tissue, and newly formed bone tissue had a woven, trabecular appearance. (b) Masson's trichrome staining revealed abundant collagenous tissue around the regenerated tissue. Vasculatures were observed inside and around the new bone. Asterisks and arrows indicate bone tissue and vasculatures, respectively. Scale bars = ((a), (b)(A)) 200μm, ((b)(B)) 15μm. Table 1 Primers sequences used for quantitative reverse transcription PCR. Target gene   Primer sequence (5′-3′) RUNX2 Forward TGTCATGGCGGGTAACGAT Reverse TCCGGCCCACAAATCTCA ALP Forward TCCGAGATGGTGGAAATAGC Reverse GGGCCAGACCAAAGATAGAG Osteopontin Forward GATGATGGAGACGATGTGGATA Reverse TGGAATGTCAGTGGGAAAATC Osteocalcin Forward CTGGTCCAGCAGATGCAAAG Reverse GGTCAGCCAGCTCGTCACAGTT BMP7 Forward TCGTGGAGCATGACAAAGAG Reverse GCTCCCGAATGTAGTCCTTG AXIN Forward ACGGATTCAGGCAGATGAAC Reverse CTCAGTCTGTGCCTGGTCAA β-catenin Forward TACTGAGCCTGCCATCTGTG Reverse ACGCAGAGGTGCATGATTTG VEGF Forward CTATGGCAGGAGGAGAGCAC Reverse GCTGCAGGAAACTCATCTCC GAPDH Forward CATTGCCCTCAATGACCACT Reverse TCCTTGGAGGCCATGTAGAC ==== Refs 1 Guan J. Zhang J. Li H. Human urine derived stem cells in combination with β -TCP can be applied for bone regeneration PLoS ONE 2015 10 5 e0125253 10.1371/journal.pone.0125253 2-s2.0-84929353125 2 Kondo N. Ogose A. Tokunaga K. 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==== Front Case Rep MedCase Rep MedCRIMCase Reports in Medicine1687-96271687-9635Hindawi Publishing Corporation 10.1155/2016/5984671Case ReportEndobronchial Carcinoid Tumour with Extensive Ossification: An Unusual Case Presentation http://orcid.org/0000-0003-3227-1553Osmond Allison 1 * Filter Emily 2 Joseph Mariamma 1 Inculet Richard 3 Kwan Keith 1 McCormack David 4 1Department of Anatomic Pathology, Western University, London, ON, Canada N6A 5C12Department of Anatomic Pathology, Dalhousie University, Halifax, NS, Canada B3H 4R23Department of Thoracic Surgery, Western University, London, ON, Canada N6A 5C14Department of Medicine, Western University, London, ON, Canada N6A 5C1*Allison Osmond: aosmond@munmed.caAcademic Editor: Glenn Bubley 2016 16 8 2016 2016 59846711 3 2016 13 6 2016 19 7 2016 Copyright © 2016 Allison Osmond et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Carcinoid tumour is a well-known primary endobronchial lung neoplasm. Although calcifications may be seen in up to 30% of pulmonary carcinoid tumours, near complete ossification of these tumours is an unusual finding. Such lesions can prove diagnostically challenging at the time of intraoperative frozen section as the latter technique requires thin sectioning of the lesion for microscopic assessment. We present an unusual case of endobronchial carcinoid tumour with extensive ossification in a 45-year-old male. Preliminary intraoperative diagnosis was achieved through the alternative use of cytology scrape smears. The final diagnosis was confirmed after decalcification of the tumour. The prognostic implications of heavily ossified carcinoid tumours remain elusive. Long-term clinical follow-up of these patients is recommended. ==== Body 1. Case Presentation A 45-year-old male presented to the Emergency Department with two episodes of hemoptysis and progressive exertional wheezing over a 9-month period. The patient's past medical history was unremarkable apart from a previous 20 pack-year smoking history. He reported a single episode of hemoptysis 8 years priorly and was lost to follow-up after initial radiologic investigations identified a 3.1 cm mass. He denied any interim respiratory symptoms. On physical exam, the patient had normal vital signs and was in no apparent distress. His chest exam was normal and there were no stigmata of chronic lung disease. There was no palpable lymphadenopathy. Chest CT imaging revealed a calcified 4.2 cm hilar mass with associated right middle lobe collapse (Figure 1(a)). The radiologic differential diagnosis included granuloma, carcinoid tumour, or benign nodule. Bronchoscopy confirmed the presence of a highly vascular and obstructive endobronchial mass (Figure 1(b)). Fine needle aspiration (FNA) of the mass was indeterminate due to low cellularity, despite multiple aspiration attempts. Due to the bronchoscopic appearance, the tumor was presumed to be a carcinoid tumor and so a thoracic surgical opinion was sought for consideration of resection. A right bilobectomy was then undertaken with an intraoperative consultation for preliminary diagnosis and to determine the bronchial resection margin status. Intraoperative gross specimen assessment revealed a hard, well-circumscribed, ossified 5.0 cm mass (Figure 1(c)) encasing the bronchial resection margin. The firm consistency of the mass precluded conventional tissue sectioning for frozen section evaluation. Cytology scrape smears (Diff Quik, H&E stains) were then prepared from a fleshy endobronchial portion of the mass. The smears contained a uniform population of tumour cells disposed singly and in loosely cohesive groups and rosettes (Figure 2(a)). The H&E scrape smear preparation confirmed the presence of a stippled “salt and pepper” chromatin pattern, characteristic of low grade neuroendocrine tumours (Figure 2(b)). A shave section of the bronchial resection margin was negative for malignancy. The preliminary diagnosis at intraoperative consultation was favoured to be carcinoid tumour with the final diagnosis deferred to permanent sections. Microscopic examination of the formalin-fixed, decalcified mass revealed mature, anastomosing trabecular bone, with intervening nests of uniform tumour cells. The cells were occasionally arranged in trabecular structures and vague rosettes (Figures 2(c) and 2(d)). Despite a prolonged decalcification process, the tumour cells were strongly positive for chromogranin, synaptophysin, and cytokeratin AE1/AE3 immunohistochemistry markers. Necrosis and proliferative activity were absent (Ki-67 index < 1%). Two associated hilar lymph nodes were negative for metastasis. The final pathologic stage was pT2aN0MX. 2. Discussion The WHO classification recognizes 4 histologic types of pulmonary neuroendocrine tumours: typical carcinoids, atypical carcinoids, small cell carcinomas, and large cell neuroendocrine carcinomas [1]. The typical carcinoid is a well-known primary endobronchial lung neoplasm accounting for 80–90% of pulmonary carcinoid tumours [1]. Most pulmonary carcinoids are identified incidentally as centrally located, well-circumscribed masses with routine imaging modalities. Clinically, pulmonary carcinoids occur more frequently in males and typically manifest in the 5th decade of life [2]. In symptomatic patients, the most common symptoms include cough, hemoptysis, and a new-onset inspiratory wheeze [2]. Development of Cushing's syndrome secondary to ectopic ACTH production is uncommon [1]. At the time of bronchoscopy, pulmonary carcinoids can be accurately identified given their characteristic location and highly vascular appearance [2]. Nevertheless, cytologic and tissue diagnosis can be achieved by taking samples under bronchoscopic visualization with appropriate hemostatic control. If an intraoperative consultation is requested for preliminary tissue diagnosis, pulmonary carcinoid tumours can be suspected based on their characteristic solid and yellow gross appearance [1]. Frozen section examination allows an accurate diagnosis of low grade neuroendocrine neoplasms. However, in our case, extensive calcification precluded routine frozen section examination and cytology scrape smears greatly assisted in determining both the preliminary diagnosis and patient treatment plan. As many as 30% of typical carcinoids may be accompanied by intralesional dystrophic calcifications [3] while complete ossification of these tumours is an unusual finding scarcely reported in the literature [3–6]. Ossification is more commonly associated with tumours of long duration [7], congruent with our case presentation. “Osteomimicry,” or the ability of tumour cells to upregulate osteogenic and osteoblastic gene expression (e.g., bone morphogenetic protein, osteocalcin) and thus acquire an osseous phenotype, is believed to play a role in ossification of pulmonary carcinoids [2]. Osteomimicry is well characterized in “bone prone” epithelial tumours (e.g., breast and prostate carcinomas) [8, 9]. This ability is believed to be advantageous as it augments epithelial-mesenchymal transition, permitting tumour cells to seed and survive in bony environments, similar to advanced breast and prostate carcinomas [9]. Moreover, a subset of patients with ossified pulmonary carcinoid tumours have presented with concomitant lymph node metastasis [3]. Whether or not osteomimicry in carcinoid tumors portends a more robust metastatic potential is unknown given the scarce number of cases reported in the literature. In our case, lymph node disease was absent at presentation and our patient remains free of metastatic disease 8 months postoperatively. In summary, although extensive ossification is an unusual presentation for pulmonary carcinoid tumours, the implication of this phenotype remains elusive. Long-term follow-up of these patients is required to better characterize this phenomenon in disease progression. Finally, this case highlights the utility of cytology scrape preparations in making a diagnosis at the time of intraoperative consultation when specimens may not be suitable for usual frozen section technique. Learning Objectives   Recognize the rare presentation of ossification in pulmonary carcinoids.   Realize the limits of intraoperative consultation in extensively ossified lung tumours. CanMEDS Competency Medical Expert is considered. Competing Interests The authors declare that they have no competing interests. Authors' Contributions Allison Osmond did the assessment at frozen section and wrote and revised the paper. Emily Filter did the preparation of intraoperative cytology smears and revised the paper. Mariamma Joseph did the initial cytology consultation and revised the paper. Keith Kwan did the pathological assessment of final resection specimen and revised the paper. Richard Inculet did the surgical resection and revised the paper. David McCormack did the initial consultation and bronchoscopy and revised the paper. Figure 1 (a) CT thorax, coronal slice demonstrating a radiopaque hilar mass; (b) the hypervascular mass, as seen under bronchoscopic exam, occluding the bronchus; (c) the right middle lobe resection specimen. The mass encases the bronchial resection margin. The fleshy, endobronchial portion (∗) was sampled at the time of frozen section. Figure 2 ((a) and (b)) Cytology scrape smears including Diff Quik, 20x (c) and H&E, 20x (inset 40x); (c) H&E section of calcified mass demonstrating mature lamellar bone and nests of tumor cells; (d) trabecular structures and vague rosettes were noted (40x); the tumor cells were diffusely positive for chromogranin positivity, synaptophysin, and cytokeratin AE1/3. ==== Refs 1 Travis W. D. Brambilla E. Burke A. P. Marx A. Nicholson A. G. WHO Classification of Tumors of the Lung, Pleura, Thymus and Heart 2015 4th ‎Geneva‎, Switzerland WHO 2 Rosado De Christenson M. L. Abbott G. F. Kirejczyk W. M. Galvin J. R. Travis W. D. Thoracic carcinoids: Radiologic-pathologic correlation Radiographics 1999 19 3 707 736 10.1148/radiographics.19.3.g99ma11707 2-s2.0-0033125055 10336200 3 Tsubochi H. Endo S. Oda Y. Dobashi Y. Carcinoid tumor of the lung with massive ossification: report of a case showing the evidence of osteomimicry and review of the literature International Journal of Clinical and Experimental Pathology 2013 6 5 957 961 2-s2.0-84882977150 23638230 4 Shin M. S. Berland L. L. Myers J. L. Clary G. Zorn G. L. CT demonstration of an ossifying bronchial carcinoid simulating broncholithiasis American Journal of Roentgenology 1989 153 1 51 52 10.2214/ajr.153.1.51 2-s2.0-0024365124 2500015 5 Yamagishi S. I. Suzuki T. Ohkuro H. Yagihashi S. Ossifying gastric carcinoid tumor containing bone morphogenetic protein, osteopontin and osteonectin Journal of Endocrinological Investigation 2004 27 9 870 873 10.1007/bf03346283 2-s2.0-14544297977 15648553 6 Cooney T. Sweeney E. C. Luke D. Pulmonary carcinoid tumours: a comparative regional study Journal of Clinical Pathology 1979 32 11 1100 1109 10.1136/jcp.32.11.1100 2-s2.0-0018601864 92479 7 Vanmaele L. Noppen M. Frecourt N. Impens N. Welch B. Schandevijl W. Atypical ossification in bronchial carcinoid European Respiratory Journal 1990 3 8 927 929 2-s2.0-0025636109 1963412 8 Chung L. W. K. Huang W.-C. Sung S.-Y. Stromal-epithelial interaction in prostate cancer progression Clinical Genitourinary Cancer 2006 5 2 162 170 10.3816/cgc.2006.n.034 2-s2.0-33847724140 17026806 9 Bendinelli P. Maroni P. Matteucci E. Luzzati A. Perrucchini G. Desiderio M. A. Microenvironmental stimuli affect Endothelin-1 signaling responsible for invasiveness and osteomimicry of bone metastasis from breast cancer Biochimica et Biophysica Acta (BBA)—Molecular Cell Research 2014 1843 4 815 826 10.1016/j.bbamcr.2013.12.015 2-s2.0-84893758552 24373848

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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/1691579Research ArticlePreparation and In Vivo Pharmacokinetics of the Tongshu Suppository http://orcid.org/0000-0003-3838-716XLiu Guoqiang 1 * Dong Leilei 1 Lu Kuan 2 Liu Sisi 1 Zheng Yingying 1 1Department of Pharmacy, The Third Hospital of Hebei Medical University, Shijiazhuang 050051, China2The Third Hospital of Hebei Medical University, Shijiazhuang 050051, China*Guoqiang Liu: liugq1223@sohu.comAcademic Editor: Sanjula Baboota 2016 16 8 2016 2016 169157928 4 2016 19 7 2016 Copyright © 2016 Guoqiang Liu et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Astragalus polysaccharide (APS) (used for intestinal protection) was added to formulate the Tongshu suppository to improve the pharmacokinetics of Aceclofenac, which were assessed in New Zealand rabbits using an orthogonal experimental design. The single-agent Aceclofenac was taken as the control formulation. The concentration-time and drug release curves were drawn, and T max (min), C max (μg·mL−1), AUC0→∞, and MRT were compared using a pharmacokinetic systems program. The formulated Tongshu suppository had moderate hardness, a smooth surface with uniform color, and theoretical drug-loading rate of 8%. Its release rate was in accordance with the drug preparation requirements. The concentration-time curves and drug release curves revealed that the maximum concentrations (C max) were 4.18 ± 1.03 μg·mL−1 and 3.34 ± 0.41 μg·mL−1 for the Tongshu and Aceclofenac suppositories, respectively, showing statistically insignificant difference, while the peak times were 34.87 ± 4.69 min and 34.76 ± 6.34 min, respectively, also showing statistically insignificant difference. Compared with the Aceclofenac suppository, the relative bioavailability of the Tongshu suppository was 104.4%, and the difference between them was statistically insignificant. In this experiment, the Tongshu suppository was prepared using the hot-melt method. In vivo pharmacokinetic studies confirmed it had higher bioavailability than the Aceclofenac suppository. ==== Body 1. Background Aceclofenac, 2-[2-[2-[(2,6-dichlorophenyl)amino]phenyl]-acetyl] oxyacetic acid, is a prostaglandin synthetase (cyclooxygenase) inhibitor which inhibits lipoxygenase and decreases prostaglandin production, thereby inhibiting the inflammatory process. Aceclofenac has been shown to have potent anti-inflammatory, analgesic, and antipyretic properties [1], which is indicated for acute and chronic treatment of the signs and symptoms of rheumatoid arthritis, osteoarthritis, ankylosing spondylitis, and scapulohumeral periarthritis [2]. Long-term treatment of intact cells with Aceclofenac has recently been shown to cause suppression of COX-2-dependent prostaglandin synthesis [3]. The usual dose of Aceclofenac is 100 mg twice a day; it is absorbed rapidly in its intact form when taken orally, and its analgesic effects begin within 30 min of ingestion [4]. Water-insolubility and gastrointestinal discomfort are two side effects, which widely influence the clinical use of Aceclofenac [5]. In order to improve its effective oral delivery, aceclofenac was mixed with various ratios of different solubilizers prepared using polyethylene glycol 400 (PEG-400) as the basic soft capsule ingredient [6]. Astragalus polysaccharides (APS) may enhance intestinal epithelial cell proliferation, migration, and differentiation in vitro by stimulating ODC gene expression and activity, and putrescine production, independent of TGF-β. Exogenous administration of APS may provide a new approach for modulating intestinal epithelial wound restitution in vivo [7]. Astragalus polysaccharides promote the regeneration of damaged gastric mucosa, probably through their antioxidative mechanism [8]. In this study, the aceclofenac was mixed with various ratios of PEG 400 in order to develop an effective novel oral drug delivery system with accelerated absorption and reduced gastrointestinal discomfort, PEG-4000, glycerol and APS were used to make the Tongshu suppository, and their dissolution studies were performed. Furthermore, the pharmacokinetics of the Tongshu suppository and the aceclofenac suppository without APS were evaluated and compared in New Zealand rabbits. 2. Methods 2.1. Materials This study was approved ethically by the Third Hospital of Hebei Medical University. The chemicals and reagents for this study were obtained as follows: Aceclofenac reference substance (China Pharmaceutical Biological Products Analysis Institute, Beijing, China), Aceclofenac drug substance (Xi'an Haixin Pharmaceutical Co., Ltd.), Astragalus polysaccharide (Xi'an Qingteng Bioscience Limited, Xi'an China), polyethylene glycol 400 (PEG400, Tianjin Yongda Chemical Reagent Co., Ltd., Tianjin, China), polyethylene glycol 4000 (PEG4000, Tianjin Guangfu Fine Chemical Research Institute, Tianjin, China), glycerol (Baishi Chemical Industry Co., Ltd., Tianjin, China), acetonitrile (chromatographic pure, American Grace Co., Shanghai, China), analytical reagents including monopotassium phosphate, caustic soda, and glacial acetic acid, and sodium acetate agents (Modern Instruments Co.). 2.2. Preparation of the Aceclofenac-Loaded Suppository with APS (Tongshu) or without APS (Control) Aceclofenac was thoroughly blended with various solubilizers including PEG 400, PEG-4000, glycerol, and APS to formulate the Tongshu suppository. The control suppository was prepared with Aceclofenac thoroughly blended with PEG 400, PEG-4000, and glycerol without APS. These ingredients were rapidly transferred to a mold and frozen in the refrigerator for 30 min and then broken away from the mold after leveling. The detailed compositions of the Tongshu and control suppositories are given in Table 1. 2.3. Dissolution Test Each Tongshu and control suppository was placed in a dissolution tester. The dissolution test was performed at 36.5°C using the paddle method at 100 rpm with 750 mL of distilled water as the dissolution medium [9]. At the predetermined interval, 2 mL aliquots of the medium were sampled and filtered. The filtrate was analyzed using the UV-Vis variable wavelength detector (Philips, Model PU8730) at 273 nm. The differences in dissolution rates of the drug from various preparations were compared using one-way analysis of variance (ANOVA). The significance between the means of different formulations was then compared by the multiple range method of least significant difference. 2.4. Pharmacokinetic Study 2.4.1. Animals and Treatments This experiment was designed as a two-cycle crossover trial for two agents [10, 11], with a washing period of one week. Before the experiment, six New Zealand rabbits were randomized into two groups and were fasting for 12 h. The first group was then given one piece of the Tongshu suppository (containing 100 mg Aceclofenac) and the second group was given the Aceclofenac suppository (100 mg); the intact suppository was inserted about 1 cm into the rabbit anus, followed by compression for about 15 min to avoid excretion. After that, 1 mL of blood was drawn from the ear vein at 0.25, 0.5, 1, 1.5, 2, 2.5, 3, 4, 6, 8, and 10 h after administration and placed into 2 mL Eppendorf tubes which were pretreated with heparin and centrifuged at 3000 r/min for 10 min. The upper plasma layer was then collected and cryopreserved at −20°C for subsequent experiments. In the crossover trials in the second week, the Tongshu suppository group in the last week was changed to the Aceclofenac suppository group, while the Aceclofenac suppository group was changed to the Tongshu suppository group, using abovementioned steps. 2.4.2. Administration and Blood-Collection Processing the plasma samples, 0.5 mL blank plasma was accurately weighted and placed into a 2 mL EP tube. After that, 500 μL of acetonitrile was added, followed by vortex mixing for 3 min and centrifugation at 10000 r·min−1 for 10 min in a high speed centrifuge. Then the upper organic phase was collected into a 1 mL syringe and filtered with a 0.45 μm filtration membrane, from which 15 μL was used for LC analysis. 2.4.3. Calculation of Pharmacokinetic Parameters All pharmacokinetic parameters were determined by noncompartmental analysis. AUC was calculated using the linear trapezoidal method. C max (the highest drug concentration measured) and T max (the time to reach the highest concentration) were directly read from the concentration/time plots. The maximum concentrations (C max) were 4.18 ± 1.03 μg/mL and 3.34 ± 0.41 μg/mL for the Tongshu and suppositories, respectively, while the peak times were 34.87 ± 4.69 min and 34.76 ± 6.34 min, respectively. 2.5. Statistic Analysis The concentrations measured at various time points were fitted using 3p97 software. The mean values of plasma-drug concentrations at each sampling point were taken as the primary and reference data, to which each individual value was fitted. AIC was considered as a judged index to determine the compartmental model and weight for mandatory fitting of the other individual data using the principle of majority. This study aimed to establish a preparation method of self-made suppository and do preliminary research on in vivo pharmacokinetics. Due to rectal administration itself, it is not appropriate to use the existing data of the conventional tablets of oral administration as reference in the in vivo studies of suppository. This study aimed to establish a preparation method of self-made suppository and do preliminary research on in vivo pharmacokinetics. Due to rectal administration itself, it is not appropriate to use the existing data of the conventional tablets of oral administration as reference in the in vivo studies of suppository. In this study, the reference suppository is also self-made and the experimental conditions and mode of administration and so forth are also the same as the study suppository, so the conclusions are more comparable. 3. Results and Discussion 3.1. Analyses of the Drug Release Curves of the Tongshu Suppository The drug release curve shown in Figure 1 indicates that the Tongshu suppository is a quick release suppository. Upon introduction of the APS additive, the early dissolution speed of Aceclofenac decreased; however, its dissolution rate increased significantly with continuous release of APS into the phosphate buffer. 3.2. Analyses of the Concentration-Time Curves of the Tongshu Suppository As can be seen from the concentration-time curves of the Tongshu suppository, it was quickly absorbed into the blood, showed fast elimination, and did not exhibit significant differences in these parameters compared with the concentration-time curves of the Aceclofenac suppository. Also, the drug release parameters observed in vitro were similar for both suppositories. 3.3. Pharmacokinetic Analyses of the Tongshu Suppository Pharmacokinetic analyses were performed using 3p97 software, and the results revealed that the Tongshu suppository mainly presented as one compartment model, suggesting that it could be promptly absorbed into the blood through venae intestines after rectal administration. This observation was also confirmed by the data processing results, where the T max was 34.87 min in the Tongshu suppository group, which was longer than the peak time of gavage of the Aceclofenac suspension alone. And C max was 4.57 ± 1.09 μg·mL−1 in the Tongshu suppository group, which was longer than the peak time of gavage of the Aceclofenac suspension alone. The K el was 0.022875 ± 0.007 min−1, which was higher than the peak time of gavage of the Aceclofenac suspension alone. Otherwise, AUC0→∞ is 496.52 ± 2.4 μg·min·mL−1 in the Tongshu suppository group and MRTis 171.395 ± 3.08 min in the Tongshu suppository group, where both significantly decreased compared with that in control group (Table 2). Aceclofenac is a tendentious COX-2 inhibitor mainly used in symptomatic treatment of osteoarthritis, rheumatoid and juvenile rheumatoid arthritis, and ankylosing spondylitis. It is insoluble in water, easily soluble in acetone and dimethylformamide, and also soluble in methanol and ethanol. It is prone to causing side effects on the gastrointestinal tract after oral administration; in addition, it is also a COX inhibitor, which tends to aggravate its stimulating effects on the gastrointestinal tract. This study aimed to explore the ways of reducing the side effects of Aceclofenac and improving its safety and compliance by changing the route of its administration and adding adjuvant APS to the formulation. In drug release, the APS additive tended to decrease the early dissolution speed of Aceclofenac, but this effect was not statistically significant. This finding might be due to dispersion of Aceclofenac molecules in the polyethylene glycol matrix and their quick release into the medium during dissolution. APS is a water-soluble medium, with certain affinity for the polyethylene glycol matrix. However, it takes some time to achieve the dynamic balance between the dissolved medium and the matrix. With continuous release of APS into the phosphate buffer, the dissolution rate increased at certain times. Because APS and Aceclofenac are mixed and added to the matrix, Aceclofenac tends to achieve quick dissolution with the release of APS, resulting in a dissolution rate comparable to that of the Aceclofenac suppository. The mobile phase was screened during HPLC analysis of Aceclofenac. Methanol was selected as the organic phase in the early stage [12, 13]. However, unsatisfactory results were obtained since absorption occurred at 273 nm in the blank suppository. This might be due to the fact that the samples were not thoroughly cleaned by the washing solution (50% methanol) or that the instrument itself was not optimally cleaned. Furthermore, methanol itself has a high viscosity, leading to failure in achieving thorough rinsing even using the maximum aspiration speed of the needle washing machine. Therefore, acetonitrile was selected in our experiment [1, 12, 14] and the adjusted mobile phase consisted of acetonitrile-sodium acetate. Initially, the chosen ratio was 60 : 40, giving rise to a peak at about 5 min and nonideal separation. Then the ratio of the organic phase was decreased; that is, a 45 : 55 acetonitrile-sodium acetate ratio was used, which resulted in good separation. The accuracy, precision, and stability of this method were in accordance with the experimental requirements and no interference from adjuvant drugs was observed. In terms of blood sample management, acetonitrile was selected as the solvent for the albumin precipitant of the plasma samples. In order to ensure the accuracy of blood concentration monitoring, we did not adopt a redissolution method. Furthermore, this method had poor repeatability and yielded impure peaks. Therefore, the filtered samples were directly drawn after the deposition process, which was confirmed to be methodologically appropriate for investigation of the in vivo pharmacokinetics of this preparation [15, 16]. In terms of in vivo analyses, the concentration-time curve and bioavailability were not statistically significantly different between the Aceclofenac and Tongshu suppositories. Compared with the oral formulations of the same products, the Tongshu suppository was unlikely to cause stimulation of the gastrointestinal tract due to nonoral administration. Furthermore, the APS additive had a certain protective effect on intestinal mucosa. According to the literature, the Tongshu suppository showed significantly improved peak time and AUC0→∞ in comparison with domestic and foreign Aceclofenac oral formulations. In addition, it also showed improved bioavailability in comparison with the homemade Aceclofenac suppository tested in this experiment. However, Aceclofenac had a lower in vivo peak concentration and shorter MRT, presenting with quick elimination in vivo [17–19]. Due to small sample size, the data from this study showed a high degree of dispersion due to individualized differences among animals, leading to poor representation. Therefore, increasing the sample size of in vivo pharmacokinetic studies is necessary, in order to obtain more useful experimental data. This study points to several important advantages of the Tongshu suppository which warrant further investigation. First, the drug release, absorption, and bioavailability of the active ingredient from the Tongshu suppository were comparable to that observed for the Aceclofenac suppository as indicated in Figures 1 and 2. Second, the advantage of the Tongshu suppository according to the results of pharmacokinetic studies is that it is quickly absorbed into the blood due to rectal administration, as opposed to Aceclofenac oral formulations studied earlier [20]. The results from Table 2 indicate that T max of the Tongshu suppository was 2.31 min longer in comparison to the T max of the Aceclofenac suppository. Third, although the APS additive from the Tongshu suppository slightly decreased the early dissolution speed of Aceclofenac, it also offered protective effects on gastrointestinal mucosa. In conclusion, formulated Tongshu suppository is characterized by fast absorption and lack of stimulative effects on the digestive system. However, its antiarthritic effects and protective effects on intestinal mucosa require further investigation. Moreover, its metabolism and removal in vivo have not been studied yet and would make for an interesting topic of future studies. 4. Conclusions The formulation and preparation of Tongshu suppository were simple and feasible, with good reproducibility. The methods have established for the determination of content and dissolution. The concentration of plasma-drug concentration determination method was established, for the study of the preparation of quality guarantee. In vivo pharmacokinetic studies confirmed it had higher bioavailability than the Aceclofenac suppository. Competing Interests The authors declare that they have no actual or potential competing interests. Authors' Contributions Leilei Dong carried out the studies, participated in collecting data, and drafted the paper. Guoqiang Liu performed the statistical analysis and participated in its design. Kuan Lu, Sisi Liu, and Yingying Zheng helped to draft the paper. All authors read and approved the final paper. Figure 1 Drug release curves of the Tongshu and Aceclofenac suppositories. Figure 2 Concentration-time curves of the Tongshu and Aceclofenac suppositories. Table 1 Preparation of the Tongshu and Aceclofenac suppositories.   Tongshu Aceclofenac PEG400 0.49 0.48 PEG4000 0.49 0.48 Glycerol 0.12 0.14 APS 0.1 0 Aceclofenac suppository 0.1 0.1 Table 2 Pharmacokinetic analyses of Tongshu and Aceclofenac suppositories. The data are expressed as mean ± SD. Parameter Tongshu suppository Aceclofenac suppository Mean ± SD Mean ± SD T max (min) 32.6 ± 3.2 30.29 ± 2.5 C max (μg·mL−1) 4.57 ± 1.09 3.14 ± 0.5 K el (min−1) 0.022875 ± 0.007 0.01885 ± 0.009 K a (min−1) 0.0553 ± 0.02 0.0573 ± 0.01 AUC0→∞ (μg·min·mL−1) 496.52 ± 2.4 580.75 ± 234.5 MRT (min) 171.395 ± 3.08 345.12 ± 60.6 ==== Refs 1 Hinz B. Auge D. Rau T. Rietbrock S. Brune K. Werner U. Simultaneous determination of aceclofenac and three of its metabolites in human plasma by high-performance liquid chromatography Biomedical Chromatography 2003 17 4 268 275 10.1002/bmc.243 2-s2.0-0038048457 12833392 2 Legrand E. Aceclofenac in the management of inflammatory pain Expert Opinion on Pharmacotherapy 2004 5 6 1347 1357 10.1517/14656566.5.6.1347 2-s2.0-3042771814 15163279 3 Yamazaki R. Kawai S. Matsuzaki T. 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==== Front Evid Based Complement Alternat MedEvid Based Complement Alternat MedECAMEvidence-based Complementary and Alternative Medicine : eCAM1741-427X1741-4288Hindawi Publishing Corporation 10.1155/2016/9594251Research ArticleEvaluation of the Effects of Pinus koraiensis Needle Extracts on Serum Lipid and Oxidative Stress in Adults with Borderline Dyslipidemia: A Randomized, Double-Blind, and Placebo-Controlled Clinical Trial http://orcid.org/0000-0002-6063-9370Lee Hansongyi 1 2 Kim Hyerang 2 Choue Ryowon 1 2 http://orcid.org/0000-0001-7632-7315Lim Hyunjung 1 2 * 1Department of Medical Nutrition, Graduate School of East-West Medical Science, Kyung Hee University, Yongin 17104, Republic of Korea2Research Institute of Medical Nutrition, Kyung Hee University, Seoul 02447, Republic of Korea*Hyunjung Lim: hjlim@khu.ac.krAcademic Editor: Mariangela Rondanelli 2016 16 8 2016 2016 959425122 4 2016 15 6 2016 28 6 2016 Copyright © 2016 Hansongyi Lee et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Dyslipidemia has been well-known as a common metabolic disorder contributing to cardiovascular disease. The aim of this study was to evaluate the effect of the Pinus koraiensis needle extracts (PKE) on the blood cholesterol and oxidative stress. Method. We conducted a 12-week randomized, double-blinded controlled trial to examine the effect of PKE on blood lipid profiles in adults with borderline dyslipidemia. Thirty-three eligible persons were recruited and randomly assigned into PKE (n = 20) and placebo groups (n = 13). Serum lipids including total cholesterol, low-density lipoprotein- (LDL-) cholesterol, high-density lipoprotein- (HDL-) cholesterol, very low-density lipoprotein- (VLDL-) cholesterol, and triglyceride were measured before and after trial. Serum insulin, glucose, and antioxidant indicators were also analyzed before and after trial and anthropometry and blood pressure were measured every 4 weeks. Results. After 12 weeks, PKE statically significant decreases in systolic blood pressure (p < 0.05) and waist circumference (p < 0.05) were observed. Also, VLDL-cholesterol significantly decreased (from 24.4 ± 10.0 mg/dL at baseline to 18.4 ± 4.1 mg/dL after 12 weeks) (p < 0.05) and superoxide dismutase (SOD) increased (6.12 ± 0.41 U/mL to 9.06 ± 0.62 U/mL) (p < 0.01) in PKE group. However, after adjustment with WC, VLDL-cholesterol was not significant between groups (p = 0.095) and while SOD remained significant between groups (p = 0.013). Conclusion. The results show that PKE was effective in improving the superoxide dismutase in the individuals with borderline dyslipidemia. Rural Development AdministrationPJ009055 ==== Body 1. Introduction Cardiovascular disease (CVD) is one of the leading causes of death worldwide, estimating the incidence rate to above 17.3 million per year. The mortality rate from CVD has continuously increased from 2.3 persons in 1983 to 16.2 persons in 1998 and reached to 25.1 persons in 2012 per 10 million person in South Korea [1]. Dietary modification for prevention and management of chronic disease is not easy, and the natural complementary and alternative therapy as dietary supplements have been used. Pinus koraiensis, which is known as Korean pine nuts, has long been used in traditional diet in many of Asian countries, such as Korea, Manchuria, and Japan. It is known to be a plentiful source of polyunsaturated fatty acids (PUFA) and monounsaturated fatty acids (MUFA), mostly trienoic acid and pinolenic acid [2]. Previous studies have shown the favorable effect of Pinus koraiensis on blood pressure [3], inflammatory response [4], and satiety and appetite control [5, 6]. However, the evidences regarding effects of blood lipid regulation of Pinus koraiensis are not still conclusive. Sugano et al. [3] examined the effect of Pinus koraiensis seed oil on blood lipids and they found that Pinus koraiensis seed oil specifically improved plasma triglyceride level and blood pressure compared to other similar materials like flaxseed oil. In some studies with similar study design, however, serum lipid profiles were not significantly changed [7, 8]. These controversial results in the experimental studies with animal model can be explained by handling with different methods of preparation and extraction, dose, and materials. However, it is hard to find clinical efficacy trials on Pinus koraiensis in human and besides it has seldom been examined the effect of Pinus koraiensis on the regulation of serum lipid profiles in the individuals with borderline dyslipidemia. Therefore, we examined the effect Pinus koraiensis needle extract (PKE) on lipid profiles and oxidative stress in the borderline dyslipidemia using a randomized and double-blinded controlled study design. This efficacy trial on PKE was also designed to provide clinical significance into the development of dietary supplementary products for early management of dyslipidemia. 2. Materials and Methods 2.1. Ethical Statement The study protocol had been approved by the Kyung Hee University Hospital Ethics Committee (Seoul, South Korea) (IRB number: KMC IRB 1227-02). The trial was performed according to the Declaration of Helsinki and it was in accordance with the principles of Good Clinical Practice. All participants signed a written informed consent prior to study enrollment. 2.2. Participants Inclusion criteria were (1) adult aged 20 or older and (2) borderline dyslipidemia (diagnosed with one of the abnormalities of serum lipid level as follows, 200–239 mg/dL of total cholesterol or 130–159 mg/dL of LDL-cholesterol or 150–199 mg/dL of triglyceride) [9]. We excluded individuals with any of the following conditions: (1) diagnosis of dyslipidemia and/or lipid lowering medication; (2) history and/or current treatment of chronic disease in cardiovascular system, kidney, and liver; (3) metabolic disturbances with thyroidal and pancreatic disease and diabetes; (4) alcoholics; (5) pregnancy and breastfeeding; (6) hormone replacement therapy; (7) unwillingness or inability to follow all trial procedures. 2.3. Sample Size Planning and Study Power Sample size was estimated based on the results from a previous trial [10], where the detection of a significant difference between groups (α = 0.05 and β = 0.80) allowing for a 25% dropout rate suggested the recruitment of 35 people into each group. 2.4. PKE and Placebo Tablets The Pinus koraiensis needle was collected from natural pine stands in Hwacheon- myeon, Hongcheon-gun, Gangwon-do, Korea. The plant materials (200 g) were extracted with 50% ethanol with solvents as methanol (Figure 1). The extract was evaporated to an aqueous concentrate and then partitioned between ethyl acetate and water for 2 times at 45°C for 8 h. The extract was filtered through a 25 μm standard sieve and was dried using a vacuum rotary evaporator to 60 Brix under low pressure, producing PKE tablets. Each PKE tablet (450 mg) contained 300.0 mg PKE (66.6%) and various bulking agents, including sugar alcohol (12.4%), cellulose (10%), polysaccharide (2%), lubricating and glossing agents (5%), and other excipients (4%). The placebo tablets contained dextrin (66.6%) instead of PKE. All subjects ingested same number of PKE or placebo tablets, 2 tablets after morning and evening meals, for 12 weeks. 2.5. Study Design and Procedure This study was randomized and double-blinded clinical trial design. Participants were recruited through a variety of outreach methods such as posters, word of mouth, presentation at community center, and website advertisements between October 2013 and January 2014 in Seoul, Korea. The persons who were interested in the study were briefly told about the purpose of the study, procedure, and the features of the products used in the study. Written consent form was obtained from the person with an affirmative response to participate into the study after further explanation of the study protocol. One hundred and two participants were interested in the study. Among them, only 35 subjects (enrollment rate: 34.3%) satisfied inclusion criteria through screening evaluation which confirmed their blood lipid profiles and other clinical statuses were enrolled in the 12-week clinical trial of PKE. The enrolled participants were randomly assigned to either test group (PKE group) or control group (Figure 2). Of the 35 subjects, two did not end in the placebo group, and hence there were 33 subjects for whom at least baseline data were collected and could be included in data analysis. After randomization, general information including age, sex, education, alcohol consumption, regular exercise, smoking status, disease checkup, and medication user was obtained using constructive survey questionnaire and anthropometrics and further laboratory measurement were conducted for baseline data collection. 2.6. Key Outcome Measures Blood samples were drawn from the mid arm vein after 12-hour overnight fasting at baseline and at 12 weeks. Obtained samples were separated into ethylenediamine tetra-acetic acid-potassium (EDTA-K2) anticoagulant tubes and serum-separate tubes (SST). After being allowed to clot for 30 minutes, SST was centrifuged (3,000 ×g, 4°C, for 10 min) and the supernatant used for analysis. All laboratory analysis was conducted in clinical laboratory analysis institute named Green Cross Laboratories Co in Gyeonggi-do, Korea. Triacylglycerol (TG), total cholesterol, high-density lipoprotein- (HDL-) cholesterol, low-density lipoprotein- (LDL-) cholesterol, aspartic acid transaminase (AST), alanine transaminase (ALT), γ-glutamyl transpeptidase (γ-GT), and high sensitive C-reactive protein (hs-CRP) were analyzed using an automatic analysis system (Modular Analytics, Roche, Germany). Free-fatty acids were measured by a colorimetric method (ACS-ACOD) by means of a commercial assay kit (Roche, Germany). Very low-density lipoprotein- (VLDL-) cholesterol was estimated by the Friedewald equation: VLDL = triglyceride/5 [11]. Superoxide dismutase (SOD) was measured by colorimetric method using commercial kit (Superoxide Dismutase Assay Kit; Cayman, USA) (reference value: non), catalase was measured by spectrophotometer (UV1700, SHIMAZDA, Japan) using commercial kit (BIOXYTECH catalase-520; OxisResearch™, USA,) (reference value: 32.5–68.5 KU/L), and malondialdehyde (MDA) was measured by ELISA kit (OxiSelect™ MDA Adduct; Cell Biolabs Inc., USA). Anthropometric measures were conducted at baseline, 6 weeks, and 12 weeks. Body weight and height were measured with standard method, wearing light clothing and no shoes. Body mass index (BMI) was calculated as the ratio of weight (kg) to the square of height (m2). Waist circumference (WC) was assessed in the erect position at the middle between the tenth rib and the iliac crest, and hip circumference (HC) was assessed at the widest horizontal diameter of the buttock. Waist-to-hip ratio (WHR) was derived from the calculation with WC and HC. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured twice by mercury sphygmomanometer in the sitting position after they had been quietly seated for more than 15 min. The mean of the two measurements was used in the analyses. 2.7. Statistical Analysis Descriptive analyses for continuous and discrete variables were presented as mean ± standard deviation (SD) or standard error (SE) and n (%), respectively. Nonparametric statistics such as Fisher's exact test and Mann-Whitney U test were used to compare differences in outcome variables between groups and Wilcoxon signed-rank test was used to assess within-group changes. General linear models (GLM) adjusted for WC the main effect and interactive effects of PKE. Efficacy analysis was conducted based on an intention-to-treat (ITT) principle [12]. All statistical analyses were performed using SPSS version 21.0 (IBM Cooperation, Chicago, USA). The significance level was defined at p < 0.05. 3. Results General characteristics of subjects were presented in Table 1. The mean ages of the subjects were 46.1 ± 6.4 years in placebo group and 47.2 ± 7.5 years in PKE group. At baseline, there are no significant differences in BMI, WC, HC, WHR, SBP, DBP, smoking, alcohol consumption, and exercise between two groups. After 12 weeks, WC were significantly decreased in both groups: −2.7 cm in decreased PKE (from 86.3 ± 9.8 cm at baseline to 84.8 ± 9.7 cm at after 12 weeks, p < 0.05) and −1.5 cm in decreased placebo group (from 88.2 ± 8.5 cm at baseline to 85.5 ± 9.3 cm after 12 weeks, p < 0.05). Also, SBP was significantly decreased −4.7 ± 8.9 mmHg (from 115.8 ± 11.8 mmHg at baseline to 110.3 ± 10.0 mmHg after 12 weeks, p < 0.05) in PKE group after 12 weeks but not in placebo group (from 115.6 ± 19.0 mmHg at baseline to 115.6 ± 14.1 mmHg at after 12 weeks) (data not shown) [Appendix]. Except for lipid profiles such as TG, TC, LDL, and FFA, VLDL-cholesterol level was significantly decreased −7.2 ± 5.3 mg/dL (from 25.0 ± 2.3 mg/dL at baseline to 18.5 ± 0.9 mg/dL after 12 weeks, p < 0.01) in PKE group; meanwhile, other indicators for lipid (TG, TC, LDL, and FFA) were not changed between and within groups after the intervention (Table 2). However, after adjustment with WC, VLDL-cholesterol was not significant between groups (p = 0.095). For the results of antioxidative enzyme capacities (SOD and catalase) and lipid peroxidase (MDA) shown in Table 3, SOD was increased in both PKE (changes: 2.27 ± 0.62 U/mL from 6.12 to 9.06 ± 0.62 U/mL, p < 0.01) and placebo (changes: 2.30 ± 3.30 U/mL, from 8.84 to 9.06 ± 11.10 U/mL, p < 0.05) groups after 12 weeks. Changes in catalase and MDA were not detected. After adjustment with WC, SOD was significantly different between groups (p < 0.013). 4. Discussion The primary objective of this study was to examine the PKE on lipid lowering in Korea adults with borderline dyslipidemia. The results showed a modest but favorable difference in total serum cholesterol, although VLDL-cholesterol showed statistically significant improvement in PKE group. Additionally, antioxidant levels, as a secondary outcome, were not significantly different between groups after supplement, although SOD was positive supplement effect. On the other results, the WC and SBP were changed in PKE group after supplement. After adjustment with WC, VLDL-cholesterol was not significant between the groups, while SOD remained significant between groups. Also, lack of any significant effect of the PKE on blood levels of AST and ALT compared with the placebo group demonstrated that Pinus koraiensis does not have a toxic effect on the hepatic function. Moreover, no adverse effects were reported by the subjects. Pinus contains about 15% of polyunsaturated fatty acid (PUFA) known as pinolenic acid (cis-5, 9, 12-18:3). Pinolenic acid contributes to triacylglycerol-lowering properties such as decreased de novo lipid synthesis, reduced substrate availability for lipoprotein formation, or changes in VLDL physicochemical properties [13]. Therefore, Pinus koraiensis may reduce triacylglycerol and VLDL concentration and may have a potential benefit in lowering CVD risk. In accordance with Sugano et al. [3], observed levels of serum triglycerides in rats supplemented with Pinus koraiensis seed oil (10 g/kg B.W/day corresponding to 1.8 g pinolenic acid/kg B.W/day) for 5 weeks showed a hypocholesterolemic effect. Similarly, Asset [7] showed the Pinus koraiensis seed oil (5 g/kg B.W/day corresponding to 0.75 g pinolenic acid/kg B.W/day) for 4 weeks lowering triglycerides serum triglycerides by 16% and VLDL-triglycerides by 21%. Earlier, Wolff [14] showed P. pinaster, kinds of pine, seed oil lowers triglycerides, VLDL-triglycerides, and VLDL-cholesterol compared to a diet enriched in oleic acid. Also, Kim et al. [15] showed that the Pinus koraiensis was upregulated LDL-receptor as well as being negative and HMG-CoA reductase. The removal of the LDL-cholesterol from blood is mainly mediated by receptor-dependent process. In our study, despite PKE supplementation, TG and TC were, respectively, 8.2% and 3.8% decreased, and data were not significant. We thought that the subjects were mainly with cholesterol borderline, rather than with dyslipidemia individuals with >240 mg/dL of serum total cholesterol or >160 mg/dL of LDL-cholesterol or >200 mg/dL of triglyceride and sample size was small. These lead to a decrease power in detecting differences between groups. Also, HDL-cholesterol was decreased in PKE group; in our group, there was not mechanistic study on why HDL-cholesterol was decreased; however, previously, one study shows that pine supplementation decreased in HDL-cholesterol, and further study will be needed. Our findings are also as follows: PKE reduced SBP by −4.7 mmHg after 12 weeks in PKE group. In accordance with animal data, the 8 weeks of the pine seed oil supplement (1.8 g pinolenic acid/kg body weight/day) alleviated SBP in spontaneously hypertensive rat (9 weeks old male rats) [3]. This mechanism may explain that pinolenic acid attenuated blood pressure through the imbalance of prostaglandins, the influencing factor of the blood pressure [3, 16]. Recently, Ko and colleges [17] showed that the essential oil of Pinus koraiensis effects suppressed body weight gain though may decrease the expression peroxisome proliferator-activated receptor (PPAR). In our study, WC was decreased in PKE group compared with placebo group, although body weight was not changed. WC and WHR have been suggested to be strongly associated with metabolic risk factors because of being inversely associated with dyslipidemia, diabetes, hypertension, and CVD. Several limitations of our study have to be addressed like low success for recruitment to the intervention. In our study, inclusion criteria were stricter than that of other studies, namely, difficulty in screening and higher screening failure rate (65%). It has affected the sample size for this study which was smaller than planned sample size (each group equals 35). These two limitations affected a major cause between groups which was not significant. Despite these limitations, our study showed excellent compliance among the 33 subjects (placebo: 94.2% and PKE group: 91.7%) and without any discomfort. In conclusion, the present study is the first to report that PKE could be of beneficial effect as VLDL-cholesterol decreased and SOD increased. However, after adjustment with WC, VLDL-cholesterol was not significant between groups, while SOD remained significant. Further studies are needed to determine difference for the lipid profiles with enough sample size. In our results, PKE also reduced WC and SBP after 12 weeks of consumption without any adverse effects. Based on our results, future studies should examine PKE effects on the usefulness for subject with dyslipidemia or metabolic syndrome. Acknowledgments This work was supported by a grant from the Next-Generation BioGreen 21 Program (no. PJ009055), Rural Development Administration, Republic of Korea. Appendix See Table 4 and Figure 3. Competing Interests The authors declare that there are no competing interests regarding the publication of this paper. Figure 1 Flow diagram for extraction and fractionation of Pinus koraiensis. Figure 2 Subject's flow chart in Korean adults with borderline dyslipidemia in Pinus koraiensis extracts or placebo group for 12 weeks. Figure 3 Changes of the SBP in the Pinus koraiensis or placebo group for 12 weeks. No significant difference between the two groups by Student's t-test. Table 1 Anthropo- and health-related subjects by treatment group at the baseline.   Placebo (n = 13) PKE (n = 20) Age (years) 46.1 ± 6.4(1) 47.2 ± 7.5 Sex, M/F (n, %) 5 (38.5)/8 (61.5) 6 (30.0)/14 (70.0) Body mass index (kg/m2) 25.1 ± 4.2 24.2 ± 3.6 Waist circumference (cm) 88.2 ± 8.5 86.3 ± 9.8 Waist-to-hip ratio 0.88 ± 0.04 0.89 ± 0.05 Systolic blood pressure (mmHg) 115.6 ± 19.0 115.8 ± 11.8 Diastolic blood pressure (mmHg) 81.7 ± 13.2 79.9 ± 9.6 Smoking (n, %) 3 (23.1) 2 (10.0)  Cigarette/day 10.8 ± 8.8 9.75 ± 7.4 Alcohol consumption (n, %) 10 (76.9) 14 (70.0)  Amount (g/week) 75.3 ± 82.2 49.4 ± 79.5 Exercise regularly (n, %) 8 (61.5) 9 (45.0)  Duration (min/week) 182.5 ± 165.0 240.6 ± 123.1 (1)Values are mean ± SD or n (%). No significant difference between the two groups by Student's t-test. Table 2 Blood lipid profiles before and after intervention, by treatment group. Placebo (n = 13) PKE (n = 20) Before After Before After Aspartic acid transaminase (U/L) 24.2 ± 3.0(1) 20.5 ± 1.3 23.1 ± 1.9 21.6 ± 1.1 Alanine transaminase (U/L) 20.8 ± 4.0 16.5 ± 2.6 21.0 ± 2.5 21.9 ± 3.1 γ-glutamyl transferase (U/L) 28.0 ± 10.7 25.1 ± 6.7 24.0 ± 3.8 23.9 ± 4.0 Triglyceride (mg/dL) 137.3 ± 38.3 110.5 ± 17.9 110.6 ± 9.6 92.5 ± 4.4 Total cholesterol (mg/dL) 205.4 ± 7.8 198.7 ± 8.4 205.9 ± 5.4 197.1 ± 5.7 LDL-cholesterol (mg/dL) 135.7 ± 6.4 130.8 ± 6.9 134.0 ± 4.7 131.5 ± 4.5 HDL-cholesterol (mg/dL) 50.2 ± 3.2 54.7 ± 3.1 59.4 ± 3.0∗ 55.4 ± 3.5 VLDL-cholesterol (mg/dL)(2) 29.3 ± 8.0 22.2 ± 3.6 25.0 ± 2.3 18.5 ± 0.9†† Free-fatty acid (μEq/L) 497.5 ± 90.1 453.7 ± 61.0 496.6 ± 48.2 500.7 ± 30.9 Glucose (mg/dL) 94.6 ± 3.9 95.8 ± 3.1 94.6 ± 2.0 92.3 ± 1.6 Insulin (μIU/mL) 7.9 ± 1.7 5.5 ± 0.8 7.4 ± 0.8 6.6 ± 0.9 QUICKI(3) 0.36 ± 0.01 0.38 ± 0.01 0.36 ± 0.01 0.37 ± 0.01† (1) Data are mean ± SE. (2)VLDL-cholesterol calculation: triglyceride/5. (3)QUICKI: quantitative insulin-sensitivity check index: 1/[log (fasting insulin) + log (fasting glucose, mg/dL)]. ∗Significant difference between the two groups by Student's t-test at ∗ p < 0.05. †Significant difference within groups by paired t-test at † p < 0.05 and †† p < 0.01. Table 3 Antioxidants profiles before and after intervention, by treatment group. Placebo (n = 13) PKE (n = 20) Before After Before After Superoxide dismutase (U/mL) 8.84 ± 1.9(1) 11.10 ± 1.8† 6.12 ± 0.41 9.06 ± 0.62†† Catalase (KU/L) 7.72 ± 5.1 6.83 ± 1.2 5.10 ± 1.89 6.46 ± 1.2 Malondialdehyde (pmol/mg) 0.88 ± 0.1 0.81 ± 0.1 1.02 ± 0.08 0.84 ± 0.06 (1)Data are mean ± SE. †Significant difference within groups by paired t-test at † p < 0.05 and †† p < 0.01. Table 4 Anthropometric measurements of the subjects.   Placebo (n = 13) PKE (n = 20) Before After Before After Height (cm) 164.5 ± 7.7(1) 161.4 ± 7.1 Weight (kg) 68.5 ± 14.6 67.7 ± 14.0 63.4 ± 14.0 63.3 ± 14.0 Body mass index (kg/m2) 25.1 ± 4.2 24.9 ± 4.0 24.2 ± 3.6 23.1 ± 5.6 Waist circumference (cm) 88.2 ± 8.5 85.5 ± 9.3† 86.3 ± 9.8 84.8 ± 9.7† Hip circumference (cm) 99.7 ± 6.7 98.6 ± 7.4† 96.6 ± 6.3 96.0 ± 6.0 Waist-to-hip ratio 0.88 ± 0.04 0.87 ± 0.04 0.89 ± 0.05 0.88 ± 0.05 Systolic blood pressure (mmHg) 115.6 ± 19.0 115.6 ± 14.1 115.8 ± 11.8 110.3 ± 10.0∗† Diastolic blood pressure (mmHg) 81.7 ± 13.2 79.3 ± 13.2 79.9 ± 9.6 79.1 ± 8.8 (1)Data are mean ± SD. ∗Significant difference between the two groups by Student's t-test. †Significant difference within groups by paired t-test p < 0.05. ==== Refs 1 Korea National Statistical Office Korea National Statistical Office Cause of Death Statistics in 1983–2012 2013 Daejeon, Republic of Korea Korea National Statistical Office 2 Wolff R. L. Bayard C. C. Fatty acid composition of some pine seed oils Journal of the American Oil Chemists' Society 1995 72 9 1043 1046 10.1007/BF02660719 2-s2.0-51249162148 3 Sugano M. Ikeda I. Wakamatsu K. Oka T. Influence of Korean pine (Pinus koraiensis)-seed oil containing cis-5,cis-9,cis-12-octadecatrienoic acid on polyunsaturated fatty acid metabolism, eicosanoid production and blood pressure of rats British Journal of Nutrition 1994 72 5 775 783 10.1079/bjn19940079 2-s2.0-0027940488 7826999 4 Park S. Lim Y. Shin S. Han S. N. Impact of Korean pine nut oil on weight gain and immune responses in high-fat diet-induced obese mice Nutrition Research and Practice 2013 7 5 352 358 10.4162/nrp.2013.7.5.352 2-s2.0-84885770752 24133613 5 Pasman W. J. Heimerikx J. Rubingh C. M. The effect of Korean pine nut oil on in vitro CCK release, on appetite sensations and on gut hormones in post-menopausal overweight women Lipids in Health and Disease 2008 7, article 10 10.1186/1476-511x-7-10 2-s2.0-42249108001 6 Hughes G. M. Boyland E. J. Williams N. J. The effect of Korean pine nut oil (PinnoThin™ ) on food intake, feeding behaviour and appetite: a double-blind placebo-controlled trial Lipids in Health and Disease 2008 7, article 6 10.1186/1476-511x-7-6 2-s2.0-42049097857 7 Asset G. Baugé E. Wolff R. L. Effects of Pinus pinaster and Pinus koraiensis seed oil supplementation on lipoprotein metabolism in the rat Lipids 1999 34 1 39 44 10.1007/s11745-999-335-2 2-s2.0-0032981339 10188595 8 Won S. B. Jung G.-Y. Kim J. Chung Y. S. Hong E. K. Kwon Y. H. Protective effect of pinus koraiensis needle water extract against oxidative stress in HepG2 cells and obese mice Journal of Medicinal Food 2013 16 7 569 576 10.1089/jmf.2012.2665 2-s2.0-84880852171 23822143 9 Korea Society of Lipidology and Atherosclerosis 2009 10 Kianbakht S. Abasi B. Perham M. Hashem Dabaghian F. Antihyperlipidemic effects of Salvia officinalis L. leaf extract in patients with hyperlipidemia: a randomized double-blind placebo-controlled clinical trial Phytotherapy Research 2011 25 12 1849 1853 10.1002/ptr.3506 2-s2.0-82155197276 21506190 11 Friedewald W. T. Levy R. I. Fredrickson D. S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clinical Chemistry 1972 18 6 499 502 2-s2.0-0015348189 4337382 12 Hollis S. Campbell F. What is meant by intention to treat analysis? Survey of published randomised controlled trials British Medical Journal 1999 319 7211 670 674 10.1136/bmj.319.7211.670 2-s2.0-0033546995 10480822 13 No D. S. Kim I.-H. Pinolenic acid as a new source of phyto-polyunsaturated fatty acid Lipid Technology 2013 25 6 135 138 10.1002/lite.201300278 2-s2.0-84878923326 14 Wolff R. L. Structural importance of the cis-5 ethylenic bond in the endogenous desaturation product of dietary elaidic acid, cis-5, trans-9 18 : 2 acid, for the acylation of rat mitochondria phosphatidylinositol Lipids 1995 30 10 893 898 10.1007/bf02537479 2-s2.0-0028863252 8538375 15 Kim J.-H. Lee H.-J. Jeong S.-J. Lee M.-H. Kim S.-H. Essential oil of pinus koraiensis leaves exerts antihyperlipidemic effects via up-regulation of low-density lipoprotein receptor and inhibition of acyl-coenzyme A: cholesterol acyltransferase Phytotherapy Research 2012 26 9 1314 1319 10.1002/ptr.3734 2-s2.0-84866133726 22275303 16 Knapp H. R. Omega-3 fatty acids, endogenous prostaglandins, and blood pressure regulation in humans Nutrition Reviews 1989 47 10 301 313 2-s2.0-0024747826 2689920 17 Ko H.-S. Lee H.-J. Lee H.-J. Essential oil of Pinus koraiensis exerts antiobesic and hypolipidemic activity via inhibition of peroxisome proliferator-activated receptors gamma signaling Evidence-Based Complementary and Alternative Medicine 2013 2013 10 947037 10.1155/2013/947037 2-s2.0-84884240600

PMC005xxxxxx/PMC5004036.txt

==== Front Can J Gastroenterol HepatolCan J Gastroenterol HepatolCJGHCanadian Journal of Gastroenterology & Hepatology2291-27892291-2797Hindawi Publishing Corporation 10.1155/2016/4123692Clinical StudyEosinophilic Esophagitis in Children and Adolescents with Abdominal Pain: Comparison with EoE-Dysphagia and Functional Abdominal Pain http://orcid.org/0000-0002-9314-8535Gunasekaran Thirumazhisai 1 * http://orcid.org/0000-0002-6931-5292Prabhakar Gautham 2 http://orcid.org/0000-0003-3809-6637Schwartz Alan 3 Gorla Kiranmai 2 Gupta Sandeep 4 http://orcid.org/0000-0001-7884-1844Berman James 5 1Advocate Children's Hospital, University of Illinois and Loyola Medical Center, 1775 Dempster Street, Park Ridge, IL 60068, USA2Advocate Children's Hospital, 1775 Dempster Street, Park Ridge, IL 60068, USA3University of Illinois, Chicago, IL 60607, USA4University of Indiana, Indianapolis, IN 46202, USA5Advocate Children's Hospital and Loyola Medical Center, 1775 Dempster Street, Park Ridge, IL 60068, USA*Thirumazhisai Gunasekaran: tsg@tummydocs.comAcademic Editor: Grigorios I. Leontiadis 2016 16 8 2016 2016 41236922 2 2016 22 6 2016 20 7 2016 Copyright © 2016 Thirumazhisai Gunasekaran et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Aim. Compare EoE-AP with EoE-D for clinical, endoscopy (EGD), histology and outcomes and also with FAP-N. Method. Symptoms, physical findings, EGD, histology, symptom scores, and treatments were recorded for the three groups. Cluster analysis was done. Results. Dysphagia and abdominal pain were different in numbers but not statistically significant between EoE-AP and EoE-D. EGD, linear furrows, white exudates were more in the EoE-D and both combined were significant (p < 0.05). EoE-D, peak and mean eosinophils (p  0.06) and eosinophilic micro abscesses (p  0.001) were higher. Follow-Up. Based on single symptom, EoE-AP had 30% (p  0.25) improvement, EoE-D 86% (p < 0.001) and similar with composite score (p  0.57 and <0.001, resp.). Patients who had follow-up, EGD: 42.8% with EoE-AP and 77.8% with EoE-D, showed single symptom improvement and the eosinophil count fell from 38.5/34.6 (peak and mean) to 31.2/30.4 (p  0.70) and from 43.6/40.8 to 25.2/22.8 (p < 0.001), respectively. FAP-N patients had similar symptom improvement like EoE-D. Cluster Analysis. EoE-AP and FAP-N were similar in clinical features and response to treatment, but EoE-D was distinctly different from EoE-AP and FAP-N. Conclusion. Our study demonstrates that EoE-AP and EoE-D have different histology and outcomes. In addition, EoE-AP has clinical features similar to the FAP-N group. ==== Body 1. Introduction Eosinophilic esophagitis (EoE) in children and adolescents is associated with a variety of symptoms [1]. The consensus recommendation identified four dominant presenting symptoms of esophageal dysfunction: dysphagia (D), abdominal pain (AP), gastroesophageal reflux (GERD)/vomiting, and failure to thrive/feeding difficulty (FTT) [2]. Historically, GERD “evolved,” in its categorization as erosive esophagitis (EE), nonerosive gastroesophageal disease (NERD), and functional GERD [3, 4]. Clinicians know that the treatment for EE and NERD versus functional GERD is undoubtedly different [4, 5]. However, treatment of EoE is the same irrespective of the dominant symptom and has not been differentiated based on symptom. Treatment of EoE in children includes steroids or diet. The symptom and/or histological improvement for these treatments vary from 50 to 100% [2] and prior studies did not often subgroup EoE patients based on the dominant presenting symptom. In practice, we observed that patients with EoE-AP have less favorable outcomes with treatment compared to EoE-D and that those children and adolescents with EoE-AP have clinical features similar to functional abdominal pain (FAP) except for the presence of eosinophils in the esophagus [2, 5]. Recent clinical trials on EoE include dysphagia as a required symptom and exclude patients who have abdominal pain without dysphagia [6]. To better define and characterize EoE, we divided the patients seen at our EoE clinic into four groups based on the dominant presenting symptom: dysphagia (EoE-D), abdominal pain (EoE-AP), GERD (EoE-GERD), and EoE-FTT. We hypothesized that the two groups of EoE (EoE-D and EoE-AP) have different patterns of endoscopic and histologic findings and response to treatment. In addition, since EoE-AP has clinical features similar to FAP, we included a third group of patients, FAP with normal endoscopy and biopsy (FAP-N), for comparison [5]. Our study aims were to compare clinical features, endoscopic and histologic features, treatments, and outcomes of patients with EoE-AP to those with EoE-D and compare both groups to FAP-N. Our goal was to look for differentiating or comparable features between these groups and to see if EoE-AP has features similar to FAP. 2. Method In this retrospective study, all children and adolescents with EoE seen over a period of 2.5 years (1/2010 to 6/2012) were divided into four groups based on the dominant presenting symptom. Patients with EoE-AP had central or generalized abdominal pain. Diagnosis of EoE was confirmed as follows: esophageal biopsy with 15 or more eosinophils/HPF, no increased infiltration of eosinophils in the stomach or duodenum, preendoscopy treatment with proton pump inhibitors (omeprazole 40–60 mg or lansoprazole 30–60 mg), and/or a negative esophageal pH study (Bravo, Given Imaging, USA) [2, 7]. An additional cohort of children with FAP-N was selected from those seen in the clinic during the same time period with clinical criteria for FAP and having a normal EGD and biopsy [5]. Patients with celiac, Crohn's, drug allergy, and eosinophils in the stomach or duodenum were excluded. The following data were collected: symptoms, physical findings, allergic diseases, CBC, CMP, ESR, U/A, and endoscopic findings (furrows, white spots/exudates, concentric rings, and friability entered as absent (0) or present (1)). Three-four biopsies were obtained from duodenum, stomach, and distal and mid esophagus for histology. Severity of abdominal pain, nausea, vomiting, regurgitation, and heartburn was scored as follows: absent, 0; mild, 1 (does not interfere with daily activities); and severe, 2 (interferes with daily activities). A dysphagia score was assigned: absent, 0; mild, 1; severe, 2 [6, 8]; and an additional score for food impaction, 3, defined as impacted food requiring endoscopic removal [9]. Peak and mean esophageal eosinophil count at distal and mid esophagus were taken at diagnosis and follow-up [9, 10]. The GERD (presenting with heartburn or regurgitation without dysphagia) and FTT groups were not included because they were not part of our hypothesis for this study and were much smaller group. Treatments included the following: topical steroids (fluticasone 880 mcg/day for age 1–10 years and 1760 mcg/day for 11–18 years, in four divided doses or budesonide 0.5 mg BID for patients up to 5 feet tall and 1 mg BID for those over 5 feet) and six food elimination or directed diet based on the allergy tests, [11, 12] based on a collaborative decision by the physician and family [12–14]. In some patients, a combination of diet and topical steroids was used. Clinical outcome was measured as follows: for dysphagia and abdominal pain as improved (score decreased by 1 or more), worsened (score increased by 1 or more), and no change (score same) and as composite score (calculated from the common five symptoms for each patient, given in Table 1, and then as a sum for all patients for each group), at diagnosis and follow-up [6, 8, 9]. EGD score and eosinophil count (peak and mean) were compared by comparing first endoscopy and the follow-up endoscopy [6, 9, 13, 14]. Statistical analysis was done using SPSS version 20. Significant p value was <0.05. For symptom outcome scores, a test of hypothesis was done by two-tailed binominal test. Institutional Review Board approval for this study was obtained through Advocate Health Care (Oak Brook, IL). 3. Data Analysis Presenting symptoms and signs, associated allergic diseases, and treatments offered were entered into a two-step cluster analysis to determine whether there were distinct clusters [15]. These clusters were then cross-tabulated with the three groups of patients to determine whether the different groups of patients could be distinguished by clinical features. These are the following: age, abdominal pain, dysphagia, nausea, vomiting, regurgitation, anorexia, nocturnal awakening, early satiety, constipation, diarrhea, allergic rhinitis, eczema, asthma, PPI use, fluticasone, budesonide, and diet. In addition, a discriminant function analysis was performed to further explore clinical features associated with the three patient groups. Cross-tabulation with chi-square test was used to compare clinical outcomes across the three groups. Within each group, cross-tabulations and chi-square tests were used to examine the impact of treatment choices (oral steroid, directed diet, elemental diet, and other medications) on clinical outcomes [15]. 4. Results Patient characteristics by condition are shown in Table 1. Other than the dominant symptom, clinical features were similar in the two EoE groups. Nausea was seen more frequently in the EoE-AP and the clinical features of EoE-AP were similar to the FAP-N. Of the total 64 patients in EoE-D and 63 in EoE-AP group, 59 and 58, respectively, had PPI treatment and the remainder (10 patients out of study population of 127) had normal pH study. The mean WBC was 5320/mm3, 5420/mm3, and 4930/mm3 in the EoE-D, EoE-AP, and FAP groups. Eosinophil count more than 350/mm3 was 18.6%, 12.9%, and 6.2% in the three groups. ESR was done in 4/64 EoE-D patients and all patients with EoE-AP and FAP and was normal in all groups. EGD and biopsy findings are noted in Table 2. Visual EGD findings of the esophagus were more apparent in the EoE-D group, particularly the linear furrows and white exudates, and differences were statistically significant. When these two findings were combined, the differences increased and remained significant. Peak and mean eosinophil counts were as follows: EoE-D, 43.1 and 21.6; EoE-AP, 38.6 and 15.2 (p  0.06). Other histological features were not significant except for higher eosinophilic microabscess (p  0.001) in the EoE-D group. 5. Treatment and Outcomes Treatments given are as follows: for EoE-D group, 45 (66.7%): topical steroids (43 fluticasone and 2 budesonide), six (9.3%): diet, nine (14.1%): topical steroids and diet, and two (3.1%): no treatment; for EoE-AP group, 37 (58.7%): topical steroids (35 fluticasone and 2 budesonide), two (3.2%): diet, 21 (33.3%): combination, and three (4.8%): no treatment. EoE-D group received more topical steroids while EoE-AP group received more of combined therapy with topical steroids and diet (chisq(9) = 18.4, p = 0.03). Follow-up period was up to 7.8 years (mean 3.4) in EoE-D, 8.8 years (mean 5.5) in EoE-AP, and in FAP 5.4 years (mean 4.8). Table 3 shows that subjects with EoE-D had a significant improvement (86%) in their dominant symptom compared to EoE-AP (30%). Table 4 shows similar results for composite symptom score. On the contrary, composite scores worsened in the EoE-AP group compared to EoE-D (p < 0.003). The test of hypothesis by the two-tailed binominal test for EoE-AP symptom outcome score showed worsening symptoms more often than 50% of the time compared to EoE-D and this was significant (p < 0.003); that is, the 69.8% not improved in symptoms in the EoE-AP group is higher than the 50% and significant. The FAP-N group improvement was similar to EoE-D group (Tables 3 and 4). EGD Findings. 36/64 (56.3%) subjects with EoE-D and 28/63 (44.4%) with EoE-AP had follow-up endoscopy and biopsies with same protocol, done after 8–12 weeks of treatment (Table 5). Of the 36 subjects with EoE-D, 28/36 (77.8%) improved based on dysphagia, and the eosinophil count at diagnosis was 43.2/40.1 (peak/mean) and 25.8/22.7 at follow-up. This improvement was statistically significant and showed a linear correlation of eosinophils with the symptom improvement. For EoE-AP, 12/28 improved (42.8%) based on AP and the eosinophil count was 38.2/34.6 (peak/mean) and at follow-up 31.4/32.6 and did not have a linear correlation like EoE-D nor had a statistically significant difference in the eosinophils. In subjects who did not have follow-up endoscopy, 27/28 (96.4%) subjects with EoE-D and 7/35 (20%) of those with EoE-AP improved based on the dominant symptom. Figure 1 shows a histogram of the distribution of scores on the discriminant function with patient groups. EoE-AP and EoE-D subjects are perfectly discriminated, but EoE-AP subjects are both difficult to distinguish from FAP-N subjects (that is, they have similar features) and highly (though not perfectly) discriminable from EoE-D subjects. Cluster analysis identified two clusters of patients with fair fit quality (average silhouette measure 0.4). Cluster 1 included all patients with EoE-AP and FAP and eight patients with EoE-D. Cluster 2 included the remaining 57 patients with EoE-D and no others. The most important predictors of cluster membership for EoE were the predominant presenting symptom, abdominal pain (Cluster 1) or dysphagia (Cluster 2). Food bolus was the next most important predictor; no patients in Cluster 1 had food bolus, while 37% of subjects in Cluster 2 had food bolus. Other symptoms were less predictive of cluster membership. In addition, Figure 1 shows the distribution of scores on the discriminant function with subject groups indicated by different shades. EoE-AP and EoE-D subjects are perfectly discriminated; that is, they are different groups. But EoE-AP subjects were difficult to distinguish from FAP patients (i.e., they have similar features) and highly (though not perfectly) discriminable from EoE-D patients. No specific treatments were associated with a greater rate of improvement overall or among groups. 6. Discussion The diagnosis of EoE was established based on the presence of increased eosinophils in the esophagus, absence of eosinophils in the duodenum and stomach, and the presenting symptom. Thus eosinophilic gastroenteropathy was excluded and only a minority of patients had diarrhea. Our study raises the question whether EoE-AP and EoE-D are one disease with different features and outcomes or two different disease processes. To answer this question, we examined differentiating factors between the two groups including demographics, symptoms, visual endoscopic findings, and eosinophils in the esophagus. Of these variables, the features statistically significant were nausea in EoE-AP, visual endoscopic findings, especially when white exudates and furrows were combined, and eosinophilic microabscess for EoE-D. With almost similar treatments, the EoE-D group showed a better and statistically significant improvement of the dominant symptom, while those with abdominal pain (EoE-AP) did not, and moreover the composite score in EoE-AP group worsened. Notably, in the EoE-D group (Table 5) there was a linear correlation with symptom and eosinophil improvement. Similar correlation was not seen with the EoE-AP. EoE-D group received topical steroids alone while the EoE-AP group was more likely to receive combined therapy with topical steroids and diet, and this may be because the EoE-AP group had more failures requiring additional therapy. Though the treatments were not controlled, individual treatments did not show an overall improvement among EoE groups, as shown on cluster analysis, which may be a surrogate of controlled treatment. The symptomatic improvement of EoE-D was similar to FAP while the clinical features of EoE-AP were similar to FAP except the eosinophils, and this raises the question whether EoE-AP and EoE-D are different or there is an overlap between EoE-AP and FAP. According to the consensus recommendations, the diagnosis of EoE, in addition to eosinophils, should include symptoms of esophageal dysfunction [2]. While dysphagia is a cardinal symptom of esophageal dysfunction, abdominal pain does not hold a similar status as many other gastrointestinal diseases including FAP have abdominal pain as a primary symptom [16, 17]. Pentiuk et al. [18] looked at the correlation of symptom score and improvement in the eosinophils before and after treatment in 34 children and, in this group, about 70% had abdominal pain as the main symptom. Among 20 of these 34 children in histological remission, 17 (58%) continued to report symptoms and the majority of these patients had abdominal pain. In addition, there was no significant difference in the frequency and severity score of abdominal pain in patients in histological remission versus histologically active. The authors concluded that, despite improvement in the eosinophil count, a simultaneous symptom improvement failed to occur. A striking observation was that the majority of patients with this dissociation had abdominal pain as the dominant symptom [19]. Aceves et al. [8] found a direct correlation in improvement with dysphagia and early satiety/anorexia and eosinophil count, but there was not a similar correlation for other symptoms including abdominal pain. Another study by Assa'ad et al. [14] on 89 children with EoE showed a histological improvement on eosinophil numbers but the study did not mention the symptom follow-up. These studies note that EoE patients with abdominal pain as main symptom have less favorable outcome with treatment. Unlike children, adult patients present primarily with dysphagia and not abdominal pain. One explanation for this is that, in adults, EoE is more of a fibrostenotic disease, while in children it is often inflammatory. Additionally there is an understanding that the symptoms in children are “evolving,” and as they age dysphagia is seen in older children while abdominal pain is seen in younger children [2, 7], or it is possible that the esophageal inflammation in EoE-AP is an incidental finding. Could there be another reason for the poor outcome in EoE-AP patients? Harris et al. [19] showed that a significant number of children and adolescents with EoE have psychosocial issues. The main symptoms of the 64 children in this EoE study were pain/physical discomfort (56%) or feeding/eating/appetite difficulties (45%); dysphagia was not mentioned as a symptom. About 30% of the patients had depression, 40% had anxiety, and about 60% had social issues. This study, unlike ours, did not group the patients by dysphagia or abdominal pain and suggested that EoE patients have psychosocial issues [19], which may explain the poor outcome in EoE-AP patients, which supports that there could be a functional component to the EoE-AP group. A recent large prospective study by Butz et al. looked at the use of topical fluticasone versus placebo in a group of children and young adults with EoE [20]. Seventy percent of patients showed a complete remission of eosinophils at the end of three-month treatment compared to no subjects in placebo group. 69% of patients in the treatment group had abdominal pain and early satiety at the start of the study. Interestingly abdominal pain persisted in 61% of patients at the end of the study. This study clearly demonstrated that, in spite of histological improvement, there was no symptomatic improvement in the abdominal pain, further evidence that EoE-AP has a poor outcome. Could there be other explanations for the EoE-AP patients to have a poor outcome? Talley et al. showed a positive correlation between functional gastrointestinal disease where the chief complaint is abdominal pain and associated duodenal eosinophilia [21]. Another study, related to this, but in children, showed similar correlation of dyspeptic symptoms and duodenal eosinophilia [22]. These studies suggest the possibility that eosinophils in the duodenum may be related to dyspeptic symptoms similar to FAP or visceral hyperalgesia. The biopsies of our patients did not have eosinophils in the duodenum or antrum, as the diagnosis will change to eosinophilic gastroenteropathy and this was an exclusion criteria as well. We also know that infection with resulting inflammation in the gut can lead to functional gastrointestinal symptoms or postinfectious functional dyspepsia (FD) or irritable bowel syndrome [23]. Various explanations are given for postinfectious FD-irritable bowel syndrome (IBS). The symptoms may depend on the type of infection and/or the site of infection, which affects the enteroendocrine cells and inflammatory cells like macrophages, eosinophils, and mast cells leading to altered motility. Can this explanation apply to EoE-AP patients? Eosinophil granules contain crystalloids composed of major basic protein, eosinophil-derived neurotoxin, eosinophil cation protein, and eosinophil peroxidase which release cytokines and chemokine, which alters smooth muscle function. In addition, eosinophil-derived products, leukotrienes, platelet-activating factor, and interleukin-13, can induce smooth muscle activation and proliferation resulting in inflammation, narrowing, or motility change [24, 25]. These in vitro studies speculate that a similar mechanism may apply to human beings. While it is possible that these mechanisms may apply to EoE-AP with esophageal eosinophil inflammation resulting in visceral hyperalgesia, it also questions whether a proximal esophageal inflammation would result in a distal dysmotility and abdominal pain. In addition to the clinical features, we examined if the cluster analysis would differentiate the two groups [15]. Cluster analysis is a multidimensional scaling that seeks to group items (signs and symptoms) into a small number of clusters based on stronger associations between an item and the center of its cluster of items than between an item and the center of another cluster. The goodness of fit of the clusters is measured by the ability to interpret their membership as well as by the “silhouette” measure of the average distance from each item to its cluster center compared with the center of the next closest cluster. Silhouette scores range from −1 to 1, with scores above 0.2 being “fair” fit to the cluster structure and scores above 0.5 representing good fit to the cluster structure and our analysis showed that the silhouette scores for the two clusters were 0.4, closer to good fit. But cluster analysis only works with clinical features; it does not account for endoscopic results, the defining test for EoE. Both cluster analysis including “silhouette” measure and discriminant function grouped the EoE-AP and FAP-N as one group and different from EoE-D. This is among the first studies to subgroup EoE in children and examine the clinical, endoscopic, and histological features and outcome of the two predominant groups of EoE and show that EoE-AP patients have poor outcomes and have features similar to FAP. Limitations of this study include the following: retrospective design, absence of validated symptom measures (though these scales were used in previously published studies) [8–11], not standardizing the dietary treatment, PPI use [26], and not correlating the exact treatment with outcomes. In addition, within the EoE-AP group, though the patients did not have overt dysphagia, it is possible, but less likely, that they may have adapted to gradual coping mechanisms and so dysphagia was not obvious. In conclusion, because EoE is a clinicopathological condition, histology is but one feature and should not be considered diagnostic on its own. Our study presents evidence to suggest that EoE-AP and EoE-D have different outcomes and the EoE-AP group has features similar to FAP. We propose that, in the management of EoE-AP group of patients, if optimal diet or pharmacotherapy does not lead to symptomatic improvement or when there is dissociation between histological and symptomatic improvement, it is worth relooking not only at adherence to diet and/or medications but also at managing the EoE-AP group with methods successful in functional abdominal pain patients. This in fact may help better prognosticate the EoE-AP patients. Acknowledgments Thanks are due to Henry Mangurten, M.D., and Denise Angst, Ph.D., for editorial revision of the paper. Competing Interests Sandeep Gupta, M.D., is on the editorial board of Clinical Gastroenterology and Hepatology. The rest of the authors declare no competing interests. Authors' Contributions Thirumazhisai Gunasekaran, M.D., performed study concept and design, analysis of data, drafting the paper, study supervision, and administration. Gautham Prabhakar performed acquisition of data and analysis. Alan Schwartz, Ph.D., performed statistical analysis and interpretation of data. Kiranmai Gorla, M.D., performed study design. Sandeep Gupta, M.D., performed critical revision of the paper and is a co-senior author. James Berman, M.D., performed critical revision of the paper for important intellectual content and is a co-senior author. Figure 1 Table 1 Clinical features of patients with eosinophilic esophagitis and functional abdominal pain.   EoE-D n (%) EoE-AP n (%) FAP n (%) EoE-D versus EoE-AP (p) EoE-AP versus FAP (p) Sex (%)            Male 58 (90.6) 49 (77.8) 26 (42.6) 0.054 <0.001  Female 6 (9.4) 14 (22.2) 35 (57.4)     Mean age, yr (range) at diagnosis 11.7 (3–17) 9.44 (2–17) 10.87 (4–17)     Mean duration of FU, yr. (range) 3.4 (0.5–7.8) 5.5 (0.4–8.8) 4.8 (0.5–5.4)     Presenting symptomsa, number (%)            Dysphagia 64 (100) 1b (1.6) 0 (0) 0.00 0.50  Abdominal painc 8 (12.1) 63 (100) 61 (100) 0.00 0.07  Nausea 11 (16.7) 29 (45.3) 27 (44.3) 0.00 0.10  Vomiting 12 (18.2) 11 (17.2) 1 (1.6) 0.16 0.00  Regurgitation 5 (7.6) 7 (11.1) 3 (4.9) 0.19 0.12  Heartburn 7 (10.6) 6 (9.5) 1 (1.6) 0.21 0.05  Diarrhea 4 (6.25) 7 (11.1) 1 (1.6) 0.51 0.075 aSome patients had more than one presenting symptom. bPatient initially presented with dysphagia; however subsequent visits showed abdominal pain as primary cause for distress. cAbdominal pain was central or generalized. Table 2 EGD and biopsy findings of patients.   EoE-D EoE-AP p EGD alterations, number (%)        Linear furrows/vertical lines 53 (82.8) 33 (51.6) 0.008  White exudates 35 (54.7) 16 (25.4) 0.003  Linear furrows and white exudates 30 (46.9) 9 (14.3) <0.001  Concentric rings/trachealization 6 (9.4) 3 (4.8) 0.16  Tears/crepe paper appearance 4 (6.3) 0 0.06 Eosinophil count peak/mean 43.1/21.6 38.6/15.2 0.06 Biopsy changes, number (%)        Eosinophilic microabscesses 23 (35.9) 6 (9.5) 0.001  Basal epithelial hyperplasia 22 (34.4) 17 (27) 0.093  Papillomatosis 10 (15.6) 12 (19) 0.154  Spongiosis 9 (14.1) 10 (15.9) 0.176 FAP: visual changes and biopsies on EGD were normal. Table 3 Symptom score change, dysphagia for EoE-D and abdominal pain for EoE-AP and FAP, baseline versus follow-up.   EoE-D EoE-AP FAP EoE-D versus EoE-AP (p) EoE-AP versus FAP (p) Total, number (%) 64 63 61      Improved 55 (85.9) 19 (30.2) 49 (80.3) <0.001 <0.001  Not improved 9 (14.1) 44 (69.8) 12 (19.7)     EoE-D: baseline mean score = 1.5; sd = 0.69. Follow-up mean score = 0.6; sd = 0.53. Mean difference is −0.89, which is significant (p < 0.001) by paired t-test. EoE-AP group: baseline mean score = 1.2; sd = 0.43. Follow-up mean score = 1.4; sd = 0.77. Mean difference is 0.20, which is not significant (p = 0.25) by paired t-test. Table 4 Composite symptom score∗ change, baseline versus follow-up.   EoE-D EoE-AP FAP Patients 64 63 61 Baseline score 156 129 152 Follow-up score 47 135 79   Composite score improved Score worsened Score improved ∗Symptoms included the following: dysphagia, abdominal pain, nausea, regurgitation, and vomiting. EoE-D: baseline mean score = 2.4; sd = 0.92. Follow-up mean score = 0.7; sd = 0.67. Mean difference is −1.68, which is significant (p < 0.001) by paired t-test. EoE-AP: baseline mean score = 2.0; sd = 0.8. Follow-up mean score = 2.1; sd = 1.08. Mean difference is 0.10, which is not significant (p = 0.57) by paired t-test. Table 5 Follow-up EGD: correlation of symptom and eosinophil count changes.   EoE-D baseline ∗On FU, improved On FU, not improved EoE-AP baseline ∗FU, improved FU, not improved FU EGD 36/64 patients 28 (77.8%) 8 (12.2%) 28/63 patients 12 (42.8%) 16 (57.2%) Eos; peak/mean 43.6/40.8 25.2/22.8 64.6/56.6 38.5/34.6 31.2/30.4 59.5/49.5 NO FU EGD 28/64 patients 27 (96.4%) 1 (3.6%) 35/63 patients 7 (20%) 28 (80%) ∗FU: 36 (D) and 28 (AP) had follow-up EGD. Improvement based on single symptom score. EoE-D group (n = 35): eosinophils baseline mean = 45.0; sd = 23.5. Follow-up mean = 17.7; sd = 20.3. Mean difference = −27.3; sd diff = 29.1, p < 0.001 by paired t. 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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/3681094Review ArticleMicrobial and Natural Metabolites That Inhibit Splicing: A Powerful Alternative for Cancer Treatment http://orcid.org/0000-0003-4645-2371Martínez-Montiel Nancy 1 Rosas-Murrieta Nora Hilda 2 3 Martínez-Montiel Mónica 1 Gaspariano-Cholula Mayra Patricia 1 http://orcid.org/0000-0002-2085-085XMartínez-Contreras Rebeca D. 1 * 1Laboratorio de Ecología Molecular Microbiana, Centro de Investigaciones en Ciencias Microbiológicas, Instituto de Ciencias, Benemérita Universidad Autónoma de Puebla, Edificio IC11, Ciudad Universitaria, 72570 Colonia San Manuel, PUE, Mexico2Laboratorio de Bioquímica y Biología Molecular, Instituto de Ciencias, Benemérita Universidad Autónoma de Puebla, Edificio 103H, Ciudad Universitaria, 72550 Colonia San Manuel, PUE, Mexico3Posgrado en Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Edificio 105 I, Ciudad Universitaria, 72570 Colonia San Manuel, PUE, Mexico*Rebeca D. Martínez-Contreras: rebeca.martinez@correo.buap.mxAcademic Editor: Yiannis Kourkoutas 2016 16 8 2016 2016 368109419 3 2016 27 6 2016 3 7 2016 Copyright © 2016 Nancy Martínez-Montiel et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In eukaryotes, genes are frequently interrupted with noncoding sequences named introns. Alternative splicing is a nuclear mechanism by which these introns are removed and flanking coding regions named exons are joined together to generate a message that will be translated in the cytoplasm. This mechanism is catalyzed by a complex machinery known as the spliceosome, which is conformed by more than 300 proteins and ribonucleoproteins that activate and regulate the precision of gene expression when assembled. It has been proposed that several genetic diseases are related to defects in the splicing process, including cancer. For this reason, natural products that show the ability to regulate splicing have attracted enormous attention due to its potential use for cancer treatment. Some microbial metabolites have shown the ability to inhibit gene splicing and the molecular mechanism responsible for this inhibition is being studied for future applications. Here, we summarize the main types of natural products that have been characterized as splicing inhibitors, the recent advances regarding molecular and cellular effects related to these molecules, and the applications reported so far in cancer therapeutics. ==== Body 1. Introduction In eukaryotes, coding regions of the genome called exons are interrupted by noncoding sequences known as introns. During transcription, exons are identified while introns are removed from the immature mRNA (or pre-mRNA) to generate a mature and functional mRNA molecule. The mechanism responsible for this process corresponds to splicing and the machinery that performs this highly regulated event is the spliceosome, which is integrated by five small nuclear ribonucleoproteic particles (snRNPs) and more than 200 proteins that include auxiliary regulatory factors and components of other co- and posttranscriptional machineries [1]. During splicing, a series of RNA-RNA, RNA-protein, and protein-protein interactions are responsible for the decisions that determine which sequences will be included in the mature transcript [2]. Moreover, some sequences can be incorporated differentially into separated splicing events, leading to an increase in the coding potential of the genome by a process called alternative splicing. 2. Alternative Splicing and the Spliceosome The general splicing mechanism involves the recognition of exon/intron boundaries in a sequence-dependent manner. In mammals, the 5′ end of the intron (5′ splice site or 5′ss) contains a characteristic TG, which recruits snRNP U1. On the opposite side, the 3′ end of the intron (3′ss) shows an invariant region called the branch point sequence (BPS), followed by a polypyrimidine-rich tract (pY-tract) and a conserved AG dinucleotide that indicates the end of the intron [3]. The recognition of the 3′ss involves the binding of SF1 to the BPS and the recruitment of the snRNP U2 auxiliary factor (U2AF) to the pY-tract and the AG dinucleotide. After the recognition of both exon/intron boundaries, an early complex is formed that commits pre-mRNA to undergoing splicing, where U2 snRNP is also recruited to the 3′ss. U2 snRNP recruitment to the pre-mRNA is one of the key steps that triggers additional interactions, leading to the formation of catalytic spliceosome complexes due to the incorporation of the tri-snRNP U4/U5/U6 within which numerous RNA rearrangements and modifications in protein composition contribute to complete a splicing cycle [2, 3]. Like most of the snRNPs, U2 is a ribonucleoproteic complex formed by 7 Sm proteins (which are common for spliceosomal snRNPs) and 17 specific proteins, being the largest snRNP [3]. Among the specific snRNP U2 components, two protein subcomplexes are found: SF3a and SF3b [3–5]. SF3a includes 3 subunits of 60, 66, and 120 kDa [6] while SF3b shows at least 8 specific subunits of 10, 14a, 14b, 49, 125, 130, 140, and 155 kDa [7]. Components of the SF3a and SF3b subcomplexes bind to sequences in the pre-mRNA tethering U2 snRNP to the BPS and the 3′ss. SF3b 155 is one of the most conserved subunits of U2 snRNP and it has shown the ability to bind splicing factors U2AF65 and p14 [3, 8]. Interestingly, this subunit has been related to the antiproliferative effect observed for some natural products that regulate the splicing mechanism and it results clear in the fact that targeting the spliceosome and modulating splice-site recognition could be relevant for the development of new therapeutic approaches, as will be further discussed. 3. The Role of Alternative Splicing in Human Disease Over the past 10 years, the role of alternative splicing in human disease has been growing. When the human genome project was completed, in silico analysis predicted that 75% of the human genes underwent splicing [26] and that 15 to 50% of the genetic diseases were related to aberrant splicing events [27]. From this initial observation, several studies have linked splicing defects with specific genetic disorders. However, the full significance of the role in alternative splicing in human disease remains to be elucidated. Some diseases that have been linked to defects on splicing include dilated cardiomyopathy, autism spectrum disorder, spinal muscular atrophy, schizophrenia, cardiac hypertrophy, amyotrophic lateral sclerosis, and frontotemporal dementia [28]. In all these cases, the molecular insights related to the splicing defect that originates the disease have been dissected. The precise regulation of the splicing event varies for each pre-mRNA and for this reason it is time consuming to demonstrate the molecular mechanism that regulates the alternative splicing for each gene. Moreover, this regulation also depends on the cellular context, complicating the scene. In this regard, future efforts need to be developed in order to dissect the alternative splicing event that is related to each disease and the possible therapeutic tools that could be applied. One specific group of diseases that have been related to splicing corresponds to different types of cancer and only recently the determinant role of splicing in cancer has been acknowledged [29, 30]. Several features of splicing events related to tumor progression have been reported and it is well documented that the alternative splicing of different pre-mRNAs is altered during oncogenic progression with the concomitant development of cancer features, like an increase in vascularization, cell proliferation, and invasion [31, 32]. The molecular hallmarks documented for several types of cancer have been recapitulated in an attempt to orientate future efforts towards cancer treatment through alternative splicing modulation [33–35]. Considering all this evidences, several studies have been oriented to modulate alternative splicing in order to treat cancer. 4. Microbial Metabolites That Regulate Splicing Natural products have been traditionally sought from actinomycetes, filamentous fungi, and medicinal plants. In this regard, several derivatives of bacterial fermentation as well as their synthetic equivalents possess the ability to interact with components of the spliceosome. In some cases, the effect on splicing associated with these drugs is achieved through the direct regulation of the expression of genes that are relevant for cancer progression [36]. Dozens of small molecule effectors targeting the alternative splicing process have been identified and evaluated as drug candidates, including a natural product of Pseudomonas sp. number 2663 called FR901464 [9], natural products from Streptomyces platensis Mer-11107 that originated the group of Pladienolides [37], Herboxidiene [15], and Isoginkgetin [38]. These molecules and their derivatives have shown activity as splicing inhibitors and many of them demonstrated potent antiproliferative properties in human cancer cell lines, being in general less toxic to normal human cells [39]. 4.1. FR901464 and Derivatives Spliceostatins are a group of compounds derived from the natural product FR901464, which was identified initially as an antitumor compound. In the original study, FR901463, FR901464, and FR901465 were isolated from the fermentation broth of Pseudomonas sp. number 2663 [9]. These 3 compounds are soluble in acetonitrile, chloroform, and ethyl acetate and poorly soluble in water and insoluble in hexane. They all show strong UV absorption at 235 nm distinctive of a conjugated diene, while the IR spectra indicated the presence of hydroxyl, ester, and a conjugated amide carbonyl (Figure 1). Initially, the three compounds from the FR9014 series mentioned before were tested for their biological activity. As a result, they all enhanced the transcriptional activity of SV40 in a CAT assay. Besides, they were all cytotoxic according to the MTT method in the following human adenocarcinomas: A549 lung cells, MCF-7 mammary cells, or HCT116 colon cells [9]. Moreover, the 3 compounds extended the life of mice bearing ascetic tumors, FR901464 being the one showing the most potent effect on the tumor systems assayed [9]. Furthermore, FR901464 induced characteristic G1 and G2/M phase arrest in the cell cycle and suppressed the transcription of some inducible endogenous but not housekeeping genes in M-8 cells. In this same cell line, internucleosomal degradation of genomic DNA showed the same kinetics corresponding to the activation of SV40 promoter-dependent cellular transcription, suggesting that a chromatin rearrangement occurs upon the treatment with the drug. Despite this effect in inducing viral gene promoters, it was observed that FR901464 reduces the mRNA levels of several endogenous genes, including c-Myc [9]. Spliceostatin A is a methylated and more stable derivative of FR901464 (Figure 1) and they both show similar activity [37, 40]; the synthesis and activity for both molecules have also been reported [41, 42]. Even when there are few studies on the molecular interactions that mediate the effect of Spliceostatin and related molecules, the antiproliferative effect of Spliceostatin has been associated with splicing and seems to be equivalent to the one registered after knocking down SF3b155 [10]. Using immunoprecipitation assays, further studies demonstrated that FR901464 and its methylated derivative Spliceostatin A inhibit pre-mRNA splicing both in vivo and in vitro by binding noncovalently to the SF3b subcomplex in the U2 snRNP. In the same study, the treatment with Spliceostatin A allowed the identification of immature forms of p27 by RT-PCR, suggesting that pre-mRNA molecules that have not been fully spliced are transported to the cytoplasm, inducing the translation of aberrant mRNAs [11]. Another analogous compound of FR901464 named Spliceostatin B was purified from the fermentation broth of Pseudomonas sp. number 2663 [43]. Spliceostatin B is soluble in DMSO, acetonitrile, acetone, water, chloroform, and dichloromethane. The structure of Spliceostatin B was determined using UV, IR, HR-MS, and NMR spectroscopic analyses, showing that it differs structurally from FR901464 at four points: the substitution of an epoxide group at C3 position with a terminal methylene moiety, the presence of a carboxyl moiety at C17 position, and the absence of two hydroxyl groups at C1 and C4 positions, respectively. These structural features are relevant for the biological function given the fact that it has been reported that loosing the C4 hydrogen bond donor decreases the cytotoxicity and that the C3 epoxide moiety is necessary for bioactivity [44]. The functional analog Spliceostatin B showed cytotoxic effect in three human cancer cell lines: HCT-116, MDA-MB-235, and H232A using the MTT method [45], but its activity was weaker than the one observed for FR901464 according to the IC values obtained [43] and in good correlation with the structural features just mentioned. Other natural products considered Spliceostatin analogs were isolated from the fermentation broth of Burkholderia sp. strain FERM BP3421 [46]. Among these new molecules, Spliceostatin E exhibited good potency against multiple human cancer cell lines with IC50 values ranging from 1.5 to 4.1 nM. The structure of Spliceostatin E was elucidated by extensive spectroscopic studies and resulted structurally in less complex than Spliceostatins A and B [46]. Even when Spliceostatin E maintains the cytotoxic activity, the synthetic molecule showed no inhibition of splicing and it did not alter the structure of nuclear speckles [42]. It has been determined that the fr9 gene cluster is responsible for the biosynthesis of FR901464 in Pseudomonas sp. number 2663. The biosynthetic fr9 gene cluster spans a DNA region of approximately 81 kb and includes 20 genes (fr9A through fr9T). Using this information, a bioinformatic approach was conducted in order to identify other strains that could produce Spliceostatin-like metabolites. Using this comparative analysis while mining the genome of Burkholderia thailandensis MSMB43 elicited the identification of a biosynthetic gene cluster similar to fr9 that was named tst, referring to the Thailanstatin compounds it produces, which are functional analogs of Spliceostatins. The tst gene cluster spans a DNA region of 78 kb, which contains 15 ORFs designated tstA through tstR. The putative functions for the tst gene products were deduced by sequence comparisons with the FR9 proteins and with other bacterial homologs, where the most striking difference is the absence of the equivalent fr9S and fr9T genes from the tst gene cluster. A detailed analysis of this cluster suggested a possible biosynthetic route for Thailanstatins, which is similar to the one demonstrated for FR901464 and corresponds to a hybrid pathway involving a polyketide synthase and a nonribosomal peptide synthetase [47]. Consistent with the bioinformatic approach, Thailanstatins A, B, and C were isolated from the culture broth of Burkholderia thailandensis MSMB43 and they proved to be significantly more stable natural analogs of FR901464 [47]. These molecules are more stable because they lack a hydroxyl group found in FR901464 and they show an extra carboxyl moiety instead as revealed by the HR-MS, NMR, UV, and IR spectrometry. Thailanstatins possess the same linear polyketide-peptide framework observed in FR901464, but they lack a hydroxyl group at the C1 position while showing an extra carboxyl moiety at the C17 position. Thailanstatins B and C have a chloride substituent at the C3 position instead of the epoxide functionality observed for both Thailanstatin A and FR901464. Finally, Thailanstatin B possesses a dimethyl acetyl group at the distal end while Thailanstatin C shows an acetyl group instead [47]. During the biological tests performed, all Thailanstatins exhibited strong antiproliferative activities when tested in the following human cancer cell lines: DU-145 (prostate cancer), NCI-H232A (non-small-cell lung cancer), MDA-MB-231 (triple-negative breast cancer), and SKOV-3 (ovarian cancer), Thailanstatin A being the one showing the strongest effect. Moreover, the three compounds showed the ability to inhibit in vitro splicing and again Thailanstatin A showed the best result being as strong as FR941464 in inhibiting splicing [47]. A summary of the molecular effects depicted for FR9414 series and other splicing inhibitors is presented in Table 1. Considering that the molecules just presented are structurally quite complex, this results in difficulty to accomplish their structural modification. However, synthetic derivatives have been generated (Figure 1), including Meayamycin and Sudemycins [48]. 4.2. Pladienolides Pladienolide B is a macrocyclic lactone originally obtained from Streptomyces platensis Mer-11107, strain isolated from a soil sample collected in Kanagawa, Japan (accession number FERM P-18144, Bioconsortia Program Laboratory National Institute of Advanced Industrial Science and Technology, Japan). The compound deposited in the Open Chemistry Database (PubChem ID 52946850) has a molecular weight of 538.7132 g/mol (Figure 2). Pladienolide B was initially identified in 2004, as part of a work that reported the isolation and structural and functional characterization of seven 12-membered macrocyclic compounds named Pladienolides A to G [37]. All these compounds displayed antiproliferative and tumor suppressive activities when assayed in cell culture and xenograft models, particularly Pladienolides B and D. The initial extraction to isolate Pladienolides was performed with n-butanol from the fermentation broth of Streptomyces platensis. Further chromatography steps over Sephadex LH-20 and silica gel column were accomplished. The bioactive fractions recovered were subjected to preparative HPLC and each fraction containing pure Pladienolides was freeze-dried. The chemical properties of Pladienolides were determined using spectroscopic methods. According to the physicochemical characterization of Pladienolides (A–G), they are soluble in methanol, acetone, n-butanol, ethyl acetate, and DMSO, but not in n-hexane, or poorly soluble in water. In all compounds there is a diene system evidenced by the UV absorption at 240 nm. The chemical structure of Pladienolides A (1), B (2), C (3), D (4), E (5), F (6), and G (7) (Figure 3) was determined by the analyses of NMR, MS, IR, and 2D NMR spectra. The carbonyl and hydroxyl groups were detected in the IR spectra. All Pladienolides are 12-membered macrolides possessing a diene unit and one epoxide moiety with a long side chain at the carbon that bears lactone oxygen [37]. Regarding their biological activity, Pladienolides have highly potent in vitro and in vivo antitumor activities with potential for use in anticancer therapy [20]. Pladienolide B has shown strong in vitro and in vivo antitumor activity and growth inhibitory effect against various cell lines, some of them being resistant to chemotherapeutic agents routinely used. Pladienolide B and some for their analogs induce cell cycle arrest at both G1 and G2/M [49]. A different study using Pladienolides was oriented to identify compounds that contribute of the adaptation of cancer cells to hypoxia using HIF-1, an HLH transcription factor involved in hypoxia adaptation in cancer cells. This approach consisted in searching inhibitors of hypoxia adaptation involved in the regulation of angiogenesis and anaerobic metabolism, considering that hypoxia-inducible genes are relevant for growth of cancer cells. The screening system consisted of the placental alkaline phosphatase (PLAP) gene reporter under the control of the human VEGF promoter containing the hypoxia-responsive element (HRE) that binds HIF-1. The reporter construction was transfected and the hypoxia-induced PLAP expression was analyzed in the U251 human glioma cells. Using a high throughput screening, Pladienolides were identified as inhibitors of hypoxia-induced PLAP expression when the cells were exposed to hypoxic conditions [50, 51]. The pure compounds were probed in their anti-VEGF-PLAP and antiproliferative activity, but only Pladienolides B and D showed a strong activity in both tests, with IC50 of 1.8 and 3.5 for Pladienolide B and of 5.1 and 6 nM for Pladienolide D. In other studies, Pladienolide B showed a potent tumor regression and inhibition of mouse xenograft acting at low-nanomolar concentrations (Table 2). The cell growth inhibition properties of Pladienolide B were identified in a study using a 39-cell line drug-screening panel and additional cell cycle analysis indicated that Pladienolide B blocks cell growth in both the G1 and the G2/M phase [13]. Pladienolide B is the most potent metabolite of S. platensis with antitumor activity, but the chemical synthesis of Pladienolide is complicated [52] and only three approaches have been reported for the synthesis of these unique macrolides [53–55]. On the other hand, the great amount of compound required for in vivo studies remains a significant challenge, due to the synthetic complexity inherent to this class of compounds. In an attempt to generate simple molecules that retain the biological activity of Pladienolides, several analogs have been developed. The more effective Pladienolide analogs for antitumor or anticancer application reported to date are Pladienolide D, E7107, and truncated-Pladienolide versions. Pladienolide D (16-hydroxylated pladienolide) is produced to a lesser extent than Pladienolide B on S. platensis Mer-11107. In order to facilitate the production of Pladienolide D, a biotransformation step of Pladienolide B into Pladienolide D was developed. In this alternative approach, the production of Pladienolide D was increased by 15-fold in the A-1544 strain of S. bungoensis by overexpressing the psmA gene, which encodes the Pladienolide B 16-hydroxylase (PsmA), responsible for the production of Pladienolide D [56]. Using a similar approach, the modified strain S. platensis Mer-11107 expressing the psmA gene from S. bungoensis A-1544 was obtained and in this case the production level of Pladienolide D was 10-fold higher [57]. Pladienolides B and D are promising candidates for further drug development because of their high efficacy and low toxicity; besides, their highly complex structure has been directed to the analog synthesis on a production scale [58]. E-7107 is a synthetic urethane derivative of Pladienolide D with activity against tumor cell lines and human xenografts [13]. E-7107 has a selective and potent antitumor activity in human tumor xenograft models such as human lung cancer LC-6-JCK, where E7107 caused complete tumor remission with poor toxicity. Moreover, E-7107 shows strong cell growth inhibitory activity against a large variety of human cancer cell lines (IC50 values range from 0.2 nM to 21.1 nM). Using an in vivo approach, E7107 produced significant tumor regression in a range of xenograft models. In this regard, animals with BSY-1 (breast), MDA-MB-468 (breast), LC-6-JCK (lung), NIH:OVCAR-3 (ovary) PC-3 (prostate), and WiDr (colon) xenografts were cured [25]. For this reason, E7107 rapidly advanced to Phase I clinical trials and the tests are currently in progress in Europe and the US (https://clinicaltrials.gov/ct2/show/NCT00459823?term=E-7107&rank=1). E7107 was tested in a Phase 1 clinical trial with patients with different types of solid tumors refractory to standard therapies, such as colorectal, esophageal, pancreatic, gastric, renal, and uterine, and was found to stabilize tumor growth [24, 59]. 40 patients received E7107 at doses from 0.6 to 4.5 mg/m2 as a 30-minute intravenous infusion on days 1 and 8 every 21 days. The MTD for E7107 using this schedule is 4.0 mg/m2 [24]. Finally, a different Pladienolide analog called FD-895 was isolated from Streptomyces hygroscopicus strain A-9561. FD-895 is a 12-membered macrolide antibiotic with a planar structure similar to Pladienolide D, but FD-895 has a hydroxyl group at the C-17 position and a methoxy group substituted for the hydroxy group at the C-21 position. FD-895 showed a cytotoxic activity against several types of cancer cells such as Adriamycin-resistant HL-60 [60]. In patients with chronic lymphocytic leukemia, FD-895 and Pladienolide B induced intron retention and spliceosome modulation. The cytotoxic effect of FD-895 involved the apoptosis induction in a caspase-dependent pathway [23]. 4.3. Herboxidiene Herboxidiene (GEXA1) is a polyketide [61] with the structure of a tetrahydrofuran with a residue of acetic acid and a conjugated diene [62]. These structural characteristics and its biological properties contributed to its name [63]. This compound was initially identified as a secondary metabolite from Streptomyces chromofuscus A7841. This compound was extracted with butanol and purified using HPLC. Further structural analysis was completed using HRFAB-MS and spectroscopic studies (RMN-1H y 13C). Initial applications for Herboxidiene included its herbicide activity [36]. In 2002, six molecules sharing similar structures were isolated from Streptomyces sp. and were called GEX1 (Figure 4). These compounds showed antibiotic and antitumor activities, GEX 1A being the molecule with the strongest antiproliferative effect, which was later identified as Herboxidiene [15, 64]. This cytotoxic activity seems to be related to cell cycle arrest in G1 and G2/M according to some in vitro experiments [65]. Besides the biological activities mentioned before, Herboxidiene has also shown activity as anticholesterol agent and as a potent splicing inhibitor. Due to the multiple biological effects demonstrated for Herboxidiene, several groups have attempted the chemical synthesis of the compound. The first total synthesis was accomplished in 1999, where the relative and absolute configurations of Herboxidiene were confirmed [66]. Later attempts used several routes, including a stereochemical synthesis in 18 steps [67], an enantioselective synthesis in 16 steps [68], or an alternative synthesis in 16 steps with a global yield of 3.4% [69]. An additional chemical synthesis reported was performed starting from two chiral ketones derived from lactate in 14 steps with a global yield of 8% [70]. A total enantioselective synthesis of Herboxidiene was reported in 2014 and the obtained product showed a mild inhibitory activity on the spliceosome [71]. In that same year, the alternative synthesis of Herboxidiene and some other analogs like a Pladienolide-Herboxidiene hybrid was reported, where alternative splicing was efficiently modulated [72]. These observations supported the potential role of Herboxidiene analogs as drug candidates for cancer treatment. Some molecules with pharmacological activities similar to those reported for Herboxidiene are Trichostatin and TMC-49A (Figure 4). These compounds have also shown anticholesterol activity. However, Herboxidiene has shown a stronger effect on lowering the amount of cholesterol in plasma by regulating the LDL (Low Density Lipoproteins) receptor [73]. It has been shown that Herboxidiene inhibits splicing due to its ability to bind SAP155, a component of the SF3b complex of the spliceosome, altering its functionality [65]. This was accomplished using tagged molecules of Herboxidiene [73]. The effect of Herboxidiene on the splicing of cancer-related genes has also been demonstrated for a couple of cases. For example, Herboxidiene inhibits the splicing of p27, generating an isoform that is unable to bind the E3 ligase, inducing the accumulation of p27, which is in turn free to recognize and block the E-Cdk2 complex responsible for the E3-mediated degradation of p27. Some of the evidence supporting the role of Herboxidiene in cancer regulation is summarized in Table 1. 4.4. Isoginkgetin Isogingketin (7-O-β- d -glucopyranoside) is a glycosylated biflavonoid (Figure 5) initially isolated from dried leaves of Gingko biloba, a medicinal plant long utilized in traditional eastern medicine. General extraction uses methanol and isolation was performed by column chromatography [38] while further characterization was completed using spectroscopic approaches including IR, UV, HR-FAB-MS, and NMR [74]. Baker and Ollis started to work on the isolation of a compound known as Ginkgetin in 1957; however, they were not able to succeed until later when the molecule was separated using a potassium salt using an approach developed in collaboration with Nakasawa [75]. When applying this technique, the recovered compound was an isomer of Ginkgetin and for this reason the molecule was called Isoginkgetin. From that moment, several studies have been performed in order to analyze the properties and applications of this natural compound. After the initial isolation, Isoginkgetin has been obtained from other plants including Dysoxylum lenticellare Gillespie [76], Chamaecyparis obtusa [77], Cephalotaxus koreana [78], and Cycas circinalis [79] as well as from the fruits of Capparis spinosa [80], Cyperus rotundus [81], Selaginella [82], and Podocarpus henkelii [83]. The biological activity of several biflavonoid compounds has been analyzed in various studies due to its natural origin and its abundance in plants, especially in ferns. Demonstrated activities for the extract of Ginkgo biloba are miscellaneous, according to the following evidence. The anti-inflammatory activity has been related to the inhibition of arachidonic acid [84], the inhibition of COX-2 [85], SOD [86], cAMP phosphodiesterases [87], and the suppression of lymphocyte proliferation [88]. Other activities include the neuroprotector and cytoprotector effects when cells are exposed either to external or intrinsic factors like UV radiation [89] or the accumulation of β-amyloid in neurons [90, 91]. This extract has also been shown to increase adiponectin secretion [92] and the activity of AMP-kinases [93]. Considering these biological activities, Isoginkgetin has been a candidate compound to treat disorders like diabetes, Alzheimer's disease, and other neurodegenerative diseases [94]. In relation to the effect of Isoginkgetin in splicing, it has been shown that the molecule has the ability to inhibit splicing both in vitro and in vivo at similar concentrations (30–33 μM). Isoginkgetin was identified as a splicing inhibitor using a cell-based reporter assay in HEK293 cells [95]. In the same study, it was suggested that the inhibitory effect possibly occurs due to the prevention of the stable recruitment of the U4/U5/U6 trismall nuclear ribonucleoprotein. Using HeLa cells, Isoginkgetin was applied to study in vivo mRNA dynamics, where an accumulation of intron-containing mRNAs was observed upon the treatment [96]. In this same cell line, Isoginkgetin mimics the effect of RNA exosome inhibition and causes accumulation of long human Telomerase RNA transcripts [97]. The effect of Isoginkgetin on splicing was also evaluated by studying the expression of interleukin 32 (IL-32) alternative isoforms, where IL-32γ isoform is overexpressed upon the treatment (Table 1), correlating with cell death in cell lines derived from thyroid cancer [19]. As observed for other splicing inhibitors, Isoginkgetin also shows antitumor activity, which has been related to the inhibition of metalloprotease MMP-9 production and to the increase of the inhibitors of metalloproteinase TIMP-1, resulting in a decrease of tumor invasion [18]. Further applications involving the use of splicing inhibitors can also expand our knowledge concerning the global regulation of gene expression. In a recent study, Isoginkgetin was coupled to a modified RNA-Seq method in order to provide a genome-wide insight into gene expression and to detect specific defects on splicing and transcription [96]. 5. Mechanistic Insights It has been demonstrated that Spliceostatin A, Pladienolide B, and Herboxidiene show the ability to interact directly with the spliceosome and that the molecular target for this molecule is the SF3b spliceosome subunit (Figure 6), a subcomplex of U2 snRNP [13]. The particular details observed for Pladienolide B are presented here. Some studies have demonstrated that drug-treated human tumor xenografts can result in complete loss of the full-length mRNA for certain genes such as MDM2 in rhabdomyosarcoma cells. Pladienolide treatment causes an accumulation of unspliced or incompletely spliced pre-mRNAs and gives rise to fewer and larger nuclear speckles, the intranuclear sites where splice factors are stored [98]. Recently, it was demonstrated that splicing inhibition by Pladienolide B decreased phospho-Ser2 level [99] suggesting that the alteration of gene splicing may represent a suitable target for those drugs. To identify the interaction between Pladienolides and a splicing protein, Pladienolide-tagged probes were used by modification of the acetoxy group at position 7 of Pladienolide B. Chemical tags included 3H-labeled, fluorescence-tagged, and photoaffinity/biotin- (PB-) tagged “chemical probes” (BODIPY-FL). The chemical probes were used in the VEGF-reporter gene expression and cell growth inhibition assays at low-nanomolar to submicromolar IC50. Pladienolide B blocks splicing and prompts nuclear export of intron-containing transcripts as observed by fluorescence microscopy, where the BODIPY-FL probe was concentrated in the nuclei of HeLa cells used as expression system overlapping with the signal obtained of splicing factor SC-35, a marker of nuclear speckles, where splicing factors are located [100]. Using immunoprecipitation experiments, the splicing proteins that interact with Pladienolide B were identified, such as 2,2,7-trimethylguanosine (TMG), Sm BB′&D1 protein, the U2 snRNP-specific protein U2B′′, spliceosome-associated protein 120 (SAP120, SF3a subunit 1), spliceosome-associated protein 155 (SAP155, SF3b subunit 1), and cyclin E. Therefore, U2 snRNP that functions at the 3′ splicing site (Figure 6) seemed to correspond to the target for Pladienolide B [21]. Further immunoprecipitation assays allowed the identification of SAP145 (SF3b subunit 2) and SAP130 (SF3b subunit 3) as Pladienolide B partners. In addition, it was reported that there is a direct interaction between the Pladienolide B probe and SAP130. The mechanism by which Pladienolide impairs in vivo splicing involves SF3b modulation by interacting with SAP130 in the SF3b complex, but it is also possible that Pladienolide B shows a partial interaction with SAP155 or SAP145. Besides, time- and dose-dependent disturbance of in vivo splicing with Pladienolide B results in the formation of enlarged “megaspeckles,” as observed when RNPS1 is overexpressed [101]. In a different approach using the CRISPR/Cas9 genome engineering system, it was demonstrated that the spliceosomal target of Pladienolide B is the SF3b1 subunit [102]. In the search of the mechanism by which Pladienolide B or E-7107 promote the formation of a defective spliceosome, it was found that E7 blocks ATP-dependent remodeling of U2 snRNP that exposes the branch point-binding region. Under this scenario, U2 snRNP fails to bind tightly to the pre-mRNA without disrupting the U2 particle or its association with SF3b [49, 103]. The use of the CRISPRCas9 system in HEK293T cells allowed the observation that some mutations in the subunits of the SF3b complex I promote higher levels of resistance to Pladienolide B. It was also found that R1074H mutation in SF3b1 could have a role in the resistance to Pladienolide [104]. In some reports, it has been proposed that mutations in SF3b1 are associated with numerous types of cancers such as acute myeloid leukemia, primary myelofibrosis, chronic myelomonocytic leukemia, breast cancer, chronic lymphocytic leukemia, and multiple myeloma [105, 106]. The sequence of the SF3b1 gene of 2087 patients with myelodysplastic syndromes (MDS) showed mutations in 20% of all of them, where the K700E mutation was the most frequently found [105]. Finally, the interaction of spliceosome modulators as Pladienolides with the SF3b complex leads to an imbalance in the splicing program in susceptible cells, which may induce apoptosis by changing the levels and/or ratios of essential (and aberrant) proteins in tumor cells [106]. 6. Concluding Remarks Alternative splicing is responsible for increasing the coding potential of the human genome and the implication of this mechanism in human health is starting to be elucidated. Future studies could analyze particular splicing events related to a specific genetic disease making the discovery of new drugs for the treatment of particular disorders possible. In the case of the treatment of cancer, available molecules that target the spliceosome have effectively reverted proliferation of different types of tumors with very low toxicity, suggesting that splicing modulation is an attractive target for cancer treatment. Moreover, considering that some of the splicing inhibitors recently discovered are natural microbial metabolites, it is possible to assume that there are several molecules with antitumor activity that remain to be discovered. Considering that the molecular mechanism related to particular types of cancer is being explored, it could be possible to develop new drugs that could be oriented to modulate a precise splicing event in order to treat a special genetic disease. Competing Interests The authors declare that they have no competing interests. Figure 1 FR901464 and derivatives. The FR9014 series were isolated from Pseudomonas sp. number 2663 and constitute the first antiproliferative molecules associated with splicing inhibition. Spliceostatin A is a methylated derivative of FR901464. Spliceostatin B was also isolated from Pseudomonas sp. number 2663. Spliceostatin E was isolated from Burkholderia sp. FERM BP3421. Thailanstatins were recovered from Burkholderia thailandensis MSMB43. Meayamycin and Sudemycins are synthetic derivatives from the natural products depicted. Figure 2 Pladienolide structure. Pladienolide is a 12-membered macrolide that possesses a long side chain at the carbon bearing lactone oxygen. Figure 3 Pladienolide analogs. (a) General structure of Pladienolides A–G, which was determined by 1H, 13C NMR, MS, IR, and 2D NMR analyses. Radicals for each isoform are summarized in the table. (b) Different functional analogs have also been reported. Figure 4 Herboxidiene structure. The characteristic structure of GEXA1 consisting of a tetrahydrofuran with a residue of acetic acid and a conjugated diene is shown in the left. This natural product was isolated from Streptomyces sp. The derivative Trichostatin is shown at right. Figure 5 Structure of Isoginkgetin. The structure of the 7-O-β- d -glucopyranoside isolated from dried leaves of Gingko biloba is depicted. Figure 6 Molecular mechanism depicted for the natural products that inhibit splicing. (a) It has been demonstrated that FR901464, Spliceostatin A, Pladienolide B, Herboxidiene, and Meayamycin have the ability to block splicing by binding SAP130, SAP145, and SAP155 subunits of snRNP U2 (green). Besides, these natural products block cell cycle in G1 and G2/M transitions (gray arrows). (b) On the other hand, Isoginkgetin blocks splicing by inhibiting the incorporation of the tri-snRNP U4/U5/U6 complex to the spliceosome. Table 1 Molecular effects of different splicing inhibitors. Splicing inhibitor Cell line Effect Reference FR9014 series MCF-7 Induces G1 and G2/M arrest of the cell cycle [9] HeLa Inhibits the recognition of the branch point sequence [10] Binding affinity to SAP145 [11] Arrest of SF3b [12] MDA-MB-468 Interacts with SF3b subunit SAP145 [13] Pladienolide WiDr Interacts with SF3b subunit SAP130 [13] HeLa Interacts with SF3b. Remodeling of U2 snRNP to expose the branch point-binding region [14] Herboxidiene Normal human fibroblast cell line WI-38.2 Induces G1 and G2/M arrest of the cell cycle [15] HeLa Causes arrest in G1 and G2/M phases and interacts with SF3b1 subunit SAP145 [16] Trichostatin WiDr Interacts with SF3B subunit SAP130 [13] Isoginkgetin HT1080 Inhibition of Cathepsin K and MMP9 [17] Inhibits metalloproteinase MMP9 production and increases the synthesis of metalloproteinase inhibitor TIMP-1 [18] HEK293 Stimulates IL-8 expression [19] Thyroid cancer Increases expression of specific IL-32 isoforms and stimulates the expression of IL-8 and CXCR1 [19] Table 2 Antitumor activity of pladienolides.   Molecule Cancer type or cell line Effect Reference Pladienolide B Breast (BSY-1, MCF-7)  Central nervous system (SF-539)  Colon (HCT-116)  Lung (NCI-H522,  NCI-H460, A549,  DMS273, and DMS114)  Melanoma (OVCAR-3)  Stomach (MKN74)  Prostate (DU-145) Growth inhibition  Cell viability was evaluated with MTT and alamarBlue assay. The growth inhibitory activity corresponded to the concentration at which cell growth was inhibited to 50% of control growth (IC50). The strongest effect was observed for lung and breast cancer cell lines. [20] Pladienolide B Anticancer drug-resistant cell lines: P388/CPT, P388/ETP, P388/CDDP, P388/VCR,  HCT-116/5-FU, and  MES-SA/Dx5 Growth inhibition  Cell viability was evaluated with MTT and alamarBlue reagent and IC50 was determined. Pladienolide B showed differential strength depending on the cell line. [20] Pladienolide B Human tumor xenografts:  BSY-1, PC-3, OVCAR-3, DU-145, WiDr, and HCT116 Antitumor  Cell suspensions of various human cancer cells were implanted subcutaneously into female or male BALB/c nu/nu mice.   Tumor volume (TV) and relative body weight (RBW) were measured for 3 months after the treatment. Pladienolide B showed strong inhibitory or regressive activities against these xenografts. [20] Pladienolide B WiDr and DLD1 human colorectal cancer cell lines Antiproliferative  Cells were incubated with 10 nM pladienolide B, 5-fluorouracil, taxol, or vincristine and then stained with propidium iodide. Pladienolide B caused a cell cycle arrest in both G1 and G2/M phases in a time-dependent manner according to FACS analysis. [21] Pladienolide B Gastric cancer cell lines and primary cultured cancer cells from carcinomatous ascites of gastric cancer patients Antitumor  Using an MTT assay, the mean IC50 value was 1.2–1.1 nM for gastric, lung, and breast cancer cell lines.   The mean IC50 value for primary cultured cells from the 12 cases studied was 4.9–4.7 nM. In xenograft models, the tumors completely disappeared within 2 weeks. [22] FD-895 Chronic lymphocytic leukemia Apoptosis  Peripheral blood mononuclear cells from CLL patients were exposed to 100 nM FD-895. 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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/6495858Clinical StudyTomographic Ultrasound Imaging to Control the Placement of Tension-Free Transobturator Tape in Female Urinary Stress Incontinence http://orcid.org/0000-0003-3268-0808Gräf Charlotte M. * Kupec Tomas Stickeler Elmar http://orcid.org/0000-0003-3523-1848Goecke Tamme W. http://orcid.org/0000-0002-0331-8781Meinhold-Heerlein Ivo http://orcid.org/0000-0002-2102-623XNajjari Laila Department of Gynecology and Obstetrics, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany*Charlotte M. Gräf: cgraef@ukaachen.deAcademic Editor: Hashim Hashim 2016 16 8 2016 2016 649585824 4 2016 12 7 2016 Copyright © 2016 Charlotte M. Gräf et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Purpose. The objective was to evaluate, by means of tomographic ultrasound imaging (TUI), the reliability of a novel approach for determining the position of the implanted tension-free transobturator tape (TOT). Furthermore, we analyzed the association between the position of the tape at rest and the subjective cure in stress incontinent women. Methods. This retrospective pilot study consists of 32 stress incontinent women, who underwent TOT procedure and routine sonographic control at day 1 postoperatively and at follow-up visit. TUI was applied on the resulting 4D volumes, thereby delivering 9 axial slices with a 4 mm interslice distance starting at the meatus urethrae internus in caudal direction. The reliability of the approach was tested by two examiners. Postoperative and follow-up ultrasound parameters of uncured and cured patients were analyzed. Results. Measurements of the position of the TOT demonstrated high intraclass correlation coefficients. We found minor differences between sonographic parameters at day 1 postoperatively and at follow-up after a median period of 321 days. In cured patients, the position of the tape was measured in a more caudal position than in uncured patients. Conclusions. TUI can be a reliable method for determining the position of the tape. Further studies are needed to evaluate whether the postoperatively determined position can be used as an indicator of future subjective cure. ==== Body 1. Introduction Suburethral tapes have become the gold standard for treating stress urinary incontinence [1]. Multiple studies [2–9] have determined the position of the tape as one relevant factor impacting the surgical outcome. Some works, however, negate such relevance [10, 11]. Various approaches for measuring the position of the tape by means of ultrasound have been proposed in the literature. These ultrasound parameters comprise, among others, the tape-symphysis pubis angle and distance [2, 11, 12] and the position of the tape in relation to the urethral length measured on midsagittal plane [2, 4–8, 11]. In this work, we introduce a fast and convenient new approach for determining the position of the tape by exploiting the advantages of the sonographic cross-sectional imaging, tomographic ultrasound imaging (TUI). One advantage of this technique is that we do not require measurements that rely on the definition of coordinate systems, which is known to be a complex task [13]. With this study we aim at evaluating the feasibility and accuracy of TUI for determining the position of implanted tension-free transobturator tape (TOT). Furthermore, we investigate the association between the position of the tape at rest and the subjective cure in stress incontinent women. 2. Methods This study relies on a retrospective trial design. 91 women were eligible for the study with clinically and urodynamically proved stress urinary incontinence. The patients underwent TOT insertion with a polyvinylidene fluoride (PVDF) tape at the Department of Urogynecology of our University Hospital between January 2010 and November 2014. Incomplete ultrasonographic data at day one postoperatively and at the follow-up examination, as well as incomplete follow-up data, were selected as exclusion criteria. Clinical parameters were chosen from medical records. As routine, the patients answered, both preoperatively and postoperatively, the International Consultation on Incontinence Modular Questionnaire-short form (ICIQ-SF). The patient was considered subjectively cured if she (1) was stress continent, (2) had no obstructive voiding, and (3) had no de novo urgency at the postoperative and follow-up examination. Patients underwent perineal ultrasound evaluation at day one postoperatively and at the follow-up examination after a period of at least 3 months. These ultrasonographic investigations were conducted in a routine manner and performed by one single examiner qualified according to the DEGUM II standard. The patients were in supine position with a bladder filling of approximately 300 mL. An E8 Voluson ultrasound system (GE Healthcare Ultrasound, Zipf, Austria) was used with a perineal probe (3.5–5 MHz) placed with minimal pressure on the perineum. With an acquisition angle of 70 degrees, the image illustrated symphysis pubis, bladder, urethra, and vagina as shown in Figure 1. 4D ultrasound was then performed while the patients were instructed to rest, strain, perform the Valsalva maneuver, and cough strongly. The resulting volumes were stored for later evaluations. TUI was performed on the 4D volumes obtained at rest using the 4D View (GE Healthcare) software. The uppermost slice was placed, perpendicular to the urethra, at the position of the MUI at rest. In caudal direction 8 further slices were obtained with a 4 mm interslice distance as shown in Figure 2. This distance was selected based on earlier clinical experiences, as we had not found tapes positioned outside this 32 mm range starting at the MUI. Three sonographic parameters that describe the position of the tape were considered: first, the slice number where the tape was found dorsal to the urethra on the axial plane, thus, reflecting the craniocaudal position as shown in Figure 2, second, the distance between the anterior margin of the tape and the longitudinal smooth muscle (LSM) complex of the urethra (TUD) as introduced by Kociszewski et al. [6], and third, the distance between the anterior margin of the tape and the inferoposterior symphyseal margin (TSD). Both distances were determined on the axial plane as illustrated in Figure 3. Two complete measurements of the sonographic parameters were performed, each by one single examiner without the knowledge of each other's results. A DynaMesh SIS (Dahlhausen) tape made of PVDF was used. The surgeon applied a modified outside-in technique, which was originally introduced by Delorme et al. [14]. In general anesthesia, a perpendicular vaginal incision was made 0.5 cm below the external urethral orifice after injecting a single shot antibiotic and emptying the bladder. Afterward, a paraurethral tunnel was dissected with an angle of 45 degrees to the sagittal plane towards the obturator membrane. Next, an incision was made 2 cm above and 4 cm lateral to the meatus urethrae externus and then the TOT was inserted using the helix. The same procedure was followed on the other side. After filling the bladder, the catheter was removed. A stress test was performed by softly pressing suprasymphyseally. To optimize the tension-free position of the tape, a urethral catheter of 18 Charrière was entered and the tape was slightly adjusted. Finally, a urethral catheter of 14 Charrière was inserted and a vaginal tamponade was applied. The catheter and the tamponade were removed after 24 hours. Statistical analysis was conducted using SPSS Version 22. Normal distribution was tested using Shapiro-Wilk test and was rejected in some cases. Hence, the Wilcoxon-signed-rank test was applied for paired data, while for independent groups the Mann-Whitney U test was used instead. For dichotomous samples, Fisher's exact test was applied. To evaluate the interrater reliability of the sonographic parameters, the intraclass correlation coefficients (ICC) (two-way random, single measurements, and absolute agreement) were determined. To assess the relation between tape position and outcome, multivariable logistic regression (backward stepwise method) was performed, yielding adjusted odds ratio (OR) with 95% confidence interval (CI). A significance level of 0.05 was used. This study was performed according to the Declaration of Helsinki and approved by the local ethics commission (reference number EK085/11). 3. Results A total of 91 women underwent TOT procedure by the same surgeon who used a PVDF tape and applied the modified outside-in technique. However, 59 patients had to be excluded from analysis. That is, 41 patients (45.1%) had an incomplete outcome and sonographic data; furthermore, 18 patients (19.8%) had incomplete sonographic data. Therefore, a total of 32 patients (35.2%) were finally included in the analysis. Baseline characteristics are presented in Table 1. Measurements of the position of the TOT demonstrated ICC values of 0.85, 0.91, and 0.93 for slice number, TUD, and TSD, respectively (Table 2). These results indicate excellent agreement. Between day one postoperatively and follow-up examination, the slice number where the tape was found did not change significantly as shown in Table 3. Furthermore, neither the TUD nor the TSD varied significantly (Table 3). Cured and uncured patients did not differ in regard to age, vaginal delivery, and concomitant procedures. The follow-up time was significantly shorter in uncured patients (Table 1). As shown in Table 4, the slice number where the tape was found differed significantly between cured and uncured patients. In particular, at the postoperative control the median slice number in cured patients was 7 (range, 5–8) compared to 6 (range, 5–7) in uncured patients. At the follow-up control, the median slice number was 7 (range, 5–8) and 5.5 (range, 4–7) in cured and uncured patients, respectively. Hence, cured patients were characterized by a tape position that was more caudal, compared to uncured patients. In contrast, there were no remarkable differences regarding the TUD or TSD for both time points as seen in Table 4. We selected age, postoperative TUD, and postoperative slice number as covariates, whereas subjective cure was chosen as the dependent parameter of the logistic regression. As the result of the stepwise backward regression method, a tape positioned in a more caudal slice increased the probability of subjective cure by a factor of 4.2 (95% CI 1.04–17.00, P = 0.04) (Table 5). This holds for the range, namely, from slices 5 to 8, measured in our study group. 4. Discussion To our knowledge, this is the first study that describes the use of TUI for determining the position of the TOT. There are several studies analyzing the association between the position of the tape and the outcome in stress incontinent patients [2–9]. Most works measure the tape-symphysis pubis distance [2, 11, 12] on the midsagittal plane and, in addition, the tape position in relation to urethral length [2, 4–8, 11]. Our method simply requires counting the slices and search on the axial plane where the tape is seen dorsal to the urethra. As a major advantage, this approach is both fast and accurate, since it allows for an exact measurement of distances on the axial plane. TUI does not depend on provided single slice volumes [15] but allows the storage for later evaluation and the observation from any perspective. Our results demonstrate that our approach seems to be a reliable method with a high degree of accuracy as demonstrated by ICC values between 0.85 and 0.93. No significant differences were found between sonographic parameters at postoperative and at follow-up control which may indicate a negligible displacement of the tape over a median period of time of 321 days. Similarly, other authors found no tape displacement in TOT patients, but only in patients with tension-free vaginal tapes (TVT) after a 6-month period [9]. Considering TVT, Kociszewski et al. [7] found a ventrocranial movement of the tape over a 4-year period, whereas other authors [16] observed a minor caudal migration (1.7 mm over a 3-year period). Similar observations were presented by Dietz et al. [12, 17]. However, in our study the patients were not controlled after the same time period (Table 1). That is, there was a significant shorter follow-up interval in uncured patients. Therefore, future research is needed that more systematically addresses to which extent different measurement intervals affect the results obtained by the present study. In cured patients, the tape was typically placed at a more distal slice, most frequently at slice number 7, which is located 24 mm below the MUI. Assuming a urethral length of 40 mm, these results correspond to related findings that determine the lower middle and distal section as an optimal target position of the tape [2, 4, 8, 18]. Since our measurement technique does not consider the urethral length, a direct comparison with these works cannot be conducted, though. In this study, we did not find an association between outcome and the TUD. Recent studies have shown that a distance smaller than 2 mm or larger than 5 mm correlates with de novo urgency symptoms and voiding problems [8]. In our cohort, most tapes were implanted within the recommended range [8] of the tape-urethra distance (postoperative: 0.45 ± 0.11, follow-up: 0.43 ± 0.12) in both cured and uncured patient groups. This could be a reason for the observation that the TUD did not correlate with outcome in our study. Furthermore, in our study the outcome and the TSD did not correlate. Other works [3, 11] report on better outcome given a smaller distance between tape and symphysis pubis. In our study, these distances are stable at 2 cm (postoperative: 2.09 ± 0.23; follow-up: 2.00 ± 0.35) similarly as in [2]. Different types of surgery techniques, follow-up time, and types of tapes are, among others, factors that hinder a direct comparison of the literature and might explain the diversity of published results [1]. Most surgeons use polypropylene as tape material. However, we selected PVDF tapes that consist of a monofilament sling with an excellent biocompatibility, thereby resulting in minimal foreign body reaction and optimal ingrowth [19, 20]. TOT, and in particular PVDF tapes [19], show no shift or only a negligible one during straining [9, 19, 21]. Hence, we considered it sufficient to perform the sonographic measurements while the patients were at rest. Our study has further inherent limitations. We did not exclude concomitant surgery. However, the cases were equally distributed across the outcome groups. Furthermore, we applied a new incision for each surgery to repair the anterior or posterior vaginal wall. However, the incision is located in a more cranial position than the tape and should not interfere with the latter [22]. Same as other authors [2], we selected subjective definitions as outcome parameter, which delivers information about the patient's satisfaction over time. More objective tests, such as stress test and urodynamic testing, provide only instantaneous information [2]. Furthermore, our dropout rate was rather high. Patients with incomplete outcome or sonographic data were excluded. Incomplete sonographic data reflects cases where data, either postoperative or at follow-up, was not found in our database. The reasons are generally not known due to the retrospective nature of the study. Partly, we assume errors during the storage of the data. In some cases, patients left the hospital before having conducted the postoperative ultrasound. In a significant number of cases, patients did not show up for a (recommended) follow-up examination despite our efforts of contacting them. As our goal was to have a homogenous group of patients, we excluded those patients for whom either postoperative or follow-up data was missing. Finally, the number of included patients is rather low. Therefore, we regard the present study as a pilot study. Nevertheless, the fact that we obtained significant differences in the slice number between uncured and cured patients despite the small sample size argues against a low statistical power of our study. As future work, prospective studies are planned to confirm these results. Competing Interests The authors declare that there are no competing interests regarding the publication of this paper. Figure 1 Perineal ultrasound image on midsagittal plane from a patient at rest with a tension-free transobturator tape (TOT). The positions of symphysis pubis (S), bladder (B), meatus urethrae internus (MUI), urethra (U), and vagina (V) are indicated. Figure 2 Using tomographic ultrasound imaging (TUI), 9 parallel slices are obtained (upper left figure showing the midsagittal view). The uppermost slice is placed at the meatus urethrae internus (MUI). In caudal direction eight further slices are obtained with a 4 mm interslice distance. The line marked with the symbol ☆ refers to slice number 7. This slice is shown in Subfigure 7 on the axial plane. Here, the major part of the tape is seen dorsal to the urethra. Figure 3 As already shown in Figure 2, tomographic ultrasound imaging (TUI) on midsagittal plane provides a set of slices (a). Here, the bold highlighted slice is represented on axial plane in (b). This view facilitates the accurate location of the tape and the measurement of distances. In particular, the image illustrates the distance between the anterior margin of the tape and the longitudinal smooth muscle (LSM) complex of the urethra (1) and the distance between the anterior margin of the tape and the inferior margin of the symphysis pubis (2). Table 1 Baseline characteristics of the study group and compared between the two outcome groups. Stress urinary incontinence (SUI). The results are given as counter (percentage) or median (range). ∗Fisher's exact or Mann-Whitney U test as appropriate, two-sided P value < 0.05 as significant. Parameter Total (n = 32) Uncured from SUI (n = 6) Cured from SUI (n = 26) P value∗ Age 55 (34–81) 54 (37–77) 57 (34–81) ns Rectocele 4 (12.5) 1 (16.7) 3 (11.5) ns Anterior wall prolapse 9 (28.1) 2 (33.3) 7 (26.9) ns Descensus uteri 4 (12.5) 1 (16.7) 3 (11.5) ns Nullipara 2 (6.3) 0 (0.0) 2 (9.1) ns Concomitant surgery 6 (18.8) 1 (16.7) 5 (28) ns Follow-up time 321 (101–1905) 225 (51–370) 453 (123–1905) 0.04 Table 2 Intraclass correlation coefficient (ICC) (two-way random, single measurements, and absolute agreement). 95% confidence interval (CI). Distance between the anterior margin of the TOT and the inferoposterior margin of symphysis pubis (TSD). Distance between the anterior margin of the TOT and the longitudinal smooth muscle (LSM) complex of the urethra (TUD). Parameter ICC 95% CI P value Slice number 0.85 0.75–0.91 <0.001 TSD 0.91 0.84–0.95 <0.001 TUD 0.93 0.88–0.96 <0.001 Table 3 Comparison of sonographic parameters between postoperative and follow-up examinations. The results are given as median (range). Distance between the anterior margin of the TOT and the inferoposterior margin of the symphysis pubis (TSD). Distance between the anterior margin of the TOT and the longitudinal smooth muscle (LSM) complex of the urethra (TUD). ∗Wilcoxon-signed-rank test.   Postoperative Follow-up P value∗ Slice number 7 (5–8) 7 (4–8) 0.11 TSD 2.09 (1.64–2.50) 2.0 (1.15–2.60) 0.30 TUD 0.46 (0.24–0.74) 0.43 (0.26–0.74) 0.22 Table 4 Comparison of sonographic parameters between cured and uncured patients. The results are given as median (range). Distance between the anterior margin of the TOT and the inferoposterior margin of the symphysis pubis (TSD). Distance between the anterior margin of the TOT and the longitudinal smooth muscle (LSM) complex of the urethra (TUD). ∗Mann-Whitney U test. Outcome Uncured (n = 6) Cured (n = 26) P value∗ Postoperative       Slice number 6 (5–7) 7 (5–8) 0.05 TSD 1.9 (1.76–2.35) 2.1 (1.64–2.50) 0.33 TUD 0.41 (0.24–0.51) 0.47 (0.28–0.74) 0.17 Follow-up       Slice number 5.5 (4–7) 7 (5–8) 0.05 TSD 1.8 (1.49–2.24) 2.03 (1.15–2.60) 0.14 TUD 0.41 (0.34–0.46) 0.43 (0.26–0.76) 0.94 Table 5 Results of the stepwise backward logistic regression, odds ratio (OR), and distance between the anterior margin of the TOT and the longitudinal smooth muscle (LSM) complex of the urethra (TUD).   Age TUD Slice number   OR P value OR P value OR P value Step 1 1.01 0.851 48.18 0.46 3.51 0.09 Step 2     52.63 0.45 3.58 0.08 Step 3         4.20 0.04 ==== Refs 1 Fong E. D. M. Nitti V. W. Mid-urethral synthetic slings for female stress urinary incontinence BJU International 2010 106 5 596 608 10.1111/j.1464-410X.2010.09544.x 2-s2.0-77955905905 21050350 2 Yang J.-M. Yang S.-H. Huang W.-C. Tzeng C.-R. Correlation of tape location and tension with surgical outcome after transobturator suburethral tape procedures Ultrasound in Obstetrics and Gynecology 2012 39 4 458 465 10.1002/uog.10086 2-s2.0-84862799795 21919102 3 Torella M. De Franciscis P. Russo C. Stress urinary incontinence: usefulness of perineal ultrasound Radiologia Medica 2014 119 3 189 194 10.1007/s11547-013-0317-4 2-s2.0-84898027486 24557982 4 Bogusiewicz M. Monist M. Gałczyński K. Woźniak M. Wieczorek A. P. Rechberger T. Both the middle and distal sections of the urethra may be regarded as optimal targets for ‘outside-in’ transobturator tape placement World Journal of Urology 2014 32 6 1605 1611 10.1007/s00345-014-1261-1 2-s2.0-84912030305 24531879 5 Jiang Y.-H. Wang C.-C. Chuang F.-C. Ke Q.-S. Kuo H.-C. Positioning of a suburethral sling at the bladder neck is associated with a higher recurrence rate of stress urinary incontinence Journal of Ultrasound in Medicine 2013 32 2 239 245 2-s2.0-84874143737 23341378 6 Kociszewski J. Rautenberg O. Perucchini D. Tape functionality: sonographic tape characteristics and outcome after TVT incontinence surgery Neurourology and Urodynamics 2008 27 6 485 490 10.1002/nau.20556 2-s2.0-50849141346 18288705 7 Kociszewski J. Rautenberg O. Kolben S. Eberhard J. Hilgers R. Viereck V. Tape functionality: position, change in shape, and outcome after TVT procedure-mid-term results International Urogynecology Journal and Pelvic Floor Dysfunction 2010 21 7 795 800 10.1007/s00192-010-1119-z 2-s2.0-77952969028 8 Kociszewski J. Rautenberg O. Kuszka A. Eberhard J. Hilgers R. Viereck V. Can we place tension-free vaginal tape where it should be? 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==== Front Can J Gastroenterol HepatolCan J Gastroenterol HepatolCJGHCanadian Journal of Gastroenterology & Hepatology2291-27892291-2797Hindawi Publishing Corporation 10.1155/2016/5210902Letter to the EditorResponse to: Comment on “Evaluation of Antiviral Therapy Performed after Curative Therapy in Patients with HBV-Related Hepatocellular Carcinoma: An Updated Meta-Analysis” Yuan Peng http://orcid.org/0000-0002-0010-1165Qian Yeben * Chen Peng Department of Hepatobiliary Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China*Yeben Qian: qianyeben@hotmail.comAcademic Editor: Eric M. Yoshida 2016 16 8 2016 2016 521090229 3 2016 7 4 2016 Copyright © 2016 Peng Yuan et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ==== Body Thanks are due to you for this letter and we would like to respond regarding some questions raised about our meta-analysis. In this letter, the authors questioned the index used in the meta-analysis and recommended hazard ratio (HR) instead of relative risk (RR) [1]. HR is truly a good index for survival analysis of one disease because it considers the effects of time and it worked when extracting data from studies we selected; however, RR is appropriate for comparing the control group and treatment group (NAs group) here, as it has equal effects to OR. The total number of patients was the same only in 1-year and 3-year recurrence, but, in OS and DFS, the numbers were different [2]. Disease-free survival has been defined as no recurrence of HCC in our article [2]. Randomized trials were really what we wanted to study in our meta-analysis; however, due to a lack of enough studies and data, this was unfortunately not possible [2]. We are not sure if postoperative NAs therapy has no impact on patients' short-term survival, for the reason that HBV reactivation usually occurs one month after operations were performed [3], so that is why we performed this meta-analysis. And as our results show, we do not agree with the comment that NAs have no short-term effects on survival and recurrence [1]. We would like to thank again the authors for this valuable letter and also for their concerns. We would like to receive further suggestions on our study. Competing Interests The authors declare that they have no competing interests. ==== Refs 1 Mo H.-Y. Xiang B.-D. Zhong J.-H. Li L.-Q. You X.-M. Comment on ‘evaluation of antiviral therapy performed after curative therapy in patients with HBV-related hepatocellular carcinoma: an updated meta-analysis’ Canadian Journal of Gastroenterology and Hepatology 2016 2016 2 7625982 10.1155/2016/7625982 2 Yuan P. Chen P. Qian Y. Evaluation of antiviral therapy performed after curative therapy in patients with HBV-related hepatocellular carcinoma: an updated meta-analysis Canadian Journal of Gastroenterology and Hepatology 2016 2016 11 5234969 10.1155/2016/5234969 3 Kubo S. Takemura S. Tanaka S. Management of hepatitis B virus infection during treatment for hepatitis B virus-related hepatocellular carcinoma World Journal Gastroenterology 2015 21 27 8249 8255 10.3748/WJG.v21.i27.8249

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==== Front Biomed Res IntBiomed Res IntBMRIBioMed Research International2314-61332314-6141Hindawi Publishing Corporation 10.1155/2016/1358142Research ArticleOptimization to the Culture Conditions for Phellinus Production with Regression Analysis and Gene-Set Based Genetic Algorithm Li Zhongwei 1 Xin Yuezhen 1 Wang Xun 1 2 Sun Beibei 1 Xia Shengyu 2 Li Hui 2 http://orcid.org/0000-0002-0478-6392Zhu Hu 2 * 1College of Computer and Communication Engineering, China University of Petroleum, Qingdao, Shandong 266580, China2Center for Bioengineering and Biotechnology, China University of Petroleum, Qingdao, Shandong 266580, China*Hu Zhu: zhuhu@upc.edu.cnAcademic Editor: Quan Zou 2016 16 8 2016 2016 135814228 5 2016 11 7 2016 16 7 2016 Copyright © 2016 Zhongwei Li et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Phellinus is a kind of fungus and is known as one of the elemental components in drugs to avoid cancers. With the purpose of finding optimized culture conditions for Phellinus production in the laboratory, plenty of experiments focusing on single factor were operated and large scale of experimental data were generated. In this work, we use the data collected from experiments for regression analysis, and then a mathematical model of predicting Phellinus production is achieved. Subsequently, a gene-set based genetic algorithm is developed to optimize the values of parameters involved in culture conditions, including inoculum size, PH value, initial liquid volume, temperature, seed age, fermentation time, and rotation speed. These optimized values of the parameters have accordance with biological experimental results, which indicate that our method has a good predictability for culture conditions optimization. National Natural Science Foundation of China4127613531172010612720936132010600561402187615025356157252261572523Program for New Century Excellent Talents in UniversityNCET-13-1031863 Program2015AA020925Fundamental Research Funds for the Central UniversitiesR1607005AChina Postdoctoral Science Foundation2016M592267 ==== Body 1. Introduction Phellinus is a kind of fungus having great medicinal value, since it is known as one of the elemental components in drugs with functions of avoiding cancers [1, 2]. Phellinus flavonoids are one of the most popular parasitifers of Phellinus in nature [3], and the research on Phellinus focuses on polysaccharides, proteoglycans medicinal mechanism, composition, and so forth, which are mostly extracted from the fruiting bodies of Phellinus flavonoids [4]. Phellinus rarely exists in the wild environment [5], and it becomes a promising research branch to cultivate it in the laboratory. With mycelial growth by liquid fermentation, the fermentation broth flavonoids, polysaccharides, alkaloids, and other active substances can be produced, which have high level physical activity, short fermentation period, and mass productions, thus providing a possible way of producing Phellinus in the laboratory [6]. In recent years, updated machine learning approaches (see, e.g., [7, 8]) have been developed and applied in biological data processing. From the understanding of the wild conditions of Phellinus, it is believed that PH value, temperature, and fermentation time have effect on the productions. Also, in general biochemical experiments, we need to consider the inoculum size, initial liquid volume, seed age, and rotation speed. In the laboratory, plenty of experiments have been designed and operated for maximizing the Phellinus production. The methods can be separated into two major groups.With biological technologies: it used optimum media on mycelial growth of Phellinus in [9] and liquid fermentation technology to cultivate Phellinus in [10]. Active ingredients in Phellinus and polysaccharide metabolism regulation are designed in [11]. With mathematical models: some researches focus on building mathematical models for the progress of producing Phellinus by differential equations [12], metabolic path and network [13], and complex network models [14]. Artificial algorithms and models have been used in the bioprocess, particularly for the optimization of culture conditions. In [15], artificial neural network (ANN) is used to optimize the extraction process of azalea flavonoids. Neural networks combined with evolutionary algorithms have been used to optimize the experimental environment, such that neural network and particle swarm optimization method were used for finding optimized culture conditions to maximize the production of Pleuromutilin from Pleurotus mutilus in [16]. Recently, with the increment of biological data, regression analysis becomes a useful tool for the data analysis. In [17] the method of fitting models to biological data using linear and nonlinear regression is proposed, where some multivariate statistical analysis strategies from [18, 19] are formulated to be helpful and useful for biologists. These results give us hints of using regression analysis and artificial algorithms to optimize the culture conditions for Phellinus production. And, to the best of our knowledge, few work focuses on the optimization of culture conditions to maximize the production of Phellinus in the laboratory. In this work, we start from operating 45 experiments for producing Phellinus from Phellinus flavonoids with different culture conditions, involving parameters PH value, temperature and fermentation time, inoculum size, initial liquid volume, seed age, and rotation speed. With the data collected during the experiments, we use regression analysis method to create a mathematical model, which can forecast the flavonoid yield and the most important element to the production of Phellinus. After that, a gene-set based genetic algorithm (GA) is proposed to optimize the culture condition, where the obtained mathematic model is used as fitness function for the evolution of individuals. Data experimental results show that predicted optimal values of the parameters have accordance with biological experimental results, which indicate that our method has a good predictability for culture conditions optimization. 2. Data Collected from Experiments In this section, biological experiments are performed for finding optimal value of certain single factor. In Table 1, experiments are operated for collecting data. In rows 1–14, it is associated with experiments with PH values ranging from 1 to 14, where the temperature is fixed to 28°C, initial volume is set to be 100 mL, the rotation speed is 140 r/m, and seed age is 8 days. Rows 15 to 20 are 6 experiments with initial volume ranging from 40 mL to 140 mL, where PH value is set to be 6, the best one obtained from experiments with PH values ranging from 1 to 14. In Table 2, experiments with including inoculum ranging from 2% to 16% and temperature ranging from 25°C to 40°C are performed. In Table 3 the situations on experiments with fermentation time ranging from 1 to 12 hours are shown. From the in total 45 experiments, we collect data of culture conditions for production of Phellinus. Different culture conditions have a fundamental influence on the production of Phellinus, but the optimized culture conditions remain unknown. 3. Methods We consider here using regression analysis and gene-set based genetic algorithm to find the optimized culture conditions for maximizing the production of Phellinus. In general, we convert the data collected in Section 2 to construct a mathematical model by regression analysis. And then, the obtained model can be used as fitness function for optimizing the culture condition with gene-set based genetic algorithm. 3.1. Regression Analysis In statistical modeling, regression analysis is a statistical process for estimating the relationships among variables [20]. Regression analysis is one of the extremely versatile data analysis methods, which is appropriated to establish dependencies between variables based on observational data and widely used to analyze the data inherent law and to predict the result. Regression analysis can be divided into linear regression and nonlinear regression analysis [21], according to the type of relationship between the independent variables and dependent variables. In general, the relationship between variables is determined by the independent variables and dependent selected variables, by which regression models can be made. After that, it is used to solve the various parameters of the model based on the measured data and then evaluate whether the regression model can fit the observed data. If the model can fit the data well, then the model can be used to further predict based arguments [22]. The regression analysis is composed of the following steps [23, 24]. Regression analysis is widely used in data mining, particularly for biological data analysis in recent years, with the purpose of finding a feasible statistical law by the large amount of data of experiments. The general process is given as follows. Step 1 . Determine the variables. Step 2 . Establish the prediction model. Step 3 . Relate analysis. Step 4 . Calculate the prediction error. Step 5 . Determine the predicted value. From the data collected in Section 2, it consists of seven independent variables and one dependent variable. The seven independent variables are inoculum size, PH values, initial liquid volume, temperature, seed age, fermentation time, and rotation speed. And, the dependent variable is flavonoid yield. From the observation of the experiments, it is found that some culture conditions are not suitable for production of Phellinus. These data are taken as extreme data are removed from regression analysis. Extreme data refers to the data which were measured in extreme experimental environment. Also duplicate data were cancelled. Only the following data are selected in regression analysis.Inoculum size 0.5%~1.2%. PH 5~7. Initial liquid volume 60~100 mL. Temperature 25~30°C. Seed age 4~9 days. Fermentation time 6~12 days. Rotation speed 140~200 r/m. After data filtering, a statistical model is made to represent these data. It is known that there is a correlation between these data relationships, so we applied linear regression analysis to fit them. At this stage, a lot of models were tested one by one with IBM SPSS software and response surface methodology. The statistical model is Y = A1∗X 2(1)+⋯+A7∗X 2(7) + B1∗X(1)∗X(2) + B2∗X(1)∗X(3) + B3∗X(1) ∗   X(4) + B4∗X(1)∗X(5) + B5∗X(1)∗X(6) + B7∗X(1)∗X(7) + B8∗X(2)∗X(3) + B9∗X(2)∗X(4) +  B10∗X(2)∗X(5) + B11∗X(2)∗X(6) + B12∗X(2)∗X(7) + B13∗X(3)∗X(4) + B14∗X(3)∗X(5) +  B15∗X(3)∗X(6) + B16∗X(3)∗X(7) + B17∗X(4)∗X(5) + B18∗X(4)∗X(6) + B19∗X(4)∗X(7) +  B20∗X(5)∗X(6) + B21∗X(5)∗X(7) + B22∗X(6)∗X(7) + C, where Y is a dependent variable of the flavonoid yield, X(1), X(2),…, X(7) are the seven independent variables associated with inoculum size, PH value, initial liquid volume, temperature, seed age, fermentation time, and rotation speed, respectively, and A, B, and C are real numbers. Although the relationship between the data may not be linear, we can put squared term for a type of data into these data. If this term is useful it will be retained after linear regression analysis; otherwise, the data will be deleted. In the regression analysis, it needs to focus on the values of R-squared and the significance of correlation coefficients for regulating the model. We use the regression analysis tools in the IBM SPSS, setting regression coefficients as estimated (E) and selecting the display model fit (M). Set the stepping method criteria as use of probability F, entry (E) as 0.5, and removal (M) as 0.10. After regression analysis, we can get the results as shown in Table 4. It is obtained that significance = 0.006 < 0.05; that is, the regression results are obvious. R-squared value is 0.88, which means that the model is valid for fitting the 88% data. We get the statistical model: Y = 3662.278∗x(1) − 4263.361∗(x(1)2) + 11737.986∗x(2) − 999.556∗x(2)2 − 0.238∗x(3)2 + 3353.461 ∗  x(4) − 59.662∗x(4)2 − 420.854∗x(5) + 42.495∗x(5)2 + 966.796∗x(6) − 53.489∗x(6)2 + 27.213∗x(7)  − 0.234∗x(7)2 + 0.434∗x(3)∗x(7) − 86781.046. 3.2. Gene-Set Based Genetic Algorithm Genetic algorithm (GA) was first proposed by J. Holland in 1975 [25, 26], whose general process is shown in Figure 1. In the mutation operation, if a short segment is selected in a mutation possibility and replaced by another segment, then the gene-set based GA is achieved [27]. In gene-set based GA, a chromosome is treated as a set of gene-sets, instead of a set of genes as in classical GAs. It starts with gene-sets of the largest size equal to half the chromosome length. It is most appropriate to genetics model because each gene-set represents a set of adjacent parameters of certain factor of the culture conditions. It is noted that, in the selection, only the winning individuals from the population can be selected. Select operators are also known as reclaimed operator (reproduction operator), whose purpose is to optimize the selection of individuals (or solutions) to the next generation. Population can be updated by fitness ratio method and random sampling method to traverse, local selection. Cross operator refers to the part of the structure of the two parent individuals to generate new recombinant replacing individual operation. Variation is to make GA have local random search capability. When the GA crossover neighborhood is close to the optimal solution, the use of such a mutation operator of local random search capability can accelerate the convergence to the optimal solution. The statistical model obtained by regression analysis is used as the fitness function here, and gene-set based GA is used to optimize the culture condition for maximizing the production of Phellinus. The data simulation is achieved by gatool in MATLAB. In the data experiments, we use a binary string composed of 7 segments to represent an individual in GA population, where each segment is associated with the value of one of the 7 parameters for the culture condition. Initial population size is 50, and cross rate is set to 0.8. Mutation rate is set to be 0.01, and selection method is roulette wheel selection. If the time is long enough then the GA process will halt by meeting the stopping conditions, such as generations limit or fitness limit. After 156 iterations the gene-set based GA process returns the best individual and shuts down the process in Figure 2. After the regression analysis and GA process, an optimized culture condition is obtained, shown in Table 5. The results obtained by our method have accordance with experimental experience in literature of Phellinus growth environmental studies. Specifically, the suitable environment is neutral acidic environment, about PH value 6. The appropriate temperature range is from 22°C to 28°C [10]. Seed age and fermentation time of species vary due to the strain [3, 28, 29]. These optimized values of the parameters have accordance with biological experimental results, which indicate that our method has a good predictability for culture conditions optimization. 4. Conclusion In this work, 45 experiments are firstly operated for collecting data related to the production of Phellinus from Phellinus flavonoids. We use regression analysis method to create a mathematical model with the collected data, and then a gene-set based GA is proposed to optimize the culture condition, where the obtained mathematic model is used as fitness function for the evolution of individuals. In the comparison results, it is believed that PH value is credible and the temperature is also within the appropriate temperature range. Taking into account environmental factors in the laboratory, the temperature value we predicted is also reliable. The seed age and fermentation time predicted are 9, close to the original data 8. Data experimental results show that predicted optimal values of the parameters have accordance with biological experimental results, which indicate that our method has a good predictability for culture conditions optimization. Neural-like computing models, such as artificial neural networks [30], spiking neural networks [31], and spiking neural P systems [32–34], have been successfully used in pattern recognition and engineering practice. It is of interest to use these neural-like computing models for optimizing culture conditions for Phellinus production. Our work would also guide for the “Precision Medicine” with personal SNP data [35] and other tasks in bioinformatics [21, 22]. Acknowledgments The research is under the auspices of National Natural Science Foundation of China (nos. 41276135, 31172010, 61272093, 61320106005, 61402187, 61502535, 61572522, and 61572523), Program for New Century Excellent Talents in University (NCET-13-1031), 863 Program (2015AA020925), Fundamental Research Funds for the Central Universities (R1607005A), and China Postdoctoral Science Foundation funded project (2016M592267). Competing Interests The authors declare that they have no competing interests. Figure 1 GA process. Figure 2 GA best fitness. Table 1 Experiments with PH values ranging from 1 to 14 and initial volume ranges from 40 mL to 140 mL. Phellinus production PH Temp. Initial volume Rotation speed Including inoculum Seed age Fermentation time 45.929 1 28°C 100 mL 140 5% 8 8 35.077 2 28°C 100 mL 140 5% 8 8 45.654 3 28°C 100 mL 140 5% 8 8 534.39 4 28°C 100 mL 140 5% 8 8 702.81 5 28°C 100 mL 140 5% 8 8 1467.7 6 28°C 100 mL 140 5% 8 8 189.20 7 28°C 100 mL 140 5% 8 8 91.049 8 28°C 100 mL 140 5% 8 8 60.841 9 28°C 100 mL 140 5% 8 8 57.255 10 28°C 100 mL 140 5% 8 8 43.238 11 28°C 100 mL 140 5% 8 8 36.288 12 28°C 100 mL 140 5% 8 8 20.943 13 28°C 100 mL 140 5% 8 8 22.306 14 28°C 100 mL 140 5% 8 8 508.495 6 28°C 40 mL 140 10% 8 8 900.662 6 28°C 60 mL 140 10% 8 8 1273.594 6 28°C 80 mL 140 10% 8 8 1153.937 6 28°C 100 mL 140 10% 8 8 1123.330 6 28°C 120 mL 140 10% 8 8 1088.064 6 28°C 140 mL 140 10% 8 8 Table 2 Experiments with including inoculum ranging from 2% to 16% and temperature ranging from 25°C to 40°C. Phellinus production PH Temp. Initial volume Rotation speed Including inoculum Seed age Fermentation time 546.609 6 28°C 100 mL 140 2% 8 8 606.345 6 28°C 100 mL 140 4% 8 8 1320.794 6 28°C 100 mL 140 6% 8 8 1447.519 6 28°C 100 mL 140 8% 8 8 1841.729 6 28°C 100 mL 140 10% 8 8 1631.990 6 28°C 100 mL 140 12% 8 8 481.1172 6 28°C 100 mL 140 14% 8 8 449.5187 6 28°C 100 mL 140 16% 8 8 1145.669 6 25°C 40 mL 140 10% 8 8 1506.055 6 30°C 60 mL 140 10% 8 8 1374.982 6 35°C 80 mL 140 10% 8 8 875.341 6 40°C 100 mL 140 10% 8 8 Table 3 Experiments with fermentation time ranging from 1 to 12 hours. Phellinus production PH Temp. Initial volume Rotation speed Including inoculum Seed age Fermentation time 56.606 6 28°C 100 mL 150 2% 8 1 83.435 6 28°C 100 mL 150 4% 8 2 303.984 6 28°C 100 mL 150 6% 8 3 449.919 6 28°C 100 mL 150 8% 8 4 777.331 6 28°C 100 mL 150 10% 8 5 1103.987 6 28°C 100 mL 150 12% 8 6 1619.554 6 28°C 100 mL 150 14% 8 7 1597.995 6 28°C 100 mL 150 16% 8 8 1546.336 6 28°C 100 mL 150 10% 8 9 1502.487 6 28°C 100 mL 150 10% 8 10 1489.364 6 28°C 100 mL 150 10% 8 11 1465.664 6 28°C 100 mL 150 10% 8 12 Table 4 Regression analysis results.   Sum of square df Mean square F R R-squared Standard error Regression 3796787.42 14 249770.53 5.234 0.93 0.88 218.48 Residuals 47719.89 10 47719.54         Sum 3973983.26 24           Table 5 Optimized culture conditions. Type Experiment data Computer data Inoculum size 10% 12%  PH 6 5.8 Initial liquid volume 100 mL 100 mL Temperature 28°C 28°C Age 8 9 Fermentation time 8 9 Rotation speed 150 150 Flavonoid yield 2164.512 2150.128 ==== Refs 1 Zhu T. Guo J. Collins L. 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==== Front Gastroenterol Res PractGastroenterol Res PractGRPGastroenterology Research and Practice1687-61211687-630XHindawi Publishing Corporation 10.1155/2016/3481578Research ArticlePrognostic Impact of mRNA Expression Levels of HER1–4 (ERBB1–4) in Patients with Locally Advanced Rectal Cancer Kripp Melanie 1 Merx Kirsten 1 Wirtz Ralph Markus 2 Gaiser Timo 3 Eidt Sebastian 2 Schwaab Juliana 1 Post Stefan 4 Wenz Frederik 5 Hochhaus Andreas 6 http://orcid.org/0000-0001-5972-8504Hofheinz Ralf-Dieter 1 http://orcid.org/0000-0002-8279-7636Erben Philipp 7 * 1III. Medizinische Klinik, Universitätsmedizin Mannheim, 68167 Mannheim, Germany2Stratifyer Molecular Pathology GmbH, 50935 Köln, Germany3Pathologisches Institut, Universitätsmedizin Mannheim, 68167 Mannheim, Germany4Chirurgische Klinik, Universitätsmedizin Mannheim, 68167 Mannheim, Germany5Klinik für Strahlentherapie und Radioonkologie, Universitätsmedizin Mannheim, 68167 Mannheim, Germany6Abteilung Hämatologie/Onkologie, Universitätsklinikum Jena, 07747 Jena, Germany7Klinik für Urologie, Universitätsmedizin Mannheim, 68167 Mannheim, Germany*Philipp Erben: philipp.erben@medma.uni-heidelberg.deAcademic Editor: Haruhiko Sugimura 2016 16 8 2016 2016 348157827 5 2016 19 7 2016 Copyright © 2016 Melanie Kripp et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. No predictive or prognostic biomarker is available for patients with locally advanced rectal cancer (LARC) undergoing perioperative chemoradiotherapy (CRT). Members of the human epidermal growth factor receptor (HER) family of receptor tyrosine kinases EGFR (HER1, ERBB1), HER2 (ERBB2), HER3 (ERBB3), and HER4 (ERBB4) are therapeutic targets in several cancers. The analysis was performed to assess expression levels and study the potential prognostic impact for disease-free and overall survival in patients with LARC. Patients and Methods. ERBB1–4 mRNA expression and tumor proliferation using Ki-67 (MKI67) mRNA were evaluated using RT-quantitative PCR in paraffin-embedded tumor samples from 86 patients (median age: 63) treated with capecitabine or 5-fluorouracil-based CRT within a phase 3 clinical trial. Results. A positive correlation of HER4 and HER2, HER3 and HER2, and HER4 and HER3 with each other was observed. Patients with high mRNA expression of ERBB1 (EGFR, HER1) had significantly increased risk for recurrence and death. Patients with high mRNA expression of MKI67 had reduced risk for relapse. Conclusion. This analysis suggests a prognostic impact of both ERBB1 and MKi67 mRNA expression in LARC patients treated with capecitabine or fluorouracil-based chemoradiotherapy. ==== Body 1. Introduction Rectal cancer is the fifth most common type of cancer in adults worldwide [1]. Although surgery may be curative in locally advanced disease, local recurrence and metastases occur despite complete resection. Until the late 1980s, the rate of local recurrence and distant metastases following curative surgery was about 30% [2]. The outcome of locally advanced rectal cancer (LARC) has significantly improved due to the combination of optimized surgical techniques, notably total mesorectal excision (TME) with neoadjuvant radio- and radiochemotherapy [3–5]. By using this treatment modality, 10-year cumulative local recurrence rate is generally below 10%. On the other hand, fluorouracil in conjunction with neoadjuvant long-term radiotherapy reduces local recurrences but does not prolong overall survival (OS) [6, 7]. Nowadays, distant metastases represent the most common type of treatment failure in rectal cancer indicating the need for optimized systemic medical treatment such as modifications of perioperative bolus 5-fluorouracil (5-FU) treatment. However, neither biomodulation of fluorouracil nor combinations with older cytostatic drugs have clearly proved advantage compared to bolus 5-FU [8]. Only administering 5-FU as continuous infusion during radiation led to improved survival and increased time to relapse [9]. Likewise, the addition of oxaliplatin to perioperative fluorouracil treatment has given diverging results in five clinical trials [10, 11]. Altogether, the identification of patients being at high risk for distant metastases still represents a major challenge to tailor the management of rectal cancer therapy. For patients with resected rectal cancer—in addition to the adequacy of surgical excision (evaluated by the circumferential resection margins)—the TNM classification is still the most reliable indicator of risk for systemic recurrence [12]. However, for patients scheduled to undergo neoadjuvant chemoradiotherapy clinical stratification (e.g., with MRI scan) has limitations especially in view of the inability to exactly predict the nodal status. Risk stratification based on molecular markers could provide better estimate of individual risk and tailored treatment. In this regard, especially molecular markers bearing the potential to serve as therapeutic targets for medical treatment are indispensable. Several drugs are licensed or in clinical evaluation for the treatment of tumors expressing human epidermal growth factor tyrosine kinase receptors (EGFR). Besides EGFR, which is encoded by the ERBB1 gene, the human epidermal growth factor receptor (HER) family of receptor tyrosine kinases includes three additional members: HER2 (ERBB2), HER3 (ERBB3), and HER4 (ERBB4). Activation of the HER signaling network has been shown to promote tumor invasion and metastasis both in vitro [13–16] and in vivo [17, 18]. Mutations and overexpression of HER family genes are frequently present in rectal cancer. For instance, a higher rate of HER2 amplification in high grade tumors was reported, and EGFR and HER3 mRNA expression was described to be associated with the occurrence of metastases in patients with LARC [19]. Here, we sought to evaluate (a) the mRNA expression of ERBB1–4 in pretreatment tumor tissue, (b) the correlation of expression of each receptor along with tumor cell proliferation using MKI67 mRNA expression in patients with LARC treated with 5-FU-based chemoradiotherapy, and (c) the impact of these markers on prognosis. 2. Material and Methods Patient Cohort. Tumor tissue for this study stemmed from patients participating in a phase III clinical trial conducted at the University Hospital of Mannheim between 2002 and 2007. These patients had histologically confirmed LARC (adenocarcinoma, cT3-4, any N or cT2, N+). This noninferiority trial compared 5-FU with the oral 5-FU prodrug capecitabine for the perioperative treatment of LARC. Details of the study protocol and the results have been published previously [20]. In brief, the trial began in 2002 as an adjuvant trial comparing capecitabine-based chemoradiotherapy with fluorouracil-based chemoradiotherapy. Patients in the capecitabine group were scheduled to receive two cycles of capecitabine, followed by chemoradiotherapy (50.4 Gy plus capecitabine 1650 mg/m2), then three cycles of capecitabine. Patients in the fluorouracil group received two cycles of bolus fluorouracil followed by chemoradiotherapy (50.4 Gy plus infusional fluorouracil 225 mg/m2 daily), then two cycles of bolus fluorouracil. The protocol was amended in 2005, to allow a neoadjuvant cohort in which patients in the capecitabine group received chemoradiotherapy followed by TME surgery and five cycles of capecitabine and patients in the fluorouracil group received chemoradiotherapy (50.4 Gy plus infusional fluorouracil 1000 mg/m2 days 1–5 and 29–33) followed by surgery and four cycles of bolus fluorouracil. Patients were randomly assigned to treatment groups in a 1 : 1 ratio. The primary endpoint was overall survival. Noninferiority of capecitabine in terms of 5-year overall survival was tested. 392 patients were evaluable with a median follow-up of 52 months. Five-year overall survival in the capecitabine group was noninferior to that in the fluorouracil group (76% [95% CI 67–82] versus 67% [58–74]; p = 0.0004). Similar numbers of patients had local recurrences in each group 12 [6%] in the capecitabine group versus 14 [7%] in the fluorouracil group, p = 0.67. All patients providing tumor tissue for the current analysis were treated at a single center (University Hospital Mannheim, University of Heidelberg). Both the clinical study protocol and the molecular investigations reported here were approved by the local ethics committee. 2.1. RNA Isolation from Formalin-Fixed Paraffin-Embedded (FFPE) Tissue and Quantitative Reverse Transcription-Polymerase Chain Reaction (RT-qPCR) Assessment Fixation of tumor specimens followed standard protocols, 10% buffered formalin for at least 8 hours. Hematoxylin-eosin (HE) stained sections were evaluated for pathological stage according to the 2002 TNM classification of the American Joint Committee on Cancer classification. For molecular analyses, HE slides were reevaluated by an experienced pathologist (S.E.) for confirmation of the presence of invasive tumor. Each case was macrodissected for an invasive tumor areal comprising at least 30% of tumor cells. One 10 μm section was used for the isolation of RNA according to a fully automated, high-throughput extraction workflow which runs on an Xtract-XL liquid-handling robot (STRATIFYER Molecular Pathology GmbH, Cologne, Germany). The extraction solutions and chemicals are commercially available in Germany as part of the XTRAKT FFPE kit, which is based on magnetic bead technology (STRATIFYER) [21]. In brief, FFPE sections were solubilized and paraffin was melted by incubating with a lysis buffer in a Thermo-mixer. Tissue was lyzed with Proteinase K. The lysates were then admixed with germanium-coated magnetic particles in buffer-controlled conditions which enhance preferential attachment of nucleic acid molecules to the surface of the particles. Purification was carried out by means of 3 consecutive washing cycles involving magnetization, centrifugation, washing, and removal of the supernatant. Nucleic acids were eluted with 100 μL elution buffer and treated with DNase I. The DNA-free RNA eluates were stored at −80°C until use. One-step RT-qPCR was applied for the relative quantification of EGFR (ERBB1), ERBB2 (HER2), ERBB3 (HER3), ERBB4 (HER4), and MKI67 mRNA expression by using gene-specific TaqMan®-based assays as described [22]. Expression levels of the target genes as well as of the reference gene Calmodulin 2 (CALM2) were assessed in duplicate by RT-qPCR using the SuperScript III PLATINUM One-Step, quantitative RT-PCR System (Invitrogen, Karlsruhe, Germany) on a Stratagene Mx3005p (Agilent Technologies, Böblingen, Germany) with 30 min at 50°C and 2 min at 95°C followed by 40 cycles of 15 sec at 95°C and 30 sec at 60°C. Forty cycles of nucleic acid amplification were applied and the cycle threshold (Cq) values of the target genes were identified. Cq values were normalized by subtracting the Cq value of the housekeeping gene CALM2 from the Cq value of the target genes (ΔCq). RNA results were then reported as 40-ΔCq values which correlate proportionally with the mRNA expression level of the target genes. The quantity of RNA following isolation (yield) was determined by measuring CALM2 expression as a surrogate marker for amplifiable mRNA. Samples with average CALM2 Cq values <32 were considered to have sufficient RNA and were eligible for further analysis. Therefore 5 of the 106 extracted samples (success rate 95%) had an average CALM2 CT value of ≥32 and were therefore excluded. CALM2 were selected as control gene based on molecular studies in breast cancer patients which showed a high stability of this gene [23]. The lengths of the amplicons detected by the EGFR (ERBB1), ERBB2, ERBB3, ERBB4, and MKI67 assays were 93 bp, 61 bp, 81 bp, 75 bp, and 108 bp, respectively, with PCR efficiencies [E = 1(10-slope)] of 89.1, 97.2, 96.0, 92.0, and 99.7%, respectively. A commercially available human reference RNA (Stratagene qPCR Human Reference Total RNA, Agilent Technologies, Waldbronn, Germany) was used as positive control. No-template controls were assessed in parallel to exclude contamination. Details of the primer/probe sets used for amplification of the target and reference genes are listed in Table 1. 2.2. Statistical Analysis Overall survival (OS) was measured from the date of randomization until death from any cause. Surviving patients were censored at the date of last contact. Disease-free survival (DFS) was measured from the date of randomization until recurrence of tumor, secondary neoplasm, or death from any cause as described [20]. Time-to-event distributions were estimated using Kaplan-Meier analyses. Continuous variables were presented as medians with the corresponding range and categorical variables as frequencies with the respective percentages. Associations of marker genes with basic patient and tumor characteristics were examined using Fisher's exact test for categorical variables and Mann-Whitney test for continuous variables. Correlations between the target genes were calculated using Spearman's rank correlation coefficient (Rho). Univariate Cox regression analyses were performed to assess the relationship between markers and OS or DFS. The cut-offs with the highest predictive values for OS and DFS were estimated using the partitioning test. All p values were two-sided with p values < 0.05 indicating statistical significance. Statistical analyses were performed with SAS Jmp 10.0 (SAS Institute, Cary, NC, USA) and Graph Pad Prism software (Version 5, La Jolla, CA, USA). With regard to OS and DFS patient samples with pretherapeutic biopsies (n = 55) were analyzed in order to exclude a possible sampling error. 3. Results 3.1. Patients' Characteristics and mRNA Expression Tumor tissue samples were obtained from 86 patients (median age 63 years, range 44–83 years). A total of 52 biopsies and 54 resection specimens from these patients were analyzed as described in the “Material and Methods.” Only biopsies deriving prior to treatment were analyzed with regard to OS and DFS. Regarding these biopsies, 30/52 biopsies were derived from the additional neoadjuvant treated patient group and 22/52 biopsies from the solely adjuvant treated patients. Resection specimens were exclusively investigated in patients receiving solely adjuvant chemoradiotherapy to analyze a possible sample effect of biopsies and resected specimens (n = 54) (Figure 1). Basic clinical and pathological characteristics are shown in Table 2 and the samples flow chart is described in Figure 1. Analyzing normalized mRNA expression values of evaluated HER (ERBB) family marker genes and MKI67, lowest expression levels were observed for ERBB3 (Median 33) and ERBB4 (Median 32.7) and highest expression levels for ERBB2 (Median 35.9) and MKI67 (Median 35.6, Figure 2) using the two-way Mann-Whitney test. Measured Median Cq values of analyzed genes were between 27.4 (ERBB3; (28.3 ERBB2; 30.7 MKI67; 32.1 EGFR)) and 32.6 (ERBB4). Using Spearman's correlations between the analyzed genes weak negative correlations were found between EGFR (ERBB1) and HER2 (ERBB2 Rho 0.18, p = 0.22) and moderate to high positive correlations between HER4 and ERBB2 (HER2), ERBB3 (HER3) and ERBB2 (HER2), and ERBB4 (HER4) and ERBB3 (HER3, Rho ranges from 0.44 to 0.64, p < 0.01 in all cases). 3.2. Association of Gene Expression with Patient and Tumor Characteristics All biopsies (n = 52) irrespective of treatment modality showed no association between normalized mRNA expression and age (≤65 versus >65 years) or gender. However, higher EGFR (ERBB1) expression levels were associated with the risk for developing recurrence (median: 35.2 versus 34.7; p = 0.036) or death during follow-up (median: 35.1 versus 34.7; p = 0.038). Furthermore a trend was observed for higher HER3 expression levels among patients still alive during follow-up (median: 33.2 versus 32.4; p = 0.083). No significant association of normalized gene expression was observed in relation to different treatment groups (5-fluorouracil versus capecitabine). Comparison of normalized gene expression in biopsies versus resected specimen in the adjuvant treatment group showed that all markers with the exception of EGFR (ERBB1) displayed higher expression levels in preoperative biopsies than in resection specimens (Table 3). Therefore solely pretreatment biopsies were analyzed with regard to DFS and OS. 3.3. Association of Gene Expression with Disease-Free and Overall Survival For the EGFR (ERBB1) mRNA values the evaluated cut-off (18% high expression) was prognostic for both OS and DFS, while for the ERBB2, ERBB3, and MKI67 no significant prognostic effect was found in the examined cut-offs in terms of OS and DFS. Concerning EGFR (ERBB1), 5/8 deaths (63%) and 7/8 relapses (88%, 6 distant metastasis) occurred in patients with high-expressing tumors compared to 8/41 deaths (20%) and 13/41 relapses (31%, 8 distant metastasis) in the low-expressing tumors. Patients with high mRNA expression of EGFR (ERBB1) had increased risk for death (HR = 4.75, 95% CI: 1.51 to 14.48, p = 0.0090) and increased risk for relapse (HR = 7.04, 95% CI: 2.6 to 18.84, p = 0.0003) compared to patients with low-expressing tumors. Kaplan-Meier curves for OS and DFS according to the mRNA status of EGFR (ERBB1) are displayed in Figures 3(a) and 3(b). For ERBB2 (HER2) mRNA expression (38% high expression) a trend for a prognostic association was observed for OS (p = 0.064) and no correlation for DFS. Furthermore, patients with high MKI67 mRNA expression (82% high expression) showed a trend for a reduced DFS using the Kaplan-Meier method (p = 0.075; Figures 3(c), 3(d), and 3(f)). Concerning ERBB2 (HER2), 2/19 deaths (11%) occurred in patients with high-expressing tumors in comparison to 11/30 deaths (37%) in the low-expressing tumors. Patients with high mRNA expression of ERBB2 (HER2) had reduced risk for death (HR = 0.27, 95% CI: 0.041 to 0.99, p = 0.048) in the proportional hazard model compared to patients with high-expressing tumors. Kaplan-Meier curves for OS according to the mRNA status of ERBB2 (HER2) are shown in Figure 3(c). With regard to MKI67, 13/39 relapses (33%) occurred in patients with high-expressing tumors in comparison to 6/9 relapses (67%) in the low-expressing tumors. Patients with high mRNA expression of MKI67 had reduced risk for relapse (HR = 0.32, 95% CI: 0.13 to 0.88, p = 0.029) in the proportional hazard model compared to patients with low-expressing tumors when adjusting for treatment group. Kaplan-Meier curves for DFS and OS according to the mRNA status of MKI67 are shown in Figures 3(e) and 3(f). 4. Discussion No molecular markers have been described thus far to identify patients with LARC carrying a high risk for distant metastases. The aim of this study was to assess the potential prognostic value of ERBB family of receptors (EGFR (ERBB1), ERBB2 (HER2), HER3 (ERBB3), and HER4 (ERBB4) expression), as well as MKI67 expression in patients with LARC treated at a single center with chemoradiotherapy based on capecitabine or fluorouracil within a phase 3 clinical trial. Expression of EGFR (ERBB1) was prognostic for both, OS and DFS, in this analysis. The mRNA expression of the four HER family members has previously been assessed from a series of 100 locally advanced rectal cancers treated with radiotherapy or radiochemotherapy and showed an association for EGFR (ERBB1) and HER3 gene expression with development of distant metastases in LARC [19]. The current analysis confirmed that higher EGFR (ERBB1) expression levels were found more frequently among patients developing metastases. Patients with high mRNA expression of EGFR (ERBB1) also had an increased risk for death compared to patients with low-expressing tumors. In contrast, ERBB3 expression was not prognostic in our analysis. However, both studies are not completely comparable as in the present study analysis for ERBB1–4 and MKI67 was based on a standardized RNA extraction method and uniformly staged and treated (5-FU based chemoradiotherapy) patients were investigated in our series. Moreover, Ho-Pun-Cheung and colleagues used two different RNA extraction protocols (TRIzol and Qiagen Columns). These differences may explain the variability in the results. Comparably, both studies used pretreatment specimen and RNA based PCR expression. EGFR (ERBB1) immunohistochemistry and RT-qPCR showed a good overall concordance of 81% in breast cancer patients as described recently [21]. This suggests related mRNA gene expression and protein levels for EGFR (ERBB1). Pretreatment tumor biopsies were also investigated in another study comprising 40 patients with LARC [24]. Responders to neoadjuvant 5-fluorouracil-based chemoradiotherapy (patients with significant tumor regression) showed significantly lower EGFR (ERBB1) gene expression levels than nonresponders (patients with insignificant tumor regression). The 3-year DFS rates of the patients with lower gene expression levels of EGFR (ERBB1) were significantly higher (90%) than those of the patients with higher gene expression levels (70%) (p = 0.003). These data are in line with the results of our current investigation where patients with high mRNA expression of EGFR (ERBB1) had increased risk for relapse and death compared to patients with low-expressing tumors treated with capecitabine or 5-FU. This provides evidence for the use of EGFR targeted therapies in patients with high expression of EGFR treated with capecitabine or 5-FU. The predictive value of MKI67 was investigated in a rectal cancer patient cohort treated with neoadjuvant 5-FU based chemoradiotherapy [25]. A small set of formalin-fixed, paraffin-embedded pretreatment tumor biopsies and posttherapeutical resection specimens were studied by immunohistochemistry. The results were compared with histopathological tumor regression according to a standardized semiquantitative scoring system. Responders (patients with high tumor regression) showed a significantly lower MKI67 expression than nonresponders in the pretherapeutical tumor biopsies (81.2% versus 16.7%; p < 0.05) as well as in the posttherapeutical resection specimens (75.8% versus 14.3%; p < 0.01). Despite obvious differences regarding the aims and methods of both investigations it is surprising that the results appear to be diametrically opposed. Clearly, the number of pretreatment tumor biopsies in the cited publication was relatively small (n = 22). As described in the Results, sampling methods (i.e., biopsies versus resection) may explain differences in gene expression levels. However, this does not explain the difference between both data sets. In primary breast cancer, for instance, high MKI67 mRNA expression measured by RT-qPCR is predictive for achieving pathological complete remission (pCR) to neoadjuvant chemotherapy [26]. RT-qPCR was superior to MKi67 determined by immunohistochemistry [27]. Even though breast cancer and rectal cancer have different biologies the applied techniques, immunohistochemistry versus mRNA expression analysis by RT-qPCR, may be in part responsible for the observed differences. With regard to HER2/ERBB2 we found a trend for a reduced risk of death for HER2 high-expressing tumors. The role of HER2/ERBB2 expression in colorectal cancer is very controversial. In a series of 1645 patients using immunohistochemistry and chromogenic in situ hybridization (CISH) with standard protocols an overall positivity rate of 1.6% in CRC patients was described [28]. Contrarily, using immunohistochemistry (IHC) scoring and detection of silver in situ hybridization amplification (SISH) HER2 status was determined in patients with rectal cancer (n = 264). Tumors with an IHC score of 3 or SISH ratios of ≥2.0 were classified HER2 positive. HER2 status was found to be positive in 12.4% of patients with pretreatment biopsies. In this analysis, patients with HER2 positivity showed a trend for better DFS and a significant benefit in cancer-specific survival. Five-year survival rate was 96.0% for patients with HER2 positive tumors (versus 80.0% for HER2 negative tumors) [29]. Recently, an Italian group has proposed specific criteria for HER2 positivity in colorectal cancer [30]. The same group has evaluated anti-HER2 treatment (lapatinib + trastuzumab) within the so-called HERACLES trial in HER2 positive colorectal cancer patients as last line treatment and found significant antitumor activity [31]. Taken together, our results support the findings of Conradi and coworkers postulating a positive prognostic effect of HER2 gene expression. However, further investigations regarding the optimal method of defining HER2 positivity are needed, particularly since targeting HER2 has resulted in excellent efficacy data even in heavily pretreated patients in the HERACLES trial. With the exception of EGFR (ERBB1), normalized gene expression was higher in biopsies than in resection specimens. This difference could be a result of the effect of ischemia. Surgical procedures significantly affect the expression of genes in colorectal cancer tissue seen as a significant difference in the molecular composition of tissue specimens collected after tumor resection compared to specimens collected via colonoscopy before tumor resection [32]. In the present analysis, normalized values were also affected. This clearly implies that ischemia alters gene expression in a gene-specific manner. This was also shown by Liu and colleagues using microarray and PCR techniques in kidney cancer [33] which clearly underlines the importance of strict standardization and documentation of preanalytical factors. Therefore, only pretreatment biopsies were evaluated in this study to exclude an influence of sampling method on gene expression. 5. Conclusion The key findings of our analysis of ERBB family in patients with locally advanced rectal cancer undergoing 5-fluorouracil based chemoradiotherapy are as follows: (i) EGFR (ERBB1) mRNA levels had a prognostic significance for DFS as well as for OS. (ii) Differences between pretreatment biopsies and resected specimen underline the importance of standardizing preanalytical procedures in biomarker studies. (iii) High MKI67 mRNA expression correlated by trend with DFS. (iv) A relevant proportion of patients had HER2 positive tumors and therefore a better prognosis. On the other hand, HER2 positivity may offer the possibility for studying trastuzumab-based treatment in this disease. Competing Interests The authors declare that there is no conflict of interests regarding the publication of this paper. Authors' Contributions Melanie Kripp and Kirsten Merx contributed equally. Figure 1 Participants and samples flow chart diagram. Figure 2 Distribution of mRNA expression values in analyzed biopsies. Normalized mRNA expression values (40-ΔCq) of RT-qPCR evaluated HER (ERBB) family marker genes and MKI67 are presented. Lowest expression levels were observed for ERBB3 and ERBB4 and highest expression for ERBB2 and MKI67 (box and whiskers plots ranging from minimum to maximum). Gene expression values were compared by two-way Mann-Whitney test (∗∗∗∗ p < 0.0001). Figure 3 (a) Kaplan-Meier curve for overall survival (OS) according to the mRNA status of EGFR (ERBB1). The predictive values for EGFR (ERBB1) high and low expression were estimated using the partitioning test. Five-year overall survival for low EGFR (ERBB1) expression was 76%, for high EGFR expression 60%; p = 0.0057. (b) Kaplan-Meier curve for disease-free survival (DFS) according to the mRNA status of EGFR (ERBB1). The predictive values for EGFR (ERBB1) high and low expression were estimated using the partitioning test. Five-year disease-free survival for low EGFR (ERBB1) expression was 71%, for high EGFR (ERBB1) expression 13%; p < 0.0001. (c) Kaplan-Meier curve for overall survival (OS) according to the mRNA status of ERBB2 (HER2). The predictive values for ERBB2 (HER2) high and low expression were estimated using the partitioning test. Five-year overall survival for low HER2 (ERBB2) expression was 59%, for high HER2 (ERBB2) expression 89%; p = 0.064. (d) Kaplan-Meier curve for disease-free survival (DFS) according to the mRNA status of ERBB2 (HER2). The predictive values for ERBB2 (HER2) high and low expression were estimated using the partitioning test. Five-year overall survival for low HER2 (ERBB2) expression was 56%, for high HER2 (ERBB2) expression 70%; p = n.s. (e) Kaplan-Meier curve for overall survival (OS) according to the mRNA status of MKI67. The predictive values for MKI67 high and low expression were estimated using the partitioning test. Five-year overall survival for low MKI67 expression was 75%, for high MKI67 expression 55%; p = n.s. (f) Kaplan-Meier curve for disease-free survival (DFS) according to the mRNA status of MKI67. The predictive values for MKI67 high and low expression were estimated using the partitioning test. Five-year overall survival for low MKI67 expression was 39%, for high MKi67 expression 70%; p = 0.075. Table 1 Primer/probe sets used for amplification of the target and reference genes. Gene Oligo ID Oligo sequences 5′-3′ Label probe Amplicon length (nts) Assay location PCR efficacy in % MKI67 Forward CGAGACGCCTGGTTACTATCAA CY5-BHQ2 108 c. ex 2-3 NM_002417 98 Reverse GGATACGGATGTCACATTCAATACC Probe ACGGTCCCCACTTTCCCCTGAGC CALM2 Forward GAGCGAGCTGAGTGGTTGTG YY-BHQ1 72 c. ex 1-2 NM_001743 99.3 Reverse AGTCAGTTGGTCAGCCATGCT Probe TCGCGTCTCGGAAACCGGTAGC EGFR (ERBB1) Forward CGCAAGTGTAAGAAGTGCGAA FAM-BHQ1 93 NM_201283 89.1 Reverse CGTAGCATTTATGGAGAGTGAGTCT Probe CCTTGCCGCAAAGTGTGTAACGGAAT ERBB2 (HER2) Forward TCTGGACGTGCCAGTGTGAA CY5-BHQ2 61 M11730_gen 97.2 Reverse CCTGCTCCCTGAGGACACAT Probe AGGCCAAGTCCGCAGAAGCCCT ERBB3 (HER3) Forward CGGTTATGTCATGCCAGATACAC ROX-BHQ2 81 NM_001982 96 Reverse GAACTGAGACCCACTGAAGAAAGG Probe CTCAAAGGTACTCCCTCCTCCCGGG ERBB4 (HER4) Forward GAGGCTGCTCAGGACCTAAGG ATTO-BHQ1 75 NM_005235 92 Reverse GAGTAACACATGCTCCACTGTCATT Probe CACAGACTGCTTTGCCTGCATGAATTTC CY5 = cyanine dye 5, BHQ = black hole quencher; FAM = 6-carboxyfluorescein; ROX = carboxy-X-rhodamine; ATTO = fluorescent dye (ATTO-TEC GmbH, Siegen, Germany). Table 2 Patients' characteristics.   Neoadjuvant treatment Adjuvant treatment N (patients) 30 56 Age (years), median [range] 67 [47–83] 62 [44–75] Gender, n (%)      Male 20 (67) 36 (64)  Female 10 (33) 20 (36) 5-Fluorouracil, n (%) 15 (50) 27 (48) Capecitabine, n (%) 15 (50) 29 (52) Recurrence during follow-up, n (%)      Local recurrence 1 (3) 3 (5)  Metastasis 9 (30) 15 (27) Table 3 Comparison of normalized gene expression values (40-ΔCq) in biopsies versus resected specimen in the adjuvant treatment group. Significant lower expression in resected specimen was observed for HER2–HER4 and MKI67 (n.s.: not significant). Gene Biopsy (n = 22) Resected specimen (n = 54) p value Gene expression median (range) Gene expression median (range) EGFR (ERBB1, HER1) 34.8 (32.9–36.1) 34.6 (33.2–36.1) n.s. 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==== Front Stem Cells IntStem Cells IntSCIStem Cells International1687-966X1687-9678Hindawi Publishing Corporation 10.1155/2016/5417565Research ArticletPA-MMP-9 Axis Plays a Pivotal Role in Mobilization of Endothelial Progenitor Cells from Bone Marrow to Circulation and Ischemic Region for Angiogenesis http://orcid.org/0000-0002-1738-1028Leu Steve 1 2 Day Yuan-Ji 3 http://orcid.org/0000-0002-2524-9684Sun Cheuk-Kwan 4 http://orcid.org/0000-0002-6305-5717Yip Hon-Kan 1 5 6 7 8 * 1Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung 833, Taiwan2Department of Biotechnology, College of Life Science, Kaohsiung Medical University, Kaohsiung 807, Taiwan3Department of Anesthesiology, Chang Gung Memorial Hospital and Graduate Institute of Clinical Medical Sciences, Chang Gung University, Taoyuan 333, Taiwan4Department of Emergency Medicine, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan5Division of Cardiology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 333, Taiwan6Center for Shockwave Medicine and Tissue Engineering, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung 833, Taiwan7Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 404, Taiwan8Department of Nursing, Asia University, Taichung 413, Taiwan*Hon-Kan Yip: han.gung@msa.hinet.netAcademic Editor: Eva Mezey 2016 16 8 2016 2016 54175652 3 2016 3 6 2016 20 6 2016 Copyright © 2016 Steve Leu et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.We examined the role of tissue plasminogen activator- (tPA-) matrix metalloproteinase- (MMP-) 9 in mobilizing endothelial progenitor cells (EPCs) from bone marrow to circulation and critical limb ischemia (CLI) region. Male C57BL/6J mice having been irradiated were categorized into wild-type mice (WT) receiving WT bone marrow cell (BMC) transfusion (group 1), WT mice receiving MMP-9 knockout (MMP-9−/−) BMC (group 2), MMP-9−/− receiving MMP-9−/− BMC (group 3), and MMP-9−/− receiving WT BMC (group 4), each of which was subdivided into sham control (SC), CLI, SC-tPA, and CLI-tPA. In groups 1 and 4, by post-CLI 18 h and day 14, circulating EPC (C-kit+/CD31+, Sca-1+/KDR+) levels were highest in CLI-tPA subgroup. In groups 2 and 3, EPC levels did not differ among all subgroups. The EPC levels in bone marrow were higher in groups 2 and 3 than those in groups 1 and 4. By day 14, in animals with CLI, expression levels of proangiogenic factors (CXCR4, SDF-1α, and VEGF) showed similar trends as circulating EPC levels. Moreover, the number of infiltrated neutrophils and macrophages in quadriceps was higher in groups 1 and 4 than groups in 2 and 3. In conclusion, tPA-MMP-9 axis plays a crucial role in EPC mobilization and angiogenesis in experimental CLI. Ministry of Science and Technology, TaiwanMOST 99-2314-B-182A-093-MY3MOST102-2320-B-182A-001-MY3 ==== Body 1. Introduction Endothelial progenitor cells (EPCs) are originally identified as bone marrow- (BM-) derived endothelial precursor cells that contribute to neovascularization [1]. In normal condition, most EPCs locate within the stem cell niche in bone marrow and only few circulating populations in the peripheral blood [1, 2]. To enhance the mobilization of bone marrow-derived EPCs, it is considered as an effective strategy to enhance EPC-mediated injury recovery postischemic damage [3, 4]. Studies have previously demonstrated mobilization of endothelial progenitor cells (EPCs) from bone marrow (BM) to circulation and their homing to ischemic region to enhance angiogenesis/vasculogenesis through upregulation of metalloproteinase- (MMP-) 9 [5] activity and suppression of the CD26/dipeptidyl peptidase IV (DPP IV) system [6], thereby improving ischemia-related organ dysfunction [5, 6]. Recently, we have demonstrated that tissue plasminogen activator (tPA) could augment the number of circulating EPCs, angiogenesis, and blood flow to ischemic tissue in a murine model of critical limb ischemia (CLI) [7]. Further analysis in our study has revealed that an increase in circuiting EPC and enhancement of angiogenesis in ischemic zone are mainly attributable to an elevation of circulating and a reduction of bone marrow (BM) SDF-1α concentration, accompanied by upregulation of MMP-9 activity in BM [7]. By using a tPA knockout mouse model, we have further identified the essential role of endogenous tPA in augmenting circulating EPCs, angiogenesis, and blood flow through regulating MMP-9 activity in the ischemic limb in a murine model [8]. However, although these studies [5–8] consistently emphasized the relationship between MMP-9 activity and the mobilization of EPCs from BM to circulation, the precise mechanisms involved in the regulation of the kinetics of EPC mobilization have not been thoroughly clarified in these studies [5–8]. Fascinatingly, some previous studies have identified that MMP-9 acts by cleaving the membrane-bound c-Kit ligand (c-Kit-L) to the soluble form c-Kit-L, which then interacts with the EPCs c-Kit receptor to initiate the signal (i.e., the downstream signaling of MMP-9) that is crucial for BM-EPC differentiation and mobilization to systemic circulation [9–12]. In addition to EPC, the role of MMP-9 in regulating migration of neuronal and mesenchymal stem cells has also been indicated through cultured cell models and gene deficient mouse model [13, 14]. A recent study also indicated that the levels and activity of MMP-9 were altered in patients with CLI [15]. To further understand whether MMP-9 plays a unique role in tPA-mediated regulation of the mobilization of BM-EPCs into circulation, the MMP-9 deficient mice (MMP-9−/−), wild-type (WT) C57BL/6J mice, and BM reconstructions of MMP-9−/− were adopted in an experimental setting of critical limb ischemia (CLI) in the present study to investigate the following issues: (1) to determine the circulating and BM levels of EPCs (c-Kit+/CD31+, Sca-1+/KDR+) in a setting of CLI with and without tPA treatment in both wild-type and MMP-9−/− mice; (2) to compare the circulating and BM levels of EPCs in BM reconstruction of wild-type mice using MMP-9−/− as BM donor and vice versa; (3) to assess the blood flow and angiogenesis in ischemic area of the animals at day 14 after CLI induction; (4) to compare the angiogenesis capacity among WT and MMP-9−/− mice. 2. Materials and Methods 2.1. Ethics All animal experimental procedures were approved by the Institute of Animal Care and Use Committee at our institute and performed in accordance with the Guide for the Care and Use of Laboratory Animals (NIH publication number 85-23, National Academy Press, Washington, DC, USA, revised 1996). 2.2. Animals, Irradiation, and Bone Marrow Cell (BMC) Transplantation MMP-9 deficient mice in C57BL/6J background were purchased from The Jackson Laboratory (Mmp9 tm1Tvu, stock number 007084) and bred in the specific pathogen-free (SPF) condition in the Association for Assessment and Accreditation of Laboratory Animal Care- (AAALAC-)certificated experimental animal center within Kaohsiung Chang Gung Memorial Hospital. The procedure and protocol of irradiation and BM transplantation were based on previous descriptions [16]. In detail, 6-week-old male WT C57BL/6J mice (Charles River Technology, BioLASCO Taiwan Co., Ltd., Taiwan) having been irradiated (600 cGy × 2 times; the interval of two irradiation times was 4 hrs) and given immediate BMC transfusion (1.0 × 106) after the 2nd irradiation were divided into group 1 (BMC from WT to WT) and group 2 (BMC from MMP-9−/− mice to WT mice). Animals in each group were then subdivided into four subgroups: (1) sham-operated control (SC receiving only skin incision over left hindlimb), (2) CLI only, (3) SC + tPA (intravenous 4 mg/kg), and (4) CLI + tPA. Six animals were utilized in each subgroup. For comparison, age-matched male MMP-9−/− mice having received the same dosage of irradiation and immediate BMC transfusion (1.0 × 106) were divided into group 3 (BMC from MMP-9−/− to MMP-9−/−) and group 4 (BMC from WT to MMP-9−/−). Similarly, animals in groups 3 and 4 were also categorized into four subgroups (n = 6 for each subgroup). For determining the BM levels of EPCs, 4 additional animals in each subgroup were utilized and were euthanized at 18 h after CLI induction. The experimental grouping and procedure are presented in Supplemental Figure 1 in Supplementary Material available online at http://dx.doi.org/10.1155/2016/5417565. 2.3. Animal Model of Critical Limb Ischemia By the end of two months (i.e., 60 days) after irradiation, both MMP-9−/− and WT mice, weighing 25–30 gm, were anesthetized with inhalational 2.0% isoflurane. The mice receiving CLI only and CLI + tPA were placed in a supine position on a warming pad at 37°C with the left hindlimbs shaved. Only sham operation was done for SC and SC + tPA animals. Under sterile conditions, the left femoral artery, small arterioles, and circumferential femoral artery were exposed and ligated over their proximal and distal portions before being excised. To get rid of all collateral circulation, all branches were also removed. However, the veins were left intact during the procedure. After the procedure, the wound was closed and the animal was allowed to recover from anesthesia in a portable animal intensive care unit (ThermoCare®) for 24 hours. 2.4. The Rationale of tPA Dosage in the Study A single dose of intravenous tPA was given at 3 h after CLI induction. The dosage of tPA in the present study was according to our recent reports [7, 8]. The rationale of adopting a tPA dosage of 4.0 mg/kg has been described in detail in our previous study [7]. 2.5. Measurement of Blood Flow with Laser Doppler in both Normal and CLI Regions The procedure and protocol of examination of blood flow using Laser Doppler was based on our recent studies [7, 8]. Briefly, assessment of blood flow over the normal and ischemic limbs for each animal was performed under anesthesia with inhalational 2.0% isoflurane prior to the CLI procedure and on days 1 and 14 after CLI induction prior to being euthanized. Each animal was placed in a supine position on a warming pad at 37°C with both hindlimbs thoroughly shaved. The blood flow was then assessed using a Laser Doppler scanner (moorLDLS, Moor, Co. UK). All data were collected and put into a computer for further analysis. Following blood flow measurement on day 14 after CLI induction, the mice were euthanized and the quadriceps muscle was collected for individual study. 2.6. Flow Cytometric Quantification of Circulating and Bone Marrow Endothelial Progenitor Cells The procedure and protocol of flow cytometric analysis was according to our recent reports [7, 8]. In detail, peripheral blood sampling at baseline and at 18 h and on day 14 after CLI induction was obtained via cardiac puncture with a 30# needle. Moreover, the BM levels of EPCs were measured at 18 h and on day 14 after CLI induction by needle aspiration and washing from the long bone of the animals. After treatment with red blood cell-lysing buffer, the cells were labeled with appropriate antibodies. Flow cytometric quantification of EPCs through identification of the chosen cell surface markers was performed based on our recent reports [7, 8]. Briefly, the cells were incubated for 30 minutes with primary antibodies, including PE-conjugated antibodies (against Sca-1 and CD31, BD Biosciences), FITC-conjugated antibody against c-Kit (BD Biosciences), and anti-KDR (NeoMarkers) antibodies which were further recognized by Alexa flour 488-conjugated secondary antibodies (Invitrogen). Isotype-identical antibodies (IgG) served as controls. Flow cytometric analyses were performed by utilizing a fluorescence-activated cell sorter (Beckman Coulter FC500 flow cytometer). 2.7. Western Blot for Protein Expression of Angiogenesis Factors The procedure and protocol of western blot were according to our recent reports [7, 8]. Briefly, equal amounts (10–30 μg) of protein extracts from ischemic quadriceps of the animals (n = 6 for each group) were loaded and separated by SDS-PAGE using 7% or 12% acrylamide gradients. The membranes were incubated with monoclonal antibodies against CD31 (1 : 1000, Abcam), CXCR4 (1 : 1000, Abcam), vascular endothelial growth factor (VEGF) (1 : 1000, Abcam), and stromal cell-derived growth factor- (SDF-) 1α (1 : 1000, Cell Signaling). Signals were detected with HRP conjugated goat anti-rabbit IgG. Proteins were transferred to nitrocellulose membranes which were then incubated in the primary antibody solution (anti-DNP 1 : 150) for two hours, followed by incubation with secondary antibody solution (1 : 300) for one hour at room temperature. The washing procedure was repeated eight times within 40 minutes. Immunoreactive bands were visualized by enhanced chemiluminescence (ECL; Amersham Biosciences) which was then exposed to Biomax L film (Fuji). For quantification, ECL signals were digitized using Labwork software (UVP). 2.8. Immunofluorescent (IF) and Immunohistochemical (IHC) Staining For IF staining, cryosections (10 μm) of quadriceps were fixed and permeated with acetone or 4% paraformaldehyde with 0.5% Triton X-100. IF staining was performed for the examinations of CD31+, CXCR4+, SDF-1α+, CD11+ (neutrophil marker), and CD68+ (macrophage marker) cells using respective primary antibodies based on our recent studies [7, 8]. Irrelevant antibodies were used as controls in the current study. For IHC staining, fixed and permeated sections were incubated with primary antibody against alpha-smooth muscle actin (α-SMA) (1 : 400, Millipore) at room temperature for 1 hour, followed by incubating with anti-mouse-HRP conjugated secondary antibody for 30 minutes at room temperature. Signals were encolored with 3,3′ diaminobenzidine (DAB) (0.7 gm/tablet) (Sigma). Finally, hematoxylin was added as a counterstain for nuclei. For quantification, three quadriceps sections were analyzed in each mouse. For quantification, three randomly selected HPFs (high power fields) were analyzed in each section. The mean number per HPF for each animal was then determined by summation of all numbers divided by 9. 2.9. Determination of the Impact of MMP-9 on Ex Vivo Angiogenesis To assess the impact of MMP-9 on angiogenesis ex vivo, both WT and MMP-9−/− mouse aortic rings (from mouse ascending aorta) were cultured in M199 culture medium for 5 days, followed by determination of the number of sprouts from each aortic ring. 2.10. Method for Determining Mouse Aortic Ring Angiogenesis Aortic ring angiogenesis was conducted in fifteen-well tissue culture slide which contained 20 µL of 10 mg/mL matrigel (BD Biosciences, NJ) 30 µL endothelial cell medium (ECM) (Sciencell). The plates were allowed to gel for 40 minutes at 37°C and 5% CO2. Thoracic aortas were excised from 10-week-old WT and MMP-9−/− mice, followed by removal of all extraneous tissue and branching vessels with forceps and a scalpel. The aorta was cut into cross sections at 1 mm intervals and embedded in matrigel-coated wells filled with 30 µL ECM medium. Two aortic rings of each mouse were utilized for angiogenesis assay. These rings were incubated for 5 days at 37°C and 5% CO2 and photographed at day 5 with 40.0x magnification. The number and length of sprouting vessels were quantified by Wimsprout (Wimasis) software. 2.11. Zymography Analysis For zymography, supernatants from bone marrow were collected and centrifuged (500 ×g, 5 min) to remove cells and debris. Protein extract was electrophoresed in 8% SDS-PAGE containing 0.1% gelatin. After migration and washing, gels were incubated (16 h, 37°C) in activation buffer (50 mM Tris-base at pH 7.5, 5 mM CaCl2, 0.02% NaN3, and 1 μM ZnCl2). Gels were stained with Coomassie staining solution (0.5% Coomassie, 50% MeOH, 10% acetic acid, and 40% H2O) for 90 minutes, followed by destaining (0.5% Coomassie, 50% MeOH, 10% acetic acid, and 40% H2O). 2.12. Statistical Analysis Data was expressed as mean values (mean ± SD). The significance of differences between two groups was evaluated with t-test. The significance of differences among groups was evaluated using one-way ANOVA, followed by Bonferroni multiple comparison post hoc test. Statistical analysis was performed using Prism 5 statistical software (GraphPad Software, La Jolla, CA, USA). A probability value of less than 0.05 was considered statistically significant. 3. Results 3.1. Comparison of Angiogenesis Capacity between Wild-Type Mice and MMP-9−/− Mice In the physiological condition, not only endothelial progenitor cell itself but also surrounding growth factors, inflammatory cytokines, chemokines, and other components of extracellular matrix all contribute in regulating angiogenesis [17]. Hence, instead of tube formation assay of isolated EPCs, we applied aortic ring angiogenesis assays to determine the effects of MMP-9 on angiogenesis. The angiogenesis on aortic ring (i.e., the numbers of sprouts) was significantly reduced in MMP-9−/− mice compared with that in WT mice (Figure 1). This finding suggests that MMP-9 activity is needed for angiogenesis. 3.2. Flow Cytometric Quantification of Serial Changes in Circulating Level of c-Kit+/CD31+ and Sca-1+/KDR+ Cells: Subgroup Analysis In SC mice prior to CLI induction (i.e., baseline condition), the circulating numbers of c-Kit+/CD31+ and Sca-1+/KDR+ cells were significantly higher in groups 1 (WT to WT) and 4 (WT to MMP-9−/−) than in groups 2 (MMP-9−/− to WT) and 3 (MMP-9−/− to MMP-9−/−), but there was no notable difference between groups 1 and 4 or between groups 2 and 3 (Figure 2). In CLI, SC + tPA, and CLI + tPA subgroups after CLI induction (i.e., at 18 h and on day 14 after CLI procedure), the circulating numbers of c-Kit+/CD31+ and Sca-1+/KDR+ cells were significantly higher in groups 1 and 4 than in groups 2 and 3, but there was no significant difference between groups 1 and 4. In addition, these parameters also showed no difference between groups 2 and 3 in their SC, SC + tPA, and CLI subgroups. However, these parameters were significantly higher in group 2 than in group 3 when their CLI + tPA subgroups were compared (Figure 2). 3.3. Flow Cytometric Quantification of Serial Changes in Circulating Levels of c-Kit+/CD31+ and Sca-1+/KDR+ Cells: Group Analysis By 18 h after CLI induction, the circulating numbers of c-Kit+/CD31+ and Sca-1+/KDR+ cells in group 1 were highest in the CLI + tPA subgroup and lowest in SC and significantly higher in the SC + tPA than in the CLI subgroups. Besides, these parameters in group 4 showed an identical pattern compared to that of group 1 among the four subgroups (Figures 2(a) and 2(b)). By day 14 after CLI induction, the circulating levels of these biomarkers exhibited a pattern similar to that at 18 h among the animals of groups 1 and 4 except for a significantly reversed change in the expression levels of these parameters between the CLI and SC + tPA subgroups (Figures 2(c) and 2(d)). By 18 h and day 14 after CLI induction, the circulating numbers of c-Kit+/CD31+ and Sca-1+/KDR+ cells in group 3 did not differ among the SC, CLI, SC + tPA, and CLI + tPA subgroups. However, these parameters in group 2 were significantly higher in the CLI + tPA subgroup than those in the SC, CLI, and SC + tPA subgroups, but there was no difference among the latter three subgroups in group 2 (Figure 2). 3.4. Flow Cytometric Subgroup Analysis of Bone Marrow EPC Level at 18 h and on Day 14 after CLI Induction By 18 h and at day 14 after CLI induction, comparison among different groups and their subgroups demonstrated that although the pattern of subgroup changes in BM levels of EPC (i.e., c-Kit+/CD31+ and Sca-1+/KDR+ cells) was similar to that in the circulation for each group, the pattern of changes in EPC prevalence between the BM and circulation among the four groups was reversed (Figures 2 and 3). The prevalence of EPC was significantly higher in the BM environment than that in the circulation in groups 2 and 3, while groups 1 and 4 displayed a reversed pattern (Figures 2 and 3). These findings imply that EPCs were trapped and retained in BM resulting from loss of MMP-9 activity in BM. 3.5. Laser Doppler Analysis of Serial Changes of Blood Flow after CLI Induction Laser Doppler scanning demonstrated no difference in the ratio of ischemic/normal blood flow (INBF) among the four groups of animals prior to (i.e., day 0) CLI induction (Figure 4). By day 2 after CLI induction, although the INBF ratio was significantly reduced in all four groups of animals compared to their baselines, there was no significant difference among the four groups at this time point (Figure 4). By day 14 after CLI, however, the ratio was significantly higher in groups 1 and 4 than that in groups 2 and 3 in their CLI and CLI + tPA subgroups (Figure 4(w)). By day 14 after CLI induction, in groups 1 and 4, the INBF ratio was significantly higher in the CLI + tPA subgroups than that in the CLI subgroups. However, the ratio did not differ between groups 1 and 4 when their respective subgroups were compared (Figure 4(w)). 3.6. Immunofluorescent Staining for Identification of Angiogenesis Cells in Ischemic Quadriceps on Day 14 after CLI Induction: Group Analysis By day 14 after CLI induction, the numbers of cells positive for CXCR4 and SDF-1α in groups 1 and 4 were highest in their CLI + tPA subgroups and lowest in the SC subgroups and significantly higher in the CLI subgroups than those in their SC + tPA subgroups (Figures 5 and 6). Moreover, the number of cells positive for these two markers in group 2 was significantly higher in the CLI and CLI + tPA subgroups than that in the SC and SC + tPA subgroups, but there was no notable difference between the former two or the latter two subgroups (Figures 5 and 6). On the other hand, no significant difference was noted in the number of cells positive for the two markers among the four subgroups of group 3. Furthermore, the numbers of CD31+ (an indicator of endothelial cells) and α-SMA+ (an indicator of small vessels) cells in groups 1, 2, and 4 were significantly higher in the SC and SC + tPA subgroups than those in the CLI and CLI + tPA subgroups and significantly higher in the CLI + tPA than in the CLI only subgroups, but no significant difference was noted between the SC and SC + tPA subgroups (Figures 7 and 8). In group 3, the number of cells positive for the two biomarkers was higher in the SC and SC + tPA subgroups than that in the CLI and CLI + tPA subgroups, but there was no notable difference between the former two and the latter two subgroups (Figures 7 and 8). 3.7. Immunostaining for Identifications of Angiogenesis Cells and Small Vessels in Ischemic Quadriceps on Day 14 after CLI Induction: Subgroup Analysis By day 14 after CLI induction, in the SC subgroups, the number of CXCR4+ cells (Figure 5), SDF-1α+ cells (Figure 6), CD31+ cells (Figure 7), and α-SMA+ small vessels (Figure 8) did not differ among the four groups. On the other hand, for the CLI only, SC + tPA, and CLI + tPA subgroups, the number of CXCR4+, SDF-1α+, CD31+, and α-SMA+ small vessels was significantly higher in groups 1 and 4 than that in groups 2 and 3, but no difference was noted among the respective subgroups between groups 1 and 4. However, the number of cells positive for the four biomarkers was significantly higher in group 2 than that in group 3 only in the CLI + tPA subgroup. 3.8. Protein Expressions of Proangiogenic Factors in Ischemic Quadriceps on Day 14 after CLI Procedure: Subgroup Analysis In the SC and SC + tPA subgroups, the protein expressions of SDF-1α (Figure 9), CXCR4 (Figure 10), VEGF (Figure 11), and CD31 (Figure 12), four indicators of angiogenesis, were similar among the four groups. Additionally, the protein expressions of these parameters did not differ between the two subgroups. In the CLI and CLI + tPA subgroups, the protein expressions of these four biomarkers were highest in group 1 and lowest in group 3 and significantly higher in group 4 than those in group 2. 3.9. Immunofluorescent Staining for Identifications of Neutrophils and Macrophages in Ischemic Quadriceps on Day 14 after CLI Induction: Group Analysis By day 14 after CLI induction, the numbers of infiltrated neutrophils (CD11+ cells) and macrophages (CD68+ cells) in ischemic quadriceps in all groups were higher in CLI and CLI + tPA subgroups than those in SC and SC + tPA subgroups (Figures 13 and 14). Moreover, in all groups, the number of cells positive for these two markers showed no significant difference between CLI and CLI + tPA subgroups (Figures 13 and 14). In addition, no difference was noted in the number of cells positive for the two markers between SC and SC + tPA subgroups of all groups (Figures 13 and 14). 3.10. Immunofluorescent Staining for Identifications of Neutrophils and Macrophages in Ischemic Quadriceps on Day 14 after CLI Induction: Subgroup Analysis By day 14 after CLI induction, in the SC and SC + tPA subgroups, the number of neutrophils (CD11+ cells) and macrophages (CD68+ cells) did not differ among the four groups. On the other hand, for the CLI and CLI + tPA subgroups, the number of neutrophils and macrophages was significantly higher in groups 1 and 4 than that in groups 2 and 3, but no difference was noted among the respective subgroups between groups 1 and 4. However, in the CLI and CLI + tPA subgroups, the number of macrophages and neutrophils was higher in group 2 than that in group 3. 3.11. MMP-9 Activity in Bone Marrow As expected, zymography analysis revealed no MMP-9 activity in BM in groups 2 and 3 (Figure 15(a)). On the other hand, as compared with groups 2 and 3, MMP-9 activity in BM was remarkably increased in groups 1 and 4 (Figure 15(a)). Additionally, the expression of this activated form of MMP-9 was highest in the CLI + tPA and lowest in the SC subgroups and significantly higher in the SC + tPA than in the CLI subgroups for groups 1 (Figure 15(b)) and 4 animals (Figure 15(c)). 4. Discussion The aim of this study, which is a continuation of two of our recent reports [7, 8], was to investigate the role of tPA-MMP-9 axis in angiogenesis and enhancement of blood flow through mobilization of EPCs from BM to circulation and CLI region. There are several notable implications from the results of the present study. First, using the BM transplantation technique with MMP-9 deficient mice, we proved a crucial role of MMP-9 in EPC mobilization from BM to circulation and homing to CLI region for enhancement of angiogenesis and restoration of blood flow. Second, tPA plays a unique role in increasing the numbers of EPCs in BM environment and circulation through enhancing MMP-9 activity in BM. Third, bolus exogenous tPA appears to be effective for further upregulating MMP-9 activity which in turn increases BM and circulating levels of EPCs. Finally, the tPA-MMP-9 signaling axis is like a lock (i.e., MMP-9) and key (i.e., tPA) that cooperate and coordinate the numbers of EPCs in BM and circulation. By day 2 after CLI induction, the ratio of INBF was similar among all groups of animals regardless of their treatment subgroups. These findings are consistent with those of our recent studies showing that a boost of tPA 3 h after CLI induction did not significantly restore the blood flow in ischemic region through thrombolysis [7, 8]. However, when we look at the results of day 14 after CLI induction in the CLI only and CLI + tPA subgroups, the ratio of INBF was significantly higher in WT mice receiving BM transplantation from WT donors (group 1) (i.e., WT to WT) and MMP-9−/− mice receiving BM transplantation from WT donors (group 4) (WT to MMP-9−/−) than that in WT mice (i.e., wild-type mice) receiving BM transplantation from MMP-9−/− donors (group 2) (i.e., MMP-9−/− to WT) and MMP-9−/− mice receiving BM transplantation from MMP-9−/− donors (group 3) (i.e., MMP-9−/− to MMP-9−/−) (Figure 4). In addition, similar to our previous finding [7], the blood flow recovery in the CLI subgroups was not as conspicuous as the CLI + tPA subgroup. Although several studies have indicated that MMP-9 plays an essential role in modulating the homing and angiogenic activity of bone marrow-derived EPCs under ischemic stress [5, 14, 18], the upstream trigger of MMP-9 is not fully identified. In our recent studies, we have shown that tPA therapy can significantly improve blood flow in a mouse CLI model only in the presence of MMP-9 [7, 8]. This result suggested that tPA might be an upstream trigger of MMP-9 signaling. Of importance, MMP-9 is expressed in several types of cells involved in limb ischemia and followed recovery, including muscle cells, fibroblasts, endothelial cells, and bone marrow cells [19, 20]. Besides, the role of MMP-9 postischemic injury remains controversial. The use of MMP inhibitors to improve outcome in ischemic stroke and acute myocardial infarction AMI has been investigated [21, 22], while neutrophil-derived MMP-9 was also indicated to trigger aortic dissection [23]. Another study also demonstrated that loss of MMP-9 impaired the blood flow recovery after CLI [5, 24]. Hence, the roles MMP-9 plays among different tissues might be distinct. In this study, we found that the transplantation of wild-type bone marrow cells rescued the impaired blood flood recovery in MMP-9−/− mice after CLI (Figure 4). This finding indicated that the bone marrow-specific expression of MMP-9 is not only critical for migration of EPCs, but also important in angiogenesis and blood flow recovery after CLI. Our findings echoed a previous study regarding the effects of MMP-9 released from bone marrow-derived cells on the progression of BBB disruption in the ischemic brain [25]. A previous finding also demonstrated that the wild-type bone marrow transplantation could rescue the impairment of blood flow recovery in MMP-9 deficient mice with CLI, even as equivalent to that in wild-type mice [24]. Therefore, despite the role of MMP-9 in noncirculating cells, MMP-9 expression in bone marrow-derived cells, such as myeloid, lymphoid, or endothelial lineage cells, is crucial for angiogenesis and blood flow recovery after CLI. Results from immunofluorescent staining also indicated that the infiltration of macrophages and neutrophils in ischemic quadriceps is reduced by loss of MMP-9 (Figures 13 and 14). Hence, it is reasonable that although MMP-9 deficiency impairs endothelial sprouting ability in aortic ring assay (Figure 1), wild-type bone marrow transplantation could revert the reduced blood flow recovery in CLI MMP-9−/− mice in vivo (Figure 4). To elucidate whether the functional outcomes of CLI were correlated to the circulating and BM levels of EPCs, EPCs were quantified by flow cytometry through identification of their surface markers. One principal finding in the present study is that, in both normal and CLI conditions, circulating numbers of EPCs (i.e., c-Kit+/CD31+ and Sca-1+/KDR+ cells) were remarkably lower in WT or MMP-9−/− mice receiving BM transplantation from MMP-9−/− donors (groups 2 and 3) than those receiving BM transplantation from WT donors (groups 1 and 4) (Figure 2). However, the alternation of EPC population in bone marrow showed an opposite trend (Figure 3). Interestingly, these biomarkers did not differ in BM or circulation in groups 1 and 4 animals (Figures 2 and 3). Additionally, zymographic study demonstrated that MMP-9 activity in BM was remarkably higher in groups 1 and 4 than that in groups 2 and 3 (Figure 15). Our findings, therefore, highlight that MMP-9 plays a pivotal role in regulating the kinetics of EPCs (i.e., mobilization from bone marrow to circulation). Interestingly, our studies [7, 8] have shown that endogenous tPA was activated only under ischemic conditions in which plasminogen is cleaved to plasmin (i.e., the active form) that elicits MMP-9 activity in the BM, leading to the degradation of SDF-1α [7, 8]. This results in a concentration gradient of SDF-1α (i.e., lower in BM and higher in circulation) that leads to a mobilization of EPCs from BM to circulation [7, 8]. Besides, MMP-9 acts by cleaving the membrane-bound c-Kit-L to the soluble form c-Kit-L, which then interacts with the EPCs c-Kit receptor to initiate a signal (i.e., the downstream signaling of MMP-9) that is essential for BM-EPC differentiation and mobilization to systemic circulation [7–12]. Our present and recent findings [7, 8] as well as those from the other previous studies [9–12] all suggest an important role of the tPA-MMP-9 signaling axis in the coordination of EPC mobilization. However, MMP-9 can also be activated by other proteases, such as MMP-3 [26, 27]. The transcription level of MMP-9 is found to be upregulated by MMP-1 and MMP-3 in macrophages [28], while the activation of MMP-3 is associated with the activity of plasmin [26]. Hence, the interaction among plasmin and MMPs may have roles in tPA-MMP-9-mediated EPC mobilization and angiogenesis post-CLI. To further confirm an upregulation of the expressions of proangiogenic factors in the CLI region in the presence of MMP-9 at protein and cellular levels, western blot and IF staining of the ischemic muscle were performed in the present study, respectively. A principal finding in the present study is that, for their SC and SC + tPA subgroups, the protein expressions of CXCR4, SDF-1α, and CD31 in CLI region did not differ among the four groups of animals. These findings suggest that, in the absence of ischemic stimulus, BM transplantation did not contribute to the enhancement of protein expressions of proangiogenic factors in remote region. Of importance is that the protein expressions of these factors in the CLI and CLI + tPA subgroups were significantly higher in groups 1 and 4 than those in groups 2 and 3. Besides, IF microscopic findings showed that, in the CLI and CLI + tPA subgroups, the pattern of cellular expressions of proangiogenic biomarkers (CXCR4+, SDF-1α+, CD31+, and α-SMA+ small vessels) was identical to that of their protein expressions in the four groups of animals. These findings, in addition to strengthening those of our recent studies demonstrating that tPA treatment augmented the protein and cellular expressions of proangiogenic biomarkers in the setting of CLI [7, 8], may also explain the remarkable improvement in blood flow in the ischemic zone in groups 1 and 4 by day 14 after CLI induction. Besides, the results of the present study provide two novel findings: (1) tPA upregulated the expressions of proangiogenic factors only in the presence of MMP-9 under ischemic condition; (2) tPA therapy may be beneficial for patients with acute myocardial infarction and acute ischemic stroke other than its role in enhancing reperfusion through the mechanism of thrombolysis. This study has limitations. First, this study did not directly confirm the hypothesis that circulating EPCs were mobilized solely from the BM. The distribution of EPC was not directly observed in the ischemic region of mice with CLI to clarify the correlation between circulation EPC and tissue EPC. Besides, we did not perform double knockout experiments (i.e., knockout of tPA and MMP-9 in the same animal) to further establish the role of the tPA-MMP-9 signaling axis in controlling EPC kinesis. 5. Conclusion MMP-9 plays a unique role in EPC mobilization from BM to circulation and homing to ischemic zone. Moreover, tPA is essential for eliciting MMP-9 activity. The proposed mechanisms have been summarized in Figure 16. The findings of the present study, therefore, provide important evidence for understanding the role of the tPA-MMP-9 signaling axis in the regulation of the kinetics of EPCs in a murine experimental setting of CLI. Supplementary Material Supplemental Figure 1: Experimental grouping and design of present study. Upper panel: The schematic illustration of the grouping for the bone marrow cell (BMC) transplantation model. Lower panel: The schematic illustration of experimental grouping and procedures for BMC transplantation, critical limb ischemia (CLI) induction, blood flow observation, and sample collection. MMP-9, matrix metalloproteinase-9; PB, peripheral blood; BM, bone marrow. Acknowledgments The authors thank supports from Ministry of Science and Technology, ROC (MOST 99-2314-B-182A-093-MY3 to Hon-Kan Yip and MOST 102-2320-B-182A-001-MY3 to Steve Leu). Competing Interests The authors declare that they have no competing interests. Authors' Contributions Steve Leu and Yuan-Ji Day equally contributed to this study. Figure 1 In vitro studies for quantification of angiogenesis ability in (a–d) illustrating the results of aortic ring culture in wild-type (WT) (a, c) and MMP-9−/− (b, d) mice, respectively. (e) Analytical result of mean distance of sprouts. (f) Analytical result of mean sprout area. ∗ indicates p < 0.0001 between MMP9−/− group and WT group. n = 6 for each group. Figure 2 Flow cytometric analysis of circulating level of endothelial progenitor cells (EPCs) at 18 h and on day 14 after critical limb ischemia (CLI) procedure. (Upper panel) Circulating numbers of c-Kit+/CD31+ cells (a) and Sca-1+/KDR+ (b) at 18 h after CLI procedure. n = 4 for each group. (Lower panel) Circulating numbers of c-Kit+/CD31+ cells (c) and Sca-1+/KDR+ cells (d) at day 14 after CLI procedure. n = 6 for each group. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. tPA = tissue plasminogen activator. (1) Statistical analysis for subgroups [i.e., sham control (SC), CLI, SC + tPA, and CLI + tPA] of each group [group 1 (WT to WT, i.e., B → B), group 2 (MMP-9−/− to WT, i.e., M → B), group 3 (MMP-9−/− to MMP-9−/−, i.e., M → M), group 4 (WT to MMP-9−/−, i.e., B → M)]. For subgroups with different black symbols (∗, †, ‡, and §), p < 0.05. (2) Statistical analysis for group comparison with respective treatment condition (comparing among bar charts with the same color). (1) For SC subgroup (red bar chart), groups with different red symbols (∗, †), p < 0.05. (2) For CLI subgroup (blue bar chart), groups with different blue symbols (∗, †), p < 0.05. (3) For SC + tPA subgroup (green bar chart), groups with different green symbols (∗, †), p < 0.05. (4) For CLI + tPA subgroups (orange bar chart), groups with different orange symbols (∗, †, and ‡), p < 0.05. Figure 3 Flow cytometric analysis of bone marrow (BM) level of endothelial progenitor cells (EPCs) at 18 h and on day 14 after critical limb ischemia (CLI) procedure. (Upper panel) Bone marrow levels of c-Kit+/CD31+ cells (a) and Sca-1+/KDR+ (b) at 18 h after CLI procedure. n = 4 for each group. (Lower panel) Bone marrow levels of c-Kit+/CD31+ cells (c) and Sca-1+/KDR+ cells (d) at day 14 after CLI procedure. n = 6 for each group. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. tPA = tissue plasminogen activator. (1) Statistical analysis for subgroups [i.e., sham control (SC), CLI, SC + tPA, and CLI + tPA] of each group [group 1 (WT to WT, i.e., B → B), group 2 (MMP-9−/− to WT, i.e., M → B), group 3 (MMP-9−/− to MMP-9−/−, i.e., M → M), group 4 (WT to MMP-9−/−, i.e., B → M)]. For subgroups with different black symbols (∗, †, ‡, and §), p < 0.05. (2) Statistical analysis for group comparison with respective treatment condition (comparing among bar charts with the same color). (1) For SC subgroup (red bar chart), groups with different red symbols (∗, †), p < 0.05. (2) For CLI subgroup (blue bar chart), groups with different blue symbols (∗, †), p < 0.05. (3) For SC + tPA subgroup (green bar chart), groups with different green symbols (∗, †), p < 0.05. (4) For CLI + tPA subgroups (orange bar chart), groups with different orange symbols (∗, †), p < 0.05. Figure 4 Serial changes of Laser Doppler scanning of hind limb blood flow prior to and after critical limb ischemia (CLI) induction. (a–d) The normal blood flow in both hind limbs in each group prior to the CLI procedure. (e) Ratio of left (ischemia) to right (normal) blood flow, p = 1.0. (f–u) The blood flow in left and right hind limbs under the treatment conditions of CLI and CLI + tPA in 4 groups (i.e., B → B, M → B, M → M, and B → M) at day 2 or day 14 after the procedure. (v) Quantitation and calculation of ratio of ischemia to normal blood flow (INBF) among the four groups at day 2. (w) Quantitation and calculation of ratio of INBF among the four groups at day 14. Statistical analysis for individual group at different treatment conditions. (1) In B → B, 1A versus 1B, ∗ indicates p < 0.01. (2) In M → B, 2A versus 2B, p > 0.5. (3) In M → M, 3A versus 3B, p > 0.5. (4) In B → M, 4A versus 4B, ∗ indicates p < 0.01. (2) Statistical analysis for group comparison with respective treatment condition. (1) For CLI subgroup (white bar chart), groups with different red symbols (∗, †), p < 0.01. (2) For CLI + tPA subgroup (black bar chart), groups with different blue symbols (∗, †), p < 0.01. SC = sham control; tPA = tissue plasminogen activator. n = 6 for each group. Figure 5 Immunofluorescent (IF) microscopic findings (400x) of CXCR+ cells in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a–p) IF microscopic findings of CXCR4+ cells in ischemic area in four treatment conditions of four groups. (1) Statistical analysis for subgroups of each group. (1) In B → B group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (2) In M → B group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (3) In M → M group, p > 0.5. (4) In B → M group, subgroups with different black symbols (∗, †, and ‡), p < 0.5. (2) Statistical analysis for group comparison with respective treatment condition. (1) For SC subgroup (red bar chart), groups with different red symbols (∗, †), p < 0.05. (2) For CLI subgroup (blue bar chart), groups with different blue symbols (∗, †, and ‡), p < 0.05. (3) For SC + tPA subgroup (green bar chart), groups with different green symbols (∗, †), p < 0.05. (4) For CLI + tPA subgroup (orange bar chart), groups with different orange symbols (∗, †, and ‡), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. SC = sham control; tPA = tissue plasminogen activator. n = 6 for each group. Figure 6 Immunofluorescent (IF) microscopic findings (400x) of stromal cell-derived factor- (SDF-) 1α+ cells in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a–p) IF microscopic findings of SDF-1α+ cells in ischemic area in four treatment conditions of four groups. (1) Statistical analysis for subgroups of each group. (1) In B → B group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (2) In M → B group, subgroups with different black symbols (∗, †), p < 0.05. (3) In M → M group, p > 0.5. (4) In B → M group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (2) Statistical analysis for group comparison with respective treatment condition. (1) For SC subgroup (red bar chart), groups with different red symbols (∗, †), p < 0.05. (2) For CLI subgroup (blue bar chart), groups with different blue symbols (∗, †, and ‡), p < 0.05. (3) For SC + tPA subgroup (green bar chart), groups with different green symbols (∗, †), p < 0.05. (4) For CLI + tPA subgroup (orange bar chart), groups with different orange symbols (∗, †), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. SC = sham control; tPA = tissue plasminogen activator. n = 6 for each group. Figure 7 Immunofluorescent (IF) microscopic findings (400x) of CD31+ cells in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a–p) IF microscopic findings of CD31+ cells in ischemic area in four treatment conditions of four groups. (1) Statistical analysis for subgroups of each group. (1) In B → B group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (2) In M → B group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (3) In M → M group, subgroups with different black symbols (∗, †), p < 0.05. (4) In B → M group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (2) Statistical analysis for group comparison with respective treatment condition. (1) In SC subgroup (red bar chart), p > 0.1. (2) In CLI subgroup (blue bar chart), groups with different blue symbols (∗, †), p < 0.05. (3) In SC + tPA subgroup (green bar chart), p > 0.1. (4) In CLI + tPA subgroup (orange bar chart), groups with different orange symbols (∗, †, and ‡), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. SC = sham control; tPA = tissue plasminogen activator. n = 6 for each group. Figure 8 Immunohistochemical (IHC) staining for alpha-smooth muscle actin (α-SMA) to detect small vessels in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a–p) IHC staining to examine the distribution of α-SMA + small vessels (black arrows) in ischemic area in four treatment conditions of four groups. (1) Statistical analysis for subgroups of each group. (1) In B → B group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (2) In M → B group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (3) In M → M group, subgroups with different black symbols (∗, †), p < 0.05. (4) In B → M group, subgroups with different black symbols (∗, †, and ‡), p < 0.05. (2) Statistical analysis for group comparison with respective treatment condition. (1) For SC subgroup (red bar chart), p > 0.05. (2) For CLI subgroup (blue bar chart), groups with different blue symbols (∗, †), p < 0.05. (3) For SC + tPA treatment condition (green bar chart), p > 0.05. (4) For CLI + tPA treatment condition (orange bar chart), groups with different orange symbols (∗, †, and ‡), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. SC = sham control; tPA = tissue plasminogen activator. n = 6 for each group. Figure 9 Protein expression of stromal cell-derived factor- (SDF-) 1α in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a) At sham control (SC) treatment condition, SDF-1α did not differ among four groups, p = 1.0. (b) At CLI subgroup, groups with different symbols (∗, †, ‡, and §), p < 0.05. (c) At SC + tPA treatment condition, SDF-1α did not differ among four groups, p = 1.0. (d) At CLI + tPA subgroup, groups with different symbols (∗, †, ‡, and §), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. tPA = tissue plasminogen activator. n = 6 for each group. Figure 10 Protein expression of CXCR4 in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a) At sham control (SC) treatment condition, CXCR4 did not differ among four groups, p = 1.0. (b) At CLI subgroup, groups with different symbols (∗, †, ‡, and §), p < 0.05. (c) At SC + tPA subgroup, CXCR4 did not differ among four groups, p = 1.0. (d) At CLI + tPA subgroup, groups with different symbols (∗, †, ‡, and §), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. tPA = tissue plasminogen activator. n = 6 for each group. Figure 11 Protein expression of vascular endothelial growth factor (VEGF) in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a) At sham control (SC) treatment condition, VEGF did not differ among four groups, p = 1.0. (b) At CLI subgroup, groups with different symbols (∗, †, ‡, and §), p < 0.05. (c) At SC + tPA subgroup, VEGF did not differ among four groups, p = 1.0. (d) At CLI + tPA subgroup, groups with different symbols (∗, †, ‡, and §), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. tPA = tissue plasminogen activator. n = 6 for each group. Figure 12 Protein expression of CD31 in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction (n = 6). (a) At sham control (SC) treatment condition, CD31 did not differ among four groups, p = 1.0. (b) At CLI subgroup, groups with different symbols (∗, †, ‡, and §), p < 0.05. (c) At SC + tPA treatment condition, CD31 did not differ among four groups, p = 1.0. (d) At CLI + tPA subgroup, groups with different symbols (∗, †, ‡, and §), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. tPA = tissue plasminogen activator. n = 6 for each group. Figure 13 Immunofluorescent (IF) microscopic findings (400x) of neutrophils (CD11+ cells) in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a–p) IF microscopic findings of neutrophils in ischemic area in four treatment conditions of four groups. (1) Statistical analysis for subgroups of each group. (1) In B → B group, subgroups with different black symbols (∗, †), p < 0.05. (2) In M → B group, subgroups with different black symbols (∗, †), p < 0.05. (3) In M → M group, subgroups with different black symbols (∗, †), p < 0.05. (4) In B → M group, subgroups with different black symbols (∗, †), p < 0.05. (2) Statistical analysis for group comparison with respective treatment condition. (1) In SC subgroup (red bar chart), p > 0.05. (2) In CLI subgroup (blue bar chart), groups with different blue symbols (∗, †, and ‡), p < 0.05. (3) In SC + tPA subgroup (green bar chart), p > 0.05. (4) In CLI + tPA subgroup (orange bar chart), groups with different orange symbols (∗, †, and ‡), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. SC = sham control; tPA = tissue plasminogen activator. n = 6 for each group. Figure 14 Immunofluorescent (IF) microscopic findings (400x) of macrophages (CD68+ cells) in ischemic quadriceps at day 14 after critical limb ischemia (CLI) induction. (a–p) IF microscopic findings of CD68+ cells in ischemic area in four treatment conditions of four groups. (1) Statistical analysis for subgroups of each group. (1) In B → B group, subgroups with different black symbols (∗, †), p < 0.05. (2) In M → B group, subgroups with different black symbols (∗, †), p < 0.05. (3) In M → M group, subgroups with different black symbols (∗, †), p < 0.05. (4) In B → M group, subgroups with different black symbols (∗, †), p < 0.05. (2) Statistical analysis for group comparison with respective treatment condition. (1) In SC subgroup (red bar chart), p > 0.05. (2) In CLI subgroup (blue bar chart), groups with different blue symbols (∗, †, and ‡), p < 0.05. (3) In SC + tPA subgroup (green bar chart), p > 0.05. (4) In CLI + tPA subgroup (orange bar chart), groups with different orange symbols (∗, †, and ‡), p < 0.05. All statistical analyses were performed by one-way ANOVA followed by Bonferroni multiple comparison post hoc test. SC = sham control; tPA = tissue plasminogen activator. n = 6 for each group. Figure 15 Matrix metalloproteinase- (MMP-) 9 activity in BM by 18 h after CLI procedure. (a) Zymography analysis of matrix metalloproteinase- (MMP-) 9 activity in BM of four groups. No MMP-9 activity was identified in M → M and M → B groups. On the other hand, MMP-9 activity was observed in B → B and B → M groups. (b) (1) Zymography analysis of pro-MMP-9 activity in B → B group of different treatment condition (white bar chart), α versus β, p < 0.05. (2) Zymography analysis of active form of MMP-9 in B → B group of different treatment condition (black bar chart), subgroups with different symbols (∗, †, ‡, and §), p < 0.05. Symbols (∗, †, ‡, and §) indicate significance (at 0.05 level). n = 4 for each group. (c) (1) Zymography analysis of pro-MMP-9 activity in B → M group of different treatment condition (white bar chart), α versus β, p < 0.05. (2) Zymography analysis of active form of MMP-9 in B → M group of different treatment condition (black bar chart), subgroups with different symbols (∗, †, ‡, and §), p < 0.05. n = 4 for each group. Figure 16 Proposed mechanisms. The proposed rescue model of bone marrow cells (BMC) transplantation on enhancing angiogenesis in matrix metalloproteinase- (MMP-) 9 deficient mice with critical limb ischemia. EPC = endothelial progenitor cells; SDF-1α = stromal cell-derived factor-1α; ECM = extracellular matrix. ==== Refs 1 Asahara T. Masuda H. Takahashi T. 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==== Front Front NeurosciFront NeurosciFront. Neurosci.Frontiers in Neuroscience1662-45481662-453XFrontiers Media S.A. 10.3389/fnins.2016.00400NeuroscienceOriginal ResearchNucleus Accumbens Shell and mPFC but Not Insula Orexin-1 Receptors Promote Excessive Alcohol Drinking Lei Kelly Wegner Scott A. Yu Ji Hwan Mototake Arisa Hu Bing Hopf Frederic W. *Alcohol and Addiction Research Group, Department of Neurology, University of California, San FranciscoSan Francisco, CA, USAEdited by: Brian McCool, Wake Forest School of Medicine, USA Reviewed by: Rodrigo España, Drexel University College of Medicine, USA; Marcelo F. Lopez, Medical University of South Carolina, USA; Stephen V. Mahler, University of California, Irvine, USA *Correspondence: Frederic W. Hopf Frederic.Hopf@ucsf.eduThis article was submitted to Neuropharmacology, a section of the journal Frontiers in Neuroscience 30 8 2016 2016 10 40009 5 2016 15 8 2016 Copyright © 2016 Lei, Wegner, Yu, Mototake, Hu and Hopf.2016Lei, Wegner, Yu, Mototake, Hu and HopfThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Addiction to alcohol remains a major social and economic problem, in part because of the high motivation for alcohol that humans exhibit and the hazardous binge intake this promotes. Orexin-1-type receptors (OX1Rs) promote reward intake under conditions of strong drives for reward, including excessive alcohol intake. While systemic modulation of OX1Rs can alter alcohol drinking, the brain regions that mediate this OX1R enhancement of excessive drinking remain unknown. Given the importance of the nucleus accumbens (NAc) and anterior insular cortex (aINS) in driving many addictive behaviors, including OX1Rs within these regions, we examined the importance of OX1Rs in these regions on excessive alcohol drinking in C57BL/6 mice during limited-access alcohol drinking in the dark cycle. Inhibition of OX1Rs with the widely used SB-334867 within the medial NAc Shell (mNAsh) significantly reduced drinking of alcohol, with no effect on saccharin intake, and no effect on alcohol consumption when infused above the mNAsh. In contrast, intra-mNAsh infusion of the orexin-2 receptor TCS-OX2-29 had no impact on alcohol drinking. In addition, OX1R inhibition within the aINS had no effect on excessive drinking, which was surprising given the importance of aINS-NAc circuits in promoting alcohol consumption and the role for aINS OX1Rs in driving nicotine intake. However, OX1R inhibition within the mPFC did reduce alcohol drinking, indicating cortical OXR involvement in promoting intake. Also, in support of the critical role for mNAsh OX1Rs, SB within the mNAsh also significantly reduced operant alcohol self-administration in rats. Finally, orexin ex vivo enhanced firing in mNAsh neurons from alcohol-drinking mice, with no effect on evoked EPSCs or input resistance; a similar orexin increase in firing without a change in input resistance was observed in alcohol-naïve mice. Taken together, our results suggest that OX1Rs within the mNAsh and mPFC, but not the aINS, play a central role in driving excessive alcohol drinking. alcoholnucleus accumbens shellinsulaorexinSB-334867National Institute on Alcohol Abuse and Alcoholism10.13039/100000027AA017072 ==== Body Introduction Addiction to abused substances, including alcohol, is characterized by strong motivation for the addictive substance (Larimer et al., 1999; Sinha, 2009; Koob and Volkow, 2010). However, despite extensive efforts, alcohol use disorders (AUDs) remain a significant problem with substantial personal, social, and economic costs (Harwood et al., 1998; Blincoe et al., 2002; Mokdad et al., 2004; Dawson et al., 2005; Hingson et al., 2005; Rehm et al., 2009; Bouchery et al., 2011; Sacks et al., 2013; CDC, 2014; SAMHSA, 2014), especially because of the limited pharmacotherapies that are effective against AUDs (Spanagel, 2009; WHO, 2014). Orexin receptors (OXRs) are of particular interest for addictive behaviors since they can promote intake of a number of motivating and addictive substances (Mahler et al., 2012, 2014; Boutrel et al., 2013; Barson and Leibowitz, 2016). OXRs are activated by the neuropeptide orexin, which is synthesized in a subset of cells in the lateral hypothalamus that project throughout the brain (de Lecea et al., 1998), and mediate a variety of regulatory and homeostatic behaviors ranging from sleep-wake cycle and neuroendocrine regulation to feeding and arousal (Mahler et al., 2014; Brown J. A. et al., 2015; Li et al., 2016). Orexin can act through OX1-type or OX2-type receptors (OX1Rs or OX2Rs), and although both receptors can contribute to addictive behaviors (Mahler et al., 2012), existing studies suggest that OX1Rs play a much more important overall role relative to OX2Rs (Moorman and Aston-Jones, 2009; Baimel et al., 2014; Barson et al., 2014; Mahler et al., 2014; Brown J. A. et al., 2015; but see Brown et al., 2013; Anderson et al., 2014). In particular, OX1Rs have been implicated in driving the pursuit and intake of high-value, salient natural rewards, such as sucrose and high-fat foods, as well as addictive substances such as cocaine, opioids, nicotine, and alcohol, with little role in sustaining consumption of less motivating substances (Borgland et al., 2009; Cason et al., 2010; Baimel et al., 2014; Mahler et al., 2014). For example, OX1Rs mediate greater alcohol preference and intake in rats (Moorman and Aston-Jones, 2009) and increased alcohol drinking in dependent mice (Lopez et al., 2016). Thus, OX1R signaling could represent an important and novel clinical and therapeutic target for intervention for AUDs (Khoo and Brown, 2014; Li et al., 2016). While considerable evidence implicates OX1Rs in driving intake of preferred rewards, the brain regions that mediate this effect on alcohol drinking are poorly understood. We recently demonstrated that projections from the anterior insula (aINS) to the nucleus accumbens (NAc) are critical for driving compulsion-like alcohol drinking in rats (Seif et al., 2013). The medial Shell subregion of the NAc (mNAsh) also plays an important role in a promoting a number of addictive and other motivated behaviors (Anderson et al., 2008; Chaudhri et al., 2010; Saddoris et al., 2013; Castro et al., 2015; Corbit and Balleine, 2015; Marchant et al., 2015; Millan et al., 2015), including a role for mNAsh OXRs during feeding and morphine-related behavior (Thorpe and Kotz, 2005; Qi et al., 2013; Sadeghzadeh et al., 2016), although there have been mixed results regarding the presence of OX1Rs within the mNAsh (See Section Discussion). The aINS is also thought to play a central role in driving addictive behaviors in both humans (Naqvi et al., 2014) and animals (Hollander et al., 2008; Seif et al., 2013), and OX1Rs within the aINS promote nicotine intake (Hollander et al., 2008). In addition, OX1Rs in the mPFC have been shown to increase alcohol relapse (Brown R. M. et al., 2015). Thus, we examined whether OX1Rs in the mNAsh, aINS, and mPFC were important for driving excessive alcohol drinking in mice, and whether mNAsh OX1Rs promoted responding for alcohol in rats. We also used electrophysiology to assess whether OX1Rs altered measures of mNAsh activity ex vivo. Methods Animals All procedures followed the Guide for Care and Use of Laboratory Animals provided by the National Institutes of Health, and with approval of the Institutional Animal Care and Use Committee of UCSF. Male C57BL/6 mice, 7–8-week of age, were purchased from Jackson Laboratories. Mice were single-housed under a reverse 12:12 light:dark cycle, with lights off at 10:00 a.m. Male Long-Evans rats, 45–50 days of age, were purchased from Harlan and singly housed, and housed under a standard light-dark cycle (with drinking experiments performed in the light cycle). Food and water were available, ad libitum, for all subjects. We used mice because of their higher level of drinking under two-bottle intake relative to rats. In contrast, operant methods in mice are much more challenging, and thus we utilized operant methods in rats. Limited daily access (LDA) to alcohol in mice The repeated, limited access choice alcohol drinking model was modified from that previously described (Lesscher et al., 2010; Kasten and Boehm, 2014). Mice were first acclimated to housing conditions for 2-week. Mice were then given two-bottle choice access to one bottle with 15% alcohol (v/v) in water and a second bottle of water. Mice first had a 24-h overnight alcohol-drinking session, followed by a 24-h withdrawal period. Thereafter, mice were presented daily with 15% alcohol and water for 2-h, Monday–Friday, in their home cage, with drinking sessions starting 3-h into the dark cycle. This excessive-drinking exposure paradigm leads to binge levels of alcohol drinking (>80 mg%) (Lei et al., 2016). In order to control for side preference, the bottle placements of the solutions were alternated between each drinking session. Intake level was measured by determining bottle weight and corrected for spill, which was determined by separate spill-control bottles. Saccharin intake in mice Drinking of a 0.05% saccharin solution under two-bottle choice was performed using a schedule identical to that used for alcohol. This concentration was determined to give approximately the same volume of intake as alcohol (e.g., 19.2 ± 2.3 ml/kg/2-h of alcohol intake for vehicle condition in Figure 1B; t(1, 27) = 1.54, p = 0.14 vs. volume of saccharin intake for vehicle condition in Figure 2B). Figure 1 OX1R blockade within the medial NAc Shell significantly reduced alcohol drinking in mice. (A) Locations of cannulae shown by gray circles; sections at approximately AP +1.34, +1.18 and +0.98 mm relative to Bregma. (B) Infusion of 3-μg SB within the mNAsh decreased alcohol intake. (C,D) No changes in (C) alcohol preference or (D) concurrent water intake. Preference was calculated as (ml alcohol)/(ml alcohol + ml water). *p < 0.05. Figure 2 mNAsh OX1R blockade did not alter saccharin drinking. (A) Locations of cannulae, as for Figure 1. (B–D) Infusion of 3-μg SB within the mNAsh did not alter (B) saccharin intake, (C) preference or (D) concurrent water intake. Alcohol self-administration in rats Rat self-administration methods were identical to those previously described (Simms et al., 2011b), using standard operant conditioning chambers (MedAssociates). Briefly, rats underwent six 14-h overnight session on an FR1 schedule, with 0.1 ml of 20% alcohol delivered after each FR1 press. During overnight training, only the active lever was available, which allowed the establishment of lever-pressing behavior. Rats then had six sessions of 45-min FR1, and then were moved to a daily 30-min FR3 schedule of responding; a second, inactive lever was also introduced during the FR3 sessions. In all phases of training, successful completion of an FR response resulted in alcohol delivery as well as a cue light above the active lever and a tone. Inactive lever presses were not accompanied by alcohol delivery or light or tone cues. Rats pressed for a minimum of 20 sessions before testing the impact of SB on responding for alcohol. Any animal receiving less 0.3 g/kg ethanol intake per session were excluded (one rat in this study). Cannula implantation surgeries In mice, after ~2-week of LDA, surgery was performed to implant bilateral guide cannulae (Plastics One) aimed at the mNAsh (AP +1.5, ML ±0.5, DV −4.5 mm), an offsite control region above the mNAsh (AP +1.5, ML ±0.5, DV −3.0 mm), aINS (AP +2.0, ML ±2.4, DV −2.0 mm), and the mPFC (attempting to target the infralimbic) (AP +1.7, ML ±0.4, DV −2.7 mm). In rats, after establishing FR3 responding, bilateral guide cannulae were implanted targeting the mNAsh (AP +1.8, ML ±0.8, DV −6.5 mm). All coordinates are given relative to Bregma. After surgery, animals were allowed to recover for 1-week before resuming alcohol drinking sessions, and handling for drug microinfusions began the week after. After completion of drug treatments, brains were harvested for verification of cannula placement. Drug microinfusions SB-334867 (SB, Tocris), a selective OX1R antagonist, was dissolved in 100% DMSO vehicle (Simms et al., 2011a). Mice received microinjections of either vehicle or 3-μg/200 nL/side (47 nmol) of SB 30-min prior to an alcohol-drinking session, or 3-μg/200 nL/side (59 nmol) of the OX2R antagonist TCS-OX2-29 (TCS, Tocris); these are relatively high doses but have previously been utilized (Borgland et al., 2006; Qi et al., 2013; Brown R. M. et al., 2015). Drugs were injected with bilateral infusion needles (Plastics One) that projected 0.3 mm past the end of the guide cannulae, at a rate of 200 nL/min. Needles were left in place for an extra 1-min before retraction. Each dose (vehicle and 3-μg SB or TCS) was microinjected twice (on different test days) and counter-balanced across treatment and animals. Rats received microinjections of either 0- or 3-μg/600 nL/side of SB, on different days using a within-animal design in a counter-balance manner, 30-min prior to alcohol self-administration sessions. Drugs were injected 600 nL/min via bilateral infusions needles (Plastics One) that project 1-mm beyond the guide cannulae. Needles were left in place for an extra 90-s. Mice or rats were given at least 1 day of alcohol or saccharin drinking between test days. Alcohol intake, especially bottle drinking, can be influenced by handling (Lum et al., 2014), and thus it is important to give animals a period of time after injection to remove possible confounds of handling on alcohol drinking, and we used a 30 min time point between drug injection and behavioral testing. Thus, given the use of DMSO as a vehicle for SB, we cannot completely rule out the possibility that this period of time might have allowed greater diffusion of OXRS to adjacent brain regions, for example into the adjacent NAcore. However, even if a briefer time was used between injection and initiation of alcohol drinking, the drinking sessions were 2 h and any such issues related to diffusion would become apparent within the first hour of drinking. Also, although we do not have specific information about the level of spread of our infusate, 200 nl has previously used as an microinjection volume for studies distinguishing mNAsh vs. NAcb Core in mice (Managò et al., 2008), and is widely used as a volume for injection for other studies in mice (e.g., Stratford and Wirtshafter, 2011; Kasten and Boehm, 2014; Ramaker et al., 2015). DMSO as vehicle could have effects on drinking. However, alcohol intake in the presence of intra-mNAsh DMSO infusion was not different from alcohol drinking levels in the uninjected days adjacent to days with DMSO infusion [DMSO infusion: 2.23 ± 0.28 g/kg; adjacent uninjected days: 2.31 ± 0.23 g/kg; t(1, 16) = 0.26, p = 0.80; n = 17, determined for the mice shown in Figure 1, DMSO results are same as shown in Figure 1]. Also, other studies have demonstrated that intracranial injection of DMSO does not have non-specific effects on behavior relative to saline injection (e.g., Naghdi and Asadollahi, 2004). Thus, the DMSO vehicle itself likely did not have non-specific effects on alcohol drinking. Brain slice preparation and ex vivo electrophysiology Slice preparation and electrophysiology methods were similar to those previously described (Seif et al., 2011, 2013; Pomrenze et al., 2015). Briefly, adult mice were anesthetized with pentobarbital (100 mg/kg), decapitated, and brain slices were cut in an ice-cold glycerol-based solution (in mM: 252 glycerol, 2.5 KCl, 1.25 NaH2PO4, 1 MgCl2, 2 CaCl2, 25 NaHCO3, 1 L-ascorbate, and 11 glucose, bubbled with carbogen) (Pomrenze et al., 2015). Slices recovered at 32°C in carbogen-bubbled aCSF (containing, in mM: 126 NaCl, 2.5 KCl, 1.2 NaH2PO4, 1.2 MgCl2, 2.4 CaCl2, 18 NaHCO3, 11 glucose, pH 7.2–7.4, mOsm 302–305) for at least 30 min before experiments, with 1 mM ascorbic acid added just before the first slice. During experiments, slices were submerged and perfused (2 ml/min) with aCSF, 31–32°C, with CNQX (10 μM) and picrotoxin (50 μM). Action potential firing and EPSCs were recorded using Clampex 10.1 and an Axon 700 A patch amplifier (Axon Instruments, Foster City, CA). All experiments were performed using whole-cell recording using visualized infrared-DIC with 2.5–3.5 M electrodes. Firing and input resistance were measured using a potassium-methanesulfonate based internal solution (in mM: 130 KOH, 105 methanesulfonic acid, 17 HCl, 20 HEPES, 0.2 EGTA, 2.8 NaCl, 2.5 mg/ml Mg-ATP, 0.25 mg/ml GTP, pH 7.2–7.4, 278–287 mOsm). DC current was passed to bring each neuron to ~-85 mV before starting firing experiments. Rheobase (minimum current needed to generate firing) was first identified for each cell by a series of 500 ms current steps, increasing in 20 pA increments, which was then terminated once rheobase was identified. We then began experiments where a more restricted set of 500 ms current steps (6–7 steps, 20 pA apart, with the first pulse subthreshold for firing) which were repeated every 30 s to measure possible changes in firing across the duration of the experiment. Depolarizing pulses alternated with a 30 pA hyperpolarizing pulse to examine the input resistance. Changes in firing and input resistance with 10 min of orexinA application (100 nM) was determined after ~15 min baseline, with SB added 5 min before orexinA exposure in some cells. To determine orexinA-related changes in firing, we averaged 7 min of baseline, and averaged the last 7 min of the 10-min orexinA exposure (since it usually takes 2–3 min before a drug effect is clear); we then subtracted the average number of action potentials generated during orexinA exposure from average number of spikes at baseline. This was determined at rheobase, the minimum current where firing was evoked, and at the current step above rheobase. Rheobase was 168 ± 24 pA (range: 100–320 pA) for experiments from alcohol-drinking mice, and 185 ± 22 pA (range: 125–240 pA) for alcohol-naïve experiments. EPSCs were measured using a cesium-methanesulfonate based internal solution (in mM: 120 cesium methanesulfonate, 20 HEPES, 0.4 EGTA, 2.8 NaCl, 5 TEA chloride, 2.5 Mg-ATP, 0.25 Na-GTP, pH 7.2–7.3, 270–285 mOsm). EPSCs were filtered at 2 kHz and digitized at 10 kHz. Series resistance (10-30 MΩ) and input resistance were monitored on-line using a 4-mV depolarizing step (50 ms) which was given after every EPSC. Electrically-evoked currents were elicited using a bipolar stimulating electrode placed ~200 μM dorsal to the recording site. As with firing, 7 min of baseline and orexinA exposure were used for determining the percent change in EPSCs with orexinA. Statistics for electrophysiology experiments were performed either using an unpaired t-test, to compare changes in firing in orexin-exposed neurons with or without SB pre-exposure, or using a paired t-test, to examine whether orexin exposure altered input resistance or EPSCs relative to pre-orexin baseline under a particular condition. Data analyses for behavioral studies In mice, after each drinking session, the water and alcohol (or saccharin) bottles were weighed; subsequently, these values were used to determine the intake of alcohol (g/kg of body weight) or saccharin (mL/kg of body weight), as well as water (ml/kg of body weight) and the preference ratio for the alcohol or saccharin (volume of reward intake/total volume of reward plus water intake). Due to variability of two-bottle choice alcohol drinking in mice, each mouse had two test sessions for vehicle and two test sessions for OXR blocker, and the average of the two drinking sessions for each treatment was used for a given animal. Importantly, all such tests were performed in a counterbalanced order: a mouse received vehicle vs. drug in a counterbalanced order for the first two test sessions, such that half the animals received vehicle in the first session, and the other half received OXR blocker in the first session. The same counterbalanced order was then used for the third and fourth test sessions, to insure that animals did not receive the same treatment in consecutive sessions, and to minimize the order effects. Rats received one test session of vehicle or SB, which was counterbalanced across animals, and active and inactive lever pressing, rewards received, and g/kg intake levels, were all determined. Finally, since the effects of vehicle and drug were tested within the same animal, all statistics for behavioral experiments were performed using a paired t-test, using SPSS (IBM). Different behavioral measures were assessed by separate paired t-tests. All data are shown as mean ± SEM. In our experience, alcohol intake levels in daily two-bottle choice sessions are more variable relative to operant responding, and bottle drinking in mice is more variable than in rat. Thus, we have adopted the method in mice where vehicle is tested twice and the two sessions averaged, and a given agent is tested twice then averaged. In addition, to determine test-retest variance, we examined the data for intra-mNAsh vehicle vs. SB during alcohol drinking. We first calculated the difference between the second-vehicle and first-vehicle test sessions that an animal underwent, or between the second-drug and first-drug test sessions. The standard deviation of test-retest was 2.54 g/kg for vehicle and 1.35 g/kg for SB. Although the test-retest variability was larger for vehicle, animals drank an average of 2.23 g/kg alcohol for vehicle sessions and 1.33 g/kg alcohol for SB sessions. Thus, the somewhat larger test-retest variability for vehicle sessions may reflect the larger volume of intake during vehicle sessions. In addition, to assess order effects, we performed a two-way RM ANOVA with drug vs. vehicle as one factor and the first vs. second test session of the given agent as a second factor. There were no significant effects of first vs. second session [F(1, 32) = 1.647, p = 0.209], or interaction of session number with group [vehicle or drug; F(1, 32) = 0.009, p = 0.924], although there was a significant effect of group [F(1, 32) = 7.602, p = 0.010], consistent with our previous analysis that SB in the mNAsh reduced alcohol drinking relative to vehicle. These findings suggest that there were no differences in intake between the first and second test sessions for either vehicle or drug. One limitation of the present experiments is the possibility that some experiments may be underpowered to observe a change in intake with OXR blockers, e.g., the trend for intra-mNAsh SB to decrease in intake in saccharin-consuming mice with n = 12 vs. n = 17 for alcohol-drinking mice. However, we were able to observe a significant depression of alcohol drinking in mice where SB was injected into the mPFC, with n = 9, suggesting that saccharin-intake experiments were sufficiently powered to detect any OXR-relate changes. For the off-site control experiments, it is clear even with n = 6 that there is no impact of SB on alcohol drinking, and if anything there is a trend for an increase in preference for alcohol (rather than inhibition of alcohol-related behavior). Nonetheless, with the smaller sample size, the off-site control group could be underpowered to detect differences in alcohol drinking. Result OX1R blockade in the medial NAc shell suppressed excessive alcohol drinking in mice We first examined whether OX1Rs in the mNAsh could regulate voluntary excessive alcohol drinking. In particular, we microinjected vehicle or a previously used concentration of the OX1R-selective antagonist, SB-334867 (SB, 3-μg/side) (Hollander et al., 2008; Espana et al., 2010; Plaza-Zabala et al., 2012), prior to an LDA drinking session using a counter-balanced, within-animal design (n = 17). Our results showed that inhibition of OX1Rs within the mNAsh (Figure 1A) significantly decreased alcohol drinking [Figure 1B; t(1, 16) = 2.78, p = 0.013]. No changes were observed in preference [Figure 1C; t(1, 16) = 0.58, p = 0.57], which likely reflects the low volume of concurrent water intake during the 2-h alcohol-drinking sessions [Figure 1D; t(1, 16) = 1.50, p = 0.15; see also Dhaher et al., 2009; Seif et al., 2015; den Hartog et al., 2016]. Thus, our results suggest that OX1Rs within the mNAsh are important for driving alcohol drinking. Suppression of alcohol drinking by the OX1R antagonist in the mNAsh might represent non-specific changes in motor function or consumption. Thus, we next examined whether SB within the mNAsh (Figure 2A) would reduce intake of 0.05% saccharin (n = 12). However, 3-μg of SB within the mNAsh had no effect on saccharin consumption [Figure 2B; t(1, 11) = 1.68, p = 0.12], preference [Figure 2C; t(1, 11) = 0.97, p = 0.35], or concurrent water intake [Figure 2D; t(1, 11) = 0.77, p = 0.46]. Thus, the suppression of alcohol drinking when infusing OX1R inhibitors within the mNAsh was likely due to a particular role in promoting alcohol drinking, rather than through more general regulation of consumption or activity. However, we do note that there was a trend for a decrease in saccharin intake with intra-mNAsh SB infusion. To assess the possible involvement of OX2Rs in alcohol drinking, we tested whether injection of the OX2R blocker TCS-OX2-29 (3-μg) into the mNAsh (Figure 3A; n = 13) would alter excessive alcohol consumption, similar to what we observed with intra-mNAsh SB. However, TCS within the mNAsh did not reduce alcohol intake [Figure 3B; t(1, 12) = 1.94, p = 0.08], and if anything had a trend to increase intake. TCS within the mNAsh also did not alter preference [Figure 3C; t(1, 12) = 0.14, p = 0.89] or concurrent water intake [Figure 3D; t(1, 12) = 1.27, p = 0.23]. These results indicate that OX1Rs but not OX2Rs within the mNAsh were important for promoting excessive alcohol drinking in mice. Figure 3 OX2R blockade within the mNAsh did not reduce alcohol drinking. (A) Locations of cannulae, as for Figure 1. (B–D) Infusion of 3-μg TCS within the mNAsh did not alter (B) alcohol intake, (C) preference, or (D) concurrent water intake. To test whether SB could affect alcohol drinking by diffusing and acting in a region adjacent to the mNAsh, we administered the same dose and vehicle into an off-site control region 1.5-mm dorsal to the mNAsh (n = 6; Figure 4A). However, no changes in alcohol intake were observed when 3-μg SB was injected into the off-site region control group [Figure 4B; t(1, 5) = 0.04, p = 0.97], and with no change in alcohol preference [Figure 4C; t(1, 5) = 2.22, p = 0.077] or concurrent water intake [Figure 4D; t(1, 5) = 1.56, p = 0.18]. Thus, the apparent mNAsh OX1R promotion of alcohol drinking was unlikely to reflect action of SB in brain areas above the mNAsh. Figure 4 OX1R blockade at an off-site control above the mNAsh did not alter alcohol drinking. (A) Locations of cannulae, as for Figure 1. (B–D) Infusion of 3-μg SB ~1.5 mM above the mNAsh did not alter (B) alcohol intake, (C) preference, or (D) concurrent water intake. In addition to the mNAsh, the aINS likely plays a central role in promoting many addiction-related behaviors. Thus, we also examined whether OX1Rs within the aINS would promote alcohol drinking (n = 9) (Figure 5A), as was observed for OX1Rs within the mNAsh (Figure 1). However, infusion of SB within the aINS had no effect on alcohol intake [Figure 5B; t(1, 8) = 0.03, p = 0.98], preference [Figure 5C; t(1, 8) = 0.17, p = 0.87] or concurrent water intake [Figure 5D; t(1, 8) = 0.73, p = 0.49]. Thus, contrary to our predictions, OX1Rs within the aINS did not play a role in promoting alcohol drinking in mice. Figure 5 OX1R blockade in the anterior Insular cortex did not alter alcohol drinking. (A) Locations of cannulae shown by gray circles; sections at approximately AP +2.22, +2.10, and +1.98 mm relative to Bregma. (B–D) Infusion of 3-μg SB within the aINS did not alter (B) alcohol intake, (C) preference, or (D) concurrent water intake. Finally, other cortical areas have also been implicated in regulating alcohol drinking, including the medial prefrontal cortex. In agreement, we found that infusion of 3-μg SB within the mPFC (Figure 6A; n = 9) significantly reduced alcohol drinking [Figure 6B; t(1, 8) = 2.34, p = 0.048], with no impact on preference [Figure 6C; t(1, 8) = 0.75, p = 0.47] or concurrent water intake [Figure 6D; t(1, 8) = 1.69, p = 0.13]. Thus, our results together suggest that mPFC but not aINS OX1Rs are important for promoting alcohol drinking. Figure 6 OX1R blockade in the mPFC significantly reduced alcohol drinking. (A) Locations of cannulae shown by gray circles; sections at approximately AP +1.98, +1.78, and +1.70 mm relative to Bregma. (B) Infusion of 3-μg SB within the mPFC decreased alcohol intake. (C,D) No changes in (C) alcohol preference or (D) concurrent water intake. *p < 0.05. NAsh OX1R blockade decreased lever pressing for alcohol in rats Since OX1R inhibition within the mNAsh of mice significantly reduced alcohol drinking, we next examined whether mNAsh OX1Rs would be important for promoting alcohol intake under a different drinking model, operant responding for alcohol in rats (n = 8) (Figure 7A). In fact, inhibition of OX1Rs within the mNAsh of rats with 3-μg SB significantly reduced lever-pressing for alcohol, tested within-rat vs. vehicle [Figure 7B; t(1, 7) = 4.17, p = 0.004], with an ~40% reduction, similar to what was observed in mice. OX1R inhibition had no effect on pressing of the inactive lever [Figure 7C; t(1, 7) = 1.34, p = 0.22], although this was already very low. In addition, OX1R inhibition within the mNAsh significantly reduced the number of rewards received [Figure 7D; t(1, 7) = 2.95, p = 0.021] and the amount of alcohol consumed [Figure 7E; t(1, 7) = 2.84, p = 0.025]. Thus, OX1Rs in the mNAsh were critical for promoting alcohol consumption in both mice and rats. Figure 7 OX1R blockade within the medial NAc Shell significantly reduced operant alcohol drinking in rats. (A) Locations of cannulae shown by gray circles; sections at approximately AP +1.70, +1.60, and +1.20 relative to Bregma. (B) Infusion of 3-μg SB within the mNAsh of rats decreased active lever presses for alcohol. (C) No changes in inactive lever presses with SB. (D,E) OX1R inhibition in the mNAsh reduced (D) rewards received and (E) alcohol intake levels. *p < 0.05. OrexinA peptide enhanced mNAsh action potential firing through OX1Rs Since OX1Rs within the mNAsh were important for promoting alcohol drinking, we next examined whether orexin would impact mNAsh firing ex vivo in brain slices from adult alcohol-drinking mice. In fact, firing evoked by depolarizing current pulses was significantly enhanced in the presence of orexinA (100 nM, n = 5), which was apparent when analyzing both at rheobase, the minimum current required to evoke action potentials in a cell [Figures 8A,B; paired t(4) = 6.54, p = 0.003], and at the current step above rheobase [Figure 8C; paired t(4) = 5.35, p = 0.006]. Importantly, this effect of orexinA was prevented by inhibition of OX1Rs with SB [3 μM, n = 4; Figures 8B,C; orexinA application with vs. without SB: t(7) = 4.09, p = 0.005 at rheobase; t(7) = 2.91, p = 0.023 at step above rheobase]. The orexinA increase in firing was not accompanied by any changes in input resistance, measured using a hyperpolarizing current pulse at resting potential [Figures 9A,B; 2.3 ± 2.7% change in R-input; paired t(4) = 1.26, p = 0.28]. In addition, orexinA did not alter EPSCs generated at a −70 mV resting potential [Figure 9C; n = 6; −3.7 ± 6.5% change in EPSC; paired t(5) = 0.21, p = 0.84]; this EPSC predominantly reflects AMPA receptor currents (Seif et al., 2013). Together, these results suggest that OX1Rs enhanced mNAsh activity in alcohol-drinking mice through altering intrinsic excitability but not glutamatergic function at −70 mV. Figure 8 OrexinA increased firing ex vivo in medial NAc Shell neurons from alcohol-drinking mice. (A) Example showing that 100 nM orexinA (OxA) increased firing in the mNAsh neurons from adult alcohol-drinking mice; firing was evoked by 500-ms depolarizing current pulses (See Section Methods). Example is from rheobase, the minimum current required to evoke firing, in this neuron (B,C) Averaged data showing the increased number of action potentials generated with OxA (B) at rheobase, and (C) at the current step above rheobase, and that blocking OX1Rs with SB prevented the OxA increase in firing. *p < 0.05. Figure 9 OrexinA ex vivo did not alter input resistance or evoked EPSCs in medial NAc Shell neurons from alcohol-drinking mice. (A,B) Examples (A) and grouped data (B) showing that OxA did not change input resistance (30 pA hyperpolarizing step). (C) Plot across time showing that OxA did not change evoked EPSCs at −70 mV. We also examined whether orexinA would alter firing in mNAsh neurons from alcohol-naïve mice. OrexinA (100 nM) significantly increased action potential firing by 1.6 ± 0.5 spikes at rheobase [paired t(4) = 3.30, p = 0.03; n = 5], which was not different from the orexin change in firing in alcohol-drinking mice [from Figure 8B; unpaired t(8) = 0.01, p = 0.99]. In addition, in agreement with results from alcohol-drinking mice, the orexin enhancement in firing in alcohol-naïve mice was not accompanied by any changes in input resistance [baseline: 307 ± 49 MΩ; orexin: 320 ± 48 MΩ; 4.7 ± 4.6% change in input resistance; paired t(4) = 1.20, p = 0.30]. Thus, orexin enhanced action potential firing in mNAsh neurons from both alcohol-naive and alcohol-drinking mice. Discussion Alcohol addiction is a significant economic and social problem, in part due to the strong motivation for alcohol that persons with AUDs exhibit. OX1Rs promote intake when there is strong drive for a reward, but the brain region(s) that mediate the OX1R promotion of excessive alcohol drinking remain largely unknown. Here, we demonstrate that the medial NAc Shell (mNAsh) is a critical region where OX1Rs act to promote excessive alcohol intake in mice. Inhibition of OX1Rs within the mouse mNAsh had no effect on consumption of saccharin or concurrent water drinking during alcohol drinking sessions, suggesting that mNAsh OX1R regulation of excessive alcohol intake was not due to nonspecific effects on motor activity or consumption. In addition, inhibition of OX2Rs within the mNAsh did not alter alcohol intake, suggesting a receptor-selective effect within the mNAsh. In addition, OX1R inhibition at an off-site control region above the mNAsh did not alter alcohol drinking. Surprisingly, OX1R inhibition within the mouse aINS also had no effect on excessive alcohol intake drinking, although aINS-NAc circuits are known to promote alcohol consumption and aINS OX1Rs drives nicotine intake. In contrast, OX1Rs within the mPFC did promote alcohol consumption. Further supporting the central role for mNAsh OX1Rs in promoting alcohol drinking, OX1R inhibition within the mNAsh of rats significantly reduced operant alcohol self-administration. Finally, orexin application ex vivo significantly enhanced action potential firing of mNAsh neurons from alcohol-drinking mice, with no changes in input resistance or evoked EPSCs. Together, our results suggest that the mNAsh and mPFC, but not the aINS, are critical regions where OX1R activation drives excessive alcohol drinking. While a number of studies suggest that OX1Rs play a prominent and selective role in responding for more motivating rewards (See Section Introduction), very little is known about the brain regions where OX1Rs act to promote excessive alcohol drinking. Here, we did not assess motivation directly, but instead examined the impact of orexin on drinking behaviors. Our findings are important since they identify the mNAsh as a region where OX1Rs drive alcohol consumption in both mice and rats. In addition, our studies indicate that OX2Rs within the mNAsh are not required to promote excessive alcohol consumption. Previous work has implicated the mNAsh in different forms of addictive and consummatory behaviors, including feeding (Baldo et al., 2013; Richard et al., 2013) and alcohol drinking (Kasten and Boehm, 2014; Lum et al., 2014; Wilden et al., 2014; Ramaker et al., 2015). The mNAsh also promotes different forms of reinstatement (Anderson et al., 2008), including for alcohol (Chaudhri et al., 2010; Marchant et al., 2015), although, under conditions of extinction, inhibiting the mNAsh promotes relapse for alcohol (Millan et al., 2010). However, cortical activation of the mNAsh promotes reinstatement of opiate conditioned place preference (CPP) (Hearing et al., 2016) and seeking (Bossert et al., 2015), and OXRs within the mNAsh also contribute to expression and reinstatement of morphine CPP (Qi et al., 2013; Sadeghzadeh et al., 2016). Thus, although the mNAsh contribution can vary depending on the addictive behavior, these studies overall concur with our findings that OX1Rs in the mNAsh promote alcohol drinking in vivo and increase neuronal activity ex vivo (see below). In contrast to the central role for mNAsh OX1Rs in driving alcohol consumption, OX1Rs within the aINS seemed to play no role in alcohol drinking. This was surprising because the aINS is thought to drive many addictive behaviors in both humans (Naqvi et al., 2014) and animals (Hollander et al., 2008; Seif et al., 2013), including compulsion-like alcohol drinking (Seif et al., 2013), and OX1Rs within the aINS mediate nicotine intake (Hollander et al., 2008). Thus, inasmuch as the aINS can promote alcohol drinking, it is likely that signaling systems other than OX1Rs within the aINS are required to promote addictive behavior. Also, OX1Rs in the medial prefrontal cortex promote cued reinstatement for alcohol in genetically-selected alcohol-preferring rats (Brown R. M. et al., 2015). In agreement, we found that mPFC OX1Rs were also important for promoting alcohol intake. Thus, our studies have identified critical regions of the cortico-accumbens circuit where OX1Rs act to promote excessive alcohol drinking. Since the mNAsh can regulate feeding, including OXRs within the mNAsh (Thorpe and Kotz, 2005; Urstadt and Stanley, 2015; but see Baldo and Kelley, 2001), the reduction of alcohol consumption after inhibiting mNAsh OX1Rs could reflect more general effects on motor and consumption. However, intra-mNAsh OX1R inhibition had no effect on saccharin consumption or concurrent water intake during alcohol-drinking sessions, suggesting that mNAsh OX1Rs play a more specific role in driving alcohol consumption. In agreement, previous studies found no change in chow intake or locomotor activity when OX1Rs were inhibited in the mNAsh (Thorpe and Kotz, 2005; Kotani et al., 2008; Qi et al., 2013). In addition, several studies implicating the mNAsh in alcohol drinking also observed no reduction in intake of sweet substances (Stratford and Wirtshafter, 2011; Rewal et al., 2012; Kasten and Boehm, 2014; Lum et al., 2014). Thus, although there was a trend for a decrease in saccharin intake in our results with intra-mNAsh SB infusion, it is more likely that this does not reflect an actual but underpowered decrease. Also, we found that mNAsh OX1R inhibition significantly reduced alcohol drinking but not preference, which likely reflects the low level of concurrent water intake during the alcohol access session (a similar pattern is also observed in Dhaher et al., 2009; Seif et al., 2015; den Hartog et al., 2016). Thus, while mNAsh signaling can contribute to many consummatory behaviors, our findings suggest that OX1Rs within the mNAsh play a particular role in promoting excessive alcohol drinking. In agreement with our observations that OX1R mNAsh promoted excessive alcohol drinking, we found that the orexin ex vivo enhanced action potential firing in mNAsh neurons from alcohol-drinking mice, and that this orexin increase in activity required OX1Rs. In contrast, there were no changes in evoked glutamatergic EPSCs, perhaps suggesting a primarily postsynaptic effect of orexin excitation within the mNAsh. In addition, orexin increased evoked firing with no changes in input resistance at the resting membrane potential. Interestingly, enhancement in mNAsh firing without changes at the hyperpolarized resting potential is similar to what has been reported for dopamine enhancement of mNAsh firing (Hopf et al., 2003). In agreement, NAc dopamine receptors regulate alcohol drinking and seeking (Bahi and Dreyer, 2012; Hauser et al., 2015), and dopamine receptors have been shown to interact with orexin to enhance mNAsh firing ex vivo (Mori et al., 2011). However, previous studies of orexin enhancement of mNAsh firing suggest a role for OX2Rs (Mukai et al., 2009; Mori et al., 2011), although these were performed in very young (12–16 d) animals, while our work was performed in adult neurons. Also, we did not find a role for OX2Rs within the mNAsh in promoting alcohol drinking. However, other work suggests that OX2Rs can interact with OX1Rs under some conditions, e.g., where either OX1R or OX2R inhibition in the mNAsh can suppress reinstatement of morphine CPP (Qi et al., 2013). Also, orexin enhancement of locomotion may be related to OX2Rs but not OX1Rs in the mNAsh (Thorpe and Kotz, 2005; Kotani et al., 2008), suggesting that mNAsh OX1Rs and OX2Rs can have differential effects. Furthermore, passive high alcohol exposures produce plasticity within the NAc Shell (Renteria et al., 2016), but we found that orexin enhanced firing ex vivo without changes in input resistance in both alcohol-drinking and alcohol-naïve mice. Nonetheless, understanding the ex vivo impact of orexinA is most critical in alcohol drinkers, since this physiological impact would be more relevant to the ability of mNAsh OX1Rs to drive alcohol intake. It is also important to understand whether the ability of OX1Rs to enhance mNAsh postsynaptic firing, but not glutamatergic activation, has a more general implication for behavioral regulation by the mNAsh. Our observation that OX1Rs increased mNAsh activity and promoted alcohol drinking are in overall agreement with previous studies using agents that inhibit neuronal function, such as GABA receptor agonists, where mNAsh inhibition decreases alcohol drinking (e.g., Stratford and Wirtshafter, 2011; Kasten and Boehm, 2014; Ramaker et al., 2015). While these studies do not demonstrate the postsynaptic function per se is the primary site of action, it is very likely that the behavioral impact of these compounds reflects inhibition of the NAc neuron activity that is known to promote behavioral expression in a number of other paradigms (e.g., McGinty et al., 2013; Pascoli et al., 2014). Thus, any action of orexin (or other neurochemicals) that increases activity of NAc neurons could promote behavioral expression of alcohol drinking. In addition, enhancement of mNAsh firing or glutamatergic activity could increase excitatory throughput of the mNAsh and increase behavioral expression, especially since NAc neurons postsynaptic firing is strongly dependent on glutamatergic excitation (Gerfen and Surmeier, 2011). Thus, while modulation of specific glutamatergic inputs to the mNAsh could alter specific aspects of behavior (e.g., Pascoli et al., 2014), it remains unclear what selective effects that overall modulation of firing vs. glutamatergic activation would have. Finally, we found that mNAsh OX1Rs did not significantly regulate intake of saccharin, in agreement with other work finding no reduction in intake of sweet substances after mNAsh inhibition (see above). In fact, increased intake of sweet and other highly palatable substances has been associated with strong inhibition of the mNAsh rather than excitation (Richard et al., 2013). In contrast, mNAsh OXRs have been associated with increased food intake in some, although not all, studies (Baldo and Kelley, 2001; Thorpe and Kotz, 2005; Urstadt and Stanley, 2015). Thus, the neuronal pathway activated by mNAsh OX1Rs seems to play a more selective impact on intake of certain substances (alcohol, food), with perhaps a very different role for other substances (sweets); this might provide insight into the specific consummatory pathways co-opted by drives for alcohol. It is important to note there have been mixed results regarding whether there are OX1Rs present in the NAshell and striatum, and that the OX1R-related blocker SB can still impact OX2Rs, although at lower affinity relative to OX1Rs (Smart et al., 2001). Importantly, however, our intracranial pharmacology experiments directly demonstrate that inhibition of OX1Rs but not OX2Rs within the mNAsh significantly reduced excessive alcohol drinking. These suggest that OX1Rs but not OX2Rs within the mNAsh promote excessive drinking. Nonetheless, while some studies have found some OX1R mRNA signal within the medial NAc (D'Almeida et al., 2005) and striatum (Hervieu et al., 2001, NAc not tested), others did not (Trivedi et al., 1998; Marcus et al., 2001). Also, a recent study utilizing a transgenic OX1R-GFP mouse found no OX1R-containing neurons within the NAc (Ch'ng and Lawrence, 2015). We note that mRNA levels do not always predict functional protein expression (e.g., as observed for OX1Rs for some brain regions described in Table 1 of Ch'ng and Lawrence, 2015). Also, small levels of receptor expression may be sufficient to allow functional signaling. e.g., where overlap of DA1R-cell and DA2R-cell markers can be seen in at least 20% of striatal neurons by electrophysiology and the very sensitive single-cell RT-PCR (Surmeier et al., 1996), even though transgenic GFP-expressing lines show very little overlap of DA1R-cell and D2R-cell markers in striatal neurons (Gerfen and Surmeier, 2011). In addition, OxA infusion within the mNAsh enhances feeding, which is prevented by SB, while OxA enhancement of locomotion is not prevented by SB (Thorpe and Kotz, 2005), indicating that SB can impact some but not all effects of OxA within the mNAsh, the remainder presumably reflecting action through OX2Rs. Also, development of morphine CPP is inhibited by SB but not OX2R inhibitors in the mNAsh (Sadeghzadeh et al., 2016). Finally, other studies have provided ex vivo evidence for functional OX1Rs within the mNAsh (Patyal et al., 2012), in addition to our demonstration of OX1R-dependent enhancement of mNAsh firing; we believe that these electrophysiological measures provide the most sensitive and direct method to assess the presence of functional receptors, in this case OX1Rs. Thus, since we directly demonstrated that inhibition of mNAsh OX2Rs with TCS had no impact on excessive alcohol drinking, our results taken together suggest that SB acts at OX1Rs within the mNAsh to suppress alcohol drinking. In addition, it is clear that the ability of OxR signaling to suppress alcohol drinking is region-specific, since both Insula and regions dorsal to the NAshell have Ox1Rs and OX2Rs, but SB within these regions had no impact on alcohol drinking. Finally, although our rat and mouse results implicate OX1R signaling within the mNAsh in promoting excessive alcohol drinking, we cannot completely rule out the possibility that the impact of intra-cranially infused SB inhibited alcohol drinking by action in a region medial or lateral to the mNAsh, such as the septum or NAc core. This is primarily a concern in mice, since we have previously shown that intra-mNAsh infusion in rats does not lead to effects within the adjacent NAc core, suggesting minimal effects of diffusion (Hopf et al., 2010). Also, the septum contains Ox1Rs although not mRNA for OX1Rs (see Wu et al., 2002; Ch'ng and Lawrence, 2015), while addiction-related orexin signaling has been associated with OX2Rs but not OX1Rs in the septum (Flores et al., 2016), and OX2Rs in the NAc core can regulate alcohol-related behavior (Brown et al., 2013). In contrast, here we found that OX1Rs but not OX2Rs drove excessive alcohol drinking in mice. Further experiments, perhaps involving local infusion of inhibitory RNAs, will be required to fully dissociate whether areas adjacent to the mNAsh are important for regulating alcohol drinking. Taken together, our studies indicate that OX1Rs within the mNAsh are critical for promoting excessive alcohol drinking, which may reflect the ability of orexin to increase action potential firing in an OX1R-dependent manner in mNAsh neurons from alcohol drinkers. In contrast, OX1Rs within the aINS did not regulate alcohol consumption, even though the aINS can regulate alcohol intake (Seif et al., 2013) and aINS OX1Rs can promote nicotine intake (Hollander et al., 2008). Since OX1Rs play a predominant role in driving motivated intake (see above), and excessive drinking in humans is driven by pathological drives for alcohol, our results suggest that the mNAsh is a key region where OX1Rs can promote excessive alcohol intake. Thus, OX1R inhibitors might represent a viable therapeutic intervention to suppress alcohol drinking in humans (Khoo and Brown, 2014; Li et al., 2016). Author contributions Study concept and design: KL, SW, FH. Acquisition of data: KL, SW, JY, AM, BH, FH; Statistical analyses and interpretation of data: KL, SW, FH; Preparation of manuscript: KL, FH. Funding Supported by NIAAA P50 AA017072. Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. We thank Dr. Dorit Ron for critical review of this manuscript, Jeffrey A. Simms for assistance with rat behavior, and Molly Sazer-Hopf for assistance with brain section images. ==== Refs References Anderson R. I. Becker H. C. Adams B. L. Jesudason C. D. Rorick-Kehn L. M. (2014 ). Orexin-1 and orexin-2 receptor antagonists reduce ethanol self-administration in high-drinking rodent models . Front. 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==== Front Evid Based Complement Alternat MedEvid Based Complement Alternat MedECAMEvidence-based Complementary and Alternative Medicine : eCAM1741-427X1741-4288Hindawi Publishing Corporation 10.1155/2016/4343084Research ArticleIcariin Attenuates OGD/R-Induced Autophagy via Bcl-2-Dependent Cross Talk between Apoptosis and Autophagy in PC12 Cells http://orcid.org/0000-0002-2963-7422Mo Zhen-tao 1 http://orcid.org/0000-0002-9471-9176Li Wen-na 1 http://orcid.org/0000-0002-1926-9531Zhai Yu-rong 1 http://orcid.org/0000-0002-8967-337XGong Qi-hai 2 * 1Zunyi Medical University, Zhuhai Campus, Zhuhai, Guangdong 519041, China2Department of Pharmacology and Key Laboratory of Basic Pharmacology of Ministry of Education, Zunyi Medical University, Zunyi 563000, China*Qi-hai Gong: gqh@zmc.edu.cnAcademic Editor: Luciana Dini 2016 16 8 2016 2016 434308411 4 2016 11 7 2016 25 7 2016 Copyright © 2016 Zhen-tao Mo et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Icariin (ICA), an active component of Epimedium brevicornum Maxim, exerts a variety of neuroprotective effects such as antiapoptosis. However, the mechanisms underlying antiapoptosis of ICA in neurons exposed to oxygen-glucose deprivation and reperfusion (OGD/R) are unclear. The B-cell lymphoma-2 (Bcl-2) protein family plays an important role in the regulation of apoptosis and autophagy through Bcl-2-dependent cross talk. Bcl-2 suppresses apoptosis by binding to Bax and inhibits autophagy by binding to Beclin-1 which is an autophagy related protein. In the present study, MTT result showed that ICA increased cell viability significantly in OGD/R treated PC12 cells (P < 0.01). Results of western blotting analysis showed that ICA increased Bcl-2 expression significantly and decreased expressions of Bax, cleaved Caspase-3, Beclin-1, and LC3-II significantly in OGD/R treated PC12 cells (P < 0.01). These results suggest that ICA protects PC12 cells from OGD/R induced autophagy via Bcl-2-dependent cross talk between apoptosis and autophagy. National Natural Science Foundation of China81560585Guizhou Science and Technology Foundation of ChinaLKZ[2013]04Zhuhai Government FundIRT1197Program for New Century Excellent Talents in UniversityNCET-11-0927 ==== Body 1. Introduction Oxygen-glucose deprivation and reperfusion (OGD/R) result in neuronal apoptosis and autophagy. Apoptosis is a process of programmed cell death. Autophagy, a pathway of cellular protein degradation, is usually activated by starvation, ischemia, growth factor deficit, and so forth and helps to maintain cellular protein homeostasis [1–3], but excessive activation of autophagy may also result in autophagic cell death and apoptosis [4–6]. The B-cell lymphoma-2 (Bcl-2) family of proteins plays an important role in cross talk between apoptosis and autophagy. The Bcl-2 family of proteins consists of antiapoptotic members such as Bcl-2 and Bcl-xL and proapoptotic members such as Bax and Bak. Bcl-2 suppresses apoptosis by binding to Bax and inhibits autophagy by binding to Beclin-1 which is an autophagy related protein [7–9]. ICA, an active flavonoid of Epimedium brevicornum Maxim, possesses various neuroprotective effects including anti-inflammation, antioxidation, and antiapoptosis [10–12]. It was reported that ICA protected neurons against OGD induced apoptosis [13]. However, the underlying mechanisms are incompletely understood. Whether ICA can protect cells from OGD induced autophagy via Bcl-2-dependent cross talk between apoptosis and autophagy is unknown. Therefore, in this study, we evaluated the abovementioned potential mechanisms of ICA in rat pheochromocytoma PC12 cells which were widely used in the study of neuropharmacology [14, 15]. 2. Materials and Methods 2.1. ICA Preparation ICA (purity, 98.3% by HPLC) was purchased from Nanjing Zelang Pharmaceutical Technology Co., Ltd. (Nanjing, China). ICA was dissolved in dimethyl sulfoxide (DMSO) to 10-3 M and stored at −20°C. When ICA was used, 10-3 M ICA was diluted with Earle's balanced salt solution or full culture medium to the final concentration of 10-5 M. The composition of Earle's balanced salt solution and full culture medium is previously reported [14]. Earle's balanced salt solution was composed of 116 m M NaCl, 5.4 mM KCl, 1 mM NaH2PO4, 0.9 mM CaCl2, 0.8 mM MgSO4, and 10 mg/L phenol red. The full culture medium contained 4.5 g/mL glucose, 5% foetal bovine serum (Gibco, USA), and 5% horse serum (Gibco, USA) in Dulbecco's modified Eagle's medium (DMEM). 2.2. Cell Cultures PC 12 cells (American Type Culture Collection, CRL-1721) were cultured as previously described [14]. PC12 cells were cultured in full culture medium and were incubated at 37°C in 5% CO2. Culture medium was refreshed every two days. 2.3. OGD/R PC12 cells were deprived of oxygen and glucose for 2 h to simulate ischemic injury in vitro as previously described [14]. PC12 cells were rinsed with phosphate buffer solution (PBS) once and incubated in Earle's balanced salt solution as described above. Then, the cells were incubated in a hypoxia chamber (HF100, Heal Force, China) with 1% O2, 94% N2, and 5% CO2 for 2 h. After deprivation of glucose and hypoxia, Earle's balanced salt solution was removed and the cells were cultured in full culture medium under normoxic conditions for 24 h. Normal control cells were refreshed with full culture medium and cultured in a CO2 incubator (HF90, Heal Force, China) under normoxic conditions. 2.4. Drug Administration PC12 cells were pretreated with 10−5 M ICA or 10 μM nimodipine in full culture medium under normoxic conditions for 1 h before hypoxia. The cells were washed with PBS once and incubated in Earle's balanced salt solution supplemented with 10−5 M ICA or 10 μM nimodipine under hypoxia conditions for 2 h. Based on our pilot experiment, we have used ICA at the concentrations of 10−7, 10−6, and 10−5 M and found the concentration of 10−5 M is effective and appropriate. 2.5. Metabolic 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium Bromide (MTT) Assay 0.1 mL of cells (1 × 105 cells/mL) was seeded into 96-well plates. The cells were divided into four groups: normal group, model group, nimodipine group, and ICA group. Each group contained 10 samples. After growth for two days, the cells were treated with OGD/R and drug administration as described above. MTT assay was performed as previously described [14]. Absorbance was measured at 570 nm on an ELISA reader (Multiskan Mk3, Thermo Scientific, USA). 2.6. Western Blotting Analysis It contained 6 samples in normal group, model group, and drug treated groups, respectively. Cell lysates were prepared by incubation in RIPA lysis buffer containing protease inhibitors. Protein concentrations were measured with a BCA kit. Approximately 30 µg of total protein was separated by SDS-PAGE (5%–10%) and then transferred to polyvinylidene fluoride (PVDF) membranes. Membranes were blocked with 5% nonfat dry milk for 60 min at room temperature and incubated with primary antibodies against Bcl-2 (1 : 1000, Cell Signaling Technology, USA), Bax (1 : 1000, Cell Signaling Technology, USA), Beclin-1 (1 : 1000, Cell Signaling Technology, USA), LC3 (1 : 1000, Novus Biologicals, USA), Caspase-3 (1 : 1000, Cell Signaling Technology, USA), and GAPDH antibodies (1 : 1000, Millipore, USA) at 4°C overnight followed by incubation with HRP-conjugated goat anti-rabbit IgG antibody (1 : 5000, Shanghai Kangchen Biotechnology, China) at room temperature for 90 min. The immunoblots were visualized using enhanced chemiluminescence provided with the ECL kit (Millipore, USA) and exposure to film. The density of blots was quantified using Band-Scan software. 2.7. Statistical Analysis Data were expressed as the mean ± SD. Statistical significance was analyzed with one-way ANOVA. P value of less than 0.05 was considered significant. 3. Results 3.1. ICA Increased Cell Viability in OGD/R Treated PC12 Cells Cell viability of OGD/R treated PC12 cells (0.27 ± 0.02) was markedly decreased compared with the normal cultured cells (0.58 ± 0.05, P < 0.01). However, cell viability of OGD/R treated cells was dramatically increased after ICA (10−5 M) or nimodipine (10 μM) administration (0.40 ± 0.04 in ICA group, 0.38 ± 0.03 in nimodipine group, P < 0.01) (Figure 1). Our previous study showed that nimodipine could increase cell viability of OGD/R treated PC12 cells, so we set nimodipine as a positive control group [14]. 3.2. ICA Increased Bcl-2 Expression and Decreased Bax and Cleaved Caspase-3 Expressions in OGD/R Treated PC12 Cells Protein levels of Bcl-2, Bax, and cleaved Caspase-3 were significantly increased by OGD/R treatment (Bcl-2: 0.27 ± 0.12, P < 0.05; Bax: 0.82 ± 0.08, P < 0.01; cleaved Caspase-3: 1.37 ± 0.17, P < 0.01), compared to the normal control cells (Bcl-2: 0.13 ± 0.07; Bax: 0.34 ± 0.14; cleaved Caspase-3: 0.40 ± 0.20). However, ICA decreased Bax and cleaved Caspase-3 levels and increased Bcl-2 levels significantly in OGD/R treated cells (Bax: 0.61 ± 0.13, P < 0.01; cleaved Caspase-3: 0.98 ± 0.15, P < 0.01; Bcl-2: 0.53 ± 0.15, P < 0.01) (Figures 2 and 3). It was reported that nimodipine increased Bcl-2 expression and reduced expression of cleaved Caspase-3 and Bax in mice following middle cerebral artery occlusion (MCAO) injury, so we set nimodipine as a positive control group [16]. 3.3. ICA Decreased Beclin-1 and LC3-II Expressions in OGD/R Treated PC12 Cells Protein levels of Beclin-1 and LC3-II were low in normal cultured cells (Beclin-1: 0.69 ± 0.06; LC3-II: 0.30 ± 0.05), but they were dramatically increased after OGD/R treatment (Beclin-1: 1.32 ± 0.17, P < 0.01; LC3-II: 1.15 ± 0.18, P < 0.01). However, ICA decreased Beclin-1 and LC3-II expressions significantly in OGD/R treated cells (Beclin-1: 0.92 ± 0.12, P < 0.01; LC3-II: 0.79 ± 0.18, P < 0.01) (Figures 4 and 5). Our previous study showed that nimodipine could reduce Beclin-1 expression and autophagosomes of OGD/R treated PC12 cells, so we set nimodipine as a positive control group [14]. 4. Discussion ICA possesses remarkable pharmacological activities on many kinds of central nervous system diseases. It can reduce neuronal injury caused by ischemic stroke in vitro and in vivo, attenuate learning and memory deficits, and alleviate depression [10, 11, 17]. Its potential mechanisms include anti-inflammation, antioxidation, and antiapoptosis [10–12]. Apoptosis is a process closely related to autophagy, and there are several cross talks between them. The role of ICA in autophagy and the cross talk between apoptosis and autophagy is obscure. Apoptosis, also called programmed cell death, is regulated by a variety of apoptosis related proteins including Bcl-2 family proteins. Bcl-2 family proteins consist of antiapoptotic proteins such as Bcl-2 and Bcl-xL and proapoptotic proteins such as Bax and Bak. Bcl-2 and Bax levels are directly related to the occurrence of apoptosis. When Bcl-2 expression is increased, Bcl-2 binds to Bax to form heterodimers and inhibits the apoptosis. When Bax expression is increased, Bax forms homodimers and promotes apoptosis [7]. Caspase-3, the executor of apoptosis, can be activated by Bax homodimers [18]. When Caspase-3 is activated, procaspase-3 is cut into an active fragment cleaved Caspase-3 and then plays the role of proteolytic enzymes to promote apoptosis [19]. Therefore, cleaved Caspase-3 is a molecular level indicator which directly reflects cellular apoptosis [20]. In the present study, we showed that Bcl-2 protein expression was significantly decreased (as shown in Figure 2); Bax and cleaved Caspase-3 protein expression were dramatically increased in PC12 cells exposed to OGD/R, compared to normal control group, whereas these effects were significantly reversed by ICA treatment (as shown in Figures 2 and 3), suggesting that ICA inhibits apoptosis in PC12 cells through upregulation of Bcl-2 protein expression and downregulation of Bax protein expression. Autophagy is a process of self-degradation through an autophagosomal-lysosomal pathway. It plays a key role in providing energy and raw material and turning over useless protein and organelles [1–3]. However, high level of autophagy may also aggravate cellular damage and result in autophagic cell death or apoptosis [4–6]. Protein light 1 chain microtubule-associated 3 (MAP1LC3) is a key protein that proves the occurrence of autophagy. LC3 converts to LC3-I and LC3-II during autophagy. LC3-II is a key component of autophagosome membranes [21], so LC3-II is a marker of autophagy. Beclin-1, an autophagy related protein, was first discovered in mammals. It can mediate other autophagic proteins attached to autophagosome membranes and reduce LC3-II accumulation [22]. Beclin-1 is also an important indicator to measure the degree of autophagy [23, 24]. As shown in Figures 4 and 5, ICA treatment reduced Beclin-1 and LC3-II protein expression in OGD/R treated PC12 cells. In our previous study, we demonstrated that Beclin-1 expression and autophagosomes were increased in PC12 cells subjected to 2 h of OGD, followed by 24 h of reperfusion, whereas the autophagy inhibitor 3-methyladenine (3-MA) reduced them in the OGD/R treated group [25]. The model was made the same as in this work. Since LC3-II is a component of autophagosome membranes, these results and our previous work suggest that ICA reduces autophagy. Bcl-2 is an important protein that inhibits apoptosis and autophagy. It not only combines with Bax to inhibit apoptosis but also binds to Beclin-1 to form a complex that inhibits Beclin-1 and autophagy activation, while maintaining resistance to apoptosis [7–9]. Our results, as shown in Figures 2 and 4, and these literatures suggest that ICA increases Bcl-2 protein expression, which further reduces the protein levels of Bax and Beclin-1. Calcium overload leads to apoptosis and autophagy [26, 27]. Our previous studies have indicated that nimodipine, a calcium antagonist, can decrease intracellular free Ca2+ concentration and autophagy in PC12 cells subjected to OGD/R [27, 28]. Therefore, this work set nimodipine as a positive control group. This study demonstrated that ICA increased Bcl-2 protein expression, reduced the protein expression of Bax, Beclin-1, LC3-II, and cleaved Caspase-3, and enhanced cell viability in PC12 cells subjected to OGD/R. These results suggest that ICA may reduce the level of autophagy and apoptosis via activating Bcl-2-dependent cross talk between apoptosis and autophagy. Acknowledgments This work was supported by the National Natural Science Foundation of China (no. 81560585), Guizhou Science and Technology Foundation of China (no. LKZ[2013]04), Premier-Discipline Enhancement Scheme Supported by Zhuhai Government Fund, Program for Changjiang Scholars and Innovative Research Team in University, China (Grant no. IRT1197), and Program for New Century Excellent Talents in University (Grant no. NCET-11-0927). Competing Interests The authors declare that there is no conflict of interests regarding the publication of this paper. Figure 1 Effects of ICA on cell viability in OGD/R injured PC12 cells. OGD/R treated cells were subjected to 2 h OGD and 24 h reperfusion. ICA (10−5 M) or nimodipine (10 μM) was given 1 h before OGD and acting through 2 h OGD. Normal control cells were refreshed with full culture medium and cultured under normoxic conditions. Cell viability was determined by MTT assay. Each group contained 10 samples. ## P < 0.01 compared with normal control group. ∗∗ P < 0.01 compared with OGD/R group. CON: normal control, OGD/R+NM: OGD/R+ nimodipine. Figure 2 Effects of ICA on Bcl-2 and Bax expressions in OGD/R injured PC12 cells. OGD/R treated cells were subjected to 2 h OGD and 24 h reperfusion. ICA (10−5 M) or nimodipine (10 μM) was given 1 h before OGD and acting through 2 h OGD. Normal control cells were refreshed with full culture medium and cultured under normoxic conditions. Bax ((a) and (b)) and Bcl-2 ((a) and (c)) protein expressions were measured by western blotting. Each group contained 6 samples. ## P < 0.01 compared with normal control group. ∗∗ P < 0.01 compared with model control group. ∗ P < 0.05 compared with model control group. CON: normal control, OGD/R+NM: OGD/R+ nimodipine. Figure 3 Effects of ICA on cleaved Caspase-3 expression in OGD/R injured PC12 cells. OGD/R treated cells were subjected to 2 h OGD and 24 h reperfusion. ICA (10−5 M) or nimodipine (10 μM) was given 1 h before OGD and acting through 2 h OGD. Normal control cells were refreshed with full culture medium and cultured under normoxic conditions. Cleaved Caspase-3 expression was measured by western blotting. Each group contained 6 samples. ## P < 0.01 compared with normal control group. ∗∗ P < 0.01 compared with model control group. ∗ P < 0.05 compared with model control group. CON: normal control, OGD/R+NM: OGD/R+ nimodipine. Figure 4 Effects of ICA on Beclin-1 expression in OGD/R injured PC12 cells. OGD/R treated cells were subjected to 2 h OGD and 24 h reperfusion. ICA (10−5 M) or nimodipine (10 μM) was given 1 h before OGD and acting through 2 h OGD. Normal control cells were refreshed with full culture medium and cultured under normoxic conditions. Beclin-1 expression was measured by western blotting. Each group contained 6 samples. ## P < 0.01 compared with normal control group. ∗∗ P < 0.01 compared with model control group. ∗ P < 0.05 compared with model control group. CON: normal control, OGD/R+NM: OGD/R+ nimodipine. Figure 5 Effects of ICA on LC3II expression in OGD/R injured PC12 cells. OGD/R treated cells were subjected to 2 h OGD and 24 h reperfusion. ICA (10−5 M) or nimodipine (10 μM) was given 1 h before OGD and acting through 2 h OGD. Normal control cells were refreshed with full culture medium and cultured under normoxic conditions. LC3II expression was measured by western blotting. Each group contained 6 samples. ## P < 0.01 compared with normal control group. ∗∗ P < 0.01 compared with model control group. CON: normal control, OGD/R+NM: OGD/R+ nimodipine. ==== Refs 1 Alirezaei M. Kemball C. C. Flynn C. T. Wood M. R. Whitton J. L. Kiosses W. B. Short-term fasting induces profound neuronal autophagy Autophagy 2010 6 6 702 710 10.4161/auto.6.6.12376 2-s2.0-77955894794 20534972 2 Wang P. Xu T.-Y. Wei K. ARRB1/β -arrestin-1 mediates neuroprotection through coordination of BECN1-dependent autophagy in cerebral ischemia Autophagy 2014 10 9 1535 1548 10.4161/auto.29203 2-s2.0-84907163183 24988431 3 Ecker N. Mor A. Journo D. Abeliovich H. Induction of autophagic flux by amino acid deprivation is distinct from nitrogen starvation-induced macroautophagy Autophagy 2010 6 7 879 890 10.4161/auto.6.7.12753 2-s2.0-77957657436 20647741 4 Siddiqui M. A. Mukherjee S. Manivannan P. Malathi K. 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==== Front Stem Cells IntStem Cells IntSCIStem Cells International1687-966X1687-9678Hindawi Publishing Corporation 10.1155/2016/9378081Research ArticleCharacterization of Cellular and Molecular Heterogeneity of Bone Marrow Stromal Cells Elsafadi Mona 1 2 Manikandan Muthurangan 1 Atteya Muhammad 1 3 Hashmi Jamil Amjad 4 Iqbal Zafar 5 Aldahmash Abdullah 1 6 Alfayez Musaad 1 http://orcid.org/0000-0003-1557-0869Kassem Moustapha 1 2 http://orcid.org/0000-0002-9199-0120Mahmood Amer 1 2 * 1Stem Cell Unit, Department of Anatomy, College of Medicine, King Saud University, Riyadh, Saudi Arabia2Molecular Endocrinology Laboratory (KMEB), Department of Endocrinology, University of Southern Denmark, Odense, Denmark3Department of Histology, Faculty of Medicine, Cairo University, Egypt4Center for Genetics and Inherited Diseases, Taibah University, Al-Madina Al-Munawara, Saudi Arabia5College of Applied Medical Sciences, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), National Guards Health Affairs, Riyadh, Saudi Arabia6Prince Naïf Health and Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia*Amer Mahmood: ammahmood@ksu.edu.saAcademic Editor: Giorgio Mori 2016 16 8 2016 2016 937808114 4 2016 26 5 2016 Copyright © 2016 Mona Elsafadi et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Human bone marrow-derived stromal stem cells (hBMSC) exhibit multiple functions, including differentiation into skeletal cells (progenitor function), hematopoiesis support, and immune regulation (nonprogenitor function). We have previously demonstrated the presence of morphological and functional heterogeneity of hBMSC cultures. In the present study, we characterized in detail two hTERT-BMSC clonal cell populations termed here CL1 and CL2 that represent an opposing phenotype with respect to morphology, markers expression: alkaline phosphatase (ALP) and CD146, and ex vivo differentiation potential. CL1 differentiated readily to osteoblasts, adipocytes, and chondrocytes as shown by expression of lineage specific genes and proteins. Whole genome transcriptome profiling of CL1 versus CL2 revealed enrichment in CL1 of bone-, mineralization-, and skeletal muscle-related genes, for example, ALP, POSTN, IGFBP5 BMP4, and CXCL12. On the other hand, CL2 transcriptome was enriched in immune modulatory genes, for example, CD14, CD99, NOTCH3, CXCL6, CFB, and CFI. Furthermore, gene expression microarray analysis of osteoblast differentiated CL1 versus CL2 showed significant upregulation in CL1 of bone development and osteoblast differentiation genes which included several homeobox genes: TBX15, HOXA2 and HOXA10, and IGF1, FGFR3, BMP6, MCAM, ITGA10, IGFBP5, and ALP. siRNA-based downregulation of the ALP gene in CL1 impaired osteoblastic and adipocytic differentiation. Our studies demonstrate the existence of molecular and functional heterogeneity in cultured hBMSC. ALP can be employed to identify osteoblastic and adipocytic progenitor cells in the heterogeneous hBMSC cultures. King Saud University ==== Body 1. Introduction Human bone marrow stromal (also known as skeletal or mesenchymal) stem cells (hBMSC) are increasingly employed in clinical trials for enhancing tissue regeneration following injury [1]. Typically, hBMSC are isolated by their ability to adhere to the plastic surfaces of in vitro culture plates. However, the cultured hBMSC exhibit morphological heterogeneity suggesting the presence of functional heterogeneity [2, 3]. It has also been suggested that the use of heterogeneous cell populations in clinical trials of hBMSC-based therapies caused variability in the observed treatment effects [4]. Thus, for the efficient use of hBMSC in therapy, better cellular and molecular characterization of hBMSC is required [1, 4]. There exist no specific markers that define the hBMSC phenotype. The plastic-adherent hBMSC are defined by the presence of surface expression of some CD surface markers with variable sensitivity and specificity [1]. Single cell clonal analysis revealed that only 25% of the cells are true stem cells based on their ability to differentiate into osteoblasts, adipocytes, and chondrocytes (trilineage differentiation) and to form heterotopic bone and bone marrow organ when implanted in vivo subcutaneously in immune deficient mice [5]. The identity of the remaining cells is not clarified, but they may represent lineage-committed cells [3]. Therefore, it is plausible that functional heterogeneity exists in cultured hBMSC, reflecting the in vivo functional and developmental heterogeneity of hBMSC [6]. In addition to their ability to differentiate into skeletal tissue cells (known as progenitor function), hBMSC possess immunomodulatory characteristics (known as nonprogenitor functions) [7]. It is not clear whether these different functions are mediated by a number of independent subpopulations within the hBMSC [2]. Only a few studies have tried to identify the subpopulation within cultured hBMSC based on surface markers, for example, STRO1 and alkaline phosphatase (ALP), but limited molecular phenotyping has been conducted [8]. We have previously demonstrated the presence of morphological and functional heterogeneity of clones isolated from telomerized hMSC (hMSC-TERT) cell line [3]. The aim of the present study was therefore to further study in detail the heterogeneity of cultured hBMSC as demonstrated by two clonal cell lines with opposite cellular and functional phenotype. We also employed the DNA microarrays to define their molecular signature and signaling pathways associated with their functional phenotype. 2. Experimental Procedures 2.1. Cell Culture As a model for hBMSC, we employed immortalized hBMSC-TERT cell line that is created from normal human BMSC by overexpression of human telomerase reverse transcriptase gene (hTERT) [9]. The hBMSC-TERT cells have been extensively characterized, and they exhibit similar cellular and molecular phenotype to primary MSC [10]. CL1 and CL2 cells are clonal cell populations of hBMSC-TERT identified in long term culture (passage numbers 15–25) of hBMSC-TERT and were chosen based on their distinct and different morphologies. Cells were cultured in Dulbecco's Modified Eagle Medium (DMEM) supplemented with D-glucose 4500 mg/L, 4 mM L-glutamine and 110 mg/L sodium pyruvate, 10% Fetal Bovine Serum (FBS), 1x penicillin-streptomycin (Pen-strep), and nonessential amino acids (all purchased from Gibco-Invitrogen, USA). For some control experiments, primary bone marrow derived MSC (phBMSC) were employed. Sixty milliliters of bone marrow was aspirated from the iliac crest bone of consenting healthy donors. This procedure was approved by the King Khalid University Hospital-King Saud University ethics committee. phBMSC were isolated from bone marrow mononuclear cells by plastic adherence as described previously [9]. 2.2. Cell Proliferation Cell proliferation rate was determined by counting cell number and calculating population doubling (PD) rate. The cells were cultured in 25 cm2 tissue culture Petri dish at cell density 0.5 × 106 cells (28000 cells/cm2). At confluence, the cells were trypsinized and counted manually by hemocytometer. At each passage, population doubling was determined by the following formula: log⁡N/log⁡2, where N is the number of cells at confluence divided by the initial cell number. Cumulative PD level is the sum of population doublings, and PD rate is PD/time in culture. 2.3. Flow Cytometry Cells were trypsinized to a single cell suspension, were recovered by centrifugation at 200 g for 5 min, washed twice in ice-cold PBS supplemented with 2% BSA, and resuspended at a concentration of 105 cells/antibody. After incubation with the preconjugated antibodies, or matched isotype controls, for 30 min on ice in the dark, cells were washed with PBS, resuspended in 500 μL of PBS, and analyzed in the BD FACSCalibur flow cytometer (BD Biosciences). Living cells were gated in a dot plot of forward versus side scatter signals acquired on a linear scale. At least 10,000 gated events were acquired on a log fluorescence scale. Positive staining was distinct as the emission of a fluorescence signal that surpassed levels achieved by >99% of control cell population stained with corresponding isotype antibodies. The ratios of fluorescence signals versus scatter signals were calculated, and histograms were generated using the software Cell Quest Pro Software Version 3.3 (BD Biosciences). The following antibodies were used all from BD Biosciences: FITC-PE-APC-Mouse IgG1k isotype control, APC-Mouse Anti-Human CD44 (#559942), FITC-Mouse Anti-Human CD63 (#557305), PE-Mouse Anti-Human CD73 (#550257), PE-Mouse Anti-Human CD105 (#560839), PE-Mouse Anti-Human CD146 (#550315), PE-Mouse Anti-Human CD166 (#560903), and Alexa Fluor® 488 Mouse Anti-Human Alkaline Phosphatase (#561495). 2.4. Electron Microscopy After trypsinizing the hBMSC cells from the flasks or 6-well plates were collected, the samples were washed with PBS, and the pellets were resuspended directly in 2.5% glutaraldehyde in 0.1 M phosphate buffer (pH 7.2), and kept at 4°C for 4 hr. First, the cells were washed with 0.1 M phosphate buffer (pH 7.2) and transferred to 1% osmium tetroxide (OsO4) solution in 0.1 M phosphate buffer (pH 7.2) for two hr. The cells were dehydrated in ascending grades of ethanol. The cells were then resuspended in acetone and were aliquoted into BEEM embedding capsules and infiltrated with acetone: resin mixture followed by embedding in a pure resin mixture for two hr. Semithin sections (0.5 μm thickness) and ultrathin sections (70 nm thickness) were prepared, examined, and photographed under a transmission electron microscope (TEM) (Jeol 1010, Jeol, Tokyo, Japan). 2.5. In Vitro Osteoblast Differentiation Cells were grown in standard DMEM growth medium in 6-well plates at 20,000 cell/cm2. When 70–80% confluence was achieved, test cells were cultured in DMEM supplemented with osteoblastic induction mixture (referred to as OS) containing 10% FBS, 1% Pen-strep, 50 μg/mL L-ascorbic acid (Wako Chemicals, Neuss, Germany), 10 mM β-glycerophosphate (Sigma) and 10 nM calcitriol (1α,25-dihydroxyvitamin D3; Sigma), and 10 nM dexamethasone (Sigma); noninduced cells (referred to as Cont) were cultured in normal growth media for the same duration as induced. The media were replaced three times per week. Cells cultured in standard culture medium were considered as control. At day 14 of differentiation, mineralized nodules became apparent and were stained with Alizarin Red S and ALP. 2.6. In Vitro Adipocyte Differentiation Cells were grown in standard DMEM growth medium in 6-well plates at 0.3 × 106 cells/mL. At 90–100% confluence, cells were cultured in DMEM supplemented with adipogenic (Adip) induction mixture containing 10% FBS, 10% Horse Serum (Sigma), 1% Pen-strep, 100 nM dexamethasone, 0.45 mM isobutyl methylxanthine (Sigma), 3 μg/mL insulin (Sigma), and 1 μM Rosiglitazone (Novo Nordisk, Bagsvaerd, Denmark). The media were replaced three times per week. Cells cultured in standard culture medium were considered as control. From day 3 of differentiation, small lipid droplets became visible and at day 7 they were stained with Oil Red-O and Nile red. 2.7. In Vitro Chondrogenic Differentiation Both CL1 and CL2 cells were trypsinized and counted, around 1 × 106 cells taken in each 15 mL conical tube centrifuged at 400 ×g for 5 minutes. For chondrocyte differentiation pellet culture system used, chondrocyte induction was done in media containing advanced DMEM/F12 supplemented with 1% ITS Premix Tissue Culture Supplement, 100 nM dexamethasone, Glutamax, and 10 ng/mL transforming growth factor-beta-3 (TGFβ-3). Cells were maintained in chondrocyte differentiation media for 21 days and changed every two days. 2.8. Cytochemical Staining 2.8.1. Alkaline Phosphatase (ALP) Staining CL1 and CL2 cells were stained before OS differentiation for the basal ALP expression and after OB differentiation at day 7 of induction. Cells cultured in 6-well plates were washed in PBS −/− (-Ca, -Mg) and fixed in acetone/citrate buffer 10 mM at pH 4.2 for 5 min at room temperature. The Naphthol/Fast Red stain [0.2 mg/mL Naphthol AS-TR phosphate substrate (Sigma)] [0.417 mg/mL of Fast Red (Sigma)] was added for one hour at room temperature. Histological tissue blocks were sectioned at 4 microns. Immunohistochemical staining was performed on CL1 and CL2 chondrocyte 3D pellets using DAKO EnVision and PowerVision according to the manufacturer's instructions (DAKO, Glostrup, Denmark). Briefly, paraffin sections were incubated for 1 hour at room temperature with primary antibodies diluted in ChemMate (DAKO) (Human Anti-Col-10 and Human Anti-Col-2 ABI). Sections were washed subsequently in Tris-buffered saline (TBS, 0.05 M, pH 7.4), incubated for 30 minutes with secondary anti-mouse Ig/HRP-conjugated polymers (K4001, En Visionþ, DAKO), and visualized with 3,30-diaminobenzidine tetrahydrochloride (DAB, S3000, DAKO) or with 3-amino-9-ethylcarbazole (AEC, DAKO) according to manufacturer's instruction. Controls were performed with nonimmune immunoglobulins of the same isotype as the primary antibodies (negative controls) and processed under identical conditions. Alcian blue staining was used to detect chondrocytes. Sections of paraffin-embedded implants were stained with Alcian blue (Sigma) solution, pH 2.5; at this pH all the glycoproteins (neutral and acidic) will be stained blue. 2.9. Alizarin Red S Staining for Mineralized Matrix Seven-day-old OS differentiated cells in 6-well plates were used for Alizarin Red S staining. The cell layer was washed with PBS and then fixed with 70% ice-cold ethanol for 1 hr at −20°C. After removing the ethanol, the cell layer was rinsed with distilled water and stained with 40 nM AR-S (Sigma) pH 4.2 for 10 minutes at room temperature. Excess dye was washed off with water followed by a wash with PBS for few minutes to minimize nonspecific AR-S stain. For quantifying the Alizarin Red S staining, the air-dried plates, the Alizarin Red S dye was eluted in 800 μL of acetic acid incubated in each well for 30 minutes at room temperature as described [11] and measured in spectrophotometer (BioTek, Epoch) at 405 nm. 2.10. Quantitative ALP Activity To quantify ALP activity in CL1 and CL2 hBMSC before and after OS differentiation, we used the BioVision ALP activity colorimetric assay kit (BioVision, Inc, CA, USA) with some modifications. Cells were cultured in 96-well plates under normal conditions; then on day of analysis, wells were rinsed once with PBS and were fixed using 3.7% formaldehyde in 90% ethanol for 30 seconds at room temperature. Subsequently, fixative was removed, and 50 μL of pNPP solution was added to each well and incubated for 1 hour in the dark at room temperature. The reaction was subsequently stopped by adding 20 μL stop solution and gently shaking the plate. OD was then measured at 405 nm. 2.11. Oil Red-O Staining for Lipid Droplets CL1 and CL2 cells differentiated to adipocytes with Adip induction media at day 7 were used. Accumulated cytoplasmic lipid droplets were visualized by staining with Oil Red-O. After washing cells grown in 6-well plates with PBS, the cells were fixed in 4% formaldehyde for 10 min at room temperature and then rinsed once with 3% isopropanol and stained for 1 hr at room temperature with filtered Oil Red-O staining solution (prepared by dissolving 0.5 g Oil Red-O powder in 60% isopropanol). To quantify staining of fat droplets, Oil Red-O was used as a stain. Oil Red-O was eluted by adding 100% isopropanol to each well, and color changes were measured by spectrophotometer at 510 nm (BioTek Spectrophotometer, Epoch). 2.12. Nile Red Fluorescence Determination and Quantification of Adipogenesis A stock solution of Nile red (1 mg/mL) in DMSO was prepared and stored at −20°C protected from light. Staining was performed on unfixed cells. Cultured undifferentiated and day 7 adipocyte differentiated cells were grown in Corning polystyrene; flat bottom 96-well TC-treated black microplates (Corning, NY, USA) were washed once with PBS. The dye was then added directly to the cells (5 μg/mL in PBS), and the preparation was incubated for 10 min at room temperature and then washed twice with PBS. Fluorescent signal was measured using SpectraMax/M5 fluorescence spectrophotometer plate reader (Molecular Devices Co, Sunnyvale, CA, USA) using bottom well-scan mode where nine readings were taken per well using Ex (485 nm) and Em (572 nm) spectra. 2.13. Quantitative Real-Time PCR (qRT-PCR) Analysis Total RNA was extracted using MagNA pure compact RNA isolation kit (Roche Applied Science, Germany, Cat number 04802993001) in an automated MagNA pure compact system (Roche, Germany) as recommended by the manufacturer. The total RNA was quantified by Nanodrop spectrophotometer (Nanodrop 2000, Thermo Scientific, USA). Complementary DNA (cDNA) was synthesized from 1 μg of the RNA samples using High Capacity cDNA Reverse Transcription kit (Applied Biosystems, USA) using Labnet, Multigene thermocycler according to the manufacturer's instructions. Relative levels of mRNA were determined from cDNA by real-time PCR (Applied Biosystems-Real-Time PCR Detection System) with Power SYBR Green PCR kit (Applied Biosystems, UK) according to the manufacturer's instructions. Following normalization to the reference gene GAPDH, quantification of gene expression was carried out using a comparative Ct method, where ΔCt is the difference between the CT values of the target and the reference gene, and fold induction was performed from the control (Cont) for the same time point. Primers (Supplementary Table  1 in Supplementary Material available online at http://dx.doi.org/10.1155/2016/9378081) were obtained from Applied Biosystems (USA) as TAQMAN primers, or previously published primers were used (see Supplementary Table  1). 2.14. DNA Microarray Global Gene Expression Analysis Four hundred ng of total RNA was used as input for generating biotin-labeled cRNA (Ambion, Austin, TX, United States). cRNA samples were then hybridized onto Illumina® human-8 BeadChips version 3. Hybridization, washing, Cy3-streptavidin staining, and scanning were performed on the Illumina BeadStation 500 platform (Illumina, San Diego, CA, USA), according to the manufacturer's instructions, and everything was done in triplicate. Expression data analysis was carried out using the Partek® genomic suite software. Raw data were background-subtracted, normalized using the “rank invariant” algorithm, and filtered for significant expression on the basis of negative control beads. Genes were considered significantly expressed with detection p values ≤ 0.01. Differential expression analysis was performed with the Illumina custom method using freshly isolated primary hBMSC (used at passage 3) as a reference control. The following parameters were set to identify statistical significance: differential p values ≤ 0.01; fold change ratio > 1.5. Pathway analysis was performed using DAVID Bioinformatics Resources 6.7 (http://david.abcc.ncifcrf.gov/) and GeneSpring GX software (Agilent Technologies). Pathway analysis for CL1 OS D14 versus CL2 OS D14 was conducted using the Single Experiment Pathway analysis feature in GeneSpring 12.0 (Agilent Technologies). 2.15. Small Interfering (si)RNA Transfection For transfection, hBMSC in logarithmic growth phase were transfected with Silencer Select Predesigned ALP siRNA (25 nM) (Assay ID; s1298 and Cat number 4390824) (Ambion, The RNA Company, USA) using Lipofectamine RNAiMAX Reagent (Invitrogen, CA, USA) plus serum-free Opti-MEM®I medium under the conditions described by the manufacturer. At day 3 of transfection, the cells were induced for osteogenic differentiation for an additional 7 days. ALP staining was used as a control for the siRNA transfection efficiency and timeline. 2.16. Statistical Analysis All of the results were presented as the mean and standard deviation (SD) of at least 3 independent experiments, with 3–5 technical repeats in each experiment. Student's t-test (two-tailed) was used for testing differences between groups. p value <0.05 was considered statistically significant. 3. Results 3.1. Comparison between CL1 and CL2: Differences in Morphology, Proliferation, and Marker Expression Profile We isolated two distinct clonal cell populations of hBMSC-TERT: hBMSC-CL1 and hBMSC-CL2 (for easiness will be termed hereafter CL1 and CL2) based on differences in cell morphology (Figure 1(a)). CL1 cells had cuboidal morphology whereas CL2 cells have spindle-shaped fibroblast-like morphology. CL1 cells had higher proliferation rate compared to CL2 (Figure 1(b)): mean PD rates of CL1 and CL2 were 0.714 and 0.429 PD/day, respectively (Figure 1(b)). Both CL1 and CL2 expressed surface marker profiles characteristics of hBMSC (>90%): CD44+, CD63+, CD73+, CD105+, and CD166+ (Figure 1(c)). However CL1 cells showed higher expression of CD146 (92.7% versus 12%) and ALP (98% versus 0%) compared to CL2 (Figure 1(d)). TEM revealed the presence of abundant pseudopodia in CL1 indicating high motility (Figure 1(e)(A)) as well as well-developed mitochondria and rough endoplasmic reticulum (rER) suggesting high metabolic activity. CL2 cells contained abundant phagocytic vacuole (pv), microvilli (mi), and lysosomes (ly) (Figure 1(e)). We performed quantitative real-time PCR (RT-PCR) for genes expressed in mesodermal progenitor cells [12]. CL1 expressed higher levels of BMP4, MIXL1, WNT3a, and TWIST compared to CL2 (Figure 1(f), p < 0.01). In contrast, CL2 expressed higher levels of Kinase Insert Domain Receptor (Type III Receptor Tyrosine Kinase) (KDR) expressed in endothelial cells and smooth muscle myosin heavy chain gene (smMHC) expressed in smooth muscle cells (Figure 1(f)). 3.2. CL1 Cells Exhibit Enhanced Osteoblast Differentiation Following osteoblast (OB) differentiation induction, ALP staining and ALP enzymatic activity were significantly higher in CL1 compared to CL2 cells (Figure 2(a), p < 0.01). Similarly, Alizarin Red staining and quantitation of formed mineralized matrix were more pronounced in CL1 cells (Figure 2(b), p < 0.01). In addition, CL1 cells expressed higher levels of osteoblastic genes, ALP, RUNX2, and osteopontin (OPN) (Figure 2(c) upper panel) compared to CL2 cells. Global gene expression microarray analysis of OB differentiated cells at day 14 showed around 1060 genes significantly upregulated more than 2-fold (p < 0.01) in CL1. Among the upregulated genes, 80 genes were annotated to bone development and osteoblast differentiation (Table 1). The highest upregulated genes included paired-like homeodomain 2 (PITX2), Insulin-like growth factor 1 (IGF1) and collagen, type V, alpha 3 (COL5A3), osteomodulin (OMD), and T-box 15 (TBX15) (Table 1). Furthermore, several known osteoblast-related genes were upregulated in CL1 cells such as bone morphogenetic protein 6 (BMP6), fibroblast growth factor receptor 3 (FGFR3), insulin-like growth factor binding protein 5 (IGFBP5), and vitamin D (1,25-dihydroxyvitamin D3) receptor (VDR) (Table 1). On the other hand, 1200 genes were upregulated in CL2 cells: 255 genes were annotated to immunity and immune response and defense. This category included genes from, complement system, chemokine (C-C motif) ligands, interferon family, chemokine (C-X-C motif) ligands, and receptor, major histocompatibility complex class II molecules, interleukins, and tumor necrosis factor receptor superfamily (Table 2 and Supplementary Table 3). 3.3. CL1 Cells Exhibit Enhanced Adipocyte Differentiation We observed significant differences between CL1 and CL2 in their response to adipocytic differentiation induction. CL1 differentiated readily to adipocytes compared to CL2 (Figure 2(d), lower panel) evidenced by higher levels of adipocytic markers gene expression, LPL (lipoprotein lipase), and adiponectin, as well as formation of mature lipid filled adipocytes visualized by Oil Red-O staining and quantitative Nile red staining (Figure 2(d)). 3.4. CL1 Cells Differentiate to Chondrocytic Lineage In pellet cultures, CL1 cells formed 3D pellets containing proteoglycan-secreting chondrocytes, which stained positive with Alcian blue. Limited chondrocyte differentiation was visible in cell pellets of CL2 cells. The differentiated chondrocytes in CL1 pellets expressed higher levels of collagen X and collagen II, which was overlapping the Alcian blue stain (Figure 2(e)). 3.5. Molecular Signature of CL1 and CL2 Cells To define the molecular signature and molecular differences between CL1 and CL2, we compared the basal gene expression pattern of CL1 and CL2 cells using DNA microarrays. The PCA analysis showed a clear separation between CL1 and CL2 (Supplementary Figure 1). Comparison between CL1 with CL2 showed that 915 genes were differentially expressed in the two cell lines (>2-fold, p < 0.01): 462 genes were upregulated, and 452 were downregulated in CL1 versus CL2. The most relevant genes that were upregulated in CL1 are listed in Table 3(a). Among these 35 highly expressed genes in CL1, the following 11 genes were present in skeletal and muscular system development and function: FOLR3, CCL3L1, SERPINB2, POSTN, IGFBP5, CCL3, NOV, ALP, TNFRSF11B, ACTG2, and CDH11 (Table 3(a)). Functional annotation of the upregulated genes in CL1 using the Ingenuity Pathway Analysis (IPA) revealed enrichment in the following categories: “tissue development,” “skeletal and muscular system development and function,” and “organismal development” (Table 3(b)). Furthermore, the DAVID annotation tool was employed to assess the functional relationships of the upregulated genes in CL1 showing enrichment in ontologies: “skeletal and muscular system development and function” that included bone size, osteoblast differentiation, bone mineralization, and bone mineral density (Table 3(c)). CL1 exhibited upregulation of WNT pathway ligands: WNT5B (2-fold) and LRP5 (2-fold) (Table 1). Also, ALP was among the highly expressed genes together with POSTN, IGFBP5, SPP1, IL-6, and DKK1 (Tables 3(a) and 1). These genes are known to play an important role in osteoblast differentiation and bone formation. For CL2, inhibitors of WNT pathway were upregulated and included SFRP1 (11-fold), DKK2 (3.2-fold), FGF2 (3.1-fold), and GBP2 (2.4-fold). Functional annotation of the upregulated genes in CL2 revealed enrichment in the following categories: “developmental process,” “multicellular organismal process,” “biological adhesion,” and “immune system process” (Supplementary Table 2A). In-depth analysis of the biological processes revealed several immune-related pathways: “MAPKKK cascade,” “immunity and defense,” “signal transduction,” “extracellular matrix protein-mediated signaling,” and “interferon-mediated immunity,” among others that were upregulated (Supplementary Table 2B). Also, 40 genes related to immune system related factors were identified as significantly enriched in CL2 compared to CL1 cells (Supplementary Table 2C). We chose the following genes for validation of the microarray results: NOV, IGFBP5, ALP, TAGLN, and CDH11 as they were highly expressed in CL1. RT-PCR analysis confirmed the microarray results (Figure 3). Furthermore, we compared the molecular phenotype of CL1 and CL2 cells with that of phBMSC. We found that more than 80% of the genes expressed in CL1 and 90% in CL2 cells were common with primary phBMSC (Supplementary Figure 2), suggesting that CL1 and CL2 molecular phenotype exist within the heterogeneous population of phBMSC cultures. 3.6. ALP Knockdown Impairs Differentiation of CL1 Cells Since ALP has been suggested as a marker for hBMSC progenitor cell lineage commitment [13] and was highly upregulated in CL1 cells, we tested its biological role in CL1 cells. ALP siRNA transfection decreased ALP protein level, ALP activity, and mRNA gene expression compared to control cells transfected with control siRNA (p < 0.01) and this inhibition was detectable up to day 7 days after osteoblast differentiation induction (Figures 4(A) and 4(B)). At day 14 of differentiation, mineralization ability of CL1 was significantly impaired (Figure 4(C)). In addition, we found that the number of mature adipocyte formations was significantly reduced to more than 75% (p < 0.01) (Figure 4(D)). To identify relevant adipocyte differentiation associated genes that were targeted by ALP deficiency, we compared the downregulated genes of ALP deficient CL1 with the upregulated genes identified during adipocytic differentiation of CL1. We identified 62 genes that were common (Figure 5(a), Table 4) and among these genes were genes related to metabolism (primarily lipid and carbohydrate) and transport including CYB5B, CHST1, TAP1, ATP8A1, LRP8, PLCD1, and FABP5 (Table 4). We further performed quantitative real-time PCR of ALP deficient CL1 cells during adipocyte differentiation. The following adipocyte-associated genes were downregulated: PPARγ2, LPL, and aP2 (Figure 5(b)), confirming impairment of adipocytic differentiation of ALP deficient CL1 cells. 4. Discussion We extensively studied two cell populations within cultured hBMSC that were identified based on differences in morphology. Cellular and molecular studies revealed differences in growth, differentiation capacity, and molecular signature. Our data support the notion of the presence of cellular and functional heterogeneity among cultured hBMSC. Cellular heterogeneity of cultured hBMSC is recognized in an increasing number of reports. Several extrinsic and intrinsic factors may contribute to the observed hBMSC heterogeneity. Extrinsic factors include donor-to-donor variations in the number and quantity of initiating cells, which result in differences in cell growth rate and differentiation capacity [14, 15]. Intrinsic factors have been examined employing single cell clonal analysis and revealed variations in differentiation potential among individual colonies within hBMSC cultures ranging from the presence of cells with trilineage (osteoblast, adipocytes, and chondrocyte) potency to cells with null potency [16]. Also, variations in the ability of clonal cells to form heterotopic bone when implanted in vivo have been reported [5]. Our study corroborates these findings and provides more detailed cellular and molecular phenotyping of two examples of cell populations that exist within the heterogeneous hBMSC cultures [17]. Determining the molecular signature of CL1 and CL2 using whole genome microarray analysis showed enrichment of lineage-commitment associated genes in CL1. For example, insulin-like growth factor 5 (IGFBP5) and interleukin 6 (IL6) were 14.7- and 3.3-fold upregulated in CL1 cells, respectively. Both factors are expressed in osteoprogenitor cells and important for osteoblast maturation [18]. We also observed that periostin (POSTN) gene was highly upregulated in CL1 cells (15.6-fold); POSTN is a 90 kDa secreted protein, originally identified in murine osteoblast-like cells and is upregulated by PTH [19]. Several studies employing murine and human cells have revealed important role of POSTN in osteoblast differentiation and during development in intramembranous ossification [20–23]. Another factor identified in CL1 cells is nephroblastoma overexpression (NOV) which is a member of the Cyr 61, connective tissue growth factor (CNN) family. The CCN family of proteins promotes osteoblast differentiation through interaction with integrins, WNT, BMP, and NOTCH signaling pathways [24–26]. In addition, a large number of signaling molecules known to be regulators of hBMSC lineage specific differentiation, for example, insulin-like growth factors [27–29], WNT [30–32], and MAPK [33–35], were enriched in CL1 cells. In contrast, CL2 expressed high levels of immune-related genes which may explain the poor differentiation response to osteoblast or adipocyte lineage. In a recent study the authors used telomerized hBMSC and showed clearly a clonal population that had very low in vitro and in vivo differentiation ability; however they had enhanced immune-related features including high IL7 expression. These nullipotent cells expressed CD317 which was associated with remarkably high basal level expression of factors with a proinflammatory and antiviral function [17]. We observed that this molecular phenotype was associated with distinct ultrastructural characteristics of the cells. In particular, CL2 had abundant phagocytic vacuole, microvilli, and lysosomes, features reminiscent of ultrastructure of immune-regulatory cells. Our data thus support the increasingly recognized feature that hBMSC exhibit immune modulatory functions and a part of the innate immune response [17]. We observed that ALP protein expression and enzymatic activity were significantly different between CL1 and CL2 cell lines and were thus a potential marker that distinguishes different cell populations with progenitor functions (CL1) from cells with nonprogenitor functions (CL2). ALP is expressed in a wide variety of tissues, including kidneys, bone, and liver [36, 37], but tissue-nonspecific ALP (ALPL) is considered a commitment marker for osteoblastic lineage [13, 38]. However, in a recent study the authors examined the differentiation potential of a number of hMSC clones in vitro and in vivo and reported that the hMSC clones with high levels of ALP expression were committed to trilineage differentiation [13]. Our data corroborate and extend these findings by reporting the effects of siRNA-mediated inhibition of ALP that resulted in an impaired hBMSC differentiation not only to osteoblasts, but also to adipocytes. Also, our results corroborate earlier studies that demonstrated in human bone biopsies the presence of ALP expression in bone marrow adipocytic cells [13, 17]. All these data suggest that ALP is a “stemness” marker of hBMSC and not just an indicator of osteoblastic lineage commitment. While CL1 and CL2 were isolated from telomerized hMSC cell line, they are relevant to normal human physiology. We observed that the molecular phenotypes of CL1 and CL2 were contained within the molecular signature of primary hBMSC suggesting that CL1 and CL2 represent cell populations within the heterogeneous cultures of hBMSC. We have also previously reported that the molecular phenotype and cellular responses of hMSC-TERT are similar to those of primary hMSC [10]. While we have identified ALP as a marker that can be used for a prospective identification of differentiation committed population of hBMSC, we identified additional distinctive molecular markers of the cells. For example, IGF-1, IGF-2, and IGF binding protein 5 were enriched in CL1 compared to CL2. IGFs and their binding proteins are very well-studied factors that play a role in hBMSC proliferation and osteoblast differentiation [18]. On the other hand, annexin A3 as well as several immune-related genes was highly enriched in CL2 compared to CL1. Future studies are needed to determine the functional significance of these molecules in relation to the functional identity of various cell populations within the hBMSC cultures and their usefulness as biomarkers to dissect the heterogeneous population of cultured hBMSC. Our finding of the presence of functional diversity within hBMSC cultures that contain progenitor and nonprogenitor cell populations has a clinical relevance. It demonstrates that the progenitor function and the immune modulatory roles of hBMSC [39] are mediated by specific and distinguishable populations of hBMSC. Thus, future clinical studies employing hBMSC should attempt to administer the relevant subpopulation of hBMSC dependent on the experimental aim, as a novel approach to improving the clinical efficiency, instead of the current use of heterogeneous hBMSC populations. Supplementary Material List of primers used for real time qPCR. Acknowledgments These studies are supported by a grant from the College of Medicine Research Centre (CMRC), Deanship of Scientific Research, King Saud University, Riyadh, Saudi Arabia. The authors would like to thank Mr. Ali Al-Roalle for all his technical help. They thank Natalie Twine for advice on DNA microarray analysis. Competing Interests The authors declare that they have no competing interests. Authors' Contributions Mona Elsafadi and Amer Mahmood contributed equally to this work. Figure 1 Cellular phenotype of two clonal populations of human bone marrow stromal stem cells: CL1 and CL2. (a) Cell morphology. CL1 cells showed large cuboidal morphology while CL2 cells had spindle-shaped fibroblast-like morphology. (b) Growth curves showing population doubling (PD) rate during long term culture. (c) Flow cytometry analysis (FACS) shows expression of CD44, CD63, CD73, CD105, and CD166 in CL1 and CL2 cells. Matched isotype control was used for gating. (d) Flow cytometry analysis presented as dot blot of CD146 and alkaline phosphatase (ALP) cell surface proteins. (e) Transmission electron microscope (TEM). (A): CL1 (1200x); (B): CL2 (1500x). n: nucleus, nu: nucleolus, rER: rough endoplasmic reticulum, ly: lysosomes, pv: phagocytic vacuole, and rer: reticular stalk of rER. (f) Gene expression analysis using RT-PCR for a group of mesodermal and stromal genes. Gene expression was normalized to GAPDH and presented as fold change. Data is shown as mean ± SD of three independent experiments. ∗ p < 0.05; # p < 0.001. Figure 2 In vitro osteoblastic and adipocytic differentiation of two clonal populations of human bone marrow stromal stem cells: CL1 and CL2 cells. Both cell lines were induced for osteoblast differentiation using standard protocol described in the Methods. (a) ALP staining at day 14 in control noninduced (Cont) and osteoblast induced cells (D14). Right panel shows ALP activity (n = 3 independent experiments, # p < 0.001). (b) Mineralized matrix formation visualized by Alizarin Red S staining. Right panel shows Alizarin Red quantification at day 14 and 21 after osteoblast differentiation (n = 3 independent experiments, # p < 0.001). (c) Quantitative RT-PCR of osteoblastic and adipocyte gene markers in CL1 and CL2 during osteoblast (upper panel) and adipocyte (lower panel) differentiation. ALP = alkaline phosphatase, OPN = osteopontin, LPL = lipoprotein lipase, and ADIPOQ = adiponectin. Data are presented as fold change in expression of each target gene normalized to GAPDH (n = 3 independent experiments, p < 0.05;  # p < 0.001). (d) CL1 and CL2 lines were induced for adipocyte differentiation using standard protocol described in the Methods. Adipocyte formation was visualized at day 7 (Adip d7) and day 14 (Adip d14) by Oil Red-O staining. Lower panel presents quantification of Nile red staining (n = 3 independent experiments, # p < 0.001). (e) CL1 and CL2 lines were induced for chondrocyte differentiation using 21-day pellet culture method as described in the Methods. The pellets were stained with Alcian blue, collagen 10 (Col X), and collagen 2 (Col II) (original magnification 5x). Figure 3 Validation of whole genome microarray analysis of two clonal populations of human bone marrow stromal stem cells: CL1 and CL2 cells. Quantitative real-time PCR for highly expressed genes in CL1 cells. NOV = nephroblastoma overexpressed, IGFBP5 = insulin-like growth factor binding protein 5, ALP, TAGLN = transgelin, and CDH11 = OB-cadherin (osteoblast). Data are presented as fold change in expression of each target gene normalized to GAPDH (n = three independent experiments, # p < 0.001) (see also Table 3). Figure 4 Effect of alkaline phosphatase (ALP) gene silencing by small interfering RNA (siRNA) on a clonal population of human bone marrow stromal stem cell CL1. (A) ALP staining at day 3, day 5, or day 7 days of osteoblast differentiation (OB induction). (B) Quantitative real-time PCR for ALP gene following ALP siRNA transfection at day 0 OB and day 7 of OB. Data are presented as fold change in expression of each target gene normalized to GAPDH (n = three independent experiments, # p < 0.01). Western blotting analysis of day 3 and day 7 after siRNA ALP transfection of CL1 cells, ALPL specific antibody, and B-actin was used. (C) Mineralized matrix formation as visualized by Alizarin Red S staining in siRNA transfected CL1 cells after 14 days of OB induction. (D) Nile red quantification of mature lipid filled adipocyte in control noninduced (Cont), adipocyte induced (Adip I), and ALP siRNA transfected cells that are adipocyte induced (ALP siRNA). Adipocyte induction was carried out for 7 days. ∗ p < 0.05. Figure 5 Adipocyte related genes downregulated in ALP knockdown CL1 cells. (a) Venn diagram of whole gene expression analysis of AD upregulated genes compared with ALP KD downregulated genes. (b) Quantitative real-time PCR of four selected common genes from Venn diagram including ALPL, PPARg2, aP2, and LPL. Data are presented as fold change in expression of each target gene normalized to GAPDH (n = three independent experiments, ∗ p < 0.05, ∗∗ p < 0.01, and ∗∗∗ p < 0.001). Table 1 Microarray data analysis showing genes related to bone development and osteoblast differentiation upregulated in CL1 versus CL2 cells. Probe ID Genbank accession Gene name Gene symbol FC A_23_P167367 NM_153426 Paired-like homeodomain 2 PITX2 308.84 A_23_P13907 NM_000618 Insulin-like growth factor 1 (somatomedin C) IGF1 118.00 A_23_P55749 NM_015719 Collagen, type V, alpha 3 COL5A3 75.11 A_23_P94397 NM_005014 Osteomodulin OMD 56.07 A_24_P128442 NM_152380 T-box 15 TBX15 54.38 A_33_P3708413 NM_003480 Microfibrillar associated protein 5 MFAP5 53.73 A_24_P72064 NM_000163 Growth hormone receptor GHR 51.47 A_23_P215454 NM_001278939 Elastin ELN 50.15 A_24_P200854 NM_006735 Homeobox A2 HOXA2 44.99 A_23_P19624 NM_001718 Bone morphogenetic protein 6 BMP6 41.43 A_23_P500501 NM_000142 Fibroblast growth factor receptor 3 FGFR3 33.95 A_23_P154605 NM_018837 Sulfatase 2 SULF2 29.57 A_23_P28815 NM_000782 Cytochrome P450, family 24, subfamily A, polypeptide 1 CYP24A1 22.47 A_23_P210109 NM_019885 Cytochrome P450, family 26, subfamily B, polypeptide 1 CYP26B1 22.42 A_23_P323180 NM_006898 Homeobox D3 HOXD3 21.08 A_32_P405759 NM_152888 Collagen, type XXII, alpha 1 COL22A1 20.36 A_33_P3363799 NM_001242607 Neural cell adhesion molecule 1 NCAM1 17.33 A_33_P3381378 NM_001257096 Paired box 1 PAX1 17.12 A_23_P383009 NM_000599 Insulin-like growth factor binding protein 5 IGFBP5 14.67 A_33_P3382856 NM_133507 Decorin DCN 14.38 A_23_P10206 NM_005328 Hyaluronan synthase 2 HAS2 14.33 A_24_P77904 NM_018951 Homeobox A10 HOXA10 13.64 A_23_P2814 NM_005905 SMAD family member 9 SMAD9 12.45 A_23_P88404 NM_003239 Transforming growth factor, beta 3 TGFB3 12.11 A_32_P4595 NM_000337 Sarcoglycan, delta (35 kDa dystrophin-associated glycoprotein) SGCD 8.95 A_23_P162171 NM_006500 Melanoma cell adhesion molecule MCAM 8.60 A_24_P38276 NM_003505 Frizzled class receptor 1 FZD1 7.81 A_23_P24129 NM_012242 Dickkopf WNT signaling pathway inhibitor 1 DKK1 7.04 A_33_P3264528 NM_005523 Homeobox A11 HOXA11 6.64 A_33_P3220470 NM_005585 SMAD family member 6 SMAD6 6.47 A_23_P23783 NM_000261 Myocilin, trabecular meshwork inducible glucocorticoid response MYOC 6.41 A_33_P3263432 NM_003637 Integrin, alpha 10 ITGA10 6.35 A_23_P383009 NM_000599 Insulin-like growth factor binding protein 5 IGFBP5 6.18 A_33_P3219090 NM_005542 Insulin induced gene 1 INSIG1 5.78 A_23_P162589 NM_001017535 Vitamin D (1,25-dihydroxyvitamin D3) receptor VDR 5.68 A_23_P374695 NM_000459 TEK tyrosine kinase, endothelial TEK 5.65 A_24_P261169 NM_006378 Sema domain, immunoglobulin domain (Ig), transmembrane domain (TM), and short cytoplasmic domain, (semaphorin) 4D SEMA4D 5.41 A_33_P3297930 NM_005202 Collagen, type VIII, alpha 2 COL8A2 5.138 A_23_P206359 NM_004360 Cadherin 1, type 1, E-cadherin (epithelial) CDH1 5.12 A_24_P264943 NM_000095 Cartilage oligomeric matrix protein COMP 5.07 A_33_P3214948 NM_014767 Sparc/osteonectin, cwcv, and kazal-like domains proteoglycan (testican) 2 SPOCK2 4.54 A_24_P55496 NM_053001 Odd-skipped related transcription factor 2 OSR2 4.38 A_24_P354689 NM_004598 Sparc/osteonectin, cwcv, and kazal-like domains proteoglycan (testican) 1 SPOCK1 4.23 A_23_P69030 NM_001850 Collagen, type VIII, alpha 1 COL8A1 3.93 A_23_P128084 NM_002206 Integrin, alpha 7 ITGA7 3.91 A_24_P3249 NM_000965 Retinoic acid receptor, beta RARB 3.91 A_24_P168574 AJ224867 GNAS complex locus GNAS 3.83 A_23_P320739 NM_002397 Myocyte enhancer factor 2C MEF2C 3.74 A_23_P429383 NM_014213 Homeobox D9 HOXD9 3.54 A_23_P42322 NM_080680 Collagen, type XI, alpha 2 COL11A2 3.42 A_23_P160318 NM_001856 Collagen, type XVI, alpha 1 COL16A1 3.36 A_33_P3407013 NM_000600 Interleukin 6 IL6 3.30 A_23_P315364 NM_002089 Chemokine (C-X-C motif) ligand 2 CXCL2 3.29 A_33_P3413168 BC007696 Collagen, type XXVII, alpha 1 COL27A1 3.08 A_23_P43164 NM_015170 Sulfatase 1 SULF1 3.05 A_23_P58676 NM_001204375 Natriuretic peptide receptor 3 NPR3 3.04 A_33_P3290562 NM_000168 GLI family zinc finger 3 GLI3 3.00 A_23_P69497 NM_003278 C-type lectin domain family 3, member B CLEC3B 2.99 A_24_P353619 NM_000478 Alkaline phosphatase, liver/bone/kidney ALPL 2.99 A_33_P3305749 NM_000965 Retinoic acid receptor, beta RARB 2.89 A_23_P307328 NM_007331 Wolf-Hirschhorn syndrome candidate 1 WHSC1 2.77 A_23_P152305 NM_001797 Cadherin 11, type 2, OB-cadherin (osteoblast) CDH11 2.77 A_23_P216361 NM_021110 Collagen, type XIV, alpha 1 COL14A1 2.62 A_23_P7313 NM_001040058 Secreted phosphoprotein 1 SPP1 2.60 A_24_P267592 NM_015474 SAM domain and HD domain 1 SAMHD1 2.54 A_23_P210482 NM_000022 Adenosine deaminase ADA 2.52 A_23_P148047 NM_000958 Prostaglandin E receptor 4 (subtype EP4) PTGER4 2.51 A_23_P345725 NM_014621 Homeobox D4 HOXD4 2.47 A_24_P125283 NM_001015053 Histone deacetylase 5 HDAC5 2.37 A_33_P3231953 NM_004370 Collagen, type XII, alpha 1 COL12A1 2.34 A_24_P298027 NM_004655 Axin 2 AXIN2 2.31 A_24_P336551 NM_199173 Bone gamma-carboxyglutamate (gla) protein BGLAP 2.29 A_33_P3313825 XM_006713316 Transforming growth factor, beta receptor II (70/80 kDa) TGFBR2 2.23 A_23_P82990 NM_033014 Osteoglycin OGN 2.20 A_32_P24585 NM_001017995 SH3 and PX domains 2B SH3PXD2B 2.20 A_24_P944458 NM_016133 Insulin induced gene 2 INSIG2 2.14 A_23_P99063 NM_002345 Lumican LUM 2.12 A_32_P5251 NM_001024809 Retinoic acid receptor, alpha RARA 2.11 A_24_P935491 NM_000090 Collagen, type III, alpha 1 COL3A1 2.10 A_33_P3312104 NM_025099 CTS telomere maintenance complex component 1 CTC1 2.06 A_33_P3321342 NM_016133 Insulin induced gene 2 INSIG2 2.04 A_23_P100486 NM_206824 Vitamin K epoxide reductase complex, subunit 1 VKORC1 2.02 A_23_P53588 NM_030775 Wingless-type MMTV integration site family, member 5B WNT5B 2.00 A_23_P616356 NM_001291902 Low density lipoprotein receptor-related protein 5 LRP5 2.00 Table 2 Microarray data analysis showing genes related immune modulation and immune defense genes upregulated in CL2 versus CL1 cells. ID Gene name Gene symbol Fold change A_23_P128094 ATP-binding cassette, subfamily B (MDR/TAP), member 9 ABCB9 2.1 A_32_P156963 Actin, gamma 1 ACTG1 3.0 A_23_P28279 ARP1 actin related protein 1 homolog B, centractin beta (yeast) ACTR1B 2.0 A_23_P211207 Adenosine deaminase, RNA-specific, B1 ADARB1 3.5 A_23_P381261 Adenylate cyclase 4 ADCY4 5.0 A_23_P169993 Adenylate cyclase 8 (brain) ADCY8 3.2 A_23_P76823 Adenylosuccinate synthase-like 1 ADSSL1 7.0 A_23_P135486 Alpha hemoglobin stabilizing protein AHSP 2.6 A_23_P216023 Angiopoietin 1 ANGPT1 7.6 A_23_P94501 Annexin A1 ANXA1 2.6 A_23_P121716 Annexin A3 ANXA3 346.8 A_23_P6398 Adaptor-related protein complex 1, beta 1 subunit AP1B1 2.2 A_23_P120931 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3C APOBEC3C 2.2 A_23_P132316 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3D APOBEC3D 2.4 A_23_P357101 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3F APOBEC3F 2.3 A_23_P143713 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3G APOBEC3G 9.6 A_23_P93988 Rho guanine nucleotide exchange factor (GEF) 5 ARHGEF5 8.7 A_24_P20383 Actin related protein 2/3 complex, subunit 4, 20 kDa ARPC4 2.2 A_23_P208389 AXL receptor tyrosine kinase AXL 2.0 A_33_P3279353 Azurocidin 1 AZU1 4.8 A_33_P3262043 BCL2-associated agonist of cell death BAD 2.3 A_24_P159648 BAI1-associated protein 2 BAIAP2 2.2 A_23_P370682 Basic leucine zipper transcription factor, ATF-like 2 BATF2 22.2 A_23_P160720 Basic leucine zipper transcription factor, ATF-like 3 BATF3 3.0 A_33_P3229272 Breast cancer antiestrogen resistance 1 BCAR1 3.3 A_23_P210886 BCL2-like 1 BCL2L1 3.4 A_23_P98350 Baculoviral IAP repeat containing 3 BIRC3 25.0 A_23_P31725 B lymphoid tyrosine kinase BLK 7.3 A_33_P3419785 BCL2/adenovirus E1B 19 kDa interacting protein 3 BNIP3 7.3 A_19_P00802936 BRICK1, SCAR/WAVE actin-nucleating complex subunit BRK1 2.2 A_23_P2431 Complement component 3a receptor 1 C3AR1 2.6 A_23_P97541 Complement component 4 binding protein, alpha C4BPA 2.6 A_23_P92928 Complement component 6 C6 4.0 A_23_P213857 Complement component 7 C7 2.2 A_33_P3745146 Cell adhesion molecule 1 CADM1 34.3 A_23_P250347 Calcium/calmodulin-dependent protein kinase IV CAMK4 3.4 A_23_P253791 Cathelicidin antimicrobial peptide CAMP 3.3 A_23_P82324 Caspase recruitment domain family, member 11 CARD11 7.9 A_23_P500433 Caspase recruitment domain family, member 9 CARD9 2.4 A_23_P202978 Caspase 1, apoptosis-related cysteine peptidase CASP1 2.4 A_23_P123853 Chemokine (C-C motif) ligand 19 CCL19 2.0 A_23_P17065 Chemokine (C-C motif) ligand 20 CCL20 14.6 A_23_P215484 Chemokine (C-C motif) ligand 26 CCL26 2.8 A_23_P503072 Chemokine (C-C motif) ligand 28 CCL28 4.3 A_33_P3316273 Chemokine (C-C motif) ligand 3 CCL3 2.3 A_23_P152838 Chemokine (C-C motif) ligand 5 CCL5 2.7 A_23_P78037 Chemokine (C-C motif) ligand 7 CCL7 16.0 A_23_P207456 Chemokine (C-C motif) ligand 8 CCL8 2.8 A_23_P361773 Cyclin D3 CCND3 2.3 A_33_P3284508 CD14 molecule CD14 4.2 A_23_P259863 CD177 molecule CD177 2.7 A_33_P3381513 CD274 molecule CD274 10.8 A_23_P15369 CD300 molecule-like family member b CD300LB 2.0 A_23_P416747 CD3e molecule, epsilon (CD3-TCR complex) CD3E 2.7 A_24_P188377 CD55 molecule, decay accelerating factor for complement (Cromer blood group) CD55 5.9 A_23_P300056 Cell division cycle 42 CDC42 4.5 A_32_P148710 Cofilin 1 (nonmuscle) CFL1 2.8 A_33_P3217584 Cholinergic receptor, nicotinic, alpha 4 (neuronal) CHRNA4 2.9 A_33_P3415300 Complexin 2 CPLX2 2.7 A_23_P133408 Colony stimulating factor 2 (granulocyte-macrophage) CSF2 16.5 A_33_P3396139 Cytotoxic T-lymphocyte-associated protein 4 CTLA4 3.0 A_33_P3287631 Cathepsin B CTSB 2.3 A_33_P3283480 Cathepsin C CTSC 8.2 A_23_P7144 Chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, alpha) CXCL1 6.5 A_33_P3712341 Chemokine (C-X-C motif) ligand 12 CXCL12 4.8 A_33_P3351249 Chemokine (C-X-C motif) ligand 16 CXCL16 11.6 A_23_P315364 Chemokine (C-X-C motif) ligand 2 CXCL2 3.3 A_24_P183150 Chemokine (C-X-C motif) ligand 3 CXCL3 2.9 A_23_P155755 Chemokine (C-X-C motif) ligand 6 CXCL6 5.0 A_33_P3214550 Chemokine (C-X-C motif) receptor 2 CXCR2 2.0 A_33_P3389230 Chemokine (C-X-C motif) receptor 3 CXCR3 2.3 Table 3 Whole genome microarray analysis of two clonal populations of human bone marrow stromal stem cells: CL1 and CL2 cells. (a) Top 35 highly upregulated genes in CL1 cells versus CL2 cells. (b) Ingenuity® Pathway Analysis (IPA®) showing the different physiological system development and function genes found in each category and the corresponding p value. (c) Upper part IPA analysis showing the categories for skeletal and muscular system development and function upregulated in CL1 cells and lower part showing genes upregulated in CL2 cells. NOV = nephroblastoma overexpressed, IGFBP5 = insulin-like growth factor binding protein 5, ALP, TAGLN = transgelin, and CDH11 = OB-cadherin (osteoblast). (a) Gene ID Fold change CL1 versus CL2 FOLR3 28.4721 CCL3L3 17.936 POSTN 15.5924 SERPINB2 −17.2599 IGFBP5 14.6708 CCL3 13.1203 NOV 11.2921 ACTG2 10.4493 CRYAB 10.0678 PSG4 9.68913 RAB3IL1 9.16897 SCIN 9.13702 MYL9 9.12814 TNFRSF11B 8.86049 TAGLN 8.75581 CDH12 8.06682 SHISA2 8.0291 THBS1 7.86854 SPP1 7.64205 LCE2A 7.41042 TMEM98 7.38011 PSG7 7.12183 MYPN 7.01837 FNDC1 6.88102 TNS3 6.72083 ABI3BP 6.67822 LRP3 6.64307 MMP3 6.34715 FAM167A 6.02684 HSPB2 6.01063 ALPL 6.01022 CTSK 5.87356 CXCL12 5.68572 THY1 4.89445 CDH10 4.86105 (b) Name p value # molecules Physiological system development and function Organismal development 7.05E − 10–1.43E − 03 181 Embryonic development 1.00E − 09–1.43E − 03 154 Organ development 1.00E − 09–1.43E − 03 145 Skeletal and muscular system development and function 1.00E − 09–1.02E − 03 123 Tissue development 1.00E − 09–1.43E − 03 236 (c) Functions annotation p value # molecules  Skeletal and muscular system development and  function upregulated in CL1 cells Size of bone 1.43E − 06 24 Differentiation of osteoblasts 3.84E − 06 25 Mineralization of bone 4.93E − 06 19 Bone mineral density 3.65E − 05 19  Skeletal and muscular system development and  function upregulated in CL2 cells Development of muscle 1.00E − 09 44 Proliferation of muscle cells 2.29E − 06 35 Remodeling of bone 3.63E − 06 21 Resorption of bone 3.94E − 06 19 Table 4 Microarray data analysis showing genes found to be upregulated during adipogenic differentiation and downregulated after ALP KO. 62 common elements in “AD up” and “ALP down” Gene name FC (ALP siRNA versus control siRNA) APOBEC3G Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3G −15.938025 IFI44L Interferon-induced protein 44-like −11.520283 PAQR5 Progestin and adipoQ receptor family member V −6.868241 PNMA2 Paraneoplastic antigen MA2 −5.9695344 DUSP23 Dual specificity phosphatase 23 −5.4786854 CLDN23 Claudin 23 −5.1885047 ANKDD1A Ankyrin repeat and death domain containing 1A −5.1646647 IL8 Interleukin 8 −4.887188 LRRC23 Leucine rich repeat containing 23 −4.7611775 IL6 Interleukin 6 (interferon, beta 2) −4.693139 LIFR Leukemia inhibitory factor receptor alpha −4.6540866 PTGFR Prostaglandin F receptor (FP) −4.457529 FAM134B Family with sequence similarity 134, member B −4.403495 CYFIP2 Cytoplasmic FMR1 interacting protein 2 −4.260462 METTL7A Methyltransferase-like 7A −4.0480843 APOBEC3F Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3F −3.9502614 CA5B Carbonic anhydrase VB, mitochondrial −3.93889 ITGA10 Integrin, alpha 10 −3.9143775 FMO3 Flavin containing monooxygenase 3 −3.852087 IMPA2 Inositol monophosphatase 2 (human) −3.8374884 CDO1 Cysteine dioxygenase, type I −3.8181455 CCDC68 Coiled-coil domain containing 68 −3.7292893 CXCL1 Chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, alpha) −3.5942702 IDO1 Indoleamine 2,3-dioxygenase 1 −3.5803545 KCNIP3 Kv channel interacting protein 3, calsenilin −3.5442894 FADS1 Fatty acid desaturase 1 −3.2951858 LSR Lipolysis stimulated lipoprotein receptor −3.2215986 ITGA7 Integrin, alpha 7 −3.1355932 HLA-DMA Major histocompatibility complex, class II, DM alpha −3.1347752 APOBEC3B Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3B −3.1074922 BMP4 Bone morphogenetic protein 4 −3.0809238 DMBT1 Deleted in malignant brain tumors 1 −3.0760298 RDH5 Retinol dehydrogenase 5 (11-cis/9-cis) −3.066812 EPAS1 Endothelial PAS domain protein 1 −3.0615559 CDKN3 Cyclin-dependent kinase inhibitor 3 −3.052319 GPC6 Glypican 6 −3.0460389 CDK4 Cyclin-dependent kinase 4 −2.9808035 FKBP5 FK506 binding protein 5 −2.9360793 PDE1B Phosphodiesterase 1B, calmodulin-dependent −2.8863106 JAM2 Junctional adhesion molecule 2 −2.884354 TFPI Tissue factor pathway inhibitor (lipoprotein-associated coagulation inhibitor) −2.8578906 NT5M 5′,3′-Nucleotidase, mitochondrial −2.7555947 NFIA Nuclear factor I/A −2.7176137 TSPAN31 Tetraspanin 31 −2.627556 ZNF25 Zinc finger protein 25 −2.6183622 SULF2 Sulfatase 2 −2.5464642 MESP1 Mesoderm posterior 1 homolog (mouse) −2.525513 BCL2L1 BCL2-like 1 −2.5119667 PLTP Phospholipid transfer protein −2.4767148 TIMP4 TIMP metallopeptidase inhibitor 4 −2.465897 CYP27A1 Cytochrome P450, family 27, subfamily A, polypeptide 1 −2.4572072 TTC39B Tetratricopeptide repeat domain 39B −2.4439611 IL1R2 Interleukin 1 receptor, type II −2.427431 FMOD Fibromodulin −2.4185398 LDLRAD3 Low density lipoprotein receptor class A domain containing 3 −2.4032724 PISD Phosphatidylserine decarboxylase −2.3884957 TMEM100 Transmembrane protein 100 −2.384632 CHST2 Carbohydrate (N-acetylglucosamine-6-O) sulfotransferase 2 −2.3805838 APOBEC3F Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3F −2.3759322 SCD Stearoyl-CoA desaturase (delta-9-desaturase) −2.3524246 SPAG4 Sperm associated antigen 4 −2.280867 MMD Monocyte to macrophage differentiation associated human −2.2055967 ASS1 Argininosuccinate synthase 1 −2.1725202 GK5 Glycerol kinase 5 (putative) −2.1667244 PDE7B Phosphodiesterase 7B −2.166515 MT1X Metallothionein 1X −2.161843 ACACB Acetyl-CoA carboxylase beta −2.1512873 LEPR Leptin receptor −2.148686 HIF1A Hypoxia inducible factor 1, alpha subunit (basic helix-loop-helix transcription factor) −2.0954225 HEXDC Hexosaminidase (glycosyl hydrolase family 20, catalytic domain) containing −2.094836 SARM1 Sterile alpha and TIR motif containing 1 −2.0797038 BBS1 Bardet-Biedl syndrome 1 −2.0146718 SERPING1 Serpin peptidase inhibitor, clade G (C1 inhibitor), member 1 −2.0102212 FAM162A Family with sequence similarity 162, member A −2.005807 TCTN1 Tectonic family member 1 −2.0033443 ==== Refs 1 Zaher W. 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==== Front Philos Trans A Math Phys Eng SciPhilos Trans A Math Phys Eng SciRSTAroyptaPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences1364-503X1471-2962The Royal Society Publishing 2755076910.1098/rsta.2015.0212rsta201502121005127ArticlesResearch ArticleMeteorological effects of the solar eclipse of 20 March 2015: analysis of UK Met Office automatic weather station data and comparison with automatic weather station data from the Faroes and Iceland Solar eclipse meteorological effectshttp://orcid.org/0000-0002-8683-182XHanna Edward 1Penman John 2Jónsson Trausti 3Bigg Grant R. 1Björnsson Halldór 3Sjúrðarson Sølvi 4Hansen Mads A. 4Cappelen John 5Bryant Robert G. 11 Department of Geography, University of Sheffield, Sheffield S10 2TN, UK2 Met Office, Edinburgh EH11 3XQ, UK3 Icelandic Met Office, 108 Reykjavik, Iceland4 Deildin fyri infrakervi/Infrastructure Department, Landsverk, FO-110 Tórshavn, Faroes5 Danish Meteorological Institute, DK-2100 Copenhagen Ø, Denmarke-mail: ehanna@sheffield.ac.ukOne contribution of 16 to a theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. 28 9 2016 28 9 2016 374 2077 Theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’ compiled and edited by R. Giles Harrison and Edward Hanna2015021211 11 2015 © 2016 The Authors.2016Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.Here, we analyse high-frequency (1 min) surface air temperature, mean sea-level pressure (MSLP), wind speed and direction and cloud-cover data acquired during the solar eclipse of 20 March 2015 from 76 UK Met Office weather stations, and compare the results with those from 30 weather stations in the Faroe Islands and 148 stations in Iceland. There was a statistically significant mean UK temperature drop of 0.83±0.63°C, which occurred over 39 min on average, and the minimum temperature lagged the peak of the eclipse by about 10 min. For a subset of 14 (16) relatively clear (cloudy) stations, the mean temperature drop was 0.91±0.78 (0.31±0.40)°C but the mean temperature drops for relatively calm and windy stations were almost identical. Mean wind speed dropped significantly by 9% on average during the first half of the eclipse. There was no discernible effect of the eclipse on the wind-direction or MSLP time series, and therefore we can discount any localized eclipse cyclone effect over Britain during this event. Similar changes in air temperature and wind speed are observed for Iceland, where conditions were generally clearer, but here too there was no evidence of an eclipse cyclone; in the Faroes, there was a much more muted meteorological signature. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. meteorologypressuresolar eclipsetemperaturewindcover-dateSeptember 28, 2016 ==== Body 1. Introduction On 20 March 2015, a very large partial solar eclipse occurred over the British Isles, with between about 85% and 97% of the solar disc obscured by the Sun (e.g. about 87% in London, 89% in Birmingham and 94% in Edinburgh). The eclipse was total in a swath several hundred kilometres north of the UK, extending south of Greenland and Iceland, across the Faroes and through to Svalbard (figure 1), and marked the last total solar eclipse visible from anywhere across Europe until 2026 (e.g. http://www.solareclipse2015.org.uk/). This was also the largest partial eclipse seen over Britain since the 11 August 1999 solar eclipse, with the previous event being total in most of Cornwall and parts of the Channel Islands and Devon [1]. A previous study examined the meteorological signature of the 1999 eclipse based on a network of about 80 amateur and professional weather stations across Britain [1]. Here, we repeat the exercise for the recent eclipse based on a similar number of well-distributed Met Office Meteorological Monitoring System (MMS) stations reporting data of surface air temperature, wind speed and direction, mean sea-level pressure (MSLP) and cloud cover every minute. Relatively few studies of this nature have been undertaken based on a dense network of meteorological stations, due to the relative rarity of solar eclipses taking place across suitably instrumented regions during modern times. However, previous studies, usually based on one to a few recording sites rather than dense station networks, report surface air temperature dips during solar eclipses of approximately 3°C (Paraguay [2]), 1.7–2.1°C (Germany [3]), 0.3–1.5°C (Svalbard [4]), 1.2–4°C (India [5–7]), up to 2.5°C (Korea [8]), 0.7–3.9°C (Greece [9,10]), 3.0°C (Antarctica [11]) and 3°C (Florida, USA [12]). Several workers also present evidence of an eclipse-related decrease in near-surface wind speed that can be attributed to more stable conditions in a cooler boundary layer (e.g. [2–4,6,9,10]). The improvements of the present study on Hanna [1] are a self-consistent database reporting measurements at a high time frequency that was only available for a subset of the stations during the previous event, and a comparison with dense networks of modern automatic weather stations (AWSs) from Iceland (just to the other side of the totality track) and the Faroe Islands (which fell under the path of totality). Figure 1. Path of the solar eclipse of 20 March 2015, showing fractional obscuration of the Sun at maximum eclipse. Image courtesy of http://www.greatamericaneclipse.com; copyright Michael Zeiler and reproduced with permission. (Online version in colour.) The 20 March 2015 eclipse began (time of first contact) at around 0818 UTC in the Scilly Isles, 0825 in London and Birmingham, 0830 in Newcastle and Edinburgh and 0839 in the Shetland Islands; the time of maximum eclipse was 0923 at Scilly, 0931 in London and Birmingham, 0935 in Newcastle and Edinburgh and 0944 in Shetland; and the eclipse ended (fourth contact) at 1032 in Scilly, about 1040 in London and Birmingham, 1044 in Newcastle and Edinburgh and 1051 in Shetland [13] (all times in this paper are in UTC=GMT). The eclipse magnitude (fraction of the Sun’s disc occulted) at maximum eclipse ranged from 85% in Jersey to 87% in London, 88% in Scilly, 89% in Birmingham, 92% in Newcastle, 94% in Edinburgh, 96% in Wick and about 97% in Shetland and the Hebrides. The altitude of the Sun at maximum eclipse varied from approximately 22° in the Hebrides to approximately 29° in Kent. Corresponding measurements of solar radiation (affected both by astronomical/geometric considerations and by meteorological conditions, especially cloud cover) for 80 well-distributed UK sites reduced from a mean 134 W m−2 at 0900 to 27 W m−2 at 0930 (around mid-eclipse), then rose to 73 W m−2 at 1000 and 245 W m−2 at 1100. Meteorological conditions during the 20 March 2015 eclipse were largely settled, with high pressure over the British Isles (figure 2) but with decaying fronts and a maritime airflow around the northern and eastern edges of the high giving generally rather cloudy conditions (figure 3). Also of note is the tighter pressure gradient over the north of the UK, indicating breezier conditions. Multispectral satellite imagery shows the thickest/brightest cloud over southeast England and northern parts of both England and Scotland, while parts of southwest England, the Midlands and eastern Scotland were relatively clear during the eclipse (figure 3). Figure 2. Met Office mean sea-level pressure chart for (a) 0000 UTC on 20 March 2015 and (b) 0000 UTC on 21 March 2015 (redrawn). Original charts obtained from the Wetterzentrale Topkarten website (http://www.wetterzentrale.de/). Figure 3. MSG-3 SEVIRI images collected on 20 March 2015 by the University of Sheffield receiving station. Images have been contrast-enhanced and all use a Polar Stereographic projection with a latitude/longitude grid overlain: (a–d) show variability in cloud-top temperatures (via the 10.8 μm SEVIRI waveband) for Northern Europe covering the period of the eclipse (from 0930 to 1015 UTC); (e) shows a detail from (a) allowing assessment of cloud cover and temperature variability over the UK during the eclipse period (0930 UTC); (f) is a multispectral false-colour rendition of (e) using optical wavelengths (R=0.6 μm, G=0.8 μm and B=HRV) obtained at 0930 UTC. Note the darkness within the total eclipse NW of the British Isles. Because this eclipse occurred earlier in the morning and in spring rather than summer, in contrast with the 1999 event, compounded by fairly widespread cloud cover and breezy conditions in the north of the UK plus a dominant cool west to northwest airstream (figure 2), it was expected that eclipse-related temperature drops would be relatively muted for the 2015 event. With such a dense network of well-calibrated weather stations, however, it was feasible to search for evidence of the ‘eclipse cyclone’: a localized low-pressure circulation feature purported to arise from temporary cooling along the eclipse track and for which some evidence was found for the 1999 eclipse [14]. Section 2 of this study gives a detailed analysis of the Met Office weather station data for the UK, while §3 examines the meteorological response observed in the Faroe Islands (where the 2015 eclipse was total) and Iceland (where the eclipse’s magnitude ranged from 96% to more than 99%, e.g. approximately 97.5% in Reykjavik). 2. Automatic weather station (AWS) set-ups and specifications For the MMS (UK) stations (electronic supplementary material, figure S1), dry-bulb temperature is measured using a four-wire electrical resistance thermometer. These are manufactured to the specifications determined by the Met Office and tested in accordance with BS EN 60751. They conform to ‘tolerance class A’. On deployment, the resolution is 0.1°C and the acceptable difference is less than ±0.2°C when checked against a reference (Inspectors) thermometer traceable to the National Physical Laboratory (NPL). Most sites use a standard Met Office Stevenson screen with no artificial ventilation or aspiration, although this is generally a modern plastic equivalent of the old traditional wooden Stevenson screen. For measuring wind speed and direction, the MMS stations use the Vector Instruments A100 L and W200P/L models, respectively. Solar radiation data were also obtained for a different but partly overlapping network of UK sites. UK Met Office radiation measurements are made by a Kipp & Zonen CM11 or CMP11 secondary standard instrument. Electronic supplementary material, figure S2, shows the networks of Faroes AWSs run by Landsverk and the Danish Meteorological Institute (DMI). Landsverk runs a network of 26 AWSs gathering meteorological data every 10 min. Meteorological data are also available for six DMI Faroes stations, although two of these only report every 3 h and so are not considered here; the remaining four stations report either hourly (in three cases) or every 10 min (for station 6010; electronic supplementary material, figure S2). Most of the Faroes (Landsverk) AWSs are placed beside roads and either have the sloping side of a mountain on one side or are placed in a mountain pass. These AWSs use the Vaisala HMP155D thermo-/hygrometer, which is a 1/3 class B DIN platinum resistor element, with a DTR13 Radiation Shield to protect the sensors from solar radiation and rain, and there is no kind of forced ventilation. The DMI stations normally also use the Vaisala HMP155 thermo-/hygrometer, and this is coupled with another passive shield: the RM Young Multi-Plate Radiation Shield model 41003. The Icelandic Met Office (IMO) AWS stations (electronic supplementary material, figure S3) use a Logan platinum-based sensor in a Young Multi-Plate Radiation Shield. Factory specifications list wind-speed-dependent radiation errors at 1080 W m−2 as 0.4°C at 3 m s−1, 0.7°C at 2 m s−1 and 1.5°C at 1 m s−1. Although most sites are standard, a few stations monitoring conditions in/near snow-support structures on steep avalanche-prone slopes are in operation in a non-standard solar radiation environment and must be considered to be atypical (station IDs 2640, 2641, 4181, 5992). Consideration was given to these stations in this paper and a comparison made with nearby standard stations; however, a detailed analysis is beyond the scope of this paper. As is still fairly standard, none of these networks use any kind of forced ventilation on the radiation shields of their thermometers, which is a point we consider later in §5. Electronic supplementary material, figure S4, shows example AWS set-ups for the UK, Faroe Islands and Iceland. 3. Analysis of UK Meteorological Monitoring System data Owing to demands of data analysis, MMS data were chosen for a set of 76 well-distributed sites across the UK (electronic supplementary material, figure S1). Here, we focus on a detailed analysis of the MMS data between 0600 and 1200 on 20 March 2015, which encompasses the whole of the eclipse period and about 90 min before and afterwards; this allows us to distinguish eclipse-related meteorological effects from the normal diurnal heating–cooling cycle. We present summaries of surface air temperature, wind speed and direction, MSLP and cloud-cover data taken every 15 min from 0830 to 1030 (electronic supplementary material, tables S1–S5), where the first and last times approximate the start and end of the eclipse and 0930 the eclipse peak. Table 1 presents an analysis of the highest temperature achieved after 0800 but before mid-eclipse, the lowest temperature attained during the eclipse period (typically around or just after mid-eclipse), and the time taken for the temperature drop. These are the actual temperature changes and they have not been corrected for the effect of the diurnal cycle (which often means that temperatures rise strongly at this time in the morning in March), and so tend to be conservative estimates of the full effect of the eclipse in suppressing temperatures compared with what they would otherwise have been. Table 1. Highest and lowest temperatures, with their times (UTC), temperature drop and time taken, during the eclipse period on 20 March 2015. station high temp (°C), time low temp (°C), time drop (°C), time taken (min) 3/Fair Isle 7.2, 0903–0905 6.4, 0932/0934–0946 0.8, 27 9/Lerwick 6.8, 0855–0859 6.0, 0913/0914 0.8, 14 12/Baltasound 7.2, 0908–0915 6.4, 0942–0954 0.8, 27 23/Kirkwall 7.5, 0852–0900 6.8, 0941/0942 and 0953–0958 0.7, 41 32/Wick 7.1, 0912–0920 6.1, 0946–0952 1.0, 26 44/Altnaharra 7.7, 0855–0857 6.4, 0939–0958 1.3, 42 54/Stornoway 8.2, 0830–0842 7.9, 0903–0925 0.3, 21 67/Loch Glascarnoch 5.7, 0902–0903 4.8, 0949–1003 0.9, 46 113/Aviemore 8.6, 0843–0845 and 0904/0905 6.7, 1001 1.9, 56 132/Kinloss 8.1, 0900–0902 7.0, 0955–1006 1.1, 53 137/Lossiemouth 8.0, 0908–0917 7.1, 0945–1004 0.9, 28 150/Aboyne 11.4, 0837–0839 9.3, 0950–0953 2.1, 71 161/Dyce 10.4, 0914–0922 8.1, 1000–1011 2.3, 38 177/Inverbervie 8.8, 0922–0927 7.9, 0944–1002 0.9, 17 235/Leuchars 9.7, 0854–0900 8.3, 0935–0942 1.4, 35 268/Charterhall 9.1, 0907 7.4, 0941–0951 1.7, 34 315/Boulmer 10.8, 0850/0851 9.2, 0941–0948 1.6, 50 326/Durham 9.8, 0902–0903 8.8, 0945–0954 1.0, 42 346/Linton on Ouse 9.0, 0901–0902 8.2, 0932–0934 and 0947–1006 0.8, 30 360/Scarborough 7.7, 0849 5.4, 0940–0949 2.3, 51 384/Waddington 5.5, 0910 4.9, 0937–0946 0.6, 27 386/Cranwell 5.7, 0905 4.5, 0942–0945 1.2, 27 393/Coningsby 5.2, 0909–0917 4.5, 0939–0946 0.7, 22 409/Marham 4.7, 0855–0858 4.3, 0934 0.4, 36 421/Weybourne 5.5, 0914 4.9, 0935–0948 0.6, 21 426/Cromer 4.7, 0854 4.2, 0922 0.5, 28 471/Rothamsted 3.9, 0826 3.5, 0942 0.4, 76 525/Sheffield 9.1, 0839–0841 8.9, 0847–0901 0.2, 6 578/Northampton, Moulton 5.1, 0839–0849 4.2, 0940 0.9, 51 605/Brize Norton 6.0, 0859 5.4, 0929–0947 0.6, 30 613/Benson 4.5, 0900–0904 4.3, 0926–0946 0.2, 22 622/Keele 6.1, 0904–0911 5.0, 0946 1.1, 35 643/Shawbury 5.9, 0814–0847 4.4, 0941 1.5, 54 657/Pershore 5.7, 0907/0908 5.4, 0932–0943 0.3, 24 676/Filton 4.4, 0848–0915 4.2, 0931–0934 0.2, 16 697/London, St. James’s Park 5.5, 0843–0844 5.1, 0932–0939 0.4, 47 708/Heathrow 5.0, 0844–0900 4.7, 0913–0915 and 0924–0930 0.3, 24 709/Northolt 4.6, 0840–0841 and 0908–0911 4.4, 0931–0954 0.2, 20 723/Kew Gardens 5.2, 0856 4.8, 0924–0940 0.4, 28 775/Manston 5.0, 0831 4.3, 0931 0.7, 60 795/Shoreham 5.2, 0838–0839 4.6, 0925–0927 0.6, 46 811/Herstmonceux 4.9, 0839, 0844–0847 4.5, 0935–0939 0.4, 48 830/Reading 4.5, 0850–0913 4.3, 0920–0955 0.2, 7 842/Hurn 5.4, 0902 4.7, 0922–0934 0.7, 20 862/Odiham 4.0, 0911 3.8, 0921–0957 0.2, 10 876/Isle of Wight, St Catherine’s Point 5.6, 0826/0827 5.2, 0936/0937 0.4, 69 888/Larkhill 4.9, 0829 4.1, 0942–0948 0.8, 73 889/Boscombe 4.7, 0850/0851 4.3, 0909–0953 0.4, 18 1023/Eskdalemuir 7.1, 0834–0852, 0908–0911 and 0920 6.7, 0943–0949 0.4, 23 1046/Ronaldsway 9.2, 0830–0843 8.4, 0924–0933 and 0954–0956 0.8, 41 1060/Keswick 8.1, 0858–0905 and 0910/0911 7.7, 0931–0949 0.4, 20 1083/Shap 9.1, 0840–0843 7.4, 1006–1008 1.7, 83 1145/Valley 8.1, 0828–0832 7.3, 0928–0942 and 0946/0947 0.8, 56 1198/Aberporth 6.7, 0847–0850 2.9, 0950–0952 3.8, 60 1226/Pembrey Sands 5.5, 0901–0908 4.0, 0941/0942 1.5, 33 1255/Mumbles 6.6, 0832/0833 5.4, 0929–0934 1.2, 56 1302/Yeovilton 6.3, 0835–0846 6.1, 0905–0941, 0950, 0952–0954 0.2, 19 1319/Isle of Portland 5.4, 0827 4.9, 0923–0938, 0941 0.5, 56 1326/Swanage 5.1, 0803, 0859, 0930, etc. 4.8, 0908 and 4.9, 0934–0936 max 0.3, 9, etc. 1336/Plymouth, Mountbatten 5.4, 0846/0847 4.0, 0933–0934 1.4, 46 1346/Chivenor 3.6, 0908–0919 3.1, 0932–0935 0.5, 13 1386/Scilly 8.4, 0849–0855 7.8, 0925–0941 0.6, 30 1395/Camborne 6.6, 0854 6.1, 0928 and 0930 0.5, 34 1450/Aldergrove 7.9, 0855–0900 7.3, 0930–0942 0.6, 30 16588/Gravesend 5.0, 0903–0916 4.6, 0949 0.4, 33 17309/Crosby 7.8, 0849–0856 7.0, 0915–0921 and 0939–1013 0.8, 19 17314/Leeming 6.7, 0912/0913 and 0920 6.5, 0936–0939 0.2, 16 18903/South Uist Range 8.3, 0801–0806 6.9, 0956–1007 1.4, 110 18974/Tiree 8.6, 0848/0849 7.2, 0956–0958 1.4, 67 19187/Coleshill 6.4, 0903 and 0905 5.8, 0938–0949 0.6, 33 19260/Edinburgh 9.6, 0849–0853 8.7, 0940/0941 and 0944 0.9, 47 25727/Southampton 5.4, 0850/0851 and 0906 5.2, 0911–0920 0.2, 5 30620/Charlwood 4.5, 0827–0843 4.3, 0919–0950 0.2, 36 55827/Braemar 8.4, 0835–0837 7.5, 0946–0957 0.9, 71 56937/Giant’s Causeway 7.5, 0854–0911 7.3, 0923–0934 and 0945 0.2, 12 56958/Emley Moor 7.1, 0838–0858 6.0, 0938–0940 1.1, 40 All sites show a discernible decrease in temperature during the eclipse but, as expected, this varies greatly (table 1; figures 4 and 5). The mean temperature decrease for all sites, based on slightly different time periods for stations, is 0.83±0.63°C (where ± denotes 1 s.d.). The sites of greatest cooling (up to 4°C) tended to be in eastern/central Scotland, parts of northern England and Wales, which tended to coincide with clear spots on the satellite images (figure 3), which is presumably due to greater radiational cooling at these sites (i.e. a stronger decline in solar radiation and/or larger loss of terrestrial radiation under clearer skies); conversely, the least cooling (as little as 0.2°C) tended to be at sites in southeast England, which had a band of thicker cloud cover during the eclipse (figure 3). However, based on regression analysis, nearly all the temperature declines at the 76 MMS stations are statistically significant (p≤0.05), with just three exceptions: Sheffield, Filton (Bristol) and London St. James’s Park. Figure 4. Surface air temperature drops during the eclipse based on 1 min MMS data (see also table 1 and figure 5). Figure 5. Surface air temperature at 76 weather stations across the UK between 0600 and 1200 UTC on20 March 2015 (figure 4; electronic supplementary material, figure S1), with the bold (red) line marking the mean of all stations. The vertical lines C1, GE and C4 mark the times of first contact, maximum eclipse and fourth contact. (Online version in colour.) Averaging the 1 min temperature data every 15 min at all sites (bottom row in electronic supplementary material, table S1) has the effect of smoothing the original temperature series because the times of peak high and low temperature vary between sites. The mean temperature of all the sites was 6.51°C at 0900 and 6.02°C at 0945, and looking at the more detailed 1 min data the temperature peak lasted from 0855 to 0902 and the low from 0941 to 0945, giving a mean time of 39 min taken for the temperature drop. This cooling of 0.49°C is more modest than the 0.83°C reported in the previous paragraph because there has inevitably been some smoothing of the original temperature data series during the averaging process. The peak temperature occurred approximately 30±17 min after first contact, and there was a shorter lag of approximately 10±14 min of the low temperature following greatest eclipse (± denotes standard deviation of the different times of high or low temperature for individual stations noted in table 1). There is very little difference in the magnitude of the temperature decrease for subsets of relatively windy (more than or equal to 8 kn at 0930; n=23) and less windy (less than or equal to 5 kn; n=20) sites, with these subsets having almost identical temperature drops of 0.54±0.31°C and 0.55±0.75°C, respectively. There is also no relationship between wind speed at any of the 15 min time steps during the eclipse and the size of the temperature decline as defined in the previous paragraph. On the other hand, 14 sites having cloud cover of less than or equal to 5 oktas at all the 15 min time steps during the eclipse experienced a considerably greater mean temperature decline (0.91±0.78°C) than cloudy sites with consistently 8 oktas of cloud cover (0.31±0.40°C; n=16): this difference is statistically significant at the 95% confidence level using a Student’s t-test. There is also a weak but significant negative correlation between mean cloud cover during the first half of the eclipse and temperature drop (figure 6). Figure 6. Surface air temperature drop during the eclipse versus mean cloud cover for UK stations in the first half of the eclipse (0830–0930). The data series are correlated at the p≤0.01 significance level. (Online version in colour.) There is a discernible reduction of wind speed during the eclipse from 8.14 kn at 0857 to 7.38 kn at 0935, which is seen as a temporary reversal of the normal diurnal increase in wind speed at this time of the morning and/or synoptic changes (figure 7; bottom row of electronic supplementary material, table S2). However, while the decrease in wind is significant (p≤0.05) across all station data (when averaged), based on individual station data, this is only true for 22 out of 63 sites, whereas 15 sites show a significant increase during the 0900–0930 time period. Also, there is no significant relationship between the drop in temperature and the drop in wind speed. There is also evidence of cloud cover having cleared at a number of sites, including Wick, Charterhall, Coningsby, Shawbury, Camborne and Coleshill, as the eclipse progressed (electronic supplementary material, table S5), although, since the distribution of the sites shows no pattern and there is no correlation with temperature decreases, this may simply be part of a trend towards less cloud at these particular stations during the morning rather than a temporary drop driven by the eclipse. There is no discernible eclipse signature on either the wind-direction or MSLP time series, for either the mean or individual profiles (electronic supplementary material, figures S5 and S6). A map of MSLP values for peak eclipse (0930) simply reflects the general synoptic pressure gradient (figure 2) and shows absolutely no evidence of an eclipse cyclone either (electronic supplementary material, figure S7). A further analysis of MSLP changes during the first and second halves of the eclipse (not presented here in detail but based on data in electronic supplementary material, table S4) shows no systematic (total or regional) MSLP drops during the first half of the eclipse, or rises in the second half, that could be related to a possible eclipse cyclone. Figure 7. Wind speed at 63 weather stations across the UK between 0600 and 1200 UTC on 20 March 2015, withthe bold (red) line marking the mean of all stations. The vertical lines C1, GE and C4 mark the times of first contact, maximum eclipse and fourth contact. (Online version in colour.) 4. Comparison of UK eclipse signature with Faroes and Iceland meteorological data Here, we compare the results above with AWS data collected from the Faroes (where the eclipse was total, with first contact at approximately 0839, with two minutes of totality at approximately 0942 and fourth contact at approximately 1048 [13]) and Iceland (where the eclipse magnitude reached 96% to more than 99%, with times of start, end and greatest eclipse similar to the above). The locations of the two sets of stations are shown in electronic supplementary material, figures S2 and S3. (a) Faroes Electronic supplementary material, tables S6–S8, summarize the usable DMI data from four sites for 0600–1200 on 20 March 2015. The mean temperature at 23 Landsverk stations (ignoring three with significant gaps, which would bias the mean) was 5.98°C at 0838, 6.07°C at 0938 and 6.24°C at 0948, with no discernible temperature drop during the eclipse. This remains the case when these stations are subdivided into ones above and below 100 m elevation (electronic supplementary material, figure S8), although even the higher-elevation stations (280 m for F12, 278 m for F49, 273 m for F33 and 245 m for F43) are near the coast and have a strong maritime influence. Also for the Faroes, there is no discernible wind-speed signature during the eclipse (electronic supplementary material, figure S9), neither is there any sign of a barometric pressure anomaly (which might be indicative of an eclipse cyclone) around mid-eclipse (electronic supplementary material, figure S10). Wind direction (not shown) was predominantly northwesterly and remained stable with no anomalous changes during and around the eclipse period. DMI stations 6011 Torshavn and 6012 Kirkja Fugloy cloud data show 90% cover at 0800, 0900, 1000 and 1100 during and immediately before/after the eclipse, and 6010 Vaga Floghavn cloud cover was 90% before and after the eclipse but did temporarily reduce to 25% at 0940, representing a partial clearance during mid-eclipse (electronic supplementary material, tables S6–S8). Station 6010 also shows a discernible reduction in temperature during the eclipse: from 6.8°C at 0850 to 5.7°C at 1020. Temperature drops of 0.6–1°C are also apparent around the time of the eclipse in several of the Landsverk temperature records (specifically F12, F22, F23, F35 and F41; electronic supplementary material, figure S8) but are insufficiently prevalent to translate into the Landsverk mean temperature profile. The six stations with discernible temperature drops (including 6010) are clustered mainly in the northwest of the Faroes archipelago but with one exception, F22 in the eastern part of the central north (electronic supplementary material, figure S2), and they are in the part of the islands where we have noted the partial cloud clearance. There is no obvious maritime exposure, elevation or topographic bias in these stations. We do not have sufficiently high-resolution satellite data to reliably discern local cloud-cover changes over the Faroes but the surface observations indicate that the northwest happened to lie in a relatively clear spot that allowed the temperature there to fall measurably around the time of totality. (b) Iceland The main AWS dataset of the IMO comprises 10 min reports of temperature together with the maximum temperature and minimum temperature during the preceding 10 min. We use the highest maximum temperature during 0830–0950 and the lowest minimum temperature during 0940–1100 to define the magnitude of temperature decrease at individual stations during the eclipse. These data are plotted in figure 8 and show the greatest declines generally in the south and west, and the smallest temperature drops in the north and east. In addition, cloud-cover data are available for a sparser network of synoptic stations and are plotted for 0900 (during the first half of the eclipse) on 20 March (figure 9). In contrast with the UK and Faroes, these indicate that moderately clear to partly cloudy conditions prevailed over much of the country—especially in the south and west (e.g. the eclipse was well seen from Reykjavik)—but it was rather cloudy in northeast Iceland. The temperature data anecdotally suggest a strong role of cloud cover in suppressing the eclipse-related temperature decline. This potential effect is explored more by binning the temperature data according to region and longitude range and graphically presenting the results (figure 10). Regions are defined as IMO AWS numbers suffixed with 1XXX…6XXX in the electronic supplementary material, figure S3. The eclipse magnitude effect was mainly longitudinal in Iceland (figure 1). The mean regional temperature drop determined from 10 min AWS data varies from 0.24±0.33°C for stations suffixed 2XXX (northwest Iceland; electronic supplementary material, figure S3) to 0.72±0.65°C for stations suffixed 6XXX (southern Iceland). For the latter region, conditions were relatively clear. The mean temperature drop by longitude band is: 0.36±0.31°C for 13–15° W (the cloudy east), 0.50±0.68°C for 15–17° W, 0.61±0.88°C for 17–19° W, 0.55±0.49°C for 19–21° W, 0.36±0.46°C for 21–23° W and 0.47±0.55°C for 23–25° W. For the lattermost two regions (westernmost stations), skies were partially clear; yet the mean temperature drop for the 21–23° W (encompassing Reykjavik but also many other stations) is no greater than in the cloudier east—this might be attributed, at least in part, to the eclipse magnitude being approximately 2% greater in the east and/or to the southwest of the country being more exposed to maritime conditions. Incidentally, at Reykjavik (where the magnitude of the eclipse peaked at between 97% and 98%) short-wave radiation declined from around 34 W m−2 at 0850 to just 2 W m−2 at 0940 before rising steeply thereafter, reaching approximately 60 W m−2 by 1035. Figure 8. Surface air temperature reductions at Icelandic Met Office automatic weather stations during the 20 March 2015 solar eclipse. Figure 9. Cloud-cover conditions in Iceland at 0900 UTC on 20 March 2015, during the first half of the eclipse. Figure 10. Mean surface air temperature response in Iceland during the 20 March 2015 eclipse: (a) by longitude; (b) by region (see the main text for full explanation). The vertical lines C1, GE and C4 mark the times of first contact, maximum eclipse and fourth contact. There is also an apparent reduction in wind speed at Icelandic AWSs during the eclipse, as seen with the UK data, but this is superimposed on a trend of decreasing wind speed during the 6 h period centred on the eclipse. The wind reduction is large and obvious for stations where the decline in temperature exceeds 1.5°C and much less apparent for stations with more modest temperature decreases (figure 11): for example, for the 15 Icelandic stations where temperature declined by more than or equal to 2°C (less than 1°C) during the eclipse, mean wind speed fell from 4.96 (5.70) m s−1 at 0800 to 2.03 (5.35) m s−1 at 0910. Therefore, this drop in wind speed is probably related to the eclipse. Figure 11. Wind speed at Icelandic automatic weather stations between 0600 and 1200 UTC on 20 March 2015, encompassing the solar eclipse period: (a) shows means of AWSs with different ranges of tx − tn temperature drops during the eclipse; (b) shows individual AWSs where the temperature drop exceeded 2.0°C. The vertical lines C1, GE and C4 mark the times of first contact, maximum eclipse and fourth contact. Finally, electronic supplementary material, figure S11, shows the MSLP at IMO AWS for 0930 UTC (around the time of mid-eclipse) and the MSLP changes during the first and second halves of the eclipse (0840–0940 and 0940–1040). Electronic supplementary material, figure S11a, does not show a cyclonic-type circulation pattern anywhere over Iceland—in fact, it shows an anticyclonic anomaly of approximately +1 hPa in central southern Iceland—and electronic supplementary material, figure S11b, does not show any systematic decrease in MSLP during the first half of the eclipse that might be related to a possible eclipse cyclone—indeed MSLP changes were generally more positive during the first half of the eclipse (mean change 0.33 hPa) compared with the second hour (mean change 0.06 hPa): this bias is especially evident in inland southern Iceland (electronic supplementary material, figure S11b). 5. Discussion and summary Weather conditions over the British Isles during the 20 March 2015 eclipse were not optimal, due to fairly extensive cloud cover, but were also fairly stable under a ridge of high pressure and the cloud cover was patchy and broken in places. Therefore, there was a wide range of temperature drops experienced, from typically just a few tenths of a degree Celsius in southeast England to elsewhere locally in excess of 2°C. A previous comprehensive analysis of observational data acquired during the 11 August 1999 solar eclipse found mean surface air temperature drops ranging from 1.2°C in southwest England and 1.3°C in Wales and Scotland to 2.3°C in southeast England, with a few sites recording a temperature decline of 3°C or more [1]. As originally anticipated, these summertime values tend to be somewhat greater on the whole than the temperature drops experienced during the 20 March 2015 eclipse, although there is considerable overlap between the ranges of temperature drops experienced during the two eclipses. As we have seen above, where skies were clear (or relatively cloudless), temperature drops in excess of 2 or 3°C occurred at a few sites during the more recent event. Temperature lows occurred approximately 10 min after peak eclipse, which is broadly in line with previous meteorological studies (e.g. 10 to 15 min [15]; 15 min [9]; 20 min [6]). Also, we point out that temperature declines during the 20 March 2015 eclipse would probably have been considerably greater overall had skies been generally clearer or winds lighter and from a drier land area (e.g. easterly), and/or if a low inversion level allowed temperature changes to be distributed across a shallower depth. Part of the measured fall in air temperature as the eclipse advanced might have been due to the effect of the reduction in solar radiation incident upon the thermometer screens themselves rather than to a change in actual air temperature. Readings made in naturally aspirated thermometer screens can be higher than the ambient air temperature due to the warming of the screens by solar radiation, especially at low wind speeds. For example, Hanna et al. [16] examined this effect in relation to new temperature records and warming trends accompanying the July 2012 record surface melting of the Greenland Ice Sheet. As a solar eclipse progresses and radiation falls, any spurious radiational heating effect will be lessened and the indicated temperature might fall slightly as a result. On the other hand, one might expect this effect to be counteracted by a general drop in wind speed towards maximum eclipse. Wind speeds occurring during the 20 March 2015 eclipse were typically about 3 to 4 m s−1, and—as we have seen—did reduce at quite a few of the sites around mid-eclipse. None of the national meteorological networks in this study use aspirated screens (which are much less prone to being affected by solar radiation), but the temperature drop at cloud-covered sites and auxiliary data available for a few weather stations outside these networks suggest that a significant part of the observed change in temperature was due to a real fall and recovery in the air temperature. For example, the lead author maintains a Davis Vantage Pro 2 AWS with a Fan Aspirated Radiation Shield (FARS) in his northeast-facing back garden, lakeside, suburban/semi-rural (town edge) site in Newark-on-Trent, Nottinghamshire, where skies were relatively clear and the Sun was visible for the duration of the eclipse (solar radiation initially peaked at 319 W m−2 at 0835, then fell to 80 W m−2 at 0935 around mid-eclipse, afterwards rising to 512 W m−2 at 1035). This station is part of the Climatological Observers Link, and data are logged every 5 min. The small plastic radiation shield (electronic supplementary material, figure S4d) is broadly comparable with similar designs used in the Faroes and Iceland AWS networks. During a calibration exercise in 2015, the Davis thermistor was found to agree within 0.2°C with a standard UKAS-calibrated reference thermometer over a temperature range of 5–35°C (n=81). On 20 March 2015, the 2 m air temperature peaked at 6.6°C at around 0900 before dropping to 6.2°C at around 1000 (about half an hour after mid-eclipse), then rising steeply to 8.2°C by 1030 and 12.2°C by 1140. The temperature drop of 0.4°C during the eclipse is not far off the 0.6°C drop measured at the relatively nearby (approx. 20 km to the northeast) MMS site of Waddington, although it is only a third of the 1.2°C drop observed for Cranwell, which is located a similar distance to the east (table 1). However, it is greater than the manufacturer’s specified solar radiation-induced error of 0.3°C for the FARS at solar noon, which, given a steady breeze and the early morning Sun fairly low in the sky, is likely to significantly overestimate the actual error with this shield during the eclipse. It is also worth reiterating that around the time of peak eclipse under relatively clear skies and a stable airmass the temperature would normally have been rising strongly, so the eclipse-induced temperature effect is very likely to be greater than these figures suggest. Our results indicate that cloud cover is a much more important determinant than wind speed in controlling the surface air temperature response during this eclipse. Also, because there is no obvious north–south gradient in temperature decreases over the UK (figure 5), it is clear that local cloud-cover variations are far more influential than small (5–10%) variations in eclipse magnitude across the country in affecting surface cooling. This is in line with previous work, e.g. an analysis of three meteorological stations during the 2008 solar eclipse over Greece [9]. There was a significant (approx. 9%) reduction in mean UK wind speed as the eclipse progressed, which counteracted the natural tendency of wind to strengthen during this period due to diurnal/synoptic effects; this effect was previously found for the 1999 eclipse and reflects more stable boundary-layer conditions associated with the temporary cooling [1]. Cloud clearance during an eclipse is also something that has previously been observed [1], and again we present data showing that this may have happened for selected UK stations on 20 March 2015, although the evidence here is weaker and there is no clear geographical pattern. Our analysis of wind-direction and MSLP data from numerous UK and Icelandic sites discounts the possibility of the much-fabled eclipse cyclone having occurred during the recent event, although this is not to rule out such a phenomenon under more favourable meteorological conditions, perhaps, under conditions of strong solar heating in summer or during a lower-latitude eclipse over land. The Iceland AWS data show a range of temperature drops from approximately 0.1 to 3.3°C during the eclipse, which are much in line with the results for the UK. The greatest cooling occurred in southern Iceland, especially inland, although a few locations in far northern Iceland also experienced temperature drops as great as 2.9°C. At this time of the year, mean temperatures at the Iceland stations were close to 0°C (with available energy potentially being used in snow and ice melt at some sites), and this, together with the lower solar elevation, should lead to a smaller temperature signature than in the UK. The redeeming factor was the generally lower cloud cover in Iceland, especially in the south and west, which meant that the temperature response ended up being similar to that observed in the UK. The lower time resolution of the Icelandic data, compared with the UK Met Office MMS data discussed above, does not permit us to analyse the peak eclipse low temperature time lag with comparable accuracy. However, the availability of maximum and minimum temperature records between the 10 min set observation times does make the comparison of temperature decreases methodologically comparable between the two countries’ sets of AWSs. The temperature drops observed in the UK and Iceland are comparable with the results of the previous analyses referenced above (although our study uses far more stations and has a much more extensive spatial coverage than most of these). Despite the Faroes being directly in the path of the total eclipse zone, the islands’ AWS data show much more limited evidence of an eclipse-related meteorological signature, which we attribute to a combination of generally cloudy conditions there and the extreme maritime location of its weather stations, with little or no continental heating/cooling as may be the case in the UK and Iceland. Supplementary Material Supplement Tables and Figures Acknowledgements E.H. would like to thank all the data providers (UK Met Office, Icelandic Met Office, Landsverk (Faroe Islands) and the Danish Meteorological Institute), Tom Cropper for advice, David McCutcheon and Joelle Hanna for help with preparing figures, and Michael Zeiler for permission to reproduce figure 1. J.P. thanks Cameron Scrimgeour for help with MMS data/software development, and we also thank Jonathan Tamlyn at Met Office Exeter for providing technical information on the MMS station set-up. Competing interests We declare we have no competing interests. Funding No funding has been received for this article. ==== Refs References 1 Hanna E 2000 Meteorological effects of the solar eclipse of 11 August 1999 . Weather 55 , 430 –446 . (10.1002/j.1477-8696.2000.tb06481.x ) 2 Fernández W , Hidalgo H , Coronel G , Morales E 1996 Changes in meteorological variables in Coronel Oviedo, Paraguay, during the total solar eclipse of 3 November 1994 . Earth, Moon Planets 74 , 49 –59 . (10.1007/BF00118721 ) 3 Ahrens D , Iziomon MG , Jaegar L , Matzarakis A , Mayer H 2001 Impacts of the solar eclipse of 11 August 1999 on routinely recorded meteorological and air quality data in south-west Germany . Meteorol. Z. 10 , 215 –223 . (10.1127/0941-2948/2001/0010-0215 ) 4 Sjöblom A 2010 A solar eclipse seen from the High Arctic during the period of midnight sun: effects on the local meteorology . Meteorol. Atmos. Phys. 107 , 123 –136 . (10.1007/s00703-010-0070-3 ) 5 Bala Subrahamanyam D , Anurose TJ , Mohan M , Santosh M , Kiran Kumar NVP , Sijikumar S , Prijith SS , Aloysius M 2010 Atmospheric surface-layer response to the annular solar eclipse of 15 January 2010 over Thiruvananthapuram, India . Boundary-Layer Meteorol. 141 , 325 –332 . (10.1007/s10546-011-9627-z ) 6 Sharma SK et al. 2010 Effects of the solar eclipse on 15 January 2010 on the surface O3, NO, NO2, NH3, CO mixing ratio and the meteorological parameters at Thiruvanathapuram, India . Ann. Geophys. 28 , 1199 –1205 . (10.5194/angeo-28-1199-2010 ) 7 Anil Kumar CP , Gopalsingh R , Selvaraj C , Nair KU , Jeyakumar HJ , Vishnu R , Muralidas S , Balan N 2013 Atmospheric electric parameters and micrometeorological processes during the solar eclipse on 15 January 2010 . J. Geophys. Res. 118 , 5098 –5104 . (10.1002/jgrd.50437 ) 8 Chung YS , Kim HS 2010 The solar eclipse and associated atmospheric variations observed in South Korea on 22 July 2009 . Air Quality, Atmos. Health 3 , 125 –130 . (10.1007/s11869-009-0060-0 ) 9 Gerasopoulos E et al. 2008 The total solar eclipse of March 2006: overview . Atmos. Chem. Phys. 8 , 5205 –5220 . (10.5194/acp-8-5205-2008 ) 10 Tzanis C , Varotsos C , Viras L 2008 Impacts of the solar eclipse of 29 March 2006 on the surface ozone concentration, the solar ultraviolet radiation and the meteorological parameters at Athens, Greece . Atmos. Chem. Phys. 8 , 425 –430 . (10.5194/acp-8-425-2008 ) 11 Kameda T , Fujita K , Sugita O , Hirasawa N , Takahashi S 2009 Total solar eclipse over Antarctica on 23 November 2003 and its effects on the atmosphere and snow near the ice sheet surface at Dome Fuji . J. Geophys. Res. 114 , D18115 (10.1029/2009JD011886 ) 12 Anderson RC , Keefer DR , Myers OE 1972 Atmospheric pressure and temperature changes during the 7 March 1970 solar eclipse . J. Atmos. Sci. 29 , 583 –587 . (10.1175/1520-0469(1972)029%3C0583:APATCD%3E2.0.CO;2 ) 13 Espenak F , Jubier X , Zeiler M 2015 Great American eclipse. See http://www.greatamericaneclipse.com (accessed 1 June 2015) . 14 Gray SL , Harrison RG 2012 Diagnosing eclipse-induced wind changes . Proc. R. Soc. A 468 , 1839 –1850 . (10.1098/rspa.2012.0007 ) 15 Winkler P , Kaminski U , Köhler U , Riedl J , Schroers H , Anwender D 2001 Development of meteorological parameters and total ozone during the total solar eclipse of August 11, 1999 . Meteorol. Z. 10 , 193 –199 . (10.1127/0941-2948/2001/0010-0193 ) 16 Hanna E , Fettweis X , Mernild SH , Cappelen J , Ribergaard MH , Shuman CA , Steffen K , Wood L , Mote TL 2014 Atmospheric and oceanic climate forcing of the exceptional Greenland ice sheet surface melt in summer 2012 . Int. J. Climatol. 34 , 1022 –1037 . (10.1002/joc.3743 )

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==== Front Philos Trans A Math Phys Eng SciPhilos Trans A Math Phys Eng SciRSTAroyptaPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences1364-503X1471-2962The Royal Society Publishing 2755076710.1098/rsta.2015.0220rsta20150220100512127ArticlesResearch ArticleThe National Eclipse Weather Experiment: an assessment of citizen scientist weather observations The National Eclipse Weather Experimenthttp://orcid.org/0000-0001-9876-4612Barnard L. http://orcid.org/0000-0001-9897-9832Portas A. M. http://orcid.org/0000-0001-8658-362XGray S. L. http://orcid.org/0000-0003-0693-347XHarrison R. G. Department of Meteorology, University of Reading, Earley Gate, PO Box 243, Reading RG6 6BB, UKe-mail: l.a.barnard@reading.ac.ukOne contribution of 16 to a theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. 28 9 2016 28 9 2016 374 2077 Theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’ compiled and edited by R. Giles Harrison and Edward Hanna2015022010 6 2016 © 2016 The Authors.2016Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.The National Eclipse Weather Experiment (NEWEx) was a citizen science project designed to assess the effects of the 20 March 2015 partial solar eclipse on the weather over the United Kingdom (UK). NEWEx had two principal objectives: to provide a spatial network of meteorological observations across the UK to aid the investigation of eclipse-induced weather changes, and to develop a nationwide public engagement activity-based participation of citizen scientists. In total, NEWEx collected 15 606 observations of air temperature, cloudiness and wind speed and direction from 309 locations across the UK, over a 3 h window spanning the eclipse period. The headline results were processed in near real time, immediately published online, and featured in UK national press articles on the day of the eclipse. Here, we describe the technical development of NEWEx and how the observations provided by the citizen scientists were analysed. By comparing the results of the NEWEx analyses with results from other investigations of the same eclipse using different observational networks, including measurements from the University of Reading’s Atmospheric Observatory, we demonstrate that NEWEx provided a fair representation of the change in the UK meteorological conditions throughout the eclipse. Despite the simplicity of the approach adopted, robust reductions in both temperature and wind speed during the eclipse were observed. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. eclipsemeteorologycitizen scienceNatural Environmental Research Council (NERC)NE/J024678/1Science and Technology Facilities Council (STFC)ST/M000885/1cover-dateSeptember 28, 2016 ==== Body 1. Introduction On 20 March 2015, a partial solar eclipse was observed throughout the United Kingdom (UK). The magnitude of the partial eclipse varied across the UK, from approximately 85% in southern regions, up to approximately 95% in the north. Over the UK, the times of first contact, eclipse maximum and fourth contact were approximately 0830 UT, 0930 UT and 1040 UT, respectively (throughout this article all times are in UT). Atmospheric observations during prior eclipses have demonstrated that the prevailing meteorology can be perturbed by the rapid changes in insolation associated with the propagation of the eclipse penumbra through the atmosphere [1]. In fact, it is known that eclipses significantly affect each layer of the Earth’s atmosphere, from the troposphere to the ionosphere, and a large volume of research has been published on this subject, as reviewed elsewhere in this issue by Aplin et al. [2]. Focusing on eclipse-driven meteorological changes, the two most pronounced and readily understood effects are the large decrease in short-wave solar radiation, which can be almost 100%1 for total eclipses [3], and a corresponding decrease in air temperature, which can be several kelvin. However, there are also more subtle and complex features in the meteorological response. For example, studies have reported both temporary decreases in the wind speed and anticlockwise rotations in the wind direction [1,4,5]. The dynamical processes driving the observed changes in the wind field have yet to be fully understood and continue to be investigated; see paper by Gray & Harrison in this issue [6]. The infrequent and transient nature of eclipses makes it challenging to obtain sufficient observations to isolate the eclipse-induced changes from the natural evolution of the prevailing weather. Consequently, Harrison and co-workers [1,5] argued that a denser spatial network of meteorological observations could help resolve the atmospheric response and hence lead to an improved physical understanding of eclipse-induced weather changes. The National Eclipse Weather Experiment (NEWEx) was conceived as a means by which this denser network of observations could be produced, by engaging the efforts of citizen scientists across the UK during the 20 March 2015 partial solar eclipse. For NEWEx, citizen scientists would record simple observations of meteorological parameters throughout the eclipse and submit these via the Internet. These observations would be collated, analysed in the context of the eclipse and the results reported back to the citizen scientists. In doing so, NEWEx would also serve as a valuable public engagement activity, and this aspect of the project is discussed by Portas et al. elsewhere in this issue [7]. Previous studies have demonstrated the potential value of engaging citizen scientists in quantitative meteorological research, for example, the UK Citizen Rainfall Network [8] and the Royal Meteorological Societies Big Urban Heat Island project [9]. Temperature changes associated with urban heat islands are approximately several kelvin [10], which is similar to eclipse-driven temperature changes. Therefore, the fact that urban heat island temperature changes have been detected by a citizen science project [9] gives us confidence that a similar approach can be used to detect eclipse-driven temperature changes. In §2, we describe the objectives, design and development of NEWEx. Section 3 describes the data processing. In §4a, the accuracy of an example of the NEWEx temperature data is assessed by comparison to a well-established record of air temperature measurements taken at the University of Reading’s Atmospheric Observatory. Sections 4b–d present the nationwide results of the NEWEx analysis for temperature, cloudiness, and wind speed and direction. Our conclusions on the outcomes of NEWEx are summarized in §5. 2. Objectives and design (a) Objectives and design criteria NEWEx had two principal objectives: (i) To use citizen science to aid the investigation of solar eclipse effects on meteorology. More specifically, to provide a spatially dense network of regular meteorological observations across the UK and hence meet a need identified by previous research [1,5]. (ii) To develop a nationwide public engagement activity for the eclipse based on the participation of citizen scientists in NEWEx. On the basis of prior studies [1,5], it was decided that participants would be asked to report observations of the air temperature, cloud coverage, and wind speed and direction, which are important meteorological variables [11]. Consideration of these objectives led to two design criteria that NEWEx needed to fulfil. Firstly, as NEWEx would ask participants to make multiple observations of up to four parameters, it was necessary that these observations be practically achievable for those unfamiliar with weather measurements, and also that a simple and efficient means was provided to report the observations to NEWEx. Secondly, NEWEx would be more successful from a public engagement perspective if the results were communicated back to the participants quickly and clearly, immediately demonstrating the value in their contributions. Therefore, it was necessary that the NEWEx analysis could be completed quickly. It was decided to attempt to process the NEWEx data in close to real time and that, to achieve this, all of the required analysis should be prepared and automated in advance, such that during the eclipse our efforts could be focused on reporting the results. The Internet clearly provides the simplest and most efficient means for participants to report their results, although there are a large variety of ways through which such a system could be implemented. Given the resources available to NEWEx, a Google Form provided the best option for data collection, as it was free, easy to configure and could certainly handle the total volume and throughput of submissions that NEWEx could reasonably expect to receive. The design and development of the NEWEx webform are discussed in an accompanying publication in this issue [7]. The core of the NEWEx processing system was developed in the Python programming language, as it has all the necessary functionality to interface with the Google Form to access the data, perform the data analysis, and produce and upload the graphical outputs to the Internet. Prior to 20 March, this system was tested with synthetic submissions to the webform, such that we were confident that NEWEx would operate smoothly and in close to real time during the eclipse. In developing the webform, it was decided that it should be designed so that a participant could report all their observations over the eclipse period in one submission. In comparison to providing a submission for each round of observations, this would reduce the labour required by the participants and make engagement with NEWEx more achievable. After several design iterations, the parameters to be observed were discretized into classification windows, as were the observation times, such that multiple observations could be submitted via a matrix of radio buttons for each parameter (see section 2b and fig. 1 in [7]). We now briefly describe the scale and range that were used to classify each parameter. (b) Time NEWEx asked participants to collect observations between 0800 and 1100, and these were split into 21 observation windows, consisting of a higher resolution period (5 min observations) during the main phase of the eclipse (0900–1000), and two lower resolution periods (15 min observations) before and after this (0800–0900 and 1000–1100). Rather than being directed to coordinate their observations with these set times, participants were asked to select the observation window that best matched the time of their observations. The 0800–1100 window was chosen as it would provide the important observations before and after first and fourth contact, respectively, such that weather changes associated with the eclipse could be separated from the background weather. The number of times available for entries was chosen to strike a balance between the desire for high-frequency observations, which would make it easier to resolve eclipse-induced changes, and those which could practically be achieved by manual observers. The observation window was split into periods with different temporal resolutions, as it was expected that the transient features associated with the main phase of the eclipse would evolve more quickly than the background weather; for this period it would be beneficial to increase the observation frequency. (c) Temperature Temperatures were reported in 0.5°C increments from −10°C to 20°C. The range was chosen by considering the climatology for the UK, across a typical range of altitudes. Near to the event time, this range was changed a little based on the long-range forecast (doing this on the basis of a short-range forecast might well have helped things). The temperature resolution used was chosen as a compromise between the magnitude of the expected temperature changes, the typical accuracy and precision of common thermometers, and the range of temperatures that needed to be covered. For example, although it is clearly beneficial to cover a wide range of parameter values at high resolution, including too many values would make the webform interface cumbersome. Analysis of the NEWEx observations suggested this was an infrequent problem, but there are suggestions that the inclusion of sub-zero temperatures may have caused some confusion. For example, one submission was found to have submitted temperatures very similar in magnitude to several other closely located submissions, except that the temperature values entered were negative. Participants were provided with basic instructions on how to measure air temperatures, stating that measurements should be taken in the shade to reduce the effect of radiation errors [12]. The type of thermometer that should be used was not specified, other than requiring a resolution of at least 0.5°C. This decision was made to help encourage participation, as it was considered that overly specifying the type of thermometer could make NEWEx inaccessible to some groups. This means that we are unable to quantify the errors associated with each submitted temperature. Meteorological thermometry was reviewed by Harrison [12], who concluded that the accuracy of liquid-in-glass thermometers is typically ±0.2°C whereas the accuracy of some inexpensive digital thermometers can be much poorer. These errors are comparable in magnitude to the eclipse-induced temperature effects that we aim to observe. However, by averaging multiple submissions, these errors can be suppressed and robust estimates of temperature can be made; for this reason, NEWEx relies on effective participation. Therefore, we can have more confidence in the NEWEx results in regions with high participation, while the uncertainties are larger in areas with lower participation. (d) Cloudiness Measurement of cloud is something for which some training of an observer is known to be useful. Conventional meteorological practice is to record both the level of the cloud (as low, medium and high), and the cloud coverage at each level, in eighths of the sky covered. For this project, a much simplified approach was used. Cloudiness observations were divided into the four categories of clear sky, some cloud, much cloud and totally overcast. (e) Wind speed and direction Accurate wind speed measurements require an anemometer, but this was not an instrument considered likely to be available to most of the participants. Wind speed can, however, be estimated entirely without instrumentation from its visible effects, using the Beaufort system, and this was the approach adopted. Wind speeds were assessed and reported in terms of the Beaufort force and the standard descriptions of each force, between Forces 0 and 6. Wind directions were classified by visual estimation of direction, using the eight-point compass directions: north, northeast, east, southeast, south, southwest, west and northwest. Using simple visual assessments of the cloudiness and wind speed and direction has some advantages. Most importantly it meant that the only apparatus required to participate in NEWEx was a timepiece and a basic thermometer. This, coupled with the simplicity of the observations, fulfils the requirement that the observations be practically achievable for participants with a wide range of resources and abilities. However, a disadvantage of requesting such low-fidelity observations was that there was uncertainty about whether they would be able to resolve the small meteorological changes resulting from an eclipse. Clearly, this represented a compromise between encouraging participation with the minimum level of instrumentation, and the limited resolution and accuracy provided by the estimations made. (f) Location It was necessary to designate a location to each of the observations submitted via the NEWEx webform. In the design stage of NEWEx, it was decided that participants would be required to provide their location using the postcode of where the observations were made. Postcodes in the UK are an alphanumeric code used by the postal service to designate geographical delivery areas. The basis for this decision is that we considered it likely that participants would have access to an appropriate postcode, but may not know their latitude and longitude, or how to access this information conveniently or reliably. A complete postcode is referred to as a ‘postcode unit’ and each unit consists of a ‘sector’, ‘district’ and ‘area’, which isolate progressively larger geographical areas. For example, the postcode unit of the Meteorology Department at the University of Reading is RG6 6BB. This unit has the following components: the postcode area is RG, for the Reading postal office; the postcode district is RG6, for the Earley suburb of Reading; and the postcode sector is RG6 6, which isolates mainly the portion of Earley spanned by the University of Reading Whiteknights campus. To convert the postcodes into physical coordinates, the Ordnance Survey Code Point Open dataset was used (https://www.ordnancesurvey.co.uk/business-and-government/products/code-point-open.html). Code Point Open is a freely available database that provides the easting and northing coordinates of the approximately 1.8 million postcode units used by the UK’s Royal Mail. The conversion from easting and northing to latitude and longitude was facilitated by the ‘oscodepoint’ Python package (https://pypi.python.org/pypi/oscodepoint). Using the Ordnance Survey codepoint data and the oscodepoint Python package, it is possible to algorithmically convert postcodes into latitude and longitude coordinates. Obtaining this location data is critical to the subsequent analysis, and so it was necessary to consider how to process incomplete or invalid postcode units. It was decided to also calculate approximate coordinates for the locations more coarsely defined by the postcode districts and postcode areas. To do this, we calculated the average latitude and longitude of the set of postcode units in their respective districts and areas. This provided, in effect, an average coordinate weighted approximately by the population density in that region. If a postcode unit submitted by a participant could not be matched to a valid postcode unit, we tried to associate it with a valid postcode district or, failing that, a postcode area. If no geographical location could be attributed to the observations, they were not analysed further. We are unable to check for postcodes that were valid but incorrectly entered, which is a source of error that we cannot quantify. 3. Data processing (a) Pre-analysis processing Several phases of quality control and processing were applied to the data before they were used in any analysis. In total, NEWEx received 503 submissions via the webform, of which 15 were removed as they were submitted before the start time of the experiment (0800) and so could contain no valid data. Of the remaining 488 entries, 40 provided location information in a format other than a standard UK postcode. From the information provided, we established full or partial UK postcodes for 23 of these 40, and the remaining 17 were removed, including three entries from The Netherlands, Spain and the Republic of Ireland. Therefore geographical coordinates were established for 471 entries, with 420 linked to a complete postcode unit, 47 to a postcode district and 4 to a postcode area. These 471 entries correspond to 309 unique locations, as several participating groups made multiple submissions. As the overwhelming majority of submissions were linked to a full postcode unit, hereafter it is assumed that any errors associated with the approximate locations attributed to the postcode districts and areas will have a negligible effect on our analyses. The geographical distribution of NEWEx submissions is illustrated in figure 1a, demonstrating that the submissions extend across the southern and central regions of the UK but become increasingly sparse to the northern and western regions, appearing to approximately follow the distribution of population density. Many submissions are clustered around London and in southeast England. Figure 1. (a) Map of the UK with the red squares marking the locations of individual NEWEx submissions that were found to have some valid data. The black box marks the 0.2°×0.2° region centred on the University of Reading’s Atmospheric Observatory, which is analysed in §4a. (b–e) The number of observations for each of the available NEWEx observation times as a function of the time that these data were submitted to NEWEx, for temperature, cloudiness, wind speed and wind direction, respectively. These four panels all share common axes and scaling. Further to removing submissions received before the beginning of the experiment, it was also considered prudent to remove all measurements attributed to observation times later than the recorded submission time. In these instances, we do not remove the entire submission, but mask the erroneous observations from further analysis. This error occurred infrequently and removes only 41 values from the complete set of 15 606 observations collated by NEWEx. Figure 1a highlights that the NEWEx observations are not uniformly spatially distributed, while figure 1(b–e) considers how the observations are distributed among the NEWEx observation times and as a function of submission time. For each parameter and each observation time, the number of observations received by NEWEx before a given submission time was calculated for submission times ranging from 0830 until 2330, in steps of 30 min. The distribution of the number of observations is shown for temperature, cloudiness, wind speed and wind direction in figure 1b,c,d and e, respectively. Each panel uses the same scaling given by the colour bar on the right of the figure. One objective of NEWEx was to analyse submissions in close to real time and to report online the findings as the eclipse progressed. Figure 1b–e demonstrates why this objective was difficult to achieve on the day. Very few submissions were received during the main phase of the eclipse, with a drastic rise in the number of submissions after 1100. The submissions continue throughout the day, but, for each parameter, the distribution of the number of observations across the observation times has approximately converged to its final shape by 1900 onwards. Ideally, these distributions would be uniform, with approximately equal numbers of observations at each observation time. However, there was clearly a strong behavioural preference for participants to provide observations during the main phase of the eclipse, with the periods before and after having approximately half the number of observations. Comparing the distributions across the parameters demonstrates that, while the temperature, cloudiness and wind speed parameters have a similar number of observations (4043, 4469 and 4121, respectively), there are significantly fewer wind direction observations (2973). It is unclear exactly why this is. Wind speed was typically quite light on the day, which may have made assessing the wind direction more difficult, and many of the NEWEx observations were recorded in an urban environment, which may have also complicated assessing the wind direction [13]. (b) Gridding To analyse the spatial evolution of the observed meteorological fields, they were gridded onto a 0.1°×0.1° latitude–longitude grid, spanning from −8.2° to 2.0° longitude and 49.0° to 60.4° latitude. For each field and each observation time, the mean of the NEWEx observations in each grid cell was calculated. Bi-linear interpolation was used to fill in grid cells with no data. In the case of the cloudiness observations, the clear sky, some cloud, much cloud and totally overcast categories were converted into 0, 1, 2 and 3, respectively. As shown in figure 1a, the observation network has regions that are sparsely populated, where the bi-linear interpolation may yield estimates that are poorly constrained due to being based on widely separated observations. To limit this, we apply a mask to the interpolated fields, removing all interpolated values that are five or more grid cells from a cell containing NEWEx observations. The gridding process is demonstrated graphically in figure 2. Figure 2. Panels demonstrating the gridding process using the NEWEx temperature observations at 0920. (a) Markers show locations of NEWEx submissions providing temperature observations at 0920, where markers are coloured according to the observed temperature. (b) Grid cell means of the NEWEx temperatures. (c) Bi-linearly interpolated, masked and contoured temperature field. (c) Temperature anomalies The eclipse occurred during the morning, when near-surface air temperatures tend to increase as part of the diurnal cycle. This diurnal signal can complicate identifying an eclipse-driven response in near-surface air temperatures. Therefore, for each grid cell, we also calculate a temperature anomaly, calculating the difference between the observed temperatures and an estimate of how the temperature would have evolved without the eclipse. The expected temperature evolution without the eclipse is estimated by assuming that the diurnal rise in temperatures is approximately linear over the period of the eclipse. The ordinary least-squares regression of the 0800–0830 and 1030–1100 temperature observations against observation time provides the linear fit used to estimate the expected air temperature without the eclipse, at times between first contact and fourth contact. With this fit, the temperature anomaly is calculated at each observation time throughout the eclipse. Figure 1b clearly shows that there are fewer observations in the 0800–0830 and 1030–1100 periods than during the eclipse. The result of this is that there is a fraction of grid cells where no temperature anomalies can be calculated because of insufficient data coverage. Therefore, the temperature anomaly field has sparser spatial coverage than the temperature field. 4. Results (a) Assessing the accuracy of NEWEx temperature estimates We now consider how accurate the NEWEx temperature estimates may be, by comparing them against a long-established source of reliable near-surface air temperature observations taken from the University of Reading’s Atmospheric Observatory (URAO) (http://www.met.reading.ac.uk/observatorymain/index.html). The URAO is located at a latitude of 51.441° N, longitude of 0.938° W, and an altitude 66 m above mean sea level. Air temperature observations were made with a platinum resistance thermometer situated 1.25 m above ground, housed inside a Stevenson screen, and recorded with a frequency of 1 Hz. The Stevenson screen acts to protect and isolate the thermometer from factors that could cause errors in the air temperature measurements, such as direct solar radiation and precipitation [12]. We use 1 min means of the URAO air temperature measurements, as provided in the electronic supplementary material of Burt [14] in this issue, which also includes further details of the observatory and discussion of the eclipse effects on the weather at URAO. The temperature time series for this area was also calculated from the NEWEx observations. All submissions within a 0.2°×0.2° latitude–longitude box centred on the coordinates of the URAO were identified. This region is marked by the black box in figure 1a. There were 15 submissions that provided temperature estimates in this region, although one was removed from further analysis as the participant provided only one temperature observation of 17°C at 0920, which was clearly an outlier. For each NEWEx observation time, the mean of the temperature estimates was calculated. Figure 3a shows the NEWEx and URAO temperature observations. The comparison is demanding as, due to the layer of cloud present in the Reading area throughout the eclipse, the temperature variation was considerably suppressed over that expected in clear skies. Grey lines show the temperature time series for individual NEWEx submissions. Note that fewer than 14 submissions are visible, as the discrete nature of the submitted temperatures, and agreement between observers, means several lines overlap. The blue line shows the mean of the NEWEx submissions, where the error bars represent two standard errors of the mean. The black dots mark the 1 min mean URAO temperature time series, while the red line shows the 15 min running boxcar-window mean of these data. Figure 3. (a) Time series of the temperature estimates for the Reading region, marked by the black box in figure 1a. The black dots show the 1 min mean temperatures from the URAO, while the red line is a 15 min rolling window mean of these data. The grey lines show the sequences of temperature observations for each submission. The blue squares show the mean of the NEWEx temperatures at each observation time, while the error bars are two standard errors of the mean. (b) Time series of the temperature anomaly for the NEWEx and URAO temperature series, in blue (squares) and red (dots), respectively. The mean NEWEx temperature series is biased to higher temperatures relative to the URAO series, although the URAO series typically lies within the lower limit of the two standard errors of the mean NEWEx temperature. The bias varies from a minimum of 0.5°C to a maximum of 1.5°C, with a mean value of 0.9°C. Although undesirable in absolute terms, the small bias is considered reasonable for the following reasons: firstly, it is unlikely that the NEWEx temperature observations were made in an environment as effectively exposed as URAO; secondly, it is unlikely that they were taken within an environment designed to minimize errors due to other environmental factors, such as that provided by the Stevenson screen at URAO. The overcast conditions in the Reading region (figure 6) mean that it is unlikely that a radiation error from direct solar heating accounts for much of this difference. Prior research into the differences between measurements of open air temperature and screen temperature demonstrates that for surface insolations of more than 500 W m−2 the temperature difference is rarely larger than 0.5°C [15]. The URAO observations show that, due to heavily overcast conditions in the southern UK, global solar radiation at the surface was low throughout the morning, being less than 160 W m−2 until 1100 [14]. Therefore, although NEWEx temperature observations are certainly subject to some radiation error, it is very unlikely that this explains much of the observed warm bias. However, it is possible that factors such as observers working in more sheltered and more urban environments, as well as possibly holding the thermometer, may explain this bias. Furthermore, the NEWEx temperature estimate is based on observations over the 0.2°×0.2° area centred on URAO, and the average temperature over this region should be expected to differ somewhat from a point measurement at URAO. Although there is a systematic difference between the NEWEx and URAO temperatures, it is possible that they both show a similar relative response during the eclipse. This is considered here by comparing the temperature anomaly of both the URAO and mean NEWEx temperature series, which was calculated as described in §3c. As discussed in §2, the NEWEx observation times are split into a higher frequency (5 min) period and two lower frequency (15 min) periods. To make a fair comparison between the mixed resolution NEWEx observations and the uniform URAO observations, the URAO data are processed before the temperature anomaly is calculated, so that they have a mixed resolution similar to NEWEx. For the higher resolution period, 5 min averages of the URAO data are used, while, for the two lower resolution periods, 15 min averages of the URAO data are used. Figure 3b shows the NEWEx and URAO temperature anomaly data, in blue and red, respectively. Error bars are included for the URAO temperature series; however, they are sufficiently narrow that they do not appear outside the markers. Both temperature anomaly profiles show a shallow decrease in temperature over the eclipse period. The NEWEx anomaly shows a maximum decrease of 0.86±0.86°C at 0935 while the maximum decrease in the URAO series was 0.29±0.01°C at 0955. Burt [14] also analyses the URAO temperatures during the eclipse and, on the basis of the 1 min mean values, estimates that the maximum temperature anomaly during the eclipse was ≈0.6°C. The magnitude of the eclipse response should be larger in the higher temporal resolution 1 min values analysed in [14], and so we consider these estimates to be consistent. There is a 20 min delay between the maximum anomaly in the NEWEx and URAO temperature series. However, given the very calm conditions, it was estimated in [14] that the URAO temperature observations from within the Stevenson screen would be lagged behind the true air temperature by approximately 5–10 min, and so it is reasonable that the maximum temperature anomaly occurred later in the URAO observations. Therefore, we conclude that NEWEx performs reasonably well at monitoring the meteorological conditions for a region, as the differences between the NEWEx temperature observations and the well-established URAO observations are small and can be explained in terms of known features of the measurement systems and data processing. (b) Eclipse-induced temperature effects Figures 4 and 5 show contours of temperature field and temperature anomaly field estimated from the gridded NEWEx observations at 0830, 0940 and 1030. The times 0830 and 1030 are the closest observation times corresponding to the times of first contact and fourth contact, respectively, and 0940 is the mean time when, according to the NEWEx data, UK sites experienced a maximum temperature anomaly. The mean of the maximum temperature anomalies was −2.2 ± 0.3°C. Figure 4. Maps showing contours of the NEWEx temperature fields at 0830, 0940 and 1030. These are the NEWEx observation times that most closely correspond to the times of first contact, maximum temperature anomaly and fourth contact, respectively. Figure 5. As for figure 4, instead showing contours of the estimated temperature anomaly, calculated as described in §3c. There was no apparent relationship between the time of the maximum temperature anomaly and the geographical location, as might be expected from the approximately northeastward propagation of the eclipse over the UK, with the times of maximum obscuration varying from approximately 0925 in the UK’s southwest peninsula to 0940 in the northwest of Scotland. However, this may be due to the 5 min resolution of the temperature observations being too low to resolve any such relationship, and because the majority of the NEWEx submissions were clustered in the central and southeastern regions, where the maximum obscuration times were similar, occurring at approximately 0930. As the mean time of the maximum temperature anomaly was 0940, this implies that the lag between maximum obscuration and maximum temperature anomaly was typically about 10 min. Comparing the structure of the temperature anomaly fields (figure 5) with the cloudiness fields (figure 6) shows that, as expected, temperature anomalies are smaller in magnitude in regions of increased cloudiness. Elsewhere in this issue, Clark [16] analyses 1 min resolution temperature observations from 266 sites contributing to the UK Met Office’s Meteorological Monitoring System (MMS) and finds eclipse-induced temperature anomalies that range between −0.03°C and −4.23°C, with a median value of −1.02°C. The temperature anomalies derived from the NEWEx observations are broadly consistent with this, as figure 5 shows that the 0940 temperature anomalies are typically within the range observed in [16]. Furthermore, there is fair agreement between the structure of the temperature anomaly field at 0940 and the contours of the maximum temperature anomaly presented in fig. 7a of [16]. However, we do note that Clark [16] reports a smaller average temperature anomaly and a longer average lag (≈15 min) between maximum obscuration and the maximum temperature anomaly. These differences are similar to those found when comparing the NEWEx and URAO temperature anomalies. The MMS temperature data are derived from 266 locations, whereas the NEWEx data come from 309 locations, but the spatial distributions of these networks are very different: MMS has a more even coverage, being less clustered around population centres. Furthermore, the MMS temperature measurements are recorded within Stevenson screens, which, similar to the comparison with URAO data, may partly explain the difference in the observed lag between maximum obscuration and maximum temperature anomaly. Figure 6. As for figure 4, instead showing contours of the cloudiness observations. Figure 7. As for figure 4, instead showing contours of the wind speed. (c) Eclipse-induced effects on cloudiness Figure 6 shows contours of the cloudiness at 0830, 0940 and 1030. These reveal that much of the southeast of the UK was overcast throughout the eclipse, with a band of mostly clear and cloud-free conditions across the Midlands. This is in good agreement with both the visible and infrared remote sensing images of the cloud field during the eclipse (cf. fig. 7a of [16] and fig. 1b of [6]) and, as discussed in §4b, is consistent with the observed temperature anomalies. Resolving changes in cloudiness caused by the eclipse is an important practical question, as images of the eclipsed Sun are scientifically very useful within the solar physics and astronomy communities (see, for example, [17,18] and Scott et al. [19] in this issue), and there is enormous public interest in viewing the eclipse. Therefore, it is important to determine whether or not the eclipse can cause changes in the cloud field that could make a successful eclipse observation more or less likely. From figure 6, there is a suggestion that the region of mostly clear and clear sky was broader at 0940 than at either 0830 or 1030, which could perhaps be an eclipse-driven change in cloudiness. However, there were also weather-related changes in cloud during the same interval, due to the slow southwards passage of a weak weather front, which complicates attributing changes in the cloud field to eclipse-driven effects. A sequence of χ2-tests of homogeneity was employed to infer whether the data suggest that the amount of cloudiness changed between 0830, 0940 and 1030. Only grid cells containing NEWEx observations at each of 0830, 0940 and 1030 were analysed. Therefore, no interpolated data are analysed and the spatial distribution of the observations used in the statistical tests does not change. For these grid cells, the histogram of the cloudiness observations was calculated for each time and these data are compiled into the contingency table in table 1; note that the total count is the same at each time due to the requirement that each grid cell include observations at each of 0830, 0940 and 1030. It is immediately clear from table 1 that the histograms of cloudiness are very similar for each time. The χ2-test of homogeneity is used to assess whether the observed proportions of cloudiness observations are consistent with the null hypothesis that they are time-independent, i.e. that the distributions of cloudiness did not change with time. The test is implemented as described in [20] and compares the observed occurrence with the expected occurrence under the null hypothesis of homogeneity. More details on the statistical testing procedures are given in appendix A. This test was employed on each of the three unique pairings of the cloudiness distributions at 0830, 0940 and 1030, i.e. 0830–0940, 0830–1030 and 0940–1030. The χ2-values and p-values of these three tests are included in table 2. For a single statistical test, it would be common to compare these p-values against a criterion of p<0.05, which would indicate that the data were unlikely to have been obtained under the null hypothesis. However, here, multiple comparisons are performed and it is appropriate to use a Bonferroni-adjusted critical p-value, such that the appropriate criterion is p<0.017. These p-values are much larger than the Bonferroni-adjusted critical p-value, which indicates that these data are not inconsistent with the null hypothesis that there was no change in these cloudiness distributions with time. Therefore, these tests provide no evidence that there was an eclipse-induced response in the cloud field. We stress that this lack of a significant change does not mean that there is no response in the cloud field to the eclipse. Instead, the low fidelity of the cloudiness observations and changes in the data coverage across the NEWEx observation period mean that we are unable to draw any definitive conclusions about whether or not there were eclipse-driven changes in the cloud field. Although a more sensitive determination of cloudiness may have been beneficial, it is necessary to bear in mind the importance of the measurements being practically achievable for a wide range of abilities; a more sensitive measure of cloudiness, such as resolving cloud amount in eighths (oktas) of sky coverage, may have also been more difficult for participants to assess, and so could have led to fewer reliable observations. Table 1. Distributions of cloudiness before, during and after the eclipse. time (UT) clear sky mostly clear mostly cloudy overcast total 0830 17 (12%) 39 (28%) 28 (20%) 56 (40%) 140 0940 18 (13%) 37 (26%) 31 (22%) 54 (39%) 140 1030 21 (15%) 37 (26%) 30 (21%) 52 (37%) 140 Table 2. Results of the χ2 homogeneity tests on distributions of cloudiness. comparison χ2 p-value 0830–0940 0.27 0.966 0830–1030 0.69 0.875 0940–1030 0.28 0.963 (d) Eclipse-induced effects on wind speed and direction Figure 7 shows contours of the NEWEx wind speeds at 0830, 0940 and 1030, in terms of the Beaufort wind force. Winds were typically very light across the UK throughout the eclipse period. The limited spatial coverage and low fidelity of the wind speed observations also make it difficult to interpret the estimated wind speed fields. However, figure 7 does appear to show limited evidence of an increased occurrence of weaker wind speeds at 0940 relative to 0830 and 1030. The same χ2 statistical testing procedure that was used with the cloudiness observations was also employed with these wind speed data. Again, only grid cells containing wind speed observations at each of 0830, 0940 and 1030 were analysed, such that no interpolated data were analysed and the spatial distribution of the observations is the same at each time. The histograms of the wind force observations are compiled into the contingency table given in table 3; wind speeds greater than Force 3 were merged into a Force ≥3 category, to meet the recommendation of the χ2-test of homogeneity that no categories have fewer than five counts. A clear feature of the values in table 3 is a marked increase in the occurrence of Force 0 winds at 0940 relative to 0830 and 1030, as well as a similar decrease in Force 2 winds. This is suggestive of a decrease in reported wind speeds at 0940. For these wind speed data, the χ2-values and p-values are reported in table 4. These p-values do not meet the Bonferroni-adjusted p-value criterion of p<0.017 that would indicate that these data are unlikely to have been obtained under the null hypothesis that the wind speed distributions were the same at all times. However, the 0940–1030 comparison is close to the critical value, which suggests that these data are moderately inconsistent with the null hypothesis. As recommended in [20], it can be instructive to look at such data in more detail. Here, this is done by computing the standardized residuals between the observed occurrence and expected occurrence under the null hypothesis of homogeneity, using the method given in [20], which is described in appendix A. The results are p-values for each cell of the 2×4 contingency table for the 0940–1030 comparison, which are reported in table 5. For the commonly used test level of α=0.05 (see appendix A), these p-values should be compared against a Bonferroni-adjusted p-value of p<0.006. Table 5 shows that the p-values of the Force 0 wind speeds are close to (but just larger than, at the fifth decimal place) the critical value, suggesting that these values are quite unlikely to have been obtained under the null hypothesis of homogeneity. Considering these statistical tests in conjunction with the observed increase in the occurrence of reported Force 0 wind speeds at 0940 suggests that there is reasonable evidence that the NEWEx observations reveal a temporary slight decrease in the wind speed near the time of the maximum temperature anomaly. Gray & Harrison [6] used the UK Met Office’s MIDAS observation network and another network of roadside observations operated by Vaisala to assess wind changes associated with the 20 March 2015 eclipse, and found a decrease in the wind speed of up to 2 knots. The analysis of the NEWEx results appears to be consistent with this. Table 3. Distributions of wind speed before, during and after the eclipse. time (UT) Force 0 Force 1 Force 2 Force ≥3 total 0830 19 (21%) 38 (42%) 26 (29%) 7 (8%) 90 0940 31 (34%) 32 (36%) 18 (20%) 9 (10%) 90 1030 15 (17%) 36 (40%) 29 (32%) 10 (11%) 90 Table 4. Results of the χ2 homogeneity tests on distributions of wind speed. comparison χ2 p-value 0830–0940 5.10 0.165 0830–1030 1.21 0.748 0940–1030 8.43 0.038 Table 5. The p-values of wind speed standardized residuals before, during and after the eclipse. time (UT) Force 0 Force 1 Force 2 Force ≥3 0940 0.006 0.539 0.062 0.808 1030 0.006 0.539 0.062 0.808 Assessment of the wind direction appears to have been challenging, as indicated by the comparatively fewer wind direction observations relative to the temperature, cloudiness and wind speed observations (figure 1). As of yet we have been unable to establish if the reported wind directions can be used to infer anything about eclipse-driven changes in the wind direction. Gray & Harrison [6] also investigated eclipse-driven wind direction changes and found a temporary backing of the wind direction by approximately 20°. These direction changes are smaller than could easily be resolved by the NEWEx wind directions, which were recorded in terms of the eight-point compass directions, and so have an angular resolution of 45°. The low angular resolution of the NEWEx wind directions, coupled with slightly less participation in the wind direction measurements, means that it may be difficult to glean any information on eclipse-driven wind direction changes from the NEWEx data. 5. Conclusion The NEWEx was, as far as we know, a world first, in measuring and analysing eclipse changes in the weather on a national scale, in close to real time, through engagement of a network of citizen scientists. Through this engagement with the public, NEWEx collected 15 606 meteorological observations from 309 locations within the UK. From these data, we have been able to derive estimates of the near-surface air temperature, cloudiness and near-surface wind speed fields across many UK sites. Additionally, NEWEx gained the attention of both the national and local press and was well received by the public, and it therefore served as a very positive science outreach experience. These aspects of NEWEx are discussed in [7]. The estimates of the near-surface air temperatures and eclipse-driven temperature anomalies were consistent with other well-established means of measuring these parameters, such as with measurements from the URAO and the UK Met Office’s MMS. This is quite remarkable given the simplicity of the observations required by participants in NEWEx and the small magnitude of the changes observed. The low fidelity of the wind speed, wind direction and cloudiness observations provided a broad picture of these conditions over the UK, but did make it difficult to detect eclipse-driven changes in these fields. Statistical tests were employed to assess whether there were differences between the distributions of both cloudiness and wind speed at times just before the eclipse, at the mean time of the maximum temperature anomaly, and at the end of the eclipse. There was no evidence to suggest that the distribution of reported cloudiness changed over these periods. However, there was reasonable evidence to suggest a temporary decrease in the reported wind speed, which was shown to be consistent with the analyses of professional meteorological data of this eclipse [6]. Analysis of the submitted observations demonstrated comparatively fewer wind direction observations relative to temperature, cloudiness and wind speed. This suggests that participants found it difficult to estimate the wind direction. This could be improved upon by suggesting that participants use a compass and some kind of tracer to estimate the wind direction, for example, soap bubbles or blades of grass. The data collection system for NEWEx worked effectively, but, given its critical role in the success of NEWEx, it is worth considering how it could have been improved. Of the 488 submissions, 40 provided location data in a format other than the requested postcode format. The impact of these errors appears to have been small, as approximate locations were obtained for 23 of these 40, while the remaining 17 were removed. Changes to the structure of the NEWEx webform could have potentially avoided this error. For example, a validation rule could have been used to return errors to participants submitting postcodes that do not conform to known properties of postcodes (for example, postcodes have a strict minimum and maximum possible length and should be alphanumeric). This functionality is available within the Google Form service used by NEWEx. Furthermore, although we could identify and remove invalid postcodes, we were unable to identify submissions that used a valid but inappropriate postcode. The occurrence of this error could be reduced by including a dynamic map on the NEWEx webform, which identifies the location of a participant’s submitted postcode, such that the participant can validate their own submission. Finally, in the pre-analysis processing of the NEWEx data, it was established that a small fraction (0.2%) of data was submitted at times prior to the recorded observation time, which is clearly an error. This error could be avoided by developing a dynamic webform that updates throughout the experiment, to limit the possibilities for participants to submit data in error. However, implementing the suggested solutions to the identified limitations would have required significantly more resources in the development stage of NEWEx, probably requiring a custom-made webform; this was beyond the scope of the resources available to NEWEx, but could be worth considering for future studies employing a similar method. The level of participation in NEWEx was good, with submissions being received from across the UK. This was in part achieved by liaising with appropriate institutions, such as the South-East Physics Network, the Scottish Institute of Physics, the Royal Society of Edinburgh and the BBC. This was supplemented by advertising NEWEx on both local and national radio, as well as social media engagement via Twitter. Participation was higher in urban areas, and in particular the southeast, which is probably due to increased population density. NEWEx could have been improved with more participation from rural and remote areas; this could possibly be achieved by directly targeting rural schools. Considering these results, it is clear that NEWEx achieved both of its principal objectives, having provided a spatial network of meteorological observations that detected eclipse-driven weather changes and also a successful nationwide public engagement activity. In August 2017, a total solar eclipse will be visible from North America, propagating from the east coast to the west coast of the USA, providing another opportunity to study eclipse-induced meteorology changes. NEWEx serves as a useful example of the strengths and challenges of using a citizen science approach to study eclipse-induced meteorological changes, and could provide a template for a similar study for the August 2017 eclipse. Acknowledgements The authors gratefully acknowledge the enthusiastic participation of everybody who contributed data to NEWEx. L.B. acknowledges helpful advice from Matthew Clark. 1 A small fraction of solar short-wave radiation received at Earth is emitted from the solar corona, which is never fully eclipsed. Data accessibility The National Eclipse Weather Experiment observations analysed in this paper are available from the University of Reading Research Data Archive at http://dx.doi.org/10.17864/1947.68. Authors' contributions L.B. contributed to the experimental design, produced the analysis code and wrote the majority of the article. R.G.H. led the design of the experiment and contributed to the analysis and writing the article. S.L.G. contributed to the design of the experiment and writing the article. A.M.P. contributed to the design of the experiment, coordinated the public engagement aspects of NEWEx and contributed to writing the article. Competing interests We have no competing interests. Funding L.B. thanks the UK’s Natural Environmental Research Council (NERC) for support under grant NE/J024678/1 and the Science and Technology Facilities Council (STFC) for support under grant ST/M000885/1. Appendix A (a) Bonferroni-adjusted p-values In null hypothesis significance testing, it is common to calculate some test statistic, for example a χ2-value, and to compare this with the distribution of values of the test statistic that would be expected if the null hypothesis were true. If the observed test statistic is sufficiently unlikely to occur under the null distribution, this indicates that these data are unlikely to have been obtained if the null hypothesis were true [21]; this can be interpreted as evidence against the null hypothesis [20]. Here, ‘sufficiently unlikely’ is a subjective judgement that must be made by the investigators, although it is typical to set a criterion of p<α, where p is the probability of obtaining a test statistic at least as improbable as the observed value, and α is the ‘level’ of the test, commonly set at α=0.05 [21]. A Type-I error, or false-positive, occurs when the null hypothesis is incorrectly rejected. For a given test, the probability of obtaining a Type-I error is equal to the level of the test. When making multiple statistical tests, it therefore becomes increasingly probable that a Type-I error will be obtained. To preserve the rate of Type-I errors across multiple tests, a Bonferroni adjustment may be applied to the level of the test (or the corresponding critical value of the test statistic). The Bonferroni adjustment makes each of the multiple tests more stringent, such that the Type-I error rate for the family of tests will be set at the chosen test level [22]. In making C comparisons, this amounts to using an adjusted test level of αb=α/C. This Bonferroni adjustment is used to set the test levels in the hypothesis tests in §4c,d. (b) Standardized residuals of contingency tables A χ2-test of homogeneity may suggest that the observed data are inconsistent with a null hypothesis, but the test gives no information as to why the data are inconsistent. Agresti [20] describes how a cell-wise comparison of observed and expected frequencies in a contingency table can be used to better understand the results of a χ2-test. This is performed by computing the standardized residuals (rij) between the observed occurrence (nij) and expected occurrence under the null hypothesis of homogeneity (), using eqn 2.9 of [20], A 1 where subscripts i and j refer to row and column indices, and pi+ and p+j are the total proportion of the data in each row and column, respectively. Under the assumption of the null hypothesis, the standardized residuals are approximately normally distributed with zero mean and unit variance [20]. The standardized residuals are converted to p-values using the standard normal distribution, where they can be compared with a Bonferroni-adjusted p-value to identify cells that appear to be inconsistent with the null hypothesis of homogeneity [22]. For the 2×4 contingency table analysed in §4d there are eight comparisons, and so to maintain a Type-I error rate of 0.05, the adjusted p-value is 0.006. ==== Refs References 1 Aplin KL , Harrison RG 2003 Meteorological effects of the eclipse of 11 August 1999 in cloudy and clear conditions . Proc. R. Soc. Lond. A 459 , 353 –372 . (10.1098/rspa.2002.1042 ) 2 Aplin KL , Scott CJ , Gray SL 2016 Atmospheric changes from solar eclipses . Phil. Trans. R. Soc. 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Hoboken, NJ : John Wiley & Sons . 21 Wilks DS 2011 Statistical methods in the atmospheric sciences , 3rd edn Amsterdam, The Netherlands : Elsevier . 22 MacDonald P , Gardner R 2000 Type I error rate comparisons of post hoc procedures for I×J chi-square tables . Educ. Psychol. Meas. 60 , 735 –754 . (10.1177/00131640021970871 )

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==== Front Philos Trans A Math Phys Eng SciPhilos Trans A Math Phys Eng SciRSTAroyptaPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences1364-503X1471-2962The Royal Society Publishing 2755075710.1098/rsta.2015.0221rsta20150221100512127ArticlesResearch ArticleCoordinated weather balloon solar radiation measurements during a solar eclipse Balloon solar eclipse measurementshttp://orcid.org/0000-0003-0693-347XHarrison R. G. http://orcid.org/0000-0002-8466-6779Marlton G. J. http://orcid.org/0000-0002-9713-9820Williams P. D. http://orcid.org/0000-0001-5580-6325Nicoll K. A. Department of Meteorology, University of Reading, PO Box 243, Reading RG6 6BB, UKe-mail: r.g.harrison@reading.ac.ukOne contribution of 16 to a theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. 28 9 2016 28 9 2016 374 2077 Theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’ compiled and edited by R. Giles Harrison and Edward Hanna2015022120 11 2015 © 2016 The Authors.2016Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.Solar eclipses provide a rapidly changing solar radiation environment. These changes can be studied using simple photodiode sensors, if the radiation reaching the sensors is unaffected by cloud. Transporting the sensors aloft using standard meteorological instrument packages modified to carry extra sensors, provides one promising but hitherto unexploited possibility for making solar eclipse radiation measurements. For the 20 March 2015 solar eclipse, a coordinated campaign of balloon-carried solar radiation measurements was undertaken from Reading (51.44°N, 0.94°W), Lerwick (60.15°N, 1.13°W) and Reykjavik (64.13°N, 21.90°W), straddling the path of the eclipse. The balloons reached sufficient altitude at the eclipse time for eclipse-induced variations in solar radiation and solar limb darkening to be measured above cloud. Because the sensor platforms were free to swing, techniques have been evaluated to correct the measurements for their changing orientation. In the swing-averaged technique, the mean value across a set of swings was used to approximate the radiation falling on a horizontal surface; in the swing-maximum technique, the direct beam was estimated by assuming that the maximum solar radiation during a swing occurs when the photodiode sensing surface becomes normal to the direction of the solar beam. Both approaches, essentially independent, give values that agree with theoretical expectations for the eclipse-induced radiation changes. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. radiosondephotodioderadiometryNERC Impact Accelerator Awardcover-dateSeptember 28, 2016 ==== Body 1. Introduction Solar eclipses provide an unusual opportunity to study a rapid and well-characterized change in the solar radiation entering the atmosphere. While radiation measurements related to eclipse changes have been made at the Earth’s surface [1], these can suffer from vagaries of the weather despite considerable planning, but fewer measurements have been made aloft because of the logistical difficulty and expense. A considerable attraction in using a platform aloft is that, as increasing height is achieved, the likelihood of cloud interfering with the measurements is reduced. Weather balloons, carrying meteorological instrument packages returning data by radio (radiosondes), potentially offer inexpensive platforms for such measurements. Some disadvantages, such as motion associated with the payload, limitations in weight, power and opportunities for instrument recovery, may, however, all have contributed to radiosonde platforms having been underexploited for eclipse measurements. Recent innovations in low-cost sensors have reinvigorated the utility of radiosondes as measurement platforms for parameters beyond the traditional meteorological variables. For example, a new data acquisition system has been developed to expand the science capabilities of standard commercial radiosonde systems in routine use internationally by meteorological services [2]. This system enhancement has already been used to successfully deploy a solar radiation sensor [3]. Importantly, both items are simple and inexpensive, which, as for the radiosonde itself, removes the need for them to be recovered: the instrumentation can be regarded as disposable. For a solar eclipse, a balloon-carried solar radiation sensor brings the possibility of measuring the radiation changes away from the immediate effects of the lower atmosphere, such as the attenuating or obscuring actions of cloud, or the absorption of radiation by atmospheric constituents such as water vapour. The major eclipse-induced changes also typically tend to occur within the typical balloon flight times of 1–2 h, which provides a rare source of well-characterized variations for an in situ instrument. Modern meteorological balloon systems are essentially portable (e.g. allowing sampling of airborne volcanic ash in hazardous conditions [4]), but the use of an established meteorological site in the eclipse zone means that additional air traffic permissions are unlikely to be needed and that substantial items of equipment do not need to be transported. Because the typical burst height for a weather balloon carrying a standard meteorological radiosonde is at 15–20 km altitude, some of the measurements can be reliably expected to be made in air which is cloud free, hence many of the conventional climatological considerations usually applied to selecting a site for an eclipse study can be overcome. 2. Objectives The path of the 20 March 2015 total solar eclipse across the North Atlantic and through the Faroe Islands generated an appreciable partial eclipse in the northern UK and Iceland. This presented an opportunity for a coordinated campaign of solar radiation measurements using radiometer radiosondes, launched from the University of Reading’s Atmospheric Observatory, the UK Met Office’s Lerwick site and the Icelandic Meteorological Office facilities at Reykjavik (figure 1). The objectives of this campaign were, first, to demonstrate that the radiosonde enhancement technology could be used straightforwardly for coordinated measurements of new atmospheric variables, and, second, to investigate data processing techniques needed to retrieve quantitative radiation information from an agitated, swinging platform carrying an inexpensive sensor. Although radiosondes have been used previously in eclipse meteorology for thermodynamic measurements [5], even including multiple soundings from the same launch site [6], it is possible that the 20 March 2015 undertaking represents the first coordinated radiosonde campaign to provide widely spatially separated non-thermodynamic eclipse measurements. Figure 1. Region of totality of the solar eclipse of 20 March 2015 (grey band), with times marked. Contours of percentage obscuration are given in the regions experiencing a partial eclipse. The radiosonde launch sites at Reading (southern UK), Lerwick (Shetland) and Reykjavik (western Iceland) are marked with hollow squares. 3. Solar radiation calculations A first consideration in configuring instrumentation for solar eclipse radiation measurements is to estimate the likely changes expected at each site. The sequence of events in a total eclipse follows from the Moon first appearing to reach the Sun (first contact) through second and third contact, between which there is the period of totality, to fourth contact when the Moon and Sun appear to emerge from each other. During the eclipse, the solar radiation is reduced from that expected for the same location and time of year, by the proportion of the solar disc’s area covered (the obscuration). Calculating the solar radiation during the eclipse can be achieved by combining the standard calculation of the daily variation in top-of-atmosphere solar radiation with a modulating function to represent the eclipse. The top-of-atmosphere solar radiation is essentially an astronomical calculation: the actual radiation in the lower atmosphere will be reduced from the top-of-atmosphere value through absorption by ozone and water vapour, which is variable. Assuming negligible difference between the actual and mean Sun–Earth distances, the time variation in solar irradiance on a horizontal surface at the top of the atmosphere ST(t) is given approximately by 3.1 where S0 is the total solar irradiance (TSI) and Z is the solar zenith angle at a time t. For a site at latitude ϕ when the solar declination is δ, the variation in Z during the day is found from the hour angle h(t) as 3.2 The solar irradiance variation with time at a particular position is conventionally calculated by combining (3.1) and (3.2) to give 3.3 On a day with a total solar eclipse, an additional modulation function is needed to represent the effect of the eclipse. The solar irradiance can then be written as 3.4 where E(t) is the eclipse function. In this case, the function is arranged to give the fraction of the Sun’s area covered as the eclipse progresses, with E(t)=0 at first and fourth contact. Full calculation of the eclipse function requires geocentric coordinates [7]. Instead, a simpler geometrical approximation is used [8], which represents the eclipsed Sun and Moon as two spherical bodies with an equal angular diameter at the Earth, and assumes that the solar disc is of uniform brightness with no darkening at the solar limb. These two bodies progress to overlap each other at a steady rate, with the fractional area of the solar disc remaining exposed given by 3.5 where fe(t) is the eclipse magnitude, the proportion of the Sun’s radius obscured by the Moon at a time t. For a total solar eclipse occurring symmetrically between first contact t=t1 and fourth contact t=t4, fe(t) can be defined as 3.6a and 3.6b with fe=1 during totality. For a symmetrical (and non-annular) partial eclipse having a maximum obscuration M at tM, the solar radiation does not reach zero and the solar radiation variation of equation (3.4) is modified to 3.7 with fe(t) found from 3.8a and 3.8b To calculate the top of atmosphere solar radiation variation on a day with an eclipse, values of t1 to t4 and M are required, available from eclipse tables. The other parameters required for the calculation are (i) the declination δ, given (in degrees) by 3.9 where d is the day of the year, (ii) the hour angle h, given (in degrees) by 3.10 with t the time of day for which the solar radiation is required and t0 the time of the local solar noon in hours and (iii) the TSI S0, 1365 W m−2. Table 1 summarizes the circumstances of the partial eclipse at Reading, Lerwick and Reykjavik, in particular the parameters t1, t4 (from which tM can be found) and M. These have been used to calculate the variation in top of atmosphere solar radiation, ST, using equation (3.7) for each site, plotted in figure 2. The variations differ between the sites. At Reading, the eclipse begins when ST has a larger value than at the other sites but undergoes a smaller change than at the other sites during the eclipse; at Lerwick and Reykjavik, the eclipse effects are greater, but change from smaller ST values than at Reading. Table 1. Circumstances of the 20 March 2015 solar eclipse at the three radiosonde launch sites. site latitude N longitude W eclipse start (UT) eclipse end (UT) magnitude Reading 51.44 0.94 0824 1040 0.88 Lerwick 60.15 −1.13 0839 1051 0.97 Reykjavik 64.13 21.90 0838 1040 0.98 Figure 2. Calculated solar irradiance on a horizontal surface at the top of the atmosphere (ST) plotted against time of day (in hours UT) for 20 March 2015, with the solar eclipse included for (a) Reading, (b) Lerwick and (c) Reykjavik. (The dotted line marks the solar irradiance calculated for the same day without the eclipse.) 4. Instrumentation The calculations in figure 2 indicate that a dynamic range of approximately 1000 W m−2 is needed for full measurement for the solar radiation measurement changes during the 20 March 2015 eclipse. The radiosonde radiation instrumentation described previously [2,3] was not intended for accurate radiometry, as its primary use was for detecting the radiation changes associated with cloud-to-clear-air transitions. However, in principle, the device should be capable of good radiation measurements, as the single conditioning circuitry employed a linear current to voltage converter, with the voltages recorded accurately on the radiosonde system using an analogue-to-digital converter. Furthermore, comparison at the surface against a calibrated radiometer had also shown a linear response to radiation, and part-to-part variation between the photodiode sensors used was small. The same device was therefore chosen for eclipse measurements. For the eclipse radiation measurements, instrumentation was constructed using the previous signal conditioning circuitry [3], and the PANDORA radiosonde data acquisition system [2]. Two similar radiometers were built for each radiosonde, but with silicon photodiode sensors of slightly different spectral ranges. The typical spectral response of a silicon photodiode begins at about 200 nm and rises steadily to a maximum around 950 nm, above which it sharply loses sensitivity. In one of the balloon radiometers, a VTB8440B photodiode was used, which includes a filter to remove the response at the infrared end of the visible spectrum. In the other, a VTB8440 photodiode was used, which is an unfiltered type and has a wider spectral range. Table 2 summarizes these details. Of the two photodiodes, the filtered device approximately covers the range of visible solar radiation, with its peak spectral response at 580 nm. The unfiltered device includes the visible range, but its principal sensitivity is weighted towards the near-infrared end of its response at 920 nm, with less response in the visible region. In a subsidiary experiment, photodiodes of both kinds were compared with a calibrated radiometer to determine their response to solar radiation; a summary is given in the electronic supplementary material. Table 2. Spectral response of photodiodes. part number λmin (nm) λmax (nm) λpeak (nm) comment VTB8440 320 1100 920 unfiltered—broader wavelength response VTB8440B 330 720 580 IR filter—visible wavelength response In use for the soundings, the photodiodes were mounted on an upper horizontal surface of the plastic enclosure housing the data acquisition system, which was strapped to the radiosonde package. This added a further 130 g of payload to the 350 g mass of the radiosonde. The existing radiosonde battery was used to power the additional instrumentation. The PANDORA system was programmed to return data every 1 s over the standard UHF data telemetry, with the photodiodes sampled 64 times per second to improve the effective resolution of the 10 bit analogue-to-digital convertor employed. 5. Results and data processing To increase the likelihood of the sensors being above the cloud during the time of maximum eclipse (about 0930 UT), the radiosondes were launched from each site close to 0845 UT. For an ascent rate of nominally 5 m s−1, this launch time was chosen to ensure that the radiosondes were above 10 km during the phase of the greatest eclipse. As well as being situated above cloud, the amount of radiative absorption from water vapour at this height is considerably reduced compared with that at the surface, and the solar radiation more closely approximates the calculated top-of-atmosphere value. The actual heights obtained from radiosondes depend, however, on the contributions of local winds, the balloons and the amount of free lift used. A further factor is that balloons can burst randomly at lower altitudes, although only rarely, for which circumstances an additional spare device was prepared as a contingency. Even so, unless such a random burst occurred at a low altitude or as part of the launch, the spare instrument was unlikely to rise sufficiently above cloud layers to give the unobstructed solar view sought. Fortunately, the contingency was not required at any of the sites. Measurements from the data acquisition system of both the unfiltered and filtered photodiode currents were merged with the standard radiosonde data of temperature, pressure, relative humidity, GPS position and flight time. The less rapidly obtained (at 2 s sampling) standard radiosonde data were linearly interpolated to give values coincident with those from the PANDORA data. Figure 3 shows the trajectories of the Lerwick and Reading balloons on 20 March 2015, derived from the standard GPS information. It is clear that the radiosondes’ altitudes during the maximum eclipse were above 10 km as planned. (Similar positional information was not available from Reykjavik, owing to a software problem, although the unfiltered photodiode data were still returned satisfactorily.) Figure 3. Details of balloon launches on 20 March 2015 from Reading ((a) flight trajectory in terms of longitude and latitude and (b) flight profile, with vertical height in km shown on a vertical axis) and Lerwick (as for (a) and (b), with trajectory (c) and profile (d)). On the profile plots (b) and (d), the points have been shaded according to the proportion of the eclipsed solar radiation measured at the same time, with black shading corresponding to the maximum obscuration and therefore the least radiation. (a) Lerwick Figure 4 shows measured data obtained at 1 s sampling from two Lerwick solar radiation soundings on the 20 March 2015, during the eclipse launch at 0858 UT (figure 4a–c), and in the afternoon after the eclipse (figure 4d–f) launched at 1500 UT. Figure 4a,d shows the vertical profiles of measured meteorological thermodynamic variables, including the dew point temperature Tdew. Tdew is equal to the local air temperature Tair, when the air is saturated, which is a good indicator of the presence of cloud. On this criterion, low cloud is evident in both ascents, and in the lowest 2 km of the eclipse ascent, consistent with visual reports from the site. Figure 4b,c,e,f shows the raw values of instantaneous currents measured by the two photodiodes carried. These also indicate low cloud from the reduction in photodiode current in this region, implying less solar radiation. Above this, the photodiode currents become more variable, dominated by the motion of the instrument package beneath the balloon carrying the sensors in and out of the direct solar beam. For the eclipse ascent, from 10 km to the burst height at 17 km, both photodiodes show steady reduction and then recovery in output current approximately symmetrically around 15 km, which is the effect of the solar eclipse. The solar radiation profiles shown in figure 4b,c during the eclipse show markedly reduced radiation compared with the measurements made later in the day (figure 4e,f). Figure 4. Vertical profiles of measurements obtained from the Lerwick soundings on 20 March at 0845 UT (a–c) and 1500 UT (d–f). These show: (a,d) thermodynamic data (air temperature Tair and dew point temperature Tdew), and instantaneous currents measured from (b,e) the spectrally filtered and (c,f) the spectrally unfiltered photodiodes. The variability apparent in the eclipse ascents (figure 4b,c) indicates that further data processing is needed for a comparison to be made with the calculations of ST given in figure 2. Because the orientation of the platform is not known, an exact correction for the alignment of the sensors with respect to the incoming solar beam cannot be made. Modest swing of the platform is usual, however, and this can be used to inform assumptions about the position of the sensors. The typical period of swing was found using a Fourier transform, by regarding the photodiode measurements as a time series. This value of approximately 10 s is consistent with that of a simple pendulum for a string length of 30 m (table 3), although the actual motion may be considerably more complicated than a simple pendulum in regions of atmospheric turbulence [9]. Table 3. Details of instrument package deployments. site launch time (UT) balloon mass (g) string length (m) median cycle time for swing (s) burst height (m) Reading 0848 200 30 9.9 17 360 Lerwick 0858 200 30 10.7 17 736 Reykjavik 0857 300 30 9.1 24 005 Figure 5 shows some possible exposure scenarios associated with the swing of the radiosonde and photodiode sensors. Figure 5a shows the arrangement of the instrument package beneath the balloon and position of the sensors on the upper surface of the instrument package. When hanging vertically (figure 5b), the position of the sensor surface is horizontal. This can then be compared with the calculation of ST for the same time, or solar zenith angle Z can be used to resolve the radiation measured to that occurring on a sensing surface normal to the solar beam. The position of the sensing surface is not known. However, if the photodiode is assumed to swing symmetrically, the photodiode will be exposed horizontally at the lowest point in the swing. Its exposure to solar radiation will increase as it swings into the solar beam, and reduce as it swings in the opposite direction. Averaging measurements obtained during several swing cycles can therefore provide an estimate of the radiation obtained horizontally, and a measure of the associated variability resulting from the swinging motion. Figure 5. Configuration of the instrumentation used for the solar radiation measurements. (a) Arrangement of the radiosonde beneath its helium-filled carrier balloon, with the photodiode sensors mounted on its upward facing surface. The radiosonde package is free to swing beneath the balloon. Geometry of the Sun and photodiode when the principal solar beam is directed at a zenith angle Z and the photodiode sensing surface is (b) horizontal and (c) normal to the solar beam. An alternative approach is suggested in figure 5c. During the pendulum-like motion of the instrument package, the greatest radiation value measured will be when the sensing surface swings normal to the solar beam. Clearly, depending on the solar elevation, the swing may not be of sufficient amplitude to bring the sensing surface normal to the beam and these conditions will only be approximately obtained. However, as the solar elevations approach the local noon, the maximum value measured during the swing will provide a better approximation to the direct beam radiation at normal incidence. Results from the two approaches of figure 5b,c are compared in figure 6, with figure 6a,b concerning the swing-averaged method and figure 6c,d concerning the swing-maximum method. For both methods, 1 min periods of the 1 s samples are calculated. This choice was informed by the median swing time of the instrument package (table 3), of approximately 10 s, which indicates that several complete cycles will usually be completed with a 1 min averaging time. Figure 6. Processed data from the Lerwick 20 March 2015 ascent, for the filtered photodiode, selected for times around the eclipse. (a) One minute averages of measured solar radiation data corrected by the solar zenith angle Z (points) plotted with the calculated top of atmosphere direct solar beam Sbcalc (line). (b) Comparison of the calculated direct beam (Sbcalc) and the data from (a), with a 1:1 dashed line added. (Error bars show 1.96 standard errors on the calculated mean value.) (c) Points show 95th percentile values chosen from 1 min of solar radiation data (S95), with Sbcalc (line), again compared directly (d) with Sbcalc with a 1:1 dashed line added. In figure 6a, average currents for the filtered photodiode around the eclipse time have been converted to solar radiation S using the linear regression found in the calibration experiment and corrected using cos Z at the same time to give the equivalent value normal to the solar beam. These values show a similar variation with time and similar magnitude to the calculated direct beam, Sbcalc, found as ST/cos Z. The quantities are compared directly in figure 6b, with the standard error on the 1 min mean used to provide an error estimate. There is increasing deviation for the larger radiation values, but values obtained are not inconsistent with the calculated values. To evaluate the swing-maximum method, the upper 95th percentile value of each 1 min of samples has been extracted (S95) and over-plotted on the time variation of ST/cos Z in figure 6c. The upper 95th percentile was used rather than the maximum value, in case the single maximum value recorded in the 1 min period was an outlier. Again, there is agreement in shape and magnitude. Figure 6d compares the values from this method with Sbcalc. No estimate of uncertainty is available as only one value can be obtained, but good agreement is nevertheless apparent between S95 and Sbcalc. (b) Reading A similar analysis to that for the Lerwick data is used for the sounding from Reading, again for the filtered photodiode sensor. Figure 7a,b shows the results for the swing-averaged methods, and figure 7c,d shows the results for the swing-maximum method. Both methods show agreement in shape with Sbcalc values, although the swing-average method slightly overestimates the radiation and the swing-maximum method underestimates it. As mentioned above, the swing-maximum method will underestimate the radiation if the swing amplitude is insufficient to bring the sensing surface normal to the solar beam direction. Figure 7. As for figure 6, but for the Reading ascent. (c) Reykjavik Owing to software difficulties, only measurements from the unfiltered photodiode sensor were obtained from the Reykjavik sounding. While a calibration is available for these sensors from the surface experiment, the wider spectral range of the unfiltered photodiodes matches the spectrum of the visible sunlight less closely. The broader spectral range, and the peak response at 920 nm brings with it the possibility that additional sources of near-infrared radiation may contribute to the measurement, or changes in the spectral composition of the radiation as a result of the eclipse [10]. The eclipse magnitude at Reykjavik is almost total (0.98), but there is still a finite current measured by the unfiltered photodiode, when very little current was observed by the filtered photodiode during the other sites’ local eclipse maxima. This is likely to be due to additional sources of near-infrared radiation as mentioned above, or the result of a spectral shift in the remaining solar radiation to this part of the spectrum where the unfiltered photodiode is particularly sensitive. As a correction to allow the shape of the response with time to be obtained, after applying the solar radiation calibration for the filtered photodiode, the offset current at maximum eclipse has been subtracted. Figure 8 shows the data obtained from the Reykjavik sounding. Figure 8a shows the thermodynamic data and the height variation with time. This suggests that the instruments were in, or close to, cloud as the maximum eclipse time was approached. Figure 8b shows the measured radiation following the procedure described above, using the swing-maximum method. While the absolute values cannot be regarded with the same confidence as for the Lerwick and Reading ascents, because of the presence of cloud and the correction procedure necessary, there is nevertheless agreement between the Sbcalc values and the equivalent solar radiation derived from the unfiltered photodiode. Figure 8. (a) Thermodynamic data from the Reykjavik sounding, showing profiles of air temperature (Tair) and dew point temperature (Tdew). Heights of the sounding against time are also plotted using + signs, with time given on the upper horizontal axis. (b) Measurements from the unfiltered photodiode during the eclipse (1 min mean values). Points show the 95th percentile value of solar radiation found from successive 1 min intervals containing 1 s samples (i.e. using the swing-maximum method), after subtracting an offset of 204.6 W m−2 at the time of the eclipse minimum. The calculated direct beam at the top of atmosphere is plotted as a line. (d) Spectral changes The different spectral responses of the unfiltered and filtered (visible light) photodiodes carried on the same instrument package can be investigated by comparing their measurements during the eclipse ascent. Figure 9a,c shows the photodiode currents obtained simultaneously plotted against each other, for Lerwick and Reading, respectively. Extrapolating the filtered photodiode response to zero current (i.e. when light in the visible spectrum would be absent) shows that a finite current would nevertheless be maintained at the unfiltered photodiode, as suggested by the current measured during the Reykjavik ascent at the eclipse maximum. Further broadband spectral information can be obtained by subtracting the current measured at the filtered photodiode (wavelength range 330–720 nm) from that of the unfiltered photodiode (wavelength range 320–1100 nm), yielding the response to radiation in the range 720–1100 nm, i.e. in the near IR. Figure 9b,d shows this near IR current as a fraction of that obtained by the unfiltered photodiode, as a function of time. This ratio changed with time, and during the maximum of the eclipse dropped by about 60% at Lerwick and about 40% at Reading. This indicates, at both sites, a relative spectral shift from the visible towards the near IR range of wavelengths, with the greater relative change at the location where the eclipse was the greater. Figure 9. Comparison of currents from the filtered (if) and unfiltered (iuf) photodiodes measured during the eclipse sounding for Lerwick (a,b) and Reading (c,d) using 1 min averages in each case. In (a,c), the currents obtained simultaneously from the two photodiodes on the same flight are plotted against each other; in (b,d), the ratios of the visible photodiode current (if) to the near-infrared current, found by differencing the photodiodes (iuf−if), are plotted against time for Lerwick and Reading. Such a spectral change can be expected from solar limb darkening, which causes the edge of the solar disc to appear darker and cooler. More limb darkening will occur at the site with the greatest eclipse, hence the proportional change in contribution of the near IR radiation will be greater at Lerwick than Reading, as observed. Previous calculations for 11 August 1999 indicated a change of 60% at 310 nm and 30% at 1500 nm, not inconsistent with the present observations [10]. 6. Conclusion The coordinated use of radiosondes carrying solar radiation detectors successfully provided measurements of the solar radiation changes caused by the same solar eclipse at three spatially separated locations. Because the eclipse provides a prescribed change in solar radiation that occurs more rapidly than the typical flight time of the radiosonde, the performance of the detectors in flight can be evaluated, which is not normally possible. In the soundings made from Reading and Lerwick, the measurements showed good agreement with a simple theoretical model of the expected changes. This encourages further use of the calculation method. Further, the agreement between model and measurements supports the use of unstabilized photodiode sensors on radiosondes for quantitative radiometry, using the swing-averaged method. In some circumstances when there is high solar elevation and appreciable swing, the swing-maximum method can provide an additional measurement, potentially independent of the swing-average method if the single swing-maximum value is removed prior to calculating the average. Finally, the simultaneous use of two photodiodes with different spectral responses on the same platform demonstrates the solar limb darkening effect. Clearly, a wider range of spectral responses could be combined in future eclipse balloon sounding experiments, or multiple narrow band sensors used simultaneously. Other future work in this area could include performing coordinated night-time radiosonde launches during lunar eclipses. It is believed that variations in the solar radiation that is reflected by the Moon during lunar eclipses have not previously been measured using radiosondes suspended from weather balloons. Lunar eclipses differ from solar eclipses in several important respects that would need to be taken into account. First, whereas solar eclipses such as the one measured herein are visible from only a relatively small fraction of the Earth’s surface, lunar eclipses are visible across the entire night side of the Earth. Second, lunar eclipses tend to be substantially longer in duration than solar eclipses. Finally, the radiation levels and their reductions during a lunar eclipse are much weaker than for a solar eclipse, indicating that more sensitive radiometers may be required. In this respect, a partial or total lunar eclipse would be more promising than a penumbral lunar eclipse, because the reduction in reflected solar radiation is greater. Supplementary Material Supplementary material Acknowledgements The UK Met Office provided essential logistical support for the balloon launches made by G.J.M. at Lerwick Observatory. Sibylle von Löwis led the Reykjavik launch and made the preliminary data analysis. Halldór Björnsson and Nína Petersen assisted with the Reykjavik launch. Figure 1 and table 1 use data provided by NASA at http://eclipse.gsfc.nasa.gov/SEgoogle/SEgoogle2001/SE2015Mar20Tgoogle.html. Data accessibility The data files for the eclipse soundings and the surface calibrations of the photodiodes are available from the University of Reading’s Research Data Archive at http://researchdata.reading.ac.uk/id/eprint/6. Authors' contributions R.G.H. directed this study, wrote software and analysed the data obtained and drafted the manuscript. G.J.M. undertook the Lerwick launches, and analysed data. P.D.W. and R.G.H. obtained support for the work and developed the Impact Opportunity to plan the fieldwork. All authors contributed to the final manuscript. Competing interests We declare we have no competing interests. Funding This work received funding from an NERC Impact Accelerator Award made by the University of Reading, which supported the technology interactions with the Icelandic Meteorological Office and the UK Met Office. ==== Refs References 1 Aplin KL , Scott CJ , Gray SL 2016 Atmospheric changes during solar eclipses . Proc. R. Soc. A 374 , 20150217 (10.1098/rsta.2015.0217 ) 2 Harrison RG , Nicoll KA , Lomas AG 2012 Programmable data acquisition system for research measurements from meteorological radiosondes . Rev. Sci. Instrum. 83 , 036106 (10.1063/1.3697717 )22462972 3 Nicoll KA , Harrison RG 2012 Balloon-borne disposable radiometer . Rev. Sci. Instrum. 83 , 025111 . (10.1063/1.3685252 )22380129 4 Harrison RG , Nicoll KA , Ulanowski Z , Mather TA 2010 Self-charging of the Eyjafjallajökull volcanic ash plume . Environ. Res. Lett. 5 , 024004 (10.1088/1748-9326/5/2/024004 ) 5 Muraleedharan PM , Nisha PG , Mohankumar K 2011 Effect of January 15, 2010 annular solar eclipse on meteorological parameters over Goa, India . J. Atmos. Sol.-Terr. Phys. 73 , 1988 –1998 . (10.1016/j.jastp.2011.06.003 ) 6 Satyanarayana M , Veerabuthiran S , Ramakrishna Rao D , Presennakumar B , Sreelatha P , Appu KS 2002 Solar eclipse induced changes in aerosol extinction profiles: a case study of 11 Aug. 1999 solar eclipse using LIDAR at a tropical station Trivandrum . Indian J. Radio Space Phys. 31 , 82 –87 . 7 Ridley EC , Dickinson RE , Roble RG , Rees MH 1984 Thermospheric response to the June 11 1983 solar eclipse . J. Geophys. Res. 89 , 7583 –7588 . (10.1029/JA089iA09p07583 ) 8 Aplin KL , Harrison RG 2003 Meteorological effects of the eclipse of 11 August 1999 in cloudy and clear conditions . Proc. R. Soc. Lond. A 459 , 353 –372 . (10.1098/rspa.2002.1042 ) 9 Marlton GJ , Harrison RG , Nicoll KA , Williams PD 2015 A balloon-borne accelerometer technique for measuring atmospheric turbulence . Rev. Sci. Instrum. 86 , 016109 (10.1063/1.4905529 )25638136 10 Koepke P , Reuder J , Schween J 2001 Spectral variation of the solar radiation during an eclipse . Meteorol. Z. 10 , 179 –186 . (10.1127/0941-2948/2001/0010-0179 )

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==== Front Philos Trans A Math Phys Eng SciPhilos Trans A Math Phys Eng SciRSTAroyptaPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences1364-503X1471-2962The Royal Society Publishing 2755076310.1098/rsta.2015.0222rsta201502221005127121000169ArticlesResearch ArticleOn the detection and attribution of gravity waves generated by the 20 March 2015 solar eclipse March 2015 Solar eclipse gravity waveshttp://orcid.org/0000-0002-8466-6779Marlton G. J. http://orcid.org/0000-0002-9713-9820Williams P. D. http://orcid.org/0000-0001-5580-6325Nicoll K. A. Department of Meteorology, University of Reading, Reading, UKe-mail: graeme.marlton@reading.ac.ukOne contribution of 16 to a theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. 28 9 2016 28 9 2016 374 2077 Theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’ compiled and edited by R. Giles Harrison and Edward Hanna201502224 1 2016 © 2016 The Authors.2016Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.Internal gravity waves are generated as adjustment radiation whenever a sudden change in forcing causes the atmosphere to depart from its large-scale balanced state. Such a forcing anomaly occurs during a solar eclipse, when the Moon’s shadow cools part of the Earth’s surface. The resulting atmospheric gravity waves are associated with pressure and temperature perturbations, which in principle are detectable both at the surface and aloft. In this study, surface pressure and temperature data from two UK sites at Reading and Lerwick are examined for eclipse-driven gravity wave perturbations during the 20 March 2015 solar eclipse over northwest Europe. Radiosonde wind data from the same two sites are also analysed using a moving parcel analysis method, to determine the periodicities of the waves aloft. On this occasion, the perturbations both at the surface and aloft are found not to be confidently attributable to eclipse-driven gravity waves. We conclude that the complex synoptic weather conditions over the UK at the time of this particular eclipse helped to mask any eclipse-driven gravity waves. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. eclipsegravity wavepressure perturbationradiosondeNERC studentNE/K500860Royal SocietyRG100661NERC Impact Accelerator AwardRoyal SocietyUF130571NERC Independent Research FellowshipNE/L011514/1cover-dateSeptember 28, 2016 ==== Body 1. Introduction During a solar eclipse, the Moon passes between the Earth and the Sun, causing a shadow to move across the Earth. The shadow causes a transient cooling in the Earth’s atmosphere of up to a few degrees Celsius along the path of the umbra, which is the region of the Earth that experiences a total eclipse. Within the umbra, the solar disc becomes completely covered for a period of a few minutes, blocking all solar radiation with the exception of that emitted from the Sun’s corona. A smaller reduction in solar radiation and temperature can also be observed within the penumbra, which is the area where a partial eclipse is experienced. An important consequence of the cooling effect of the Moon’s shadow during a solar eclipse was first hypothesized by Chimonas & Hines [1]. It was proposed that, as the Moon’s shadow moves at a supersonic speed through the Earth’s atmosphere, the associated cooling would cause internal gravity waves to propagate from the region of the shadow. Gravity waves are generated as adjustment radiation whenever a fluid departs from its large-scale balanced state [2–4]. Such a loss of balance will occur in the atmosphere when the horizontal temperature gradient suddenly changes due to the cooling during an eclipse. Simple analogies for this wave radiation process are the generation of surface gravity waves that form in the wake of a ship as it sails through the ocean, or the aerodynamic generation of acoustic waves that create sound as a plane flies through the air [5]. Chimonas [6] further developed the theory by predicting that the magnitude of the wave-induced pressure perturbations caused by an eclipse would be of magnitude 1 Pa at the Earth’s surface. A number of investigators have found evidence of eclipse-driven pressure changes using sensitive micro-barometers. Measurements during the 7 March 1970 solar eclipse across the USA revealed pressure perturbations with a dominant period of 89 min, together with weaker perturbations with periods in the range from 15 to 57 min [7]. Similar measurements were made from Mauritania during the transit of the 30 June 1973 total solar eclipse across Africa. However, owing to large pressure changes associated with the local weather, eclipse-induced pressure perturbations could not reliably be calculated in this case [8]. During the 23 October 1976 total solar eclipse in southern Australia, pressure perturbations with a magnitude of 0.1–0.2 Pa were observed with a period of 23 min [9]. Waves with periods of 4 h were measured during the 11 June 1983 solar eclipse over southeast Asia by making multiple coordinated observations spanning a continental geographical range [10]. During the 11 August 1999 total solar eclipse in the UK, pressure perturbations with a period of 35 min were observed, and spectral techniques were used to demonstrate that this specific wave period was unique to the eclipse [11]. Most recently, during the 29 March 2006 solar eclipse in Greece, oscillations with periods of 20–50 min were observed in the ozone layer by examining the ozone photolysis rates calculated from total column ozone measurements [12]. The ozone oscillations were similar to oscillations observed in temperature and humidity at the surface, suggesting a possible link between the surface and mid-level atmosphere during the eclipse. Despite the encouraging findings of most of the above studies, it must be remembered that eclipse-induced waves are not always evident [13]. Care should be taken to separate perturbations that are eclipse-driven from those that are associated with normal meteorological influences. Table 1 shows a selection of eclipse pressure perturbation studies made in the last 50 years. The factors shown are the time of day, the distance that observations were made from the umbra, whether or not disturbed meteorological conditions were present, and whether or not a pressure perturbation was reliably found. Although the list may not be comprehensive or objective, it does outline how varying weather conditions can lead to a null result being reported. Table 1. A list of previous eclipse perturbation experiments, with their observation distance, latitude of umbra nearest to observation, the presence of disturbed weather and indication as to whether a perturbation was observed. eclipse investigators observation distance from umbra (km) approximate local time of eclipse maximum nearest to observation latitude of total eclipse nearest to observation was disturbed weather present between the umbra and observation? perturbations observed? 7 March 1970 Anderson et al. [7] 20 1200 30°N yes possible 30 June 1973 Jones & Bogart [14] 10 1130 2°N no no 30 June 1973 Anderson & Keefer [8] 40 1100 20°N yes no 11 May 1975 Jones [15] 2500 0630 69°N yes no 23 October 1976 Goodwin & Hobson [9] 500 1600 38°S no yes 9 March 1999 Jones [16] 5000 1200 57°N yes no 11 August 1999 Farges et al. [17] 20 1100 47°N no yes 11 August 1999 Aplin & Harrison [11] 100 1100 47°N no yes 29 March 2006 Zerefos et al. [12] 100 1300 36°N no possible The present study examines temperature and pressure perturbations during the total solar eclipse that occurred over northwest Europe on 20 March 2015. The umbra tracked across the Atlantic and Arctic Oceans, where the only landmasses experiencing totality were the Faroe Islands, and Svalbard in the Arctic Circle. The penumbra, however, was experienced over most of northern Europe, with 85% totality across the British Isles and the Scandinavian Peninsula. Our study aims to examine whether gravity waves generated by the eclipse are detectable in surface temperature and pressure measurements from two sites in the UK: the Reading University Atmospheric Observatory (RUAO), which is located at 51.43° N, 0.93° W and experienced 85% totality, and the UK Met Office Lerwick Observatory, which is located at 60.13° N, 1.18° W on the Shetland Isles and experienced 97% totality. In addition, measurements above the surface are analysed from radiosonde balloons launched at the same two sites, to determine whether any eclipse-generated gravity waves are detectable in the upper atmosphere. 2. Methodology (a) Surface measurements At the Reading Observatory, surface temperature was measured using a 100 Ω platinum resistance thermometer that was located inside a Stevenson screen. In addition, surface pressure was measured using a Druck precision barometer that is sensitive to 1 Pa and is identical to that used by Aplin & Harrison [11]. At the Lerwick Observatory, surface temperature was measured using an H&B PRT100 and surface pressure was measured using a Vaisala PTB220 sensor with an uncertainty of 5 Pa. Surface temperature and pressure measurements from Reading and Lerwick were all averaged over durations of 1 min, to increase the signal-to-noise ratio. The data were truncated to examine the 3 h period centred on the time of maximum occlusion, which was approximately 0930 UTC. This time window was chosen based on previous experiments, which have identified that the majority of the relevant wave perturbations are recorded between 15 min and 1 h from the eclipse maximum [9,11]. To examine rapid fluctuations in the surface measurements, both pressure and temperature time series were detrended using a smoothing spline to remove any relatively slow background variability. To minimize tapering effects around the edges of the selected time window, the smoothing spline was fitted to 6 h of data surrounding the eclipse and was then truncated down to 3 h. The residual data were then smoothed using a 10-point moving Savitzky–Golay method similar to that used by Zerefos et al. [12]. To examine periodicities in the residual data, Lomb periodograms [18] were taken, which tolerate missing data points and produce statistical significance values for each peak in the periodogram. As discussed in §1, there may be other meteorological sources of gravity waves present. To attempt to determine whether any of the pressure perturbations detected are eclipse-driven, one can examine the wave propagation direction and speed to see whether any gravity waves are propagating away from the umbra. Information about the wave direction and speed can be calculated from the difference in the wind vectors between minimum and maximum pressure perturbations [19]. (b) Upper atmosphere measurements Given that the source of the gravity waves that are generated during an eclipse is in the upper atmosphere, and given that gravity waves propagate through the atmosphere, it may be possible to detect the gravity waves using radiosondes suspended from weather balloons. Such radiosondes have been used previously to investigate the properties of gravity waves in the troposphere and stratosphere using the temperature and horizontal wind component profiles [20,21]. Technological advances in the last 15 years have allowed radiosonde data to be archived at 1 s resolution. Therefore, vertical velocities can now be inferred from the radiosonde’s ascent speed and archived in addition to horizontal velocities. Vertical velocity variations in radiosonde profiles have previously been attributed to gravity waves [22] opening a complementary approach to observing gravity waves in the atmosphere. To give an example of our analysis methodology, figure 1 shows data from a previous radiosonde ascent that was made over mountainous terrain (not during an eclipse). The ascent velocity shows the presence of a mountain wave across the depth of the tropopause. Further gravity wave activity is evident in the lower stratosphere. The intrinsic angular frequency ω of a gravity wave [23] can be calculated using 2.1 where f is the Coriolis parameter, N is the Brunt–Väisälä frequency and α is given by 2.2 where x′, y′ and z′ are the three-dimensional displacements of an air parcel that is moving under the influence of the gravity wave. To a first approximation, the radiosonde can be considered to move as a passive air parcel, to which the following parcel displacement method analysis can be applied. To calculate the displacement perturbations from the radiosonde, the ascent speed and horizontal wind components are first smoothed to remove high-frequency instrumental noise. For this study, data spanning heights of 13–17 km are selected, as these were the heights at which maximum obscuration of the solar disc was observed by the radiosonde [24] and are above the nominal height of the tropopause in the mid-latitudes. Figure 1. (a) Temperature, (b) u and v wind components and (c) vertical ascent speed from a Vaisala RS92 radiosonde ascent made from the Mesospheric, Stratospheric and Tropospheric Radar site at Aberystwyth, Wales, UK, on 3 March 2015. A second-order polynomial was fitted to the u, v and w wind components to calculate the background velocities , and . As a sensitivity test, several different polynomial fits were tested, but these did not significantly change the outcome, in agreement with [21]. The background velocities and true velocities were then integrated over the selected height window to yield the mean displacements , and . Because the horizontal displacement since launch is irrelevant in this analysis, x and y were integrated from the launch site and z was integrated from a height of 13 km. The mean displacements were then subtracted from the true displacements to yield the displacement perturbations, x′, y′ and z′. In order to select the points at which to perform the analysis, local maxima along the variable S were chosen, where 2.3 This choice was made because the contributing displacement perturbation magnitudes will then sum together to yield the largest detectable perturbation of the wave. If random fluctuations had been added together instead, they would have been less likely to yield a maximum. Figure 2 shows the selection of peaks and the contributing displacement perturbations for one of the ascents from Lerwick on the day before the eclipse. In this case, a large gravity wave is dominant between 14 and 15 km, with weaker gravity waves above and below it. To ensure that the perturbations shown in figure 2 are not simply noise, lines have been placed across the individual displacements for each dimension at maxima of S. In the case of no gravity waves being present, the alignment of troughs and peaks would be random across all three displacement dimensions. Figure 2 demonstrates that for all maxima along S, at least two peaks of the displacement dimensions are in phase. In cases where a third is not in agreement, it is often 90° out of phase, adding more confidence that the radiosonde is detecting a gravity wave. Figure 2. (a) Longitudinal displacement perturbation x′, (b) latitudinal displacement perturbation y′, (c) vertical displacement perturbation z′, and (d) magnitude of perturbations for all dimensions S. In (d), crosses mark the places where the analysis is applied. Dashed lines have been added to illustrate how peaks and troughs in at least two axes contribute to the maxima in S. These data are from a 13 to 17 km height window from a radiosonde ascent from Lerwick Observatory on 19 March 2015 at 0845 UTC. Finally, N was calculated from the thermodynamic variables measured by the radiosonde over a 250 m height window using 2.4 Here, θ is the potential temperature, the over-bar denotes an average over the height window, and g is the acceleration due to gravity. N is a measure of static stability, with N2<0 indicating that the air is hydrostatically unstable, thereby removing the restoring force that is required for gravity-wave propagation. The characteristics of a monochromatic internal gravity wave can be inferred from a sounding by removing the background wind speeds and then plotting the horizontal velocity perturbations on a hodograph. For an ideal gravity wave, the hodograph would take the shape of an ellipse. By fitting an ellipse to an observational hodograph, the frequency of the gravity wave can be found. Specifically, the ratio of the major to minor axes of the fitted ellipse is proportional to ω/f [20]. This relationship allows the frequency of the gravity wave to be found from a hodograph if the Coriolis parameter is known. A disadvantage of this method is that one needs an almost complete ellipse to carry out the analysis. An advantage is that the wave propagation direction can be inferred from the orientation of the major axis of the ellipse, albeit with an 180° ambiguity [20]. Fortunately, this ambiguity can be resolved using wind and temperature data from the radiosonde. First, the velocity perturbation along the orientation of the major axis U′ is calculated. The temperature perturbation T′ is calculated in an identical method to the horizontal wind perturbations. For a gravity wave, T′ is ±90° out of phase with U′, hence by taking the vertical derivative of T′ the phase shift is removed and both quantities will have either the same or opposing signs. Hence, the sign of η can be used to deduce wave propagation, where 2.5 If the sign of η is positive (negative), then the wave propagates (anti) parallel to the positive bearing of the major ellipse axis [25], where the over-bar refers to spatial averaging over height. Wavelet transform techniques [26] have also been used to disentangle multiple coexisting gravity waves and allow information to be extracted about individual gravity waves. For the upper air data used here, ellipses are fitted only to complete ellipses observed in the hodographs. The thermal gradient is calculated over 100 m and U′ is sampled over the same height window. These are then averaged over the height range of the detected hodograph. The moving parcel method is a useful tool as it enables the frequency of inertia-gravity waves to be inferred even if there is an incomplete or partial ellipse observed on the hodograph. However, as the moving parcel method uses the relationship between the vertical and horizontal components, it cannot be used to calculate wave propagation direction. The aim is to combine the strengths of these two methods to reliably gather as much information as possible about the inertia-gravity waves present in the atmosphere. 3. Results The path of the 20 March 2015 solar eclipse transited across the North Atlantic Ocean as depicted in figure 3. The light grey shaded area indicates the path of the umbra, with the time of totality marked along the trajectory. Totality was experienced from 0908 UTC in the North Atlantic to 1020 UTC in the Arctic. At the Lerwick Observatory, 97% totality was experienced, with first contact at 0839 UTC and fourth contact at 1051 UTC. At RUAO, 88% totality was experienced, with first contact at 0824 UTC and fourth contact at 1040 UTC. In order to detect relatively weak perturbations in pressure and temperature caused by gravity waves, weather conditions would ideally be meteorologically quiet, because the passage of depressions and weather fronts can cause variations in temperature and pressure on hourly time scales. It is therefore imperative to begin by examining the synoptic weather conditions during the eclipse. Figure 3. Path of the Moon’s umbra over northwestern Europe during the 20 March 2015 solar eclipse. Times of totality are marked along the umbra’s trajectory. The Lerwick and Reading observatories are marked with L and R, respectively. (a) Synoptic conditions over the United Kingdom The surface pressure chart (figure 4) from the ECMWF ERA-Interim reanalysis [27] shows a large area of high pressure to the west of the UK, extending eastwards over central and southern UK. To the north, a low-pressure system moves zonally during the eclipse. Asterisks depict precipitation observed by automated weather stations, indicating frontal activity associated with the low-pressure system over northern England and Scotland during the course of the eclipse. Figure 5 shows the large amount of cloud associated with the system present over the northern UK. To the north-west of Scotland, cumulus rain showers can be seen, which are associated with the passing of a cold front. Over southern and central UK, a large swathe of stratiform cloud is present, which is associated with high pressure at this time of year. Finally, the visible satellite image shows the Moon’s umbra beginning to cross the Atlantic Ocean. In summary, the more complicated meteorological situation over Lerwick suggests that eclipse-induced wave phenomena may be less likely to be detected than at Reading, despite Lerwick being closer to totality. Figure 4. Surface pressure analysis over the UK at 0900 UTC on 20 March 2015 using ERA-Interim reanaylsis surface data. Black dots indicate automated weather stations where precipitation has been observed at the analysis time. Figure 5. Visible image from the Meteosat SEVIRI geostationary satellite taken at 0900 UTC over the UK on 20 March 2015. Courtesy of the NERC Satellite Receiving Station, Dundee University, Scotland. http://www.sat.dundee.ac.uk/. (b) Surface measurements at Reading For the entire duration of the solar eclipse, Reading was under the region of stratiform cloud that is shown in figure 5. This cloud is the cause of the low values of solar radiation that are shown in figure 6. Data from a Vaisala CL31 ceilometer in figure 7 show a cloud base height of around 250 m. Despite the presence of cloud cover, there is an obvious reduction of 20–30 W m−2 in solar radiation from 0900 to 1000 UTC during the eclipse, although this reduction would have been much larger in clear-sky conditions. Figure 6. Global solar radiation, Sg, observed using a Kipp and Zonen CM11 pyranometer at RUAO between 0700 and 1100 UTC on 20 March 2015. Figure 7. Cloud base recorded by Vaisala CL31 ceilometer at RUAO between 0700 and 1100 UTC on 20 March 2015. Figure 8 shows time series of surface temperature and pressure at Reading between the hours of 0830 and 1030 UTC. Figure 8a shows that the surface pressure decreased by about 0.7 hPa during the eclipse. Although the timing of the start of the pressure decrease coincides with the decrease in solar radiation during the eclipse, the pressure drop is probably not eclipse-induced but rather caused by the ridge of high pressure becoming less dominant. The atmospheric cooling effect of the eclipse can be seen in figure 8c, which shows a 0.3°C surface cooling during the course of the eclipse. The cooling started at about 0900 UTC, when the solar radiation began to drop. Figure 8. Surface measurements made from Reading during the eclipse on 20 March 2015. (a) Station pressure at 1 min resolution, where the smoothing spline is shown by the black line. (b) Detrended pressure data, where the black line indicates the Savitzky–Golay smoothing. (c) Dry bulb temperature, at 1 min resolution, where the smoothing spline is depicted by the black line. (d) Detrended temperature data, where the black line indicates the Savitzky–Golay smoothing. The corresponding detrended data points are shown in figure 8b,d. A Savitzky–Golay 10-point smoothing was applied, followed by a Lomb periodogram. Visual inspection indicates a 0.05°C drop in temperature between 0930 and 1000 UTC. This drop could be indicative of an eclipse-driven gravity wave, because a temperature change of this magnitude cannot be attributed to incoming solar radiation variability, which is minimal as shown in figures 6 and 7. Visual inspection indicates a wave period of approximately 30 min. In the pressure data, there are various wave forms in the residual data, and therefore a spectral analysis method is more appropriate. The Lomb periodogram of the detrended surface temperature data in figure 9b shows a significant peak at a period of about 35 min, in good agreement with our initial visual inspection of the time series. The detrended surface pressure also shows a peak at periods of 45–50 min. However, in order to determine whether or not these peaks are attributable to the eclipse, we must assess the likelihood of such perturbations occurring on a non-eclipse day. Therefore, a similar analysis was performed on data recorded at the same time of day on the days both immediately preceding and following the eclipse. Figure 9a,c shows Lomb periodograms of the detrended surface temperature and pressure data from 19 and 21 March, respectively. It can be seen that on 19 March there are peaks in the temperature and pressure in the period range 45–60 min. On 21 March, there is a temperature peak in the period range 30–60 min, but for pressure the dominant peak occurs at a period of 20 min. In figure 10b, compass plots show the direction of wave propagation calculated from pressure and wind information assuming every perturbation in pressure is related to a wave. On the eclipse day, there are a large proportion of detected waves propagating to the south, which could be eclipse-driven waves propagating away from the umbra. However, when examining the days surrounding the eclipse in figure 10a,c, where waves propagate in multiple directions, there is little confidence in exclusively attributing the waves to the eclipse. Therefore, for the surface measurements made at Reading during the eclipse, we are unable to distinguish the temperature and pressure perturbations from those caused by other meteorological phenomena. Figure 9. Lomb periodograms of the detrended temperature (solid) and pressure (dashed) for time series taken between 0800 UTC and 1100 UTC on (a) 19 March 2015, (b) 20 March 2015 and (c) 21 March 2015 at the RUAO. Figure 10. Compass plots showing wave speed (m s−1) and direction calculated using the difference of wind vectors at RUAO for 0800 to 1100 UTC on (a) 19 March 2015, (b) 20 March 2015 and (c) 21 March 2015. (c) Surface measurements at Lerwick A low-pressure system was passing over the Lerwick Observatory on 20 March (discussed in §3a), suggesting that it may be difficult to detect any eclipse-driven waves. Surface pressure and temperature from 0800 to 1100 UTC are shown in figure 11. From the surface temperature data, the onset of the solar eclipse is difficult to infer, because unlike in Reading (§3b) visual inspection indicates no obvious temperature anomaly. The surface pressure dropped by approximately 2 hPa during this period, which is attributable to the low-pressure system in the vicinity. In the residual pressure values shown in figure 11b, visual inspection indicates that a wave form could be present, but the reduced sensitivity of the barometer at Lerwick compared with the barometer at Reading makes the detection exercise more difficult. Figure 11. Same as figure 8, but for Lerwick. As in §3c, Lomb periodograms were constructed from the detrended surface pressure and temperature data collected at Lerwick for both 19 and 20 March, and are shown in figure 12a,b. The Lomb periodograms show temperature and pressure perturbations with periods of about 55–60 min during the eclipse. There is also a smaller peak at a period of approximately 30 min. For the non-eclipse day shown in figure 12b, there is a pressure perturbation peak at a period of approximately 30 min, indicating that there is no evidence to attribute the peak on eclipse day to the eclipse. There is a small peak at periods of about 60–90 min on 19 March, but the peak carries less statistical significance than the one detected on 20 March. Wave speed and direction were calculated for Lerwick between 0800 and 1100 UTC for both 19 and 20 March, as for Reading; however, for both days the derived values are random and do not show anything significant that would imply an eclipse-driven wave. The results are shown in the electronic supplementary material, figure S2. Figure 12. Lomb periodograms of the detrended temperature (solid) and pressure (dashed) for time series taken between 0800 and 1100 UTC at Lerwick Observatory on (a) 19 March 2015 and (b) 20 March 2015. (d) Upper atmospheric measurements Radiosonde launches made from the Lerwick and Reading observatories had reached the lower stratosphere when the eclipse was at its highest totality. The moving parcel analysis that was presented in §2b was performed on the data between heights of 13 and 17 km. At Reading, radiosondes were launched on the mornings of both 19 and 20 March. The period calculated from the moving parcel technique and hodographic technique is shown in figure 13a,b. As only two ascents were made, it is difficult to deduce whether the wave periods that were detected during the solar eclipse were caused by it. However, the periodicities that were deduced were typical of those of gravity waves in the lower stratosphere. Figure 13. Periodicities of internal gravity-wave activity between 13 and 17 km for radiosonde launches using the moving parcel method (circles) and the hodographic method (filled squares) from Reading at (a) 0845 UTC on 19 March 2015 and (b) 0845 UTC on 20 March 2015. At Lerwick, six radiosondes were launched over a 48 h period, being a mix of research and operational launches. Figure 14a–f presents time series of the radiosondes launched and the time periods derived from the moving parcel and hodographic analysis. A range of time periods is detected, with the majority similar to those of internal gravity waves. There is no evidence to suggest that the solar eclipse generated any distinctly different gravity-wave activity. The variability in the time periods for each ascent could be attributable simply to synoptic conditions and their interactions with the tropopause. During the ascent for the eclipse, only two complete ellipses were observed in the hodographs. Coupled with the large variability in propagation direction observed over the 48 h period, it is impossible to deduce whether the eclipse generated any gravity waves that were propagating away from the source of the eclipse. Propagation directions are shown in the electronic supplementary material, figures S3 and S4. Figure 14. Periodicities of internal gravity-wave activity between 13 and 17 km using the moving parcel method (circles) and the hodographic method (filled squares) for launches at: (a) 0852 UTC on 19 March 2015, (b) 1500 UTC on 19 March 2015, (c) 2300 UTC on 19 March 2015, (d) 0854 UTC on 20 March 2015, (e) 1100 UTC on 20 March 2015 and (f) 1500 UTC on 20 March 2015, all from Lerwick Observatory. Although there is in general good agreement in the periodicities derived by the two techniques of moving parcel and hodographic analysis, figures 13b and 14a show large differences. In both cases, the moving parcel method appears to underestimate the period when compared to that of the hodograph, which may be attributed to errors in the moving parcel calculation method (discussed in equations (2.1)–(2.4)). Specifically, in the calculation of S (equation (2.2)), vertical and horizontal displacements may be phase shifted by 90° meaning that the full extent of the vertical or horizontal displacements may not be accounted for. Secondly, the hodographic analysis only uses horizontal velocity perturbations, therefore neglecting that the vertical velocity information may affect the periodicities detected from that using the moving parcel analysis. Finally, differences may also occur due to the reliance of the hodographic analysis on the selection of complete ellipses, of which more occur on some flights than others. 4. Discussion (a) Surface measurements The results presented in §3b,c do not allow us to attribute any of the oscillations in surface pressure and temperature unambiguously to internal gravity waves generated as adjustment radiation in response to the cooling effect of the solar eclipse. At Reading, pressure and temperature perturbations were detected with periodicities of 30–55 min, which is similar to the periodicities observed in previous studies. A lack of variability in the cloud base height and solar radiation during the eclipse do suggest that the perturbations are not associated with weather systems. Wave propagation directions show little evidence to support exclusive eclipse-driven gravity waves at Reading. There may have been an eclipse-driven wave present, but it is impossible to detect it among other perturbations in pressure and temperature. In [9,11], spectral analyses were carried out at different times to see whether the detected perturbations were exclusive to the eclipse. A similar approach has been adopted here. We found that at Reading, similar perturbations were found on different days, leading to the conclusion that it would be difficult to distinguish eclipse-driven gravity waves from normal meteorological variability. A similar situation occurred at Lerwick, although the pressure and temperature perturbations are present in the eclipse day data and not in the other data. The large-scale synoptic and mesoscale conditions near Lerwick could have explained the pressure and temperature perturbations. For example, a passing rain shower is identified in the satellite image. The Lerwick Observatory is based on the eastern side of a mountainous island, meaning that a mountain wave could form as the airflow is forced upward over the island, and such a mountain wave would have similar periodicities to an eclipse-driven gravity wave. (b) Airborne measurements In §3d, the moving parcel and the hodographic techniques that were used to infer the periodicities of gravity waves in the lower stratosphere give time periods similar to those expected from the literature [23]. However, this technique did not detect gravity-wave periodicities during the eclipse that were significantly different from those detected during non-eclipse ascents. Furthermore, the hodographic direction technique did not resolve any eclipse-driven waves propagating away from the umbra at either site. Chimonas [6] theorized that the ozone layer would be the internal gravity-wave source, due to cooling from a reduction in ultraviolet radiation, although the author did not rule out other parts of the atmosphere being sensitive to a decrease in solar radiation. During the 2006 solar eclipse in Greece, Zerefos et al. [12] reported similar oscillations in the ozone layer and at the Earth’s surface. This similarity indicates that internal gravity waves are generated by the eclipse-induced cooling at both the surface and in the ozone layer, which are both parts of the atmosphere that are sensitive to solar irradiance. This feature also provides a possible explanation as to why eclipse-induced pressure perturbations were not detected at the surface sites in this study. At Reading, the magnitude of the solar radiation decrease during the eclipse was about 40 W m−2, which caused a small cooling of 0.3°C. When compared to the solar radiation change of 600 W m−2 recorded during the 1999 solar eclipse [11,12] and the temperature drop of approximately 3°C recorded during the 2006 solar eclipse in Greece, it is possible that during the 2015 eclipse there was insufficient cooling at the surface to cause such a bow wave. This theory can be extended to Lerwick, where the temperature and pressure perturbations at the surface were dominated by synoptic effects. Both the low-pressure systems at Lerwick and the blanket of low cloud over the southeast UK would count as disturbed weather. Other factors that could have affected the magnitude of the cooling are the time of day and year. During the August 1999 eclipse, the Sun’s zenith angle would have been lower and the eclipse was later in the day, causing larger cooling effects. In [7,9,12], pressure perturbations were observed at lower latitudes than the UK, which would also have appreciably reduced the solar zenith angle, further increasing the magnitude of the cooling effect. Sunrise is an extreme example of poor conditions in which to observe pressure perturbations during an eclipse. On 31 May 2003, an annular eclipse occurred over northern Scotland and the Arctic. The eclipse occurred near sunrise at 0400 UTC. A similar pressure sensor to the one that was used in the present study at Reading was deployed at Inverness. Figure 15 is a Lomb periodogram of detrended pressure over the 14 h following the annular eclipse. There are no statistically significant peaks in the spectrum, apart from that at 0.2 h−1, which is attributable to synoptic-scale weather. Figure 15. A Lomb periodogram of quadratically detrended data collected in the 14.5 h following the annular eclipse on 31 May 2003 (courtesy of Karen Aplin). Inadequate cooling near the surface could explain the absence of eclipse-induced pressure perturbations, but in the lower stratosphere there is less obscuration of solar radiation due to fewer clouds and less absorption and scattering. The lower stratosphere contains the ozone layer, which at high latitudes contains higher ozone concentrations at lower altitudes (15–20 km) [28]. This implies that a reduction in temperature could be experienced at this height during an eclipse. Muraleedharan et al. [29] showed temperature changes in the lower stratosphere; however, it is hard to attribute the changes due to the eclipse and not synoptic weather conditions which regulate tropopause height, and hence lower stratospheric temperatures. This would not negate internal gravity waves propagating downwards from higher up, whose amplitude may change in order to conserve energy. Given how the meteorological conditions in the troposphere can affect the tropopause, it could be likely that this could generate disturbances which could mask an eclipse-generated wave. It may also be a simple case that eclipse-driven internal waves are too subtle to be measured by the radiosonde’s GPS location system and pressure sensors. 5. Conclusion This study has found little substantial evidence to suggest that pressure and temperature perturbations caused by eclipse-induced gravity waves could have been present over the UK during the 20 March 2015 solar eclipse. Contributions from the weather conditions, time of day and geographical location all obscured the interpretation of the perturbations, making them difficult to distinguish from perturbations caused by normal synoptic-scale influences. In particular, insufficient cooling due to cloud cover and the time of year could be a major factor as to why distinctive pressure perturbations were not detected. The results agree with other studies seeking eclipse-induced gravity waves, such as [8] and those discussed in [13], which have encountered similar problems due to disturbed weather conditions. Further work might concentrate on making similar observations during a future solar eclipse. In particular, the solar eclipse of 21 August 2017 across the USA offers greater potential for detecting eclipse-induced gravity waves, because it will occur in the summer months at lower latitudes. In addition, a simple adjustment to the payload of the weather balloon could allow measurements to be made higher up in the atmosphere. This adjustment would improve the detection prospects for eclipse-induced internal gravity waves, because the density drop-off with increasing altitude causes wave amplitudes to grow quasi-exponentially with height in order to conserve kinetic energy. Finally, the moving parcel method used to derive frequencies could be further improved upon by a more comprehensive comparison with wind profiler observations of gravity waves with in situ measurements. Supplementary Material Supplementary plots and diagrams for : On the detection and attribution of gravity waves generated by the 20 March 2015 solar eclipse Acknowledgements University of Reading technicians set up the equipment and facilitated the radiosonde launches. Met Office staff at the Lerwick Observatory facilitated radiosonde launches and provided surface data. Karen Aplin of the University of Oxford provided the data for figure 15 and discussions relating to the data recorded during the 2003 annular eclipse, which was funded by the Royal Meteorological Society. Data accessibility The meteorological data for each radiosonde ascent and the surface measurements made from Reading are available from the University of Reading’s Research Data Archive at http://researchdata.reading.ac.uk/id/eprint/5. Surface and operational radiosonde data from the Lerwick Observatory are available from the Met Office on request. ERA-Interim surface pressure data are available from the ECMWF. Station precipitation data are obtained from http://www.ogimet.com/synops.phtml.en. Authors' contributions G.J.M. carried out the balloon launches from the Lerwick Observatory and performed the data analysis in the manuscript. P.D.W. obtained support for the work and developed the Impact Opportunity to plan the fieldwork. P.D.W. and K.A.N. contributed to discussions over techniques used to interpret the data. All authors contributed to the final manuscript. Competing interests We declare we have no competing interests. Funding G.J.M. is an NERC student under grant no. NE/K500860. The radiosonde equipment was funded by the Royal Society under grant no. RG100661. This work received funding from an NERC Impact Accelerator Award made by the University of Reading, which supported the technology interactions with the UK Met Office. P.D.W. is supported by a University Research Fellowship from the Royal Society under grant no. UF130571 and K.A.N. is supported by an NERC Independent Research Fellowship under grant no. NE/L011514/1. ==== Refs References 1 Chimonas G , Hines CO 1970 Atmospheric gravity waves induced by a solar eclipse . J. Geophys. Res. 75 , 875 (10.1029/JA075i004p00875 ) 2 Williams PD , Read PL , Haine TWN 2003 Spontaneous generation and impact of inertia–gravity waves in a stratified, two-layer shear flow . Geophys. Res. Lett. 30 , 2255 (10.1029/2003GL018498 ) 3 Williams PD , Haine TWN , Read PL 2005 On the generation mechanisms of short-scale unbalanced modes in rotating two-layer flows with vertical shear . J. Fluid Mech. 528 , 1 –22 . 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A 374 , 20150225 (10.1098/rsta.2015.0225 )27550768 25 Hamilton K 1991 Climatological statistics of stratospheric inertia-gravity waves deduced from historical rocketsonde wind and temperature data . J. Geophys. Res. 96 , 20 831 –20 839 . (10.1029/91JD02188 ) 26 Zink F , Vincent RA 2001 Wavelet analysis of stratospheric gravity wave packets over Macquarie Island: 1. Wave parameters . J. Geophys. Res. Atmos. 106 , 10275 –10288 . (10.1029/2000JD900847 ) 27 Dee DP et al. 2011 The ERA-Interim reanalysis: configuration and performance of the data assimilation system . Q. J. R. Meteorol. Soc. 137 , 553 –555 . (10.1002/qj.828 ) 28 Wallace JM , Hobbs PV 2006 Atmospheric science: an introductory survey , pp. 185 –186 . New York, NY : Academic Press . 29 Muraleedharan PM , Nisha PG , Mohankumar K 2011 Effect of January 15, 2010 annular solar eclipse on meteorological parameters over Goa, India . J. Atmos. Solar Terres. Phys. 73 , 1988 –1998 . (10.1016/j.jastp.2011.06.003 )

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==== Front Philos Trans A Math Phys Eng SciPhilos Trans A Math Phys Eng SciRSTAroyptaPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences1364-503X1471-2962The Royal Society Publishing 2755076110.1098/rsta.2015.0223rsta201502231005127121003193ArticlesResearch ArticleThe National Eclipse Weather Experiment: use and evaluation of a citizen science tool for schools outreach NEWEx: CS tool for schools' outreachhttp://orcid.org/0000-0001-9897-9832Portas Antonio M. http://orcid.org/0000-0001-9876-4612Barnard Luke http://orcid.org/0000-0001-6411-5649Scott Chris http://orcid.org/0000-0003-0693-347XHarrison R. Giles Department of Meteorology, University of Reading, Earley Gate, PO Box 243, Reading RG6 6BB, UKe-mail: a.portas@leedsbeckett.ac.ukOne contribution of 16 to a theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. 28 9 2016 28 9 2016 374 2077 Theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’ compiled and edited by R. Giles Harrison and Edward Hanna2015022323 5 2016 © 2016 The Authors.2016Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.The National Eclipse Weather Experiment (NEWEx) was a citizen science project for atmospheric data collection from the partial solar eclipse of 20 March 20. Its role as a tool for schools outreach is discussed here, in seeking to bridge the gap between self-identification with the role of a scientist and engagement with science, technology, engineering and mathematics subjects. (The science data generated have had other uses beyond this, explored elsewhere.) We describe the design of webforms for weather data collection, and the use of several external partners for the dissemination of the project nationwide. We estimate that up to 3500 pupils and teachers took part in this experiment, through the 127 schools postcodes identified in the data submission. Further analysis revealed that 43.3% of the schools were primary schools and 35.4% were secondary. In total, 96.3% of participants reported themselves as ‘captivated’ or ‘inspired’ by NEWEx. We also found that 60% of the schools that took part in the experiment lie within the highest quintiles of engagement with higher education, which emphasizes the need for the scientific community to be creative when using citizen science projects to target hard-to-reach audiences. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. citizen scienceschools outreache-sciencemeteorologyastrophysicssolar eclipsecover-dateSeptember 28, 2016 ==== Body 1. Introduction (a) Background On the morning of 20 March 2015, the Moon’s orbital path crossed in front of the Sun, casting a shadow over planet Earth. For this event, the UK was one of the few locations privileged to experience a significant partial eclipse. Eclipses have long stimulated the imagination of humankind, even though they are a well-understood consequence of Keplerian planetary motion. Although they have been thoroughly studied and their astronomical predictability has been known for centuries, questions remain over the consequences for the weather of the short-lived lunar shadow in the atmosphere. This astronomical event provided a novel opportunity to investigate some of these weather-related questions. Through involving schools across the UK to provide a huge source of observant young citizen scientists, we recognized that addressing the scientific questions could be combined with a strongly purposed science outreach activity. This combination of motivations provided the impetus for what became known as the National Eclipse Weather Experiment (NEWEx). Citizen science (CS) projects continue to bloom across the academic community, and a considerable body of literature now exists that focuses not only on the science outcomes but also on the experiences of the participating volunteers and scientists. Unarguably, the exponential growth of modern technologies has catalysed successful CS projects, such as those forming part of the Zooniverse (www.zooniverse.org) (e.g. Solar Stormwatch, www.solarstormwatch.com [1]) or Open Air Laboratories (www.opalexplorenature.org). These allow the use of websites or apps for data collection or analysis of large datasets, avoiding a specialized level of scientific knowledge yet still bringing tangible positive outcomes to those who get involved. For instance, the ISPEX project [2] developed and distributed a low-cost add-on for smartphones that converted them into spectropolarimetric instruments to obtain high-resolution maps of aerosol properties. Through a nationwide campaign on 8 July 2013, this resulted in roughly 6000 measurements of the concentration of aerosols in the atmosphere, when the weather forecast was favourable for the experiment. A central question remains as to what motivates volunteers, especially students and teachers, to take part in CS projects. A study conducted by Raddick et al. [3], under the Galaxy Zoo project, points to ‘contribution’ to a original scientific research as a major motivation to engage with this particular CS project to classify the morphology of galaxies obtained from large datasets. According to these authors, different citizen scientists will be driven by their own set of individual motivations, and more research is needed to shed light on the science learning outcomes, if any, gained by the contributing volunteers. On the other hand, a study conducted among the astronomy scientific community gives us some insights into scientists’ views on education and public outreach [4]. The authors of that study highlighted the fact that astronomers develop their scientific aptitude from a very early stage (often at primary school level), and therefore they see the benefits of exposing youngsters to science, technology, engineering and mathematics (STEM) related activities. The authors also point out that outreach is still seen by many peers as a hobby and it often lacks financial support from grants and policy-makers, alongside a lack of encouragement from senior staff within academic departments. Earlier familiarization with STEM subjects was also the topic of a recent report commissioned by the Women In Science and Engineering (WISE) organization under their campaign ‘People like me’ [5] (www.wisecampaign.org.uk/uploads/wise/files/not_for_people_like_me.pdf). The author explores reasons for the UK shortage of skilled workers in STEM, which reinforced the idea that more needs to be done to engage with schools-based audiences. This is especially so for those from under-represented backgrounds in higher education (HE) institutions. Changes in the HE landscape in England and Wales during the last decade translated into universities cementing their commitment to engage positively with their local communities, schools and colleges through outreach programmes, and, specifically, boosting the widening participation agenda (see [6] for a chronological summary). These programmes often extend down from the university at institutional level to individual departments. To do so, they rely heavily on the altruistic dedication of academics and postgraduate students, who see outreach and public engagement with science as a vehicle for dissemination of their own research, as well as a gateway to improve their communication skills. In contextualizing NEWEx within this ecosystem, we believe that this CS project encouraged those who took part to self-identify with the role of a scientist, as it was clearly capable of drawing in a wide profile of schools nationally, which would provide feedback about data collection, science outcomes and the legacy of the project. (b) Aims of the paper An assessment of the performance of the CS weather observations collected by volunteers for NEWEx is discussed by Barnard et al. [7] in this issue. In this paper, we focus on its use as a tool for schools outreach and reflect on the design of the data collection activity through the use of webforms. We consider particularly the outreach side of the project, especially where relevant for schools and colleges across the UK. We also discuss the dissemination of the experiment achieved by working alongside national platforms such as the BBC’s School Report, give an analysis of who took part in the experiment, and finish with a summary of recommendations potentially useful in undertaking future events of a similar nature. Section 2 is dedicated to the description of the design and implementation of data collection from the perspective of usability. In §3, we draw a profile of the schools that collected data during the experiment, and in §4, we explore the post-experiment feedback from users who had taken part in the experiment. Finally, in §5, we draw our conclusions, not only establishing a set of recommendations as to how similar weather data collection activities might be implemented for future eclipses, but also considering the impact of similar CS projects on school audiences. 2. Data collection for the National Eclipse Weather Experiment (a) Science considerations The major science motivation for this project was to investigate the effects of a substantial solar eclipse on the weather. This science activity effectively began with Clayton [8], who brought together weather measurements over a wide area during the US solar eclipse of 1901. Further advances were made from the dual-site work of Aplin & Harrison [9] made in cloudy and clear weather during the total solar eclipse of 11 August 1999. This study used high temporal resolution meteorological data to observe the short-term eclipse-related changes in temperature, wind speed, wind direction and cloud breakage from two meteorological sites in the UK, the Kehelland Met Office near Camborne, Cornwall, and the University of Reading Atmospheric Observatory. The authors found an eclipse-induced decrease in surface air temperature of up to 3°C in the clear conditions at Reading, and less than 1°C in the cloudy conditions in Cornwall. The effects on wind speed, wind direction and cloud breakage were rather less conclusive, although widespread public interest in the weather-related aspects of the topic was noted (www.newscientist.com/article/mg17623712-100-moons-shadow-stirs-up-eclipse-wind). Further analysis of the 1999 eclipse using a high-resolution weather forecasting model [10] indicated the need for a denser network of observations to advance understanding of wind speed and cloud effects. This led to the idea of using a CS approach to obtain meteorological parameters across the UK during the solar eclipse of 20 March 2015—NEWEx. In addition to the science motivation of acquiring a spatially widespread and dense dataset, NEWEx presented a unique opportunity to obtain measurements from a national CS project and the strong associated science outreach possibilities. The central aim behind NEWEx, as a CS experiment, was to encourage regular observation of simple meteorological parameters, using a webform for efficient reporting, which also allowed rapid analysis. Volunteers who took part in NEWEx were asked to collect information associated with variables similar to those previously explored by Aplin & Harrison [9]: temperature, wind speed, wind direction and cloud coverage. One of the main concerns was how to facilitate the simple measurement of these variables in order for the data to be of research use, while finding the best possible platform to collect these data on a national scale. These two factors had to be considered in the context of wide variability in the capabilities expected of the CS data collectors. Another consideration, which is more fully explored by Barnard et al. [7], was how to produce rapid and tangible outcomes from the data collected, to capitalize on the interest of schools and the general public. This was also expected to infuse the data collectors with a sense of ownership and positive contribution towards the project. This latter aspect was addressed by embedding analysis infrastructure from the outset, to provide plots and updated data on regular intervals of time on part of the University of Reading Department of Meteorology’s website. On the eclipse day, these plots made the front page of national news media outlets within hours of their release. (b) Designing the website for data collection The transient nature of the eclipse and the need to collect data across the entire UK argued strongly for the use of a webform, to provide a systematic, uniform and efficient collection tool. In the analysis of the total solar eclipse of 1999 [10], data values were used from the UK meteorological measurement network, which then amounted to 121 sites reporting hourly. Not all of these sites reported their data in a consistent way, which limited the analysis undertaken. Use of the webform permitted a greater density of rapid measurements. The advantages and disadvantages of collecting online data for research have been widely discussed previously [11]. The options for designing webforms lie across a spectrum, from an entirely custom design supported by a programmer, to the use of a standard tool supported on a wide variety of platforms by a major corporation. Because of the platform compatibility issue, and indeed cost, we decided to use Google Forms (www.google.co.uk/forms) to design our system, as this platform provided the necessary Web infrastructure required, and ultimately the capacity for an unknown number of users, which could possibly be very large. Google Forms also had an adequate level of adaptability needed for the basic data collection. For example, it allowed for different types of responses, such as regular text, multiple-choice entries and, among others, the ability to select an item from a list. The information required from the user was location, surface air temperature, cloud cover, wind force and wind direction, with the meteorological observations recorded at regular intervals. Location was entered via a postcode, as the exact measurement location was not needed, and provided some level of confidentiality. (The spatial aspects of the data are explored further by Barnard et al. [7].) The temperature information was expected to be obtained from a simple (liquid-in-glass or digital) thermometer, typically able to be read to a resolution of between 0.1°C and 0.5°C. The wind strength was to be categorized by Beaufort force, for which the standard descriptions were given, and the wind direction by a pull-down menu of eight compass directions. Cloud amount information was simplified into three categories of overcast, broken cloud and clear. In this way, the only instrumentation actually needed was a thermometer to measure the air temperature. Basic instructions on measuring air temperature in the shade were given, following the usual meteorological practice [12]. Table 1 summarizes the range and step size of each parameter recorded by the survey. Table 1. Data entries sought on NEWEx webform for data collection. The parameters used are presented, as well as the range of values employed and, when applicable, their step size. parameter range of values step size time 0800–0900; 1000–1100 15 min time 0900–1000 5 min temperature −10 to 20°C 0.5°C wind speed Beaufort Force 0–6 1 wind direction N–NE–E–SE–S–SW–W–NW n.a. cloudiness clear sky, some cloud, much cloud, overcast n.a. The webforms matured through two major iterations. At each stage, concerns existed over how to balance the mixed abilities of the users with the accuracy required from the data for scientific purposes. In the first iteration of the webform, generated about a month before the eclipse, the user was asked to enter the time of observation to a resolution of 1 min and then to fill in the temperature in degrees Celsius, rounded to the nearest 0.5°C, wind speed in miles per hour and wind direction, the latter chosen from a drop-down list of compass points. This first version was released internally among peers. Feedback made it very clear that, for more than one observation, the webform would have to be repopulated each time. Clearly, this presented a substantial risk that the users would just give up on the data entry, so an improvement was sought. Major changes were made and a second iteration of the webform was generated, designed to avoid burdening the citizen scientists with multiple webform submissions. This revised version, as shown in figure 1, was structured so that all the observations from one observer, for the entire eclipse, could be submitted in a single submission. To do this, the observations of each meteorological variable were discretized into a matrix of radio buttons, with the columns giving the meteorological parameter values, and the rows corresponding to different observation times. This meant that numerical values were not entered individually, but instead selected from available options. This had the additional benefit of preventing entries from being mis-keyed, reducing the error checking requirement and the associated loss of data. A complete transcript of the webform is available in the electronic supplementary material. Figure 1. Second and final version of the webform released to the public to allow users to record their entire observations with a single submission. (Online version in colour.) The Google Form was embedded in the University of Reading Department of Meteorology’s website. This increased traffic to the website and, with it, the profile of the institution. However, there was a fear that if large numbers of volunteers participated in submitting data via the webform (and there was no basis for estimating the take-up in advance), both the webform and the software produced to gather and analyse the data might fail. Therefore, it was important that the complete data submission and analysis system was tested beforehand with a large number of submissions. This was done by generating synthetic meteorological observations by 10 000 observers, which were then submitted via the webform automatically, over a few minutes, as further explained in [7]. This volume of data was significantly more than that expected to be received during the eclipse, and it was demonstrated that there was no difficulty in the complete NEWEx submission and analysis system processing these. After putting up the webpages of information about the forthcoming NEWEx activity, we handled the many ad hoc questions of how to enter data and what instruments were needed to acquire data, by producing a list of frequently asked questions on the same website. This provided a means to manage the enquiries effectively, particularly those around the type of instruments needed. Furthermore, the material was used to draw attention to important information about safe ways to observe a solar eclipse. (c) Dissemination methods adopted We marketed NEWEx through a multitude of communication vehicles, with the intention of national coverage, so as to get good spatial information on the transient phenomena expected in the atmosphere. To do this, we relied heavily on third parties, such as learned societies with distribution lists, partnerships with other institutions and direct engagement with the media. We also drew attention to the eclipse by publicizing a special in-house event. This was in the evening prior to the partial eclipse, for which we organized a series of lectures attended by 215 members of our local community. This brought together specialists not only to talk about the science but also to explore the folklore behind eclipses. This interdisciplinary approach brought together the science, history and arts associated with eclipses. Further details on the depiction of eclipses in art can be found in Blatchford in this issue [13]. For the eclipse morning itself, we sent out invitations to local schools to attend a solar eclipse event held on the Whiteknights campus of the University of Reading co-hosted by the Reading Astronomical Society (www.readingastro.org.uk), which provided a variety of telescopes and filters. Fifty-five students from both primary and secondary local schools attended this event alongside the majority of members of staff and postgraduate students of the Department of Meteorology. At the regional level, we made use of our partnerships with the South East Physics Network, the Institute of Physics and the Royal Meteorological Society, all of whom willingly disseminated the experiment among their contacts. A particularly fruitful collaboration arose from engagement with BBC Education, through their School Report (www.bbc.co.uk/schoolreport) project. This is a news report filmed and directed by school children for school children, in the past working with over 1000 schools in developing journalistic skills. This synergistic collaboration resulted in a special edition of School Report, with some of this paper’s authors being interviewed by local secondary school pupils (www.bbc.co.uk/schoolreport/31591588); the relationship that developed also led to contributions to the BBC Stargazing Live event held at Leicester Racecourse on the eclipse day, in which live regular updates from NEWEx were provided. Even though only 26% of the participants found out about NEWEx through media coverage (see §4 for further details), we reinforce the importance of the media as a vehicle for dissemination: from local radio interviews to influential national newspapers (www.theguardian.com/science/solar-eclipse, www.dailymail.co.uk/sciencetech/article-3003941/Did-feel-eerie-wind-solar-eclipse-Onlookers-report-wind-dropping-birds-going-silent.html) and television, the unexpected ability of NEWEx to raise media interest highlighted the broad interest in the topic. 3. Analysis of the data (a) Summary of National Eclipse Weather Experiment data collection Data submission for NEWEx began on the morning of the eclipse day (20 March 2015, a Friday) at around 7.30 GMT, with the last data entry a few days after the experiment on 27 March 2015. During this period, we received 503 webform submissions, 475 of which were submitted on the day of the eclipse, with the remainder submitted subsequently. The geographical location of each submission was determined from the participant’s postcode, which was converted by software to geographical longitude and latitude. Some multiple data entries were associated with the same postcode. We now focus on entries with postcodes matching school locations across the UK. (b) Data selection and validation During the first inspection of the 503 NEWEx data entries, incomplete and duplicate postcodes were sought and removed. To study the schools’ profiles, our approach was to keep the first entry per site and discard any subsequent duplicate entries with the same complete postcode. This reduced the sample to 271 individual full postcodes. (The accompanying publication by Barnard et al. [7], which assessed the performance of data collected by CS volunteers, presents greater numbers, as full postcodes were not needed to validate their data entries.) We discarded partial postcodes, because we could not match them with schools or non-schools postcodes as we categorize data for further analysis. The geographical distribution of the individual postcodes can be found in figure 2a, where they are divided into two groups, schools and non-schools, which is a distinction developed further in this paper. In table 2, we subdivided postcodes by region to highlight the fact that the schools that participated were not evenly distributed across the country. We found a higher concentration of schools postcodes from the South East (68 out of 127), followed by Scotland (39 out of 127). By contrast, we found fewer schools postcodes from Northern Ireland (2 out of 127) and Wales (6 out of 127). Figure 2. (a) Geographical distribution of postcodes associated with NEWEx data submission online for both schools postcodes (yellow squares) and non-schools postcodes (pink dots). (b) Distribution of postcodes associated with NEWEx data submission according to their quintiles of young participation with HE, also known as POLAR classification. (POLAR quintile 5 relates to the highest engagement postcodes, quintile 1 to the lowest.) Table 2. Distribution of complete postcodes by region, submitted during the NEWEx. Postcodes have been categorized as originating from schools or non-schools (as explored in §3). region schools non-schools both South East 28 (22.0%) 40 (27.8%) 68 (25.1%) Scotland 17 (13.4%) 22 (15.3%) 39 (14.4%) London 14 (11.0%) 4 (2.8%) 18 (6.6%) East Midlands 13 (10.2%) 10 (6.9%) 23 (8.5%) Yorkshire and The Humber 12 (9.4%) 5 (3.5%) 17 (6.3%) East of England 12 (9.4%) 15 (10.4%) 27 (10%) South West 12 (9.4%) 15 (10.4%) 27 (10%) North West 10 (7.9%) 8 (5.6%) 18 (6.6%) West Midlands 6 (4.7%) 11 (7.6%) 17 (6.3%) North East 2 (1.6%) 6 (4.2%) 8 (3%) Wales 1 (0.8%) 6 (4.2%) 7 (2.6%) Northern Ireland 0 (0.0%) 2 (1.4%) 2 (0.7%) total 127 (100%) 144 (100%) 271 (100%) (c) Demographics of contributing schools Postcodes from entries were checked with the Department for Education Edubase2 website (www.education.gov.uk/edubase/home), which holds information on educational establishments in England and Wales. When postcodes were found to be Scottish, we made use of the Scottish, Government equivalent online database (www.educationscotland.gov.uk/parentzone/myschool/findaschool/). We found that 127 (47.2%) of the postcodes submitted were associated with schools against 144 (52.8%) of the postcodes belonging to non-schools. Out of the 127 school postcodes, 55 belonged to schools identified as Primary (43.3%), and 45 to schools identified as Secondary (35.4%); for a further 27 establishments this distinction was not applicable (21.3%). Postcodes associated with schools were then analysed further, motivated by the widening participation agenda mentioned in the introduction of this paper. As mentioned above, HE institutions aim to become more diverse by seeking students from under-represented backgrounds. In the UK, every postcode is associated with a measurement of participation rates in HE (www.hefce.ac.uk/pubs/year/2012/201226/), also known as Participation of Local Areas (POLAR) classification. This database is maintained by the Higher Education Funding Council for England (HEFCE) and each individual postcode falls within one of five quintiles identified by POLAR. Areas with the least young participation rates fall within quintile 1 (POLAR 1) and those with the greatest young participation rates fall within quintile 5. Cross-referencing of the NEWEx postcodes with the POLAR data classification is presented in figure 2b. This shows that the engagement of schools with NEWEx came predominantly from those in the quintiles 3 to 5, who, following the definition of this category, already have high rates of participation with HE. Quintile 4 (24%) and quintile 5 (36%) together contribute 60% of the participating postcodes. 4. Feedback After the eclipse data collection itself was over, a further Google Form was devised and the link sent out to participants for feedback. (The questions asked are shown in the electronic supplementary material supporting this article.) The feedback form was divided into two sections. A first section contains general questions about the user, such as their location, category and overall experience. A further section was schools-related, as we wanted to unveil the impact and legacy of the project beyond the data collection and quasi-live results, as further explored by Barnard et al. [7]. The information obtained from this analysis was both quantitative and qualitative. A total of 31 responses were obtained between 27 March and 30 March. Twenty-seven respondents were identified as schools, two as general public and one as other. (a) Sample of survey The 27 feedback responses that identified themselves as schools constituted 22% of the original number of NEWEx schools postcode data. Nonetheless, only 20 of these could be matched with the postcode data collected during the eclipse. This means that only 16% of the schools submitting data during the eclipse responded to our post-eclipse survey. There is no doubt that such a discrepancy could be easily attributed to human input error or inconsistency between the location where observations were taken (within the vicinity of the school) compared with the actual postcode of the school. The much-reduced overall response suggests that the main commitment to the science activity was an important motivator in the original NEWEx participation. We can further speculate that seeking feedback nearly a week after the partial solar eclipse might also have reduced the number of returns. Nevertheless, we believe 22% to be a useful response level, and the very specific nature of the comments provided led us to consider them further. (b) Demographics We found that 37% of participating schools heard about the experiment via the Department of Meteorology’s website, 26% via media coverage and the remaining 37% through other routes. As for the age groups of the pupils involved in the experiment, we found that 41% were 11–14 years old (corresponding to Key Stage 3), and 26% of pupils were between 7 and 11 (Key Stage 2). We present both quantitative results in figure 3. When asked about the impression made on pupils by the activity, 96.3% of respondents were ‘captivated’ or ‘inspired’ by the NEWEx. Figure 3. Sources of information about the project (a) and age groups of pupils who collected data for NEWEx (b) according to the feedback survey. It is impossible to calculate the precise number of school students involved in the experiment, because we did not explicitly ask for specific numbers of CS volunteers involved in the experiment, but ranges instead. Our most conservative estimate (based on the ranges plus exact numbers provided by some schools) indicates between 577 and 775 pupils. We can only speculate about the total number of students involved nationwide in NEWEx, as to do so requires the assumption that the 22% of schools providing feedback provide a good statistical representation of the groups of schools participating. Extrapolating on this basis in the remaining 78% of schools that did not respond to our post-eclipse survey conservatively points towards the involvement of 2600–3500 pupils in NEWEx. The feedback survey also revealed important anecdotal feedback, which we quote below. Transcripts can be found in the electronic supplementary material to this article. Overall, pupils used their own data ‘to draw some line graphs’. One respondent pointed to the benefits of the availability of their own data: ‘We produced graphs of all the data we had collected every 2 minutes - temperature, pressure, humidity, wind speed - which allowed pupils to draw their own conclusions very quickly.’ In another context, pupils downloaded the maps released on the departmental website and explained any trends: ‘We looked at our location in particular and we tried to get the children to see if it tied-in with their raw data.’ (c) Usability of webform as a tool to collect data The feedback survey revealed that 92.6% of the respondents found data entry on the webform to be ‘easy’, with the remaining 7.4% responding ‘other’, which we will explore next. Only one of the respondents found it ‘really poor - could not see the time slots or criteria at the top of the page when I scrolled across to enter data?…’, suggesting that a freeze frame could be helpful to guide the user through the input table. Another respondent commented on data entry being easy, nonetheless ‘…we had extra info to do with pressure/humidity/data every 2 minutes so an “attach” option would have been good’. Indeed, some schools subsequently sent in their data by email to the Department of Meteorology directly in case it could be used for further analysis. In both cases, the nature of the comments reflects the limitations of the generic webform platforms rather than the way the data collection was designed. As mentioned in §2, with the second iteration of the webforms, we focused on fixing and sampling time intervals around the peak of the eclipse in order to streamline data entry, so we regard that process (of initial trial and revision) as having been rather successful. (d) Participation aspects of the experiment Participants were also invited to provide feedback on participating in the experiment. Overall we found positive feedback on the engagement with the CS project. ‘We enjoyed being part of this - even if the skies were full of cloud!’, reports back one of the participants. In fact, local weather may have dictated the engagement with the project because, when skies were clear, the astronomical phenomena became the principal interest: ‘We did end up giving up on the experiment - but only because the pupils being 10 years old struggled with the excitement of the eclipse and taking readings at the same time! This is through no fault of the way the experiment had been set up by yourselves. Everything was fully explained and clear to follow.’ Obviously, for many of the participants, this was probably the first eclipse they had experienced, and this would take precedence over the weather experiment. Nevertheless, if the eclipse was not visible at a site due to cloud, the eclipse occurrence could, at some sites, only have been evident from the temperature measurements. Interestingly, Barnard et al. [7] report that CS volunteers collected half of the data during the peak of the eclipse and the other half prior to and after the peak, which could be interpreted as symptomatic of a genuine interest in the science goals associated with NEWEx. Unfortunately, we cannot further speculate about the volume and frequency of data submitted against cloudiness in situ, which could shed some light on the most prevalent motivations of CS volunteers in terms of direct participation in science versus observation of natural phenomena. Revisiting the work of the Zooniverse paper [3] around motivations of volunteers who took part in Galaxy Zoo, ‘contribution’ towards original scientific research gathers 40% of responses. It was never a primary goal of our project to conduct such a thorough investigation on motivations behind participating in NEWEx. The study conducted in [3] made use of a robust Likert scale applied to a matrix of motivations; volunteers were asked not only to rank those, but also to choose the most important motivation. Our approach was qualitative, allowing respondents to provide additional comments on their involvement with NEWEx. Raddick et al. [3] emphasize the need to compare the motivations behind their Galaxy Zoo project with those of other CS projects. This could be seen as a challenge for future NEWEx- like experiments. We also revisit the idea mentioned in §1 on the need for the scientific community to expose school audiences to positive STEM-related activities from an early age to create a long-lasting impact and combat the shortage of STEM graduates in the UK. This was supported by some of the following comments: ‘Opening up the investigation to the public allowed children in our school to work on a real life situation, using equipment they were unfamiliar with, working as a team and interpreting data.’ One of the participants added that ‘…the experiment was a really good way of getting students excited about science and because it was real data collection for a real project, it gave them a taste of what being a scientist is really like’. Even though NEWEx facilitated a short-lived window of useful skills that scientists employ to conduct research, more needs to be done by practitioners to combat stereotypes associated with scientists and science, as discussed by MacDonald [5]. As the author further explains, in order to bridge the gap with an STEM identity, younger audiences need to be exposed to 10 different types of scientists (profiled in this study), all with unique skillsets beyond their academic knowledge. We like to think that NEWEx allowed volunteers to identify with the ‘investigator’, ‘explorer’ and ‘service provider’ profiles and that the work of MacDonald [5] will be of value when designing future CS projects, as it can help to engage with hard-to-reach audiences. How to include hard-to-reach audiences, such as POLAR schools belonging to quintiles 1 and 2 (both demographics add up to 16% of the overall schools who engaged with NEWEx), is a current and complex question among practitioners. Producing a rigid set of guidelines of proven effectiveness seems unachievable, as there are so many unforeseen and unexplored factors in nature versus nurture (e.g. parental engagement, school infrastructure, quality of teaching). In addition, an open question remains of how to deal with audiences that simply do not want to engage with STEM-related activities. Finally, we would like to point the reader to one apposite comment which summarizes the goals we set ourselves when we first devised NEWEx as a CS tool for schools outreach: ‘Our entire School participated, as we have a total of 38 children from age 5–11. Each child pretended to be scientists, astronomers and meteorologists! They actually were indeed “citizen scientists”, thanks to your outreach to the whole of the UK. This participation experience combined with the actual eclipse viewing really touched each of our students. We cannot thank you and the BBC enough for this incredible opportunity to learn, have fun, and see how wonderful it can be to connect with nature and science. We hope our session with the kids watching the eclipse and actually collecting data for your project, has planted at least one seed in the mind of a child that will inspire the next generation of eminent scientists in the UK! A heartfelt thanks to you all, and with our kindest regards.’ 5. Summary and recommendations In this paper, we have presented NEWEx as a CS tool for schools outreach, covering the issues of designing, facilitating and disseminating the collection of data through the use of online surveys or webforms. We have also explored the demographics of schools taking part in the CS project, together with their feedback about the experience. We summarize the highlights of our findings below: — A fundamental part of NEWEx was conveying the enthusiasm for the science opportunity in getting schools across the UK involved in weather data collection for the 20 March 2015 solar eclipse; Barnard et al. [7] report that half of the data submitted coincide with the peak of the eclipse, which can be seen as a genuine interest from volunteers to contribute to scientific research. — Postcode analyses mapped 47% of NEWEx submissions to schools. — Schools that participated were not evenly distributed across the country, with a high proportion (22%) coming from the South East. In total, 43.3% of schools were identified as primary, 35.4% as secondary and for the remaining 21.3% of schools this distinction was not applicable. — Some 60% of schools that took part in NEWEx were found to be situated in postcodes where the engagement levels with HE as classified by HEFCE falls within the two highest quintiles denoted POLAR 4 and 5. — Post-experiment feedback data indicated that 2600–3500 pupils and their teachers took part in this CS project. In total, 96.3% of the participants responding were ‘captivated’ or ‘inspired’ by NEWEX. — Anecdotal feedback shows a good level of satisfaction with the usage of the webform for data submission and tangible educational outcomes of the project, as teachers made the best usage of the data in their classroom. The following points should be seen as general recommendations for future NEWEx-like CS projects: — Webforms were found to be a reliable tool to use for national data collection. Careful webform design needs to take into consideration the wide abilities of the data collectors. Simplifying the data collection (e.g. fixing the times of the observations and minimizing the number of instruments necessary) were strong themes in our webform design. — Webforms associated with data gathering, should include a simple identification of the data collector (e.g. school, public, other). — Use of partner organizations was of extreme importance in engaging with a nationwide audience. The combination of local partners and national partners (particularly BBC Education’s School Report) catapulted NEWEx into the media and into schools. — In addition to questions that help draw the demographics of participating volunteers, feedback forms could include an in-depth motivation matrix survey to thoroughly understand what motivates volunteers to participate in CS projects. The popularity of CS projects has been increasing over the last decade and the evidence drawn from NEWEx here shows that they can play an important role in positively engaging students with science. We hope that our findings will be of great help not only to improve future NEWEx-like activities, but also to general outreach and public engagement practitioners. Supplementary Material NEWEx data submission and feedback webforms Supplementary Material NEWEx - postcodes and feedback data Acknowledgements The authors would like to thank first, and above all, all the anonymous data collectors who helped make NEWEx a huge success. Peter Gibbs from BBC Weather, and Angela Morrow and Pamela Lingham of BBC Education helped considerably with the national aspects. Pete Castle of the University of Reading Communications Office ably coordinated the many media approaches. The Director of Outreach and all of the Outreach Officers from SEPnet helped to disseminate the project. Finally the authors would also like to thank the anonymous referee for the constructive feedback provided. Data accessibility The datasets supporting this article have been uploaded as part of the electronic supplementary material. Authors' contributions A.M.P. drafted and analysed the data for the paper. A.M.P. and R.G.H. designed the NEWEx and feedback webforms. L.B. produced figure 3 and contributed drafting of §§2b and 3a. R.G.H. revised the final manuscript with contributions from all authors. Competing interests We have no competing interests. Funding We received no funding for this study. ==== Refs References 1 Barnard LM et al. 2012 The Solar Stormwatch CME catalogue: results from the first space weather citizen science project . Space Weather 12 , 657 –674 . (10.1002/2014SW001119 ) 2 Snik F et al. 2014 Mapping atmospheric aerosols with a citizen science network of smartphone spectropolarimetres . Geophys. Res. Lett. 41 , 7351 –7358 . (10.1002/2014GL061462 ) 3 Raddick MJ , Bracey G , Gay PL , Lintott CJ , Murray P , Schawinski K , Szalay AS , Vandenberg J 2010 Galaxy Zoo: exploring the motivations of citizen science volunteers . Astron. Educ. Rev. 9 , (10.3847/AER2009036 ) 4 Dang L , Russo P 2015 How astronomers view education and public outreach: an exploratory study . Commun. Astron. Public J. 18 , 16 –21 .See http://www.capjournal.org/issues/18/18_16.pdf 5 MacDonald A 2014 ‘Not for people like me?’ Under-represented groups in science, technology and engineering. See https://www.wisecampaign.org.uk/uploads/wise/files/not_for_people_like_me.pdf . 6 Lewis B 2002 Widening participation in higher education: the HEFCE perspective on policy and progress . Higher Educ. Q. 56 , 204 –219 . (10.1111/1468-2273.00212 ) 7 Barnard L , Portas AM , Gray SL , Harrison RG 2016 The National Eclipse Weather Experiment: an assessment of citizen scientist weather observations . Phil. Trans. R. Soc. A 374 , 20150220 (10.1098/rsta.2015.0220 )27550767 8 Clayton HH 1901 The eclipse cyclone and the diurnal cyclones . Ann. Astron. Observ. Harvard College 43 , 5 –33 . 9 Aplin KL , Harrison RG 2003 Meteorological effects of the eclipse of 11 August 1999 in cloudy and clear conditions . Proc. R. Soc. Lond. A 459 , 353 –372 . (10.1098/rspa.2002.1042 ) 10 Gray SL , Harrison RG 2012 Diagnosing eclipse-induced wind changes . Proc. R. Soc. A 468 , 1839 –1850 . (10.1098/rspa.2012.0007 ) 11 Wright KB 2005 Researching internet-based populations: advantages and disadvantages of online survey research, online questionnaire authoring software packages, and web survey services . J. Comput.-Mediat. Commun. 10 (10.1111/j.1083-6101.2005.tb00259.x ) 12 Harrison RG 2014 Meteorological measurements and instrumentation , 1st edn Chichester, UK: John Wiley & Sons. 13 Blatchford I 2016 Symbolism and discovery: eclipses in art . Phil. Trans. R. Soc. A 374 , 20150211 (10.1098/rsta.2015.0211 )27550758

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==== Front Philos Trans A Math Phys Eng SciPhilos Trans A Math Phys Eng SciRSTAroyptaPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences1364-503X1471-2962The Royal Society Publishing 2755075910.1098/rsta.2015.0224rsta20150224100512712ArticlesResearch ArticleEclipse-induced wind changes over the British Isles on the 20 March 2015 Eclipse-induced wind changeshttp://orcid.org/0000-0001-8658-362XGray S. L. http://orcid.org/0000-0003-0693-347XHarrison R. G. Department of Meteorology, University of Reading, PO Box 243, Reading RG6 6BB, UKe-mail: s.l.gray@reading.ac.ukOne contribution of 16 to a theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. 28 9 2016 28 9 2016 374 2077 Theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’ compiled and edited by R. Giles Harrison and Edward Hanna2015022429 3 2016 © 2016 The Authors.2016Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.The British Isles benefits from dense meteorological observation networks, enabling insights into the still-unresolved effects of solar eclipse events on the near-surface wind field. The near-surface effects of the solar eclipse of 20 March 2015 are derived through comparison of output from the Met Office’s operational weather forecast model (which is ignorant of the eclipse) with data from two meteorological networks: the Met Office’s land surface station (MIDAS) network and a roadside measurement network operated by Vaisala. Synoptic-evolution relative calculations reveal the cooling and increase in relative humidity almost universally attributed to eclipse events. In addition, a slackening of wind speeds by up to about 2 knots in already weak winds and backing in wind direction of about 20° under clear skies across middle England are attributed to the eclipse event. The slackening of wind speed is consistent with the previously reported boundary layer stabilization during eclipse events. Wind direction changes have previously been attributed to a large-scale ‘eclipse-induced cold-cored cyclone’, mountain slope flows, and changes in the strength of sea breezes. A new explanation is proposed here by analogy with nocturnal wind changes at sunset and shown to predict direction changes consistent with those observed. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. meteorologyeclipsemeasurementsnocturnal jetcover-dateSeptember 28, 2016 ==== Body 1. Introduction Solar eclipse events cause a unique natural perturbation to the Earth’s atmospheric system. After the effects on solar radiation, humankind perceives solar eclipses most obviously through their effects on the near-surface atmospheric conditions: namely temperature, relative humidity (RH), and wind speed and direction. Beyond their importance as a scientific curiosity of nature, these changes can give rise to socio-economic impacts. For example, an eclipse in Svalbard led to the formation of fog that grounded air traffic [1] and the reduction of solar radiation and commonly observed reduction in near-surface wind speeds can both negatively impact the generation of renewable energy. The cooling and increases in RH attributable to eclipses are well documented. By contrast, there is less consensus on induced changes in circulation. The purpose of this study is to investigate the meteorological responses to the solar eclipse of 20 March 2015 over the British Isles with a particular emphasis on wind speed and direction. The band of totality for this eclipse was to the north of the British Isles with obscuration over the British Isles ranging from 83% (at Dover on the southeast English coast) to 98% (at Stornoway in the Scottish Outer Hebrides). Times of First contact, maximum eclipse and Fourth contact were 0825, 0932 and 1042 UTC, respectively at Dover and 0832, 0936 and 1043 UTC, respectively at Stornoway. A review of atmospheric changes from solar eclipses which includes effects on the surface temperature and circulation is presented in [2]. Cooling of several degrees Celsius typically occurs with the magnitude dependent on the time of day, season, extent of the eclipse (if partial) and cloud conditions. The peak cooling lags the time of maximum eclipse (if a partial eclipse) or totality (if a total eclipse) by 15–30 min. Relative humidity changes are typically anti-correlated with air temperature changes and increase directly as a consequence of the cooling during eclipses. For example, a 20% increase over a plant canopy in Thiruvananthapuram, India, was observed during the 2010 annular eclipse (92% obscuration) associated with a 4°C drop in air temperature [3]. A reduction of specific humidity has also been reported and attributed to eclipse-induced subsidence of drier air [4]. A reduction in surface wind speed during eclipse events has commonly been reported and related to the characteristic stabilization of the near-surface boundary layer that occurs after sunset (e.g. [2,5–7]). By contrast, Eaton et al. [8] did not observe changes in wind components that exceeded natural variability, although a reduction in the variance of the wind speed was observed. Some studies have also reported sudden increases in wind speeds or gusts at the times of First and Fourth contact of the eclipse [2,9]. These may be due to downwards turbulent mixing from a jet forming above the eclipse-induced inversion (following the mechanism responsible for the formation of the nocturnal jet) [7] or atmospheric pressure changes associated with the eclipse [10]. Changes in wind direction have also been attributed to eclipse events although there is little consistency in type of change or attributed cause. H. H. Clayton was the first to propose (in 1901) that total eclipses modified the atmospheric circulation [11]. He observed a cold-cored anticyclonic circulation developed around the centre of the eclipse, extending outwards to approximately 1500 miles from the umbra. Beyond this, he observed a cyclonic circulation extending a further 1000 miles to the edge of the penumbra. Clayton attributed this cyclone to the relatively small cooling in the ‘body of the atmosphere’ [10]. The existence or otherwise of Clayton’s ‘eclipse cyclone’ was the subject of debate both at the time of the eclipse (see comment [12] and Clayton’s response [13]) and more recently. As described by Alpin et al. [2], some evidence consistent with the existence of of ‘eclipse cyclone’ has been described by several observational and modelling studies [14–16]. Other studies have also reported wind direction changes during eclipse events [5,6,17] but attributed them to synoptic evolution and/or local changes in mesoscale circulations such as sea breezes or mountain slope flows. Determination of eclipse-induced meteorology changes requires a best estimate of how conditions would have evolved in the absence of the eclipse event. Estimating this evolution is a challenge; weather conditions change daily and evolve during the period of the eclipse event due to diurnal variations and synoptic-scale changes (e.g. the passage of fronts). In a previous paper [14], we diagnosed wind changes induced by the eclipse on 11 August 1999 through comparing measurements from a network of surface stations operated by the Met Office across the UK with the output of a high spatial resolution operational forecast model ignorant of the eclipse. Focusing on an inland cloud-free region (containing many measuring sites), a mean regional wind speed decrease of 0.7 m s−1 (1.9 knots ≡ 1 m s−1) and backing in wind direction (anticlockwise turning in the direction the air is going towards) of 17° during the maximum eclipse hour were diagnosed. We take the same approach here to diagnose synoptic-evolution and diurnal evolution relative eclipse changes for the 20 March 2015 eclipse. Compared with the previous study of the 1999 eclipse, vastly more data are now available; we aim here to exploit this as fully as possible. Hourly measurements from two independent surface station networks (Met Office land surface stations and a network of roadside stations used for monitoring road conditions) are compared with operational output from the Met Office weather forecast model (which did not include code to represent the eclipse). Motivated by signals in the synoptic-evolution relative changes, high temporal resolution (1-min and 20-min data) observational timeseries from selected regions are then presented to focus on the variability in these regions. The remainder of this paper is structured as followed. An overview of the synoptic situation is given in §2. The datasets used are described in §3 beginning with observational datasets (the Met Office Integrated Data Archive System (MIDAS) land and marine surface stations dataset and Vaisala roadside dataset) and followed by the operational forecast model output. The results (§4) are presented in three subsections: §§4a and 4b present the synoptic-evolution relative eclipse-induced effects on near-surface atmospheric fields deduced from the MIDAS and roadside stations, respectively; §4c presents 1-min and 20-min temporal resolution timeseries of the observational data. Throughout §4, there is a focus on the wind fields, with temperature and RH shown primarily to demonstrate consistency between the different datasets and with previous studies on eclipse effects. Section 5 summarizes the findings and considers a new explanation for the observed wind direction changes and §6 presents some conclusions. 2. Synoptic overview The weather situation on 20 March 2015 over the British Isles was generally cloudy with weak near-surface winds (typically less than 10 knots over England and Wales). The centre of a weak low pressure system tracked southeastwards during the morning from east of Iceland to the Scandinavian coast (figure 1a,c). The trailing cold front from this system cut across the British Isles and moved southwards during the morning. An upper-level cold front is marked in figure 1a,c to the south and east of the surface cold front at both 0600 and 1200 UTC on the surface analyses and a broad high pressure region existed to the south and west of the British Isles. The associated geostrophic surface winds can be inferred from the isobars marked on the surface analyses and were northwesterly over Scotland, Wales, Ireland and northern England and northeasterly over southern England and the Republic of Ireland at 0600 UTC but had turned more northerly by 1200 UTC. The winds were weak (inferred from the slack pressure gradients), especially to the south of the British Isles. This synoptic situation led to low-level cloud over most of the British Isles, with the exception of a clear sky band well to the south of the surface cold front (figure 1b); this zone provided good eclipse viewing conditions. At the time of the eclipse this band stretched across the Midlands from the county of Lincolnshire on the east coast and covered Wales and the county of Cornwall in southwest England. The calm meteorological conditions in the majority of the British Isles provided an opportunity to investigate possible eclipse-induced changes in surface weather data. Figure 1. (a) Met Office surface analysis at 0600 UTC, (b) infra-red satellite image at 0922 UTC and (c) Met Office surface analysis at 1200 UTC. All for 20 March 2015. Surface analyses are © Crown copyright. Satellite image is courtesy of Dundee Satellite Receiving Station. 3. Datasets (a) Observations Two observational datasets are used in this study: (i) the MIDAS surface stations dataset and (ii) measurements from a network of roadside stations operated by Vaisala for monitoring road conditions. The locations of stations from each dataset (specifically those stations with temperature observations available at 1200 UTC on 20 March 2015) are shown in figure 2. The MIDAS dataset contains land and marine surface observations from the Met Office station network across the British Isles and from other Met Office stations worldwide [18]. Hourly weather observation MIDAS data were extracted across the British Isles from the British Atmospheric Data Centre (BADC). The weather station types and message reports extracted were the same as in [14] and the same checking of quality flags was performed. Quality flags indicate the automated processing that has been performed on each measurement and whether the measurement has failed any checks. Data from 331 stations distributed across the British Isles were extracted and data were typically available (i.e. present in the station records) from approximately 280 stations for temperature and 220 stations for cloud and wind at the times analysed. Wind speed and direction (at 10 m height) and air temperature (at 1.25 m height) were analysed with data reported to 1 knot, 10 degrees and 0.1°C resolution, respectively. Wind speeds and directions are 10-min averages obtained during 20 min to 10 min prior to the reported observation hour. Wind direction observations are undefined when the wind speed is zero. It is UK practice to regard the actual observation time as 10 min prior to the observation hour; however, observations are assumed to apply to the observation hour in the analysis that follows. In addition to the hourly MIDAS data downloaded from BADC, 1-min temporal resolution data for wind speed and direction from the MIDAS stations were obtained directly from the Met Office. These data did not include quality flags. Figure 2. Locations of observational stations where temperature data are available at 1200 UTC on 20 March 2015 from (a) the MIDAS dataset and (b) the Vaisala roadside dataset. Magenta, black, green and red boxes in both panels mark the ‘Central southern England’, ‘Wales’, ‘Midlands1’ and ‘Midlands2’ regions, respectively, as specified in table 1. The roadside observations were obtained courtesy of Vaisala, a company that develops, manufactures and markets products and services for environmental and industrial measurement. Vaisala operates on behalf of national agencies and local authorities a dense network of stations situated along the major UK highways. The stations vary in the types of measurements made and the frequency and timing of measurements (specifications for the Vaisala Road Weather Station RWS200 can be found in the product catalogue [19]) but hourly data for air temperature were provided from 868 stations across the UK. Data values were typically available from approximately 740, 610 and 590 stations for air temperature, wind speed and wind direction, respectively, for each time analysed. The data values do not include quality flags but come from standardized commercial products which are subject to regular calibration and maintenance to ensure validity. Although the siting of the roadside stations is constrained by the UK road network, the majority of stations lie in relatively exposed locations away from vegetation, buildings and cuttings in order to maximize sky view factor (sky view factor is one of the main parameters affecting the behaviour of road surface temperature), reduce adverse effects on wind speed and direction, air temperature and humidity readings, and to reduce shading on the road temperature sensors particularly in low sun conditions. The aim is that the stations are sited in locations that are representative of the climatic region they represent, after allowing for power supplies and the ability to operate safely. The potential lack of representivity (for this study) arising from stations being sited according to the road network is balanced against the benefits of the very large number of stations. Almost all of the air temperature sensors are located at approximately 3.5 m above the ground with some of the wind instruments also located at this level. However, a large proportion of the wind instruments are located at the top of the roadside mast at approximately 4 m. No height corrections to the measured wind speeds are made in the data that was available. Air temperature and wind speed and direction were extracted at both hourly (whole UK) and 20-min (selected regions) intervals for this study; although greater temporal resolution data were available for some stations, the use of 20-min data provided the greatest number of stations operating at consistent temporal resolution. Temperature was reported to 0.1°C, wind speed to 0.1 m s−1 and direction to 1°. (b) Numerical model forecast The evolution of the meteorological variables expected in the absence of the eclipse was determined using numerical model output from an operational weather forecast produced by the Met Office following the methodology of [14]. The Met Office routinely performs weather forecasts over both the whole globe and limited-area domains initialized several times each day. Different configurations of the same Met Office model, the Unified Model, are used for both weather forecasting and climate prediction. The Unified Model is an operational finite-difference model that solves the non-hydrostatic deep-atmosphere dynamical equations with a semi-implicit, semi-Lagrangian integration scheme [20]. The model includes full representation of physical processes through parametrization schemes. In the limited area configuration, the horizontal grid is rotated in latitude/longitude to yield an approximately isotropic grid measured by Euclidean distance. The forecast used was produced by the UK variable resolution (UKV) configuration of the model [21] with an initialization time of 0300 UTC on 20 March 2015; this forecast was chosen as the latest forecast initialized before the onset of the eclipse. The UKV model configuration has a domain that extends over the British Isles and part of northern France. The grid spacing is 1.5 km in the inner domain, reducing to 4 km in a rim extending around the outer edges. There are 70 vertical levels on a staggered stretched grid extending up to approximately 70 km altitude; the lowest model levels on which temperature and horizontal wind components are held are at 5 and 2.5 m height (above the terrain), respectively. This model configuration is run operationally four times each day (initialized at 0300, 0900, 1500 and 2100 UTC using an incremental 3D-Var data assimilation scheme) out to 36 h [21]. Most model fields are output at hourly intervals including the 2-m temperature, 2-m RH and 10-m wind components used in this study. The boundary conditions for the model come from the global model forecast which runs with coarser resolution (17-km grid spacing). The operational version of the model does not include representation of eclipses in the model code and hence the forecast produced reveals how the atmospheric state would have evolved in the absence of the eclipse. The effects of model, initial condition and boundary condition errors are assumed to be small (relative to eclipse-induced effects) given the short lead time of the forecast used. 4. Results (a) Synoptic-evolution relative eclipse-induced anomalies deduced using MIDAS network observations The cloud, 10-m wind and 2-m temperature conditions before (0800 UTC), during (1000 UTC) and after (1200 UTC) the eclipse are plotted at the locations of the MIDAS stations in figure 3 and in figure 4a,c,e. The eclipse maximum response in atmospheric near-surface fields generally lags the maximum eclipse time (e.g. the maximum eclipse-induced temperature anomaly lags the maximum eclipse by approx. 15 min [15]). Hence, 1000 UTC is chosen to illustrate the eclipse-induced changes as this is the first available hourly data after the maximum eclipse. Data are plotted at all station points where it is available at the given times. The cloud and wind conditions (figure 3) can be compared with those inferred from the satellite imagery and surface analyses, respectively, shown in figure 1. The clear sky band across the Midlands, Wales and Cornwall at 1000 UTC is evident, with stations in this zone reporting cloud cover in the range 0–2 oktas. By 1200 UTC this band has moved slightly south and is now located in central southern England. The direction and relative strength of the 10-m wind vectors are generally consistent with the geostrophic winds inferred from the isobars in the surface analyses and are very weak in inland southern England (typical speed is less than 5 knots). At 0800 UTC temperatures to the north of the British Isles are warmer than those to the south (typically 6–8°C in the north and 4–6°C in the south, figure 4a, likely to be a result of less cloudy skies overnight to the south resulting in lower temperature minima there). The diurnal cycle is the dominant cause of the change in temperature during the morning (figure 4a–c) and by 1200 UTC temperatures reach up to 12–14°C in central and northeast England. Figure 3. (a,c,e) Total cloud cover amount at MIDAS stations (oktas) and (b,d,f) 10-m wind vectors at MIDAS stations (with scale indicated by representative length in the upper-left of each plot) at (a,b) 0800, (c,d) 1000 and (e,f) 1200 UTC. Note that an okta is a unit of measurement indicating the proportion of sky covered by cloud ranging from 0 (completely clear sky) to 8 (completely overcast), with a station value of 9 indicating that the sky is totally obscured. Figure 4. Two-metre temperature (°C) from (a,c,e) MIDAS stations and (b,d,f) model temperatures interpolated to MIDAS station locations at (a,b) 0800, (c,d) 1000 and (e,f) 1200 UTC. Although a comparison between figure 4a,c indicates a lack of the expected diurnal warming between 0800 and 1000 UTC, the effect of the eclipse on temperature is illustrated more directly by comparison between the observed and modelled temperatures at 1000 UTC. This is because comparison of the observed and forecast temperatures enables the changes in the observations resulting from the diurnal and synoptic-scale atmospheric evolution to be taken into account. Figure 4b,d,f shows the model forecast output interpolated from the 1.5 km model grid to the locations of the MIDAS stations. At 0800 UTC, prior to eclipse onset, there is a generally good agreement between the observed and forecast temperatures. At 1000 UTC temperatures across the entire British Isles are cooler than forecast and this difference is particularly apparent in the clear sky band across the midlands, Wales and Cornwall where differences reach up to approximately 4°C. By 1200 UTC observed temperatures have largely recovered to match those forecast. The exception to this is in southeast England where temperatures remain lower than forecast by approximately 2°C. Comparison of the 1000 UTC observed and forecast temperatures at station points (figure 4c,d) provides clear evidence of eclipse-induced cooling, greatest under clear skies. However, the observed and forecast temperatures do not exactly agree even before the onset of the eclipse, and station-to-station variability in the magnitude of the observed and forecast temperature difference exists even for neighbouring stations; these differences are expected and likely result from a combination of forecast error (even at this short forecast lead time), measurement error, and the interpolation of the model data to the station points (which does not take altitude changes into account). Figure 5a illustrates this difference (observed minus forecast temperature) at 0900 UTC. To allow for these differences existing before eclipse onset, figure 5c and e shows the change in the temperature difference (observed minus forecast temperature) from 0900 to 1000 UTC and from 1000 to 1100 UTC, respectively. These changes are termed ‘synoptic-evolution relative’ changes hereafter and the magnitude of these changes should be considered relative to the difference in temperature between observed and modelled temperature prior to eclipse onset. To smooth the station to station variability, the panels of figure 5 show difference fields at station points averaged over boxes of 1° longitude and 0.5° latitude (roughly square in Euclidean distance at this latitude). The time from when the synoptic-evolution relative temperature changes are determined (0900 UTC) is after the onset time of the eclipse over the British Isles. This time was chosen to enable the changes to be determined over a 1-h period focused on the time period of the likely greatest eclipse-induced changes. Considering this 1-h period will reduce uncertainty associated with the differences between the observations and forecast by providing an estimate of these differences at a time as close as possible to the time when the maximum eclipse-induced changes are expected (within the constraint of the hourly-forecast data availability). For example, the maximum temperature anomalies are expected to have occurred at approximately 0945 (approx. 15 min after the maximum eclipse at approx. 0930). Figure 5. (a,b) MIDAS observations minus model difference for (a) 2-m temperature (°C) and (b) 2-m RH (%) at 0900 UTC. (c,d) Change in (observation minus model) difference between 0900 and 1000 UTC for (c) temperature and (d) RH. (e,f) As for (c,d) but for change in difference between 1000 and 1100 UTC. A positive value for temperature difference or change in difference indicates either warmer observed relative to modelled temperature (a) or a warming with time of the observed relative to the modelled temperature (c and e). A positive value for RH difference or change in difference indicates either increased observed relative to modelled RH (b) or an increase with time of the observed relative to the modelled RH (d and f). Station values are averaged over 1° longitude by 0.5° latitude regions. Small magnitude values are shaded light grey (−0.2 to 0.2°C; −1 to 1%). At 0900 UTC observation minus forecast differences in temperature are typically within ±1°C, with generally negative values to the south and positive values to the north of the British Isles (figure 5a). The north–south difference could suggest that the eclipse may have already induced a weak cooling in the clearer skies to the south (e.g. the obscuration was already approx. 45% at Reading in Berkshire at 0900 UTC), but a similar difference already exists at 0800 UTC (cf. figure 4a,b). The synoptic-evolution relative temperature change from 0900 to 1000 UTC is negative across the entire UK (isolated positive changes exist in the Republic of Ireland) implying eclipse-induced cooling occurred; typical magnitudes are 1–3°C (figure 5b). Many of the averaging boxes with the larger temperature changes occur in the clear sky band. Comparing the temperature change from 1000 to 1100 UTC with that from 0900 to 1000 UTC the sign is generally reversed, implying a warming in the observations relative to the forecast over this period and so a recovery from the eclipse-induced cooling. This is consistent with the improved agreement between observed and forecast temperatures an hour later at 1200 UTC (cf. figure 4e,f). The exception to this recovery is in southeast England which is associated with further (though weak) cooling from 1000 to 1100 UTC. Changes in RH have previously been attributed to eclipse events (see §1) and the right-hand panels of figure 5 illustrate the synoptic-evolution relative RH changes in the same format as the temperature changes shown in the left-hand panels. At 0900 UTC the observations and forecast RH values generally agree within ±10% with some larger differences found over Wales, southwest England and Scotland (where local high and variable orography and coastal effects might be expected to lead to larger differences as the interpolation of the forecast data to the station points will be less representative). The synoptic-evolution relative RH changes from 0900 to 1000 UTC are generally positive, implying an eclipse-induced RH increase of the air relative to the synoptic evolution, and reach 5–20% in the clear sky band. Changes from 1000 to 1100 UTC are generally negative across England and Wales (with the exception of southeast England) implying a recovery (RH decrease) of the air towards the values that would have occurred in the absence of the eclipse. The RH changes are anticorrelated with the temperature changes implying that cooling associated with the eclipse leads to the RH increase and that this effect dominates over that due to any decrease in specific humidity. The typical magnitudes of the RH increase are also consistent with those expected from cooling at constant specific humidity: for example, a cooling of 4°C at 10°C for constant specific humidity should lead to an RH increase of approximately 20%. Eclipse-induced effects on temperature and RH are well understood and documented. By contrast, the effects on wind speed and direction are more controversial (see §1). Figure 6 shows the synoptic-evolution relative changes in wind speed and direction in the same format as in figure 5. At 0900 UTC observed wind speeds and directions are generally within ±2 knots and ±40° of the forecast values over southern England, but larger differences exist elsewhere, especially over Scotland for wind speed and Wales for wind direction. As with the RH field, larger differences over high and variable orography are not surprising; note also that the stations are less densely located over Scotland and Wales than in England (figure 3b,d,f) reducing the smoothing effect of the box averaging. Focusing on England, a generally negative synoptic-evolution relative change in wind speed occurs from 0900 to 1000 UTC of up to 4 knots followed by further changes of typically ±2 knots from 1000 to 1100 UTC with increases slightly dominating over decreases. These changes imply a reasonably consistent eclipse-induced weakening of the winds followed by some signs of a recovery. The changes are less consistent across the British Isles than the equivalent changes in temperature and RH. This can partly be attributed to the very weak winds over England at this time (figure 3b,d,f and note that cup anemometers also have a starting wind speed, i.e. a minimum wind speed that can be recorded, which is typically approx. 1–4 knots [22]). Synoptic-evolution relative changes in direction are also not very consistent across the British Isles (figure 6d,f). However, there is a generally positive synoptic-evolution relative wind direction change across England from 0900 to 1000 UTC followed by a generally negative change from 1000 to 1100 UTC. In the calculation, a positive change means that the angle anticlockwise relative to East that the wind vector points towards in the observations has increased relative to that angle in the forecast and so a backing of the wind direction; a negative change implies the observed wind direction has veered relative to the forecast. Hence, we conclude that the synoptic-evolution relative wind evolution reveals a reasonably coherent weakening in the (already weak) wind speeds and the suggestion of a backing of wind direction over England during the eclipse. Figure 6. (a,b) MIDAS observations minus model (interpolated to station locations) difference for (a) 10-m speed (knots) and (b) 10-m direction (°) at 0900 UTC. (c,d) Change in (observation minus model) difference between 0900 and 1000 UTC for (c) speed and (d) direction. (e,f) As for (c,d) but for change in difference between 1000 and 1100 UTC. A positive value for speed difference or change in difference indicates either stronger observed relative to modelled wind (a) or a strengthening with time of the observed relative to the modelled wind (c and e). A positive value for direction difference or change in difference indicates either a backed observed relative to modelled wind (b) or a backing with time of the observed relative to the modelled wind (d and e). Station values are averaged over 1° longitude by 0.5° latitude regions. Small magnitude values are shaded light grey (−0.2 to 0.2 knots; −4 to 4°). Note that in panel (a) there is one data value of −14 knots; this is shaded in the colour indicted as the −10 to −4 knot range. The lack of strongly robust eclipse-induced wind response motivates a further analysis using the independent roadside station network, which has an enhanced density of measurement sites. (b) Synoptic-evolution relative eclipse-induced anomalies deduced using Vaisala roadside network observations The greater density of the roadside network stations compared to the MIDAS stations used and general consistency of the temperature and winds measured there with those from the MIDAS station network (and model forecast prior to eclipse onset) can be seen by comparison of figure 7b,d,f with figure 3 (right panels) and figure 4. (Note that roadside observations were not available for the Republic of Ireland.) The roadside station temperatures are very consistent with the MIDAS station observations and forecast generally the same temperatures (in the same regions) within the 2°C discretization used for plotting. The warmest roadside station temperatures slightly exceed those from the MIDAS stations which accounts for the warmest colour band covering 4°C in figure 7a,c,e instead of 2°C as in figure 4. The wind speeds measured by the roadside stations are generally weaker than those measured by the MIDAS stations. This is likely to be attributable to the lack of numerical adjustment of the height of wind measurements from the measurement height to 10 m (as is performed where required for the MIDAS observations). The wind directions across the UK from the roadside and MIDAS observations are regionally consistent. Figure 7. (a,c,e) temperature at roadside stations and (b,d,f) wind vectors at roadside stations at (a,b) 0800, (c,d) 1000 and (e,f) 1200 UTC. Figure 8 shows the synoptic-evolution relative changes in wind speed and direction for the roadside observations; this is derived in the same way as for the MIDAS observations shown in figure 6. Overall, the fields plotted appear more spatially coherent for the roadside observations than for MIDAS observations, especially over England and Wales; this is likely a consequence of the greater density of stations for the roadside observations. At 0900 UTC, the observed wind speeds can be seen to be generally weaker than the forecast winds by 1–2 knots over Wales and inland England areas though by more over Scotland and along the southern UK coast where winds were stronger (figure 8a). This may partly be attributable to the eclipse since 0900 UTC is after eclipse onset (although the observed MIDAS wind speeds were generally stronger than the forecast ones at 0900 UTC (figure 6a)); other likely reasons for this are discussed above based on comparison of the roadside and MIDAS wind vectors. Observed roadside wind directions are generally within ±20° of those forecast (figure 8b) with a slight preference for the observed winds to be backed relative to those forecast, as also found with the MIDAS observations (figure 6b). The synoptic-evolution relative changes in roadside wind speed and direction from 0900 to 1000 UTC and from 1000 to 1100 UTC are consistent in sign with those found for the MIDAS observations, especially over England, and the greater spatial coherence of the patterns lends confidence that they are robust. Figure 8. As for figure 6, but for comparison of the roadside observations with the model. All data values are within ranges indicated on the colour bars. These robust synoptic-evolution relative changes now motivate the closer examination of high temporal resolution (1-min and 20-min data) observations from selected stations. (c) Regional eclipse-induced surface meteorological change deduced from high temporal resolution observations The advantage of analysing 1-min and 20-min temporal resolution station data is that eclipse-induced changes occurring on timescales of less than an hour can be resolved. The disadvantages are that synoptic-evolution relative changes cannot be easily determined for comparison (the operational model output is only available on the hour for fields analysed here) and the 1-min MIDAS wind data are very noisy compared with the hourly MIDAS wind data (which is provided as an average over a 10-min period). Figures 9–12 show wind speed and direction data at 1-min (MIDAS observations) and 20-min (roadside observations) intervals for four selected regions; these regions are marked on figure 2 and the specifications are given in table 1. The selection of these regions was motivated by the robust eclipse-induced changes in wind speed and direction (relative to the synoptic evolution) found over England in §4a,b and the preferential occurrence of large eclipse-induced changes in temperature and RH in the clear sky band across the midlands, Wales and Cornwall. The Wales and Midlands1 regions were selected as covering the cloud free regions over central England at 1000 UTC. Midlands2 is a subregion of Midlands1, chosen to focus on the clearest region and such that there is consistency in the wind speed station data for the stations chosen (i.e. the evolutions of wind speed and direction follow tight plumes). The central southern England region was selected as a cloudy inland region just south of the cloud-free band with lots of stations. Figures 9–13 show the data from individual stations (thin grey lines) and mean values (bold red lines) with error bars. UKV model forecast output interpolated to the station locations is also shown in the panels showing the 1-min MIDAS data (figures 9 and 10) and the temperature and RH values for the 20-min roadside data (figure 13). In figures 9 and 13, the model output data are shown in box and whisker format; in figure 10, the orange diamonds mark the model values at the stations and black diamonds mark the mean of the station values. Stations within the regions that recorded zero wind speed at any time within the limits plotted were excluded from the analysis so as not to bias the mean values of wind speed and wind direction (direction is undefined when speed is zero). This constraint removed several stations from analysis, particularly in the Wales region where the winds were weakest. Figure 9. One-minute temporal resolution MIDAS 10-m wind speed data (knots) as a function of time for sets of stations in four regions: (a) central southern England, (b) Wales, (c) Midlands1 and (d) Midlands2. Stations are selected within the latitude and longitude limits at which 1-min wind speed data are available at all times and the speed is non-zero at all times. Vertical dashed line marks the approximate time of the maximum partial eclipse (0930 UTC). Thick red line shows the mean value with error bars given by ±1.96 s.d. (yielding the 95% CI). Model forecast values interpolated to station locations are overplotted in blue in box and whiskers format. The box encloses the interquartile range with the horizontal line marking the median value. The whiskers extend out to the maximum or minimum value of the data, or to 1.5 times either the 1st or 3rd quartile if there is data beyond this range. Outliers are identified with circles. Number of stations plotted is (a) 17, (b) 7, (c) 16 and (d) 8. The upper bound of speeds plotted is limited for clarity so data from individual stations occasionally exceeds this. Figure 10. As figure 9, but for wind direction. Wind directions are described conventionally, as the angle clockwise from North that the wind is coming from (e.g. an angle of 90° is an easterly wind). Stations are selected within the latitude and longitude limits at which 1-min wind speed data and direction data are available at all times and the speed is non-zero at all times. Model forecast values interpolated to station locations are overplotted in orange diamonds (rather than as box and whiskers as in figure 9); black diamond denotes mean values. Number of stations plotted is the same as in figure 9. Note y-axis varies between panels. Figure 11. As figure 9, but for 20-min temporal resolution roadside wind speed data. Number of stations plotted is (a) 26, (b) 19, (c) 44 and (d) 12. Figure 12. As figure 11, but for wind direction. Number of stations plotted is the same as in figure 11. Figure 13. Twenty-minute temporal resolution roadside observations as a function of time for (a) temperature and (b) RH in the Midlands1 region only. Stations are selected within the latitude and longitude limits at which 20-min (a) temperature and (b) RH data are available at all times. Vertical dashed line marks the approximate time of the maximum partial eclipse (0930 UTC). Thick red line shows the mean value with error bars given by ±1.96 s.d. (yielding the 95% CI). Model forecast values interpolated to station locations are overplotted in blue in box and whiskers format (as in figure 9). Number of stations plotted is 62 (for both fields). Table 1. Specification of regions. The location of the regions is shown in figure 2. region latitude limits (°N) longitude limits (°E) comment central southern England 51, 52 −2, 0 cloudy, inland Wales 51.5, 53 −5, −2.5 clear band Midlands1 52.25, 53.5 −2, 0.5 clear band Midlands2 52.75, 53.5 −1, 0.4 clear band; subset of Midlands1 Beginning with the 1-min MIDAS observations, figure 9 shows that wind speeds evolved due to synoptic evolution and the diurnal cycle during the time period shown (gradually decreasing on average over the central southern England region, for example). However, within this evolution, over a several hour timescale, a more rapid evolution can be discerned around the time of the eclipse (the approximate time of the maximum partial eclipse, 0930 UTC, is marked by the bold dashed line). A reduction in wind speed from approximately 0900 to 1000 UTC is clearly evident in the central southern England and Midlands regions (in the central southern England region this the post-eclipse increase is somewhat obscured by the general reduction in wind speed during the period shown). Over Wales, a reduction in the range of wind speed during the eclipse is more apparent than a reduction in the mean wind speed. The reduction in wind speed of about 2 knots is followed by a rapid recovery in the Midlands1 and Midlands2 regions over approximately 15 min. By contrast, the wind speeds forecast by the UKV model do not undergo a rapid reduction around the time of the eclipse. The wind speeds are under-predicted by the forecast in the central southern England, Midlands1 and Midlands2 regions prior to the eclipse and so are a better match to those observed after the eclipse. In the Wales region, the mean forecast wind speed is a good match to that observed throughout the period plotted; however, a reduction in the spread across stations is not observed in the forecast wind speeds, unlike in the observations. While the effect of other forcings on the wind speed cannot be ruled out, the change observed around the time of the eclipse is attributed here to the eclipse due to its rapidity, the lack of similar wind speed changes in the model forecast winds, and the consistency of the wind speed changes with those observed in other eclipse events. In figure 10, a backing from approximately 0900 to 0930 UTC by approximately 20°, followed by a slow veering, in the wind direction during the eclipse is clearly evident in the Midlands1 and Midlands2 regions. There is no obvious wind direction change associated with the eclipse over the cloudy central southern England region. Over Wales the wind directions are very variable, as expected given the hills and mountains in this region which can dominate local wind flows; it is not possible to discern an eclipse-induced wind direction change in this region. The forecast wind directions are a good match to those observed over the central southern England and Wales regions (although the observed range of directions is enhanced after the eclipse relative to the model forecast). In the Midlands1 and Midlands2 regions, the forecast and observed wind directions are a good match until 0900 UTC after when the forecast winds continue to veer whereas the observed winds back leading to a difference of approximately 30° at 1000 UTC. The timescale of the wind speed and direction changes attributable to the eclipse is approximately 1 h which provides rationale for the calculations of synoptic-evolution relative changes over 1-h periods presented in figures 5, 6 and 8. The 20-min roadside observations have similar temporal evolutions to the 1-min MIDAS observations. The wind speeds are generally weaker in the roadside observations (e.g. cf. figure 11a with 9a) which is consistent with the systematic bias seen across the entire UK and discussed in §4b. A reduction in mean wind speed of about 2 knots from approximately 0900 to 1000 UTC is evident in the Wales, Midlands1 and Midlands2 regions but not discernable in the central southern England region (figure 11a). The roadside observation wind direction timeseries for the Midlands1 and Midlands2 regions show the same pattern of backing followed by veering during the eclipse period as the equivalent MIDAS observation plots (cf. figures 12c,d and 10c,d) although the wind directions are more widely spread within the each region. In the central southern England region (figure 12a), the mean direction veers during the eclipse period relative to the direction before and after the eclipse although this does not seem to be directly attributable to the eclipse as the veering takes place transiently during the 20 min after 0900 UTC, and is not sustained throughout the eclipse. In the Wales region (figure 12b), the mean wind backs sharply at 0940 UTC. The large variability in the wind directions in this region together with the sharpness of the backing suggest that this change also cannot be attributed to the eclipse. Confidence in the wind speed reduction and backing attributed to the eclipse can be qualitatively assessed from the size of the changes during the eclipse compared with the size of the error bars plotted in figures 9–12 (the error bars indicate the 95% confidence interval in the mean). The error bars are generally statistically smaller for the roadside observations than for the MIDAS observations due to the larger number of available stations. The highest confidence in the eclipse-induced changes is found by considering the Midlands1 region, the larger of the two Midlands regions located in clear skies, and the roadside data. The size of the eclipse-induced anomalies can only be approximated from the plots since the effects of the synoptic and diurnal evolutions cannot be precisely quantified. The estimated wind speed reduction of about 2 knots exceeds the confidence interval of 1.3 knots calculated at 0930 (figure 9c). However, the estimated backing of approximately 20° is about half the confidence interval of 38° and hence cannot be considered robust. Confidence in the changes in these wind fields can be contrasted with that in temperature and RH. Figure 13 shows the temporal evolution of temperature and RH from the roadside observations in the Midlands1 region. Both fields clearly fail to completely recover from the eclipse-induced changes leading to a lag in the morning warming and RH reduction of the near-surface air. Despite this complication, the eclipse-induced changes of perhaps 1°C and 10% clearly exceed the confidence intervals (calculated as 0.6°C and 3.6% at 0930). 5. Discussion An analysis has been presented of the near-surface atmospheric anomalies over the British Isles attributable to the partial solar eclipse of 20 March 2015. Previous research has demonstrated consistent cooling and associated RH increase associated with eclipse events. However, the wind field response has been more unclear with some researchers identifying a response and others not. To account for the synoptic-scale evolution during the eclipse, eclipse-induced anomalies have been determined through comparison of meteorological observations against the output of a state-of-the-art high-resolution operational weather forecast over the UK; the solar eclipse was not represented in the model code and so the forecast provides a ‘best guess’ of the forecast evolution that would have occurred in the absence of the eclipse. Two types of meteorological measurements were analysed: (i) measurements from the MIDAS Land Surface Stations (both hourly observations over the British Isles and 1-min observations from selected stations) and (ii) measurements from a roadside measurement network operated by Vaisala to monitor road conditions. The roadside network is extensive over the UK with 868 stations used compared with the 331 MIDAS stations from which hourly weather observations were obtained. Whereas the MIDAS dataset is routinely used for British Isles meteorological analysis, we believe this is the first meteorological analysis using the unique roadside network dataset. Weather conditions for observing eclipse-induced surface weather changes were poor over most of the British Isles with widespread cloud and relatively weak winds. However, a band of clear skies extended across middle England, Wales and into northern Cornwall. Hence, in addition to the British Isles-wide analysis presented here, 1-min and 20-min observations have been presented from regions within this clear sky band and from a region with contrasting weather conditions: cloudy central southern England. MIDAS wind and cloud observations over the British Isles are consistent with the Met Office surface analyses (in terms of direction and relative strength as inferred from the isobars) and satellite imagery. MIDAS temperature observations show show the expected diurnal warming during the morning and comparison with the model output illustrates the cooling attributable to the eclipse (reaching up to 4°C at station points in the cloud-free regions). Synoptic-evolution relative eclipse-induced gridded (1° longitude by 0.5° latitude grid box averages) temperature anomalies and RH anomalies (inferred from comparing the changes in the MIDAS observations with those from an operational model forecast ignorant of the eclipse) reach up to 3°C and 20%, respectively, in the cloud-free band. Synoptic-evolution relative eclipse-induced gridded wind speed and direction changes are less homogeneous across the UK than for temperature and RH but, focusing on the clear sky band, there is reasonably consistent weakening (by up to 2 knots in the already weak winds) and backing in the wind direction (by 20–40°) during the eclipse followed by a somewhat consistent strengthening and veering after the eclipse. The temperature and wind evolution during the eclipse from the roadside observations are consistent with those in the MIDAS observations although the winds are generally weaker. This difference is likely attributable to a lack of numerical adjustment of the height of wind measurements from the measurement height to 10 m (as is performed where required for the MIDAS observations); sheltering of the roadside stations may also contribute. The larger number of roadside stations is highly advantageous as it yields smoother gridded wind speed and direction distributions over the UK compared with the MIDAS dataset. A consistent weakening and backing followed by strengthening and veering compared to the model output is found fairly consistently across the clear sky regions in middle England and Cornwall. High temporal resolution (1-min and 20-min data) observations for stations within three clear sky regions and one cloudy region illustrate the timescales during which the eclipse-induced wind changes occur. Wind speeds slacken from shortly before 0900 UTC to nearly 1000 UTC by up to about 2 knots in all regions at the MIDAS stations and three of the four regions at the roadside stations (the exception being the cloudy central southern England region). Backing of approximately 20° occurs over the same timescale although this is only evident in the clear sky Midlands regions (at both station types); no clear directional changes are observed in the cloudy central southern England region and the directional changes are highly variable in the Wales region (hypothesized to arise due to local slope-induced flows in this orographic region). The sign and magnitude of these regional changes are consistent with those determined from MIDAS observations from the 11 August 1999 eclipse over the UK (0.7 m s−1 and 17°) [14]; this eclipse was at its maximum over the UK (total over southwest UK) at about 1015 UTC, so at a similar time of day to the 20 March 2015 event. This consistent wind response during two different eclipse events and determined using two independent observational networks provides confidence that wind direction changes occur robustly during eclipse events over inland regions with low orography. The backing of the wind direction observed during the eclipse is reminiscent of the changes in wind direction which can also occur at sunset leading, in some circumstances, to a jet—the nocturnal jet—of relatively enhanced wind speeds above the surface [23,24]. The situation leading to a nocturnal jet was originally studied by Blackadar [25]; Thorpe & Guymer [26] used a layer model to consider the effect of surface friction on the jet and showed that the jet maintained its increased speed through decoupling of the jet from the surface. This decoupling minimizes the surface drag on the flow, a further consequence of which is a change in wind direction. Wind direction changes can also occur without the full decoupling of the flow associated with the nocturnal jet if the relative effects of surface drag, the pressure gradient force and Coriolis acceleration change. A change in the boundary layer depth can lead to such wind direction changes. During a typical convective cloudy day, a convective boundary layer steadily develops which then transitions to a shallow stable layer after sunset (e.g. [27]). The circumstances of a substantial eclipse are similar, but the changes occur more rapidly. Wind profiles of the whole boundary layer were obtained using an Ultra High Frequency (UHF) band Doppler Radar during the 11 August 1999 eclipse by Girard-Ardhuin et al. [28], who reported appreciably lessened reflection from the boundary layer top, associated with a suppression of turbulence and boundary layer reduction. A decline in the boundary layer height was also directly observed during the 29 March 2006 solar eclipse in Greece by [29] who showed, using lidar and balloon soundings in clear conditions over Athens, that mixed layer heights during the 84% partial eclipse were reduced from 800 m to 620 m. For the 20 March 2015 eclipse, there is observational evidence of the depth of the boundary layer available from a radiosonde ascent launched from Reading (51.44° N, 0.94° W) before eclipse onset (0848 UTC) which landed in Winchester (31 miles southwest) at 1013 UTC, and from a UHF Doppler radar wind profiler operating at Cardington (52.10° N, 0.42° W, [30]) throughout the eclipse event (neither sets of data are shown). The boundary depth, inferred from the height of the temperature inversion, decreases during the morning in the vicinity of Reading, but this decrease is not inconsistent with the synoptic evolution expected from model profiles. By contrast, at Cardington there is evidence from the wind profiler of a slow reduction in boundary layer depth throughout the morning (from approx. 900 m at 0300 UTC to approx. 600 m at 0800 UTC and then to 500 m at 1000 UTC) before the boundary layer deepens again after noon. Thus, the boundary layer is shallowest at about the time of the maximum eclipse. While this boundary depth reduction cannot be confidently attributed to the eclipse, a similar decrease in boundary layer depth is not observed in hourly model profiles (again from a model ignorant of the eclipse) taken at Cardington. Burt [31] provides other evidence of boundary layer changes during this eclipse through observations showing a reduction in cloud base height of 20 m during the passage of the eclipse, together with other boundary layer changes in temperature and wind speed consistent with findings from the wider observation network analysed in this paper. Comparison of the operational weather forecasts made by the Met Office UKV model against a forecast made by the same model but including a parametrization for the eclipse in the model code shows shallower boundary layer depths in the clear sky region, and in Scotland and Northern Ireland, in the forecast from the model with the eclipse parametrization at the time of the maximum eclipse [32]. These model results reveal that a boundary layer depth change attributable to the eclipse would be expected to have occurred at Cardington but not at Reading, consistent with the available observations described above. Effects of boundary layer depth changes can be represented by a theoretical model of the boundary layer such as that of [26]. This model relates the surface drag coefficient, CD, and boundary height, h, with the northwards, u and westwards, v, components of the wind speed by two coupled equations: and where f is the Coriolis parameter and ug is the free geostrophic wind speed above the layer. These coupled time-dependent ordinary differential equations can be solved numerically for u and v as a function of time t, if representative values of CD and h are assumed, given initial conditions for u and v at t=0. Figure 14a shows time-dependent numerical solutions (i.e. the variations of u and v with time t) calculated for two different layer depths, beginning with initial values of u and v (at t=0) chosen to approximate the wind speeds in the Midlands regions around the eclipse time. (A fourth order adaptive Runge–Kutta numerical method was used for these calculations, from Press et al. [33].) In figure 14a, the magnitudes of the wind vectors at hourly intervals found by integration from the initial values are plotted against each other in hodograph form, to show the associated changes in direction with time. The two boundary layer heights were selected to give an illustrative comparison between the situations of sustaining an established boundary layer in clear skies, and the much shallower boundary layer which may be formed during an eclipse. With time, the wind direction in the shallow boundary layer case turns anticlockwise, compared with the more constant wind direction maintained in the deeper boundary layer case. Figure 14b shows the continuous variation in wind directions against time (from which the sampled hourly values of figure 14a were obtained.) Although the exact surface and flow parameters of the regions are not attempted to be represented, the wind direction change apparent under these assumptions is not inconsistent with that observed in figure 12c,d. Similar nocturnal oscillatory behaviour has been observed in near surface winds from the Cabauw observatory [23]. Figure 14. Illustrative calculations of the variation in wind direction for atmospheric boundary layer heights of 1000 m (dashed lines) and 200 m (solid lines), using the theoretical model in [26]. (a) Hodograph showing the wind vectors at hourly intervals, beginning from initial wind vector components u and v of 3 ms−1 (at t=0). The values of u and v have been normalized by an assumed geostrophic wind speed ug of 10 ms−1. (b) Time series of the calculated wind directions for the two boundary layer heights. (Drag coefficient CD=8×10−3, and Coriolis parameter calculated for 50°N.) 6. Conclusion In addition to the well-documented cooling, increase in RH and slackening of the near-surface wind speed, wind direction changes can also be attributed to an eclipse. While confidence in wind speed changes is similar to that in temperature and RH, these far exceed confidence in the wind direction changes. Nevertheless, the wind direction changes remain of broader interest, because of their relationship to the supposed ‘eclipse wind’. It is noteworthy that the wind direction changes have been found to be robust across the two eclipse events in 1999 and 2015, with the latter analysis here using two independent observation networks. Some theoretical support for the wind direction changes identified in the clear sky inland regions is provided by considering the rapid eclipse-induced cooling as analogous to the formation of nocturnal wind structures. This may provide a more parsimonious explanation for the surface wind direction changes observed than the substantial mesoscale structure postulated by Clayton [11]. Finally, a spatially dense, high temporal resolution (subhourly) meteorological observation network is invaluable for studies of meteorological responses to transient phenomena. The roadside network here employed now provides a further novel valuable source of such meteorological measurements. Acknowledgements The authors thank David Bullock from Vaisala for his extraction of and provision of data from the roadside network of stations. Whitney Nobbs undertook an important preliminary study of the roadside network data available. The Met Office is thanked for making the operational weather forecast data and MIDAS dataset available through BADC. Matthew Clark from the Met Office kindly provided the 1-min MIDAS wind data. Janet Barlow (University of Reading) provided very helpful ideas that led to the nocturnal jet formation mechanism being discussed here. We thank the National Centre for Atmospheric Science (NCAS) for provision of the Cardington wind profiler data and Emily Norton from the NCAS Atmospheric Measurement Facility, in particular, for kindly producing plots for us of the Cardington wind profiler observations. Data accessibility The hourly weather observations MIDAS dataset and operational output from the MetUM is available through the British Atmospheric Data Centre (BADC). The data files for the Vaisala roadside network and 1-min Met Office surface station wind measurements were obtained directly from Vaisala and the Met Office, respectively. Competing interests We declare we have no competing interests. Authors' contributions S.L.G. extracted and analysed the observational and model data and drafted the manuscript. R.G.H. and S.L.G. both designed the study. 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==== Front Philos Trans A Math Phys Eng SciPhilos Trans A Math Phys Eng SciRSTAroyptaPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences1364-503X1471-2962The Royal Society Publishing 2755076810.1098/rsta.2015.0225rsta20150225100512712IntroductionIntroductionThe solar eclipse: a natural meteorological experiment A natural meteorological experimenthttp://orcid.org/0000-0003-0693-347XHarrison R. Giles 1http://orcid.org/0000-0002-8683-182XHanna Edward 21 Department of Meteorology, University of Reading, PO Box 239, Reading RG6 6BB, UK2 Department of Geography, University of Sheffield, Winter Street, Sheffield S10 2TN, UKe-mail: r.g.harrison@reading.ac.ukOne contribution of 16 to a theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. 28 9 2016 28 9 2016 374 2077 Theme issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’ compiled and edited by R. Giles Harrison and Edward Hanna2015022523 5 2016 © 2016 The Authors.2016Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.A solar eclipse provides a well-characterized reduction in solar radiation, of calculable amount and duration. This captivating natural astronomical phenomenon is ideally suited to science outreach activities, but the predictability of the change in solar radiation also provides unusual conditions for assessing the atmospheric response to a known stimulus. Modern automatic observing networks used for weather forecasting and atmospheric research have dense spatial coverage, so the quantitative meteorological responses to an eclipse can now be evaluated with excellent space and time resolution. Numerical models representing the atmosphere at high spatial resolution can also be used to predict eclipse-related changes and interpret the observations. Combining the models with measurements yields the elements of a controlled atmospheric experiment on a regional scale (10–1000 km), which is almost impossible to achieve by other means. This modern approach to ‘eclipse meteorology’ as identified here can ultimately improve weather prediction models and be used to plan for transient reductions in renewable electricity generation. During the 20 March 2015 eclipse, UK electrical energy demand increased by about 3 GWh (11 TJ) or about 4%, alongside reductions in the wind and photovoltaic electrical energy generation of 1.5 GWh (5.5 TJ). This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. eclipse meteorologyweather forecastingscience outreachcitizen sciencerenewable power generationcover-dateSeptember 28, 2016 ==== Body 1. Introduction Eclipses have long entranced humankind as an astronomical spectacle, and yield a unique set of circumstances for disparate scientific studies. The Danish astronomer Ole Rømer used an eclipse of Jupiter’s moon Io to make the first estimate of the speed of light [1], and Sir Arthur Eddington exploited the 1919 solar eclipse for his famous test of Einstein’s theory of General Relativity [2]. Solar eclipses have provided valuable opportunities to investigate the solar atmosphere, but the studies they also permit of the terrestrial atmosphere have historically received much less attention. An atmospheric response is implicitly acknowledged in Edmund Halley’s report of the 1715 eclipse (figure 1), where he records, ‘I forbear to mention the chill and damp which attended the darkness of this eclipse of which most spectators were sensible’ [3], p. 261. However, quantitative atmospheric responses were not reported until the 1830s, with a great increase in related research following eclipses in 1980 and 1999 [4]. A modern application of eclipse meteorology in populated regions is in estimating loading of the electrical power network, as, following the expansion of wind and solar generation capability, a solar eclipse transiently reduces the generation from these renewable sources during an increase in electrical demand. Figure 1. Edmund Halley’s map of the passage of the Moon’s shadow during the total eclipse of 22 April 1715 (referred to the Julian calendar). (Online version in colour.) A solar eclipse’s value for atmospheric science lies in the accurate predictability of its magnitude and duration. This means that the response of the atmosphere to a well-characterized stimulus can be observed and evaluated. The more common requirement of non-eclipse experiments in atmospheric science is the need to observe effects in the presence of multiple related or unrelated changes. These complicate the interpretation, as different driving effects are often difficult to disentangle. Even so, for the solar eclipse to offer a genuine atmospheric experiment with the possibility of theoretical interpretation using numerical models, observations with dense spatial coverage and accurate, sensitive instrumentation are also likely to be required, which implies the lunar shadow will need to pass over a populated region. In part, this may explain why the potential for atmospheric and meteorological investigations has only been recognized relatively recently (e.g. [5]), in comparison with that for the astronomical endeavours. The pioneering work of H. Helm Clayton [6] offers the first example of a solar eclipse for a quantitative regional meteorological experiment, in synthesizing measurements from several sites made during the 28 May 1900 US eclipse to elucidate the associated lower atmospheric structures. A great deal more is now possible in terms of automatic monitoring of the atmospheric response to a solar eclipse, which, through its combination with numerical modelling, marks a clear new direction for eclipse meteorology from solely observational studies. The use of recording technology is not in itself new—an early example of automatic solar radiation measurements made at Kew Observatory near London, UK, during the 1954 eclipse over the southern UK is shown in figure 2, and displays the characteristic ‘bite out’ of the diurnal cycle—but the ready availability of sophisticated, often cheaper modern instrumentation and the immediate connectivity provided by the Internet yields observation networks with much greater site density and data rates [8]. Such networks exist for different purposes: they are operated by meteorological services in order to characterize the state of the atmosphere for weather forecasting models, or by local authorities for routine monitoring purposes, or sometimes otherwise by self-funded amateurs or enthusiasts (citizen scientists). The value of the latter ad hoc activity for studying a solar eclipse was even recognized by Edmund Halley [3, p. 261], who reports that, ‘…I have added the following synopsis of such observations as have hitherto come to my hands, acknowledging the favour of those who have been willing to promote our endeavours’. Figure 2. Top of atmosphere solar radiation (STOA, solid line) calculated for London, UK, on 30 June 1954 (see also [7]), during the partial solar eclipse which had its maximum obscuration at London of 71% at 1233 UT. The dashed black and thin grey solid line show hourly measurements of the diffuse (Sd) and total (Sg) solar irradiance made by the Met Office at their Kew Observatory, near London. The modern abundance of measurement networks means that vastly more atmospheric data than ever can now be obtained during solar eclipses, and there are good prospects for combining multiple sources rapidly, although effectively marshalling and combining these sources can pose its own challenges. The net result is that the surface atmospheric response to a solar eclipse can be measured at an unprecedented spatial resolution. Satellite and airborne observations of many atmospheric parameters are available, as are detailed numerical models which describe the evolution of the atmosphere with time using the laws of motion and thermodynamics, in which the effect of an eclipse can be represented or ignored. The availability of modern high spatial resolution numerical models, satellite data, in situ atmospheric data and extensive surface measurement networks allows detailed investigation of the atmosphere’s eclipse response. As a result, it has become timely to exploit the solar eclipse fully as a unique atmospheric experiment, in which theoretical understanding of the atmosphere can be compared with spatial measurements of the response to a brief interruption in the solar radiation. Such validation and verification leads to improvement in atmospheric models, which have great societal benefits from providing accurate weather prediction. Continuing the long heritage of Philosophical Transactions of the Royal Society A in reporting the scientific use of eclipses as an experimental tool (e.g. [1–3]), this special theme issue presents a collection of investigations of the 20 March 2015 solar eclipse, in which the lunar shadow tracked through the North Atlantic to yield a substantial partial eclipse in the UK and Iceland, with totality viewable from the Faroe Islands and Svalbard. Stimulated by this event, the combination of papers presented seeks to address the broader aspects and utility of a solar eclipse, through including an essay on the depictions of solar eclipses in art [9] alongside a review of the existing understanding of eclipse meteorology [4]. In addition, Portas et al. [10] describe the use of the 20 March 2015 solar eclipse for science outreach activity, using a citizen science approach to generate a bespoke observing network; the related science results are analysed separately by Barnard et al. [11]. Multiple conventional measurement systems are employed to analyse eclipse-related changes in surface meteorological [12–16]; 17, sounding balloon [7], satellite [18] and ionospheric data [19]. Atmospheric modelling studies to underpin interpretation of the observations for advancing conceptual understanding are provided by Clark [20] and Gray & Harrison [21]. This work briefly summarizes the findings of this set of papers and further investigates the societal impact of the 20 March 2015 eclipse by evaluating its effect on electrical power generation in the UK. 2. Experimental eclipse studies (a) The influence of eclipses Solar eclipses have long been recognized and revered by civilizations in the ancient and modern world. The depiction of solar eclipses in western art gives one example of their historical recognition as significant phenomena, which is addressed in the paper by Blatchford [9]. After their early portrayal as indicators of events of mystical importance, eclipses represented in art from the Renaissance and the Enlightenment were linked with emerging scientific knowledge of the related astronomical phenomena, such as the diamond ring effect around the Moon. Eclipses are also represented in more modern art, such as in a railway travel poster of the 1920s. The inspiration presented by an eclipse is therefore common to the artist and scientist alike, and implicitly offers a vehicle for outreach. Portas et al. [10] describe their use of the 20 March 2015 eclipse for a national science outreach activity—the National Eclipse Weather Experiment (NEWEx). Using a range of promotion methods building on the existing networks of learned societies, BBC Education and BBC Stargazing Live, they report that up to 3500 participants joined the project to record eclipse-induced weather changes across the UK from Cornwall to Shetland. To maintain momentum with the participants, basic synthesis of these observations acquired on the morning of 20 March 2015 was made rapidly, and a summary of the results was disseminated using national media during the afternoon. A more detailed analysis of the NEWEx data is presented by Barnard et al. [11], who show that, despite the simplicity of the weather measurements of air temperature, wind and cloud made by a network of untrained citizen scientists, the results were similar to the measurements obtained by professionally coordinated operational instrument networks. One informative aspect of the 20 March 2015 eclipse in terms of science outreach was that, despite layer cloud obscuring the astronomical event for many regions of the southern UK, the temperature obtained nevertheless did indicate a change, illustrating the role in science of indirect measurement and inference. The educationally detrimental aspects of one meteorological factor were therefore partially offset by the utility of investigating another. (b) Surface meteorological changes Measurement of meteorological responses to eclipses has historically been dominated by observations of surface changes, principally in temperature [4]. However, there is also interest in the surface wind speed and direction and surface pressure, because these quantities provide essential information about the lower atmosphere’s structure [22]. As remarked earlier, the spatial resolution of modern surface measurement networks having rapid sampling rates is unprecedented, which is reflected in the studies presented. For comparison, in their analysis of the UK eclipse of 11 August 1999, both Hanna [23] and Gray & Harrison [24] used hourly resolution data from up to 121 UK meteorological stations. For the 20 March 2015 eclipse, Hanna et al. [12] used 1 min data from 76 UK sites, with an additional 30 in the Faroes and 148 in Iceland. Clark [13] employed 1 min data from the UK’s Meteorological Monitoring System (MMS), amounting to 266 measuring sites. Gray & Harrison [21] included analysis of measurements from a further independent network of 868 roadside sites, providing air temperature, wind speed and direction at hourly resolution or better. The NEWEx citizen science system generated some 15 000 observations of air temperature, cloudiness, and wind speed and direction from 309 locations across the UK, during a 3 h window centred on the time of peak eclipse [11]. Broadly consistent patterns existed in the observations across the UK from these different measurement systems, although changes in the synoptic conditions during the eclipse complicated the interpretation in some regions. Hanna et al. [12] showed a mean reduction in temperature ranging from 0.31°C in cloudy conditions to 0.91°C in clear conditions, with the minimum lagging the solar radiation minimum by 10 min. Clark [13] found a median temperature reduction of 1.02°C, which lagged the solar radiation minimum by 15 min. Further, Gray & Harrison [21] found consistency between roadside wind and near-surface temperature data and that from the Met Office sites. Hanna et al. [12] reported a 9% mean reduction in wind speed, and found no evidence of surface pressure change, and Clark [13] likewise reported a statistically significant slackening of the wind. The difference in the eclipse-induced temperature drop between cloudy and clear conditions was between 0.6°C [12] and 1.6°C [13] using different methodologies. For inland regions without cloud where eclipse-induced effects were greatest, Gray & Harrison [21] reported reductions in wind speed together with an anticlockwise change in wind direction. An alternative source of surface data covering a region is to use satellite remote sensing. Good [18] used data from the SEVIRI satellite to show the variation in land surface temperature. The greatest reduction in temperatures occurred in the cloud-free region of the central UK, which is consistent with the spatial pattern in the near-surface air temperatures reported by Hanna et al. [12] and Clark [13]. Many other parameters have previously been studied at a single site during an eclipse (e.g. [4,22]). Burt [14] and Bennett [15] analysed the wide range of measurements made at the Reading University Atmospheric Observatory, UK, where the eclipse reduced the solar radiation by 85% but the measurements were obtained under a 400 m thick layer cloud with its base at about 200 m above the surface. During the 2015 eclipse, Burt [14] found a reduction in near-surface turbulence and a reduction in cloud base height. This is partly consistent with results from the 11 August 1999 eclipse over southeast England where decreased convection was observed and convective cloud dissipated [23]. However, Bennett [15] concluded that the reduction in turbulence was insufficient to influence the surface atmospheric electric field. (c) Upper air measurements Much as an eclipse yields predictable and rapid changes in the solar radiation environment, the presence of cloud can prevent accurate measurements of ‘ideal’ (theoretically calculated) eclipse-induced solar radiation changes, although there is obviously still significant darkening. One approach is to position the solar radiation detectors above the cloud. Modified weather balloons offer an inexpensive platform to carry photodiode sensors to provide such data during a typical meteorological balloon flight of approximately 2 h duration. Harrison et al. [7] describe a coordinated campaign of balloon-carried solar radiation sensors from launch sites straddling the path of the 20 March 2015 eclipse, at Reading, UK (51.44° N, 0.94° W), Lerwick, UK (60.15° N, 1.13° W), and Reykjavik, Iceland (64.13° N, 21.90° W). All three balloons reached sufficient altitude above the cloud to demonstrate agreement of the measured eclipse-induced solar radiation changes with theory. Marlton et al. [16] used the soundings from Reading and Lerwick to search for eclipse-induced gravity waves in the troposphere, which have previously been associated with some eclipses [4]. Despite observations of pressure fluctuations, the complexity of the synoptic conditions at the time and the island topography at Lerwick precluded the fluctuations being unambiguously attributed to the eclipse. (d) Ionospheric measurements Detectable changes occur in the upper atmosphere from a solar eclipse. Scott et al. [19] showed eclipse-induced changes in the cut-off frequency of the ionosphere’s E layer (at 100 km) above Chilton, UK, during 20 March 2015, and compared them with simultaneous changes in solar ultraviolet and X-ray emissions. This provides a calibration for the long series of ionosonde measurements which began in the UK in 1932, which enables solar disc properties to be inferred from eclipse-influenced historical ionosonde data. (e) Modelling Numerical models of the atmospheric circulation provide detailed three-dimensional information concerning the evolution of wind fields and temperatures. Such models can be configured to include the influence of an eclipse, or used to predict the changes which would have occurred in the absence of an eclipse. Differencing results from the same model with and without knowledge of the eclipse included allows predictions of the eclipse-induced changes to be made, or the observations made can be differenced from the predictions of an eclipse-ignorant model to determine the eclipse-induced effects. The second approach was used by Gray & Harrison [24] for studying the 1999 eclipse, and this was undertaken again for the 20 March 2015 eclipse in Gray & Harrison [21], but with a much more extensive set of measurements for comparison. The first approach was used by Clark [20] with a nested arrangement of Met Office models to provide predictions at 1.5 km horizontal resolution over the UK. Both modelling studies show small anticlockwise changes in the wind direction in some areas, which are associated with near-surface changes in atmospheric mixing. 3. Electrical power generation considerations Solar eclipses briefly influence the production of electricity from photovoltaic (PV) and wind generation. The proportion of electrical energy provided by renewable sources such as that from large arrays of PV cells and wind turbines has increased considerably in recent decades, particularly in wind generation. In 2013 about 21% of global energy generation was produced from renewable sources, which is estimated to reach 25% in 2040 [25]. Some countries have made determined obligations to achieve an increase in the fraction of electricity generated from renewables, for example: Ireland is committed to produce at least 40% of all electrical energy consumed from renewable sources by 2020 [26]. While solar eclipses are relatively rare events—Earth experienced 228 eclipses during the twentieth century [27]—the global increase in the contribution of solar and wind sources to electricity generation means that the transient effect of solar eclipses on electricity generation will need to be considered more often. The demand for electricity varies during the day, from day to day and across the week, for which predictions of the likely load are made to plan the generation needed to maintain a stable supply network. The timing of a solar eclipse is of course known in advance, but the actual effects on generation and demand will be weather dependent. The studies of eclipse meteorology provide information to apply to this problem, together with experience obtained from previous eclipse effects on power generation. For example, in the 1999 solar eclipse, when there was a smaller contribution from renewable sources, the UK electrical power demand was reduced as people stopped what they were doing and went to watch the eclipse in mostly clear skies (J. Caplin 2016, personal communication). For the 20 March 2015 solar eclipse, more of the UK was overcast than for the 1999 event and the proportion of renewable electrical generation increased. Figure 3 shows the position of the major wind turbine sites in the UK, together with the regional effect of the 20 March 2015 eclipse. From this distribution of wind turbine sites, it is clear that changes in the wind due to the eclipse had a significant potential to influence generation. (The distribution of the solar generation sites is not shown, but these contribute less power in total than wind generation, and are mainly in the south of the UK, which experienced less solar obscuration than the north.) Figure 3. Distribution of UK electrical generation sites operating by wind power, with their positions marked by black points having radii proportional to their generating capacity (from [28]). The region of totality of the solar eclipse of 20 March 2015 is shown as a grey band with the times of totality marked, and contours of percentage obscuration are drawn for the regions experiencing a partial eclipse. Figure 4 shows measurements and predictions of energy demand in the UK National Grid during the 20 March 2015 solar eclipse. Figure 4a shows the prediction of the reduction in PV generation, on the basis of a direct and unlagged response to the reduction in incoming solar radiation. The effect of the PV reduction is to draw more power from the National Grid, together with other eclipse-related additional demand, such as for lighting and heating. Figure 4b shows the increase in total demand, compared with a forecast based on demand from the previous 2 days. Some of this increase in demand also comes from a reduction in wind generation. Figure 4c shows the reduction in wind generation recorded during the solar eclipse. This response is lagged on the minimum in the solar response, by approximately 30 minutes. Clark [13] remarked on the effects of coastal topography on the time response in the wind flow, which may have been a factor at some of the coastal generating sites. Figure 4. National grid electricity variations associated with the 20 March 2015 solar eclipse. Time series (in hours UT) of (a) forecast expected drop in photovoltaic (PV) generation, (b) forecast and measured total demand of electricity and (c) measured variation in wind generation. (All panels also show the calculated change in solar radiation received by a horizontal surface at the top of atmosphere, STOA, following [7] as the orange dashed line; measured power grid data in (b,c) were sampled at 1 min intervals.) The integrated effect of the solar eclipse on UK electrical energy generation has been evaluated by assuming an otherwise linear increase in generation between the beginning and end of the eclipse (between 0848 UT and 1100 UT on 20 March 2015), and is summarized in table 1. This shows that the change in wind contribution is important to allow for, as the reduction in energy from less wind generation amounts to half as much again in terms of the reduction in energy from the loss of PV generation. Although the combination of wind and PV reductions constitutes only about 4% of the concurrent UK national demand for an eclipse, which is a rare event, the identifiable response is useful in electrical supply system planning for other meteorological fluctuations. Table 1. Forecast and observed changes in UK electrical demand and generations from 0848 UT to 1100 UT during the 20 March 2015 partial solar eclipse. energy (MWh) forecast change in PV generation −1020 measured change in wind generation −510 measured change in demand on the National Grid 3040 total demand on the National Grid during eclipse 95 116 4. Conclusion As an astronomical phenomenon an eclipse is almost perfectly predictable from orbital parameters far in advance of the event itself. In contrast, the meteorological conditions and response, which determine the viewing conditions of the eclipse, are far less predictable even until a short time beforehand. The detail of the meteorological response itself, obtained through observations made over a wide area, provides direct information with which to test weather prediction models, improvements in which have much greater societal benefits than just the prediction of eclipse viewing conditions. Such results from a natural experiment represent an important impact of the study of eclipse meteorology. In addition, as a scientific outreach opportunity, an eclipse offers excellent prospects for motivating interested individuals in the viewing zone. For the 20 March 2015 eclipse, which was effectively the first major UK solar eclipse of the social media era, successful and enthusiastic nationwide engagement was obtained. Comparison of models and measurements during the 20 March 2015 eclipse indicate that, beyond the relatively well-predicted changes in temperature in regions with and without cloud, there are consistent changes in wind speed and direction which may provide a partial explanation for the various and disparate suggestions of eclipse-related changes in wind. Although the conceptual picture of Clayton [6] has provided the primary explanatory framework for this possibility, the limitations of this ‘eclipse cyclone’ interpretation, based entirely on surface measurements, are becoming clear. High-resolution numerical simulations show instead that the wind effects can be related to eclipse-induced changes in the atmospheric boundary layer where the surface interacts strongly with the mean flow, and the wind direction is affected by drag over the surface. Beyond the verification and improvement of weather prediction models from the advances in basic understanding of atmospheric phenomena, eclipse meteorology provides a predictive capability for electric power generation networks. The effect of reduction in solar generation is the most obvious quantity to predict, but the effect of wind speed reductions also has to be anticipated. In the UK for the 20 March 2015 eclipse, the reduction in wind generation was half as much again as that from the reduction in PV generation. The combination of eclipse-aware atmospheric models with well-characterized knowledge of generating networks offers promise in testing predictions of changes in national electrical generation from meteorological fluctuations. Because of the expansion in the use of renewables, the need to correctly balance naturally induced transient changes in electricity demand and generation will only increase. In advancing this and the refinement of weather prediction models of great importance to society, the opportunities of the solar eclipse as a unique natural experiment should not be neglected. Supplementary Material ElectricityData_Electronic Supplementary Material Acknowledgements Figure 1 was provided by the Institute of Astronomy at the University of Cambridge (https://www.repository.cam.ac.uk/handle/1810/221308). The measurements presented in figure 2 were originally obtained by the Met Office, provided through the British Atmospheric Data Centre. Figure 3 uses data provided by NASA at http://eclipse.gsfc.nasa.gov/SEgoogle/SEgoogle2001/SE2015Mar20Tgoogle.html. Jeremy Caplin (Energy Forecasting Manager, National Grid) provided data and gave invaluable help with calculating the impact on electric power generation. Data accessibility The data for figure 2 exist in the Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current), provided by the NCAS British Atmospheric Data Centre. (http://catalogue.ceda.ac.uk/uuid/220a65615218d5c9cc9e4785a3234bd0). The National Grid data values on which figure 4 is based are available in the electronic supplementary material. Authors' contributions R.G.H. drafted the manuscript and analysed the data presented. E.H. revised the manuscript. Competing interests None. Funding No external funding was received for this work. ==== Refs References 1 Rømer O 1676 A demonstration concerning the motion of light, communicated from Paris, in the Journal des Sçavans, and here Made English . Phil. Trans. 12 , 893 –894 . 2 Dyson FW , Eddington AS , Davidson C 1920 A determination of the deflection of light by the Sun’s gravitational field, from observations made at the total eclipse of May 29, 1919 . Phil. Trans. R. Soc. Lond. 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==== Front JMIR Hum Factors JMIR Hum Factors JMIR Human Factors JMIR Human Factors 2292-9495 JMIR Publications Toronto, Canada v3i2e21 27528543 10.2196/humanfactors.5083 Original Paper Original Paper Designing for Risk Assessment Systems for Patient Triage in Primary Health Care: A Literature Review Morita Plinio Gomes Jose Nascimento Leonardo Gerbasi Meg Deckard Gloria Khan Shahzad Ali Jatoba Alessandro DSc http://orcid.org/0000-0002-7059-6546 1Fundação Oswaldo Cruz Centro de Estudos Estratégicos Campus Annex Bldg, 10th Fl., Office 1002 Av. Brasil 4036 Rio de Janeiro, Brazil 55 21 3882 9282 ext 2010 55 21 3882 9282 alessandro.jatoba@fiocruz.br Burns Catherine Marie PhD 2http://orcid.org/0000-0002-6182-958X Vidal Mario Cesar Rodriguez Dr Ing 3http://orcid.org/0000-0001-9753-1278 Carvalho Paulo Victor Rodrigues DSc 4http://orcid.org/0000-0002-9276-8193 1 Fundação Oswaldo Cruz Centro de Estudos Estratégicos Rio de Janeiro Brazil 2 University of Waterloo Department of Systems Design Engineering Waterloo, ON Canada 3 Universidade Federal do Rio de Janeiro COPPE Rio de Janeiro Brazil 4 Instituto de Engenharia Nuclear Rio de Janeiro Brazil Corresponding Author: Alessandro Jatoba alessandro.jatoba@fiocruz.br Jul-Dec 2016 15 8 2016 3 2 e2131 8 2015 21 9 2015 22 10 2015 7 7 2016 ©Alessandro Jatoba, Catherine Marie Burns, Mario Cesar Rodriguez Vidal, Paulo Victor Rodrigues Carvalho. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 15.08.2016. 2016 https://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on http://humanfactors.jmir.org, as well as this copyright and license information must be included. Background This literature review covers original journal papers published between 2011 and 2015. These papers review the current status of research on the application of human factors and ergonomics in risk assessment systems’ design to cope with the complexity, singularity, and danger in patient triage in primary health care. Objective This paper presents a systematic literature review that aims to identify, analyze, and interpret the application of available evidence from human factors and ergonomics to the design of tools, devices, and work processes to support risk assessment in the context of health care. Methods Electronic search was performed on 7 bibliographic databases of health sciences, engineering, and computer sciences disciplines. The quality and suitability of primary studies were evaluated, and selected papers were classified according to 4 classes of outcomes. Results A total of 1845 papers were retrieved by the initial search, culminating in 16 selected for data extraction after the application of inclusion and exclusion criteria and quality and suitability evaluation. Conclusions Results point out that the study of the implications of the lack of understanding about real work performance in designing for risk assessment in health care is very specific, little explored, and mostly focused on the development of tools. primary health care triage clinical decision support systems health information systems ==== Body pmcIntroduction In health care, patient triage and risk assessment has always been a major concern [1-4]. Keeping patients safe and ensuring that they receive the right treatment has been studied in different research areas such as psychology [5,6], software engineering [7,8], ergonomics [9-11], and others. These studies of how health care workers make decisions in such complex systems have given some insights into how to design for patient safety. Furthermore, in order to improve patient triage, system designers must understand functional work requirements and constraints in the beginning of the design process; otherwise, it becomes difficult to incorporate human factors after the design is completed [12]. While interacting with a complex physical environment, only a few elements of a problem can be within the span of human conscious attention simultaneously [13]. Moreover, different levels of complexity exist, and it is virtually impossible to reduce the number of variables of a complex system without losing its essential properties [14]. Thus, the objective of this paper was to present a systematic literature review that aimed to identify, analyze, and interpret available scientific evidence related to the contributions of cognitive engineering [15,16] to the design of tools, devices, and work processes to support patient triage and risk assessment. This paper reviews the state-of-the-art research in this theme, identifying gaps in order to suggest further investigation. We explore the topic of decision-making in patient triage, examining the extent to which empirical evidence supports or contradicts the theoretical hypothesis that formative approaches, such as those commonly included in cognitive engineering approaches, are important for the design for the health care domain. The conceptual significance of this paper resides in providing the means to help researchers understand how the disciplines of ergonomics and human factors contribute to the improvement of work situations in health care, enhancing the design of devices and work processes to support effective behaviors [17] in the patient triage and risk assessment process. Methods Databases and Search The authors performed an electronic search on 7 bibliographic databases: ScienceDirect, PubMed, SpringerLink, ACM Digital Library, Wiley Online Library, Scopus, and IEEE Xplore. We considered these databases appropriate because of the quantity of indexed journals and coverage of relevant disciplines such as health sciences, engineering, and computer sciences. The flexibility of their search engines (for combining search terms) and the ability to export results to formats accepted by reference managing software were also considered in the selection of academic databases. Research Question In this literature review we collected, classified, and analyzed recent work related to the topic of risk assessment in health care. We have highlighted scientific evidence on the efforts that have been made to improve the design of technology, medical devices, tools, and processes, to support decision making in patient risk assessment. The following research question motivated this review: What are the contributions, advantages, and disadvantages of using cognitive engineering in the design of software for risk assessment during patient triage? Selection Criteria This literature review included original journal papers published in English between 2011 and 2015, including papers available online in 2015. This time frame was chosen in order to concentrate on more recent contributions and represent the current status of research related to our topic. Conference papers, books, chapters, and reports have not been included in this literature review. Table 1 presents a summary of the search terms and respective variations derived from the research question. We have used free search terms with no controlled descriptors in order to have a broader search. Table 1 Search terms and variations. Term Variations Cognitive engineering Cognitive ergonomics; cognitive systems engineering; cognitive work analysis; cognitive task analysis; human factors; ergonomics Risk assessment Triage; patient triage; risk management Health care Medical care; clinical care; emergency care We used variations of search terms to match eventual synonyms, abbreviations, alternative spellings, and related topics. The authors performed trial searches using various combinations of search terms in order to check the search terms against lists of already known primary studies, using the following search query: (“Human factors” OR “Ergonomics” OR “Cognitive ergonomics” OR “Cognitive engineering” OR “Cognitive systems engineering” OR “Cognitive work analysis” OR “Cognitive task analysis”) AND (“Risk assessment” OR “Triage“ OR ”Patient triage” OR “Risk management”) AND (“Health care” OR “Medical care” OR “Clinical care” OR “Emergency care”). We describe inclusion and exclusion criteria in Textbox 1. Inclusion and exclusion criteria. Inclusion criteria Studies that assess difficulties, critical factors, challenges, or problems in applying human factors and ergonomics in the design of risk assessment support tools or processes in health care Studies that present good practices, lessons learned, and success factors in applying human factors and ergonomics concepts in the design of systems for patient triage and risk assessment Studies presenting models, processes, techniques, or tools to enable the improvement of patient triage and risk assessment in health care Exclusion criteria Studies that do not address any of the research questions Literature reviews In addition to general inclusion and exclusion criteria, the quality of primary studies has been evaluated, as well as their suitability to the presented research questions, in order to investigate whether quality differences provide useful explanations, guide the interpretation of findings, and determine the strength of inferences, as well as how they address the research questions. The quality of a scientific study relates to the extent to which it minimizes bias and maximizes internal and external validity [18]. The following aspects have been evaluated in the study: The objective, research questions, and methods are well defined The contributions are well described The kind of scientific study is clearly stated The source population is identified The interventions or strategies are sufficiently described to allow reasonable replication The outcome is defined and measurable The objectives are accomplished and research questions are clearly answered The study addresses the research question Selected publications were given scores from 1 to 5 for each aspect, where 1 corresponds to “strongly disagree” and 5 “strongly agree.” The sum of the scores determined their methodological quality and suitability to research question as follows: Very high, 100% of the methodological quality aspects met High, 75%-99% met Medium, 50%-74% met Low, 0%-49% met A committee of 4 researchers applied the inclusion and exclusion criteria and performed the assessment of methodological quality of the selected papers. Committee members were doctorate students in systems design engineering and had similar levels of expertise in ergonomics and human factors. A tenured professor, head of the ergonomics and human factors laboratory, supervised the committee during the process. After reading the papers, the committee met in order to present their evaluation. The final score for each criterion for methodological quality represents the consensus of committee members. A study proceeded to data extraction when it met a score of at least 50% on methodological quality. Definition of Outcomes We stratified the selected papers according to 4 classes of outcomes as follows: Class A—design of risk assessment decision support for health care: papers fit this class when the outcomes proposed the implementation of new tools to support decision making in health care risk assessment work situations; Class B—design frameworks, processes, and methods for risk assessment in health care: this class related to publications where outcomes presented frameworks or processes applied to the design of risk assessment work situations in health care environments; Class C—recommendation or implementation of improvements in risk assessment work situations in health care: this class of outcomes was met by papers that suggested transformations in the work place, environment, equipment, or processes in risk assessment work situations in health care; Class D—analysis of the effect of new technology or processes to risk assessment in health care: this class was met by papers that presented studies about the implications of transformations made by new devices or processes for risk assessment in health care environments. Papers selected for data extractions were also classified according to the type of study: case study, experimental study, exploratory study, empirical study, or field study. Results Outcome Statistics Among the 7 databases searched, 5 of them had their results exported to a library in the reference management software Zotero (Roy Rosenzweig Center for History and New Media, George Mason University). The results of 2 of them (IEEE Xplore and SpringerLink) could not be exported to Zotero because of limitations of the search engine but could be exported in CSV format and organized in Microsoft Excel spreadsheets. The steps for paper selection included reading the title, abstract, and full paper. Exclusions on the first and second steps were based on how titles and abstracts of papers indicated relations with the topic we explored in this literature review [18-20]. On the third step, inclusion and exclusion criteria were applied in order to select papers for data extraction. Table 2 presents the results of paper selection steps and the distribution of the papers across the various databases. Table 2 Summary of search results. Database Selected papers Search results, N Selected after title reading Selected after abstract reading Selected after full reading, n Percentage of selected papers, % ScienceDirect 403 55 8 4 1.0 PubMed 249 19 6 5 2.0 SpringerLink 149 27 3 2 1.3 ACM Digital Library 159 18 3 2 1.3 Wiley Online Library 238 22 5 1 0.4 Scopus 33 10 5 1 3.0 IEEE Xplore 614 31 6 1 0.2 Total 1845 182 36 16 0.9 We retrieved 1845 papers in the initial search. After reading the titles and abstracts 36 papers were selected for full reading. Among these, 16 papers met the inclusion and exclusion criteria and were submitted to quality and suitability evaluation, as well as data extraction. Table 3 summarizes the key elements of these selected papers. The outcome code refers to the outcome categories that were defined in the Definition of Outcomes subsection. All papers listed in Table 3 reached 50% or more on the score for methodological quality. Most of the studies are case studies (8 papers), followed by exploratory studies (6 papers). Finally, 2 of the 16 selected papers are experimental studies. We proceeded with the data extraction and the stratification of papers according to the 4 classes of outcomes described in the Definition of Outcomes subsection and listed in the Outcome column of Table 3. In Table 4, the distribution of these outcome types, across the various databases, is presented. The final distribution of papers by the databases was examined as it gives some guidance in terms of where future researchers may wish to look for relevant high-quality papers in the human factors and ergonomics approaches to health care. Table 3 Summary of selected papers. Authors Summary Type of study Outcome McClean et al [26] McClean et al propose the use of a framework for modeling the care process in hospitals in order to improve the assessment of patients’ clinical status and define the length of their stay at the hospital. The paper presents a case study based on data extracted from patients of a hospital in Belfast and demonstrates results of patient survival rates when using their length of stay and destination as outcomes. Case study B Alemdar et al [24] The authors adopt techniques for human behavior analysis from a medical perspective through the analysis of daily activities in terms of timing, duration, and frequency and propose an evaluation method applicable to real-world applications that require human behavior understanding through an experimental study. Experimental study A Hundt et al [25] According to Hundt et al most vulnerability in the design of computerized tools to support physician order entry occur by not considering the work system in which the technology is implemented; therefore, the authors state that the human factors engineering discipline offers a range of approaches for anticipating vulnerabilities, enabling designers to address them before technology implementation. Case study A Card et al [27] Card et al present a case study that shows the rationale for taking a proactive approach to improving health care organizations’ emergency operations. It demonstrates how the Prospective Hazard Analysis Toolkit can drive organizational learning and improve work situations. Case study B Pennathur et al [28] Through a study conducted in hospitals, Pennathur et al propose an information trail model for capturing fundamental characteristics of information that workers in emergency departments create and use for patient care. The model proposed by Pennathur et al addresses our research subquestions by presenting a method for tackling complexity and prevents failures by increasing understanding of the information flow in the process of assessing patient conditions, based on the idea that people in a complex cognitive work system organize information on their own. Exploratory study B Aringhieri et al [30] In their paper, Aringhieri et al present an exploratory study on the ambulance location and management in the Milano area, in which they evaluate the current emergency system performance. According to the authors, despite the availability of technological support, in Italy, the use of resources in emergency departments is based on operators’ experience. Exploratory study C Iakovidis and Papageorgiou [22] Iakovidis and Papageorgiou propose a model and evaluate its effectiveness in two scenarios for pneumonia risk assessment. Their results indicate that the major contribution of the proposed model is that it incorporates additional information regarding the hesitancy of the experts in the definition of the cause-effect relations between the concepts involved in the health care domain. Iakovidis and Papageorgiou state that the proposed approach is capable of modeling real-world medical decision-making tasks closer to the way humans perceive them. Exploratory study A Kong et al [23] Kong et al propose the employment of a belief rule-base inference methodology using the evidential reasoning approach in order to support modeling and reasoning with clinical domain knowledge. According to Kong et al, the approach they propose helps in reducing uncertainties in clinical signs, clinical symptoms, and clinical domain knowledge, which are critical factors in medical decision making. Exploratory study A Cagliano et al [29] Cagliano et al propose a framework that operationalizes Reason’s theory of failures [42] by developing a methodology for investigating health care processes and related risks in patients based on expert knowledge. They apply their approach to the pharmacy department of a large hospital. Exploratory study B Park et al [39] Park et al studied how the design of electronic medical record (EMR) systems affects medical work practices. They analyzed consequences of EMR on clinical work practices and related design issues, such as usability or functionalities of EMR systems, in order to associate the work practices changes led by the EMR system with the actual design of the system. Case study D Hepgul et al [31] Hepgul et al present an examination of the role of clinical expertise and multidisciplinary teams in identifying patients at risk of developing depression, and in monitoring those receiving treatment for the occurrence of depression. Case study C Glasgow et al [40] Glasgow et al propose a comparison between risk estimates from statistical models previously developed and evaluated and risk estimates from the patients’ surgeons. Through this comparison, they are able to evaluate the predictive validity of the decision support model for safer surgery in predicting risk for specific complications. Moreover, they enable the assessment of the validity of this model by correlating its predictions to the ones made by experienced surgeons. Exploratory study D Johnston et al [32] Johnston et al describe the importance of overcoming hierarchical barriers between junior and senior surgeons as a crucial success factor for prioritization of health care. Case study C Ferguson and Starmer [35] Ferguson and Starmer highlight the role of expertise in risk assessment in health care facilities and evaluate the effects of framing risks on the improvement of interpretation in such environments. Experimental study C Norris et al [33] In their paper, Norris et al describe a project that takes a systems approach to identify risks, engage health care staff and patients, facilitate ideas, and develop new designs for the bed-space in order to demonstrate the application of human factors to a complete design cycle. Case study C Hastings et al [34] Hastings et al propose a method to classify older adults in the emergency department according to health care use, by examining associations between group membership and future hospital admissions. Case study C Table 4 Publications classified according to outcomes, distributed by databases. Database Outcomes A Design of risk assessment  decision support for health care B Design frameworks,  processes, and methods for risk assessment in health care C Recommendation or  implementation of improvements in risk assessment work situations in health care D Analysis of the effects of new technologies or processes to risk assessment in health care ScienceDirect 1 1 1 1 PubMed - - 4 1 SpringerLink - 1 1 - ACM Digital Library 1 1 - - Wiley Online Library - 1 - - Scopus 1 - - - IEEE Xplore 1 - - - Total 4 4 6 2 Percentage, % 25 25 38 12 In the next subsections, we present an overview of the selected publications, describing how they address our research questions. Design of Risk Assessment Decision Support for Health Care Cognitive ergonomics is concerned with mental processes, such as perception, memory, reasoning, and motor response, as they affect interactions among humans and other elements of a system [21]. Thus, Iakovidis and Papageorgiou [22] and Kong et al [23] explore methods for modeling human performance to increase understanding of context and domain, including aspects of memory usage, and reasoning. With this approach, they try to bridge some gaps between analysis and the design of health care decision support tools. Regarding our research question, Iakovidis and Papageorgiou propose the use of fuzzy cognitive mapping, which includes concepts that can be causally interrelated and represent uncertain and imprecise knowledge through fuzzy logic. These concepts encompass tools for modeling and simulation of dynamic systems, based on domain-specific knowledge and experience. The analysis of the domain and cause-effect relations among the system provides additional clues regarding the experts’ knowledge and way of thinking, which increases understanding of work conditions. Kong et al suggest that the complexity of inference mechanisms and difficulties in representing domain knowledge hamper the design of clinical decision support systems such as the ones used in patient risk assessment. Therefore, representation of human reasoning and uncertain medical knowledge are critical areas that require refined methodologies and techniques. The paper by Alemdar et al [24] also addresses the challenges in understanding information flow during work performance in order to enable the construction of a health conditions assessment device based on models of machine learning. They also explore the implications of poor understanding of how work is performed in technology design, and its effect on workflows and processes. Hundt et al [25] highlight that proactive risk assessment methods demand high commitment by team members, and their effectiveness for health information technology implementations has not yet been examined. Although the physician order entry is not a risk assessment process per se, managing patients involves the evaluation of their health conditions and the prioritization of treatment, which is similar to the patient triage process. Design Frameworks, Processes, and Methods for Risk Assessment in Health Care Papers organized in this class of outcomes support the idea that work in health care involves significant information-based cognitive activities; however, it’s mostly supported by exogenously designed information systems. This means that gaps of information about the domain and insufficient input from end users on their needs and practices might bring limitations to the design process. McClean et al [26] aim at identifying better pathways to patients based on their characteristics such as age, gender, and diagnosis. Therefore, determining the pathway of the patient enables the assessment of patients’ risks. According to Card et al [27], risk management in health care is largely concerned with routine risks that stem from everyday service provision, which makes it possible for health care organizations to learn from experience and make risk management more effective. However, regarding emergency operations, workers do not often use previous experience to improve risk management processes. Pennathur et al [28] study situation awareness during diagnosing—starting with the identification of patients’ complaints and laboratory tests results—as the major concern in designing for decision support in patient triage. Understanding the way workers interpret quantitative and qualitative information from patient history, physical conditions, and many other aspects is essential in generating diagnosis and treatment plans. Moreover, there is strong need for understanding the triggering events of medical errors as well as their correlations in order to decrease the probability of occurrence [29]. Recommendation or Implementation of Improvements in Risk Assessment Work Situations in Health Care Papers in this class of outcomes demonstrate some approaches that aim at transforming work situations in patient triage. Many approaches could be found such as mathematical programming, resilience engineering, process management, and so on. We highlight the work of Aringhieri et al [30], in which they state that huge amounts of data about health care workers' activities are never used for improving the system performance and the prioritization of resources. Thus, they suggest that modeling, simulation, and mathematical programming can be successfully applied to an emergency service, in order to evaluate its current performance and to provide suggestions to improve the way resources are prioritized. We also highlight some studies we present in this section that show the differences between the actions of experienced and inexperienced workers as potential object for analysis in order to enable the design of suitable tools for supporting patient triage [31,32]. Understanding human performance and context variables involved in transferring information from junior staff to senior staff—and, eventually, to nursing staff—is an essential aspect in designing work processes in patient triage, as deficiencies in this process may occur because of not only lack of experience but also unavailability of information about patient conditions, poor risk assessment guidelines, communication failures, and lack of consideration to the human, technical, and patient factors involved in this critical process. Moreover, we find that some authors seek knowledge and understanding into the health care processes and studying patterns through observations carried out jointly by the research teams in order to ensure multidisciplinary perspectives and enable the improvement of work situations and the design of effective support devices [33-35]. We can see similar approach in use for field researches in ergonomics and human factors [17,36-38]. Analysis of the Effects of New Technologies or Processes to Risk Assessment in Health Care The 2 papers in this category [39,40] study how human factors enable the analysis of workers’ strategies and workload in patient triage situations. For example, according to Park et al the use of the electronic notes led to an increased workload for residents because of the longer charting times and the shifted responsibility from workers. Moreover, according to Glasgow et al optimal strategy for patient risk mitigation might be identifying risk at the individual level, although minimal knowledge exists on the accuracy of risk assessment with or without decision support tools. These studies support the claim that the design of technological devices for medical use should not necessarily follow the design adopted by professionals in their current physical notes, as the social nature of clinical work might be hampered if the specific documenting locations, the medium, and the information needed to complete tasks are not properly addressed. Discussion Principal Findings Among the 20 papers discarded after full reading, 11 of them did not address the research question. A total of 2 publications were discarded because of low methodological quality according to the aspects we had defined. The 2 databases that presented more search results initially were IEEE Xplore (614 publications) and ScienceDirect (403 publications). However, in the final assessment, more relevant papers were found in the PubMed and ScienceDirect databases. This may suggest that other researchers looking to obtain high-quality papers in the areas of human factors and ergonomics in health care would be best served to approach these sources first. We believe that the broad range of the ScienceDirect database contributed to a large number of references found, as well as a large number of relevant papers in the final selection. The ScienceDirect database collects publications from diverse fields, from physical sciences and engineering, life sciences, health sciences, and social sciences and humanities. The PubMed database is relatively more specialized, concentrating on publications from the life sciences and biomedical topics—it uses the Medical Subject Headings (MeSH) controlled vocabulary [41]. Our results suggested that there is some interest in the literature in understanding work performance in patient risk assessment. Furthermore, many different approaches have been taken to try and understand the human cognitive work of patient risk assessment. A broad definition of cognitive engineering was applied here, looking for papers that looked at cognition or work processes, and the perspective was broader than more typical cognitive engineering methods. There were more findings in sources specific to medical applications, although some relevant work was still found in engineering and computer science sources. A total of 2 papers proposed human factors methods for coping with complexity in risk assessment but were not directly applicable to health care and, therefore, discarded. This finding points out the significance of studies about judgment and uncertainty in risk assessment in multiple domains. It also shows that risk assessment in health care presents many opportunities for the use of human factors and ergonomics to improve work situations. We found that the most selected papers are related to recommendations for improvement (6 publications), decision support tools (4 publications), and design methods (4 publications), while 2 publications explore the effect of new technologies and processes. Recommendations for improvements typically seek transformations in work situations in order to help people work better, more comfortably, mitigating harmful situations, and reducing problems to workers. Studies that examined decision support tools presented the general aspects of developing technology to support decision making in patient triage, such as guidelines, implementation aspects, and milestones in the adoption of decision support tools for patient triage. Design methods refer to techniques, concepts, and modeling tools for coping with complexity. Some approaches taken by our selected papers related to each other to some extent, especially in developing an understanding of human behavior in complex systems and in finding ways to improve these work situations. For example, some papers presented technologies for patient triage, while discussing how some technologies affect the workload for practitioners. Similarly, design methods were often related to technology as some papers presented design techniques, concepts, and tools that enable the identification of opportunities for information technology or the design of medical decision support. Moreover, opportunities for information technology are, essentially, opportunities for improvement in workflow and practice. Therefore, the results showed that most related research explored the potential of cognitive engineering to provide tools to improve the design for complex work situations such as risk assessment in health care work environments, although the effects of these applications on human performance have not been extensively assessed. Conclusions This literature review gathered recent contributions to multiple areas, from engineering to biomedical, that cognitive engineering gives for the design of tools for health care risk assessment, especially by contributing knowledge about work performance in such settings. In this paper, we presented information about how this research topic has been approached, results, accomplishments, and opportunities for further research. Papers selected for review were very diverse in terms of the aims of the study, the underlying theoretical frameworks and methodologies used, reflecting how interdisciplinary our research topic is, and the wide range of research backgrounds employed in finding answers to our research question. Furthermore, results included studies from several areas such as medicine, engineering, and computer science. We did not present specific research question associated with each area; therefore, some papers might have been excluded for not addressing the research question, although they might have explored our research theme to some extent. An opportunity for further studies would be to expand the search to include other contributions of human factors and ergonomics to the design for health care—rather than specific contributions to patient risk assessment—as well as the contributions of other areas to the risk assessment in health care. This could address important aspects, for example, which areas have made recent contributions to the improvement of health care services, and subsequently to the risk assessment in health care environments. Moreover, as risk assessment is a topic present in many areas, further research might be interesting to collect studies about the design for risk assessment in other areas rather than health care. We would like to thank the Group of Ergonomics and New Technologies/Federal University of Rio de Janeiro. This study was partially funded by the Science Without Borders Program/Brazilian National Council for Scientific and Technological Development. 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==== Front J Med Internet Res J Med Internet Res JMIR Journal of Medical Internet Research 1439-4456 1438-8871 JMIR Publications Toronto, Canada v18i8e220 27526637 10.2196/jmir.6153 Original Paper Original Paper Efficacy of Internet-Based Self-Monitoring Interventions on Maternal and Neonatal Outcomes in Perinatal Diabetic Women: A Systematic Review and Meta-Analysis Eysenbach Gunther Rasekaba Tshepo Furler John Lau Ying RN, PhD http://orcid.org/0000-0002-8289-3441 1National University of Singapore Alice Lee Centre for Nursing Studies Level 2, Clinical Research Centre Block MD11, 10 Medical Drive Singapore, 117597 Singapore 65 66011603 65 67767135 nurly@nus.edu.sg Htun Tha Pyai MBBS, MPH 1http://orcid.org/0000-0001-5567-0392 Wong Suei Nee BSc (Hons), MSc 2http://orcid.org/0000-0003-3086-2480 Tam Wai San Wilson BSC, MPhil, PhD 1http://orcid.org/0000-0003-0641-3060 Klainin-Yobas Piyanee BSN, MSN, PhD 1http://orcid.org/0000-0003-2581-4572 1 National University of Singapore Alice Lee Centre for Nursing Studies Singapore Singapore 2 National University of Singapore Medical Resource Team, National University of Singapore Libraries Singapore Singapore Corresponding Author: Ying Lau nurly@nus.edu.sg 8 2016 15 8 2016 18 8 e2205 6 2016 30 6 2016 11 7 2016 20 7 2016 ©Ying Lau, Tha Pyai Htun, Suei Nee Wong, Wai San Wilson Tam, Piyanee Klainin-Yobas. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 15.08.2016. 2016 https://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. Background Self-monitoring using the Internet offers new opportunities to engage perinatal diabetic women in self-management to reduce maternal and neonatal complications. Objective This review aims to synthesize the best available evidence to evaluate the efficacy of Internet-based self-monitoring interventions in improving maternal and neonatal outcomes among perinatal diabetic women. Methods The review was conducted using Cochrane Central Register of Controlled Trials, PubMed, EMBASE, Cumulative Index to Nursing and Allied Health Literature, PsyINFO, Scopus, and ProQuest Dissertations and Theses to search for English-language research studies without any year limitation. A risk of bias table was used to assess methodological quality. Meta-analysis was performed with RevMan software. Cochran Q and I2 tests were used to assess heterogeneity. The overall effect was assessed using z tests at P<.05. Of the 438 studies identified through electronic searches and reference lists, nine experimental studies from 10 publications were selected. Results Half of the selected studies showed low risk of bias and comprised 852 perinatal diabetic women in six countries. The meta-analysis revealed that Internet-based self-monitoring interventions significantly decreased the level of maternal glycated hemoglobin A1c (z=2.23, P=.03) compared to usual care among perinatal diabetic women at postintervention. Moreover, Internet-based self-monitoring interventions significantly decreased the cesarean delivery rate (z=2.23, P=.03) compared to usual care among the mixed group at postintervention. Conclusions This review shows neonatal or other maternal outcomes are similar between Internet-based self-monitoring interventions and usual diabetes care among perinatal diabetic women. The long-term effects of the intervention must be confirmed in future studies using randomized controlled trials and follow-up data. Internet pregnancy in diabetics interventions meta-analysis ==== Body pmcIntroduction Diabetes mellitus (DM) is one of the most common complications of pregnancy; preexisting diabetes mellitus (type 1 or type 2) and gestational diabetes mellitus (GDM) affect approximately 2.5% to 2.7% and 4.6% to 8.0% of all pregnant women, respectively [1]. Both GDM and preexisting diabetes are associated with increased medical costs and perinatal morbidity [1]. Existing interventions must be improved considering the increasing global incidence of diabetic pregnancy with serious perinatal outcomes [2]. Self-monitoring intervention is important in reducing maternal and neonatal complications related to diabetic pregnancies, both in cases of preexisting diabetes [3] and GDM [4]. Self-monitoring refers to systematic observation and recording of ongoing goal-directed activities [5] based on self-regulation theory [6]. Self-regulation involves self-awareness of the current condition of an individual [7]. Awareness could trigger a self-evaluation response involving the interpretation of one’s condition against a goal or standard; after self-evaluation, a series of responses could be determined through self-adjustment and self-reinforcement [1,6]. Self-monitoring capitalizes on this motivation to achieve glycemic control [8], improve weight management [9], and reduce hospitalization and readmission rates [10]. Self-monitoring using the Internet offers new opportunities to engage participants in self-management. A previous study [11] suggested that self-monitoring using Internet-based interventions and face-to-face interventions elicited similar outcomes among the patients. Development of Internet-based interventions by using theory-based methods could promote substantial changes in the health behavior of a patient [12]. The Internet offers a diverse range of strategies for exchanging information and gaining knowledge [13] and thus can provide interactive ways to integrate communication with sensor-based systems (glucometer and pedometer) for transmitting information to a device or computer [14,15]. Sensors are used to record and transmit data to a computer, which then transmits the data to the provider and provides personalized/tailored feedback to the individual [14,15] regarding self-monitoring compliance with treatments and self-adjustment to diet, activity, and weight management. Internet-based interventions employ a tracking system to improve self-reinforcement by using reminders (cues to action) [16], alerts [14], or graphic progress [17] through text messages (short message service, SMS) and email. Asynchronous and synchronous interactions generate identical interactional benefits [18]. Peer-support interactivity allows women to interact with one another with a pseudonym [15]; this process could empower women to take ownership of their well-being and initiate resolutions for issues they are encountering, thereby contributing to a sense of increased self-efficacy among perinatal diabetic women [19]. A longitudinal follow-up is important to test the sustainability of self-monitoring patterns over an extended period [20]. The advantages of using the Internet to deliver interventions include low cost, easy distribution, and convenient delivery to multiple locations at specific times [4,21]. Internet access is increasingly used as an educational and supportive source of information for perinatal women [22,23]. Internet-based interventions are rapidly developed with increased access to instant cyber connectivity; however, the effect of Internet-based self-monitoring on improving maternal and neonatal outcomes among perinatal diabetic women remains unclear. Meta-analysis is used to document the application of Internet-based self-monitoring interventions among general diabetic population [24-26]. However, only a few studies were conducted on perinatal diabetic women. Four reviews focused on the use of technologies to evaluate healthy pregnant women in terms of maternal outcomes [27], women with complicated pregnancies in terms of cost effectiveness [28], a mixed group of patients (with type 1 DM and GDM) in terms of maternal-neonatal outcomes [29], and patients with GDM in terms of maternal outcomes [30]. These studies reported mixed results, did not include ongoing studies without outcomes [27], lacked systematic searching strategies [28,29], and evaluated limited studies (n=3) [30]. None of the studies focused on Internet-based self-monitoring approaches. Hence, further research must be performed, particularly in light of the rapid improvements in technologies worldwide. This review aims to systematically assess studies that examined Internet-based self-monitoring interventions for improving maternal and neonatal outcomes among perinatal diabetic women. Methods This study was performed in accordance with the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [31]. The protocol is registered to the PROSPERO database (CRD42016034142). Eligibility Criteria The full inclusion and exclusion criteria for the systematic review are described in Multimedia Appendix 1. Studies were included if they met the following criteria: Population: perinatal women aged 18 years and older with GDM, type 1 DM, and/or type 2 DM; Interventions: interact with perinatal diabetic women to undertake one or more of the following components associated with self-awareness, self-interpretation, self-adjustment, or self-reinforcement of glycemic level, physical activities, dietary intake, weight management, or medication adherence [7,10] by using the Internet; Comparison: usual diabetes care as control group; Outcomes: primary outcomes included glycated hemoglobin A1c (HbA1c) level, cesarean delivery, neonatal birth weight, and neonatal hypoglycemia at postintervention; secondary outcomes included biological outcomes (fasting blood glucose, weight gain, and change in body mass index [BMI] or weight), cognitive outcomes (satisfaction rate, empowerment, self-efficacy, or health-related quality of life), behavioral outcomes (insulin treatment rate or compliance rate with self-monitoring), emotional outcomes (depression or stress), and neonatal outcomes (large for gestational age or macrosomia) at postintervention; and Type of design: experimental studies that were either a randomized controlled trial (RCT) or controlled clinical trial (CCT). We excluded studies if they were nonexperimental, qualitative, protocol, or conference papers regarding general diabetic populations. Search Strategy The search strategy aimed to find published or unpublished studies written in English. No restriction was applied to the search performed from inception until February 16, 2016 in the following electronic databases: Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Scopus, and ProQuest Dissertations and Theses. Index and keyword terms were used (Multimedia Appendix 2). The keywords were exploded and truncated following the syntax rules of each database. Unpublished trials of relevance to the review were searched from the Clinical Trials Registry (www.clinicaltrials.gov). Unpublished data were requested if eligible trials maximized the scope of the search. Finally, we searched the reference lists of the included studies and relevant previous reviews to check for additional eligible studies. Study Selection Two authors (LY and TP) independently screened the titles and abstracts of the identified references from the literature search to identify potentially eligible studies. The full texts of the remaining references were evaluated. Ineligible reports were excluded based on inclusion criteria, and the reasons for exclusion were recorded. A third reviewer (KY) resolved disagreements between the two reviewers regarding inclusion of a study. Quality Assessment After identifying studies that fulfilled the selection criteria and verifying their eligibility by reading the completed articles, the studies were subjected to quality assessment. The quality of the studies was independently judged using criteria for determining bias in intervention studies recommended by the Cochrane Handbook for Systematic Reviews of Interventions [32]. The following indicators of internal validity specific to the methodology of RCT were collected: (1) random sequence generation (selection bias), (2) allocation concealment (selection bias), (3) blinding of participants and personnel (performance bias), (4) blinding of outcome assessment (detection bias), (5) incomplete outcome data (attrition bias), and (6) selective reporting (reporting bias) [32]. Assessment related to risk biases was assigned a judgment of “low risk,” “high risk,” or “unclear risk” of bias. One reviewer (LY) reviewed all studies with a subset reviewed by a second reviewer (TP). Disagreements were settled through discussion or consulting a third reviewer (KY). Data Extraction Two of the authors (LY and TP) extracted relevant data from all included articles. The following variables were obtained using structured data extraction items based on setting, country, design, population, gestation, age, intervention, control, sample size, outcomes, attrition, and intention-to-treat (ITT) analysis. The details of self-monitoring interventions were extracted based on components (glycemic, diet, weight gain control, physical activities, or/and medication adherence), transmission (asynchronous or asynchronous), functionality, facilities, interactivity, provider, peer support, duration, and follow-up. The two authors (LY and TP) thoroughly reviewed the summary tables for accuracy and relevance. When relevant data were missing or questionable in both published and unpublished trials, the authors were contacted for verification and to obtain additional information. Among 59 full-text articles, 10 were not clear because they had insufficient details (n=2) or no (n=8) outcomes. Although 10 authors were approached, none responded to our queries. Therefore, we excluded these 10 studies in the review. Statistical Analysis RevMan software (Review Manager version 5.3 for Windows from the Nordic Cochrane Center, the Cochrane Collaboration, 2014) was used for meta-synthesis. Risk ratio (RR) was used as the effect measure for dichotomous outcome with Mantel-Haenszel method. Mean difference was used for continuous outcomes with inverse-variance method. Heterogeneity between studies was evaluated using Cochran Q (chi-square test) and I2 statistics. The statistical significance for heterogeneity using the chi-square test was set as P<.10. The I2 statistic was applied to describe total variations in study estimates because of heterogeneity. Heterogeneity degree was estimated using I2 by setting 0%, 25%, 50%, or 75% for no, low, moderate, and high heterogeneity, respectively [33]. The fixed-effect model was used in cases without significant heterogeneity (P>.10), and the DerSimonian and Laird random-effects model was used in cases with heterogeneity among the studies (P<.10) and I2 values of more than 50% [33]. Subgroup analysis was performed to explore the source of heterogeneity, and the predefined subgroup was the type of DM. Results Figure 1 shows the selection process (PRISMA flow diagram). A total of 438 studies were identified from the initial database search and reference lists. Of these studies, 37 articles were curated using Endnote to remove duplicates. Subsequently, 401 studies were included for screening and 332 articles were excluded based on analysis of text words in titles and abstracts. In all, 69 full-text articles were retrieved, reviewed, and selected based on relevance and quality for eligibility. Of these, 59 articles were excluded because of the following: nonexperimental nature; type of protocol; nondiabetic perinatal women as subject; not using Internet approach; lack of self-monitoring component; reported qualitative, unclear, insufficient, or no outcomes; and Internet approach employed on diabetes screening, reminder, data collection. Finally, nine studies from 10 publications were identified for inclusion in this systematic review. Figure 1 PRISMA flow diagram of article selection procedure. Study Characteristics This meta-analysis included nine studies with 852 participants conducted across four countries (Table 1), which included the United States (n = 5) [15,16,34-36], Spain (n=2) [14,37,38], Italy (n=1) [39], and Ireland (n=1) [40]. All these studies were published articles. Research was conducted between 2007 [36] and 2015 [16]; 2015 had the highest number of publications (n=3) [14,16,40]. Seven of the studies used RCT designs and two used CCT designs [14,39]. The target populations were perinatal women with GDM or impaired glucose tolerance (n=5) [15,35,36], mixed group (n=4) [14,16,39], type 1 DM (n=0), and type 2 DM (n=0). The sample sizes varied among the nine studies and ranged from 19 [41] to 235 [39]. Nine studies reported more than one outcome. Attrition rates ranged from 2% [14,37,38] to 32% [16]. None of the studies used ITT analysis, and eight studies were supported by grants. Table 1 Characteristics of the nine selected studies (10 publications).a Author, year [ref] Setting/Country Design Population/gestation/age, mean (SD) Intervention N Duration (weeks) Outcomes Attrition rate, % Bartholomew et al 2015 [16]b Antenatal clinic in Hawaii, USA RCT GDM or type 2 DM; <30 w; 33.2 (5.4) Mobile phone, Internet technology (CIT) I: 50; C: 50 3 Fasting and 2-hour postprandial blood compliance rate with SMBG; satisfaction rate I: 20; C: 32 Carral et al 2015 [14]b GDM unit in Cadiz, Spain CCT GDM, type 1 or 2 DM; <30 w; 33.8 (4.6) Web-based telemedicine system I: 40; C: 64 — HbA1c (%); weight gain; cesarean delivery rate; insulin treatment rate; neonatal birth weight; large for gestational age; neonatal hypoglycemia I: 5; C: 14 Dalfra et al 2009 [39] 12 Diabetes clinics in Italy CCT GDM or type 1 diabetes; <30 w; 33.8 (4.6) Telemedicine with Glucobeep server I: 105; C:130 10 HbA1c (%); weight gain; cesarean delivery rate; insulin treatment rate; neonatal birth weight; macrosomia; SF36; CES-D; DSS; DHDS Total: 15; I:—; C:— Given et al 2015 [40]b 2 Diabetes clinics in Ireland RCT GDM or IGT; 24-28 w; I: 33.5 (4.2), C: 30.1 (5.5) Web-based telemedicine system I: 24; C: 26 12 HbA1c (%); cesarean delivery rate; insulin treatment rate; neonatal birth weight; macrosomia; neonatal hypoglycemia; satisfaction rate I: 12.5; C:15.4 Homko et al 2007 [36]b Antenatal clinic or one of its satellites in Philadelphia, PA RCT GDM; <33 w; 18-45, I: 29.8 (6.6), C: 29.2 (6.7) Internet-based telemedicine system using ITSMyHealthfile and Lassoweb data engine I: 34; C: 25 — HbA1c (%); FBS (mg/dL); cesarean delivery rate; DES; neonatal birth weight; large for gestational age; neonatal hypoglycemia I: 5.8; C:13.8 Homko et al 2012 [35]b Antenatal clinics (2) in Philadelphia, PA RCT GDM; <33 w; 18-45, I: 30.3 (6.0), C: 30.0 (7.5) Internet-based telemedicine system with automatic telephone option I: 40; C: 40 — FBS (mg/dL); cesarean delivery rate; neonatal birth weight; large for gestational age; neonatal hypoglycemia I: 10; C: 5 Kim et al 2012 [15]b University health system in Michigan RCT GDM within 3 years; >18 years (—) Web-based pedometer program I: 28; C: 21 13 Change in weight; change in BMI; change in self-efficacy for weight and activity I: 9.5; C:17.9 Nicklas et al 2014 [34]b Hospital in Boston, MA RCT GDM; postnatal; 18-45 (—) Web-based lifestyle intervention I: 36; C: 39 24-40 Change in weight; change in BMI I: 8.3; C:10.3 Pérez-Ferre et al 2010a,b [37,38]b Diabetes unit of a hospital in Madrid, Spain RCT GDM; <28 w; I: 33.3 (5.6), C: 34.2 (5.2) Web-based telemedicine system I: 50; C: 50 12 HbA1c (%); weight; weight gain; cesarean delivery rate; neonatal birth weight; large for gestational age; neonatal hypoglycemia I: 2.0; C: 4.0 a All studies had a usual treatment control group and none used ITT. —: Information not mentioned in article; BMI: body mass index; C: control group; CCT: controlled clinical trial; CES-D: Center for Epidemiologic Studies Depression Scale; DES: Diabetes Empowerment Scale; DHDS: Diabetes Health Distress Scale; DSS: Diabetes-related Stress Scale; FBS: fasting blood sugar; GDM: gestational diabetes mellitus; HbA1c: glycated hemoglobin A1c; I: intervention group; IGT: impaired glucose tolerance; ITT: intention-to-treat analyses; OGTT: Oral Glucose Tolerance Test; RCT: randomized controlled trial; SF36: SF-36 Health Survey; SMBG: self-monitoring of blood glucose. b These studies had grant support. Study Quality The summary of risk of bias is presented in Figure 2, and the risk of bias graph is shown in Multimedia Appendix 3. Seven of nine studies had adequate sequence generation for randomization. Two studies [16,34] had adequate allocation concealment. None of the studies implemented blinding of participants. Three studies [15,34,37,38] implemented blinding of outcome assessment. All studies addressed low-risk bias concerning incomplete outcome data. Eight had low-risk bias for selective reporting. Figure 2 Risk of bias summary. Description of Internet-Based Self-Monitoring Interventions Detailed elements of the Internet-based self-monitoring interventions are presented in Multimedia Appendix 4. The components of the self-monitoring interventions included glycemic control (n=8), diet control (n=7), physical activities (n=5), weight control (n=3) [15,34,39], and medication adherence (n=7). Functionalities of the interventions included system alert and reminder (n=4) [14,16,35,40], graphical progress (n=2) [15,37,38], and uploading, entering, and tracking own information (n = 3) [16,34,36] using website (n = 9), phone (n = 7), SMS text message (n = 5), email (n = 6), and animated video (n = 1) [34] that integrated communication with glucometer (n = 4) and pedometer (n = 1) [15]. The majority of the interventions used asynchronous communication (n=6), and three used synchronous communication [15,39,40] through two-way (n=9) feedback communication. The providers of the intervention were physicians (n = 7), nurses (n = 4), dietitians (n=1) [34], telemedicine service provider (n=1) [40], and study staff (n = 1) [15]. Only one intervention consisted of peer support using an online forum [15]. The duration of the intervention varied among the nine studies and ranged from 3 weeks [16] to 40 weeks [34]. Three of the studies [14,16,34] had follow-up after intervention. None of the studies reported using theoretical or conceptual framework to design their interventions. Efficacy of Internet-Based Self-Monitoring Interventions on Maternal Outcomes Five studies [14,36-39,40] assessed the efficacy of interventions among 508 perinatal women by using HbA1c levels as the outcome. The meta-analysis revealed that the intervention significantly improved HbA1c levels (mean difference −0.12, 95% CI −0.22 to −0.02), as determined using inverse-variance method and fixed-effects model (I2=0%, P=.69; Figure 3). A nonsignificant P value for the Cochran Q statistic indicated that the selected studies were homogeneous. The overall effect of intervention on HbA1c was significant (z=2.39, P=.02). Subgroup analyses were performed to compare the effects of the interventions on HbA1c between the GDM (n = 3) [36-38,40] and mixed groups (n = 2) [14,39]. However, no significant effect was found for subgroup differences (P=.73). Six studies [14,35-39,40] assessed cesarean delivery rate as outcomes of interventions among 526 perinatal women, and the meta-analysis showed low heterogeneity (I2= 20%, P=.28) (Figure 4). Moreover, the interventions did not significantly improve cesarean delivery rate for overall effect (RR=0.84, 95% CI 0.68-1.05; z=1.55, P=.12). Two subgroup analyses using the Mantel-Haenszel method and fixed-effects model revealed that the interventions significantly decreased the cesarean delivery rate among the mixed group (RR=0.73, z=2.23, P=.03) in two studies [14,39], but had no effect among the GDM group (RR=1.05, z=0.30, P=.77) in four studies [35-38,40]. No significant subgroup differences were found (P=.10). None and low heterogeneity were found between subgroups of women with GDM (I2= 0%, P=.97) and the mixed group (I2= 23%, P=.27). Figure 3 Forest plot of mean difference (95% CI) in change of HbA1c (%) for the Internet-based self-monitoring intervention and control groups. IV: inverse variance. Figure 4 Forest plot of risk ratio in change of cesarean delivery rate for the Internet-based self-monitoring intervention and control groups. Efficacy of Internet-Based Self-Monitoring Interventions on Neonatal Outcomes Figure 5 shows the pooled meta-analysis results of six articles that determined the effect of interventions on neonatal body weight among 582 perinatal women. The meta-analysis showed low to moderate heterogeneity (I2= 41%, P=.13). Four studies [35-38,40] of GDM group and two studies [14,39] of mixed group revealed similar neonatal weight (mean difference=27.30, z=0.62, P=.54) between the Internet-based self-monitoring intervention and control groups. Two subgroup analyses were performed and no significant differences were found between intervention and control groups either in the GDM group (mean difference=92.21, z=1.47, P=.14) or the mixed group (mean difference=–36.42, z=0.59, P=.56). The heterogeneity of GDM group (I2=39%, P=0.18) and mixed group (I2=30%, P=.23) ranged from low to moderate. The test for subgroup differences was not significant (P=.14). Figure 6 shows the pooled meta-analysis results of five studies on neonatal hypoglycemia among 379 women. The intervention group demonstrated no significant difference on the overall effect (RR=1.09, z=0.24, P=.81) compared with the control group, as assessed using the Mantel-Haenszel method and fixed-effects model. No heterogeneity was found in the mixed group (I2= 0%, P=.85) and overall result (I2= 0%, P=.93). The result of subgroup analysis was not different (P=.79) between the mixed and GDM groups. Table 2 summarizes the efficacy of the intervention on maternal outcomes including fasting blood sugar [35,36], weight gain [14,37,38], changes in BMI and weight [15,34], insulin treatment rate [14,37,38], satisfaction rate [16,40], compliance rate with self-monitoring of blood glucose [16], health-related quality of life [39], depressive symptoms [39], diabetic-related stress [39], diabetes health distress [39], diabetes empowerment [36], and change in self-efficacy for weight and activity [15], as well as neonatal outcomes including large for gestational age [14,35-38] and macrosomia [39,40]. The outcomes were not significantly different between intervention and control groups. Although the effects of diabetes-related stress and diabetes empowerment significantly differed in the Diabetes-related Stress Scale scores (P=.02) [39] and Diabetes Empowerment Scale scores (P=.003) [36], the findings of the single study could not contribute sufficient evidence to draw conclusions. The heterogeneity (I2) ranged from 0% in the pooled meta-analysis of three studies on weight gain [14,37,38] to 95% from the pooled meta-analysis of two studies on satisfaction rate [16,40] by using fixed- and random-effect models, respectively. Although we identified substantial heterogeneity (I2>50%), we encountered difficulty in investigating the result by using subgroup and sensitivity analyses for the two to three studies that indicated changes in BMI or weight [15,34], insulin treatment rate [14,37-39], and satisfaction rate [16,40]. Figure 5 Forest plot of mean difference (95% CI) in change of neonatal body weight (grams) for the Internet-based self-monitoring intervention and control groups. IV: inverse variance. Figure 6 Forest plot of risk ratio for change in neonatal hypoglycemia rate for the Internet-based self-monitoring intervention and control groups. Table 2 Efficacy of Internet-based self-monitoring interventions on other maternal and neonatal outcomes.a Outcomes Studies included, n RRb/MDc (95% CI) Overall effect Heterogeneity Model z P I 2 P Maternal outcomes Fasting blood sugar 2 [35,36] –0.66c (–4.28, 2.96) 0.36 .72 44% .72 Fixed Weight gain 3 [14,37,38] –0.48c (–1.44, 0.47) 0.99 .32 0% .98 Fixed Change in BMI 2 [15,34] –0.91c (–1.91, –0.09) 1.77 .08 64% .09 Random Change in weight 2 [15,34] –2.53c (–5.10, –0.04) 1.93 .05 65% .09 Random Insulin treatment rate 3 [14,37-39] 1.06b (0.56, 2.02) 0.19 .85 71% .03 Random Satisfaction rate 2 [16,40] 1.75b (0.40, 7.58) 0.74 .46 95% <.001 Random Compliance rate with self-monitoring of blood glucose 1 [16] 1.02b (0.87, 1.20) 0.24 .81 SF-36 Physical component 1 [39] –2.2c (–4.50, 0.10) 1.88 .06 NA NA NA SF-36 Mental component 1 [39] 2.10c (0.75, 4.95) 1.44 .15 NA NA NA CES-D 1 [39] 1.50c (–1.35, 4.35) 1.03 .30 NA NA NA DSS 1 [39] 4.10c (0.75, 7.45) 2.40 .02 NA NA NA DHDS 1 [39] 4.90c (–0.20, 10.00) 1.88 .06 NA NA NA DES 1 [36] 0.40c (0.14, 0.66) 3.00 .003 NA NA NA Change in self-efficacy for weight 1 [15] 2.79c (–2.57, 8.15) 1.02 .31 NA NA NA Change in self-efficacy for activity 1 [15] –1.40c (–5.02, 2.22) 0.76 .45 NA NA NA Neonatal outcomes Large for gestational age 4 [14,35,36,37,38] 1.39b (0.81, 2.40) 1.19 .23 0% .68 Fixed Macrosomia 2 [39,40] 1.46b (0.27, 7.98) 0.44 .66 69% .07 Random a CES-D: The Center for Epidemiologic Studies Depression Scale; DES: Diabetes Empowerment Scale; DHDS, Diabetes Health Distress Scale; DSS, Diabetes-related Stress Scale; SF36: SF-36 Health Survey. NA: not applicable. b RR: risk ratio. c MD: mean difference. Discussion This meta-analysis includes data from nine experimental studies, which included 852 women from four countries. The results revealed that the Internet-based self-monitoring interventions significantly decreased maternal HbA1c levels compared with usual care among perinatal diabetic women at postintervention. Internet-based self-monitoring interventions significantly decreased the cesarean delivery rate compared to usual care among the mixed group at postintervention. Internet-Based Self-Monitoring Interventions The major components of the interventions included self-monitoring glycemic control, medication adherence, physical activity, and diet control. Most of the interventions used websites, phone devices, and/or a glucometer through an asynchronous two-way feedback system. None of the selected studies developed interventions by using theoretical frameworks. Nevertheless, the hypothesized mechanism of action of the interventions should be described according to the Template for Intervention Description and Replication checklist and guide [42]. Theory can explain the rationale of the elements essential to the intervention and how the intervention really worked [43]. Theory can inform interventions in different ways, from identifying theoretical constructs to be targeted or mechanisms underlying particular behavior change techniques to selecting for women the approach that could most likely benefit them toward the right direction [12]. However, the sustainability of the positive findings from these studies is questionable because only three interventions [14,16,34] had follow-up mechanisms. Evidence demonstrated a gradual decline in adherence to self-monitoring of diet, exercise, medication adherence, and weight management [20]. Thus, future studies need to report the long-term effects of the intervention over an extended period. Only one study used a peer-support approach that provided diabetic women with opportunities to discuss problems with others experiencing the same issues [15]; this limitation suggests further research is warranted to determine whether peer-based online forums are effective in improving neonatal or maternal outcomes [19]. Quality of the Evidence and Potential Biases A high range of heterogeneity occurred between none (0%) to high (95%). The overall methodological quality of the studies included in the review was mixed and 78% (7/9) of the studies used methods to randomly assign women to either the intervention or the usual-care group using methods that we judged were at low risk of bias. This result was due to our selection criteria for either RCTs or CCTs. Thus, the majority prevented selection bias and insured against accidental bias. Only 22% (2/9) of the studies achieved adequate allocation concealment. Therefore, participants or providers could possibly foresee assignments to introduce selection bias. A potentially important source of bias in this meta-analysis was that none of the studies (0/9) achieved blinding of participants and personnel. Support intervention studies face considerable difficulties in blinding providers and women to an Internet-based group. Thus, all women would have performance bias. Only 33% (3/9) of the studies achieved an effective blinding of outcomes, perhaps owing primarily to the nature of the interventions. Even during an attempt made to blind outcome assessment, a high risk of response bias remained possible for outcomes relying on self-report and objective outcomes. Hence, the majority of women might harbor favorable expectation or increased apprehension in the Internet-based group or they might feel deprived or relieved in the usual-care group. The overall impact of sample attrition had a low-risk bias in all studies (9/9), which could improve the generalizability of findings and reduce attrition bias. Approximately 90% (8/9) of the studies reported primary and secondary outcomes that were reported in prespecified methods. Consequently, the selected studies did not obtain misleading results. None of the studies used ITT analysis, which is a method designed to solve problems of noncompliance and missing outcomes to maintain prognostic balance generated from the original random treatment allocation [44]. Therefore, all trials indicated overoptimistic estimates of the efficacy of the intervention on outcomes [44]. Glycated Hemoglobin A1c The results of this meta-analysis suggest that Internet-based self-monitoring interventions elicit significant effects on helping perinatal diabetic women to reduce their HbA1c levels, which is consistent with the previous meta-analytic review among adults with type 2 DM [24,25]. A previous review identified 11 studies that analyzed HbA1c levels and found that eight of these studies demonstrated a small significant decline in HbA1c because of substantial heterogeneity (I2= 58%) in the effect interventions [24]. Although our review had no heterogeneity (I2= 0%) in the five identified studies, the small effect might be explained by different intensities of in-person contact between the intervention and control groups. We found the same in-person follow-up interval in both groups of two studies [36-38], but different intervals between the intervention and control group were indicated in three other studies [14,39,40]. A previous review [24] suggested that the intensity of in-person contact between consultation visits might relate to the efficacy of an Internet-based approach. We could not find the significant effect among subgroups of GDM [36-38,40] because of the small sample size, which had lower statistical power to select the true effect [45]. According to self-regulation theory [6], perinatal diabetic women could review their own data to obtain better understanding of their medical condition for self-awareness. The Internet could provide increased ease and convenience of self-monitoring because processing power and connectivity could allow remote access to information, and algorithms can target most of the components of existing face-to-face interventions [13]. Two-way personalized/tailored feedback with recommendations via email, online, or text message [14,36-39,40] helped gain diabetic knowledge and information for self-adjustment of glycemic control [14,36-39,40], diet control [14,36-39,40], appropriate activities control [36,39], weight gain control [39], and medication adherence control [14,36-39,40]. Sending automated alerts and reminders [14,40], voice messages [39], and visualizing data using graphs [37,38] encouraged engagement to the intervention to reinforce self-monitoring. Therefore, perinatal diabetic women capitalized on this motivation to improve HbA1c levels. Cesarean Delivery Rate Internet-based self-monitoring interventions were found to significantly decrease the cesarean delivery rate for a pool of 307 women in the mixed group [14,39], but no significant difference was found for a pool of 219 women with GDM [35-38,40]. The results of the meta-analysis are consistent with a previous meta-analytic review among women with GDM [30]. The study reported nonstatistically significant differences were found in cesarean delivery rates between telemedicine and a usual-care group; however, cesarean delivery rate analysis included only three studies [35,36,38]. This analysis includes an additional three studies [14,39,40]. The reason behind the significant decrease in the cesarean delivery rate in the mixed group but not in the GDM group remains unclear. Small sample size possibly underpowered the detection of any difference in cesarean delivery rate [45] among the GDM group, which suggests additional research is needed. Other Maternal and Neonatal Outcomes This review showed similar neonatal or other maternal outcomes between the Internet-based self-monitoring interventions and usual diabetes care. However, the question remains as to whether Internet-based interventions may offer cost-effective service compared to usual care [28]. Interventions delivered over the Internet are likely to cost less than face-to-face services requiring frequent contact with health care personnel, and their relatively low delivery cost could result in an Internet-based intervention being more cost effective [4,26]. Currently, a dearth of evidence was detected regarding the effects of intervention on cognitive, behavioral, and emotional outcomes among perinatal diabetic women. Despite the identified nine individual cognitive, behavioral, and emotional outcomes in this review, evidence was too limited to draw any conclusion. Thus, additional good quality trials in this area are needed before firm conclusions can be made regarding the efficacy of Internet-based self-monitoring interventions on cognitive, behavioral, and emotional outcomes. Limitations This review has several limitations. First, this review included only studies published in English, all of which were conducted in developed regions with high access to the Internet or mobile devices. Therefore, the results may not be applicable to marginalized groups in developing regions. Second, the subgroup analyses we performed prevented drawing definitive conclusions on the efficacy of Internet-based self-monitoring interventions. Subgroup analyses may pose significant interpretation problems, such as false positive or false negative outcomes [46,47]. The false positive outcomes were found for subgroup analyses when no true outcome exists, and have been estimated at 5% per subgroup [46,47]. The false negative outcomes were found because of the small number of outcome events in each subgroup. Therefore, limited statistical power minimized the random error among the estimates of event rates. Third, the small sample size is another limitation given that five of them used a small sample size from 49 [15] to 50 [40], and we found a lack of studies with type 1 or type 2 DM during pregnancy. Fourth, HbA1c is known to be a 3-month mean measure of glycemic control, but the duration of intervention was not mentioned [14,36] or was less than 3 months [39] in three selected trials. Therefore, the validity of this measure as an outcome at postintervention might be questionable. Fifth, a nonsignificant effect was found in the GDM subgroup, but a significant effect was detected in the mixed group; thus, the effect of the type of diabetes rather than the true intervention effect was contentious. Finally, two studies [14,39] had CCT designs with insufficient control of extraneous variables, which diminished the internal validity of their findings. Implications for Future Research Continuing research in this area is needed to develop effective Internet-based self-monitoring interventions to improve maternal and neonatal outcomes. Future studies should consider the theoretical base of the interventions [12] with a peer-support component [19] and long-term follow-up [20] to improve the efficacy and sustainability using a RCT design with ITT analyses [44]. However, determining the effective elements of Internet-based application is necessary. Further investigations are needed to divide these applications into specific components, features, transmission, functionality, facilities, interactivity, duration, and mode of delivery to differentiate the distinct effects of different functions [12]. This requirement is especially true in view of the lack of current research that explores the mechanism of effective interventions in different types of perinatal DM. Clinical Implications Internet-based self-monitoring interventions may function as important extensions of the range of services to enhance the access of diabetic women to support with self-monitoring especially between consultation visits. Based on the findings of this study, websites that integrate communication with sensor-based systems and a tracing system should be considered high priority in designing self-monitoring interventions to improve maternal glycemic control and cesarean delivery rates. The ubiquity of the Internet facilitates dissemination of information and support to a broader audience and allows information and support to be tailored according to individual characteristics and experiences [26]. Perinatal diabetic women could access and review content at any time and place. Multimedia features and interactivity could accommodate different learning styles [48]. Data visualization capabilities and cloud computing offer accessible display of outcome information, flexible dissemination channels within and between service settings, and ready access to collaborative communication and shared resources for perinatal women and health care providers [13]. Furthermore, gaming technology, Bluetooth technology, interactive voice response, virtual reality, Facebook presence, as well as blogs and Global Positioning System navigation systems are another advancing wave of technological development that might potentially help map out new avenues to promote and support Internet-based self-monitoring among perinatal diabetic women. Conclusion The rising popularity of the Internet might result in a shift from the traditional model of care toward an Internet-based health model. Internet-based self-monitoring interventions may introduce new approaches of improving maternal HbA1c and cesarean delivery rates to perinatal diabetic women. Despite the limitations of this review and analysis, our findings have identified a need for future research to employ RCT designs with follow-up data to confirm the long-term effects of Internet-based self-monitoring interventions on maternal and neonatal outcomes among perinatal diabetic women. The research was funded by a start-up grant (Ref: NUHSRO/2013/147/SU/01, WBS No: R545000055133) and HSS Seed Fund (1/2016) from the National University of Singapore. Multimedia Appendix 1 Selection criteria for systematic review. Multimedia Appendix 2 Index and keyword terms for searching in seven databases. Multimedia Appendix 3 Risk of bias graph. Multimedia Appendix 4 Description of Internet-based self-monitoring interventions in 9 selected studies. Abbreviations BMI body mass index CCT controlled clinical trial CINAHL Cumulative Index to Nursing and Allied Health Literature DM diabetes mellitus GDM gestational diabetes mellitus HbA1c glycated hemoglobin A1c ITT intention-to-treat PRISMA Preferred Reporting Items for Systematic Reviews and Meta-analysis RCT randomized controlled trial RR risk ratio SMS short message service Authors' Contributions: LY contributed to the conception and design of this study. LY and SN designed the search strategies and performed the literature search. LY, TP, and KY performed the review selection and LY contributed to the analysis and interpretation of data. LY contributed to drafting the article incorporation with all authors. All authors approved the final submitted manuscript. 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==== Front Front PsycholFront PsycholFront. Psychol.Frontiers in Psychology1664-1078Frontiers Media S.A. 10.3389/fpsyg.2016.01305PsychologyFocused ReviewiPads and the Use of “Apps” by Children with Autism Spectrum Disorder: Do They Promote Learning? Allen Melissa L. *Hartley Calum Cain Kate Department of Psychology, Lancaster UniversityLancaster, UKEdited by: Nicola Pitchford, University of Nottingham, UK Reviewed by: Natalia Kucirkova, Manchester Metropolitan University, UK; Elizabeth Sheppard, University of Nottingham, UK *Correspondence: melissa.allen@lancaster.ac.uk30 8 2016 2016 7 130511 5 2016 16 8 2016 Copyright © 2016 Allen, Hartley and Cain.2016Allen, Hartley and CainThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.The advent of electronic tablets, such as Apple's iPad, has opened up the field of learning via technology, and the use of electronic applications (“apps”) on these devices continues to dramatically rise. Children with communication and social impairment, specifically those with Autism Spectrum Disorder (ASD), often use educational and recreational apps within the context of their home and school settings. Here we examine in which contexts learning via this medium may be beneficial, and outline recommendations for the use of electronic tablets and the design features for apps to promote learning in this population that is characterized by a unique profile of needs and heterogeneous ability levels. Autism Spectrum DisorderiPadtechnologylearningcommunication ==== Body Introduction Severe language impairments are a common characteristic of Autism Spectrum Disorder (ASD; DSM-V: American Psychiatric Association, 2013). Approximately 80% of children with ASD aged 5 years and younger who enter special education are non-verbal (Bondy and Frost, 1994), and 30% are minimally-verbal at 9-years (Anderson et al., 2007). These linguistic difficulties can have a devastating impact on children's capacity to communicate, but special educators have developed numerous interventions that enable communication without expressive language. In educational and clinical settings, picture-based strategies such as the Picture Exchange Communication System (PECS; Bondy and Frost, 1994) are the most popular due to their low demands, focus on visual spatial processing (a relative strength in ASD; Mottron et al., 1999), and proven capacity to facilitate communication in minimally-verbal children (Flippin et al., 2010). However, the emergence of the Apple iPad in 2010 (and similar tablet hardware) has elicited a surge toward technology-mediated education and interventions, which may benefit children with ASD due to the device's portability, easy to use touch screen interface, and ability to emit multimodal output (Lofland, 2016). While there are countless software applications (“apps”) designed to support language development and communication using digital pictures, little research has investigated the ability of children with ASD to comprehend and learn from symbolic information presented via tablet technology. Similarly, there is little guidance as to how the features of electronic apps can be maximized to specifically facilitate learning in this population. These areas of enquiry are, however, rapidly emerging. Symbolic understanding of pictures Prior to addressing learning via electronic media, it is important to ascertain the extent to which children with ASD understand the symbolic role of pictures, and how they might learn from them. On a fundamental level, many children with ASD have been shown to have a different route of pictorial understanding than typically developing (TD) peers. For instance, Preissler (2008) showed that minimally-verbal children with ASD and cognitive impairment who use picture based systems to communicate associatively mapped words onto black-and-white pictures themselves and failed to extend labels to depicted referents, unlike TD children (see Preissler and Carey, 2004). However, Hartley and Allen (2015a) found that a similar population of children with ASD extended labels to symbolized referents approximately twice as often in color picture trials relative to non-color picture trials (see also Hartley and Allen, 2015b for the facilitative role of iconicity for pictorial comprehension). This finding suggests that different types of pictures may promote or inhibit understanding. Perceptual cues: shape and color Other research shows that when children with ASD generalize names from pictures, they often do so based on atypical cues. In Hartley and Allen (2014a), children with and without ASD learned the names of unfamiliar objects depicted in photographs and were required to sort items according to whether or not they were also referents of the newly-learned names. While the TD controls only generalized labels to items that matched on shape (a category-defining cue), children with ASD frequently generalized to items that matched depicted objects on shape or color (a category-irrelevant cue). Thus, it appears that minimally-verbal children with ASD do not know intuitively what names refer to when paired with pictures (i.e., the picture itself, the depicted object's shape, or the depicted object's color) and their symbolic comprehension is significantly influenced by the type of picture. Taken together, these differences suggest that there might be an atypical route of word learning via pictures in ASD (see also Hartley and Allen, 2014b), but they leave open the question of whether media type (e.g., iPad or book) can impact the capacity for symbolic understanding. KEY CONCEPT 1 symbolic understanding Symbols represent external referents in the world, and the relationship between a symbol and its referent is determined by the intention of the creator of the symbol. The word ‘monkey’ and picture of a monkey both refer to, and symbolize, real monkeys. Symbolic understanding of pictures requires that an individual ‘sees through’ the picture to its referent. Our study We thus investigated whether picture-based learning, in particular extension of words learned via pictures to real objects, in children with ASD is impacted by the use of an iPad (Allen M. L. et al., 2015). For TD children, “traditional” picture books facilitate learning because they provide optimal opportunities for joint interaction and engagement (see Ganea et al., 2008). However, by definition, children with ASD are impaired in the domain of social-cognition (DSM-V: American Psychiatric Association, 2013) and are often averse to engaging in social-interactions (Sigman et al., 1986). For this reason, we theorized that the increasingly self-contained nature of the iPad might reduce environmental stress associated with social interaction, allowing greater cognitive resources to be focused on learning. We also explored whether the type of picture impacted children's learning when presented on either the iPad or a more “traditional” picture book. A critical issue is whether children with ASD show the same biases when developing vocabulary as TD children. Previous research shows that, by 24 months, TD children infer the general rule that noun-referent relations are constrained by shape, and will generalize labels based on this feature rather than other perceptual properties (e.g., color, size, texture; Landau et al., 1988). This “shape bias” is driven by TD children's sensitivity to word-shape co-occurrences during infancy (Samuelson and Smith, 2005) and their abstraction of prototypes (mental representations of a category's “central tendency”; Younger, 1990). By contrast, children with ASD do not show an attentional bias for shape in word learning contexts (Tek et al., 2008; Hartley and Allen, 2014a), likely due to deficits in foundational nonverbal processes (Frith and Happé, 1994; Klinger and Dawson, 2001) or a delay in learning the strategy (Field et al., 2016). However, presenting multiple differently-colored examples of a target referent (rather than a single exemplar) when teaching a new name may serve to highlight similarity of shape, thus fostering shape-based generalizations despite unusual attentional biases. KEY CONCEPT 2 shape bias Children tend to generalize nouns to other category members based upon similarity of shape, rather than other properties of objects such as color, texture, or material. This ‘bias’ helps to explain the rapid and effortless way most typically developing children learn about words and category membership. To investigate the cues that influence word learning in children with ASD, and whether this is influenced by medium of presentation (e.g., iPad or book), we worked with 16 minimally-verbal children with ASD (M receptive language: 3.9 years; M nonverbal IQ: 57.5)—the target audience for producers of communication apps on the iPad. All children were recipients of picture-based interventions such as PECS and were frequently exposed to iPads in educational settings. Participants were taught the names of unfamiliar objects presented in photographs across four within-subjects conditions: (1) via an iPad, repeatedly presenting a single representation of the target object, (2) via a picture book, repeatedly presenting a single exemplar, (3) via an iPad, presenting multiple differently colored representations of the target object, and (4) via a picture book, presenting multiple differently colored representations. Children were then tested on their ability to extend the newly-learned names to three-dimensional (3-D) referents matching on shape and color, and to generalize names to novel category members matching on shape but not color. Crucially, our results revealed that medium of presentation—iPad or book—did not impact on children's extension of names from pictures to real objects. Rather, children with ASD only extended labels to depicted objects at above-chance rates when presented with multiple differently-colored pictures of the target referent, and tended to map narrow associative word-picture relations when presented with a single exemplar. By demonstrating that a single label does not refer to a unique referent (i.e., a specific target picture), the multiple example conditions may have increased children's awareness that words can be extended to various items in one's environment, including perceptually similar objects. By contrast, the process of repeatedly pairing a verbal label with one target picture in single exemplar trials may have narrowed the relation to the extent that the picture itself (rather than the depicted object) was more frequently considered the referent of the word (Plaisted, 2001; Preissler, 2008; Hartley and Allen, 2015a). Thus, the nature of the pictures being presented may be a more important influence on symbolic learning in ASD than whether they are presented on an iPad or in a book. Do apps benefit communication and learning for children with ASD? Although our small scale study on word learning did not reveal any advantages in the use of an iPad vs. traditional picture books, other studies report success when teaching communication skills to minimally-verbal children with ASD. Lorah et al. (2015) found that across 17 studies, 93% of individuals improved their ability to communicate by using an iPad or iPod as a multi-functional speech generating device (SGD). Furthermore, they identify several papers that report learning and preference advantages for iPad-based SGDs in comparison to other augmentative and alternative communication (AAC) interventions, such as manual sign language and picture exchange protocols (Flores et al., 2012; van der Meer et al., 2012a,b,c; Lorah et al., 2013; Achmadi et al., 2014; Couper et al., 2014). For example, Lorah et al. (2013) revealed that teaching requesting behaviors via an iPad SGD yielded greater overall success, improved maintenance, and required less time in comparison to a “traditional” picture exchange protocol. Another recent study by Xin and Leonard (2015) found that three minimally-verbal children with ASD successfully learned how to initiate requests, respond to questions, and made more frequent social comments after 6 weeks' training on an SGD iPad app (however their study did not include a comparison AAC). Thus, when used as an SGD, the iPad can effectively promote communication in minimally-verbal children with ASD. KEY CONCEPT 3 augmentative and alternative communication (AAC) AACs encompass a variety of forms of communication to allow an individual with spoken or written language impairment to express their needs. Examples include gestural systems, picture based systems or communication devices with voice output. However, other studies report that iPad-based interventions are no more effective (and in some respects less effective) than alternative interventions. Agius and Vance (2016) found that three children with ASD mastered a series of requesting behaviors in a similar timeframe when trained on PECS and an iPad-based SGD. Although children achieved similar proportions of independent requesting with both AACs post-intervention, they required fewer prompted responses when learning via PECS (making it more efficient) and follow-up data suggested that maintenance of iPad-supported requesting was reduced. El Zein et al. (2016) compared the effectiveness of a reading comprehension intervention when instruction was teacher-directed or iPad-assisted. While both interventions improved reading comprehension and reduced task refusal, the teacher-directed intervention was relatively more effective at promoting target behaviors. In a randomized control trial, Fletcher-Watson et al. (2015) examined the efficacy of an iPad-based app targeting social-communication skills in 54 children with ASD below 6 years of age. The game-like app was designed to motivate and rehearse two key joint attention skills—attention to people and social cue following—and was accessed by half of the participants for 2 months (the other half formed a “treatment as usual” control group). The app consisted of two parts. In Part 1, a human character was depicted on the screen and children were required to touch it. Children progressed through increasingly-difficult “levels” that simultaneously presented non-human distractors that had to be ignored. In Part 2, the human character was presented in a shop and pointed toward a desired item at one of six locations around the screen. Children were required to touch the desired item, and the more difficult levels involved the character just looking rather than pointing. The app's efficacy was evaluated by comparing standardized measurements of children's social-communication (e.g., eye contact, quality of social overtures, bids and responses to joint attention) and vocabulary taken before and after the intervention period. Crucially, there were no significant differences between children's pre- and post-intervention scores on any assessment, and time spent playing the app did not correlate with any measured ability. However, the app was highly engaging for children and regarded favorably by parents. These important results call into question the usefulness of iPads for promoting “real world social skills” in children with ASD. However, they do highlight the potential for an intervention administered on a tablet such as the iPad to directly increase levels of engagement, which could be explored in terms of how it might impact upon later learning. Taken together, these findings suggest that iPad-based interventions can effectively promote certain target skills (e.g., instrumental requests), but not others (e.g., spontaneous social communication). There are also potential differences in the learning mechanisms supporting the two types of skills we reviewed: instrumental requesting relies upon associative learning, whereas spontaneous social communication requires broader social-pragmatic awareness and social motivation which may be more fundamentally impaired in ASD. The balance of evidence suggests that iPads do not readily improve learning and communication for children with ASD, but it is important to note that there is no strong evidence indicating that tablets and educational apps are detrimental to learning. ASD presents a unique challenge given the heterogeneity of the condition (Folstein and Rosen-Sheidley, 2001), resulting from multifaceted interactions between genes, behavior, and the brain across development (Pelphrey et al., 2011). In addition to differences in language ability, individuals with ASD vary in terms of their cognitive skills (Volkmar et al., 2014), behavioral difficulties, and levels of social understanding (Rice et al., 2012). Due to this variation, learning styles of individuals across the spectrum are not uniform in nature (Tsatsanis, 2004). Tsatsanis (2004) advocates the need for individualized educational programming to directly combat the heterogeneity of learning style and blanket materials often issued within therapeutic intervention for those with ASD. For instance, individuals with and without co-morbid intellectual impairment have differences in memory and attention that affect learning processes. The efficacy of any intervention, whether mediated by technology or teacher/caregiver, depends greatly upon both features of the intervention package itself, as well as the individual child. In the following sections we consider how educational apps used on tablets and iPads have the potential to maximize learning for this heterogeneous population. KEY CONCEPT 4 heterogeneity of ASD ASD is by definition a spectrum condition, meaning that individuals vary in terms of presentation of core diagnostic behaviors and their severity and levels of adaptive functioning. It is important to consider the vast heterogeneity in diagnosis, research, and treatment, as a singular approach is not sufficient. Future research and the potential of language and communication apps for ASD: attitudes to iPad and tablet interventions An important advantage of iPad-based interventions is that they are often preferred over more traditional AACs by children with ASD (Lorah et al., 2013, 2015). This preference may increase the likelihood of children using the app and, through this, elicit greater communication, thereby demonstrating greater learning. In addition to children with ASD showing a preference to use an iPad rather than more traditional AACs, iPads may result in greater engagement and time on task. Research to date supports this: interventions delivered with an iPad result in greater engagement and reduced challenging behavior during the intervention period compared with interventions delivered by teachers and therapists (Fletcher-Watson et al., 2015; Lee et al., 2015; El Zein et al., 2016). These studies did not all demonstrate better learning when the intervention was delivered by the iPad. However, children's motivation to engage with learning material should not be overlooked, because motivation processes directly impact knowledge acquisition and transfer (Dweck, 1986). Thus, the attractiveness of these new technologies may be usefully exploited to support better learning outcomes and future research needs to identify how best to achieve this. Parents can also be enthusiastic about iPads and, in particular, their therapeutic potential due to engagement, which may result in greater use and learning. Clark et al. (2015) found that parents of children with ASD and professionals specializing in ASD both held positive attitudes toward iPad use. The parents in this study reported that 97% of their children used an iPad at a frequency of 4.6 out of 5 days on average, and ~65% of professionals integrated iPads into their practice (e.g., as an intervention or a reward). However, a recent study by Allen and colleagues (Allen A. A. et al., 2015) suggests that parents' positive attitudes toward the iPad are not always enduring. Parents of children who owned, and did not own, an iPad answered questions concerning the potential usefulness of the technology for enhancing their children's communication. Notably, the expectations of parents with children who did not own an iPad were significantly more positive than those of parents with children who had used an iPad-based AAC. The authors argue that these results indicate “…a conflict between the non-users' illusions and the users' subjective reality regarding the iPad's potential to improve augmentative and alternative communication…” for children with ASD (Allen A. A. et al., 2015, p. 41). Future research and the potential of language and communication apps for ASD: a consideration of their design features The iPad advantage found for engagement and time on task may arise because of the game-like interface of many apps, which successfully promotes these processes, as noted above. However, we must not assume that all apps are equal: specific features may influence the quality of engagement (Kucirkova et al., 2014a), and therefore motivation and learning. Any therapeutic intervention needs to be individualized to meet the needs of a particular child, as the “blanket” materials often implemented do not account for individual differences (Tsatsanis, 2004). It is important to inform the design of any app with expert advice from practitioners and, when possible, to seek input from the children themselves to ensure the content is appropriate for users with ASD (Fletcher-Watson et al., 2016). One reason for the absence of clear advantages for interventions delivered by apps vs. more traditional methods may be to do with a failure to consider and exploit specific features of apps that can benefit learning. Digital technology affords a unique advantage and opportunity for customization that traditional paper material cannot provide. Apps can either be “closed” or “open”: both are interactive, but only the latter allows the user to change or modify content. For children with ASD, personalization of content to support communication may be critical. Communication apps that use picture based systems (such as PECS; Bondy and Frost, 1994) historically required an individual to print out pre-drawn icons, which were not perceptually similar to real world referents and thus often opaque and difficult to learn. The functionality of tablets with inbuilt cameras can be exploited by apps; actual items can be instantly photographed and included in an individual's picture repertoire in a communication app, so that a child's own objects can now be easily accessed. We have not found any studies that directly compare different functionalities or levels of customization for the same basic app, although some degree of customization currently exists, at least for communication programs such as Proloquo2Go (see Sennott and Bowker, 2009). Samsung's promising “Look at me” app utilizes the camera in digital devices to promote eye contact and allows a customizable experience based upon each child's achievements; empirical testing of its validity is currently underway (The Look at Me Project, 2016)1. Furthermore, in a naturalistic study of TD children's use of different educational apps, Kucirkova et al. (2014a) found that those that allowed personalization by adding photographs, audio, and text comments to create a narrative promoted greater engagement with the task. Similar motivational benefits using a story creation app (“Our Story”) have been reported for children with language and communication difficulties (Kucirkova et al., 2014b; Critten and Kucirkova, 2015). Thus, personalization could be usefully exploited to facilitate engagement. Apps (for word learning at least) could also be developed to exploit children's word-learning biases. As noted earlier, TD infants show a shape bias when generalizing new labels for objects, whereas children with ASD do not. Apps can be developed to allow fine-grained customization of pictorial features, which could usefully support learning in ASD. For example, it is easier to program an app than to print a book to present multiple differently-colored examples of a target referent rather than a single exemplar. Such features could be used when teaching a new name to highlight the similarity of shape, and foster shape-based generalizations in this population. We are not suggesting that technology can replace all learning experiences. We note the importance of sensorimotor experiences and attention, and their roles in facilitating word learning in young children (Yu et al., 2008). Further to this, two-dimensional (2-D) representations presented on a screen do not afford manipulation nor provide cues from the caregiver's direction of gaze. However, one of the key features of the tablets on which apps are used is their touch-screen; thus, touch, gesture, and pointing can be supported by the use of tablet hardware (Flewitt et al., 2014) and the apps used to support learning could be designed to enhance this type of sensory interaction to a greater extent than possible with traditional print medium embedded. In addition, the flexibility of an app to manipulate perceptual features of stimuli might be usefully exploited to support learning in children with ASD. Virtual environments can also provide for extra processing time (Southall, 2013) and reduce anxiety associated with face-to-face interactions and thus may be particularly beneficial for children with ASD. Another way that apps for tablets can be exploited to support learning is scaffolding. Scaffolding refers to the assistance provided to learners on an “as needed basis” that enables them to acquire skills and accomplish tasks that they cannot manage independently (Wood et al., 1976). It might include simplifying the task, at first, providing verbal and visual prompts, and modeling to facilitate success and learning. More support is required when a task (or behavior) is new, and the level of support is gradually reduced as gains in behavior are observed and competence develops. Scaffolding has been shown to be effective in facilitating learning across a wide range of content domains and age and ability ranges (Wood and Wood, 1996). Effective scaffolding might further benefit learning because it could reduce errors made on task, resulting in faster, and more robust learning (Warmington et al., 2013). Adaptive scaffolds can be embedded into apps to structure and support an individual's learning, just as caregivers and teachers make adjustments during interactions to enable success. Where technology may have one advantage over child-human instructor interactions, is in the ability to program them so that multimodal prompts and supports are readily available to suit the learner's current level. To reflect on our word learning paradigm, an app can be programmed to reinforce and consolidate learning by presenting stimuli in different colors, orientations, etc., more easily than a caregiver or teacher can do so; the latter needs to prepare a range of exemplars in advance and have these all to hand. Further, we can envisage the development of apps that seamlessly move from the highly personalized photographs of objects in an individual's environment, to other photographs, colored pictures, through to black and white line drawings to promote generalization in tune with the learner's performance. Recommendations for app use In light of the ever-growing number of “autism communication apps,” it is increasingly important that parents and practitioners are directed toward software that is most likely to be effective. Boyd et al. (2015) outline five important factors that should be considered when selecting apps for use with children with ASD. Firstly, it is vital to identify apps that are based on scientific principles and/or supported by empirical research (Boone and Higgins, 2007). Helpfully, the website for Autism Speaks, one of the world's leading ASD science and advocacy organizations, lists hundreds of autism-focused software apps and it is possible to filter on the basis of empirical support (Autism Speaks, 2016)2. Secondly, it is often favorable to select apps that enable the creation and integration of customized visual supports using the tablet's camera (Sennott and Bowker, 2009). Personalized stimuli of this nature improve the specificity of children's communication, expand opportunities for interaction, and enable caregivers to utilize content that is most likely to facilitate children's symbolic understanding (Hartley and Allen, 2015a,b; Allen M. L. et al., 2015). Thirdly, caregivers should reflect on the motor skills required to effectively engage with a given app. Many children with ASD experience deficits in fine motor skills, and parents should select apps with these difficulties in mind (McNaughton and Light, 2013). Fourthly, it is important to consider the time and resources that are necessary in order to teach children with ASD how to operate and communicate using a given app. While manualized AACs such as PECS have well-established and highly-structured training “stages” (Flippin et al., 2010), there are no standardized guidelines explaining how children with ASD should be taught to use iPads or specific apps, therefore placing emphasis on the caregiver to devise their own strategy (Boyd et al., 2015). Finally, apps should be evaluated on their affordability. Although iPads and their applications are relatively low-cost (in general), they often lack the technical support associated with more conventional AAC devices (McNaughton and Light, 2013). Furthermore, those apps that are supported by empirical research are often expensive (e.g., Proloquo2Go has a download price of £199.99/$249.99). Consequently, some parents may (quite understandably) be tempted by cheaper alternatives that lack empirically-validated efficacy or fail to provide the full range of functionality required by their children. Conclusion Research investigating learning with apps from iPads and electronic media by individuals with ASD is quickly developing as the use of such devices becomes widespread. In terms of strictly promoting spontaneous communication, there does not seem to be an advantage for electronic platforms relative to more traditional picture books. Incorporating the presentation of multiple examples into clinical and educational practices regardless of medium (e.g., the delivery of picture based PECS systems; the development of iPad communication apps) may facilitate understanding in children with ASD that 2-D representations can refer to 3-D objects, leading to improvements in their ability to communicate using pictorial aids. This review does suggest that digital technology provides one important advantage relative to traditional methods in that it can be easily adapted to accommodate different learning styles and the individual's current knowledge than face-to-face learning: the number of repetitions of material to be learned, the quantity and type of scaffold to aid learning, and the level of difficulty, can all be adjusted automatically based on the learner's response (Akbulut and Cardak, 2012). Finally, we see an advantage for app-based learning by extending the learning environment. Children do not just learn at school; they learn at home. One advantage of educational apps is that they can provide a seamless transition from school to home, promoting greater learning. This can be critically important for language interventions for children with ASD, where repeated exposure is required. Author contributions MA, CH, and KC contributed to the intellectual contribution and writing of the manuscript. Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer ES and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review. 1Retrieved from http://pages.samsung.com/ca/lookatme/English/. 2Autism apps. Retrieved May 10, 2016, from https://www.autismspeaks.org/. Melissa L. Allen, PhD is a Senior Lecturer in Psychology at Lancaster University. After receiving her PhD at New York University, she completed a Post-Doctoral Fellowship at Yale University, jointly in the Psychology Department and the Developmental Disabilities Clinic. Dr. Allen has been working in the field of autism for over 15 years. 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==== Front Neural PlastNeural PlastNPNeural Plasticity2090-59041687-5443Hindawi Publishing Corporation 10.1155/2016/7365609Research ArticleNeuromuscular Plasticity: Disentangling Stable and Variable Motor Maps in the Human Sensorimotor Cortex Kraus Dominic http://orcid.org/0000-0002-9782-5281Gharabaghi Alireza * Division of Functional and Restorative Neurosurgery and Centre for Integrative Neuroscience, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany*Alireza Gharabaghi: alireza.gharabaghi@uni-tuebingen.deAcademic Editor: David E. Vaillancourt 2016 16 8 2016 2016 736560911 4 2016 28 6 2016 19 7 2016 Copyright © 2016 D. Kraus and A. Gharabaghi.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Motor maps acquired with transcranial magnetic stimulation (TMS) are evolving as a biomarker for monitoring disease progression or the effects of therapeutic interventions. High test-retest reliability of this technique for long observation periods is therefore required to differentiate daily or weekly fluctuations from stable plastic reorganization of corticospinal connectivity. In this study, a novel projection, interpolation, and coregistration technique, which considers the individual gyral anatomy, was applied in healthy subjects for biweekly acquired TMS motor maps over a period of twelve weeks. The intraclass correlation coefficient revealed long-term reliability of motor maps with relevant interhemispheric differences. The sensorimotor cortex and nonprimary motor areas of the dominant hemisphere showed more extended and more stable corticospinal connectivity. Long-term correlations of the MEP amplitudes at each stimulation site revealed mosaic-like clusters of consistent corticospinal excitability. The resting motor threshold, centre of gravity, and mean MEPs across all TMS sites, as highly reliable cortical map parameters, could be disentangled from more variable parameters such as MEP area and volume. Cortical TMS motor maps provide high test-retest reliability for long-term monitoring when analyzed with refined techniques. They may guide restorative interventions which target dormant corticospinal connectivity for neurorehabilitation. Deutsche ForschungsgemeinschaftDFG GH 94/2-1DFG EC 307Bundesministerium für Bildung und ForschungBFNT 01GQ0761BMBF 16SV3783BMBF 0316064BBMBF 16SV5824 ==== Body 1. Introduction Adaptive reorganization of cortical maps after brain damage is referred to as plasticity and is regarded as relevant during recovery and compensation by reflecting changes of neural circuit architecture and synaptic connectivity [1]. The connectivity of these neuronal networks is, however, also being continuously modified by use-dependent mechanisms independent of any injury or recovery. When studying changes of cortical map plasticity during disease progression or therapeutic interventions, it is therefore necessary to disentangle stable and variable map parameters. In this context, brain stimulation techniques are particularly suitable for monitoring the cortical maps, for example, to probe effective corticospinal connectivity by measuring time-locked motor evoked potentials (MEP) at target muscles. The techniques applied in animal research and human studies, for example, intracortical microstimulation or epicortical electrical stimulation, differ with regard to their level of invasiveness and spatial accuracy [2–7]. Transcranial magnetic stimulation (TMS)—albeit with significantly less spatial resolution than surgical mapping techniques—has been established as a powerful alternative mapping tool for clinical and research application [8]. When applied, for example, in the context of stroke patients, TMS mapping revealed a reduced excitability and a decreased cortical representation of the impaired movement [9, 10]. After short-term therapy, the cortical motor map and the manual dexterity increased at least temporarily [11]. Following longer interventions, clinical gains were paralleled by the recruitment of cortical motor representation in the affected hemisphere outside the primary motor cortex [9, 12, 13]. However, more recent studies have challenged these previous findings by revealing corticospinal connectivity outside the primary motor cortex in healthy subjects [14] as well as by demonstrating relevant variability of the spatial extent of motor maps independent of any intervention [15]. This ambiguity might be related to methodological differences; in recent years, individual magnetic resonance images (MRIs) have been used in conjunction with navigated TMS (nTMS). This technique monitors the coil position, direction, and tilting, thus increasing the repeatability of both coil placement [16, 17] and orientation [18]. When the TMS coil was aligned on the basis of the individual shape of the central sulcus, the somatotopy in the primary motor hand area could be captured [19]. Navigated TMS might thus be more precise than standard TMS, for example, in capturing nonprimary motor cortex corticospinal connectivity [14], but is perhaps still not precise enough to distinguish between the natural daily or weekly fluctuations of the motor map extent [15] and lasting cortical plasticity in the course of a disease or intervention. Such a differentiation would necessitate stable cortical map parameters that are resistant to such natural fluctuations. In this context, simulation studies have indicated that the individual gyral anatomy has a major impact on TMS-induced electrical field distributions [20–25]. The reliability of motor maps might thus be improved when accounting for interindividual differences in brain anatomy. Combining nTMS maps with individual MRIs facilitated—as a first step on the way—the analysis of group data in normalized space [15, 26, 27]. Previous nTMS approaches, however, still projected the TMS coil positions as a grid of target points on the brain surface, resembling a plane that covered both gyri and sulci, and did not account for differences in cortex morphology [15, 17–19, 28–30]. To overcome this limitation, we recently proposed a novel projection, interpolation, and coregistration technique for estimating nTMS sites onto the individual anatomy, namely, by following the surface curvature of gyri [31]. The novelty of this approach was thus not related to the application of neuronavigation to the TMS mapping procedure itself, as was the case in previous nTMS studies, but instead consisted in the application of the stereotactic information provided by nTMS to visualize the stimulation findings in relation to the specific anatomy [31]. The specific visualization of the stimulation sites, obtained by nestling them to the gyral curvature, was complemented by a mathematical interpolation which considered all neighboring stimulation results in a distance-weighted fashion. This technique achieved a lower variability of cortical motor maps between subjects in normalized space than standard TMS mapping [31]. In the present study, we reasoned that this refined TMS technique would also provide high test-retest reliability of cortical motor maps, although the inherent variability of TMS metrics, like other metrics representing human physiology, may be related to many biological reasons. We tested the long-term stability of nTMS in healthy subjects, not for days and weeks as tested previously but for several months, and with six instead of only two or three different measurement time points. Since these previous studies—which applied the standard TMS mapping approach—revealed low retest reliability even for these short observation periods, a repetition of this standard procedure for longer follow-up periods will not provide any further insight. We therefore focused our long-term examination on the novel approach which was recently introduced [31]. Notably, the limited reliability observed in previous studies was not related to focal mapping parameters such as centre of gravity or hotspot but to mapping parameters that capture the extent of the cortical motor map, such as the map area. We therefore addressed these classical parameters and also applied complementary measures to describe the cortical extent of the cortical motor map, such as motor maps of the mean spatial overlap, the mean MEP amplitude, and the intraclass correlations of the MEP amplitude in the present study. We detected extended sensorimotor areas with high functional overlap between subjects and in the course of the mapping sessions. Therefore, long-term stable map areas could be disentangled from the more fluctuating ones by which they were surrounded. At each stimulation site, intraclass correlations of the MEP amplitudes revealed mosaic-like clusters of consistent corticospinal excitability spanning over distributed areas in the sensorimotor cortex. Moreover, and somewhat unexpectedly, relevant interhemispheric differences with more stable corticospinal connectivity in the nonprimary motor areas of the dominant hemisphere were unraveled, reflecting use-dependent plasticity. 2. Material and Methods 2.1. Subjects Twelve right-handed subjects (mean age 24 years, range 19–28, 8 males) with verified right-handedness (EHS > 70) according to the Edinburgh Handedness Inventory [32] were studied in the course of six experiments with a mean of 14.7 days between experiments. In all subjects, cortical motor maps of the nondominant, right hemisphere were captured; in six of the participants, additional motor maps of the dominant, that is, left, hemisphere could be acquired. In three of the subjects, an additional seventh measurement was performed ~1.5 years after the sixth session. All measurements were performed at the same time of day. However, the participants were deliberately not requested to alter their daily routines. We thereby hoped to emulate real-life conditions of clinical practice as closely as possible. All participants gave written informed consent and had no contraindication to TMS [33] or a history of any neurological or psychiatric disease. The studies were approved by the local ethics committee and were in accordance with the declaration of Helsinki. 2.2. Mapping Protocol The cortical mapping was performed by the same person in all experiments (DK) as described previously [31]: we used a navigated TMS stimulator (eXimia®, Nexstim, Helsinki, Finland) and a biphasic figure-8 coil (Nexstim, Helsinki, Finland) with a mean diameter of 50 mm and an estimated focality of 0.68 cm2 (eXimia Focal Bipulse, Helsinki, Finland). The neuronavigation system controlled the position, orientation, and tilt angle of the TMS coil. Prior to the mapping, individual anatomical T1-weighted magnetic resonance images were acquired by a 3-Tesla Siemens TIM Trio MRI system (Siemens AG, Erlangen, Germany) using the t1-MPRAGE gradient echo, a field of view (FOV) of 256 mm and 176 sagittal slices, a voxel size of 1 × 1 × 1 mm3, a repetition time (TR) of 2300 ms, and an echo time (TE) of 2.98 ms. Individual MRIs were loaded into the eXimia system for coregistration with the subject's head using three anatomical landmarks (nasion + both crux helix) and nine additional points on the scalp (registration error < 2 mm). The electromyography (EMG) signal of the extensor digitorum communis (EDC) of both arms was recorded with the integrated EMG device of the eXimia system (3 kHz sampling rate, band-pass filter of 10–500 Hz) using Ag/AgCl AmbuNeuroline 720 wet gel surface electrodes (Ambu GmbH, Germany). The MEPs were acquired from relaxed muscles. The EDC was chosen for this study, since this muscle is the main target during brain-robot interface-based interventions [34–36] designed for stroke rehabilitation [37, 38]. The electrodes were placed 2 cm apart from each other on the muscle belly of the forearm [39], differently from the procedure usually applied for hand muscles. For each subject, the cortical representation of the EDC muscle was determined using 40% of maximum stimulator output at the anatomically defined “hand knob” of the primary motor cortex (M1) as the starting position. If the initial stimulator output was not sufficient to elicit MEPs, it was increased in steps of 5%. The current waveform of the stimulator was biphasic. The orientation of the induced current in the brain was posterior-anterior for the first phase and anterior-posterior for the second phase of the stimulus as stipulated by the manufacturer. The orientation of the electric field, calculated on the basis of the individual MRI of each subject by the eXimia software, was kept perpendicular to the central sulcus, and the location with the highest MEP response was selected as the stimulation point. Having determined the “hotspot” with about 30 stimuli by moving the coil around the hand knob, we varied the orientation of the coil within an angle of approximately 90° in steps of roughly 10° and with 3 stimuli at each angle, around the original orientation. Using this method, we were able to ascertain the orientation with the highest response in this spot. This orientation was posterior-anterior in all cases with only slight (±20°) interindividual differences. The resting motor threshold (RMT) was determined using the relative frequency method, that is, selecting the minimum stimulus intensity (by changing the stimulator output in 2% steps of maximum stimulator output (MSO)) that resulted in MEPs >50 μV in the peak-to-peak amplitude in at least 5 out of 10 consecutive trials [40, 41]. The cortical map representation was acquired at 110% RMT with the same coil orientation as was applied at the hotspot. This map was extended in random order around the hotspot with evenly distributed stimuli until MEPs could no longer be evoked in the EDC. Despite some interindividual variability, this procedure was sufficient to cover the entire cortical representation of the EDC in all subjects [31]. A visual grid (5 mm × 5 mm × 5 mm), predefined in the navigation software, was used for guidance during the mapping procedure, applying 2-3 stimuli per cell and resulting in an average of 10 stimuli per 1 cm2. Specifically, two stimuli were applied per cell; when one of them did not result in a response, a third stimulus was applied. The actual navigation coordinates of each stimulus were then used for data analysis, resulting in a spacing of approximately 3 mm, due to the small variability of the stimulation sites within each cell. Stimulation sites were visualized on the surface at a depth of 20 mm to ensure that the stimuli were located within the cortex in all subjects (range of scalp to cortex distance: 13–18.5 mm). This procedure was chosen due to the fact that the manufacturer allows adjustments to be made in steps of 5 mm only, that is, at 15 mm, 20 mm, and 25 mm. This TMS protocol thus resulted in stimulation sites 20 mm below the scalp and spaced approximately 3 mm apart with their coordinates located in individual MRI space. 2.3. Data Processing Data were analyzed using Matlab R2010b (MathWorks GmbH, Ismaning, Germany) with a custom-built code, the Toolbox SPM8 (Wellcome Trust Centre for Neuroimaging, London, UK), the FreeSurfer Software Suite (Martinos Centre for Biomedical Imaging, Charlestown, USA), and SPSS V21 (IBM GmbH, Ehningen, Germany). For data analyses, we then used the actual navigation coordinates (i.e., the MRI coordinates within the reference frame of the eXimia system) of each stimulus, resulting in an interstimulus spacing of approximately 3 mm. Finally, these spots were interpolated for visualization, sampled on a 1 × 1 × 1 mm grid to close the gap between stimulation sites, and then projected onto the gyral anatomy following the procedure described below [31]. Importantly, this interpolation technique increased the reliability of every single stimulus by considering all its neighboring stimulation results in a distance-weighted way. This technique also provides a higher level of focality than the conventional approach of treating each stimulus as a discrete event. The level of focality is thus higher than the actual area activated by the stimulation pulse. Please note that this interpolation procedure resulted formally in a volume (mm3) instead of the conventional surface (mm2) to describe the extension of the cortical map. Since the calculated value (mm3) was proportional to the real surface area (mm2) and was always calculated in the same way for all sessions, it provided a suitable measure for determining the test-retest reliability. During the mapping, about 100 stimuli were applied, with some subject-to-subject variability due to the individual cortical representation of the EDC [31]. Recent findings indicate that reliable motor maps could be created with around 60 stimuli [42]. During this study, the respective map could also be captured with less than 100 stimuli in subjects who had a small cortical representation of the EDC, while in others, more stimuli were required. Such variability of individual cortical maps has already been shown in detail elsewhere [31]. The procedure lasted for ~15 minutes and the subjects were instructed to keep their muscles relaxed during this time. During offline analysis, the EMG data were visually inspected and any trials in which muscle preactivation was detected were discarded (<1% of all trials had to be removed due to EMG activation). 2.3.1. nTMS Processing Since the stereotactic information provided by the nTMS (eXimia, Nexstim, Helsinki, Finland) refers to the coil position outside the head only, additional calculations are necessary to translate this information beyond the coil and onto the brain. We therefore used the coordinates of the TMS coil to project all stimulation points of the map onto the cortex in the direction of the magnetic field between the two coil windings [31]. The coil coordinates acquired via the navigation system were thereby transferred to the individual MR image of each subject at a depth of ~20 mm (see previous section). Thereafter, the mean MEP amplitude and the centre of gravity (CoG) of each map were determined. Due to the uncertainty of the exact stimulation depth using TMS, the CoG is usually calculated in two dimensions only. Moreover, we applied individual space (and not normalized space) to analyze the reliability of the CoG so as to enable us to compare it with the literature. The maximum amplitude-weighted stimulation point was calculated using the following formula [43]: (1) CoG=∑ai∗xiA,∑ai∗yiA with a i as the MEP amplitude at positions x i (medial-lateral) and y i (anterior-posterior) and A as the sum of all MEP amplitudes. The MEP amplitudes of all stimuli were then projected onto a 1 × 1 × 1 mm grid and interpolated by taking all neighboring stimulation results into account in a distance-weighted way. This resulted in a three-dimensional map area with mean MEP amplitude for each grid cell. The sum of active grid cells (with MEPs > 50 μV) subsequently resulted in the map area and the map volume (area ∗ mean map MEP), that is, the MEP amplitude-weighted area, for each measurement. Please note that this mean MEP amplitude is different from the mean Map MEP amplitude (Table 2) which captures all the noninterpolated stimulation amplitudes of one session. The individual MRI volumes and coregistered MEP maps were spatially normalized to MNI space, using SPM8 for further group analysis [44]. 2.3.2. FreeSurfer Processing The MNI normalized MRI images were then imported into the FreeSurfer software [31], which aligned the individual central sulci, and a cortical surface structure was reconstructed using the inbuilt functions [45]. An average brain surface with >160k mesh points was then created by coregistration of the cortical surface structures [44]. The coregistered MEP maps were first projected onto the individual surface structures with the inbuilt function mri_vol2surf of FreeSurfer and then transferred onto the average surface structure with mri_surf2surf. As a result, all maps were projected onto the same surface coordinate system, enabling us to gain further statistics for each mesh point of the cortical surface. This procedure enabled us to calculate the mean MEP amplitude over all measurements and subjects, the mean overlap of all subjects in the course of the experiments (in percent), and the intraclass correlation (ICC) values for the MEP amplitudes at each mesh point. 2.3.3. Statistical Analysis A repeated measure ANOVA (rmANOVA) with Greenhouse-Geisser correction was performed to determine differences in TMS parameters between sessions. Intraclass correlation was applied to compute the test-retest reliability [46] for mean map MEP, map area, map volume, RMT, coordinates of the CoG, and the MEP amplitudes at each stimulation site, that is, surface mesh point. A two-way random average measure (ICC(2, k)) was chosen in SPSS according to McGraw and Wong [47] for the map parameters. In addition, we calculated an ICC(1, k) value for each surface mesh point using the MEP amplitude in that coordinate. ICC values usually range from 0 to 1 but can become negative if the variance in the subject is higher than the group variance. Values above 0.75, between 0.5 and 0.75, and below 0.5 are regarded as reflecting high, moderate, and poor test-retest reliability, respectively [46]. 3. Results 3.1. Group Data of TMS Parameters The data of all experimental sessions was acquired and analyzed without any drop-outs and no significant mean differences of TMS parameters between sessions were revealed in the rmANOVA. The original TMS parameters of each hemisphere are summarized on the group level in Tables 1 and 2 and on the single subject level in Figures 1 and 2, respectively. 3.2. Reliability of TMS Parameters In the nondominant, right hemisphere, ICC values over six sessions showed high reliability for the RMT (ICC = 0.989; 95% Confidence Interval CI: 0.975 to 0.996, Figure 1(a)), the medial-lateral (ICC = 0.947; 95% CI: 0.882 to 0.983, Figure 1(b)) and anterior-posterior CoG (ICC = 0.98: 95% CI: 0.955 to 0.933, Figure 1(c)), and the mean map MEP amplitude, that is, the average of all MEP amplitudes of the cortical map (ICC = 0.869; 95% CI: 0.711 to 0.956, Figure 1(d)). The map volume (ICC = 0.695; 95% CI: 0.32 to 0.899, Figure 1(f)) and map area (ICC = 0.178; 95% CI: −0.879 to 0.73, Figure 1(e)) showed moderate and poor reliability, respectively. In the dominant, left hemisphere, ICC values over six sessions revealed high reliability for the RMT (ICC = 0.990; 95% CI: 0.970 to 0.998, Figure 2(a)), the medial-lateral (ICC = 0.979; 95% CI: 0.927 to 0.997, Figure 2(b)) and anterior-posterior CoG (ICC = 0.972; 95% CI: 0.914 to 0.996, Figure 2(c)), and the mean map MEP amplitude (ICC = 0.855; 95% CI: 0.566 to 0.977, Figure 2(d)). The map volume (ICC = 0.152; 95% CI: −0.130 to 0.535, Figure 2(f)) and map area (ICC = −0.056; 95%: −0.173 to 0.403, Figure 2(e)) revealed poor reliability. In three subjects, a seventh session (highlighted in red, Supplementary Figure 1 (a–f) in Supplementary Material available online at http://dx.doi.org/10.1155/2016/7365609) could be acquired for the nondominant hemisphere. The high reliability of the RMT (ICC = 0.995; 95% CI: 0.976 to 1), medial-lateral CoG (ICC = 0.973; 95% CI: 0.878 to 0.999) and anterior-posterior CoG (ICC = 0.892; 95% CI: 0.537 to 0.997), and the mean map MEP amplitude (ICC = 0.928; 95% CI: 0.664 to 0.998) in the previous six sessions could be preserved in the seventh measurement, that is, ~1.5 years after the sixth session. 3.3. Motor Map Group Data The mean overlap percentage revealed a high spatial overlap over the hand area of M1 and the corresponding somatotopic sensory (S1) area of both hemispheres; that is, in these regions (indicated in yellow) at least 75% of the subjects presented with MEPs > 50 μV. This core area was surrounded by a fringe area (indicated in red) extending medially and laterally on M1 and S1 and anteriorly on the premotor (PM) cortex. In this fringe area, less than 75% of the subjects presented with MEPs > 50 μV (Figure 3). The mean MEP amplitude depicted a smaller activation area than the previous overlap map; that is, activation was confined to those cortical areas in which all subjects had mean MEPs > 100 μV (indicated in yellow) and >50 μV (indicated in red) (Figure 4). Notably, this area covered a large part of M1 and S1 and extended towards the PM cortex in the left, dominant hemisphere, while it remained fairly restricted to the hand knob of M1 and the corresponding S1 in the right, nondominant hemisphere. These interhemispheric differences remained stable, even when the right cortical map was restricted to the very same six subjects who were analyzed for the left cortical map (Supplementary Figure 2). 3.4. Motor Map Reliability The intraclass correlation (ICC) values for the MEP amplitudes at each mesh point confirmed the previous cortical maps (of the mean MEP amplitude), showing the same interhemispheric differences and revealing moderate to high reliability (up to >0.75) of the MEP amplitude in the course of the six experiments (Figure 5). Interestingly, these long-term correlations of the MEP amplitude at each stimulation site presented mosaic-like clusters of consistent corticospinal excitability spanning over distributed areas in the sensorimotor cortex. 4. Discussion This study introduces complementary and highly consistent measures for capturing the extent of the cortical motor map with transcranial magnetic stimulation (TMS) and demonstrates the high test-retest reliability of these maps for long observation periods by considering the individual gyral anatomy. We examined motor-evoked potentials (MEPs) of the extensor digitorum communis muscle of healthy subjects over a period of twelve weeks with six biweekly acquired TMS motor maps, whereas previous studies on TMS test-retest reliability spanned observation periods of one to six weeks with a total of two to three measurements only [15, 48–54]. The demonstrated consistency of the acquired motor map parameters over several months qualifies them as biomarkers for monitoring disease progression or the effects of therapeutic interventions, for example, in the context of neurorehabilitation. However, these results need to be extrapolated carefully to individuals with brain damage since patients might have more variable cortical physiology. Particular attention should be paid to the specific TMS parameters chosen for long-term monitoring. Like previous studies, but for longer observation periods, we were able to disentangle the highly stable TMS parameters, that is, the resting motor threshold (RMT), centre of gravity (CoG), and mean MEPs across all TMS sites, from the more variable ones, that is, the map area. We, therefore, suggest not transferring the classical motor map parameters, map area and volume, to patients but rather the complementary ones introduced and tested in this study, that is, motor maps of the mean spatial overlap, the mean MEP amplitude, and the intraclass correlations of the MEP amplitude (see paragraphs below). More specifically, the high reliability, captured by the intraclass correlation (ICC), of the RMT and mean map MEP amplitude confirmed previous findings following shorter observation periods [49–53]. Former findings on the consistency of the CoG were more variable [15, 48, 51, 53] than the high reliability in the present study for observation periods of up to 1.5 years. When it came to the cortical representation area of corticospinal connectivity, the findings were more variable. With regard to the classical parameter map area, this study demonstrated poor reliability in the course of six sessions. This finding agrees with previous observations of decreasing reliability of the map area from moderate/high [51, 52] to poor/moderate [15] when increasing the length of the observation period and the number of measurements from two to three. These findings are probably related to the individual conditions of the subjects over time, that is, reflecting the natural daily or weekly fluctuations of the motor map extent [15]. To differentiate them from lasting cortical plasticity in the course of a disease or intervention, more stable cortical map parameters that are resistant to such natural fluctuations would be necessary. Accordingly, complementary measures for capturing the extent of the cortical motor map were suggested in the present study and revealed spatially specific areas of high reliability throughout the whole observation period of twelve weeks: motor maps of the mean spatial overlap, the mean MEP amplitude, and the ICC of the MEP amplitude enabled us to disentangle a highly reliable core from the surrounding fringe areas of corticospinal connectivity. Future studies may test whether the demonstrated reliability of these complementary motor map parameters will persist when acquired with fixed coil positions (e.g., lateromedial, posteroanterior) or monophasic stimulation. The overlap map of the present study revealed a core over the hand area of M1 and S1, surrounded by less consistent findings that extended medially and laterally on the sensorimotor cortex and anteriorly on the premotor cortex (Figure 3). These observations were confirmed by the two other motor maps, that is, maps of the mean MEP amplitude and the ICC of the MEP amplitude. However, both of these covered a smaller cortical area than the overlap map. Notably, the maps of the mean (Figure 4) and ICC (Figure 5) of the MEP amplitude in particular revealed relevant interhemispheric differences. In the left, dominant hemisphere, these maps covered a large area of M1 and S1 and extended towards the PM cortex, whereas they remained fairly restricted to the hand knob of M1 and the corresponding S1 in the right, nondominant hemisphere. Moreover, the ICC map unraveled mosaic-like clusters of consistent corticospinal excitability spanning over distributed areas in the sensorimotor cortex and intermingling with spots of decreased reliability. We interpret the spatial differences between the overlap maps and the mean MEP amplitude maps as a reflection of the high variability of the classical TMS parameter map area. More specifically, we propose that the map area represents the instantaneous cortical representation, that is, the natural daily or weekly fluctuations of the motor map extent, and that the mean MEP amplitude map (Figure 4) reflects a stable motor map that is more resistant to this variability. Rapid functional plasticity of the map area has already been described during different learning processes. Comparing implicit versus explicit motor learning could show an increase of the motor map during the implicit learning period, which was reversed to baseline as soon as explicit knowledge was gained [55]. In another study with Braille readers, the cortical map area varied with the activity of the hand, that is, showing a larger map area during working days than at weekends [56]. By contrast, the stable interhemispheric differences of the mean MEP amplitude map and the ICC map in this study were very probably related to the right-handedness of the participants. This implied a lifelong higher use of the right hand in activities of daily living and therefore a persistent use-dependent reorganization and more extended (towards premotor and somatosensory areas) cortical representation area of this hand in the left, dominant hemisphere [54, 57]. However, further studies with more subjects are necessary to draw definite conclusions. The present study confirmed earlier animal experiments [58–61] and human studies [14, 39, 62–64], which indicated that corticospinal connections are not limited to the primary motor cortex but extend to different regions of the sensorimotor system. Approximately half of the primate brain's pyramidal tract neurons are located in postcentral areas, for example, the primary somatosensory cortex, sharing functional properties with regard to movement-related activity and discharge patterns as a function of muscle strength with precentral pyramidal tract neurons [31, 65–67]. In the present study, we confirmed this extended corticospinal connectivity of the somatosensory cortex and demonstrated marked interhemispheric differences, that is, highly reliable MEPs elicited from the left S1 of the dominant hemisphere, in healthy subjects. However, due to the rather nonfocal nature of TMS, a complementary explanation of these findings might be possible. Even if the centre of the TMS coil is over the primary somatosensory cortex, this does not necessarily mean that somatosensory cortex stimulation produces the descending volley. It could mean that neurons located rather posterior in the motor cortex, but still anterior to the somatosensory cortex, are activated by the magnetic stimulation delivered to S1 [39]. Therefore, we clearly acknowledge that it is not possible for this type of study to draw conclusions regarding the precise site of cortical stimulation. On the other hand, intraoperative electrical stimulation in humans with both mono- and bipolar focal stimulation of the premotor and somatosensory cortex also elicited MEPs [39, 63], supporting the hypothesis of direct corticospinal connectivity of nonprimary motor cortex areas. Despite the fact that they have considerably less spatial resolution than surgical mapping techniques, the TMS maps unraveled mosaic-like clusters of consistent corticospinal excitability. This is consistent with the findings of intracortical microstimulation in nonhuman primates which demonstrated that identical movements are elicited by the stimulation of multiple and noncontiguous sites [39, 60]. Although previous studies have already suggested that TMS maps are suitable for reproducing these experimental microstimulation findings in humans [15, 52], the present examination is the first to demonstrate the long-term reliability of this specific cortical pattern and to characterize the extended topographic distribution in the sensorimotor cortex intermingled with spots of decreased reliability. We consider this pattern to be evidence of the specific activation of neuronal pools in the respective cortical areas, for example, S1 or PM, thus rendering the alternative explanation, that is, the current spread to distant areas such as to M1 and the pyramidal tract, rather unlikely. These findings therefore underline the TMS technique presented here as a powerful and precise mapping tool for clinical and research application. Interestingly, this study is the first to demonstrate the long-term retest reliability of corticospinal connectivity of the premotor cortex, for the left, dominant hemisphere in particular. The right, nondominant hemisphere showed a larger fluctuation of the PM corticospinal connectivity, suggesting that this pathway is a dormant reserve for compensatory activation, for example, when the nondominant hand is used more frequently or when lesions of the M1 corticospinal connections, for example, after stroke, necessitate alternative pathways. Along the same lines, recent neurofeedback interventions have explored the plasticity of the nondominant, right hemisphere in the healthy [39] and lesioned brain [37, 68]. These findings indicate that combining motor imagery-related β-band event-related desynchronization with proprioceptive feedback in a brain-robot interface environment [69, 70] might be sufficient to unmask latent corticospinal connectivity [37], redistribute sensorimotor connectivity patterns, and enhance corticospinal pathways of both the S1 and PM cortex [39, 71]. Moreover, pilot data applying this concept demonstrated operant conditioning of the targeted brain state and provided a direct brain-behavior relationship [72] with functional gains after stroke, which were specific for the trained task [68]. 5. Conclusion We demonstrated the high test-retest reliability of the applied TMS mapping technique for long observation periods. This study revealed the long-term reliability of motor maps with relevant interhemispheric differences, that is, more extended and stable corticospinal connectivity in the sensorimotor cortex and nonprimary motor areas of the left, dominant hemisphere. Different cortical maps allowed the disentangling of stable cortical reorganization from more rapid plastic fluctuations. Mosaic-like clusters of consistent corticospinal excitability spanning over distributed areas in the sensorimotor cortex indicated functionally specific and spatially precise activation of neuronal pools by TMS. Moreover, these findings may guide restorative interventions addressing dormant corticospinal connectivity for neurorehabilitation. Supplementary Material Supplementary figure 1: Intrasubject distribution of original data for seven experimental sessions. Supplementary figure 2: Motor map group data with mean MEP amplitude in the right hemisphere for the same six subjects examined in the left hemisphere. Acknowledgments Dominic Kraus was supported by the Graduate Training Centre of Neuroscience, International Max Planck Research School for Cognitive and Systems Neuroscience, Tuebingen, Germany. The authors thank Dr. Robert Bauer for his statistical advice and Seyed A. Nicksirat for his help with the figures. Alireza Gharabaghi was supported by grants from the German Research Council [DFG GH 94/2-1, DFG EC 307] and from the Federal Ministry of Education and Research [BFNT 01GQ0761, BMBF 16SV3783, BMBF 0316064B, and BMBF 16SV5824]. Competing Interests The authors report no competing interests. Figure 1 Intrasubject distribution of original data for six experimental sessions (■: Session 1; ●: Session 2; ▲: Session 3; ▼: Session 4; ◆: Session 5; ◄: Session 6) in the right, nondominant hemisphere of twelve subjects for RMT (a), medial-lateral CoG (b), anterior-posterior CoG (c), mean map MEP amplitude (d), map area (e), and map volume (f). Figure 2 Intrasubject distribution of original data for six experimental sessions (■: Session 1; ●: Session 2; ▲: Session 3; ▼: Session 4; ◆: Session 5; ◄: Session 6) in the left, dominant hemisphere of six subjects for RMT (a), medial-lateral CoG (b), anterior-posterior CoG (c), mean map MEP amplitude (d), map area (e), and map volume (f). Figure 3 Motor map group data of individual means over time with mean overlap percentage. Color bar indicates percent of subjects presenting with MEPs > 50 μV throughout the experimental sessions. Figure 4 Motor map group data of individual means over time with mean MEP amplitude. Color bar indicates mean MEP amplitude in μV throughout the experimental sessions. Figure 5 Motor map reliability with intraclass correlation (ICC) for the MEP amplitudes > 50 μV at each mesh point. Color bar indicates ICC value of repeatability in the course of the six experiments revealing mosaic-like clusters of consistent corticospinal excitability. Table 1 Right hemisphere: original group data of TMS parameters (resting motor threshold, the coordinates of the centre of gravity, mean map MEP amplitude, map area, and map volume) for six experimental sessions in the right, nondominant hemisphere of twelve subjects.   Session   Session 1 Session 2 Session 3 Session 4 Session 5 Session 6 RMT (% MSO) 43.1 ± 8.0 44.1 ± 8.6 44.2 ± 8.8 44.1 ± 8.4 43.0 ± 8.2 43.1 ± 8.4 CoG m-l (mm) 60.7 ± 6.4 61.3 ± 3.8 60.9 ± 5.4 60.9 ± 4.3 60.7 ± 4.6 60.0 ± 4.4 CoG a-p (mm) 109.0 ± 8.4 108.9 ± 9.7 108.0 ± 8.9 107.3 ± 10.6 107.2 ± 9.6 105.7 ± 10.9 Mean map MEP amplitude (µV) 255.6 ± 155.3 240.7 ± 147.9 165.3 ± 48.3 227.5 ± 177.7 190.9 ± 144.7 227.5 ± 118.1 Map area (mm3) 1795.6 ± 1006 2291.4 ± 1118.3 2306.8 ± 1979.8 1958.4 ± 1597.6 1522.7 ± 969.4 2299.5 ± 1125.5 Map volume (mm3 ∗µV) 512772.6 ± 475433.5 650398.9 ± 579946.1 405527.8 ± 380330.5 678479.5 ± 1120122.4 331512.3 ± 345943.7 579769.2 ± 444784.6 Mean ± SD. Table 2 Left hemisphere: original group data of TMS parameters (resting motor threshold, the coordinates of the centre of gravity, mean map MEP amplitude, map area, and map volume) for six experimental sessions in the left, dominant hemisphere of six subjects.   Session   Session 1 Session 2 Session 3 Session 4 Session 5 Session 6 RMT (% MSO) 42.3 ± 7.9 44.7 ± 7.4 44.7 ± 7.8 43.7 ± 7.9 44.3 ± 10.2 43.7 ± 8.7 CoG m-l (mm) 134.5 ± 6.2 135.5 ± 5.9 135.3 ± 7.2 133.9 ± 8.2 132.2 ± 7.2 131.0 ± 7.3 CoG a-p (mm) 108.9 ± 11.3 109.4 ± 9.5 106.9 ± 8.5 111.7 ± 8.2 112.4 ± 7.7 111.3 ± 8.9 Mean map MEP amplitude (µV) 242.5 ± 98.9 269.6 ± 106.8 275.5 ± 142.7 227.9 ± 122.7 209.5 ± 140.9 179.4 ± 53.1 Map area (mm3) 1726.8 ± 1359.7 1805 ± 839.8 2134.0 ± 1530.9 1616.3 ± 1132.3 1818.5 ± 667.4 1491.5 ± 614.9 Map volume (mm3 ∗µV) 442868.3 ± 470689.2 468965.8 ± 268648.9 531075.8 ± 324023.0 448895.9 ± 498086.2 381524.2 ± 239264.6 258593.3 ± 100338.3 Mean ± SD. ==== Refs 1 Xerri C. 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==== Front J Drug DelivJ Drug DelivJDDJournal of Drug Delivery2090-30142090-3022Hindawi Publishing Corporation 10.1155/2016/9024173Research ArticleDesign, Characterization, and Optimization of Controlled Drug Delivery System Containing Antibiotic Drug/s http://orcid.org/0000-0002-3325-9604Patel Apurv * http://orcid.org/0000-0001-7658-6544Dodiya Hitesh Shelate Pragna http://orcid.org/0000-0002-0968-0749Shastri Divyesh Dave Divyang Department of Pharmaceutics and Pharmaceutical Technology, K.B. Institute of Pharmaceutical Education and Research Center, Gandhinagar 382023, India*Apurv Patel: patel.apurv.m@gmail.comAcademic Editor: Ali Nokhodchi 2016 16 8 2016 2016 902417315 3 2016 3 7 2016 Copyright © 2016 Apurv Patel et al.2016This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The objective of this work was design, characterization, and optimization of controlled drug delivery system containing antibiotic drug/s. Osmotic drug delivery system was chosen as controlled drug delivery system. The porous osmotic pump tablets were designed using Plackett-Burman and Box-Behnken factorial design to find out the best formulation. For screening of three categories of polymers, six independent variables were chosen for Plackett-Burman design. Osmotic agent sodium chloride and microcrystalline cellulose, pore forming agent sodium lauryl sulphate and sucrose, and coating agent ethyl cellulose and cellulose acetate were chosen as independent variables. Optimization of osmotic tablets was done by Box-Behnken design by selecting three independent variables. Osmotic agent sodium chloride, pore forming agent sodium lauryl sulphate, and coating agent cellulose acetate were chosen as independent variables. The result of Plackett-Burman and Box-Behnken design and ANOVA studies revealed that osmotic agent and pore former had significant effect on the drug release up to 12 hr. The observed independent variables were found to be very close to predicted values of most satisfactory formulation which demonstrates the feasibility of the optimization procedure in successful development of porous osmotic pump tablets containing antibiotic drug/s by using sodium chloride, sodium lauryl sulphate, and cellulose acetate as key excipients. ==== Body 1. Introduction Oral controlled drug delivery system can provide continuous delivery of drugs at controlled rate and predictable kinetics throughout the GI transit. Oral controlled drug delivery system targets drug delivery to a specific region for either local or systemic effect throughout the GI transit. This system also gives zero-order release profile [1]. Oral controlled release system can provide better effectiveness in treatment of chronic disease, reduce side effects, and improve patient compliance due to less frequent dosing interval. Drug release from oral controlled release dosage forms are affected by pH of GI fluid, GI motility, and presence of food in GI tract. Drug release from osmotic drug delivery system is independent of pH and other physiochemical parameters and it is possible to modulate the release characteristic by optimizing the properties of drug and system [2, 3]. Osmotic pressure is used as driving force for osmotic drug delivery systems to release the drug in controlled manner. Osmotic pressure created due to imbibition of fluid from external environment into the dosage form regulates the delivery of drug from osmotic device. Osmotic drug delivery technique is the most interesting and widely acceptable among all other technologies used for the same purpose. Intensive research has been carried out on osmotic systems and several patents are also published. These systems can be used for both routes of administration, that is, oral and parenteral. Oral osmotic systems are known as gastrointestinal therapeutic systems (GITS). Parenteral osmotic drug delivery includes implantable pumps [3]. Dicloxacillin sodium and amoxicillin trihydrate are β-Lactam antibiotics. Dicloxacillin sodium and amoxicillin trihydrate have short half-life and high protein binding. The drug that shows linear pharmacokinetics is suitable for oral controlled release tablets and it would be advantageous to slow down its release in GI tract not only to prolong its therapeutic action but also to minimize side effects of drugs. 2. Material and Methods 2.1. Materials Dicloxacillin sodium was obtained as gift sample from Suvik Hitek Pvt. Ltd. (Gandhinagar, India). Amoxicillin trihydrate was obtained as gift sample from Astral Life Care (Mumbai, India). Sodium chloride was purchased from Merck Pharmaceutical (Mumbai, India). Sodium lauryl sulphate was purchased from Bombay Tablet (Gandhinagar, India). Cellulose acetate and PVP K30 were purchased from Chemdyes Corporation (Gujarat). Magnesium stearate and talc were purchased from Suvik Hitek Pvt. Ltd. (Gandhinagar, India). 2.2. Differential Scanning Calorimetry (DSC) DSC studies were carried out for the pure drug, physical mixtures of drug and excipients, and placebo of the porous osmotic pump tablets to study the compatibility. The analysis was performed under nitrogen (nitrogen flow rate 50 mL/min) in order to eliminate oxidative and pyrolytic effects at a standard heating rate of 10°C/min over a temperature range of 50°C–400°C using Universal V4 5A TA instruments. 2.3. Preparation of Porous Osmotic Pump Tablet 2.3.1. Preparation of Core Tablets Core tablets of dicloxacillin sodium were prepared by wet granulation method. All the ingredients were sieved through # 40 sieve. Individual ingredients, sufficient for a batch of 25 tablets, were weighed on a digital weighing balance as per Table 1. All the ingredients (except PVP K30, magnesium stearate, and talc) were mixed in mortar and pestle using geometric dilution method. The dry blend was granulated with sufficient quantity of PVP K30 which was dissolved in isopropyl alcohol. The powder mass was dried at 60°C in hot air oven for 6 h and passed through # 20 sieve. Then dried granules were mixed with magnesium stearate and talc for 3 min. Tablets were prepared by 9 mm concave die punch set using rotary tablet punching machine [4, 5]. 2.3.2. Method of Preparation of Tablet Coat Solution Cellulose acetate and PEG 400 were added to 3/4th of the total volume of acetone and stirred at 35 rpm using propeller stirrer for half an hour till the solution was clear. Magnesium stearate and coloring agent were triturated thoroughly in a mortar and added to the above solution and stirring continued further. Finally, the volume was made up with acetone [4, 5] (see Table 2). 2.4. Coating of the Core Tablets Tablet coating was done using coating pan apparatus. Speed of coating pan was set at 30 rpm, and inlet air temperature and flow rate were 50°C and 3.2 kg/min, respectively. Spraying rate for coating solution was kept at 4-5 mL/min. Number of tablets per batch was fixed at 50 tablets. Ten tablets of test batch were mixed with 40 dummy tablets. Empty coating pan was run at above set parameters for 5 min. Tablets were loaded to the pan and allowed to gain equilibrium. Coating solution was sprayed at 5 mL/min rate for 2-3 seconds. Coating solution on the tablets was allowed to dry for 5 min and again sprayed. Approximately 100 mL coating solution was used for a batch of 50 tablets. 2.5. Characterization of Osmotic Tablet 2.5.1. Hardness The fracture strength, which is defined as the force, was required to break a tablet by radial compression and was measured with a Monsanto tablet hardness tester in present study. The mean hardness is calculated and expressed as kg/cm2. 2.5.2. Friability The friability of the tablets was measured in a Roche friabilator. Tablets of a known weight (w 0) or a sample of 10 tablets are dedusted in a drum for a fixed time (100 revolutions) and weighed (w) again. Percentage friability was calculated from the loss in weight as given in equation as below. The weight loss should not be more than 1%. Consider (1) %  Friability=w0−ww0×100. 2.5.3. Weight Variation Test To study weight variation, 20 tablets of each formulation were weighed using an electronic balance individually, calculating the average weight, and comparing the individual tablet weights to the average. The tablets meet the IP test if no more than 2 tablets are outside the percentage limit and if no tablet differs by more than 2 times the percentage limit. 2.5.4. Thickness The thickness of the tablets was determined using a Vernier caliper. 20 tablets were used and mean was calculated. Tablet thickness should not deviate by ±5%. 2.6. Determination of Drug Content Ten tablets were accurately weighed and powdered. A quantity of the powder equivalent to 100 mg of dicloxacillin sodium was weighed accurately and extracted in 100 mL water by shaking for 20 min. After filtration through Whatman filter paper number 1 and sufficient dilution with water, samples were analyzed spectrophotometrically at 273 nm. Amount of drug present was determined from the calibration curve of dicloxacillin sodium [5]. 2.7. In Vitro Drug Release Study The release rate of dicloxacillin sodium from developed tablets was determined using USP dissolution testing apparatus I (Basket type). The dissolution test was performed using 900 mL 0.1 M HCl (pH 1.2) for 2 hr and then in pH 6.8 phosphate buffer for 10 hr, at 37 ± 0.5°C and 100 rpm. A sample (1 mL) of the solution was withdrawn from the dissolution apparatus hourly for 12 h, and the samples were replaced with fresh dissolution medium. The samples were passed through Whatman filter paper after dilution and the absorption of these solutions was measured at 273 nm. The cumulative percentage drug release was calculated. 2.8. Curve Fitting Analysis For the determination of the drug release kinetics from the porous osmotic pump tablet, the in vitro release data were analyzed by zero-order, first-order, Higuchi, and Korsmeyer and Peppas equations [6]. 2.9. Zero-Order Release Kinetics To study the zero-order release kinetics the release data was fitted into the following equation: (2) dQdt=K0, where “Q” is the amount of drug release, “K 0” is the zero-order release rate constant, and “t” is the release time. The graph is plotted percentage cumulative drug release (% CDR) versus time. 2.10. First-Order Release Kinetics To study the first-order release kinetics the release rate data are fitted into the following equation: (3) dQdt=K1Q, where “Q” is the fraction of drug release, “K 1” is the first-order release rate constant, and “t” is the release time. 2.11. Higuchi Release Model To study the Higuchi release model the release rate data are fitted into the following equation: (4) Q=KHt1/2, where “Q” is the fraction of drug release, “K H” is the release rate constant, and “t” is the release time. The graph is plotted as % CDR versus square root of time. 2.12. Korsmeyer and Peppas Kinetics To study the Korsmeyer and Peppas release kinetics the release rate data are fitted into the following equation: (5) MtM∞=KKPtn, where M t/M ∞ is the fraction of drug release, “K KP” is the release rate constant, “t” is the release time, and “n” is the diffusion exponent related to mechanism of drug release. The graph is plotted as log % CDR versus log time [6]. 2.13. Selection of Polymers by Plackett-Burman Factorial Design A Plackett-Burman design was adopted to selection of polymers of different category. In this design six factors were evaluated. Hence by applying Plackett-Burman factorial design, influence of six independent variables, osmotic agents (NaCl, MCC), pore forming agents (SLS, sucrose), and coating agents (cellulose acetate, ethyl cellulose), was studied over three dependent variables' drug release at 2 hr, 6 hr, and 12 hr and was checked [6, 7]. Formulation of osmotic tablets of factorial batches is shown in Tables 3 and 4. 2.14. Optimization of Osmotic Tablet by Box-Behnken Factorial Design In this optimization technique, the desirability approach was used to generate the optimum settings for the formulation. From the trial batches, three independent variables were found to affect drug release significantly. Concentration of coating agent (NaCl) and pore forming agent (SLS) and concentration of coating agent (cellulose acetate) were taken as independent variables [8, 9]. For the optimized formulation, the drug release at 2 hr, 6 hr, and 12 hr and release exponent (n) were kept in target. Formulation of osmotic tablets of factorial batches is shown in Tables 5 and 6. 2.15. Effect of pH on Drug Release The optimized formulation of porous osmotic pump tablets was tested for the effect of pH on drug release. The best formulations were undergone in dissolution studies in 0.1 N HCl, 6.8 pH phosphate buffer, 7.5 pH phosphate buffer, and distilled water in rotation speed of 100 rpm and 37 ± 0.5°C using USP dissolution test apparatus type 1. 2.16. Effect of Agitation Intensity Drug Release The optimized formulation of matrix and porous osmotic pump tablets are tested for the effect of agitation intensity on drug release. The best formulations are undergone in dissolution studies by maintaining different rotation speed of 50, 100, and 150 rpm and at 37 ± 0.5°C in 7.5 pH phosphate buffer for 8 h using USP dissolution test apparatus type 1. 2.17. Stability Studies The stability studies were carried out as per the ICH and WHO guidelines of stability testing. Optimized formulations were kept inside the stability chamber maintained at 45°C and 75% RH for the period of 30 days. At the end of the stability study period, samples were analyzed for parameters like physical characteristics, drug content, and in vitro drug release. 3. Result and Discussion 3.1. Drug Polymer Compatibility Studies Using DSC DSC thermograms of pure drug (dicloxacillin sodium) and physical mixtures of drug and excipients (NaCl, SLS, and CA) were studied for their interactions. It was observed that there was no significant drug polymer interaction observed among drug, NaCl, SLS, and CA even at higher temperature. From DSC study, we can see that there is no change in drug's melting peak (169.28°C–172.77°C) after the preparation of mixture. There is the no interaction between drug and excipient shown in this study. So, we can conclude that drug is compatible with all polymers. DSC thermograms were shown in Figures 1 and 2. 3.2. Screening of Polymers by Plackett-Burman Factorial Design 3.2.1. Physicochemical Properties Twelve batches were prepared for screening of polymers. The mean values of hardness, friability, thickness, weight, and drug content of prepared porous osmotic pump tablets are shown in Table 7. 3.2.2. In Vitro Dissolution Study To study all the possible combinations of all factors at all levels, a six-factor, two-level Plackett-Burman factorial design was constructed and conducted in a fully randomized order. Six factors, NaCl(X1), MCC(X2), SLS(X3), sucrose(X4), EC(X5), and CA(X6), were selected as independent variables. Twelve batches were prepared to study Plackett-Burman factorial design for osmotic tablets. Two checkpoint batches were also evaluated to validate the design. The dependent variables (responses) studied were % drug release after 1 hr, 6 hr, and 12 hr of dissolution. Results of the drug release profile obtained for osmotic tablets are shown in Figures 3(a), 3(b), 3(c), and 3(d). Effect of formulation variable on drug release at 1 hr, 6 hr, and 12 hr was carried out using Design-Expert Software (Version 7.1.6, Stat-Ease Inc., Minneapolis, MN). Effect of Formulation Variable on Drug Release at 1 hr (Y1). From the equation, factor value of X1 was +2.08 and X2 was −1.41 indicating that X1 had more effect on drug release than X2. Factor value of X3 was +5.75 and X4 was +0.41 indicating that X3 had more effect on drug release than X4. Factor value of X5 was +0.08 and X6 was +0.53 indicating that X6 had more effect on drug release than X5. Positive sign of X1, X3 , and   X6 indicates positive effect on drug release. Figures 4(a)–4(d) show contour plot and 3D surface plot for Y1 suggesting effect of variables as described above. Consider (6) Y1=2.08X1−1.41X2+5.75X3+0.41X4+0.08X5+0.53X6. The relationship between formulation variables (X1 and X2) and Y1 was further elucidated using 3D surface plot. From Figure 4(b) it can be concluded that factor NaCl(X1) had more osmotic effect on drug release while MCC(X2) had no significant effect on drug release. The relationship between formulation variables (X3 and X4) and Y1 was further elucidated using 3D surface plot. From Figure 4(d) it can be concluded that factor SLS(X3) had more pore forming effect on drug release while sucrose(X4) had no significant effect on drug release. Effect of Formulation Variable on Drug Release at 6 hr (Y2). From the equation, factor value of X1 was +6.66 and X2 was −3.66 indicating that X1 had more effect on drug release than X2. Factor value of X3 was +12.66 and X4 was +0.66 indicating that X3 had more effect on drug release than X4. Factor value of X5 was −0.16 and X6 was +3.83 indicating that X6 had more effect on drug release than X5. Positive sign of X1, X3, and  X6 indicates positive effect on drug release. Figures 5(a)–5(d) show contour plot and 3D surface plot for Y2 suggesting effect of variables as described above. Consider (7) Y2=6.66X1−3.66X2+12.66X3+0.66X4−0.16X5+3.83X6. The relationship between formulation variables (X1 and X2) and Y2 was further elucidated using 3D surface plot. From Figure 5(b) it can be concluded that factor NaCl(X1) had more osmotic effect on drug release while MCC(X2) had no significant effect on drug release. The relationship between formulation variables (X3 and X4) and Y2 was further elucidated using 3D surface plot. From Figure 5(d) it can be concluded that factor SLS(X3) had more pore forming effect on drug release while sucrose(X4) had no significant effect on drug release. Effect of Formulation Variable on Drug Release at 12 hr (Y3). From the equation, factor value of X1 was +5.08 and X2 was −5.19 indicating that X1 had more effect on drug release than X2. Factor value of X3 was +19.75 and X4 was −1.08 indicating that X3 had more effect on drug release than X4. Factor value of X5 was +2.41 and X6 was +7.25 indicating that X6 had more effect on drug release than X5. Positive sign of X1, X3, and  X6 indicates positive effect on drug release. Figures 6(a)–6(d) show contour plot and 3D surface plot for Y3 suggesting effect of variables as described above. Consider (8) Y3=5.08X1−5.19X2+19.75X3−1.083X4+2.41X5+7.25X6. The relationship between formulation variables (X1 and X2) and Y3 was further elucidated using 3D surface plot. From Figure 6(b) it can be concluded that factor NaCl(X1) had more osmotic effect on drug release while MCC(X2) had no significant effect on drug release. The relationship between formulation variables (X3 and X4) and Y3 was further elucidated using 3D surface plot. From Figure 6(d) it can be concluded that factor SLS(X3) had more pore forming effect on drug release while sucrose(X4) had no significant effect on drug release. 3.3. Optimization of Osmotic Tablet by Box-Behnken Factorial Design 3.3.1. Physiochemical Parameter 15 batches were prepared for optimization of osmotic tablets. Tablets were evaluated for uniformity of weight, uniformity of contents, tablet thickness and diameter, and hardness and friability. Results of the physiochemical tests obtained are shown in Table 8. 3.3.2. In Vitro Dissolution Study To study all the possible combinations of all factors at all levels, a three-factor, three-level Box-Behnken factorial design was constructed and conducted in a fully randomized order. Three factors, NaCl(X1), SLS(X2), and CA(X3), were selected as independent variables. 15 batches were prepared to study Box-Behnken factorial design for osmotic tablets. Two checkpoint batches were also evaluated to validate the design. The dependent variables (responses) studied were % drug release after 1 hr, 6 hr, and 12 hr of dissolution. Results of the drug release profile obtained for osmotic tablets are shown in Figures 7(a), 7(b), 7(c), and 7(d). Figure 7(a) contains dissolution profile for batches F13–F16. Figure 7(b) contains dissolution profile for batches F17–F20. Figure 7(c) contains dissolution profile for batches F21–F124. Figure 7(d) contains dissolution profile for batches F25–F127. Effect of Formulation Variable on Drug Release at 1 hr (Y1). Equation shows that coefficients b 1 and b 2 bear a positive sign and b 3 bears a negative sign and coefficient value for X1 is 7.50, X2 is 0.25, and X3 is −0.50. So it indicates that X1 has more effect on drug release than X2 and X3. Figures 8(a) and 8(b) show cube and 3D surface plot for Y1 suggesting effect of variables as described above. Consider (9) Y1=7.50X1+0.25X2−0.50X3+1.50X1X2+0.00X1X3+0.50X2X3−1.92X12+1.58X22+0.58X32. The relationship between formulation variables (X1, X2, and X3) and Y1 was further elucidated using cube and 3D surface plot. From Figure 8(a) it can be concluded that factor Nacl(X1) has more effect on drug release than SLS(X2). From Figure 8(b) it can be concluded that factor X3 (Coating agent) has negative effect on drug release. As we increase the level of X3, it decreases drug release. Effect of Formulation Variable on Drug Release at 6 hr (Y2). Equation shows that coefficients b 1 and b 2 bear a positive sign and b 3 bears a negative sign and coefficient value for X1 is 11.62, X2 is 0.38, and X3 is −0.75. So it indicates that X1 has more effect on drug release than X2 and X3. Figures 9(a) and 9(b) show cube and 3D surface plot for Y2 suggesting effect of variables as described above. Consider (10) Y1=11.62X1+0.38X2−0.75X3+3.25X1X2+0.50X1X3+0.00X2X3−3.54X12+3.96X22−0.96X32. The relationship between formulation variables (X1, X2, and X3) and Y2 was further elucidated using cube and 3D surface plot. From Figure 9(a) it can be concluded that factor NaCl(X1) has more effect on drug release than SLS(X2). From Figure 9(b) it can be concluded that factor X3 (Coating agent) has negative effect on drug release. As we increase the level of X3, it decreases drug release. Effect of Formulation Variable on Drug Release at 12 hr (Y3). Equation shows that coefficients b 1 and b 2 bear a positive sign and b 3 bears a negative sign and coefficient value for X1 is 17.50, X2 is 0.88, and X3 is −0.80. So it indicates that X1 has more effect on drug release than X2 and X3. Figures 10(a) and 10(b) show cube and 3D surface plot for Y2 suggesting effect of variables as described above. Consider (11) Y3=17.50X1+0.88X2−0.80X3+5.00X1X2−1.00X1X3+2.25X2X3−1.29X12+5.96X22−1.04X32. The relationship between formulation variables (X1, X2, and X3) and Y3 was further elucidated using cube and 3D surface plot. From Figure 10(a) it can be concluded that factor NaCl(X1) has more effect on drug release than SLS(X2). From Figure 10(b) it can be concluded that factor X3 (coating agent) has negative effect on drug release. As we increase the level of X3, it decreases drug release. 3.4. Selection of Optimized Batch Selection of best batch was carried out using Design-Expert Software (Version 7.1.6, Stat-Ease Inc., Minneapolis, MN). After statistical analysis the desirability function was applied to select the best batch. The desirable values selected for dependent variables Y1, Y2, and  Y3 are given in Table 9. Desirable value range selected that was 5% varies from optimum value. Batch F22 came closest to satisfying all the selection criteria. The results were further reinstated using the overlay plot in Figure 11. The yellow region of the plot indicates the area where all the selection criteria are satisfied. Batch F22 falls in this yellow area, indicating the formulation having amount of osmotic agent (150 mg), pore forming agent (15 mg), and coating agent (2%) that possessed the desirable characteristics. 3.5. So F22 Batch Was Selected as Optimized Batch 3.5.1. Effect of pH on Drug Release When formulation F22 was subjected to in vitro release studies in buffers with different pH and distilled water, no significant differences in the release profiles were seen compared to that in phosphate buffer pH 6.8. Thus the fluid in different parts of the GI tract will scarcely affect drug release from the osmotic system. 3.5.2. Effect of Agitation Intensity on Drug Release The release profile of dicloxacillin sodium from the optimized formulation F22 was independent of the agitational intensity of the release media. 4. Osmotic Tablet of Amoxicillin Trihydrate Optimized batch of amoxicillin trihydrate was prepared using F22 batch composition of Box-Behnken design batches. From the drug release data and also release pattern shown in Figure 12 it can be concluded that there is no significant difference between two drug release profiles. 5. Release Kinetics and Release Mechanism Six kinetic models were used for controlled release curve fitting to select the most appropriate model. The dissolution data for optimized batch was fitted to the zero-order, first-order, Higuchi, Hixson-Crowell, Korsmeyer-Peppas, and Weibull models. Best fitting model was selected on the basis of highest correlation coefficient and lowest F value. Comparative statistical parameters for all the models were obtained as shown in Table 11. Drug release mechanism was explored on the basis of release exponent (n) value. Model fitting results revealed that the Korsmeyer-Peppas model was best fitted to the release kinetics (r 2 = 0.9960, highest; F = 6.8629, lowest). Higuchi model was also close to the Korsmeyer-Peppas model. Hence F test was performed for both models. It revealed significant difference between the two models. Hence Korsmeyer-Peppas model was finally selected as best fitted model. Release exponent n was found to be 0.580, indicating that the drug was released from the formulation by anomalous (non-Fickian) mechanism. 6. Stability Study After the 1-month storage of formulation F22, values of all parameters like hardness, diameter, thickness, % drug content, and friability were checked periodically and found to be almost similar to the initial values. The drug profile was similar to the initial profile shown in Figure 13. There was not any significant change in any value and also no changes in the physical appearance. So it can be said that formulation is stable (see Table 12). 7. Conclusion The observed independent variables were found to be very close to predicted values of optimized formulation which demonstrates the feasibility of the optimization procedure in successful development of porous osmotic pump tablets containing dicloxacillin sodium and amoxicillin trihydrate as model drug by using sodium chloride (150 mg) as osmotic agent, sodium lauryl sulphate (15 mg) as pore former, cellulose acetate (2%) as coating agent, and control membrane permeability. Batch F22 was selected as optimized batch. Stability studies also revealed that optimized formulation is stable. From the comparison of dissolution profile of optimized batch for both drugs (dicloxacillin sodium and amoxicillin trihydrate) it can be concluded that there was no significance difference in drug release observed, so it concludes that porous osmotic pump tablets of antibiotic drugs were successfully developed (see Table 10). Competing Interests The authors declare that they have no competing interests. Figure 1 DSC spectra of pure drug (dicloxacillin sodium). Figure 2 DSC spectra of drug and polymers. Figure 3 (a) Drug release profile for batches F1 to F3. (b) Drug release profile for batches F4 to F6. (c) Drug release profile for batches F7 to F9. (d) Drug release profile for batches F10 to F12. Figure 4 (a) Contour plot for response Y1 (drug release at 1 hr) (for X1  and  X2). (b) 3D surface plot of response Y1 (drug release at 1 hr) (for X1  and  X2). (c) Contour plot for response Y1 (drug release at 1 hr) (for X3  and  X4). (d) 3D surface plot of response Y1 (drug release at 1 hr) (for X3  and  X4). Figure 5 (a) Contour plot for response Y2 (drug release at 6 hr) (for X1  and  X2). (b) 3D surface plot of response Y2 (drug release at 6 hr) (for X1  and  X2). (c) Contour plot for response Y2 (drug release at 6 hr) (for X3 and  X4). (d) 3D surface plot of response Y2 (drug release at 6 hr) (for X3  and  X4). Figure 6 (a) Contour plot for response Y3 (drug release at 12 hr) (for X1  and  X2). (b) 3D surface plot of response Y3 (drug release at 12 hr) (for X1  and  X2). (c) Contour plot for response Y3 (drug release at 12 hr) (for X3  and  X4). (d) 3D surface plot of response Y3 (drug release at 12 hr) (for X3  and  X4). Figure 7 (a) Drug release profile for batches (F13–F16). (b) Drug release profile for batches (F17–F20). (c) Drug release profile for batches (F21–F24). (d) Drug release profile for batches (F25–F27). Figure 8 (a) 3D surface plot of response Y1 (drug release at 1 hr) (for X1  and  X2). (b) 3D surface plot of response Y1 (drug release at 1 hr) (for X1  and  X3). Figure 9 (a) 3D surface plot of response Y2 (drug release at 6 hr) (for X1  and  X2). (b) 3D surface plot of response Y2 (drug release at 6 hr) (for X1  and  X3). Figure 10 (a) 3D surface plot of response Y3 (drug release at 12 hr) (for X1  and  X2). (b) 3D surface plot of response Y3 (drug release at 12 hr) (for X1  and  X3). Figure 11 Overlay plot of Y1, Y2, and  Y3. Figure 12 Drug release data of dicloxacillin sodium and amoxicillin trihydrate. Figure 13 Drug release data for stability study of osmotic tablet (F22). Table 1 Formulation of osmotic tablet. Ingredient Weight (mg) Dicloxacillin sodium 244 Sodium chloride 100 MCC 60 Sodium lauryl sulfate 15 Sucrose 60 PVP K30 15 Magnesium stearate 3 Talc 3 Total weight of one tablet = 500 mg. Number of tablets per batch = 20. Table 2 Composition of coating solvent. Ingredient Composition Cellulose acetate 2% w/v PEG 400 2% v/v TiO2 0.2% w/v Coloring agent 0.2% w/v Acetone Up to 100 mL Table 3 Formulation of osmotic tablet (F1–F6). Ingredient Batch number F1 F2 F3 F4 F5 F6 Dicloxacillin sodium (mg) 244 244 244 244 244 244 NaCl (mg) 150 150 150 150 150 50 MCC (mg) 30 30 90 30 90 30 SLS (mg) 20 10 10 20 10 10 Sucrose (mg) 90 30 30 90 90 30 PVP K30 (mg) 15 15 15 15 15 15 EC (%) 4 4 2 2 4 2 CA (%) 2 2 4 4 4 2 PEG 400 (%) 2 2 2 2 2 2 Magnesium stearate (mg) 3 3 3 3 3 3 Talc (mg) 3 3 3 3 3 3 Coloring agent q.s q.s q.s q.s q.s q.s Table 4 Formulation of osmotic tablet (F7–F12). Ingredient Batch number F7 F8 F9 F10 F11 F12 Dicloxacillin sodium (mg) 244 244 244 244 244 244 NaCl (mg) 50 50 50 150 50 50 MCC (mg) 30 90 90 90 30 90 SLS (mg) 20 20 10 20 10 20 Sucrose (mg) 50 90 90 30 90 30 PVP K30 (mg) 15 15 15 15 15 15 EC (%) 4 2 4 2 2 4 CA (%) 4 2 2 2 4 2 PEG 400 (%) 2 2 2 2 2 2 Magnesium stearate (mg) 3 3 3 3 3 3 Talc (mg) 3 3 3 3 3 3 Coloring agent q.s q.s q.s q.s q.s q.s Table 5 Formulation of osmotic tablet (F13–F20). Ingredient Batch number F13 F14 F15 F16 F17 F18 F19 F20 Dicloxacillin sodium (mg) 244 244 244 244 244 244 244 244 NaCl (mg) 100 100 50 100 150 50 50 100 SLS (mg) 10 10 20 20 20 15 15 20 PVP K30 (mg) 15 15 15 15 15 15 15 15 CA (%) 4 2 3 4 3 4 2 2 PEG 400 (%) 2 2 2 2 2 2 2 2 Magnesium stearate (mg) 3 3 3 3 3 3 3 3 Talc (mg) 3 3 3 3 3 3 3 3 Coloring agent q.s q.s q.s q.s q.s q.s q.s q.s Table 6 Formulation of osmotic tablet (F21–F27). Ingredient Batch number F21 F22 F23 F24 F25 F26 F27 Dicloxacillin sodium (mg) 244 244 244 244 244 244 244 NaCl (mg) 100 150 150 50 150 100 100 SLS (mg) 20 15 10 10 15 15 15 PVP K30 (mg) 15 15 15 15 15 15 15 CA (%) 2 2 3 3 4 3 3 PEG 400 (%) 2 2 2 2 2 2 2 Magnesium stearate (mg) 3 3 3 3 3 3 3 Talc (mg) 3 3 3 3 3 3 3 Coloring agent q.s q.s q.s q.s q.s q.s q.s Table 7 Physiochemical parameters of factorial batches. Batch code Diameter (mm) Thickness (mm) Hardness (kg/cm2) % friability Uniformity of weight (mg) % drug content (% w/w) F1 10.0 ± 0.05 5.2 ± 0.5 6.3 ± 0.2 0.54 540 ± 2.7 103.2 ± 2.1 F2 10.1 ± 0.05 4.9 ± 0.5 6.8 ± 0.4 0.39 470 ± 4.8 99.3 ± 3.6 F3 10.1 ± 0.05 5.1 ± 0.2 6.5 ± 0.5 0.72 530 ± 2.9 98.2 ± 4.3 F4 10.1 ± 0.05 5.2 ± 0.5 6.3 ± 0.7 0.43 540 ± 3.1 97.3 ± 4.7 F5 10.0 ± 0.05 4.6 ± 0.4 6.8 ± 0.3 0.11 385 ± 3.4 100.3 ± 2.2 F6 10.0 ± 0.05 5.4 ± 0.3 6.9 ± 0.2 0.47 590 ± 1.8 99.5 ± 1.4 F7 10.1 ± 0.05 4.7 ± 0.5 6.8 ± 0.2 0.52 380 ± 4.4 101.4 ± 1.2 F8 10.0 ± 0.05 4.9 ± 0.5 6.8 ± 0.5 0.65 500 ± 2.5 96.3 ± 3.3 F9 10.0 ± 0.05 4.8 ± 0.4 6.5 ± 0.2 0.83 430 ± 3.7 98.4 ± 1.4 F10 10.0 ± 0.05 5.2 ± 0.2 6.8 ± 0.4 0.49 540 ± 1.2 99.2 ± 3.8 F11 10.1 ± 0.05 4.8 ± 0.5 6.8 ± 0.5 0.57 430 ± 5.1 97.7 ± 2.6 F12 10.0 ± 0.05 4.8 ± 0.5 6.5 ± 0.3 0.34 440 ± 2.9 97.2 ± 1.3 All values are mean of three readings. Table 8 Physiochemical parameters of factorial batches. Batch code Diameter Thickness Hardness % friability Weight variation % drug content F13 10.1 ± 0.05 4.6 ± 0.5 6.8 ± 0.3 0.54 375 ± 2.6 101.2 ± 2.3 F14 10.1 ± 0.05 4.6 ± 0.3 6.4 ± 0.3 0.39 375 ± 4.8 98.3 ± 3.6 F15 10.0 ± 0.05 4.2 ± 0.2 6.5 ± 0.3 0.72 335 ± 2.9 99.2 ± 4.1 F16 10.0 ± 0.05 4.7 ± 0.5 6.3 ± 0.5 0.43 384 ± 3.1 95.3 ± 4.4 F17 10.1 ± 0.05 5.1 ± 0.4 6.8 ± 0.2 0.11 435 ± 3.4 103.3 ± 2.5 F18 10.0 ± 0.05 4.2 ± 0.3 6.9 ± 0.3 0.47 330 ± 1.8 97.5 ± 1.7 F19 10.0 ± 0.05 4.3 ± 0.5 6.8 ± 0.5 0.52 330 ± 4.4 101.4 ± 1.2 F20 10.1 ± 0.05 4.7 ± 0.5 6.8 ± 0.4 0.65 380 ± 2.5 98.3 ± 3.5 F21 10.1 ± 0.05 4.8 ± 0.4 6.5 ± 0.2 0.83 385 ± 3.7 99.4 ± 1.4 F22 10.0 ± 0.05 5.0 ± 0.2 6.8 ± 0.2 0.49 430 ± 1.2 97.2 ± 3.8 F23 10.1 ± 0.05 4.9 ± 0.5 6.9 ± 0.3 0.57 426 ± 5.1 98.7 ± 2.6 F24 10.0 ± 0.05 5.2 ± 0.5 6.5 ± 0.2 0.34 440 ± 2.9 98.2 ± 1.3 F25 10.1 ± 0.05 4.2 ± 0.4 6.6 ± 0.5 0.43 325 ± 1.3 99.4 ± 5.4 F26 10.1 ± 0.05 4.7 ± 0.1 6.9 ± 0.2 0.61 380 ± 3.4 98.5 ± 1.7 F27 10.0 ± 0.05 4.7 ± 0.5 6.8 ± 0.1 0.53 380 ± 2.7 99.9 ± 2.3 All values are mean of three readings. Table 9 Desirable values selected for dependent variables. Dependent variables Desirable values Lower limit Upper limit Y1 (% drug release at 1 hr) 20 30 Y2 (% drug release at 6 hr) 50 60 Y3 (% drug release at 12 hr) 90 100 Table 10 Comparison of drug release profiles of dicloxacillin sodium and amoxicillin trihydrate. Time (hr) Dicloxacillin sodium Amoxicillin trihydrate 0 0 0 1 28.56 30.07 2 34.38 35.98 3 38.72 38.72 4 45.72 43.72 5 57.23 57.23 6 61.81 60.37 7 67.04 69.84 8 74.53 72.53 9 79.45 77.75 10 84.02 82.09 11 89.39 90.39 12 95.72 93.88 Table 11 Kinetic modeling of drug release. Parameter Kinetic model Zero-order First-order Higuchi Hixson-Crowell Korsmeyer-Peppas Weibull Sum of residuals 1314.416 346.8983 205.599 336.2533 75.4920 258.9369 Correlation coefficient (r) 0.9781 0.9821 0.9905 0.9877 0.9960 0.9860 R square (r 2) 0.8595 0.9629 0.9780 0.9635 0.9918 0.9719 F 109.534 28.9081 17.1332 28.0211 6.8629 25.8936 Model fitting results revealed that the Korsmeyer-Peppas model was best fitted to the release kinetics (r 2 = 0.9960, highest, F = 6.8629, lowest). Higuchi model was also close to the Korsmeyer-Peppas model. Hence F test was performed for both models. It revealed significant difference between two models. Hence Korsmeyer-Peppas model was finally selected as best fitted model. Release exponent n was found to be 0.580, indicating that the drug was released from the formulation by anomalous (non-Fickian) mechanism. Table 12 Results of stability study of optimized batch (F22). Evaluation parameters Initially After 30 days Weight variation (n = 10) 430 ± 1.2 429 ± 3.3 Diameter (mm) 10.0 ± 0.05 10.0 ± 0.05 Thickness (mm) 5.0 ± 0.2 5.0 ± 0.1 Hardness (kg/cm2) 6.8 ± 0.2 6.7 ± 0.5 Friability (%) 0.49 0.52 % drug content 97.2 ± 3.8 97.0 ± 1.3 Y1 (% drug release at 1 hr) 28.56% 30.07% Y2 (% drug release at 6 hr) 61.81% 60.37% Y3 (% drug release at 12 hr) 95.72% 93.88% ==== Refs 1 Srikanth P. Raju N. Wasim Raja S. Brito Raj S. A review on oral controlled drug delivery International Journal of Advance Pharmaceuticals 2013 3 1 51 58 2 Stevenson C. L. Theeuwes F. Wright J. C. Handbook of Pharmaceutical Controlled Release Technology 2007 New York, NY, USA Marcel Dekker Edited by D. L. Wise 3 Gupta S. Singh R. P. Sharma R. Kalyanwat R. Lokwani P. Osmotic pumps: a review International Journal of Comprehensive Pharmacy 2011 2 6 2 8 4 Gupta B. P. Thakur N. Jain N. P. Banweer J. Jain S. Osmotically controlled drug delivery system with associated drugs Journal of Pharmacy & Pharmaceutical Sciences 2010 13 4 571 588 10.18433/j38w25 2-s2.0-78650315524 21486532 5 Edavalath S. Shivanand K. Prakasam K. Rao B. P. Divakar G. Formulation development and optimization of controlled porosity osmotic pump tablets of diclofenac sodium International Journal of Pharmacy and Pharmaceutical Sciences 2011 3 1 80 87 2-s2.0-79251551644 6 Sanford Bolton C. B. Pharmaceutical Statistics Pratical and Clinical Application 2004 135 4th 7 Jain S. P. Singh P. P. Javeer S. Amin P. D. Use of Placket-Burman statistical design to study effect of formulation variables on the release of drug from hot melt sustained release extrudates AAPS PharmSciTech 2010 11 2 936 944 10.1208/s12249-010-9444-6 2-s2.0-77954817591 20509057 8 Ferreira S. L. C. Bruns R. E. Ferreira H. S. Box-Behnken design: an alternative for the optimization of analytical methods Analytica Chimica Acta 2007 597 2 179 186 10.1016/j.aca.2007.07.011 2-s2.0-34547512906 17683728 9 Aslan N. Cebeci Y. Application of Box-Behnken design and response surface methodology for modeling of some Turkish coals Fuel 2007 86 1-2 90 97 10.1016/j.fuel.2006.06.010 2-s2.0-33846242657

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==== Front eNeuroeNeuroeneuroeneuroeNeuroeNeuro2373-2822Society for Neuroscience 10.1523/ENEURO.0015-16.2016eN-NWR-0015-168New ResearchSensory and Motor SystemsAnalysis of Family Structures Reveals Robustness or Sensitivity of Bursting Activity to Parameter Variations in a Half-Center Oscillator (HCO) Model Parameter Variations Influence Bursting Activityhttp://orcid.org/0000-0001-9960-5752Doloc-Mihu Anca http://orcid.org/0000-0001-7135-3469Calabrese Ronald L. Department of Biology, Emory University, Atlanta, Georgia 30322The authors declare no competing financial interests. Author contributions: A.D.-M. and R.L.C. designed research; A.D.-M. performed research; A.D.-M. contributed unpublished reagents/analytic tools; A.D.-M. and R.L.C. analyzed data; A.D.-M. and R.L.C. wrote the paper. This research was supported by National Institutes of Health Grant R01-NS-085006 (to R.L.C.). Correspondence should be addressed to Anca Doloc-Mihu, Department of Biology, Emory University, Atlanta, GA 30322. E-mail: adolocm@emory.edu.04 8 2016 30 8 2016 Jul-Aug 2016 3 4 ENEURO.0015-16.201621 1 2016 24 7 2016 28 7 2016 Copyright © 2016 Doloc-Mihu and Calabrese2016Doloc-Mihu and CalabreseThis is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.Visual Abstract The underlying mechanisms that support robustness in neuronal networks are as yet unknown. However, recent studies provide evidence that neuronal networks are robust to natural variations, modulation, and environmental perturbations of parameters, such as maximal conductances of intrinsic membrane and synaptic currents. Here we sought a method for assessing robustness, which might easily be applied to large brute-force databases of model instances. Starting with groups of instances with appropriate activity (e.g., tonic spiking), our method classifies instances into much smaller subgroups, called families, in which all members vary only by the one parameter that defines the family. By analyzing the structures of families, we developed measures of robustness for activity type. Then, we applied these measures to our previously developed model database, HCO-db, of a two-neuron half-center oscillator (HCO), a neuronal microcircuit from the leech heartbeat central pattern generator where the appropriate activity type is alternating bursting. In HCO-db, the maximal conductances of five intrinsic and two synaptic currents were varied over eight values (leak reversal potential also varied, five values). We focused on how variations of particular conductance parameters maintain normal alternating bursting activity while still allowing for functional modulation of period and spike frequency. We explored the trade-off between robustness of activity type and desirable change in activity characteristics when intrinsic conductances are altered and identified the hyperpolarization-activated (h) current as an ideal target for modulation. We also identified ensembles of model instances that closely approximate physiological activity and can be used in future modeling studies. analysiscomputationdatabasehalf-center oscillatorinvertebratesrobustnessNIHR01 NS085006 cover-dateJuly/August 2016 ==== Body Significance Statement Robustness is an attribute of living systems and mathematical models that describe them. We developed a method for assessing the robustness of activity types (e.g., bursting), which can be applied to brute-force databases of neuronal model instances in which biologically relevant parameters are varied, and where sensitivity analyses are conceptually and practically difficult to apply. By organizing all instances with appropriate activity into families, in which all members vary only by the one parameter defining the family, we developed measures of robustness for activity type based on family structure and address a fundamental challenge to robustness, modulation, which, by changing parameters, may alter activity type. The method determines which parameters predictably alter activity characteristics, (e.g., burst period), without changing activity type. Introduction Robustness is a fundamental feature of complex systems (Kitano, 2004) like neuronal networks, yet remains only operationally defined, and the underlying mechanisms that support it are largely unknown (Gutierrez et al., 2013; Marder et al., 2015). If robustness for a neuronal network is defined as the maintenance of a desirable activity state in the face of parameter variation (e.g., maximal conductance of intrinsic membrane and synaptic currents), then abundant experimental evidence (Swensen and Bean, 2005; Schultheiss et al., 2012; Talebi and Baker, 2012; Tang et al., 2012; Langen et al., 2013; Caplan et al., 2014; Dethier et al., 2015;) suggests that neuronal networks are robust to animal-to-animal variations, modulation, and environmental perturbations of these parameters. Modulation poses a particular challenge to network robustness, because it often must modify network activity without changing activity type (e.g., changing the period of a rhythmically active network without disrupting its rhythmicity or phase). Some modeling studies have addressed the mechanisms underlying such functional robustness (Goldman et al., 2001, 2003; O’Leary et al., 2014). Also, sensitivity analysis is commonly used to assess the influence of a parameter on activity characteristics and type in neuronal models (Olypher and Calabrese, 2007), but is difficult to apply to multidimensional parameter spaces that neurons occupy, though there has been some notable progress (Marder et al., 2014; Drion et al., 2015). The purpose of this study was twofold, with a focus on assessing robustness. First, we developed a strategy for assessing the robustness of model neurons applicable to large databases of model instances based on a grid structure (brute-force). We classified instances in the database into small groups called families in which members vary only by the value of the parameter that defines the family, and we used the family structures to develop new measures for assessing the robustness (or sensitivity) of electrical activity to changes in model parameters. Second, we applied our measures to an existing model of a two-neuron half-center oscillator (HCO). Central pattern generators (CPGs; Marder, 2011; Calabrese, 2014) pace adaptable rhythmic behaviors, such as walking and breathing. Their inherent rhythmicity and adaptability to perturbations results from the interaction of their intrinsic and synaptic properties with neuromodulatory and sensory inputs. CPGs exhibit remarkably robust activity types (e.g., rhythmic alternating bursting), yet extensive modulation of activity characteristics (e.g., burst period) occurs. Thus, they represent an excellent test bed for exploring the interplay of robustness and modifiability. Reciprocally inhibitory neurons (often autonomous bursters) called HCOs are prevalent circuit building blocks of CPGs that assure robust alternating bursting (Selverston et al., 2000; Cymbalyuk et al., 2002). HCO models display a wide range of bursting activity when intrinsic and synaptic conductances of the neurons are varied (Prinz et al., 2004). We used the HCO model of Hill et al., 2001', which reproduces the electrical activity observed in the leech heartbeat CPG and consists of a pair of reciprocally inhibitory model neurons represented as single isopotential compartments with intrinsic and synaptic conductances of the type defined by Hodgkin and Huxley (1952). Each model neuron contains eight voltage-dependent currents, five inward currents (INa, a fast Na+ current; IP, a persistent Na+ current; ICaF, rapidly inactivating low-threshold Ca current; ICaS, slowly inactivating low-threshold Ca current; and Ih, a hyperpolarization-activated cation current), three outward currents (IK1, a delayed rectifier-like K current; IK2, a persistent K current; and IKA, a fast transient K current), and two types of inhibitory synaptic transmission: graded (ISynG) and spike mediated (ISynS). To explore the HCO parameter space [maximal conductances (ḡ values) of intrinsic and synaptic currents], we simulated ∼10.5 million model instances, whose characteristics we recorded into a database named HCO-db (Doloc-Mihu and Calabrese, 2011). Here, we systematically explored the parameter space of two identified groups from the database: realistic HCOs or (rHCOs), which show normal physiological activity with 99,066 instances; and functional HCOs (fHCOs), which show nonphysiological but functional alternating bursting activity with 1.1 million instances. We subdivided instances from both groups into families of instances that vary by only one parameter that defines the family. By examining family structures and patterns, we developed new measures of robustness of bursting activity to alterations of model parameters. Using this analysis, we showed that the HCO model is robust to variations of Ih but is highly sensitive to the IP. Moreover, the burst period is reliably and predictably regulated by modulating ḡh, suggesting that it is ideal for neuromodulation. This new analysis also allowed us to identify ensembles of instances that show typical robust physiological activity for future analysis of parameter variations. Materials and Methods Half-center oscillator (HCO) model We used a half-center oscillator model (Hill et al., 2001) that produces rhythmic alternating bursting activity resembling the electrical activity in the heartbeat CPG of the leech. This model is publicly available on ModelDB repository (https://senselab.med.yale.edu/ModelDB; accession #19698). The model consists of a two reciprocally inhibitory model interneurons, represented as single isopotential electrical compartments with intrinsic and synaptic membrane conductances of the Hodgkin and Huxley (1952) type. Each model neuron contains, in addition to a leakage current, eight voltage-dependent currents, five inward currents (INa, IP, ICaF, ICaS, and Ih), and three outward currents (IK1, IK2, and IKA). In what follows, this half-center oscillator model is simply referred to as the model or the model neurons, and the currents are referred to by their letters. The model has two types of inhibitory synaptic transmission between the two interneurons: SynG and SynS. The graded transmission SynG was modeled as a postsynaptic conductance controlled by presynaptic Ca2+ concentration and the spike-mediated transmission SynS was modeled as a postsynaptic conductance triggered by presynaptic spikes. The values for the maximal conductances and the leak reversal potential are the free parameters in the model. For our canonical model, these values are ḡCaS = 3.2 nS, ḡh = 4 nS, ḡP = 7 nS, ḡK2 = 80 nS, ḡLeak = 8 nS, ḡSynS = 60 nS, ḡSynG = 30 nS, ḡNa = 200 nS, ḡCaF = 5 nS, ḡK1 = 100 nS, ḡKA = 80 nS, and Eleak = −60 mV (Doloc-Mihu and Calabrese, 2011). The kinetics, voltage dependencies, reversal potentials of the intrinsic currents, and the synaptic connections of the HCO model interneurons have all been verified and previously adjusted to fit the biological data of leech interneurons (Hill et al., 2001). The differential equations of the model are given in the study by Doloc-Mihu and Calabrese, 2014. In previous work, Doloc-Mihu and Calabrese, 2011 performed extensive simulations of this model by systematically varying eight key parameters (a brute-force approach). All model simulations were started from the same initial conditions, which were different for each of the two neurons and were obtained by running the canonical HCO model (Hill et al., 2001) for 200 s, such that one of the two neurons was in its bursting state and the other one was being inhibited. The same parameter values were used in each of the paired model neurons. The eight parameters varied were as follows: seven maximal conductances (ḡSynS, ḡSynG, ḡLeak, ḡP, ḡCaS, ḡh, and ḡK2), across 0%, 25%, 50%, 75%, 100%, 125%, 150%, and 175% of their canonical values, and Eleak across −70, −65, −60, −55, and −50 mV. After changing a parameter, we ran each model instance for 100 s to allow the system to establish stable activity, and then we ran it for another 100 s, from which we recorded the voltage traces of the electrical activity corresponding to its paired neurons and the corresponding spike times. The firing characteristics were analyzed and recorded in a database. By systematically varying the eight key parameters (a brute-force approach) in all possible combinations, we developed a database of 10,485,760 simulated model instances named “HCO-db” (available upon request; see description in Doloc-Mihu and Calabrese, 2011). The resulting parameter space includes 10,321,920 instances, which have at least one synaptic component present and thus are potential working HCOs, and 163,840 isolated neuron instances, which contain twin neurons without any synaptic interaction. Definitions In voltage traces, we recognized a spike only if the potential waveform crossed a threshold of −20 mV. We defined a burst as having at least three spikes and a minimum interburst interval of 1 s. We defined the burst period as being the interval between the middle spikes of two consecutive bursts. Phase was calculated on a per burst basis, as being the delay from the middle spike of a burst of neuron B to the middle spike of the preceding burst of neuron A divided by the interval from this middle spike of the next burst of neuron A to the middle spike of the preceding burst of neuron A. The duty cycle was defined as the percentage of the period occupied by a burst. Each burst spike frequency is defined as the number of spikes within the burst divided by the burst duration. The spike frequency of a neuron is defined as the mean of all burst spike frequencies divided by the mean of all burst durations. We defined a half-center oscillator instance (here referred to simply as HCO) as having two model interneurons each showing bursting activity with at least two bursts in a 40 s time interval, with each burst having normal spikes (coefficient of variation of the amplitudes of the spikes within any burst, <0.07); a small variation of period (coefficient of variation of period, < 0.05); relative phase in the range of 0.45–0.55; and at least one synaptic component present (either ḡSynS ≠ 0, or ḡSynG ≠ 0, or both ḡSynS ≠ 0 and ḡSynG ≠ 0). We considered an rHCO instance as being an HCO that showed physiological bursting corresponding to that observed in leech oscillator heart interneurons. Precisely, it was an HCO with period between 5 and 15 s, average spike frequency between 8 and 25 Hz, and duty cycle between 50% and 70%. All HCO instances that did not meet the criteria to be designated as realistic (i.e., rHCOs) were designated as fHCOs because they still maintained functional alternating bursting. Note that rHCOs and fHCOs are nonoverlapping subsets of HCOs. We defined an isolated neuron instance (isolated neuron) as having two identical interneurons (though started with different initial conditions, but otherwise identical), and no synaptic interaction (i.e., ḡSynS = 0 and ḡSynG = 0). We defined a burster instance as being an isolated neuron instance for which both neurons had at least two bursts, each with normal spikes, and regular periods (as defined above for the HCOs). We defined a realistic burster as being a burster that showed realistic bursting corresponding to isolated leech oscillator heart interneurons. Precisely, it was a burster with a period between 5 and 15 s, and an average spike frequency between 8 and 25 Hz. Note that realistic bursters can be thought of as being HCOs with no synaptic connections. We define a family as being a subset (of a group) of instances that all have the same parameter values except the one that defines the family (e.g., all realistic bursters that vary only by ḡP constitute a family of P). We define a family sequence as the order of values (e.g., increasing) of its defining parameter. Note that each family member has a unique ḡ value of the defining parameter, and all the ḡ values within the same family form the family sequence. A family sequence is delimited by a beginning and an ending parameter value (permissible range), not by the grid limits of the database. If the family sequence includes all grid points in the database within the permissible range, this family is called “noninterrupted”; if not all grid points within the permissible range are members of the family sequence, then the family is called “interrupted.” In the latter case, we say that the family sequence has broken down. By using our definitions from above as criteria, we identified from our HCO-db database those four groups that include simulated instances showing appropriate burst characteristics (period, spike frequency, duty cycle): 99,066 rHCOs (realistic); 1,103,073 fHCOs (functional not realistic); 307 realistic bursters; and 117 bursters that are not realistic. By querying our HCO-db database, we analyzed (with our own Java and Matlab scripts) the sensitivity of the leech burst characteristics to changes in maximal conductances for the realistic groups of instances. Sensitivity classification For each family, plotting the burst characteristics (period, spike frequency) versus the ḡ value of each family member and then connecting the points obtained corresponding to the adjacent family members via lines forms a curve. We built and used our own Matlab scripts to automatically separate the families according to their curve steepness calculated as the maximum slope. As a family curve is not smooth but is made of several connected line segments, it was important first to assess its monotonicity. Then, the algorithm can be applied easily. The algorithm used the polyfit and polyval functions in Matlab (code inspired from Matlab Central, Jean-Luc Dellis “getthetangent”: http://www.mathworks.com/matlabcentral/fileexchange/23799-getthetangent/content/getthetangent.m) to fit a smooth curve (polynomial of degree 5 was enough for most h families) to our family curves. The slope of a curve at a certain point is the slope of the tangent at that point. So, the algorithm finds the tangent to the curve with the maximum slope (calculated by using the derivative of the curve). The tangent to a family curve gave the slope or the angle of the decay (with respect to the x-axis). Our algorithm first found the families that decline steeply and classified them as the high-sensitivity group; then it found the families that had a gradual decline and classified them as the low-sensitivity group; and finally the rest of the families were classified as the medium-sensitivity group. We set up a threshold of −2.5 for the high-sensitivity group (angle range, ∼68–90° clockwise), and a maximum of −0.4 for the low-sensitivity group (angle range, ∼0–22° clockwise). Results We started our study by first searching for mechanisms involving correlated conductance parameters (ḡ values) that influence the robustness of activity type, here realistic HCO bursting activity, since parameter correlation is one mechanism that produces and maintains robustness. Recent work (Doloc-Mihu and Calabrese, 2014) investigated the potential relationships between parameters that maintain bursting activity in isolated neurons from the HCO model (bursters, see Definitions, in Materials and Methods). The authors found a linearly correlated set of three maximal conductances (of leak current, ḡLeak; of a persistent K current, ḡK2; and of a persistent Na+ current, ḡP) that maintains bursting activity in burster (including realistic burster) model instances, therefore underlying the robustness of bursting activity. In addition, they found that bursting activity was very sensitive to individual variation of these parameters; only correlated changes could maintain the activity type. Now we ask whether or not there is a similar linear correlation between maximal conductances of the ḡLeak of the ḡK2 and of the ḡP that maintains realistic HCO bursting activity. Nonlinear correlation between ḡP, ḡLeak, ḡK2, and Eleak for realistic HCOs To address this question, we developed a Matlab script to visualize the following five characteristics of a dataset at once: three parameters, which form a 3D parameter space of the data (here, rHCOs), the number of instances projected onto each point in this space given by the size of each point, and pie charts of a fourth parameter showing all instances projected onto each point in the 3D space. Here, the three parameters forming the 3D space were ḡP, ḡK2, and ḡLeak, and the fourth parameter was Eleak. The plot obtained is shown in Figure 1. We selected these parameters inspired by the research in the study by Doloc-Mihu and Calabrese, 2014. The pie chart was split into five slices according to the number of values possible for Eleak, with each slice having a different color. If there was no instance projected into the 3D space for a particular value of the fourth parameter, then its corresponding slice was not shown in the pie chart. For a better visualization of the points projected onto the 3D plot (Fig. 1), we used the natural logarithm to size the pies (as radius). For example, the largest point from the plot included 2,440 projected realistic HCO instances, with 488 per each Eleak slice, and its pie size was ln(2440) = 7.7998. Figure 1. 3D view of the 99,066 realistic HCO instances. Plot of all rHCO instances projected onto the 3D space given by the maximal conductances of IP, IK2, and ILeak. Each point displays a pie chart of the Eleak of all instances from the group having the same values of ¯gP, ¯gK2, and ¯gLeak as the respective projected point. The number of instances projected onto each point in the 3D space is shown by the size of the Eleak pie (as radius). For a better visualization of the points, we applied the natural logarithm to the sizes of the pies. The plot in Figure 1 shows that there is no linear correlation among ḡP, ḡK2, and ḡLeak that is similar to the one observed for bursters in the study by Doloc-Mihu and Calabrese, 2014, which showed a clustering of the points along the main diagonal. The 3D shape from Figure 1 has a complicated contour, similar to a wedge, and reveals potential nonlinear correlation among these three maximal conductances. A similar wedge-like shape correlation was observed by Goldman et al. (2001, their Fig. 2) among maximal conductances of A, Ca, Na, and KCa currents in a theoretical study on lobster superior temporal gyrus neurons. Figure 2. The number of instances within the rHCO group and fHCO group vs their period values for each value of ¯gh. fHCOs are in blue and rHCOs are in red. Period values were between 1 and 40 s for the fHCOs and between 5 and 15 s for the rHCOs. Plots were obtained using the bar Matlab function (R2014a). Each bar shows the period values within one unit or between [n, n + 1). The bars corresponding to the realistic instances were shifted with 0.3 on the x-axis for better visualization. ¯gh values are given as the percentage of the canonical (100%). Expansions of all the Eleak pie charts revealed that the main diagonal is a border between Eleak values: above the main diagonal were predominantly more positive values of Eleak (−50 and −55 mV); along the diagonal were all Eleak values; and below the diagonal were mostly more negative values (−70 and −65 mV). The number of instances seemed to be biased toward the main diagonal as the biggest pies can be seen along it. That is, realistic HCO activity is influenced (produced) by almost equal (including ±25% and ±50% variations) values of ḡP, ḡK2, and ḡLeak (range, 0–175%), along with middle values of Eleak (−55, −60, and −65 mV). However, while a linear correlation among ḡP, ḡK2, and ḡLeak was not observed for the realistic HCO instances, these three parameters (along with Eleak) defined a limited parameter space in which realistic activity was observed. Now we wanted to ask how other parameters (working individually) influence the alternating bursting activity in the HCOs, given the constraints imposed by Eleak, ḡLeak, ḡK2, and ḡP. Increasing ḡh promotes bursting Here, we answer this question by first looking at how varying the value of ḡh affects bursting activity in HCOs and realistic HCOs. From now on, we separate the HCOs into two nonoverlapping groups, the rHCOs and fHCOs, which include all HCOs that are not realistic HCOs. Many fHCOs (461,724 instances) had only the duty cycle outside the physiological range [0.5–0.7] for the three criteria used to determine realistic status. Also, there were many (155,556 instances) fHCOs that had only spike frequencies that were too high (>25 Hz) or too low (<8 Hz). There were relatively fewer fHCOs (23,523 instances) that had burst periods that were too low (<5 s) or too high (>15 s). A good number of fHCOs (84,586 instances) did not satisfy any of the physiological criteria. Also, there were fHCOs that did not meet two of these three realistic requirements, in every combination: 30,751 fHCOs failed period and spike frequency; 87,025 fHCOs failed period and duty cycle; and 259,908 fHCOs failed spike frequency and duty cycle. Figure 2 illustrates the number of instances within each of the rHCO and fHCO groups versus with their period values for each value of ḡh. Figure 2 reveals right-skewed distributions of the fHCO and rHCO instances for each h value. For fHCOs, increasing the value of ḡh has the following two effects: it monotonically increases the number of instances within the group (from 94,639 instances for ḡh = 0 to 181,083 for ḡh = 175%), and it increases the number of instances with faster bursting activity (periods between 5 and 10 s). For the latter, we used the skewness Matlab function to show that the fHCOs distributions have positive monotonically increasing skewness values (from 0.95 for ḡh = 0 to 1.93 for ḡh = 175%) as the value of ḡh increases. For rHCOs, Figure 2 shows a peak in the number of these instances for ḡh = 75%. Similar to the distributions of the fHCOs, the distributions of the rHCOs show positive monotonically increasing skewness values (from 1.38 for ḡh = 0 to 2.9 for ḡh = 175%) as the value of ḡh increases. We conclude that a larger ḡh value promotes functional and realistic HCO bursting. The amount of h current thus appears to be important in regulating alternating bursting in mutually inhibitory heart interneurons. Moreover, increasing ḡh values increases the number of instances with shorter burst periods (between 5 and 10 s). Next, we investigated in more detail the effect of each parameter on the realistic bursting activity. Robustness as defined by the family size For each parameter, we queried the HCO-db database to build up the families (of instances) existing for that particular parameter within the rHCO group (we also build up the families within fHCOs; data not shown). Then, we partitioned the rHCOs into families according to the number of members in the family (see Definitions). Table 1 summarizes, for each parameter, the number of families of each size (number of members) within the rHCOs. From Table 1, we can see that P has many families (on the order of thousands) with a small number of members (one and two members) and no large families (with three to eight members). K2 shows a family structure similar to that of P, with thousands of families with a small number of members (one to three members), but also has a small number of families with four and five members. Leak, CaS, and SynS share a similar family structure, with thousands of families with a small number of members (one to three members), and a good number of families with four to six members. Finally, h and SynG show a different family structure, including a large number of families with seven and eight members, and thousands of the rest. Table 1: The number of families for each parameter within the realistic HCO group One member Two members Three members Four members Five members Six members Seven members Eight members P 92,970 3,048 (3,048) K2 68,702 13,163 (11,836) 1,299 (1,223) 34 (34) 1 (1) Leak 66,611 11,873 (10,305) 2,133 (1,569) 452 (301) 92 (54) 7 (6) CaS 43,500 17,851 (13,471) 5,263 (3,854) 929 (765) 67 (63) 4 (4) SynS 38,588 16,950 (11,131) 6,390 (3,341) 1,542 (832) 236 (121) 10 (7) h 16,877 9,895 (5,545) 6,325 (2,525) 4,322 (1,411) 2,703 (930) 1,285 (415) 537 (240) 144 (144) SynG 10,551 7,047 (2,830) 5,086 (1,276) 4,124 (865) 3,046 (535) 1,971 (483) 1,061 (448) 1,023 (1,023) Families with the same number of members are grouped together. In parentheses, we show the number of noninterrupted families. Family sequence In this work, we used the ḡ values within the same family in increasing order of their values to form the family sequence (see Definitions). By analyzing the family sequences, we revealed that many families have internal gaps or breaks. A family sequence is delimited by a beginning and an end parameter value (permissible range), not by the grid limits of the database. A family is noninterrupted if its sequence includes all grid points in the database between these limits; otherwise, the family is called interrupted (i.e., if there is at least one missing grid point from the family sequence between these limits). In Table 1, we present in parentheses the number of noninterrupted families. The percentage of noninterrupted families within the total number of families of a given number of members varied for different parameters. For ḡK2, it showed a steady increase with increasing number of family members from 89.9% to 100%. For ḡP, we had all families as noninterrupted families (100%). For the rest of the parameters, the percentage of noninterrupted families fluctuated (i.e., changed nonmonotonically), as follows: between 58.7% and 86.7% for ḡLeak (corresponding to families with five and two members, respectively); between 73.2% and 100% for ḡCaS (for families with three and six members, respectively); between 51.2% and 70% for ḡSynS (for families with five and six members, respectively); between 32.3% and 100% for ḡh (for families with six and eight members, respectively); and between 17.5% and 100% for ḡSynG (for families with five and eight members, respectively). Interestingly, both ḡh and ḡSynG showed a similar tendency: both had a large number of families with any given number of members, and, with the exception of their families with eight members, both displayed very low numbers of noninterrupted families (<56% for ḡh and <42.2% for ḡSynG). Here, we used a large number of families with many members (best if all eight members are present) as a measure of the robustness of realistic bursting activity over the defining parameter changing within these families. Moreover, noninterrupted families indicated strong robustness to the variation of the defining family parameter. Using this criterion, from above we can conclude that realistic HCO activity is robust to changes in h and SynG, and that it is sensitive to changes in P and maybe K2. Next, we looked at the family beginning and end values of the defining ḡ, for each ḡ value, along with their potential sequence interruptions to assess potential robustness or sensitivity. Robustness as defined by family sequence breakdown For each parameter, we plotted the distributions of its families that were interrupted. The presence of interruptions in a family sequence indicates that realistic HCO activity is not robust over the entire permissible range of the family’s defining parameter, with all other parameters remaining constant. Conversely, noninterrupted (or continuous) families indicate robustness to the variation of the defining family parameter. Sequence breakdown versus changes in ḡh Figure 3 illustrates the distributions of interrupted and noninterrupted h families for the rHCOs. There were a total of 25,057 families with two to seven members, of which 11,066 were noninterrupted and 13,991 were interrupted. As the permissible range of the family sequence increased—move along any given row (beginning point) toward the right-most column (largest end point)—the number of interrupted families increases, while the number of noninterrupted families tends to decrease then increase for the largest sequence end point (ḡh = 175%). For large permissible ranges, there are a large number of families with multiple interruptions in their sequences. Conversely, the smaller the permissible range, the larger the proportion of noninterrupted families. This analysis also points out that with a large permissible range (>4) of ḡh, regardless of the beginning or end point permissible, there are a considerable number of families with a sizeable number of members (more than four), albeit some with interruptions, and there are many families that have such permissible ranges (4,669). What is somewhat surprising about these results is that there are so many interruptions in family sequences, and for large permissible ranges there can be several interruptions. It is thus important to explore whether these interruptions lead to a change in activity type or reflect a more subtle change like a movement beyond the physiological range criteria (e.g., spike frequency) for an rHCO, while maintaining fHCO activity. Figure 3. Distribution of h families of rHCOs based on the sequence breakdown of their members. Labels at the margins indicate the beginning (vertical dimension) and end (horizontal dimension)¯gh values of the family sequences. Colors indicate the number of members within the family. The titles of panels show the total number of families [total number of interrupted families plus the number of noninterrupted families (star)]. Numbers under each panel title give the total number of interrupted families (left) and the number of noninterrupted families (right). For each panel, the y-axis indicates the number of families. Bins corresponding to the families having all members with noninterrupted̄gh values are marked with an orange star. All panels show data at the same scale. Sequence breakdown versus changes in ḡCaS Figure 4 illustrates the distributions of interrupted and noninterrupted CaS families for the rHCOs. There were a total of 24,110 CaS families with two to six members, of which 18,157 were noninterrupted and 5,953 were interrupted. No family is thus able to span the entire range of ḡCaS values tested. Figure 4 shows that the number of interrupted families generally decreases as the permissible range increases (look across rows), which is in stark contrast to h families (Fig. 3), except for sequences that start at ḡCaS = 0, where there is a peak for sequences that end at ḡCaS = 75%. Similarly, the number of noninterrupted families decreases as the permissible range increases (look across rows). This analysis points out that there are no families with seven or eight members and few with six members (4 families) with a modest number of families with five members (67 families), most of which are noninterrupted (63 families). Still, as with h families, there can be several interruptions in family sequences except for families with permissible ranges of approximately four. As with h families, it is important to explore whether these interruptions lead to a change in activity type or reflect a more subtle change like a movement beyond the physiological range criteria (e.g., spike frequency) for an rHCO, while maintaining fHCO activity. Figure 4. Distribution of CaS families of realistic HCOs based on the sequence breakdown of their members. Labels at the margins indicate the beginning (vertical dimension) and end (horizontal dimension)¯gCaS values of the family sequences. Colors indicate the number of members within the family. The titles of panels show the total number of families [total number of interrupted families plus the number of noninterrupted families (star)]. The numbers under each panel title give the total number of interrupted families (left) and the number of noninterrupted families (right). For each panel, the y-axis indicates the number of families. Bins corresponding to the families having all members with noninterrupted̄gCaS values are marked with an orange star. Empty panels have been removed. To visualize bins with few families, panels are at different scales. Sequence breakdown versus changes in ḡP For rHCOs, we obtained only families with two members for P, and all these families are noninterrupted (Table 1). There were no families of P that started at 0. The peak in the number of P families was obtained for families starting at 50% and ending at 75% (1,614 families), followed by families starting at 75% and ending at 100% (861 families). Sequence breakdown versus changes in ḡK2 For rHCOs, there were a total of 14,497 K2 families with two to five members, of which 13,144 families were noninterrupted. The number of K2 families, both noninterrupted and interrupted, increased monotonically as the end point of the sequence increased, with the largest number (4,600 and 741, respectively) of these families for ḡK2 = 175%. There was an increase in the number of families as the ḡK2 end point increased, which suggests that more ḡK2 promotes realistic HCO bursting. Sequence breakdown versus changes in ḡLeak For rHCOs, there were a total of 14,557 leak families with two to six members, of which 12,273 were noninterrupted. The maximum number of noninterrupted families of any size (number of members) was when the sequence started with no leak present (ḡLeak = 0), and as the amount of ḡLeak increased the number of noninterrupted families decreased monotonically. Lower ḡLeak values (0–100%) seemed to promote more noninterrupted families and, thus, resulted in more robust realistic HCO activity. Sequence breakdown versus changes in ḡSynS There were a total of 25,128 SynS families with two to six members, of which 15,432 were noninterrupted. For each number of members, the number of noninterrupted families increased monotonically and steeply as the sequence beginning point increased and also as the sequence end point increased (peak at 175%). These observations suggest that stronger spike-mediated synaptic transmission promoted robust realistic HCO activity. Sequence breakdown versus changes in ḡSynG There were a total of 22,335 SynG families with two to seven members, of which 6,437 were noninterrupted. Like h, SynG had many families (1,023 families) with all eight possible members (noninterrupted sequence). As the sequence beginning point increased (peak at 0), both the number of noninterrupted families and interrupted families decreased monotonically and steeply (from 1,904 and 8,267 for ḡSynG = 0 respectively, to 384 and 218, respectively, for ḡSynG = 150% and ḡSynG = 125%). So, it appears that more ḡSynG did not promote robustness. Robustness as shown by missing family members In the following, we analyze the missing members from all rHCO families (noninterrupted and interrupted); the missing members outside the family’s permissible range (beginning and end points); and the missing members in the family sequence to determine the proportion of missing members that maintain functional HCO activity (regular alternating bursting but not realistic). We use this as a measure of the robustness of alternating bursting activity state. Bursting activity shows robustness to changes in ḡh The plots in Figure 5 illustrate the distributions of the missing members from h families of the rHCOs for each  ḡh value. In these plots, the bars at ḡh = 0% and ḡh = 175% values contain only missing members outside the family’s permissible range, and all bars but these extremes are mixed. As family size decreases, more of the missing values illustrated are from beyond the family’s permissible range. We grouped together all families with the same number of members (and thus the same number of missing members) and showed their data on the same subplot. We color coded the activity type of the missing members. It is easy to see that yellow, the color corresponding to the fHCOs, is predominant, which reveals that most (from 85% for families with seven members to 68% for families with one member) of the missing members from the interrupted h families of the rHCOs are in fact fHCO instances. Table 2 shows the number of missing (h) family members of rHCOs that have functional HCO bursting grouped by the physiological criterion or criteria that they fail. For all families, regardless of size (number of members), the biggest number of missing instances from rHCO interrupted families did not meet the duty cycle criterion. A very small number of these missing instances from rHCO families did not satisfy any of the three realistic criteria. In addition, Table 1 shows that there was a large number of multimember h families of the rHCOs (with more than a third of them being noninterrupted), including 144 perfect h families with all eight members present (circuit stability/strength). These observations show that variations in ḡh might move HCO bursting outside the physiological range but still keep it in the functional HCO range, which shows the robustness of the functional alternating bursting activity to these variations. Figure 5. Distribution of missing members from h families of rHCOs for each̄gh value. The activity type of the missing members is color coded as shown in the legend. Table 2: The number of missing h family members of rHCOs that have functional HCO bursting classified according to the physiological criteria that they fail Period Spike frequency Duty cycle Period and spike frequency and duty cycle Period and spike frequency Period and duty cycle Spike frequency and duty cycle Two members 3,759 3,679 26,449 51 496 3,691 4,324 Three members 2,188 1,597 16,102 31 288 1,923 1,716 Four members 1,286 598 9,538 22 154 1,087 633 Five members 656 195 4,643 22 96 559 216 Six members 162 57 1,628 0 3 146 37 Seven members 31 9 393 0 0 24 2 Bursting activity shows robustness to changes in ḡCaS, if it is sufficiently high Distributions (data not shown) of the missing members from CaS families of the rHCOs for each ḡCaS value revealed that, if the model neurons had low ḡCaS values (0, 25%, and 50%), most of the missing members from the CaS families (∼61%) had continuous spiking activity, and that if the model neurons had sufficiently high ḡCaS (at least 75%), then most (between 79% for families with one member and 95.6% for families with five members) of the missing members from these families had fHCO bursting activity. That is, a minimum of ḡCaS = 75% was the cutoff for system robustness; changes in ḡCaS values <75% will result in changes in the activity type, and changes in ḡCaS values starting from 75% will result in keeping the functional HCO bursting activity. Bursting activity shows sensitivity (no robustness) to changes in ḡP Table 1 shows that the rHCOs had P families with only one or two members, and none of these are interrupted. The plots in Figure 6 show the distributions of the missing members from interrupted P families of the rHCOs for each ḡP value; thus, the plots in Figure 6 had seven and six missing members, respectively. These plots reveal that the activity of the rHCOs was quite sensitive to changes in the ḡP value: any change in ḡP value was very likely (>85.6%) to move the activity type outside functional HCO bursting. For ḡP values <100%, the activity type became predominantly silent (60%) or spiking (12%), and for ḡP values ≥100% the bursting activity became (between 28.8% for families with one member and 66.7% for families with two members) asymmetric (e.g., one cell is silent while the other cell is spiking; Doloc-Mihu and Calabrese, 2011), continuous spiking (between 25.8% for families with one member and 17.4% for families with two members), functional (13.6%), or silent (8%, but only for families with one member). In summary, the activity became predominantly nonfunctional (i.e., no alternating bursting). Figure 6. Distribution of missing members from P families of rHCOs for each ¯gP value. The activity type of the missing members is color coded as shown in the legend. Bursting activity shows more sensitivity (than robustness) to changes in ḡK2 Table 1 shows that K2 had mainly noninterrupted families (13,094), with some interrupted families (1,403). The distributions of the missing members from K2 families for the rHCOs (data not shown) reveal that rHCO activity was quite sensitive to changes in ḡK2 value: a change in ḡK2 value was very likely (>81%) to move the activity type outside functional HCO bursting. For low ḡK2 values (0% or 25%), the activity type became mainly spiking or plateau, and for the rest of the ḡK2 values the activity became mostly asymmetric, to a lesser extent spiking, or in a significant number of cases fHCO (varying from 16% to 26% across ḡK2 values), which was very similar to the sensitivity to changes in P current. Increasing the amount of ḡK2 changed the activity type from spiking to bursting, but mostly asymmetric bursting and not fHCO activity. Bursting activity shows moderate sensitivity to changes in ḡLeak Table 1 shows that Leak had mostly noninterrupted families (12,235) with a fairly large proportion of interrupted families (2,322). Distributions of the missing members from Leak families for the rHCOs (data not shown) reveal that the activity of the rHCOs was quite sensitive to changes in ḡLeak values, as the proportion of missing members that showed functional HCO activity was low, varying between 21% and 51% across ḡLeak values. Increasing ḡLeak values >100% increased the proportion of missing members with spiking activity and decreased the proportion of missing members with asymmetric activity (i.e., outside the fHCO activity). It seems that ḡLeak = 100% was the cutoff for model sensitivity: any ḡLeak value above it decreased the proportion of missing family members with fHCO bursting. This observation indicates that high ḡLeak values move the model neurons outside the fHCO bursting range, but lower ḡLeak values can maintain activity inside the fHCO bursting. Bursting activity shows robustness to changes in ḡSynS towards higher values Table 1 shows that SynS had many noninterrupted families (15,432) but also many interrupted families (9,696). Distributions of the missing members from SynS families for the rHCOs (data not shown) revealed that low values of ḡSynS (<100%) produced mostly (between 57.7% and 93.7% across ḡSynS values) missing members with spiking activity, and that for sufficient values of ḡSynS (≥100%) most (between 64.5% and 96.8%) missing members of the SynS families had fHCO bursting activity. As the amount of ḡSynS increased, there were substantially more missing members with fHCO activity and fewer missing members with spiking activity within each group of families with the same number of missing members. This means that a strong spike-mediated synapse was necessary (at least ḡSynS = 100%) to maintain fHCO bursting activity. In addition, the relatively large number of multimember SynS families of the rHCOs shows that rHCO bursting activity was quite robust to variations of the spike-mediated synapse (ḡSynS); variations of ḡSynS, especially toward large values (at least ḡSynS = 100%) maintained either realistic or functional HCO bursting activity. Bursting activity shows robustness to changes in ḡSynG Table 1 shows that SynG had mainly interrupted families (15,898) with a significant proportion of noninterrupted families (6,437). Distributions of the missing members from SynG families for the rHCOs (data not shown) revealed that most (between 75% and 81%) of the missing members from the SynG families of the rHCOs were in fact fHCO instances. This observation indicates that varying ḡSynG does not disrupt fHCO bursting activity. Based also on the large number of multimember SynG families of the rHCOs, including 1,023 families with all eight members present, it seems that in the HCO model realistic bursting activity was robust to variations of the ḡSynG; variations in ḡSynG values maintained either realistic or functional HCO bursting activity of the neurons. Sensitivity of burst characteristics to variations of ḡ To assess the sensitivity of a characteristic (period, spike frequency) to the variation of a parameter, we plotted the burst characteristic (period or spike frequency) versus the corresponding maximal conductance values of all family members for each of the families (of the parameter considered) that have the same number of members. Then, we connected via a line the burst characteristic values corresponding to two consecutive maximal conductance values (adjacent family members); thus, for each family a curve was plotted. We developed Matlab scripts to automatically analyze each such family curve. First, our scripts checked whether a family curve was monotonic or not, by simply comparing the burst characteristic values of each two adjacent family members (i.e., by calculating their difference). If, for a family, all these differences have the same sign (either positive or negative), the family curve is considered monotonic; otherwise, it is considered nonmonotonic. We separated the families into subgroups according to their monotony (e.g., all four member h families showing monotonically decreasing curves corresponding to period were grouped together). Then, our scripts calculated the average change in burst characteristic for each such subgroup of families (sum over all families of the difference of the last and first members’ burst characteristic values in each family divided by the number of families). Increasing ḡh increases the spike frequency and decreases the period Figure 7, A and B, shows the period plots obtained for h families with eight members and with four members, respectively, for the rHCO group. However, we obtained similar plots for all possible h family sizes of the rHCOs. For all families of h, such plots (Fig. 7A,B) showed that increasing the maximal conductance (ḡh) of the hyperpolarization-activated current monotonically decreases the burst period of the rHCOs, which confirms and extends the results in the study by Hill et al. (2001) stated for the canonical model when one parameter was varied at a time (more restricted parametric space). This decrease occurs because of the ability of the h current to depolarize the inhibited neuron and advance the transition to the burst phase. Figure 7. Variations of burst characteristics (period and spike frequency) vs ¯gh for the realistic HCOs. Lines connect adjacent family members. A, Period vs ¯gh for h families with eight members (144 families). All curves are monotonically decreasing. B, Period vs ¯gh for h families with four members (4,322 families). For four-member families, regardless of the beginning point, all curves are monotonically decreasing. C, Spike frequency vs ¯gh for h families with eight members. Most of the curves are monotonically increasing. D, Spike frequency vs ¯gh for h families with four members. For four-member families, regardless of the beginning point, the vast majority of curves are monotonically increasing. Figure 7, C and D, shows the spike–frequency plots obtained for h families with eight members and with four members, respectively, for the rHCO group. For most families of h (except for 8 out of 2,703 families with five members, for 22 of 4,322 families with four members, for 63 of 6,325 families with three members, and for 353 of 9,895 families with two members), spike–frequency plots (Fig. 7C,D) revealed that increasing the maximal conductance (ḡh) of the 560 hyperpolarization-activated current monotonically increased the spike frequency of the rHCOs. As the family size increased, the average increase in spike frequency for each family increased, from ∼0.29 Hz for h families with two members to 0.71 Hz for h families with eight members (amount calculated as the ratio between the average increase in frequency for all families having same number of members and the number of families). However, as stated in the previous section, increasing ḡh did not increase the burst period but decreased it, due to the ability of Ih to promote the escape of the inhibited neuron. The increase in spike frequency happens because by increasing ḡh the inhibited neuron escapes earlier and starts bursting earlier, which makes the burst duration shorter, leading to higher average spike frequencies. Increasing ḡCaS increases both period and spike frequency For most families of CaS, such period plots (data not shown) revealed that increasing the maximal conductance of the slow Ca current (ḡCaS) monotonically increased the cycle period of the rHCOs. For many of these families, the increase was almost linear. However, for few CaS families—2 families (of 929) of four members, 35 families (of 5,263) of three members, and 137 families (of 17,851) of two members—increasing ḡCaS decreased (not monotonically) the period. We conclude that these results confirm and extend the previous results in the study by Hill et al. (2001). For all families of CaS, spike–frequency plots (data not shown) revealed that increasing the maximal conductance of the slow Ca current (ḡCaS) monotonically increased the spike frequency of the rHCOs. For most families, the increase was big (with an average increase from 5 Hz for families with three members up to >11 Hz for families with six members). This result confirmed the results in the study by Hill et al. (2001) regarding the influence of CaS on spiking activity of the canonical model and explains the effect on period because increased spike frequency leads to greater inhibition of the opposite cell of the HCO. Increasing ḡP increases both period and spike frequency For most (except for 34 of 3,048) families (of two members) of P, plots (data not shown) revealed that increasing the maximal conductance of the persistent Na+ current (ḡP) increased the period of the rHCOs. For many of these families, the increase was large (>9.77 s); the average (over all families with two members) increase of the period was 4.255 s. For the rHCOs, spike–frequency plots (data not shown) of P families revealed that increasing the maximal conductance of the persistent Na+ current (ḡP) increased the spike frequency. For many P families, the increase was noteworthy, with an average increase of 5.37 Hz. The effect on spike frequency accounts for the effect on period through increased inhibition of the opposite cell of the HCO. Increasing ḡK2 decreases the period For the rHCOs, plots (data not shown) of period versus ḡK2 values for all families of K2 revealed that for most (except for 19 of 13,163 families with two members) families of K2, increasing the maximal conductance of the persistent K current (ḡK2) monotonically decreased the period of the rHCOs. For many of these families, the decrease was large (average of 3.32 s for families with two members, of 4.87 s for families with three members, and of 6.59 s for families with four members). Once again, our results confirm and extend the previous results of the study by Hill et al. (2001). For many families of K2 (except for 424 of 13,163 families with two members, and for 4 of 1,299 families with three members), spike–frequency plots (data not shown) showed that an increase in the maximal conductance of the persistent K current (ḡK2) led to a decrease in the spike frequency. The decrease was >2 Hz on average, and it occurs due to the ability of IK2 to decrease the peak of the (slow-wave) oscillation during the burst. Again, the change in spike frequency with ḡK2 accounts for the change in period due to a change in inhibition of the opposite cell in the HCO. Increasing ḡLeak decreases both period and spike frequency For the rHCOs, plots (data not shown) of period versus ḡLeak values for all Leak families revealed that for most (except for 345 of 11,873 families with two members, for 1 of 2,133 families with three members, and for 1 of 452 families with four members) families increasing ḡLeak decreased the period. The average decrease of the period was 2.46 s for families with two members and went up to 5.78 s for families with six members. For most Leak families (except for 13 of 11,873 families with two members), spike–frequency plots (data not shown) of spike frequency versus ḡLeak values revealed that increasing ḡLeak decreased the spike frequency. The average decrease of the spike frequency was 2.72 Hz for families with two members, and it increased up to 7.55 Hz for families with six members. Again, the change in spike frequency with ḡLeak accounts for the change in period due to a change in inhibition of the opposite cell in the HCO. Increasing ḡSynG results in negligible changes in period and spike frequency Plots (data not shown) of period versus ḡSynG values for all rHCO families of SynG revealed that for many families (except for 1,241 of 7,047 families with two members, for 1,099 of 5,086 families with three members, for 1,114 of 4,124 families with four members, for 1,038 of 3,046 families with five members, for 799 of 1,971 families with six members, for 572 of 1,061 families with seven members, and for 761 of 1,023 families with eight members) increasing ḡSynG increased the period. As the number of members within families increased, there was an increase in the number of families for which increasing ḡSynG decreased the period. However, the change (either increase or decrease) in period was small (<0.4 s on average), and therefore we conclude that SynG does not play an important role in controlling period. For most families of SynG, spike–frequency plots (data not shown) revealed that increasing ḡSynG changed the spike frequency of the rHCOs negligibly (average change between 0.18 and 0.31 Hz for families with two and seven members, respectively). For most families (except for 2,291 of 7,047 families with two members, for 1,522 of 5,086 families with three members, for 999 of 4,124 families with four members, for 704 of 3,046 families with five members, for 409 of 1,971 families with six members, for 214 of 1,061 families with seven members, and for 170 of 1,023 families with eight members), increasing ḡSynG slightly increased the spike frequency. We conclude from the small changes in burst characteristics (period and spike frequency) when ḡSynG is varied that, while some amount of graded transmission may contribute to alternating bursting (maybe 25% is good enough), there is no added benefit to having higher ḡSynG values. Increasing ḡSynS increases the period, but decreases the spike frequency For almost all rHCO families of SynS, plots (data not shown) revealed that increasing the maximal conductance of the spike-mediated synapse (ḡSynS) monotonically increased the burst period of the rHCOs (except for 74 of 16,950 families with two members, and for 3 of 6,390 families with three members). The average increase of period was from 2 s for families with two members to 5 s for families with six members. For many SynS families (>55%), spike–frequency plots (data not shown) showed that increasing the maximal conductance of the spike-mediated synapse (ḡSynS) decreased the spike frequency of the rHCOs. The decrease started from an average of 0.35 Hz for families with two members, and it increased to an average of 2.5 Hz for families with six members. The larger the family size, the larger was the number of the families that show this decrease in spike frequency (from 55% of families with two members to 90% of families with six members). Analysis of family structure shows how ḡh influences period of realistic HCO instances To analyze how burst characteristics in rHCOs are influenced by varying a ḡ value, we took advantage of family structure and made graphs like those in Figure 7, in which we plotted a burst characteristic [e.g., period (Fig. 7A,B) or spike frequency (Fig. 7C,D)] vs ḡ values for families of different sizes. By looking across families, we could spot trends in these relationships. We will focus here on period versus ḡh values for h families of rHCO instances. All these plots show monotonically decreasing curves of period versus ḡh values for each h family, regardless of family size (we checked the monotonies using our Matlab scripts). We observed that these monotonically decreasing curves show different rates of decline, indicating different sensitivities of period to changes in ḡh. Some seemed to decline very steeply with increasing ḡh, and some seemed to decline quite gradually. Using our own Matlab scripts (see Sensitivity classification), we automatically separated the h families according to their curve steepness (period sensitivity) into the following three groups: high-sensitivity (steep slope), medium-sensitivity, and low-sensitivity (shallow slope). Figure 8A shows the split between the curves of the h families with eight members whose curves were illustrated in Figure 7A. Our algorithm found 35 families with high-sensitivity, 57 with medium-sensitivity, and 52 with low-sensitivity. Table 3 provides the number of curves for each sensitivity group for all h families of rHCOs. It is easy to see that the group with steep slopes had the smallest number of families (curves). Most families with many (six to eight) members were in the medium-sensitivity group, otherwise the low-sensitivity group prevailed. For each sensitivity group (high, medium, and low), the plots in Figure 8B show the ranges of each parameter for h families with eight members. Plots in Figure 8C show the parameter ranges for the h families with four members (Fig. 7B, family curves). In the plots of Figure 8, B and C, the size of each point shows how many distinct families of the respective family group have a certain parameter value. For better visualization, the points in Figure 8B have been scaled up five times because there was a small number of families for many parameter values, and black diamond shapes show the median values for each parameter. Figure 8. Sensitivity of period to the variation of ¯gh for h families of realistic HCOs. A, Plots of period vs ¯gh for h families with eight members (144 families). Lines connect adjacent members of an h family forming a curve. Curves were split into three groups according to their period sensitivity (slopes), as follows: high (steep slopes; 1); medium (medium slopes; 2); and low (shallow slopes; 3). B, Parameter values vs the number of distinct families for all h families with eight members separated into these three groups of sensitivity. The size of each point quantifies how many different families have that parameter value (here, we scale up the sizes by five times for a better display). Black diamond shapes show the median values for each parameter. C, Parameter values vs the number of distinct families from all h families with four members separated into the three groups of sensitivity. For simplicity, plots do not show data for ¯gSynG since the graded transmission did not have a significant influence on burst characteristics (see Sensitivity of period to variations of ¯g's, and Sensitivity of spike frequency to variations of ¯g's). Table 3: The number of h family curves of the rHCOs classified according to their (period) sensitivity (curve slopes) Three members Four members Five members Six members Seven members Eight members High 690 684 583 323 121 35 Medium 1,002 1,239 979 528 233 57 Low 4,633 2,399 1,141 434 183 52 For the high-sensitivity group (Fig. 8 B1,C1), the reversal potential Eleak showed a full range. For h families with many members (six to eight members), Eleak (−55 or −60 mV) showed the greatest number of families; for the rest of h families (with three to five members), a hyperpolarized Eleak (−65 or −70 mV) showed a slight increase in the number of families. ḡLeak showed also a full range of its values, with an increase in the number of families as ḡLeak decreases. ḡK2 had values between 25% and 175%, which meant that K2 must be present for rHCO h families to have high h sensitivity. An increased amount of ḡK2 seemed to increase the number of families, with a maximum reached at 150% (median, 125%). ḡP had a range similar to ḡK2, with values between 25% and 175% (median, 75%). ḡCaS showed a full range of its values for h families with three members, and a range between 25% and 150% for the other h families. More interestingly, for ḡCaS values between 25% and 75%, we observed the most h families, while for higher values we observed just a few families (peak at 50%, which was also the median value). ḡSynS seemed to be needed (at least 25% present) to have full stability (eight member families); otherwise, it showed the whole range of values (e.g., families with four members; Fig. 8C1). ḡSynG and ḡh showed the full range, with an almost equal number of families at each value. For the medium-sensitivity group (Fig. 8B2,C2), the reversal potential Eleak showed a full range for all h families except the ones with eight members, for which the range was from −60 to −50 mV. There was a monotonic decrease in the number of families as the reversal potential becomes hyperpolarized. ḡLeak showed a full range for its values for all h families except those families with eight members, for which the range was from 25% to 175%. ḡK2 had values between 25% and 175%, except for one case of a family with five members, which meant that K2 must be present to have rHCOs h families with medium-sensitivity. An increased amount of ḡK2 seemed to increase the number of families, with a maximum reached at 150%; the median value was at 125%. ḡP had a range similar to that of ḡK2, with values between 25% and 175% (median, 75%). ḡCaS showed a range between 25% and 175% for the h families with three to seven members, and a range between 25% and 100% for the families with eight members. ḡSynS seemed to be needed (at least 75% present) to have full stability (eight-member families), otherwise it showed a whole range of values. ḡSynG and ḡh showed the whole range of values for all families of different sizes. For the low-sensitivity group (Fig. 8B3,C3), the reversal potential Eleak showed a full range for families with fewer than seven members, and a range between −60 and −50 mV for families with many members (seven and eight members). More interestingly, for this sensitivity group there was a monotonic decrease in the number of families as the reversal potential becomes hyperpolarized. ḡLeak showed a full range for families with fewer than seven members. ḡK2 had values between 25% and 175% for h families with six to eight members, and a full range for the remaining h families (three to five members), although analysis showed a very small number of families where there is no K2 (Fig 8C3, this point in the plot is too small to see and represents one family). An increased amount of ḡK2 seemed to increase the number of families, and the median value was at 125%. ḡP had values between 25% and 175% for families with five to eight members, and full range for the remaining h families; the median value was 75%. ḡCaS showed a full range for families with three members, and a range between 25% and 175% for the remaining h families. The median values were at 100% for families with three to five members and at 75% for the others (six to eight members). ḡSynS seemed to be needed (at least 75% present) to have full stability (eight-member families), otherwise it showed the whole range of values (data not shown). ḡSynG and ḡh showed the whole range for all families of different sizes. There is no set or range of parameters that we can detect that characterizes the period sensitivity (period vs ḡh). Moreover, we observed no linear correlations of parameters in any of the period sensitivity groups. For example, we applied principal component analysis (PCA) to each of the three sensitivity subgroups of eight-member h families of rHCOs in Figure 8, A and B (data not shown), and found no linear correlations. There are, however, a few observations that we can make from the plots in Figure 8 about how parameters contribute to period sensitivity. The graded synapse ḡSynG seems to not have any influence on period sensitivity as varying it does not change the number of families (constant). ḡK2, ḡP, and ḡCaS seem to be needed to produce rHCOs (values of at least 25%). As expected, Eleak and ḡLeak seem to affect activity in the same way; the number of rHCOs increases for high sensitivity or decreases for low sensitivity for both parameters at the same time. ḡK2 and ḡP also affect activity but differently, as it seems that one compensates for the effect of the other; this result (correlated triplet of ḡLeak, ḡK2, and ḡP) was observed (Doloc-Mihu and Calabrese, 2014) in regular bursting neurons (isolated HCO cells). The amount of ḡCaS does seem to have an effect on sensitivity type. There are few high-sensitivity h families with three members with zero ḡCaS and few low-sensitivity h families with three members with zero ḡK2 and ḡP. Except for h families with three members where it shows the full range from 0% to 175%, it seems that the amount of ḡCaS shows the smallest range for the high-sensitivity group (25–75%) for families with eight members, and 25–150% for families with four to six members, with most families having values between 50% and 100%. Except for families with eight members, the low- and medium-sensitivity families show a range of 25–175% for ḡCaS. For the high-sensitivity families with different numbers of members, the median is consistently at 50% of ḡCaS; for medium-sensitivity families, it is at 50% for h families with many members (seven and eight), and at 75% for the remaining h families (3-6 members); and for the low-sensitivity families, it is either at 75% or at 100% of ḡCaS. Analysis of family structure helps identify ensembles of model instances for modeling studies Our family analysis can help to identify parameter sets that approximate the physiological activity of any neuronal or network model more closely than hand-tuning methods and more efficiently than search methods, such as genetic algorithms (Holland, 1992). We propose selecting these robust parameter sets from the noninterrupted families with a large number of members (more than four members); each family identifies one such potential set of parameters. Our first step for identifying a good ensemble of model instances to best approximate the HCO physiological bursting was to select from the set of noninterrupted large member families a subset that have nonzero values for each parameter (i.e., ḡ ≠ 0) other than the defining parameter. For example, there were 119 such families from the 144 h families of realistic HCOs with eight members. Then, for our next step we selected from the above subset only those families that include members whose corresponding isolated neurons show a specific activity type. For example, in Figure 9, A1 and B1, we show (in red) two h families of realistic HCOs selected from the families with eight and five members, respectively. We selected these families such that the isolated neurons corresponding to their members have spiking and realistic bursting, respectively. In Figure 9, A2 and B2, we show the voltage traces of both neurons for some members of these two h families; 22 s was represented in each trace. One can see how varying ḡh influences the bursting activity. The first family (Fig. 9A) shows a moderate sensitivity to variations of ḡh, and the second one (Fig. 9B) shows a high sensitivity (busting speeds up fast by modulating h). Figure 9. Examples of ensembles of physiological model instances with large noninterrupted families from which one can choose a canonical model to reflect typical robust physiological activity. Plots show period vs ¯gh values for h families of realistic HCOs with lines connecting adjacent family members. The chosen ensemble is highlighted in red. The voltage traces of the two interneurons corresponding to a certain model from the family are shown above their corresponding ¯gh values (bigger red circles); each trace is the same amount of time (22 s). Horizontal lines indicate −50 mV for each trace. A1, Ensemble corresponding to a noninterrupted h family with eight members (of 119 families having all other ¯g’s ≠ 0) showing medium-sensitivity slope curve of period vs ¯gh. A2, The three selected models give rise to spiking isolated neurons by cutting any synaptic transmission (¯gSynS = 0 and ¯gSynG = 0). B1, Ensemble corresponding to a noninterrupted h family with five members (out of 513 noninterrupted families having all other ¯g values ≠0) showing a high-sensitivity slope curve of period vs ¯gh. B2, The three selected models give rise to realistic bursting isolated neurons by cutting any synaptic transmission between the two neurons. The voltage traces shown in Figure 9, A2 and B2, illustrate activity closely corresponding to leech physiological HCO activity (period between 5 and 15 s; average spike frequency between 8 and 25 Hz; duty cycle between 50% and 70%), as indeed each member of a rHCO family must. Model instances from the family in Figure 9A2 are of particular interest to us since they have the strong synaptic inhibition, observed experimentally. By having a duty cycle <50% (49.38%), the canonical model of Hill et al. (2001) would not be included in our realistic HCO group but in the functional HCO group (it belongs to the set of h families of fHCOs with six members). Like the canonical model of Hill et al. (2001), our model instances from Figure 9A2 have isolated neurons with spiking activity type. All the h families of rHCO model instances from Figure 9A1 thus better approximate the physiological activity of the leech HCO system than the canonical model of Hill et al. (2001), because every member of every family conforms to the physiological activity. Similarly, other large h families of rHCOs (Fig. 9B1, four-member families) conform to the physiological activity. These families thus comprise a useful ensemble of model instances for exploring the mechanisms of the physiological activity. We conclude that our family-based method is a good tool for identifying such ensembles. Discussion We used an HCO model that replicates the rhythmic alternating bursting of mutually inhibitory interneurons of the leech heartbeat CPG to investigate the robustness (or sensitivity) and modulability of bursting activity to maximal conductance (ḡ) variations. We systematically explored the parameter space of two groups from the 10.5 million instances comprising the entire HCO model space, whose characteristics were previously recorded into a database, as follows: rHCOs with 99,066 instances; and fHCOs with 1,103,073 instances (Doloc-Mihu and Calabrese, 2011). To analyze such a large number of instances, we developed a new method (family based) that allowed us to classify instances from these two large groups (rHCOs and fHCOs) into much smaller subgroups of instances called families. Families are groups of model instances that differ only by the value of the one parameter that defines the family. By examining family structures and patterns, we developed new measures of robustness (or sensitivity) of bursting activity to changes in model parameters and investigated how such variations can be harnessed to modulate activity characteristics without compromising robustness. These measures can be easily adapted to other forms of electrical activity and other parameter types, and applied to brute-force databases. Our decision to limit our parameter variations to variations of ḡ values while holding constant other kinetic parameters of the ionic currents was based on our available voltage-clamp analyses, which used average data to determine activation/inactivation and temporal characteristics of the currents. This decision limits the impact of our analysis (Amendola et al., 2012) but not the ability to apply our method to other systems where varying these parameters seems appropriate. Robustness measures We investigated independently the role of each conductance in the robust maintenance of functional bursting activity. Families organize model instances (rHCOs and fHCOs) into small subsets of instances sharing the same seven parameter values. Using families, we defined robustness with a number of different measures and analyzed all families of each parameter with respect to these measures to find potential patterns. Our first measure was based on the family size: the greater number of these large families, the greater robustness. rHCO families with many members (seven or eight members of possible eight members) all maintain realistic bursting activity over a large range of values of the parameter. By this measure, realistic HCO activity was robust to changes in ḡh and ḡSynG, but it was very sensitive to changes in ḡP, and to a lesser extent to changes in ḡK2. Our previous results (Doloc-Mihu and Calabrese, 2014) show that isolated neurons that are realistic bursters had only CaS families with one to three members, meaning that the activity of the realistic bursters was quite sensitive to changes in the value of ḡCaS. By adding inhibition (HCO configuration), the number of CaS families with many members (one to six) increased, making the system less sensitive to variations in the value of ḡCaS. However, the small number (four) of CaS families with six members for rHCOs suggested that the system is not as robust to variations in ḡCaS values as it is to variations in ḡh values. Our second measure of robustness was based on family sequence (the sequence of values of the varied parameter within the family), as follows: a noninterrupted family sequence shows robustness (not broken by changing the defining family parameter value over its permissible range) and an interrupted family sequence shows sensitivity (susceptible to a change in activity type or nonphysiological burst characteristics by changing the defining family parameter values). We found that the higher the values of ḡh within the family, the more robust the sequence; thus, the higher likelihood of finding realistic HCO activity. Conversely, the lower the values of ḡh within the family, the more sensitive the sequence. Lower ḡLeak values (0–100%) resulted in more robust realistic HCO activity (more noninterrupted families than for higher ḡLeak values). Stronger (≥60 nS) spike-mediated synaptic transmission promoted robust realistic HCO activity. The system is quite robust to variations of graded transmission (SynG). Our third measure of robustness was based on the activity type shown by the missing family members in both interrupted and noninterrupted families (i.e., both within and outside the permissible range): best if missing members have functional HCO activity, because by varying the parameter the HCO bursting is still kept functional. Plots of distributions of missing points from h families of rHCOs revealed that HCO bursting activity was robust to variations of ḡh, as variations of ḡh maintained fHCO bursting activity, though they might interrupt or terminate a realistic HCO family sequence. We conclude that ḡh is a potential target for modulation, since the HCO system shows robustness to its variations. The h families of the realistic bursters group (isolated neurons) were in general small (64 families with two and three members) with very few larger families (6 families with four members and 1 family with five members), with most missing members silent (data not shown; Doloc-Mihu and Calabrese, 2014). A change in ḡh has a significant chance of disrupting regular bursting activity in synaptically isolated neurons transforming their activity into silence, but by adding inhibition and forming an HCO, such variations of ḡh maintain functional HCO bursting activity. Based on these observations, it seems that in the heartbeat HCO inhibition makes the activity very robust to variations of ḡh. Plots of distributions of missing points from CaS families of rHCOs revealed that HCO bursting activity was robust to variations of ḡCaS, if ḡCaS was ≥75% of the canonical value. Realistic HCO activity is robust with a low ḡLeak (0–100%) present in the system (missing members have mostly fHCO activity); ḡLeak >100% favors spiking and silent activity. The distribution of missing points from P families of rHCOs revealed that changes in the amount of ḡP moved the HCO bursting activity outside the fHCO bursting range (to spiking, silent, or asymmetric activity). We conclude that ḡP is not good as a target for modulation since the activity type of the system is very sensitive to its variations. Changes in the amount of ḡK2 also disrupted HCO bursting activity, but not quite as severely as ḡP. Finally, distributions of the missing members from SynS families for the rHCOs show that at least 100% of ḡSynS was necessary to maintain fHCO bursting. Strong spike-mediated synaptic transmission promotes functional HCO activity. For h families of rHCOs, most of the missing members (increasing percentage, from 62.3% for families with two members to 85.6% for families with seven members) have fHCO bursting activity for which only their duty cycle is outside the permissible physiological range (0.5–0.7). This result pertains to all h families of rHCOs (Table 3). The percentage of these missing members of h families that had burst periods either too long or too short to have rHCO activity (only their period outside the permissible range of 5–15 s) varied between 6.8% for families with seven members and 10.3% for families with five members. The number of missing members that spike too slowly (spike frequency <8 Hz) or too quickly (spike frequency >25 Hz) during the burst diminishes (from 8.7% for families with two members to 2% for families with seven members). For all h families, <0.3% of missing members from h families of rHCOs went outside the permissible realistic HCO range for all three criteria. A corollary of our measures of robustness, which directly indicates the suitability of a parameter for functional modulation of the bursting activity, was based on a reliable and predictable (monotonic) variation in burst characteristics (period and spike frequency) within the realistic and functional range when a parameter was individually varied. Several clear patterns have emerged for rHCOs. Increasing ḡh increased the spike frequency moderately and decreased the period, speeding up the realistic HCO bursting activity. Increasing ḡCaS increased the spike frequency more strongly and increased the period. Increasing ḡP strongly increased the spike frequency and the period. For many K2 families, increasing ḡK2 decreased the spike frequency and the period. For most Leak families, increasing ḡLeak decreased the spike frequency and the period. Increasing ḡSynG showed negligible changes in spike frequency and period, and increasing ḡSynS decreased the spike frequency and increased the period. All these results on the influence of parameter variation on burst characteristics confirmed and extended the previous results in the study by Hill et al. (2001) obtained in a more restricted parametric space (variation of a single parameter over a range similar to the one presented here but on a background of canonical values for all other parameters). So, to decrease period, for example, we can increase the amount of ḡh, ḡK2, and ḡLeak or decrease the amount of ḡCaS, ḡP, and ḡSynS. If we consider the other measures of robustness and this measure of modulatory effectiveness, then varying ḡh appears ideal for modulating period because the HCO system is very robust to the variation in ḡh and ḡh consistently and substantially modulated period with minimal adverse effects on spike frequency or duty cycle. For a specific (chosen) parameter, t, we propose the following simple formula as a general measure of robustness for large databases: (1) Rt,n=wX*Xt,n+wY*Yt,n+wZ*Zt,n where Xt,n is the number of families with more than a chosen number of members (n, best when n is large); Yt,n is the number of noninterrupted families with more than n members; Zt,n is the number of interruptions (missing families members) that do not change the activity type; and wX, wY, wZ are chosen weights that show the importance of each individual robustness measure in assessing the final robustness of the parameter t, with wX+ wY+ wZ=1. The formula is a simple weighted cumulative sum of the three measures of robustness that we proposed above. The weights indicate the importance of each measure of robustness within the system and depend on what the user values as robust in their system. In our study here, we chose to assess the robustness for the realistic HCOs. We selected as a parameter t, the maximal conductance of the hyperpolarization-activated cation (h) current, ḡh. For n=4, our numbers for calculating total robustness follow. First, we selected from our rHCOs all h families with more than four members and obtained the first measure of robustness, Xh,4 =4,669. The total number of noninterrupted families is Yh =11,210, and the number of interruptions that keep the functional bursting activity, fHCO is Zh= 98,882. Next, Yh,4 =1,729, and Zh,4 =8,945. Finally, we chose to assess robustness by giving equal importance to our first two measures and by not considering the third one (i.e., wX= wY =0.5,  wZ=0, and Rh,4=3,199). To put this number in perspective, it can be normalized to the user’s goal. For example, normalizing to the total number of families with more than four members shows that ∼70% (0.685) of the h families with more than four members maintain realistic alternating bursting activity when ḡh varies (i.e., no interruptions). Robustness and parameter correlations We emphasize that we previously found no linear correlations among parameters in the rHCO group (Doloc-Mihu and Calabrese, 2014). Figure 1 reveals a nonlinear correlation among Eleak, ḡLeak, ḡK2, and ḡP for the rHCOs (c.f. Goldman et al., 2001), but no other nonlinear correlations were observed. Nor were there any linear correlations (via the PCA method) or other nonlinear correlations in any subgroup tested. For example, we applied PCA to each of the three sensitivity subgroups of eight-member h families of rHCOs of Figure 8, A and B (data not shown), and found no linear correlations. How then would parameter correlations affect robustness as determined by our cumulative measure? Our previous work showed that for the component neurons of the HCO to be endogenous bursters, there must be a strict linear correlation among ḡLeak, ḡK2, and ḡP. We enforced this correlation in our database by requiring endogenous bursting of the component neurons in all families considered. We then used the same measures as above and obtained Xh,4enf=53, Yh,4enf=51, Zh,4enf=2, and Rh,4enf=52. These numbers indicate that this correlation, should it be biologically enforced, would limit the robustness. This finding is consistent with the observation that endogenous bursting in heart interneurons is very sensitive to changes in leak (e.g., as caused by sharp microelectrode penetration) and that it is not necessary for robust alternating bursting activity (Sorensen et al., 2004) or when h current is modulated (Tobin and Calabrese, 2006). Moreover, the vast majority [94,487 (95.37%)] of rHCOs in our database are made up of component neurons that are spiking. It is interesting to note that such biologically enforced correlations have been observed in the stomatogastric nervous system (Goaillard et al., 2009; Tobin et al., 2009) and cardiac ganglion of crustaceans (Ball et al., 2010). In the cardiac ganglion at least, such correlations appear to increase robustness. Period sensitivity We separated our h families with eight members into three groups according to their period sensitivity to increasing ḡh (high, medium, and low sensitivity). For high-sensitivity families, increasing ḡh speeds up bursting strongly; a large decrease of period with increasing ḡh occurs (typically before 50% ḡh), then this decrease moderates at higher ḡh values. For low-sensitivity families, increasing ḡh speeds up bursting more uniformly; period decreases moderately but almost linearly for all ḡh values. The medium-sensitivity families are intermediate; period decreases steadily with increasing ḡh, but there is neither a sudden drop nor a range of weak period decrease. This splitting seems functional to us and shows how parameters interact within specific ranges to produce these different types of sensitivities. We put in the medium-sensitivity group all those families that were in neither the high-sensitivity nor the low-sensitivity group. One could argue that defining this group of medium sensitivity might not be germane to the analysis, because the set of h families illustrates period curves whose slopes (with respect to the horizontal axis) occupy the entire spectrum of angles. The decision to keep three groups versus two groups (high and low-sensitivity) was based on visual inspection of 100 randomly selected slopes. This process helped us to set the criteria for slope angles of the two important cases of low and high-sensitivity. The results show that the region with the steepest slope (high-sensitivity region) can appear anywhere, but in ∼98% of the cases it appears at the very beginning of the curve [i.e. at low values of ḡh (<100%)]. For the medium-sensitivity group, a steep slope region occurs at higher ḡh (100–150%) or not at all. For the low-sensitivity group, there is no steep slope region, only a nearly constant slope. Note that all curves show monotonically decreasing periods with the increase in ḡh. Splitting the families into three sensitivity groups, moreover, helped us to define how other parameters define period sensitivity to the variation of ḡh by analysis of the ends of a spectrum. We used this analysis of h families to investigate the effects of background conductances on the period of realistic HCO bursting. To sum up this period sensitivity analysis, several parameters influence the realistic HCO burst period. Shorter periods seem to be influenced by K2 and P working together against Leak, with CaS also having some effect. Longer periods seem to be affected by K2 and Eleak working together against P, by the amount of CaS, which has the same influence as K2, and also by the spike-mediated synaptic transmission SynS. From this analysis, we conclude that period is influenced by groups of parameters but it is easily and predictably controllable by modulating ḡh. It appears that in the HCO system there are several different mechanisms that influence robust realistic bursting. One mechanism that we found involves Eleak, ILeak, IP, and IK2 working together to compensate for the variations in each to keep bursting functional. In isolated bursting neurons, these parameters interact in a linearly correlated way (Doloc-Mihu and Calabrese, 2014). Linking these isolated bursting neurons by mutually inhibitory synapses into HCOs increases the system robustness and causes these parameters to interact in a nonlinear way. Another mechanism we found involves specific parameters working individually to change the burst characteristics (here, we focused on burst period and spike frequency). Our results show that realistic, physiological bursting activity is robust to changes in the amount of h current, and that h is a great target for modulating period (because varying the amount of ḡh changes the burst period in a significant and predictable way). This result confirms and supplements the conclusions of previous theoretical studies (Nadim et al. 1995; Hill et al., 2001) and extends them to combinations of key parameters that are varied together. Moreover, the peptide myomodulin upmodulates the h current in heart interneurons that comprise HCOs and consistently speeds the burst period (Masino and Calabrese, 2002; Tobin and Calabrese, 2006). Recent experiments (Tsuno et al., 2013) show that Ih is a good modulation target for the phase of neurons in rat cortex, emphasizing the general importance of this current for modulation. Applicability of the robustness measures Last, we emphasize that the measures of robustness we developed here are easily adaptable to other neuronal and network models. Brute-force databases, such as HCO-db, lend themselves to the family analysis we performed here. By identifying families and applying our measures—the number of large families, the number of noninterrupted families, and the missing family members that show functional albeit not physiological activity (i.e., no change in activity type)—one can identify parameters that can be safely modulated. Then, using large families one can identify those parameters that consistently modulate an adaptable and desirable activity characteristic. Family analysis can also allow the identification of robust parameter sets that more closely approximate physiological activity of any neuronal or network model, and thus allow the construction of an ensemble of physiological model instances for further mechanistic studies. For example, the ensemble of physiological model instances with large noninterrupted families we have identified will allow us to ask whether for effective, functional modulation there are advantages to covarying currents over a single particularly efficacious current like h in the leech heartbeat HCO. Acknowledgments: We thank our student Ranran Li for help with the 3D view. Synthesis The decision was a result of the Reviewing Editor Marlene Bartos and the peer reviewers coming together and discussing their recommendations until a consensus was reached. A fact-based synthesis statement explaining their decision and outlining what is needed to prepare a revision is listed below. The following reviewers agreed to reveal their identity: Ilya Rybak, Jorge Golowasch This study has been carefully reviewed by two experts and the major criticism is summarized below. The main focus of the presented work is the question of 'What constitutes robustness of activity in systems in which the ionic conductances show high levels of variability?' By addressing this question the article does advance the field. Despite this positive comment both reviewers formulated a detailed long list of major and minor criticisms which strikes the center of the study. In the following summary only the major critical points have been summarized. However, we strongly recommend that the authors address all points raised by the reviewers. (1) The main objectives and goals of this work and, finally, the obtained results in relation to these objectives and goals are not clearly formulated. (2) The model of Hill et al. (2001) is one of the best examples of computational neural models in neuroscience. In the present manuscript, the author analyzed the robustness and sensitivity of that model to variation of some key parameters. Please carefully address the following questions: What can this study add to that classical model? Does this study allow a new evaluation of this model and/or suggest how to improve it, or can it confirm that the original model is good enough? Explicitly discuss the significance of the results in the Discussion and Significance Statement. (3) Please provide in the discussion the implications of the new discoveries. (4) Please improve the writing style of the manuscript. In particular remove all typos, grammatical and syntactical errors. Reviewer 1: Major points I believe that the manuscript may be significantly improved by focusing on the following issues: 1. I would advice the authors to clearly formulate the main objectives/goals of this work and, finally, the obtained results in relation to these objectives/goals. It is not completely clear from the paper (as it is written) whether the authors (a) present a new method of parameter search in a large parameter space based on a novel method allowing a reduction of this space, which can be applied to many other models, but is currently applied to a particular, previously published model as an example, or (b) they specifically focus on the analysis of the robustness of this particular model to the variation of some of its key parameters. So it would be very useful for a reader if the authors could clearly state their objectives/ goals from very beginning, like "The objective(s) of this study was (were) ....", in the Abstract and Introduction and then provide discussion the obtained results in the Discussion in relation to the formulated objectives. This does not require significant changes in the text, but adding clearly formulated statements in the Introduction and Discussion and a better formulation of these issues in the Abstract and Significance Statement. In the former case (a), some general conclusions about the proposed search method and its advantages should be formulated and discussed independent of the particular model used, so that the researchers could understand how to use this novel approach/method in the analysis of other models. In the latter case (b), it would be interesting to see some discussion concerning the range of the selected parameters from the literature, measured from real biological preparations, and the anticipated effects of their changes (e.g. by some pharmacological blockers) on the generated rhythmic activity, such as the period of oscillation (if such data exists), or to see the corresponding testable predictions (if such data does not exist). The model of Hill et al. (2001) is one of the best examples of computational neural models in neuroscience. In the present paper, the author analyzed the robustness/sensitivity of that model to variation of some key parameters. So the question is what to do with this new knowledge. What this study can add to that classical model? Does this study allow a new evaluation of this model and/or suggest how to improve it, or can it confirm that the original model is good enough? I would advice the authors to explicitly discuss the significance of their results (what can be done based on these results or how they can be used) in the Discussion and Significance Statement. 2. Many parameters that define the kinetics of a particular ionic channel can affect the value of the corresponding ionic current and the performance of the entire model. For example an ionic current can be changed by changing the maximal conductance, or without changing the maximal conductance, by changing some other channel parameters, such as half-activation or half-inactivation voltages, slopes of voltage-dependent characteristics, and so on. In this case, the selection of parameters to be included in the space of parameters for search should be somehow justified. The authors stated that "...neuronal networks of animals are robust to natural variations, modulation and environmental perturbations of parameters like maximal conductance of intrinsic membrane and synaptic currents. Our study here focuses on the role of all these maximal conductances ....." However, there is a difference between using parameters "like maximal conductances" and using only maximal conductances. The use of maximal conductance as the only unknown parameter of a voltage-dependent channel could be justified as soon as all other voltage- and time- dependent characteristics of this channel have been experimentally measured from a representative neuron type. If the values of all these parameters were only suggested, but not measured, then what justification can be used for including in the parameter space only maximal conductances and keeping all other unknown channel parameters fixed. This issue should be discussed in the Discussion. Minor Abstract: How a reader can understand from the Abstract the difference between the "realistic HCO" and the "functional "HCO", and what is "h" and "P"? In my opinion, all non-standard terms in the Abstract should be either defined or removed. Line 11: please clarify and rewrite: "when working individually in the robust maintenance of normal alternating bursting activity" Line 13: replace "CPG (central pattern generator)" with "central pattern generator (CPG)" Line 20: change "families that have a biological meaning" to families that varied only by one parameter while the remaining parameters were held constant (or something equivalent). Lines 24-28: The statement " Our results showed that the HCO system is very robust to variation in h which in turn consistently and substantially modulated period. The system is very sensitive to variations in P but functional bursting is stabilized by synaptic inhibition. We also found that period is determined by the interactions of shifting sets of parameters across the parameter space, but is easily and predictably modulated by varying h" is very difficult to understand. I would advice the authors to formulate their main results clearly and more general, so that people could understand their main achievements by reading the Abstract? Significance Statement: I would advice to include a more generally formulated significance of the work without details concerning concrete currents. Results and Discussion Line 99: replace "our own" with "new" or "novel" Line 100: "instances that have a biological meaning" not clear what this means, I would suggest removing this and replacing it with a short explanation of a family. Line 191: please clarify "and all the g's within the same family form the family's sequence" Line 195: according to your definition "realistic bursters" should be a subgroup of "bursters", however, the numbers given here don't correspond to that. Line 289: please explain "As a statistic" Line 293: "this" to "the" Line 306: change "Using this criterion, from above," to "Using these criteria" Line 314: replace "(starting and ending gh values)" with something like "sorted by their starting and ending g values". Throughout the text you might even consider changing "starting" and "ending" to "lowest" and "highest" since especially with interrupted families there is not really a "start" or "end". Line 419: change "if enough CaS is present" to "if gCaS is sufficiently high" (or similar) Line 423: change "model neurons had enough CaS" to "model neurons had sufficiently high gCaS" (or similar). Line 732: remove "biological meaning" and add a short explanation of "family" Figure legend 3 and 4: you use the term "circuit break" that is not defined anywhere else, please make consistent with the rest of the text Figure 1: - please add the unit of Eleak in the key and I suggest giving Eleak values in mV instead of V also correct the last one Eleak = -0.5, should be -0.05 V or -50 mV Figure 8: - I suggest rearranging the panels from high to low sensitivity (or vice versa) - Please remove the grey line at 100% and the stars since they don't add to the understanding, 100% is per definition the canonical model and since this model is not represented in the figures as you describe in the text, indicating it is not just unnecessary but also confusing. The stars are not mentioned in the figure legend and don't serve a purpose, as far as I can tell. Reviewer 2: Neurons have been recently shown to express well-defined activity (e.g. bursting, tonic firing) in spite of the fact that their ionic conductance levels can vary over very broad ranges. Correlated expression of these conductances has been claimed to be important to maintain activity more or less bounded as conductances vary. This is best studied and has been confirmed in systems in which neuronal cell types can be identified without ambiguity, such as small invertebrate and vertebrate networks. The present work addresses the question of what constitutes robustness of activity in systems in which the ionic conductances show such high levels of variability and makes some important points. In that way, the article does advance the field. For this the authors use computational models of rhythmically active networks previously identified in leech heartbeat CPGs. By building millions of networks made of a pair of reciprocally inhibiting neurons (half-center oscillators, HCOs) that only differ in the values of the maximal conductances of the two cells, the authors examine how difficult it is to disrupt rhythmic activity in these HCOs as each of the 9 maximum conductances that make up these cells is varied over large ranges of values. Major critiques 1) The authors identify ionic currents that the rhythmic activity is sensitive to and ionic currents that it is not (i.e. that the activity is robust to). This study is important as it identifies currents that are likely to be primary targets for neuromodulation in this system and those that the system is either sensitive or robust to. However, it does not, in my opinion, go nearly far enough in discussing the implications of these discoveries. In fact, I find the discussion of this manuscript to be mostly a long summary summary of the results with little other discussion of the implications of their study. Questions that one would like to see addressed, for example, might be: are the currents identified in this study as most likely to be modulated actually modulated in the biological system that inspired this work? Ih modulation in cortex is mentioned, but is the system a reasonable model of cortical networks where this occurs? Are the currents that the authors identify here as those that the system is robust to the ones that the biological system allows variations of? Since this study is not particularly novel in its approach (but certainly much more comprehensive than previous ones), it is not entirely clear what the fundamental message is other than assigning approximate scores of robustness of the system to each ionic conductance modified, and stating that IH is a good target for modulation (and this is a valid statement only if modulation is acceptable as long as loss of rhythmic activity is not the result). However, modulation may be necessary to switch activity modes. 2) Although the manuscript is pitched as a study of robustness in the context of ionic current correlated expression (which was more thoroughly address in a previous paper from this group), the authors begin their description of the system with a figure that describes a (non-linear) correlation between 4 parameters in the system (Fig. 1) but never return to address any possible significance of this. Also, the issue of correlations seems to be forgotten after that, while I would have wished to read something about the existence or lack of existence (unless I missed it) of correlations within the subfamilies they identify. 3) The significance statement really isn't a significance statement but another summary. 4) Additionally, this manuscript appears to be carelessly written and that makes it sometimes difficult and annoying to read: there are many typos and grammatical or syntactical errors that are too numerous to list here, but that should be heavily revised; another example is the presence of a figure in the first page of the manuscript (after the title page) that has no number, no description and is not referred to in the text anywhere; yet another example is the absence of the references to Calabrese, 1997 and Talebi &amp; Baker, 2012, in the bibliography. Other confusing/unclear aspects of the manuscript are listed below. Minor critiques 1) Abbreviations in the abstract appear without explanation (e.g. h in line 24, P in line 25) 2) Line 50: Talebi &amp; Baker, 2012 reference is missing 3) Line 86: compartment should be "cell" really 4) Lines 143-145 and also legend in Fig. 8 (and panels B and C in that figure). This "mapping" of Eleak values to a % is confusing and completely unnecessary. In fact, you don't do that in Fig. 1. Why not move the Eleak points to the right side of each panel and add proper membrane potential labels to the right axis? 5) Line 163. Actually spiking frequency should be number of spike intervals (or spikes-1) divided by burst duration. 6) Line 288-289. The definition of continuous (non-interrupted) families is unclear to me. Here they are described as "each member has a unique value of g (that defines it), and these gs form a continuous uninterrupted sequence." I initially thought that uninterrupted families would be cases were families are missing for intermediate values of the defining conductance within the full 0-175% conductance range (e.g. the case of GCaS=[25,150] in Fig. 4). But "interrupted" appears to really mean a smaller range than the tested range (i.e. truncated). Still, it seems strange that for a given conductance only the families with the most members in it have uninterrupted families (Figs. 3 and 4). I guess that I both do not understand the definition well enough, and that the implications are also not clear. In fact, I find subsections starting in line 312 on "sequence break down" current by current tedious and not terribly informative. Perhaps a better description, ideally in some clever graphical form, and later discussion of the underlying implications would be more interesting. 7) Lines 318-334. This section is very confusing to me. There are statements that are simply not consistent with what the referred figure (Fig. 3) shows. For example, in line 328-329 it is said that "as the sequences' ending gh values were increasing ... the number of continuous families decreased and the number of interrupted families increased." What I see across columns (for any one row except the 3rd) that the continuous families decrease but always increase again at the highest ending gh (i.e. they are not monotonic). Also, it would be much easier to follow the description of numbers of families as gs vary if these numbers were actually shown on the subplots. I would suggest that in both Figs 3 and 4 the bracketed conductance values [g_start,g_end] were replaced with the # of families and that the entire graph was given labels at the margins to indicate the starting (vertical dimension) and ending g (horizontal dimension). 8) Lines 331-333. "In conclusion, the sequences broke down at low starting gh, but not at high starting gh (175%, 150%) where we found the most continuous families". That is also not what I see. In fact, at the limit of the smallest range of conductances (first subpanel in each row) is where we find most continuous families (indeed, all are continuous). 9) Line 386. The title does not reflect the text that follows. This and the following section (line 401 should be collapsed into one. 10) Section starting at line 401. This refers to Fig. 5, which I also find extremely confusing. The y-axes are labeled "Nr of missing members" but each plot has a header that also refers to missing members, yet these are 2 orders of magnitude different, and most certainly do not refer to the same thing. Then, what is "one missing member" or "7 missing members"? The text talks abot families with x members and not about families with x missing members like the figure describes. 11) Line 602. The conductance should be GsynS instead of GsysG, right? 12) Lines 618-634. This seems to me that should be in Methods and seems rather a trivial fitting and derivation procedure. What am I missing? Also, why use a 5th order polynomial for the fits when the curves look like simple exponentials? 13) Line 633. The threshold values 2.5 and 3 mentioned here appear to be slope values. Yet I can't see where a slope of 2 comes from. Also how can the low sensitivity group have a higher slope than the high sensitivity one? 14) The description in the text of Fig. 8 is again quite confusing. The figure shows panels for 8 member families (B) and 4 member families (C). First, the y-axes should be labeled. Second, the text instead describes numbers of families for 6-8 members, 3-5 members, less than 7, etc., which cross the borders of what the figures show and are in general not consistent with the figure's data. 15) Lines 704 and 706. The use of the description that conductances "affect each other" is not appropriate here. They are really not affecting each other. They are affecting activity, or they are related (or correlated?) to each other, but they do not affect each other. 16) Line 707. gK2 and gP are said to compensate for each other. This does not seem obvious to me as both gK2 and gP change non-monotonically, and thus direct relationships are not obvious. Are there any correlated relationships for any of these sensitivity subgroups perhaps? If they compensate for each other, I would expect to see a positive (linear or non-linear) correlation. Is that the case? 17) Lines 739-740. The lack of correlations mentioned here refers to the entire dataset, correct? Again I wonder if there may be any correlations (linear or not) between currents in each of the sensitivity subsets. 18) Line 787. "out of the physiological range" seems to me better than "out of the animal range". 19) Line 880. "Eleak has the same role as K2". I can't see this. An increase in Eleak (current becomes increasingly inward) is compensated for by an increase in K2 (outward current increases). If anything, they have opposite roles. 20) Line 890. "Mediums"? 21) Line 891. What is w.r.t.? 22) Lines 916-917. I like this conclusion. It is intuitively right but still a nice and clear point to make. 23) Line 927: Calabrese 1977 reference is missing 24) Line 1031. "All subpanels" Do you mean panels or bins? 25) Line 1034. Why "Circuit break"? What breaks here is the existence of families with certain member size, not the circuits. 26) Legend Fig. 8. It would be nice to show a scale bar for the circle diameters. I am not sure who is scaled x5 and who isn't. 27) Table 1. Top row of numbers should be labeled "# of members" or something like that. 28) Line 1079. "with all members having..." Do you mean members or families? 29) Fig. 6. 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==== Front eNeuroeNeuroeneuroeneuroeNeuroeNeuro2373-2822Society for Neuroscience 10.1523/ENEURO.0113-16.2016eN-NWR-0113-163New ResearchDisorders of the Nervous SystemGlucocorticoids Mediate Short-Term High-Fat Diet Induction of Neuroinflammatory Priming, the NLRP3 Inflammasome, and the Danger Signal HMGB1 High-Fat Diet Primes Neuroinflammation via CORTSobesky Julia L. D’Angelo Heather M. http://orcid.org/0000-0003-2690-7738Weber Michael D. Anderson Nathan D. http://orcid.org/0000-0001-8613-6897Frank Matthew G. Watkins Linda R. Maier Steven F. http://orcid.org/0000-0001-7224-4109Barrientos Ruth M. Department of Psychology and Neuroscience, and the Center for Neuroscience, University of Colorado Boulder, Boulder, Colorado 80309-0345The authors declare no competing financial interests. Author contributions: J.L.S., L.R.W., S.F.M., and R.M.B. designed research; J.L.S., H.M.D., M.D.W., N.D.A., M.G.F., and R.M.B. performed research; J.L.S. and R.M.B. analyzed data; J.L.S., M.G.F., S.F.M., and R.M.B. wrote the paper. Correspondence should be addressed to Ruth M. Barrientos, Department of Psychology and Neuroscience, and Center for Neuroscience, Campus Box 345, University of Colorado Boulder, Boulder, CO 80309-0345. E-mail: ruth.barrientos@colorado.edu.24 8 2016 30 8 2016 Jul-Aug 2016 3 4 ENEURO.0113-16.20169 5 2016 11 8 2016 17 8 2016 Copyright © 2016 Sobesky et al.2016Sobesky et al.This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.Abstract The impact of the foods we eat on metabolism and cardiac physiology has been studied for decades, yet less is known about the effects of foods on the CNS, or the behavioral manifestations that may result from these effects. Previous studies have shown that long-term consumption of high-fat foods leading to diet-induced obesity sensitizes the inflammatory response of the brain to subsequent challenging stimuli, causing deficits in the formation of long-term memories. The new findings reported here demonstrate that short-term consumption of a high-fat diet (HFD) produces the same outcomes, thus allowing the examination of mechanisms involved in this process long before obesity and associated comorbidities occur. Rats fed an HFD for 3 d exhibited increases in corticosterone, the inflammasome-associated protein NLRP3 (nod-like receptor protein 3), and the endogenous danger signal HMGB1 (high-mobility group box 1) in the hippocampus. A low-dose (10 μg/kg) lipopolysaccharide (LPS) immune challenge potentiated the neuroinflammatory response in the hippocampus of rats fed the HFD, and caused a deficit in the formation of long-term memory, effects not observed in rats fed regular chow. The blockade of corticosterone action with the glucocorticoid receptor antagonist mifepristone prevented the NLRP3 and HMGB1 increases in unchallenged animals, normalized the proinflammatory response to LPS, and prevented the memory impairment. These data suggest that short-term HFD consumption increases vulnerability to memory disruptions caused by an immune challenge by upregulating important neuroinflammatory priming and danger signals in the hippocampus, and that these effects are mediated by increases in hippocampal corticosterone. : danger-associated molecular patternshippocampusneuroimmunologyneuroinflammationneuroinflammatory primingshort-term high-fat diet cover-dateJuly/August 2016 ==== Body Significance Statement American adults consume diets that are higher in saturated fats and/or refined sugars [i.e., a high-fat diet (HFD)] than ever before, and these diets have been associated with significant cognitive deficits. This study aims to examine the mechanisms that underlie this relationship. Here, we demonstrate that short-term HFD consumption elevates the neuroinflammatory priming signals corticosterone, NLRP3 (nod-like receptor protein 3), and HMGB1 (high-mobility group box 1) in the hippocampus. When followed by an immune challenge, HFD produced a potentiated proinflammatory response and memory deficit. Inhibiting corticosterone signaling during HFD consumption prevented the priming, the potentiated neuroinflammation, and the memory impairment. Together, these data suggest that the glucocorticoid receptor is an important target for attenuating the neuroinflammatory effects associated with HFDs. Introduction American adults consume diets higher in saturated fats and/or refined sugars [i.e., a high-fat diet (HFD)] than ever before (Beilharz et al., 2015; Guyenet and Carlson, 2015), and these diets have been associated with cognitive deficits in humans and rodents (Eskelinen et al., 2008; Ross et al., 2009; Kanoski et al., 2010; Solfrizzi et al., 2010; Heyward et al., 2012). It has been proposed that HFD-associated neuroinflammation may be a mechanism that underlies cognitive deficits in overweight and obese individuals (Beilharz et al., 2014, 2015; Marissal-Arvy et al., 2014; Miller and Spencer, 2014; Sobesky et al., 2014; Spagnuolo et al., 2015; Stranahan, 2015), and this is a plausible proposal given the large body of literature implicating neuroinflammation as a cause of memory declines (Rachal Pugh et al., 2001; Yirmiya and Goshen, 2011; Barrientos et al., 2015b). However, because there are numerous comorbidities associated with obesity, studies directed at understanding the underlying mechanisms of obesity-induced memory declines can be easily confounded (Guh et al., 2009). A growing literature has demonstrated that HFD consumption can cause memory impairments in humans and rodents in as little as 3-5 d, long before frank signs of obesity appear (Kanoski and Davidson, 2010; Holloway et al., 2011; Beilharz et al., 2014, 2016). These findings support the notion that the macronutrient profile of foods may be as important for cognitive health as is obesity status or total energy intake. Moreover, they provide a context in which inflammatory mechanisms could be examined without confounding by other comorbid conditions. It is well known that HFD consumption induces inflammation in peripheral tissues through active secretion of adipokines by adipocytes (Coppack, 2001; Xu et al., 2002; Cano et al., 2009). Importantly, peripheral inflammation is capable of signaling the brain, via various routes of communication (Konsman et al., 2002), leading to de novo production of cytokines in the brain that can then alter behavior (Layé et al., 1994). Saturated free fatty acids have been shown to directly pass into the hypothalamus, where they activate toll-like receptor 4 (TLR4), producing a proinflammatory response there and causing behavioral modifications (Milanski et al., 2009; Maric et al., 2014). However, for reasons that remain unclear, free fatty acids do not pass directly into the hippocampus (Milanski et al., 2009). While HFD consumption alone has been shown to induce proinflammatory gene expression in various brain regions, including hippocampus (Hansen et al., 1998; Thaler et al., 2012; Beilharz et al., 2014, 2016), it should be noted that these studies specifically included a substantial sugar component in their high-fat diet regimen, which may be a critical factor. A larger body of literature (from studies using saturated HFDs that do not have high sugar contents, such as the present one), suggests that hippocampal cells are primed by HFD consumption, and that a secondary challenge must occur before neuroinflammatory cytokines are detected or memory impairments are observed (Boitard et al., 2014; Cai et al., 2014; Knight et al., 2014; Sobesky et al., 2014). These studies have shown that HFD consumption alone does not produce elevated cytokine expression in the brain, but does elevate microglial markers of activation. Moreover, short-term HFD consumption sensitizes the hypothalamus and hippocampus to over-respond to an immune challenge, such as to lipopolysaccharide (LPS), and, in turn, produces functional impairments mediated by those brain regions. However, little is known about the mechanisms that mediate this short-term HFD-induced priming effect, and thus is the focus of the present study. Here, we explored the novel idea that short-term consumption of HFD would induce an elevation in hippocampal corticosterone (CORT), which would in turn prime the hippocampus to amplify its inflammatory response to a mild inflammatory challenge, finally resulting in impairments in memory consolidation. Despite its classic role as an immunosuppressant, there is a growing literature demonstrating that CORT can prime hippocampal microglia (Frank et al., 2010a, 2014; Barrientos et al., 2015a) and potentiate the neuroinflammatory response to a subsequent inflammatory challenge (Frank et al., 2010a; Munhoz et al., 2010; Hains et al., 2011; Loram et al., 2011). Here, we demonstrate that short-term HFD consumption produces CORT elevations in the hippocampus, increases the expression of neuroinflammatory priming signals, potentiates the proinflammatory response to LPS, and causes a deficit in forming long-term memory. To test that this HFD-induced CORT increase is a critical mechanism in this cascade, we administered the GR antagonist mifepristone at the time of HFD intake. If this treatment would prevent an HFD-plus-LPS-induced potentiated neuroinflammatory response and memory impairment, this would provide new insight into the mechanisms underlying the impact of HFD consumption on cognitive declines. Materials and Methods Animals Male Wistar rats (Harlan Laboratories) were used. All animals were ∼3 months of age and weighed between 275 and 375 g at the time of arrival. Following arrival, animals were allowed to acclimate to the facility for at least 7 d prior to diet modifications. Subjects were pair housed in standard large cages [52 × 30 × 21 cm (length [L] × width [W] × height [H])] with food and water administered ad libitum. The colony room was maintained at 22°C on a 12 h light/dark cycle (lights on at 7:00 A.M.). All experiments were conducted in accordance with protocols approved by the University of Colorado Animal Care and Use Committee. Diet Animals were randomly assigned to one of three diets. One group (the regular group) continued consuming regular chow [catalog #TD.8640, Envigo; energy density, 3.0 kcal/g; 29% calories from protein; 54% from carbohydrates (no sweetener added), and 17% from fat (0.9% saturated, 1.2% monounsaturated, 2.7% polyunsaturated)]. A second group (the control group) was fed a control diet matched to the regular diet in macronutrients [catalog #TD.2029x, Envigo; energy density of 3.1 kcal/g; 24% calories from protein, 60% from carbohydrates (no sweetener added), and 16% from fat]. This group was included to control for the effects that may be present due to switching to a novel diet for 3 d. A third group (the HFD group) was fed an adjusted-calorie high-fat diet [catalog #TD.06414, Envigo; energy density of 5.1 kcal/g; 18.4% calories from protein, 21.3% from carbohydrates (90 g/kg sucrose, 160 g/kg maltodextrin), and 60.3% from fat (37% saturated, 47% monounsaturated, 16% polyunsaturated)]. Since there were no differences between the regular and control groups with regard to the data examined in experiment 1 (CORT levels, cytokine levels, or expression of the priming genes; see Results), for the remainder of the study only the regular chow group was compared with the HFD group. Glucose, insulin, and leptin measurement Glucose (2 h fasting) was measured in whole blood using a commercial glucometer (Contour, Bayer). Plasma insulin was measured using a commercial ELISA kit for rat insulin from Abnova with a detection range of 0–140 μl/U/mL, and a sensitivity of <5 μl/U/mL. Plasma leptin was measured using a commercial ELISA kit for rat leptin from Millipore with an intra-assay variability of <3%. The detection limit of the assay is 0.08 ng/ml. LPS injections LPS (Escherichia coli, serotype 0111:B4; Sigma-Aldrich), a potent TLR4 agonist, was used to induce an inflammatory response. LPS was administered intraperitoneally at a dose of 10 μg/kg, or saline served as the vehicle control. The dose of LPS was selected as it has shown to induce by itself only a subthreshold proinflammatory response in the hippocampus (Johnson et al., 2002). Mifepristone injections To block the signaling activity of CORT, the glucocorticoid receptor (GR) antagonist mifespristone (Sigma-Aldrich) was dissolved in 100% propylene glycol and administered subcutaneously at a dose of 50 mg/kg/ml. Propylene glycol (100%) was used as the vehicle control. Tissue collection Rats were injected intraperitoneally with a lethal dose of sodium pentobarbital until unresponsive and transcardially perfused with ice-cold 0.9% saline for 3 min. Following saline perfusion, brains were extracted from skull and placed on a clean glass dish inverted on ice, wherein hippocampus was dissected, placed into prelabeled 1.5 ml Eppendorf tubes, and flash frozen in liquid nitrogen. All samples were stored at −80° C until further processed. PCR RNA isolation from whole tissue samples RNA was isolated from whole tissue using a standard method of phenol-chloroform extraction (Chomczynski and Sacchi, 1987). Briefly, tissue samples were rapidly homogenized in 1 ml of TRIzol reagent (Invitrogen). Samples were homogenized using a Tissue Tearor homogenizer. After incubation at room temperature for 5 min, chloroform was added to the supernatant, vortexed for 2 min, and centrifuged (at 4°C, 12,000 × g, for 15 min) to achieve phase separation of nucleic acid. Isopropyl alcohol (0.5 volume of the TRIzol volume) was added to precipitate nucleic acid. Samples were briefly vortexed and incubated at room temperature for 10 min followed by centrifugation (at 4°C, 12,000 × g) for 10 min. Nucleic acid precipitate was washed in 75% ethanol (1 ml) and centrifuged (at 4°C, 7500 × g, for 5 min). The ethanol was gently poured out, the RNA pellet was allowed to dry, and resuspension was performed with 40 μl of nuclease-free water (Ambian). cDNA synthesis of whole tissue-derived RNA Total RNA was reverse transcribed into cDNA using the SuperScript II First Strand Synthesis System for RT-PCR (Invitrogen). A standard amount of sample was added to nucleic acid-free water to equate 11 μl. This RNA was incubated for 5 min at 65°C in a total reaction volume of 13 μl containing random hexamer primers (5 ng/μl) and deoxynucleotides (dNTPs; 1 mm). Samples were chilled on ice for at least 1 min. A cDNA synthesis buffer (6 μl) was added to the reaction and incubated at 20°C for 2 min. Reverse transcriptase (1 μl; 200 units of SuperScript II) was added to the reaction and incubated at 25°C for 10 min followed by 42°C for 50 min. Reaction was terminated by heating to 70°C for 15 min. Primer specifications cDNA sequences were obtained from the GenBank at the National Center for Biotechnology Information [NCBI (www.ncbi.nlm.nih.gov)]. Primer sequences were designed using the Eurofins MWG Operon Oligo Analysis and Plotting Tool (http://www.operon.com/technical/toolkit.aspx) and tested for sequence specificity using the Basic Local Alignment Search Tool at NCBI (Altschul et al., 1997). Primers were obtained from Invitrogen, and primer specificity was verified by melt curve analysis. Gene function and primer sequences of the genes of interest are presented in Table 1. Table 1: PCR primer description and sequences Gene Primer sequence: 5' → 3' Function β-Actin F: TTCCTTCCTGGGTATGGAAT R: GAGGAGCAATGATCTTGATC Cytoskeletal protein (housekeeping gene) IL-1β F: CCTTGTGCAAGTGTCTGAAG R: GGGCTTGGAAGCAATCCTTA Proinflammatory cytokine IL-6 F: AGAAAAGAGTTGTGCAATGGCA R: GGCAAATTTCCTGGTTATATCC Proinflammatory cytokine IκBα F: CACCAACTACAACGGCCACA R: GCTCCTGAGCGTTGACATCA Marker for transcription factor NF-κB activity CD11b F: CTGGGAGATGTGAATGGAG R: ACTGATGCTGGCTACTGATG Macrophage/microglial antigen marker HMGB1 F: GAGGTGGAAGACCATGTCTG R: AAGAAGAAGGCCGAAGGAGG Endogenous danger signal NLRP3 F: AGAAGCTGGGGTTGGTGAATT R: GTTGTCTAACTCCAGCATCTG Rate limiting protein in NLRP3 inflammasome formation CX3CR1 F: TCAGGACCTCACCATGCCTA R: CGAACGTGAAGACAAGGGAG Microglia-selective chemokine receptor TLR4 F: TCCCTGCATAGAGGTACTTC R: CACACCTGGATAAATCCAGC Pattern recognition receptor CD, cluster of differentiation; F, forward; R, reverse. Quantitative real-time PCR PCR amplification of cDNA was performed using the Quantitect SYBR Green PCR Kit (Qiagen). cDNA (1 μl) was added to a reaction master mix (25 μl) containing 2.5 mm MgCl2, HotStar Taq DNA polymerase, SYBR Green I, dNTPs, fluorescein (10 nm), and gene-specific primers (500 nm each of forward and reverse primer). For each experimental sample, triplicate reactions were conducted in 96-well plates (Bio-Rad). PCR cycling conditions consisted of a hot-start activation of HotStart Taq DNA polymerase (at 94°C, for 15 min) and 40 cycles of denaturation (at 95°C, for 15 s), annealing (at 55–58°C, for 30 s), and extension (at 72°C, for 30 s). A melt curve analysis was conducted to assess the uniformity of product formation, primer dimmer formation, and the amplification of nonspecific products. The PCR product was denatured (at 95°C, for 1 min) and annealed (at 55°C, for 1 min) prior to melt curve analysis, which consisted of incrementally increasing reaction temperature (0.5°C/10 s) from 55°C to 95°C. Real-time detection and relative quantification of PCR product The formation of PCR product was monitored in real time using the MyiQ Single-Color Real-Time PCR Detection System (Bio-Rad). The Fluorescence of SYBR Green I was captured at 72°C. The threshold for the detection of PCR product above background was set at 10× the SD of the mean background fluorescence for all reactions. Background fluorescence was determined from cycle 1 to five cycles prior to the exponential amplification of product, and subtracted from the raw fluorescence of each reaction/cycle. The threshold for the detection of PCR product fell within the exponential phase of amplification for each reaction. The threshold cycle (CT; number of cycles to reach the threshold of detection) was determined for each reaction. Relative quantitation of gene expression Relative gene expression was determined using the 2-ΔΔCT method (Livak and Schmittgen, 2001). The mean CT of triplicate measures was computed for each sample. Sample mean CT of the internal control (β-actin) was subtracted from the sample mean CT of the respective gene of interest (ΔCT). The sample with the absolute highest mean ΔCT was selected as a calibrator, and the mean ΔCT of each experimental sample (ΔΔCT) was subtracted from this value. 2ΔΔCT yielded a fold change in gene expression of the gene of interest normalized to the internal control gene expression and relative to the calibrator sample. Relative gene expression for each sample was calculated, and data are presented as the percentage of regular diet values. Hippocampus processing for ELISA and Western blot In preparation for assays, tissue samples were sonicated in 0.3 ml sonication buffer (Invitrogen). Tissues were then mechanically homogenized using an ultrasonic cell disrupter (Thermo Fisher Scientific). Sonication consisted of 20 s of cell disruption at 52% amplitude. Sonicated samples were centrifuged (at 4°C, 10,000 × g, for 10 min), and supernatants were removed and stored at 4°C until ELISA or Western blots were performed. Bradford protein assays determined the total protein concentrations of sonicated tissue. Interleukin-1β and CORT Levels of interleukin (IL)-1β protein and CORT were determined using commercially available rat-specific ELISA for IL-1β (R&D Systems) and corticosterone kits (Enzo Life Sciences). The assays were performed according to the manufacturer instructions. IL-1β was determined and normalized to total protein. Western blot Samples were heated to 75°C for 10 min then loaded into a standard polyacrylamide Bis-Tris gel (Invitrogen). SDS-PAGE was performed in MOPS running buffer (Invitrogen) at 175 V for 75 min. Protein was transferred onto a nitrocellulose membrane using the iBlot dry transfer system (Invitrogen). The membrane was blocked with Odyssey blocking buffer (LI-COR) for 1 h and incubated with a primary antibody in blocking buffer overnight at 4°C. The following day, the membrane was washed in 1× PBS containing Tween 20 (0.1%) and then incubated in blocking buffer containing either goat anti-rabbit or goat anti-mouse (LI-COR) IRDye 800CW secondary antibody at a concentration of 1:10,000 for 1 h at room temperature. Primary antibodies included the following: mouse anti-rat high-mobility group box 1 (HMGB1) monoclonal antibody (1:4000; Abcam); rabbit anti-rat nod-like receptor protein 3 (NLRP3) monoclonal antibody (1:1000; Millipore); and mouse anti-rat β-actin (1:200,000; Sigma-Aldrich). Protein expression was quantified using an Odyssey Infrared Imager (LI-COR) and normalized to the housekeeping protein value for that sample, and data are presented as the percentage of the within-blot regular diet control samples. Context pre-exposure fear conditioning A context pre-exposure fear-conditioning paradigm was used to measure memory performance, as this paradigm has been shown to be highly sensitive to disruptions to the hippocampus (Rudy et al., 2002; Matus-Amat et al., 2004). Contextual fear conditioning depends on the following two processes: the construction of a conjunctive representation of the conditioning context; and the association of that representation with shock. Acquiring a conjunctive representation depends on an intact hippocampus. Because in this paradigm the two processes are engaged independently (on separate days), it allows more accurate detection of impairments selective to the hippocampus (Matus-Amat et al., 2004). The conditioning context was one of two identical Igloo ice chests [54 × 30 × 27 cm (L × W × H)] with white interiors. A fan and an activated 24 V DC light bulb were mounted on the ceiling of each chest. The conditioning chambers [26 × 21 × 24 cm (L × W × H)], placed inside each chest, were made of clear plastic and had window screen tops. Chambers were cleaned with water before each animal was conditioned or tested. Rats were taken two at a time from their home cage and transported to the conditioning context in a black ice bucket with the lid on so that the rats could not see where they were being taken. Rats were placed in the context and allowed to freely explore, and then they were transported back to their home cage, where they remained for ∼40 s before the next exposure. This procedure was repeated six times. Rats remained in the conditioning context for 5 min on the first exposure and for 40 s on the five subsequent exposures. The rats were transported in the black bucket each time that they were returned to their home cage, but with the lid off, so that they could discern whether they were headed to the context or to their home cage. The purpose of these multiple exposures was to establish the features of the black bucket as retrieval cues that could activate the representation of the context. Immediately after the last exposure, rats received an injection of saline or LPS (as described earlier). Seventy-two hours later, each animal was taken from its home cage and transported to the conditioning context in the black bucket again. There, they immediately received one 2 s footshock (1.5 mA delivered through a removable floor of stainless steel rods 1.5 mm in diameter, spaced 1.2 cm center to center). Each rod was wired to a shock generator and scrambler (Coulbourn Instruments). They were then quickly taken out of the chamber and transported back to their home cage. The time that the rats spent in the conditioning context never exceeded 5 s. A day later, the rats were placed back in the conditioning context, and memory was assessed by observing freezing behavior over a 6 min period. Two hours later, rats were placed in a novel, neutral, control context and observed for 6 min to detect any generalized fear or anxiety. After placing the rat into the chamber, every 10 s each rat was judged as either freezing or active at the instant the sample was taken. Freezing, the dominant defensive fear response of the rat, is a complete suppression of behavior that is accompanied by immobility, shallow breathing, and a variety of other autonomic changes, including an increase in heart rate and pilo-erection (Kim and Fanselow, 1992). Freezing in these experiments was defined as the absence of all visible movement, except for respiration. Scoring was performed by observers blind to experimental treatment, and inter-rater reliability exceeded 97% for all experiments. Data analysis All data are presented as the mean ± SEM. Statistical analyses were computed using GraphPad Prism version 6 and StatView version 5. All experiments had six to eight rats per group. One-way ANOVAs were used for the analyses in experiment 1. Two-way ANOVAs were run for the analyses in experiment 2. Three-way ANOVAs were run for the analyses in experiments 3 and 4. In the case of a significant interaction, post hoc tests were run. The threshold for significance was set at α = 0.05. Results Short-term HFD consumption increases body mass To determine whether short-term consumption of an HFD would significantly increase body mass, animals from the three diet groups were weighed on the day of diet switch (day 0) and every day for 3 d. Body weight averages for all three groups at the start of the experiment were not different (p = 0.98; Fig. 1, inset; Table 2). A repeated-measures ANOVA was run to analyze the percentage of weight gained among the three diets across the 3 d. A significant interaction (diet × time) effect (F(4,42) = 8.49, p < 0.0001; Fig. 1a) led to post hoc analyses revealing a significant increase in the HFD group compared with the regular group on day 2 (p < 0.01). On day 3, the HFD group gained more than the regular group (p < 0.0001) and the control group (p < 0.05). In addition, the control group gained significantly more than the regular group (p < 0.01). Figure 1. Body mass and metabolic changes. a, Daily percentage change in body mass over the 3 d in which rats had free access to the regular chow diet, control diet, and the HFD. Inset, Body weights on day 0 of rats assigned to the three groups. b–d, Levels of whole-blood glucose (b), plasma insulin (c), and plasma leptin (d) in rats fed a regular chow diet, a control diet, and an HFD. Data are reported as the mean ± SEM. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. Table 2: Statistics Figure Data Structure Type of test p Values 1 (inset) Normal distribution One-way ANOVA 0.98 1a Normal distribution Two-way repeated-measures ANOVA (time × diet) Tukey’s post hoc test Day 1 Regular vs control Regular vs HFD Control vs HFD Day 2 Regular vs control Regular vs HFD Control vs HFD Day 3 Regular vs control Regular vs HFD Control vs HFD <0.0001 95% CI −2.022 to 0.077 −1.518 to 0.581 −0.546 to 1.553 −1.887 to 0.211 −2.513 to −0.414 −1.675 to 0.424 −2.632 to −0.533 −3.762 to −1.663 1b Normal distribution One-way ANOVA 0.31 1c Normal distribution One-way ANOVA 0.93 1d Normal distribution One-way ANOVA Tukey’s post hoc test Regular vs control Regular vs HFD Control vs HFD <0.0001 95% CI −5.787 to −0.827 −8.047 to −3.086 −4.740 to −0.221 2 Normal distribution One-way ANOVA Fisher’s LSD post hoc test Regular vs control Regular vs HFD Control vs HFD 0.028 95% CI −0.378 to 0.180 −0.658 to −0.100 −0.559 to −0.001 3a Normal distribution One-way ANOVA 0.194 3b Normal distribution One-way ANOVA 0.131 3c Normal distribution One-way ANOVA Fisher’s LSD post hoc test Regular vs control Regular vs HFD Control vs HFD 0.026 95% CI −29.17 to 9.432 −46.26 to −7.658 −35.74 to 1.556 3d Normal distribution One-way ANOVA Fisher’s LSD post hoc test Regular vs control Regular vs HFD Control vs HFD 0.049 95% CI −16.12 to 16.28 −34.89 to −1.426 −34.44 to −2.038 3e Normal distribution One-way ANOVA Fisher’s LSD post hoc test Regular vs control Regular vs HFD Control vs HFD 0.026 95% CI −55.03 to 47.63 −104.2 to −1.550 −98.77 to 0.406 3f Normal distribution One-way ANOVA Fisher’s LSD post hoc test Regular vs control Regular vs HFD Control vs HFD 0.017 95% CI −21.42 to 15.11 −45.09 to −7.351 −41.33 to −4.796 4a Normal distribution Two-way ANOVA Diet Challenge Diet × challenge Scheffé’s post hoc test Regular:saline vs regular:LPS Regular:saline vs HFD:saline Regular:LPS vs HFD:LPS HFD:saline vs HFD:LPS 0.002 <0.0001 0.040 0.008 0.071 0.010 0.0003 4b Normal distribution Two-way ANOVA diet challenge diet × challenge Scheffé’s post hoc test Regular:saline vs regular:LPS Regular:saline vs HFD:saline Regular:LPS vs HFD:LPS HFD:saline vs HFD:LPS 0.040 <0.0001 0.031 0.0014 0.778 0.042 0.0007 4c Normal distribution Two-way ANOVA diet challenge diet × challenge Scheffé’s post hoc test Regular:saline vs regular:LPS Regular:saline vs HFD:saline Regular:LPS vs HFD:LPS HFD:saline vs HFD:LPS 0.003 <0.0001 0.015 0.0003 0.091 0.013 0.0008 5a Normal distribution Three-way ANOVA Diet Treatment Challenge Diet × treatment Diet × challenge Treatment × challenge Diet × treatment × challenge Scheffé’s post hoc test Vehicle:saline:regular vs vehicle:saline:HFD Vehicle:LPS:regular vs vehicle:LPS:HFD Mife:saline:regular vs Mife:saline:HFD Mife:LPS:regular vs Mife:LPS:HFD Regular:saline:vehicle vs regular:saline:Mife Regular:LPS:vehicle vs regular:LPS:Mife HFD:saline:vehicle vs HFD:saline:Mife HFD:LPS:vehicle vs HFD:LPS:Mife Regular:vehicle:saline vs regular:vehicle:LPS Regular:Mife:saline vs regular:Mife:LPS HFD:vehicle:saline vs HFD:vehicle:LPS HFD:Mife:saline vs HFD:Mife:LPS 0.0002 0.0053 <0.0001 0.105 0.038 <0.0001 0.033 0.083 0.0005 0.235 0.531 0.100 0.152 0.126 0.003 <0.0001 0.346 <0.0001 0.323 5b Normal distribution Three-way ANOVA Diet Treatment Challenge Diet × treatment Diet × challenge Treatment × challenge Diet × treatment × challenge Scheffé’s post hoc test Vehicle:saline:regular vs vehicle:saline:HFD Vehicle:LPS:regular vs vehicle:LPS:HFD Mife:saline:regular vs Mife:saline:HFD Mife:LPS:regular vs Mife:LPS:HFD Regular:saline:vehicle vs regular:saline:Mife Regular:LPS:vehicle vs regular:LPS:Mife HFD:saline:vehicle vs HFD:saline:Mife HFD:LPS:vehicle vs HFD:LPS:Mife Regular:vehicle:saline vs regular:vehicle:LPS Regular:Mife:saline vs regular:Mife:LPS HFD:vehicle:saline vs HFD:vehicle:LPS HFD:Mife:saline vs HFD:Mife:LPS 0.572 0.543 <0.0001 0.002 0.211 0.171 0.003 0.173 0.011 0.364 0.133 0.088 0.115 0.500 0.014 <0.0001 0.003 <0.0001 0.004 5c Normal distribution Three-way ANOVA Diet Treatment Challenge Diet × treatment Diet × challenge Treatment × challenge Diet × treatment × challenge Scheffé’s post hoc test Vehicle:saline:regular vs vehicle:saline:HFD Vehicle:LPS:regular vs vehicle:LPS:HFD Mife:saline:regular vs Mife:saline:HFD Mife:LPS:regular vs Mife:LPS:HFD Regular:saline:vehicle vs regular:saline:Mife Regular:LPS:vehicle vs regular:LPS:Mife HFD:saline:vehicle vs HFD:saline:Mife HFD:LPS:vehicle vs HFD:LPS:Mife Regular:vehicle:saline vs regular:vehicle:LPS Regular:Mife:saline vs regular:Mife:LPS HFD:vehicle:saline vs HFD:vehicle:LPS HFD:Mife:saline vs HFD:Mife:LPS 0.015 0.426 <0.0001 0.0004 0.005 0.237 0.0014 0.946 0.001 0.348 0.589 0.026 0.119 0.078 0.011 0.0005 0.032 <0.0001 0.031 5d Normal distribution Three-way ANOVA Diet Treatment Challenge Diet × treatment Diet × challenge Treatment × challenge Diet × treatment × challenge Scheffé’s post hoc test Vehicle:saline:regular vs vehicle:saline:HFD Vehicle:LPS:regular vs vehicle:LPS:HFD Mife:saline:regular vs Mife:saline:HFD Mife:LPS:regular vs Mife:LPS:HFD Regular:saline:vehicle vs regular:saline:Mife Regular:LPS:vehicle vs regular:LPS:Mife HFD:saline:vehicle vs HFD:saline:Mife HFD:LPS:vehicle vs HFD:LPS:Mife Regular:vehicle:saline vs regular:vehicle:LPS Regular:Mife:saline vs regular:Mife:LPS HFD:vehicle:saline vs HFD:vehicle:LPS HFD:Mife:saline vs HFD:Mife:LPS 0.145 0.043 <0.0001 0.003 0.361 0.173 0.289 0.027 0.063 0.049 0.435 0.075 0.751 0.017 0.027 0.001 0.006 0.005 0.002 5e Normal distribution Three-way ANOVA Diet Treatment Challenge Diet × treatment Diet × challenge Treatment × challenge Diet × treatment × challenge Scheffé’s post hoc test Vehicle:saline:regular vs vehicle:saline:HFD Vehicle:LPS:regular vs vehicle:LPS:HFD Mife:saline:regular vs Mife:saline:HFD Mife:LPS:regular vs Mife:LPS:HFD Regular:saline:vehicle vs regular:saline:Mife Regular:LPS:vehicle vs regular:LPS:Mife HFD:saline:vehicle vs HFD:saline:Mife HFD:LPS:vehicle vs HFD:LPS:Mife Regular:vehicle:saline vs regular:vehicle:LPS Regular:Mife:saline vs regular:Mife:LPS HFD:vehicle:saline vs HFD:vehicle:LPS HFD:Mife:saline vs HFD:Mife:LPS 0.009 0.226 0.01 0.006 0.942 0.044 0.060 0.010 0.027 0.130 0.037 0.145 0.072 0.939 0.021 0.010 0.017 0.091 0.75 5f Normal distribution Three-way ANOVA Diet Treatment Challenge Diet × treatment Diet × challenge Treatment × challenge Diet × treatment × challenge Scheffé’s post hoc test Vehicle:saline:regular vs vehicle:saline:HFD Vehicle:LPS:regular vs vehicle:LPS:HFD Mife:saline:regular vs Mife:saline:HFD Mife:LPS:regular vs Mife:LPS:HFD Regular:saline:vehicle vs regular:saline:Mife Regular:LPS:vehicle vs regular:LPS:Mife HFD:saline:vehicle vs HFD:saline:Mife HFD:LPS:vehicle vs HFD:LPS:Mife Regular:vehicle:saline vs regular:vehicle:LPS Regular:Mife:saline vs regular:Mife:LPS HFD:vehicle:saline vs HFD:vehicle:LPS HFD:Mife:saline vs HFD:Mife:LPS 0.017 0.083 0.061 0.0007 0.269 0.111 0.459 <0.0001 0.136 0.760 0.149 0.074 0.375 0.049 0.0007 0.0001 0.876 0.338 0.535 6a Normal distribution Three-way ANOVA Diet Treatment Challenge Diet × treatment Diet × challenge Treatment × challenge Diet × treatment × challenge Scheffé’s post hoc test Vehicle:saline:regular vs vehicle:saline:HFD Vehicle:LPS:regular vs vehicle:LPS:HFD Mife:saline:regular vs Mife:saline:HFD Mife:LPS:regular vs Mife:LPS:HFD Regular:saline:vehicle vs regular:saline:Mife Regular:LPS:vehicle vs regular:LPS:Mife HFD:saline:vehicle vs HFD:saline:Mife HFD:LPS:vehicle vs HFD:LPS:Mife Regular:vehicle:saline vs regular:vehicle:LPS Regular:Mife:saline vs regular:Mife:LPS HFD:vehicle:saline vs HFD:vehicle:LPS HFD:Mife:saline vs HFD:Mife:LPS 0.908 0.377 0.197 0.177 0.126 0.342 0.035 0.234 0.012 0.772 0.440 0.735 0.456 0.631 0.014 0.476 0.688 0.002 0.904 6b Normal distribution Three-way ANOVA Diet Treatment Challenge Diet × treatment Diet × challenge Treatment × challenge Diet × treatment × challenge 0.154 0.722 0.297 0.157 0.518 0.740 0.051 Mife, Mifepristone. Short-term HFD consumption effects on metabolic measures To determine whether short-term consumption of an HFD would significantly alter metabolic function, glucose, insulin, and leptin were measured in animals from the three diet groups. A one-way ANOVA was run for each measure. Levels of glucose (F(2,15) = 1.29, p = 0.31; Fig. 1b) and insulin (F(2,15) = 075, p = 0.93; Fig. 1c) were not different among the three groups. The leptin level (F(2,15) = 17.19, p = 0.0001; Fig. 1d) was significantly elevated in both the control (p < 0.01) and HFD (p < 0.0001) groups compared with the regular chow group. The control and HFD groups did not differ from each other (p = 0.08). Experiment 1: short-term HFD consumption produces neuroinflammatory priming Following 3 d on their respective diets, rats were taken from their home cage and killed, and whole hippocampal tissue was collected and processed to measure CORT; the IL-1 inflammasome-associated protein NLRP3; the endogenous danger-associated molecular signal HMGB1; the pan-macrophage activation marker cd11bl chemokine (fractalkine) receptor 1 (CX3CR1), which is selectively expressed on microglia; IL-1β; and the pattern recognition receptor TLR4. These analytes were chosen to serve as markers of an inflammatory phenotype. It should be noted that CORT was measured in the hippocampus rather than in the circulation because, although brain levels of CORT usually reflect the levels of CORT in the circulation, incongruencies have been reported (Barrientos et al., 2015a), and since the focus of this study is on the hippocampus, measuring CORT levels specifically in the hippocampus was ideal. Hippocampal CORT levels were significantly higher in rats that were fed the HFD compared with levels in both the regular (p < 0.01) and control (p < 0.05) diet groups (F(2,18) = 4.39, p < 0.05; Fig. 2). CORT levels did not differ between the regular and control groups (p > 0.05). There were no significant differences in IL-1β protein (F(2,23) = 0.42, p > 0.05; Fig. 3a) or gene expression (F(2,21) = 2.24, p > 0.05; Fig. 3b), or in TLR4 gene expression (F(2,15) = 0.26, p = 0.77; not shown) in the hippocampus among the groups. Short-term consumption of an HFD caused significant increases in gene expression of the endogenous danger signal HMGB1 (F(2,20) = 4.41, p < 0.05; Fig. 3c), NLRP3 (F(2,19) = 3.54, p < 0.05; Fig. 3d), the macrophage activation marker CD11b (F(2,20) = 4.42, p < 0.05; Fig. 3e), and the fractalkine receptor CX3CR1, which is selectively expressed on microglia (F(2,19) = 5.12, p < 0.05; Fig. 3f). Figure 2. Hippocampal CORT levels among rats fed a regular chow diet, a control diet, or an HFD. Data are reported as the mean ± SEM. *p < 0.05. Figure 3. a–f, Hippocampal levels of IL-1β protein (a), and mRNA expression of IL-1β (b), HMGB1 (c), NLRP3 (d), cd11b (e), and CX3CR1 (f) of rats fed a regular chow diet, a control diet, or an HFD. Data are reported as the mean ± SEM. All mRNA levels are relative to regular chow diet values. *p < 0.05; **p < 0.01. Experiment 2: short-term HFD consumption potentiates inflammatory response to LPS To evaluate whether short-term HFD consumption would amplify the hippocampal proinflammatory response to a subsequent immune challenge, LPS or saline was administered to rats on the third day of consuming their respective diets, and were killed 2 h later. Hippocampi were collected and processed to measure the expression of the proinflammatory cytokines IL-1β and IL-6. LPS by itself produced increases in hippocampal IL-1b protein, and IL-1 and IL-6 mRNA. Importantly, the consumption of HFD exaggerated these increases to LPS. IL-1β protein levels were potentiated in the hippocampus of the HFD plus LPS group (F(1,27) = 4.64, p < 0.05; Fig. 4a) compared with levels exhibited by the regular plus LPS group (p < 0.01). Similarly, IL-1β (F(1,24) = 5.24, p < 0.05; Fig. 4b) and IL-6 (F(1,23) = 6.90, p < 0.05; Fig. 4c) gene expression were potentiated in the HFD plus LPS group compared with levels exhibited by the regular plus LPS group (p < 0.05). Figure 4. a–c, Hippocampal expression levels of proinflammatory cytokines IL-1β protein (a), IL-1β mRNA (b), and IL-6 mRNA (c) of rats fed a regular chow diet or an HFD 2 h following an injection of peripheral saline or LPS. Data are reported as the mean ± SEM. *p < 0.05; **p < 0.01; ***p < 0.001. Experiment 3: mifepristone attenuates HFD plus LPS-induced potentiated neuroinflammation Glucocorticoids mediate the neuroinflammatory priming that is produced by stress (Frank et al., 2012) and aging (Barrientos et al., 2015a). Thus, given the observation in experiment 1 that 3 d of HFD consumption increases hippocampal levels of CORT and induces a primed neuroinflammatory phenotype, as well as an exaggerated response to subsequent LPS consumption (experiment 2), we explored the hypothesis that increased signaling by CORT during HFD consumption mediates the impact of the HFD consumption on neuroinflammation. To test this hypothesis, we administered peripheral injections of the blood–brain-permeable GR antagonist mifepristone (Schreiber et al., 1983) or vehicle to rats fed a regular chow diet or an HFD. Although the goal was to block GR signaling in hippocampus, peripheral administration was deemed satisfactory, as peripheral mifepristone administration at this dose has previously been demonstrated to be effective in preventing CORT-mediated neuroinflammatory priming within hippocampus (Frank et al., 2012). Injections were given 24 and 48 h after the initiation of diet (half-life of mifepristone, ∼18 h). On the third day of HFD consumption, rats were given an injection of either LPS or a saline vehicle and were killed 2 h later. Hippocampi were collected and processed to measure IL-1β, IL-6, NLRP3, HMGB1, and IκBα [nuclear factor κ light chain enhancer of activated B-cell inhibitor α (a measure of nuclear factor-κB [NF-κB] activation)]. NF-κB is a transcription factor that regulates the transcription of many inflammatory cytokines. Mifepristone treatment effectively reduced the potentiated expression of all of these proinflammatory markers induced by HFD and LPS. Three-way ANOVAs were used to analyze these data. A significant diet (regular vs HFD) × treatment (vehicle vs mifepristone) × challenge (saline vs LPS) interaction effect on IL-1β protein was found (F(1,50) = 4.800, p < 0.05; Fig. 5a). Post hoc tests revealed that within the regular chow group, vehicle plus LPS-treated rats exhibited higher levels of IL-1β protein than vehicle plus saline-treated controls (p < 0.0001). Similarly, within the HFD group, vehicle plus LPS-treated rats exhibited higher levels of IL-1β protein than did vehicle plus saline-treated controls (p < 0.0001). Within the vehicle plus LPS groups, HFD-fed rats exhibited higher levels of IL-1β protein than regular chow-fed controls (p < 0.001), replicating the findings from experiment 2. In support of our hypothesis, we found that within the HFD plus LPS groups, mifepristone treatment produced a significant decrease in IL-1β protein compared with vehicle-treated rats (p < 0.01). Similar results were observed with all of the molecules we examined. Significant interaction effects were observed for IL-1β mRNA (F(1,50) = 9.891, p < 0.01; Fig 5b), IL-6 mRNA (F(1,50) = 11.512, p < 0.01; Fig 5c), IκBα mRNA expression (F(1,51) = 9.794, p < 0.01; Fig 5d), NLRP3 protein expression (F(1,44) = 8.187, p < 0.01; Fig 5e), and HMGB1 protein expression (F(1,46) = 5.23, p < 0.05; Fig 5f). All post hoc significant differences between groups are depicted in the figures. Most notable of these is the significant decrease in expression in the mifepristone-treated rats within the HFD plus LPS groups compared with the vehicle-treated rats (IL-1β, p < 0.05; IL-6, p < 0.05; IκBα, p < 0.05; NLRP3, p < 0.05; HMGB1, p < 0.001). Figure 5. a–f, Hippocampal expression levels of IL-1β protein (a), IL-1β mRNA (b), IL-6 mRNA (c), IκBα mRNA (d), NLRP3 protein (e), and HMGB1 protein (f) 2 h following a saline or LPS injection among rats fed a regular chow diet or an HFD and treated with vehicle or mifepristone. Data are reported as the mean ± SEM relative to regular chow diet values. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. Experiment 4: mifepristone attenuates HFD plus LPS-induced contextual memory impairments In this experiment, two questions were addressed. First, we determined whether short-term HFD intake followed by an immune challenge would impair contextual memory. We also determined the role of CORT signaling in any such impaired memory function. Previous findings have shown that increases in proinflammatory cytokines in the hippocampus produce impairments in hippocampal-dependent memory function (Rachal Pugh et al., 2001; Barrientos et al., 2002). Thus, given that the interaction of short-term HFD intake and LPS challenge produces potentiated levels of hippocampal IL-1, we tested the impact of these challenges on contextual memory function. Moreover, to test the hypothesis that elevations in hippocampal CORT level contribute to this effect, we administered mifepristone, as in the previous experiment, to determine whether this treatment would attenuate any impairments caused by diet and LPS administration. On the third day on their respective diets, rats were pre-exposed to the conditioning context, during which a contextual representation is normally formed (see Procedural details). Immediately following this procedure, rats received either LPS or saline. Three days later, rats were brought back to the conditioning chamber and given a 2 s footshock and taken immediately back to their home cage. The next day, rats were placed back into the conditioning chamber and tested for memory of context fear. LPS did not interfere with the development of context fear memory in rats fed the regular chow diet, nor did mifepristone have any effect. However, 3 d of eating an HFD led LPS potently impairing the development of context fear memory, and this impairment was prevented by mifepristone. A three-way ANOVA was used to analyze these data. A significant diet (regular vs HFD) × treatment (vehicle vs mifepristone) × challenge (saline vs LPS) interaction effect on freezing behavior was found (F(1,42) = 4.742, p < 0.05; Fig. 6b). In support of the first hypothesis, post hoc tests revealed that within the vehicle plus LPS groups, HFD-fed rats froze significantly less than did regular chow-fed controls (p < 0.05). Within the HFD group, vehicle plus LPS-treated rats froze significantly less than did vehicle plus saline-treated controls (p < 0.01). In support of the second hypothesis, within the HFD plus LPS groups, mifepristone treatment produced a significant increase in freezing behavior compared with vehicle-treated rats (p < 0.05). Data examining freezing behavior in the control context produced no main effect of diet, treatment, or challenge (p > 0.05; Fig 6a). There were also no significant interaction effects (p > 0.05). These data demonstrate that rats did not show any generalized fear leading to greater freezing. Figure 6. a, b, Percentage of freezing to the conditioning context (a) or the control (neutral) context (b) among rats fed a regular chow diet or an HFD, treated with vehicle or mifepristone, and challenged with saline or LPS. Data are reported as the mean ± SEM. *p < 0.05; **p < 0.01. Discussion Although rats were fed the HFD for only 3 d, they gained a significant amount of weight over that gained in rats fed the regular and control diets. Interestingly, rats that were fed the control diet also exhibited a significant increase compared with rats fed the regular diet, suggesting that at least a portion of the increased body mass exhibited by the HFD group could be attributed to the novelty of the diet, as the consumption of a novel diet has been shown to induce weight gain after an initial (1 d) period of neophobia (Eckel and Ossenkopp, 1993; Modlinska et al., 2015). Taking this factor into account, the HFD group gained 1% body weight above that of the control diet group. Note that this is only 3-4 g. Nonetheless, these findings are consistent with what others have found after short-term consumption of a high-fat diet (Hansen et al., 1998; Beilharz et al., 2014, 2016; Cai et al., 2014). Glucose and insulin were not at all different among the three diet groups. Leptin levels, however, were elevated in both the control and HFD groups compared with the regular chow group. Interestingly, similar HFD-induced leptin increases were reported in rats that had been fed the same HFD used here for 5 months (Sobesky et al., 2014), suggesting that long-term HFD is not necessary to induce leptin increases. The fact that the control diet produced an increase in leptin, but did not produce increases in corticosterone, HMGB1, NLRP3, cd11b, or CX3CR1 suggests that increased leptin levels alone are not responsible for the primed inflammatory response in the hippocampus. It is not clear why the control diet, which is matched to the regular diet in macronutrients, would produce an increase in leptin, though a possibility is that this increase was triggered by the rapid and short-term novel diet-induced weight increase. Despite the fact that both control-fed and HFD-fed groups demonstrated a body mass increase compared with the regular chow-fed group, only the HFD-fed group exhibited an elevation in hippocampal CORT levels. These data are consistent with other findings showing that short-term HFD consumption increases plasma CORT levels (Tannenbaum et al., 1997). Rats fed the control diet showed no such CORT elevation, eliminating the possibility that a novel diet alone produced this elevation in CORT levels. Classically, the immune-modulatory impacts of CORT have been viewed as primarily anti-inflammatory (De Bosscher and Haegeman, 2009). However, this notion is being updated as prior stress sensitizes proinflammatory responses to subsequent LPS (Johnson et al., 2002; Munhoz et al., 2006; Hains et al., 2011), and the proinflammatory effects of stress have been linked to CORT signaling (Munhoz et al., 2010; Frank et al., 2012). It appears that the timing of rises CORT in levels is important for determining the resulting anti-inflammatory or proinflammatory function, as CORT elevations prior to a secondary challenge increase the response to LPS, but CORT signaling after the inflammatory challenge dampens the response (Frank et al., 2010a). Short-term HFD consumption alone did not produce increases in IL-1β protein or mRNA, confirming what others have found (Beilharz et al., 2014; Boitard et al., 2014; Cai et al., 2014; Sobesky et al., 2014). Perhaps if a substantial sugar component would have been added to the HFD, an elevated inflammatory response would have occurred, as others have reported (Hansen et al., 1998; Thaler et al., 2012; Beilharz et al., 2014, 2016). Short-term HFD consumption did, however, increase expression of the alarmin HMGB1 and the NLRP3 protein. These data are consistent with previous findings showing that levels of these molecules are elevated in response to increases in CORT levels (Busillo et al., 2011; Frank et al., 2014; Weber et al., 2015). HMGB1 is an endogenous danger signal, or danger-associated molecular pattern (DAMP), that can stimulate inflammation through interactions with a number of pattern recognition receptors, such as TLR2 and TLR4 (Yanai et al., 2012), to activate the proinflammatory transcription factor NF-κB (Su et al., 2011). NLRP3 is a structural component of one type of inflammasome, which regulates the cleavage and release of IL-1β through the activation of caspase-1 (Khare et al., 2010; Schroder and Tschopp, 2010). In particular, the NLRP3 inflammasome has been implicated in the mediation of inflammatory priming, as the activation of this inflammasome requires both a priming step and an activation step (Latz, 2010). It is important to note that HMGB1 has been demonstrated to increase NLRP3 mRNA and protein in hippocampus as well as microglia (Frank et al., 2016). Further, HMGB1 primed the neuroinflammatory and microglial proinflammatory response to a subsequent immune challenge (Frank et al., 2016). In light of these findings, a distinct possibility is that HMGB1 primed the NLRP3 inflammasome as a consequence of HFD treatment, but this possibility awaits testing. It should be noted that, although these changes were not observed in microglia per se, we did observe increased hippocampal expression of the macrophage antigen cd11b, and the microglial-selective chemokine receptor CX3CR1, suggesting that HFD may indeed activate microglia, as others have found (Cai et al., 2014; Knight et al., 2014). However, future experiments will be aimed at determining the specific role of microglia in these HFD-induced changes. Together, these data suggest that although short-term consumption of HFD did not produce frank neuroinflammation in the hippocampus, it did produce increased expression of molecular signals that are known to prime the hippocampus to over-respond to a subsequent immune challenge. It is interesting to note that similar findings were reported following long-term HFD consumption (Sobesky et al., 2014), strongly suggesting that long-term HFD consumption is not necessary to produce a primed neuroinflammatory microenvironment. Though short-term HFD alone was insufficient to induce an inflammatory response in the hippocampus, short-term HFD amplified hippocampal IL-1β and IL-6 increases to peripheral LPS. These data confirm that the inflammatory response in the hippocampus was indeed primed by HFD and are consistent with what others have found (Boitard et al., 2014; Cai et al., 2014; Sobesky et al., 2014). These findings provide a good basis to expect that short-term HFD consumption followed by a subsequent immune challenge would produce an impairment of hippocampal-dependent memory, as there is now a substantial literature confirming the role of proinflammatory cytokines in impairing hippocampal memory function (Rachal Pugh et al., 2001; Yirmiya and Goshen, 2011; Barrientos et al., 2015b). Indeed, the present data demonstrated that short-term HFD consumption alone did not impair memory, but when combined with a mild LPS immune challenge, HFD consumption robustly impaired contextual memory consolidation, a memory function specifically mediated by the hippocampus (Barrientos et al., 2002; Rudy et al., 2002; Matus-Amat et al., 2004). In experiment 3, the GR antagonist mifepristone was administered at the time of diet consumption to evaluate the role of CORT signaling in the neuroinflammatory priming caused by short-term consumption of an HFD. The data strongly suggest that CORT is a key mediator of these effects. HFD potentiated the expression of IL-1 and IL-6 in LPS-injected rats, replicating the findings from experiment 2. Mifepristone treatment effectively normalized this proinflammatory response to LPS, leading to levels that resembled those of the regular chow-fed group. The data in this experiment also demonstrated that short-term HFD consumption produces a greater expression of NLRP3, HMGB1, and IκBα in the absence of LPS, replicating the findings from experiment 1 showing that HFD alone upregulates neuroinflammatory priming signals in the hippocampus. Mifepristone treatment, in unchallenged HFD-fed rats, significantly reduced the expression of HMGB1 and IκBα, but not of NLRP3. These data suggest that CORT directly induces HMGB1. Moreover, in LPS-challenged rats, mifepristone significantly reduced the expression of HMGB1 and IκBα, as well as of NLRP3. Of note, these findings are the first to demonstrate glucocorticoid modulation of levels of DAMPs either in the periphery or the CNS. Of course, it should be noted that MAP kinases (e.g., p38) and NF-κB are signal transduction pathways downstream of innate immune response receptors (e.g., pattern recognition receptors), which bind HMGB1 (Kawai and Akira, 2010), and therefore may play a role in mediating neuroinflammatory priming. Thus, these may be important targets to block these effects. A key question arising from the present findings concerns how CORT induces HMGB1 in HFD-treated animals. One possibility is that elevated levels of CORT in brain may damage neural cells, leading to the passive release of HMGB1, which then signals microglia to generate a proinflammatory response. The basis for this speculation derives from work by Sapolsky (1999) demonstrating that glucocorticoids exacerbate the neurotoxic effects of excitotoxic agents, thereby “endangering” neurons. Given the data from experiment 3 showing a robust inhibitory effect of mifepristone on neuroinflammatory priming signals as well as on the LPS-induced proinflammatory response, we expected and were not surprised to find that mifepristone treatment prevented the HFD plus LPS-induced memory impairments. These data are consistent with findings showing the following: (1) that the inhibition of proinflammatory signals in the hippocampus at the time of memory consolidation prevents memory impairments (Frank et al., 2010b; Barrientos et al., 2012); (2) protracted corticosterone release in HFD-fed adolescent rats alters amygdala-dependent cognitive function and neuronal plasticity (Boitard et al., 2015); and (3) mifepristone effectively reduces immune-activated proinflammatory responses, specifically from hippocampal microglia, and prevents E. coli-induced memory impairments in aged rats (Barrientos et al., 2015a). The data presented here strongly implicate a role for CORT as a mediator of HFD-induced neuroinflammatory priming, and potentiated inflammatory responses to LPS that lead to contextual memory impairments. This is concluded because the inhibition of CORT signaling with mifepristone prevented all of these effects. Together, these data suggest that the glucocorticoid receptor may be an important target for attenuating the neuroinflammatory effects associated with HFDs. Acknowledgments: We thank Debra Berkelhammer, Charlotte Crist, Renata Daniels, Erika Galer, Simone Nadel, and Shaelyn Silverman for their technical assistance. Synthesis The decision was a result of the Reviewing Editor Leonidas Stefanis and the peer reviewers coming together and discussing their recommendations until a consensus was reached. A fact-based synthesis statement explaining their decision and outlining what is needed to prepare a revision is listed below. The following reviewers agreed to reveal their identity: Sophie Layé, Katia Karalis Both reviewers agree that the study is very well executed and that the data are clear and provide some innovation. Both indicate that further work is needed to characterize the effects of the different diet regimens, and that additional molecular components should be investigated. Overall, further work is needed in order to strengthen the manuscript. In particular, further measurements of various biochemical indices, such as p38, Asc1, and TLR4, will provide further insights. Western immunoblotting for NLRP3 is needed. The choice of the diet regimen and, importantly, the effects of the diet on the metabolic profile, including glucose, insulin, leptin, and lipids should be clarified and discussed within the context of the findings. Statements regarding the knowledge of the relationship between food consumption and behavior should be moderated. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3243310.1038/srep32433ArticleDischarging a Li-S battery with ultra-high sulphur content cathode using a redox mediator Kim Kwi Ryong 12Lee Kug-Seung 3Ahn Chi-Yeong 12Yu Seung-Ho 12Sung Yung-Eun a121 Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul 151-742, South Korea2 School of Chemical and Biological Engineering, Seoul National University, Seoul 151-742, South Korea3 Beamline Department, Pohang Accelerator Laboratory (PAL), Pohang 790-784, South Koreaa ysung@snu.ac.kr30 08 2016 2016 6 3243312 04 2016 09 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Lithium-sulphur batteries are under intense research due to the high specific capacity and low cost. However, several problems limit their commercialization. One of them is the insulating nature of sulphur, which necessitates a large amount of conductive agent and binder in the cathode, reducing the effective sulphur load as well as the energy density. Here we introduce a redox mediator, cobaltocene, which acts as an electron transfer agent between the conductive surface and the polysulphides in the electrolyte. We confirmed that cobaltocene could effectively convert polysulphides to Li2S using scanning electron microscope, X-ray absorption near-edge structure and in-situ X-ray diffraction studies. This redox mediator enabled excellent electrochemical performance in a cathode with ultra-high sulphur content (80 wt%). It delivered 400 mAh g−1cathode capacity after 50 cycles, which is equivalent to 800 mAh g−1S in a typical cathode with 50 wt% sulphur. Furthermore, the volumetric capacity was also dramatically improved. ==== Body Lithium-sulphur (Li-S) batteries have attracted much recent attention, due to the low cost and high theoretical specific capacity (1672 mAh g−1) of sulphur12. They have great potential as energy storage devices for electric vehicles (EVs) and energy storage systems (ESSs)3. However, there are several obstacles for their commercialization. One is the presence of polysulphides, which are intermediate products formed during charge/discharge, and their dissolution into the electrolyte leads to continuous loss of the active material and self-discharge45. Past researches have focused on constraining the movement of polysulphides by infiltrating sulphur into meso and/or micro porous carbon materials, physically restricting the dissolution of polysulphides6789, or designing a surface (e.g., functionalized carbon, metal oxide or metal carbide) that effectively adsorbs polysulphides1011121314. Another major obstacle is the insulating nature of sulphur. In order to compensate for the low electrical conductivity of sulphur (5 × 10−30 S cm−1 at room temperature), 30–40 wt% conductive agent is typically needed. This also necessitates the use of a binder (10–20 wt%) to attach the conductive agent and active material onto the current collector. The conductive agent and binder limited the amount of sulphur in the cathode to 50–60 wt%671112, leading to significantly lowered energy density and specific capacity per cathode mass, as well as increased manufacturing cost. The solution is increasing the effective conductivity of the cathode at high sulphur loading. To the best of our knowledge, all studies reporting high sulphur mass loading in Li-S batteries have achieved it by using thick cathodes15161718. This increases the areal capacity but not the volumetric capacity, even though the latter is more meaningful criterion19. Improving the volumetric capacity requires a higher sulphur ratio in the cathode material. Infiltrating sulphur into porous carbon only provides a limited solution, since the increased sulphur ratio is achieved at the cost of reduced conductivity from carbon. Additional conductive agents are needed in these composites, therefore sulphur loading in the cathodes remains low20. In this paper, the effective cathode conductivity is increased by introducing a redox mediator cobaltocene (Co(η5C5H5)2) into the electrolyte. It has a redox potential within the region of polysulphide reduction, and therefore can act as an electron transfer agent between the conductive surface and polysulphides. We will show that cobaltocene enabled Li2S nucleation and growth not only on the conductive carbon surface but also in the electrolyte. This redox mediator allows us to achieve significant improvement in the electrochemical performance of the cathode with ultra-high sulphur content (80 wt%). Results Cobaltocene acts as a redox mediator To measure the redox potentials of sulphur, cyclic voltammogram (CV) test was performed using a sulphur loaded commercial carbon non-woven layer (gas diffusion layer, GDL) as the working electrode, and Li metal as the counter electrode. In Fig. 1a, two pairs of electrochemical redox peaks appear. The high potential reduction peak (2.30 V vs. Li/Li+) involves the reduction of sulphur into long-chain polysulphides (Li2SX, 4 ≤ X ≤ 8). The low potential reduction peak (2.05 V) indicates the reduction of polysulphides to Li2S. Note that the area under the 2.05 V reduction peak is smaller than that of the 2.30 V peak, it is opposite from typical behaviour in Li-S batteries212223. It is due to the limited surface area of GDL. A separate CV test was performed in a coin cell with 50 mM cobaltocene dissolved electrolyte, using a bare GDL as working electrode. From Fig. 1b, cobaltocene has a sharp redox potential at 2.00 V, which is lower than the second reduction peak of sulphur (2.05 V). Therefore, in principle, cobaltocene has the potential capability for reducing polysulphides to Li2S. In order to test this possibility, we prepared three coin cells with different concentration of cobaltocene (0 mM, 12.5 mM and 25 mM) in 1 M [S] catholyte in Li2S6 form. The working and counter electrodes were GDL and Li metal, respectively. All tests were performed under galvanostatic discharge conditions with a current density of 500 μA cm−2. Since the active material was a polysulphide, there is no high discharge plateau (at about 2.30 V) related to the reduction of sulphur to polysulphides24, as shown in Fig. 2a. The discharge capacity increases with cobaltocene concentration. According to the CV results, 50 mM cobaltocene only contributes 30 μAh cm−2 to the discharge capacity. Therefore, the increased capacity here is not from cobaltocene itself, but from the low discharge plateau where the polysulphides are reduced to Li2S. Li2S formation Scanning electron microscope (SEM) images of bare GDL and after the first discharge (Fig. 2b–e) show a large number of highly agglomerated Li2S particles when the concentration of cobaltocene is increased. It is a clear evidence that cobaltocene effectively reduces the polysulphides to solid Li2S. Typical Li-S batteries have a potential plateau at 2.1–2.0 V after a gently sloping region between 2.3–2.1 V. However, this plateau almost disappeared in the absence of cobaltocene. This can be understood from the magnified SEM images. The surface of bare carbon fiber was clear and smooth (Supplementary Fig. 1a), but completely covered with Li2S particles after discharge (Supplementary Fig. 1b). Since Li2S is insoluble in the electrolyte and has high electrical resistivity, electron transfer from conductive carbon surface to the Li2S/electrolyte interface incurs high polarization25. More specifically, the limited conductive surface area cannot support enough sites to accommodate Li2S, leading to the characteristic potential drop and limited discharge capacity. The redox mediator acts as an electron transfer agent between conductive surface and polysulphides: it is reduced directly at the carbon fiber surface to Mred, which diffuses into the electrolyte, then reduce the polysulphides there while itself is oxidized back to Mox. Hence the redox mediator allows Li2S nucleation and growth on the carbon surface and in the electrolyte simultaneously. Afterwards, Li2S nanoparticles in the electrolyte will attach to and agglomerate with those already on the carbon surface to reduce the surface energy (Fig. 2f). As a result, cobaltocene in the electrolyte allows not only more Li2S formation but also a thicker Li2S layer (Supplementary Fig. 1c). We also quantitatively demonstrated it using energy-dispersive X-ray spectroscopy (EDS) analysis (Supplementary Fig. 2). In order to confirm that the cobaltocene reduces polysulphides by being oxidized into cobaltocenium, we conduct X-ray absorption near-edge structure (XANES) analysis. Figure 3 shows the normalized Co K-edge XANES spectra for Mred (0.5 M cobaltocene in electrolyte) and Mox (obtained by adding polysulphides into Mred and stirring for 6 h) at energies corresponding to the electronic transition from Co 1s to 4p. There are three peaks in the rising edge region. The pre-edge peak at 7710 eV corresponds to electric dipole-forbidden (1s → 3d) transition, which is enabled by 4p–3d hybridization due to the distortion of local structure. The absorption peak at 7720 eV is assigned to 1s → Cp (π*) transition (Cp is cyclopentadienyl). The strong peak at the top of the edge is 1s → 4p transition (7730 eV)262728. As the reaction proceeds, the 1s → 4p transition energy (above 7720 eV) increases and the peak shifts from 7728 to 7732 eV, presenting clear evidence of the oxidation of Co2+ (cobaltocene) into Co3+ state (cobaltocenium)29. In addition, the intensities of pre-edge peak and the shoulder on the rising edge are increased. Similar results have been reported for other organometallic compounds (e.g., ferrocenium, the oxidized state of ferrocene)30. To further verify that the increased capacity is from Li2S formation, we conducted in-situ X-ray diffraction (XRD) analysis during the first cycle with and without 50 mM cobaltocene. A cathode with 70 wt% S, 15 wt% carbon and 15 wt% binder was used as the working electrode. The cells were galvanostatic charged/discharged at 200 μA cm−2. Without cobaltocene, the intensities of orthorhombic α-sulphur (PDF no. 00-008-0247) peaks gradually decreased during the initial discharge and completely disappeared after the high potential region (Fig. 4a). No additional identical peak was found until the end of the discharge. It suggests that there is no detectable crystalline Li2S. Nevertheless, the gradually sloping (as opposed to a plateau) discharge curve at the low potential region is due to a thin insulating Li2S layer covering the conductive carbon surface and hindering charge transfer. As explained earlier, this layer leads to limited discharge capacity from the low potential plateau. With cobaltocene, in contrast, there is a clear discharge potential plateau for Li2S formation. XRD patterns also display Li2S (111) Bragg peak at 19.5 nm−1 (PDF no. 00-023-0369) towards the end of discharge (Fig. 4b). It could be interpreted that more and larger Li2S particles were formed in the presence of cobaltocene. The complete disappearance of the Li2S peak during the charging process means that the thick Li2S layer formed through solution and surface reactions is effectively converted to polysulphides and then to sulphur. The Li2S particles in direct contact with the conductive surface can be easily charged. However, their insulating nature inhibits the charging of Li2S particles away from the conductive surface. Cui’s group reported polysulphides could act as a redox mediator during the charging process31. Our group also reported similar result recently32. A small amount of polysulphides in electrolyte could effectively reduce the charging overpotential. This is also the case here. The long chain polysulphides migrate to Li2S and produce short chain polysulphides through disproportionation reaction. The short chain polysulphides could dissolve into the electrolyte and participate in the charging process. Battery cycling for ultra-high sulphur content cathode The results discussed so far show that cobaltocene can transfer electrons from electrode to the polysulfieds. This could compensate for the limited conductivity of the cathode with extremely low conductive agent ratio. A cathode with 80 wt% sulphur, 10 wt% carbon and 10 wt% binder was prepared by simple mortar mixing method. When cells using this cathode were cycled at 0.1 C (167.2 mA g−1S) with and without 50 mM cobaltocene, the initial discharge capacities were dramatically different, as seen in Fig. 5a. After several cycles, the cell with cobaltocene displayed a capacity of about 750 mAh g−1S, while the reference cell delivered only 250 mAh g−1S, which was mainly from the high potential plateau region (inset of Fig. 5a). Moreover, there was abrupt change in voltage during charging process (see Supplementary Fig. 3). We showed initial several cycle data due to the unstable charging behaviour without cobaltocene. The slightly increased capacity might be due to the wetting process as reported before33. Correspondingly, increase of capacity during initial several cycles with cobaltocene was observed, and this was due to the activation process of cobaltocene as redox mediator. We also confirmed the reproducibility of these electrochemical properties with longer cycle number as showed in Supplementary Fig. 4. As explained earlier, the low capacity without cobaltocene is due to the limited amount of conductive carbon, which not only transfers electrons but also provides sites for Li2S nucleation and growth. The redox mediator cobaltocene acts as a liquid conductive agent. It effectively transfers electrons from the cathode to the polysulphides, and therefore allows Li2S nucleation and growth on and off the conductive framework. Currently, the typical cathode in Li-S batteries contains only 50 wt% sulphur. Therefore, although its specific capacity based on the sulphur mass is high, the value based on total cathode mass is very low. The measured value of 200 mAh g−1 per cathode mass after 50 cycles (Fig. 5b) is similar to that of commercial LiCoO2 cathode1. Our cathode with 80 wt% sulphur using cobaltocene shows 200% increased capacity after 50 cycles. We also shown the discharge capacity based on cathode volume at Fig. 5c. The volumetric capacity is dramatically improved due to the increased sulphur content in cathode. The rate capability performance with cobaltocene is shown in Supplementary Fig. 3. The thick layer of large Li2S particles on the conducive surface after discharge significantly hinders the following charging process. Even though the polysulphides could act as a redox mediator as described earlier, they are far less effective than cobaltocene, especially at high current density. Still, the cell was functional and delivered about 200 mAh g−1S capacity at a high current density of 1.2 A g−1S. When the charging current was fixed to 0.2 A g−1S from the 6th cycle on (slow charging), the rate capability improved remarkably. It delivers about 350 mAh g−1S capacity at 1.2 A g−1S current density. Therefore, we believe that the rate capability could be further improved with another redox mediator that could effectively recharge Li2S. Conclusion In summary, we have successfully realized the high performance Li-S battery for ultra-high sulphur content (80 wt%) cathode by using cobaltocene as a redox mediator in the electrolyte. The redox mediator acts as an electron transfer agent: it is reduced at the cathode and then oxidized by the polysulphides remote from the conductive surface to produce Li2S. This novel approach can effectively produce Li2S both on the conducting surface and in the solution. Taken together, this unified mechanism allows sufficient Li2S formation with a very low amount of conductive agent in the cathode, as confirmed by our electrochemical method, SEM, XANES and in-situ XRD studies. The results reported here provide a simple and scalable approach to one of the most important challenges in creating ultra-high sulphur content cathodes for Li-S batteries. Methods Synthesis The blank electrolyte consists of 1 M lithium bis(trifluoromethanesulfone)imide (LiTFSI) in a mixture of 1,2-dimethoxyethane (DME) and 1,3-dioxolane (DOL) at a 1:1 volume ratio, with 0.1 M LiNO3 as an additive. To prepare the polysulphide catholyte, sulphur powder (Alfa Aesar) and lithium sulphide (Alfa Aesar) in fixed ratio were added to the blank electrolyte to achieve 1 M sulphur concentration in the form of Li2S6. The catholyte was heated at 45 °C for 24 h. A designated amount of cobaltocene was prepared at room temperature after stirring for 12 h. All processes were performed in an Ar-filled glove box. Sulphur loaded commercial carbon non-woven layer (GDL, Toray) was prepared by dropping sulphur dissolved CS2 solution onto GDL electrode. Characterizations X-ray absorption near-edge fine structure (XANES) was measured at 8C nano-probe XAFS beamline (BL8C) of Pohang Light Source (PLS-II) in the 3.0 GeV storage ring with a ring current of 360 mA. The radiation source of BL8C is a tapered in-vacuum-undulator. The X-ray beam was monochromated by a Si(111) double crystal and then it was delivered to a secondary source aperture where the beam size was adjusted to be 0.3 mm (v) × 1 mm (h). A high voltage (3000 V) was applied to ionization chambers which were filled with N2/Ar mixture gases to detect x-ray intensity. XAFS measurement was conducted in a transmission mode. The samples were prepared with solvent wetted glass fiber separators. After wetting the glass fibers were covered with Kapton tape. The obtained spectra were processed using Demeter software. In order to align the spectra Co foil was measured simultaneously with the samples. The in-situ XRD analysis was carried out at 5D beamline of the Pohang Light Source. The in-situ cells were assembled with specially prepared 2032 coin cells. The coin cells had a Kapton tape window in the center. The morphology and structure of products were characterized with a field-emission scanning electron microscope (FESEM, ZEISS, MERLIN Compact). Electrochemistry The 80 wt% sulphur cathode slurry was created by mixing sulphur, carbon (Super P and multi-walled carbon nanotube (MWCNT) in 1:1 mass ratio) and polyvinylidene difluoride (PVDF) binder with N-Methyl-2-pyrrolidone (NMP) solvent in weight percentages of 80%, 10% and 10%, respectively. The slurry was pasted onto an Al current collector through the doctor blade method, and dried at 60 °C for 12 h. The coated foil was then roll-pressed and cut into 11 mm-diameter disks with a punching machine. The sulphur loading mass was 1.3–1.5 mg cm−2. The same procedure was used to prepare the 70 wt% sulphur cathode, except that slurry was made of 70 wt% sulphur, 15 wt% carbon (Super P and MWCNT in 2:1 mass ratio) and 15 wt% PVDF binder. The 50 wt% sulphur cathode was prepared from a 5:3:2 mixture of S, Super P and PVDF. The volumetric capacity was calculated based on cathode volume (except Al foil). The thickness of cathode was measured using Micrometer measurement. The 2032 coin-type half cells were assembled using the sulphur cathode and catholyte from above. The counter and reference electrodes were fabricated from lithium foil in an Ar-filled glove box. All electrochemical measurements were carried out using a WBCS3000 cycler (WonATech, Korea) at room temperature. The cyclic voltammogram (CV) tests were performed at a sweep rate 0.2 mV s−1 between 3.0 and 1.5 V. All galvanostatic charge/discharge tests were performed between 3.0 and 1.5 V. The C-rates used in this study were based on the mass and theoretical specific capacity of sulphur (i.e., 1672 mAh g−1). Additional Information How to cite this article: Kim, K. R. et al. Discharging a Li-S battery with ultra-high sulphur content cathode using a redox mediator. Sci. Rep. 6, 32433; doi: 10.1038/srep32433 (2016). Supplementary Material Supplementary Information The authors would like to acknowledge the financial support by IBS-R006-G1. Author Contributions K.R.K. conceived the idea and designed the experiments. K.R.K. prepared materials and carried out the electrochemical experiments. XANES experiments were performed by K.-S.L. and C.-Y.A. conducted the SEM experiments. S.-H.Y. participated in the manuscript editing and discussion of this work. K.R.K. analyzed the data and wrote the manuscript in collaboration with Y.-E.S. Figure 1 Cyclic voltammograms. (a) Sulphur and (b) cobaltocene. The sweep rate was 0.2 mV s−1. Figure 2 Cobaltocene acts as a redox mediator. (a) Galvanostatic discharge curves of cells with different concentrations (0, 12.5, 25 mM) of cobaltocene in 1 M [S] catholyte. SEM images of (b) bare GDL and after discharge with (c) 0 mM, (d) 12.5 mM, and (e) 25 mM cobaltocene. (f) Schematic illustration of unified mechanism. Li2S nucleation and growth through conductive surface pathway and solution pathway with cobaltocene. Figure 3 Chemical states of redox mediators. Normalized Co K-edge XANES spectra for Mred and Mox. Figure 4 Galvanostatic discharge-charge curves of the first cycle and in-situ XRD patterns for points labeled on the curves. (a) Without cobaltocene, and (b) with 50 mM cobaltocene. Only the XRD patterns with cobaltocene show the appearance of Li2S peaks at the end of discharge. Figure 5 Electrochemical performance. (a) Electrochemical characterization of ultra-high sulphur content (80 wt%) cathode with and without cobaltocene. The cycle performance shows dramatically improved discharge capacity with cobaltocene. The inset shows glavanostatic discharge curves of various cycles. (b) Specific capacities based on cathode and (c) volumetric capacities versus cycle number of 80 wt% S cathode with cobaltocene and 50 wt% S cathode. All tests were performed at 0.1 C. ==== Refs Ji X. & Nazar L. F. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3234410.1038/srep32344ArticleAromatase inhibition rapidly affects in a reversible manner distinct features of birdsong Alward Beau A. a1*de Bournonville Catherine 2†Chan Trevor T. 1Balthazart Jacques 2Cornil Charlotte A. 2Ball Gregory F. 1‡1 Department of Psychological and Brain Sciences, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA2 GIGA Neuroscience, University of Liege, Avenue Hippocrate, 15, 4000 Liege, Belgium, USAa balward@stanford.edu* Present address: Stanford University, Department of Biology, 450 Serra Mall, Stanford, CA, USA 94305, USA. † Present address: University of Massachusetts, Amherst, Department of Psychological and Brain Sciences, Amherst, MA, USA 01003. ‡ Present address: University of Maryland, College Park, Department of Psychology, 4094 Campus Drive, College Park, MD USA 20742. 30 08 2016 2016 6 3234429 06 2016 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Recent evidence has implicated steroid hormones, specifically estrogens, in the rapid modulation of cognitive processes. Songbirds have been a useful model system in the study of complex cognitive processes including birdsong, a naturally learned vocal behavior regulated by a discrete steroid-sensitive telencephalic circuitry. Singing behavior is known to be regulated by long-term actions of estrogens but rapid steroid modulation of this behavior has never been examined. We investigated if acute actions of estrogens regulate birdsong in canaries (Serinus canaria). In the morning, male canaries sing within minutes after light onset. Birds were injected with fadrozole, a potent aromatase inhibitor, or vehicle within 2–5 minutes after lights on to implement a within-subjects experimental design. This single injection of fadrozole reduced the motivation to sing as well as song acoustic stereotypy, a measure of consistency over song renditions, on the same day. By the next day, however, all song measures that were affected had returned to baseline. This study indicates that estrogens also act in a rapid fashion to regulate two distinct features of song, a learned vocal behavior. ==== Body Behavioral and cognitive processes have been shown to be modulated by steroid hormones1. This modulation of behavior by steroid hormones can occur through both genomic and non-genomic actions, although evidence for the latter has begun to accumulate only relatively recently2. For instance, in male Japanese quail (Coturnix japonica) and female Long Evans rats (Rattus norvegicus) estrogens have been shown to facilitate sociosexual behaviors in a rapid, short-lasting (i.e., acute) manner345. Aggressive behavior in song sparrows (Melospiza melodia) has also been shown to be rapidly regulated by estrogens: a single injection of the aromatase inhibitor fadrozole decreased within a day territorial aggression during the non-breeding season6. There is also recent evidence that cognitive processes like memory are similarly under the control of the acute actions of steroid hormones78 but our understanding of the role of these acute actions of steroid hormones remains incomplete. Birdsong is an excellent model system for the study of complex cognitive processes9. Songbirds naturally learn their song in a manner akin to how humans learn speech1011. The production of song relies on the interaction between multiple functionally-discrete telencephalic nuclei (collectively called the song control system or SCS) as well as areas involved in motivation, providing an opportunity to study complex cognitive processes with multiple, distinct features. Moreover, multiple sites for the actions of steroid hormones have been identified throughout the SCS12. Therefore, it is especially useful to investigate the modulation by steroid hormones of these behaviors in songbirds. Birdsong is well known to be regulated by steroid hormones such as testosterone and its metabolites1213. Castration in canaries (Serinus canaria) substantially reduces song output and treatment with exogenous testosterone restores singing after approximately three days141516. In zebra finches (Taeniopygia guttata) chronic treatment with ATD (1,4,6-androstatriene-3,17-dione), a potent inhibitor of aromatase, the enzyme that converts testosterone to estradiol (E2), reduces song output17. Androgen receptors are expressed in the telencephalic song control nuclei HVC, RA, LMAN, and in a variety of nuclei in the hypothalamus and midbrain and estrogen receptors (ER) are expressed in HVC (ER alpha) in some songbird species as well as in the hypothalamus (both ER alpha and beta)1819. Aromatase is also widely distributed throughout the songbird brain particularly in the hypothalamus and the preoptic area (POA) including the medial preoptic nucleus (POM)20, as well as in non-hypothalamic areas such as the dorsal telencephalon202122. This distribution is generally consistent with what is observed in rodent species2324. However, aromatase activity is in general much higher in the songbird brain25 and there is, contrary to what is observed in rodents, an especially high degree of aromatase activity in the telencephalon262728. Aromatase is noticeably absent from cell bodies in song control regions such as HVC and RA, but densely expressed in the auditory regions adjacent to HVC, such as the caudomedial nidopallium (NCM) and caudomedial mesopallium (CMM). Specifically, aromatase is expressed in NCM neurons in both cell bodies and presynaptic terminals, and in presynaptic terminals in HVC2930. This presynaptic distribution of aromatase in HVC suggests that birdsong, a learned vocal behavior, may be under the control of the acute actions of steroid hormones such as estrogens. In the current study, we investigate in a well-studied songbird species, the canary, the role of the fast actions of estrogens in the regulation of birdsong. Results Effects of aromatase inhibition on song The descriptive statistics of all song measures and the result of their statistical analyses are presented in Table 1. Acute aromatase inhibition leads to a decrease in the motivational measures of song Three birds did not sing at all on the day they were injected with vehicle and 5 did not sing on the day they were injected with fadrozole (Fisher exact probability test: p = 0.67). Only birds that sang on each injection day were included in these analyses (See ‘Methods: Song recording and analysis’). Representative songs are shown for a bird treated with vehicle versus fadrozole in Fig. 1 (Fig. 1A,B). On the day of injections, birds treated with fadrozole started singing after significantly longer latencies following injection than birds treated with vehicle (Fig. 1C; t6 = 3.44, p < 0.05, d = 1.30). Fadrozole-treated birds also spent less time singing (Fig. 1D; t6 = 2.98, p < 0.05, d = 1.13) and sang shorter songs (Fig. 1E; t6 = 2.75, p < 0.05, d = 1.04). Acute aromatase inhibition reduces song stereotypy Fadrozole treatment also caused a decrease in the stereotypy of song as evident based on the fact that birds treated with fadrozole sang songs with higher bandwidth CV (Fig. 1F; t6 = 3.49, p < 0.05, d = 1.31) (higher CV = lower stereotypy). All significant differences concerning singing motivation and song stereotypy between the fadrozole and vehicle conditions were associated with large effect sizes as reflected by the Cohen’s d values larger than 1 in each case (see Table). The effects of acute aromatase inhibition on song disappeared the day after treatment All features of song that were affected on the day of fadrozole treatment were back to normal levels the day after treatment (Fig. 2; t11 = 0.71, p ≥ 0.49 for all comparisons except for % time spent singing where a statistical tendency was still present; t11 = 2.05, p = 0.07). Effects of fadrozole on aromatase activity Average levels of aromatase activity at 30 min or 4 hours after a fadrozole or control injection are shown in Fig. 3. Values for aromatase activity in the 30-min HPOA group of one vehicle-treated and one fadrozole-treated birds were outliers (see ‘Methods’) and these birds were removed from the analysis of aromatase activity in the 30-min HPOA group (see Fig. 3 for final sample sizes per group). In the HPOA, after thirty minutes, fadrozole treatment led to a substantial reduction of aromatase activity compared to vehicle (Bonferroni’s, t13 = 3.40, p < 0.05); however, this difference had disappeared four hours after injection (Bonferroni’s, t6 = 0.35, p = 0.75). In the NCM, 30 minutes after injection fadrozole similarly caused a large reduction in aromatase activity relative to vehicle (Bonferroni’s, t16 = 3.32, p < 0.01), whereas this difference was no longer present at four hours after injection (Bonferroni’s, t6 = 1.50, p = 0.18). Discussion Many studies on the hormonal regulation of birdsong have focused on investigations of the long-term effects of sex steroid hormones (e.g., see13 for a review). Recently, evidence has begun to accumulate indicating that certain behaviors and cognitive processes may be regulated by estrogens acting in a much faster, presumably non-genomic, fashion345731. Moreover, song sparrows show enhanced concentrations of estrogens in the brain in the breeding season versus the non-breeding season32 and estradiol increases aggression within 20 minutes in this species33. The experiment presented here suggests that estrogens may act in this fashion in the regulation of a complex, learned vocal behavior. Our experiment demonstrates that acute aromatase inhibition causes a variety of song features to undergo rapid and prominent changes. A single fadrozole injection decreased motivational measures of song and decreased song stereotypy on the day of treatment and all of the affected measures returned to baseline by the next day. These results suggest that aromatase present in different brain regions plays an important role in regulating these distinct features of song. For instance, as mentioned above, aromatase is densely expressed in the POM of zebra finches and the conversion of testosterone to E2 is required for the full activation of singing behavior in this species172034. These observations suggest that one possible site at which the acute inhibition of aromatase causes the observed reduction in the motivation to sing is the POM. Indeed, work in male Japanese quail has shown that estrogens act in an acute manner in the brain to activate motivational aspects of male-typical sexual behaviors3435 and based on the extensive work on male sexual behavior in this species, a likely site for these rapid actions of estrogens in the regulation of motivation is the POM363738. Work in canaries and starlings supports the contention that aromatase in POM is critical for the rapid changes in the motivation to sing observed in the current study. For instance, lesions to POM cause substantial reductions in the motivation to sing39 and testosterone implanted solely in POM of castrated canaries enhances the motivation to sing in the absence of increases in song stereotypy1415. Testosterone implanted in the POM of castrated canaries took approximately 7 days to fully enhance the motivation to sing15, suggesting the effects were genomic in nature. It has been established that testosterone enhances the expression and activity of aromatase in the preoptic area of songbirds4041 and the increased expression of the corresponding gene in the POM might represent one of the genomic effects underlying song activation. As a consequence, the POM would then be a plausible site where locally produced neuroestrogens act to regulate the motivation to sing5. Part of these effects could additionally be rapid and mediated by non-genomic regulations of aromatase activity42434445. However, the relatively rapid changes in song stereotypy are unlikely to be controlled by changes in aromatase activity or the activation of ER in the POM. ER Activation in the SCS has been shown to enhance song stereotypy. For instance, blocking ER in the HVC of white crowned sparrows via the chronic infusion of the ER antagonist tamoxifen reduced song acoustic stereotypy46. In our experiment, blocking aromatase activity likely led to an acute decrease in E2 concentrations acting in HVC, thus causing a reduction in song acoustic stereotypy. The source of E2 could have been the testis or E2 generated in the brain itself (i.e., neuroestrogens). Indeed, while aromatase is not expressed in HVC itself, it is expressed at high levels in the nidopallium surrounding HVC. For instance, neurons in NCM, an auditory region within the nidopallium, express aromatase20 and those aromatase-expressing neurons project to HVC21. Remage-Healey and colleagues47 have shown that E2 produced in NCM enhances the selectivity of HVC neurons to the bird’s own song (BOS). The depletion of E2 production caused by fadrozole injection may have caused disruptions in BOS selectivity, which could have led to decreased song stereotypy. Hence, there are multiple ways by which the inhibition of aromatase could have led to decreases in song stereotypy. Finally, recent work suggests there may be a link between the actions of steroid hormones and regulation of speech production and vocal plasticity in humans4849. Work in songbirds has been critical in providing possible causal mechanisms for steroid hormones in the regulation of vocal plasticity141546505152. However, all of these studies used time scales that were far too long (i.e., days to weeks) to elucidate the acute actions of steroid hormones in regulating vocal plasticity. The results presented here provide evidence that the motivation to produce learned vocalizations and vocal plasticity itself are mediated by acute actions of steroid hormones. Song control in canaries might thus be under steroid control both in the long- and in the short-term which is consistent with the recently proposed dual action hypothesis of estrogen action2. This raises the intriguing question of whether changes in vocal plasticity in humans may also be regulated by acute actions of steroid hormones. Methods Animals and pre-experimental manipulations We used 12 canaries of the American singer strain because preliminary studies from our laboratory had found that they sing readily after handling and other non-invasive manipulations. Birds were obtained from a local breeder (Maryland Exotic Birds). Upon entry into the lab birds were placed on a short day (SD) photoperiod (8 L:16D) for six weeks to maintain photosensitivity53. The protocols and procedures used here were approved by the Johns Hopkins University Animal Care and Use Committee (protocol number: AV14A112) and followed the ASAB/ABS Guidelines for the use of animals in research. Acclimation and injection procedures Birds were placed in sound-attenuated, isolation chambers (41 cm × 48 cm × 51 cm) set to long days (14L:10D) to simulate breeding conditions5354. We randomly selected three groups of four birds to experience lights on at either 08:00 h, 08:02 h, or 08:04 h which experienced lights off at 22:00 h, 22:02 h, or 22:04 h, respectively. This was done to ensure all birds were injected during the same relative time frame following lights on. Seven days later birds were handled and injected with vehicle propylene glycol (propylene glycol:saline = 4:1) 2–5 minutes after lights on to simulate the handling associated with the injections and habituate birds to the injection procedure. Injections were made intraperitoneally by using forceps to lift up the skin above the abdomen and inserting the needle and immediately making the injection. One person would grab the bird from its cage 2–5 minutes after lights on and hold it in their hand while another person made the injection. The whole injection procedure took less than a minute in almost all cases. Procedures Three days after the acclimation period, between two and five minutes after lights on, birds were either injected with fadrozole (Fadrozole hydrochloride, Sigma Aldrich F3806; 30 mg/kg; (n = 6) dissolved in propylene glycol:saline (4:1) or with vehicle only (n = 6). The dose of fadrozole was selected based on previous studies in fish, birds and mammals demonstrating rapid behavioral effects of this dose of fadrozole or of the related and similar inhibitor vorozole355556 (See ref. 52 for a comparison of effective doses producing acute effects in various animal models). This dose of vorozole had also been shown to completely inhibit with 30 min brain aromatase activity in quail35. Three days later these injections were repeated but the subjects assigned to each treatment were reversed so that each bird had been subjected to both the vehicle and fadrozole treatment. Four days following the second injection, birds were injected again with either vehicle or fadrozole and their brains were extracted 30 minutes or 4 hours later (see ‘Brain and Blood Collection’ below). Male canaries sing prolifically within minutes following light on141554575859. However, based on pilot studies, injections (using vehicle) can delay the onset of singing behavior for multiple hours. Therefore, to increase the likelihood that samples of song from each bird could be captured on the day of injection, song was recorded on these days from lights on (800 h) to 1200 h and from 1300 h to 1600 h. The day before the first injection, song was recorded from 800 h to 1030 h to provide a baseline level of singing14155457. On the day following the injection of fadrozole, song was also recorded for 800 h to 1030 h. These various recording procedures were designed to answer two questions: 1) How is song affected on the fadrozole injection day as compared to song recorded on the day when only the vehicle was injected? and 2) Are any of the observed changes still present on the following day? Song recording and analysis On the first day of the acclimation period, birds were placed individually in sound-attenuating recording chambers (41 cm × 48 cm × 51 cm). Isolation chambers were outfitted with a microphone (BT-MP8087 Mini microphone; B&H Photo and Electronics Corp, New York, NY) and camera (KPC-600 Pinhole Camera 3.6 mm; B&H Photo and Electronics Corp, New York, NY) connected to a computer running DVRserver (V6.33b; Mammoth Technologies, Austin, TX) designed for real-time video and audio surveillance recording. The DVRserver captured song behavior. Recordings were converted to.wav files sampled at 22,050 Hz which translated to a frequency range of 0–11 kHz. Song files were run through a high-pass filter set to a threshold of 900 Hz to remove low-frequency noise and converted to a digital format using Goldwave™ (Version 5.55; GoldWave, St. John’s, NF, Canada) before they were visualized into sound spectrograms using Avisoft (SASlab Pro, Berlin, Germany), a Windows application for investigating animal acoustic communication. For the spectrograms, the fast Fourier transform length was set to 512 with an overlap of 75% for the temporal resolution. Songs were defined as vocalizations that have a duration >1 second of continuous vocalizations with gaps no longer than 500 milliseconds141554576061. Each song was verified by looking at the original sonograms to further eliminate noise and false positives that escaped the filter. Based on previous work, we used Avisoft to quantify the following song features: latency to sing following injection, % time singing, mean song duration–three measures of the motivation to sing–and song acoustic stereotypy1415465459. We calculated % time singing by dividing the total time each bird spent singing by the total sampling time on each day and multiplying this value by 100. Mean song duration was calculated by averaging across each song on each day. We predicted that inhibiting aromatase with fadrozole would cause reductions in both the motivation to sing341735 as well as song stereotypy46. We used Avisoft to quantify song stereotypy. Our previous work as well as the work of others has shown that in canaries the actions of testosterone and its metabolites are critical for enhancing song acoustic stereotypy141546. We used Avisoft to quantify the bandwidth for each song, and from this we computed song bandwidth stereotypy. Song bandwidth stereotypy was chosen based on previous work1415. For each recording day (baseline day, injection day, day after injection), average (AVG) bandwidth and the associated standard deviation (SD) were computed over all songs on those specific days. The stereotypy of bandwidth was computed using the coefficient of variation (CV) (CV = (SD/AVG)*100)); the higher the CV of song bandwidth, the lower the stereotypy of said. CV of acoustic variables has been used in previous studies as measures of song stereotypy141546596263. It should be noted that some birds did not sing at all on a given day. Because the experiment used a within-subjects design (birds compared to themselves in different conditions) and the reasons potentially explaining this inactivity can be variable including but not limited to the aromatase inhibition after fadrozole injection, these birds where no recording was available for a given day (after injection of either fadrozole or vehicle) had to be removed from the analyses (See beginning of the ‘Results’ section for exact numbers). This explains why the degrees of freedom in the results are often smaller than the number of birds actually included in the experiment. Brain and blood collection Four days after the last injection of this experiment, birds (12 males from this experiment and 16 additional males) were injected within 2–5 minutes after lights on with vehicle (n = 14) or fadrozole (n = 14). Their brains were rapidly extracted 30 minutes (10 from each group) or 4 hours (4 from each group) later and frozen on dry ice. One bird from the 30-minute group that was injected with vehicle and one bird of the 30-minute group injected with fadrozole escaped and flew around for an extended period of time before or after being injected and they were consequently excluded from the analysis of aromatase activity reducing the number of available brains to 9 in these two groups. We ensured not to give birds a fadrozole injection on the day of brain extraction if they had received an experimental injection of fadrozole four days earlier to minimize possible carry-over effects. Brains remained on dry ice for at least five minutes before being stored at −70 °C until assessment of aromatase activity (see above). These brains were used to assess the efficacy of fadrozole on inhibiting brain aromatase (see below). The 30-minute time point was chosen based on observations in a previous study in male Japanese quail that showed Vorozole™ (another very similar aromatase inhibitor) caused a substantial reduction in aromatase activity 30 minutes after it was injected35. The 4-hour time point was chosen based on behavioral observations from this experiment that most birds treated with fadrozole begin showing a rebound in song behavior after about 4 hours, suggesting aromatase activity has returned to normal levels. Microdissections and assay of aromatase activity To assess the efficacy of fadrozole in inhibiting the activity of aromatase, we microdissected two regions of the brain that are well known to express very high levels of aromatase, the hypothalamic-preoptic area (HPOA) and the NCM, and ran on these samples an in vitro assay measuring aromatase activity (AA). The method used for microdissecting out the HPOA was modified for use in canaries from that used by Cornil and colleagues64 in quail. The brain was sectioned in 200 μm thick coronal slices with the plane of section adjusted to the stereotaxic atlas of canary65. Sections were mounted on frozen microscope slides and individual regions were then immediately collected by cutting them out with a scalpel. The hypothalamic/preoptic area (HPOA) was collected from the most rostral section containing the full extension of the tractus septopallio-mesencephalicus (TSM) to the most caudal section containing the end of the anterior commissure (CA). For each section, the dissection was defined by a dorsal cut performed ventral to the septum and a lateral cut at the most lateral edge of the diencephalon (defined as the junction between each telencephalon and optic lobe). In the most caudal sections an additional oblique cut was performed at the basis of the diencephalon to remove each optic lobe. A caudal mediodorsal telencephalic region containing the NCM was then collected. Both regions were delimited by a dorsoventral cut parallel to the interhemispheric line aligned to the point where the telencephalon meets the optic lobe and a ventral cut at the level of the lamina medullaris dorsalis for the rostral sections and at the level of the lamina arcopallialis dorsalis for the most caudal sections. To ensure aromatase from the hippocampus did not confound the activity present in the NCM region that was microdissected, the hippocampus was removed using a razor blade. Microdissected tissues were immediately transferred into refrigerated 1.5 ml tubes kept on dry ice and stored at −80 °C until further use. The aromatase activity assay was performed by methods described in Cornil et al.64 with only minor modifications. The microdissected regions were homogenized with a glass homogenizer in 240 μL ice-cold buffer containing 150 mM KCL, 1 mM Na-EDTA, 10 mM Tris-HCl pH 7.2. Aromatase activity was quantified in these homogenates by measuring the tritiated water production from [1β-3H]-androstenedione24. On an ice bath, triplicate aliquots (50 μl) of homogenate were added to 50 μl of 100 nM [1β-3H]-androstenedione (Specific activity = 24.0 Ci/mmol) and 50 μl of buffer. To initiate the assay, 50 μl of NADPH was added so as to reach a final concentration of 1.2 mM. All these steps were conducted at 4 °C in 1.5-ml Eppendorf® tubes which were then quickly capped and incubated for 20 minutes at 37 °C. The reaction was stopped by cooling the samples in an ice bath and adding 0.4 ml ice-cold 10% trichloroacetic acid containing 2% activated charcoal. After centrifugation at 1200 g for 15 min, supernatants were applied to small columns made of Pasteur pipettes plugged with glass beads and filled (3 cm high) with a Dowex cation exchange resin AG 50 W-X4, 100–200 mesh (Biorad, Richmond, CA). The columns were then eluted with 3 × 0.6 ml distilled water. Effluents were collected in scintillation vials and 10 ml Ecoscint A (National Diagnostics, Atlanta, GA) were finally added. Vials were counted for 3 min on a Packard Tri-Carb 1600 TR Liquid Scintillation analyzer. For each subject an additional tube was incubated in the presence of an excess (final concentration about 40 μM) of the potent and specific aromatase inhibitor, R76713 (Racemic vorozole, Janssen Pharmaceutica, Beerse, Belgium) providing blank values of enzymatic activity. A recovery of 93 ± 2% is usually obtained from samples of 10,000 dpm tritiated water conducted throughout the entire purification procedure (incubation, centrifugation and Dowex column). Enzyme activity was expressed in total fmol h−1 after correction of the counts for quenching, recovery, blank values and percentage of tritium in β-position in the substrate. Statistical Analyses To test the effects of fadrozole on the inhibition of aromatase in the HPOA and NCM, we conducted Bonferroni-corrected planned comparisons comparing the effects of Fadrozole at the different time points. Aromatase activity values were log-transformed. Outliers were excluded if they were beyond +/−2 standard deviations from the mean. Paired t-tests were used to assess the effects of treatment on song measures. Percentages of birds singing on each injected day were compared with the Fisher exact probability test. Effects were considered significant at p ≤ 0.05 using two-tailed statistical analyses. Effect sizes were reported as Cohen’s d for t-tests when significant differences were observed. Additional Information How to cite this article: Alward, B. A. et al. Aromatase inhibition rapidly affects in a reversible manner distinct features of birdsong. Sci. Rep. 6, 32344; doi: 10.1038/srep32344 (2016). We thank Kathryn Rownd for technical assistance. This work was supported by National Institutes of Health/National Institute of Neurological Disorders and Stroke Grant R01 35467 (to G.F.B. and J.B.) and Grant SSTC PAI P7/17 from the Belgian Science Policy (to C.A.C., J.B. and G.F.B.). C.A.C. is F.R.S.-FNRS research associate. C.d.B. was supported by a non-FRIA fellowship from the University of Liège. Author Contributions B.A.A., J.B., C.A.C. and G.F.B. conceived of and designed the experiments; B.A.A. and C.d.B. carried out the aromatase assay; B.A.A. and T.T.C. carried out the injections; B.A.A. and T.T.C. analyzed singing behavior; B.A.A., C.d.B. and G.F.B. analyzed the data; B.A.A., J.B., C.A.C. and G.F.B. wrote the manuscript. All authors gave final approval for publication. Figure 1 Effects of acute aromatase inhibition with fadrozole on multiple measures of song. Representative songs from a bird treated with (A) vehicle (VEH) versus (B) fadrozole (FAD). Treatment affected measures of the motivation to sing including (C) the Latency to sing, (D) % Time singing, (E) Song duration, and a measure of song stereotypy (F) Song bandwidth coefficient of variation (CV). The higher the CV, the lower the stereotypy and vice versa. Bars represent the mean of all data in the corresponding group. Asterisks indicate a significant difference. Differences were considered significant at p < 0.05. Figure 2 Comparison of song features reflecting the motivation to sing (A,B) and the song stereotypy (C) on the baseline (BL) day and on the day after fadrozole (FAD) injection. CV = Coefficient of Variation. The higher the CV, the lower the stereotypy and vice versa. Bars represent the mean of all data in the corresponding group. In all cases differences were non-significant (ns). Figure 3 Effects of fadrozole on aromatase activity (AA) at two different time points after injection. Fmol/h = fentomoles per hour. The numbers within each bar represent sample size. Asterisks indicate a significant difference between the AA in the respective brain regions as indicated by Bonferroni-corrected planned comparisons at the different time points. Bars represent the means ± standard errors. Differences were considered significant at p < 0.05. Table 1 Descriptive statistics and statistical information for the effects of fadrozole injection on song features. Statistical Information Day of injection, vehicle (VEH) versus fadrozole (FAD) Baseline (BL) versus Day after FAD (DAF) Measure Mean ± SEM Mean Dff ± SEM Diff t df p Cohen’s d Mean ± SEM Mean Dff ± SE Diff t df p Cohen’s d Latency to sing after injection (min) VEH: 129.7 ± 47.1 114.9 ± 33.4 3.44 6 0.01* 1.30 — — — — — — FAD: 244.6 ± 65.6 % Time singing VEH: 5.1 ± 1.1 3.2 ± 1.1 2.98 6 0.02* 1.13 BL: 11.7 ± 2.6 3.5 ± 1.7 2.05 11 0.07 — FAD: 1.9 ± 0.6 DAF: 8.2 ± 2.5 Song duration (sec) VEH: 10.0 ± 2.1 4.3 ± 1.9 2.75 6 0.03* 1.04 BL: 7.4 ± 1.2 −0.5 ± 0.8 0.7 11 0.49 — FAD: 5.7 ± 1.1 DAF: 7.9 ± 1.2 Bandwidth CV VEH: 50.0 ± 9.3 −29.8 ± 8.5 3.49 6 0.01* 1.31 BL: 53.7 ± 8.4 −2.3 ± 3.6 0.7 11 0.53 — FAD: 70.8 ± 14.9 DAF: 55.9 ± 7.9 Descriptions of the different song variables are provided within the main text. Means ± Standard Error of the Mean (SEM) are shown for the two treatments. Additionally, the Mean Differences (±SEM) within-subject (Mean Diff ± SEM Diff) are shown for each comparison. Effect sizes are represented with Cohen’s d. Significant within-subject effects are written in bold with a single asterisk next to its p value. All statistical tests were two-tailed. Effects were considered significant at p ≤ 0.05. DAF = day after fadrozole. ==== Refs Adkins-Regan E. Neuroendocrinology of social behavior . ILAR J. 50 , 5 –14 (2009 ).19106448 Cornil C. A. , Ball G. F. & Balthazart J. The dual action of estrogen hypothesis . Trends Neurosci. 38 , 408 –416 (2015 ).26089224 Seredynski A. L. , Balthazart J. , Christophe V. J. , Ball G. F. & Cornil C. A. Neuroestrogens rapidly regulate sexual motivation but not performance . J. Neurosci. 33 , 164 –74 (2013 ).23283331 Seredynski A. L. , Balthazart J. , Ball G. F. & Cornil C. A. Estrogen receptor β activation rapidly modulates male sexual motivation through the transactivation of metabotropic glutamate receptor 1a . J. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3234010.1038/srep32340ArticleBroad Spectrum Anti-Influenza Agents by Inhibiting Self-Association of Matrix Protein 1 Mosier Philip D. 1Chiang Meng-Jung 2Lin Zhengshi 2Gao Yamei 2Althufairi Bashayer 1Zhou Qibing 13Musayev Faik 1Safo Martin K. 1Xie Hang a2Desai Umesh R. b11 Department of Medicinal Chemistry and Institute for Structural Biology, Drug Discovery and Development, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, United States of America2 Division of Viral Products, Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, United States Food and Drug Administration, Silver Spring, Maryland, United States of America3 Department of Nanomedicine & Biopharmaceuticals, National Engineering Research Center for Nanomedicine, Huazhong University of Science and Technology, Wuhan, Hubei, Chinaa Hang.Xie@fda.hhs.govb urdesai@vcu.edu30 08 2016 2016 6 3234001 06 2016 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The matrix protein 1 (M1) of influenza A virus (IAV) exists as a three-dimensional oligomeric structure in mature virions with high sequence conservation across different IAV subtypes, which makes it a potential broad spectrum antiviral target. We hypothesized that impairing self-association of M1 through a small molecule ‘wedge’, which avidly binds to an M1-M1 interface, would result in a completely new class of anti-influenza agents. To establish this proof-of-principle, we performed virtual screening on a library of >70,000 commercially available small molecules that resulted in several plausible ‘wedges’. Biophysical studies showed that the best molecule bound the M1 protein potently and weakened M1-M1 self-association. Most importantly, the agent reduced the thickness of the M1 layer in mature virions and inhibited in ovo propagation of multiple IAV strains including H1N1, pandemic H1N1, H3N2 and H5N1, which supports the “wedge” hypothesis. These results demonstrate that M1 is a promising druggable target for the discovery of a completely new line of broad spectrum anti-IAV agents. ==== Body It is estimated that more than 35 million cases of influenza-like illness have occurred in the US alone in a single season (2013–2014)1 despite the availability of multiple seasonal influenza vaccines. This is due to the rapid mutation of viral surface glycoproteins hemagglutinin (HA) and neuraminidase (NA) resulting in frequent antigenicity changes2, which makes annual influenza vaccine strain selection difficult to match with circulating viruses3. In recent years, tremendous efforts have been focused on developing universal vaccines that target a variety of conserved epitopes in HA to induce broadly neutralizing antibodies456. In addition, alternative approaches that target the virus’s internal proteins such as matrix protein 1 (M1) and nucleoprotein (NP) have also been pursued for promoting cross-reactive T cell immunity78. However, developing universal vaccines is extremely challenging due to the high plasticity of influenza A virus (IAV), of which 18 HA subtypes and 11 NA subtypes are known today. With increased activities of highly pathogenic avian influenza virus detected globally91011, there is an urgent demand for effective counter-measures including broad spectrum antivirals for pandemic preparedness. Current anti-IAV drugs target either the M2 ion channel (adamantine and rimantidine) or NA (oseltamivir, zanamivir and peramivir) of the viral envelope. However, the rapid evolution of NA and to a lesser extent M21213, as well as the widespread resistance to M2 inhibitors1415161718, underscore the urgency for better antiviral agents. Efforts to discover such agents have employed drug design strategies based on either mechanistic (e.g., Kim et al.19) or structural (e.g., Massari et al.20) paradigms. Such strategies are being earnestly pursued against HA, NA, M2, nonstructural protein, RNA polymerases, and NP2122, which represent all, but one, proteins of the IAV. The one protein of IAV against which no inhibitor has been developed to date is the M1 protein. The M1 protein forms a three-dimensional layer underneath the lipid bilayer of the virion serving as a bridge to connect the membrane proteins including HA and NA with the internal viral ribonucleoprotein (vRNP) core23. The M1 protein is critical for structural and functional integrity of the mature virion24 and is involved in multiple replication steps including virion uncoating, nuclear export of the vRNP complex, and assembly and budding of newly formed viral particles23. These pleotropic, but highly coordinated, roles of M1 possibly arise from its propensity to assume multiple conformational states dependent on the local conditions, such as pH and lipid binding25262728293031. In fact, self-association or oligomerization (to maintain the integrity of the viral capsid at neutral pH) and de-oligomerization (to release the vRNPs in the late endosome at low pH) of the M1 layer are essential for viral replication32. At a molecular level, the M1 polypeptide monomer displays a three-dimensional surface that can be visualized as a ‘brick’ (Fig. 1). Self-association of M1 results in the formation of the M1 layer in mature virions, which is an elongated, non-covalent polymer underneath the envelope membrane that is critical for viral integrity. We reasoned that reducing the stability of the M1 layer by disrupting the self-association of M1 ‘bricks’ using an appropriate small molecule (or ‘wedge’) could be a powerful strategy to discover a completely new line of antiviral agents. ‘Wedges’ that bind to at least one of the M1-M1 interfaces could interfere with M1 layer formation resulting in deformed viral particles with impaired replication potential. This novel approach of targeting M1 for drug discovery is a high-risk venture because it involves disrupting the interaction of a large interface with a comparatively very small agent3334. However, with regard to M1 it may have some advantages. An appropriate small molecule need not completely prevent M1-M1 self-association, but alter it just enough to reduce the stability of the M1 layer. A second advantage, especially with regard to druggability of the target protein, is that self-association to form the M1 layer presents multiple sites of binding for a complementary ‘wedge’, which enhances the probability of destabilization of the M1 layer by a small molecule. Finally, a most important advantage is that the M1 protein is relatively more conserved than other IAV proteins151735 (see below), which can be expected to minimize the impact of selection pressures (either environmental or drug-induced). Results and Discussion Genetic Basis for Targeting M1 The M1 protein is one of the most highly conserved proteins in the IAV35. It has been shown to evolve at a much slower rate than even its cognate M segment product, the M2 proton channel17. Analysis of a large set of M1 and M2 sequences (vide supra) corroborates these findings. The M1 sequences show 29.8% identity and 57.5% similarity, whereas M2 sequences show only 2.1% identity and 20.6% similarity (Supplementary Fig. 1, 2, 3 and 4). More strikingly, mutations are extremely rare at many positions in M1. Very few sequences out of the hundreds possess a divergent amino acid residue, which results in a sequence conservation rate of nearly 100%. Further, the positions of lowest sequence identity in M1 are dominated by a few homologous amino acid residues (e.g., 15:V/I; 95:R/K; 101:R/K; 121:A/T; 142:V/A/G; 166:V/A; and 227:A/T). In contrast, significantly higher stereo-electronic variability is observed for positions of lowest sequence identity in M2 (e.g., 18:R/K/N; 28:V/I/D/T). Although M1’s high degree of conservation could be attributed to low evolutionary selection pressure compared to other IAV proteins (most notably HA and NA, which are known to mutate at a very high rate), it may also mean that sequence variation may compromise its ability to form a confluent protein coat, which is critical for other functions, such as stabilizing the viral envelope during membrane fusion23 and the nuclear export of viral ribonucleoproteins36. Thus, changes in the M1 sequence may be detrimental to the virus. This implies that disruption of M1 self-association by either kinetic or thermodynamic means will likely produce a deformed M1 layer, which might reduce viral replication potential. We posited that such disruption could be induced by small molecules that bind to one or more M1-M1 interfaces (Fig. 1). Virtual Screening Identifies a Number of Candidates That Could Target M1 To discover destabilizers of the M1 layer formation, we studied the nature of forces that support M1-M1 interaction using published crystal structures under different conditions2527293031. An M1 ‘brick’ interacts with a neighboring M1 through a combination of electrostatic and hydrophobic forces2629. One face of the brick, which includes the basic nuclear localization signal (NLS; 101RKLKR105) in one corner (designated here as the ‘P’ face), is positively charged, while the opposing face contains a collection of acidic residues (the ‘N’ face), thus favoring complementarity (Fig. 1b). Interestingly, a face containing a hydrophobic pocket (the ‘H’ face) is found adjacent to the ‘N’ and ‘P’ faces, which may serve as a “hot spot” for a small molecule to bind. We hypothesized that a ‘wedge’ could be identified by targeting such a hot spot in the neighborhood of the ‘N’ and ‘H’ faces (Fig. 1a). To identify such ‘wedges’, a virtual screening approach was employed using two drug-like libraries (Maybridge and LOPAC, 72,280 small molecules; Fig. 1c) resulting in the identification of several ‘hits’ (see Supplementary Figs 5 and 6 for all structures). In Vitro Studies Identify a Promising Anti-IAV Agent For initial screening, Madin-Darby Canine Kidney (MDCK) cells infected with H1N1 A/WSN/33 (WSN/33) were cultured with individual hit compounds at various concentrations. Forty-eight hours later, the supernatants were harvested for hemagglutination (HA) assay. Among the ten hit compounds identified from the first library, six (MRS, MIB, SAL, SKF, PHE and MIT) showed dose-dependent inhibition of in vitro replication of WSN/33, whereas the remaining four compounds (AMI, E64, MET and MES) had no obvious antiviral effects (Fig. 2a). Of the six inhibitors identified, MRS, MIB, SAL, SKF and MIT exhibited substantial cytotoxicity (Supplementary Fig. 10a). In contrast, PHE not only showed a high antiviral activity (Fig. 2a) but also possessed minimal cytotoxicity (Supplementary Fig. 10a). Four more compounds (PDS, RDR, SPB and HTS) were identified by screening the second library but each was found to be less effective than PHE at blocking WSN/33 plaque formation (Fig. 2b). Structurally, PHE is a small hydrophobic molecule of molecular weight ~400 that can be chemically synthesized in a few steps. Thus, it represented a promising molecule to further establish the concept of anti-IAV activity through inhibition of M1 self-association. Molecular Modeling Suggests PHE Binds to More Than One Site on M1 The initial virtual screening exercise relied on identifying agents that bind at a specific M1-M1 interface site, which was deemed promising from the perspective of discovering potential protein–protein interaction (PPI) inhibitors. The in vitro screening success with PHE implies that it may bind at the site predicted by the molecular modeling. It is possible that PHE also binds to alternative sites/interfaces, especially because it is a carboxylic acid derivative that possesses substantial flexibility as well as hydrophobic character, features that are complementary to multiple putative M1 binding sites. To assess this potential, we performed a comprehensive ‘blind’37 docking study. Forty-one overlapping binding sites were defined around basic, acidic, or hydrophobic side chains so as to cover the entire M1 surface. By utilizing a binding site identification strategy that relies on multiple scoring functions, which minimizes bias38, we identified four unique sites in addition to the original targeted site that afford favorable PHE binding characteristics (Supplementary Table 1 and Supplementary Figs 7 and 9). These sites were localized either directly on, or adjacent to, the ‘N’ and ‘P’ faces. Interestingly, one of the sites was found to be directly opposite to the initially identified site (Supplementary Fig. 8). Instructively, several studies have been reported on the role of some of residues likely to be present in the region surrounding the putative PHE binding site including K95, K98, R101, K102, K104 and R10524394041. These studies indicate that mutations at these positions significantly affect IAV morphology, replication and/or pathogenicity of the IAV, which support the expectation that PHE binding will disrupt M1-M1 interaction resulting in a deformed M1 layer. In a traditional drug discovery process, such promiscuity would be viewed as a limitation for a putative drug candidate. However, in the present context it is likely to be an advantage because multiple binding sites could engage more than one PHE molecule, thereby enhancing the probability of M1 layer destabilization (Supplementary Figs 7 and 9). Additionally, multi-site binding may also enhance the apparent affinity of the small molecule. Thus, the comprehensive modeling study indicates that PHE is likely to be a good candidate to critically assess the rationale of targeting M1 for the discovery of potent anti-IAV agents. Biophysical Studies Show PHE Binds to M1 and Prevents its Oligomerization To test whether PHE binds directly to M1, we utilized surface plasmon resonance (SPR)-based interaction studies (see Methods). M1 was immobilized on NeutrAvidin-gold chips using a biotinylated form of the protein. The association of soluble M1 with chip-bound M1 followed the expected binding profile at pH 7.4 (Fig. 3a). In contrast, the dissociation of M1 from bound M1 was much slower indicating that self-association is an off-rate driven process (Fig. 3b). Considering that M1 in solution may exist in dimeric or oligomeric forms29, the SPR kinetics lead to an apparent affinity of 50 ± 30 pM. The M1–PHE interaction was studied in a similar manner and displayed much faster association and dissociation rates (Fig. 3c,d). The ratio of off- to on-rate of interaction led to an affinity of 870 ± 150 nM at pH 7.4 for PHE binding to monomeric M1. This indicates a fairly tight binding interaction for a molecule as small as PHE. We then turned to bio-layer interferometry using Octet Qke equipped with streptavidin biosensor tips to assess whether PHE impairs M1 self-association (see Methods). This technique is particularly suited to assess oligomerization process as the signal is highly sensitive to changes in molecular weight of the tip-bound target. The increase in molecular weight following M1-M1 self-association shifted the wavelength of interference by more than 175% (Fig. 3e). In contrast, M1 in the presence of 1 to 50 μM PHE displayed reduced signal corresponding to a weakened oligomerization process. The plot of maximal response versus PHE concentration displayed a classic hyperbolic relationship, which gave an IC50 of ~6 μM and a maximal decrease in M1 chain extension of ~60% (Fig. 3f). This indicates that PHE disrupts M1 oligomerization at pH 7.4 with fairly high potency and efficacy. PHE Potently Disrupts M1 Layer Formation in Assembled Virions and Inhibits Replication of Multiple IAV Strains In Ovo Next we sought to assess PHE’s anti-IAV potential in an in vivo model. As a selective agonist of the nuclear transcription factor–peroxisome proliferator-activated receptor β/δ (PPARβ/δ), PHE has both pro-inflammatory and anti-inflammatory effects on host intermediary metabolism and immune regulation42, which can theoretically jeopardize our efforts to prove M1 as a druggable target. To overcome PHE-associated complications, we utilized embryonated hen’s egg, which is a preferred matrix for amplifying influenza viruses43 because of absence of mature immune defense. We co-injected WSN/33 with PHE into 10-day-old specific-pathogen-free embryonic eggs and then purified WSN/33 amplified in allantoic fluids for transmission electron microscopy (TEM). In the absence of PHE (vehicle only), WSN/33 mature virions were well-formed and of uniform size (Fig. 4a). More than 70% of these virions had a full complement of glycoproteins (spikes) on the surface (Fig. 4b,g). In contrast, virions prepared from PHE co-injected eggs were not only significantly lower in density but also much more variable in size (Fig. 4c,e). PHE co-injection also dramatically altered the morphology of WSN/33 viral particles (Fig. 4d,f vs b). In the presence of PHE, the frequency of fully spiked mature virions fell below 18%, while >82% of viral particles were either partially spiked or completely deprived of spikes (Fig. 4g). Under high magnification, the M1 layer in WSN/33 mature virions with vehicle only appeared as a clearly defined dark band underneath heavily spiked envelope (Fig. 4b). In contrast, the viral particles prepared from PHE co-injected eggs were either loosely coated (Fig. 4d) or completely stripped with a much thinner M1 layer underneath (Fig. 4f). Indeed, the thickness of the M1 layer was substantially reduced by PHE in a concentration-dependent manner (Fig. 4h). In the viral particle, envelope proteins HA and NA via their cytoplasmic tails interact with the M1 layer2344. PHE-induced destabilization of the M1 layer is likely to disfavor optimal interaction with HA/NA leading to the loss of spikes on viral particles. Thus, consistent with the biophysical data (Fig. 3), these results clearly indicate PHE is able to disrupt M1 layer formation in assembled virions resulting in the loss of strong hold of surface HA and NA. The consequence of this impairment is that both initiation of infection, which is mediated by HA, and release and spread of newly synthesized viruses, which are mediated by NA45, are made dysfunctional leading to inefficient virus replication. Indeed, PHE blocked the in ovo replication of WSN/33 in a dose-dependent manner (Fig. 4i). This antiviral activity of PHE was not due to cytotoxicity since all chicken embryos survived at the highest dose of 740 ng/g tested (Supplementary Fig. 10b). More significantly, PHE was also able to block the in ovo replication of different IAV strains including pandemic H1N1 A/Maryland/13/2012 (Fig. 4j), H3N2 A/Switzerland/9715293/2013 (Fig. 4k) and A/Fiji/2015 (Supplementary Fig. 11a), and H5N1 vaccine reassortants A/Indonesia/05/2005XPR8 (Fig. 4l) and A/Egypt/N03072/2010XPR8 (Supplementary Fig. 11b), all in a dose-dependent manner regardless of surface glycoproteins. For the viral strains studied, a high dose of ~740 ng/g was found to be sufficient to prevent 90% in ovo replication. These results support the principle that targeting M1 with small molecules such as PHE can generate broad spectrum anti-IAV activity. Summary This work demonstrates a novel principle that small hydrophobic molecules with drug-like properties (e.g. PHE MW~400; logD~1.5) can be potent anti-IAV agents (>90% inhibition at 740 ng/g) by impairing the process of M1 oligomerization. This anti-IAV drug design strategy—‘wedge’ disruption of M1 layer formation—belongs to the category of protein–protein interaction (PPI) inhibitors. Although several designed small molecules have been shown to successfully inhibit other PPIs3334, e.g., small molecule inhibitors of cIAP/SMAC, bromodomain/histone, MDM2/p53 systems, this is the first report to our knowledge of their successful design with regard to type A influenza virus. Although belonging to the category of PPIs, PHE belongs to a slightly different type of PPI. Whereas traditional PPIs inhibit formation of complex between one protein molecule with another protein molecule, PHE inhibits formation of the M1 layer, which involves a large number of M1 molecules. Inhibiting self-association, which could be thought of as a non-covalent polymerization process, is difficult. For a molecule as small as PHE (MW <500), the in vitro apparent affinity of 1 μM is therefore very promising. This potency decreases significantly in viral replication assays (50 μM) most probably due to factors such as efficacy of host cell penetration, binding to proteins such as ovalbumin, etc. However, such loss in potency when moving to in vivo systems is also found for most drugs suggesting that a clinically relevant PHE-like drug may be realized through our new ‘wedge’ design strategy. Although PHE was demonstrated to be a promising anti-IAV agent in this study, literature reports that PHE influences host intermediary metabolism, inflammation and immune regulation42. These effects on the host may limit PHE’s clinical development. Yet, the identification of PHE as the first M1-targeting molecule implies that clinically relevant anti-IAV agents are possible to develop using the ‘wedge’ design strategy. Although PHE most probably targets multiple sites on M1, appropriate analogs of PHE may be possible to design so as to uniquely target an M1 interface/site. In fact, PHE affords a number of opportunities for developing advanced agents through structural modifications of its functional groups such as phenolic OH, carboxylic acid and ethyl substitution. Overall, considering that M1 is highly conserved across IAV strains and the M1 ‘wedge’ design is a unique principle, this work puts forward a completely new paradigm of targeting M1 to derive broad spectrum antivirals with far-reaching clinical benefits in the near future. Methods Sequence Alignment Primary amino acid sequences corresponding to the M1 protein and the M2 proton channel were downloaded from the NCBI Influenza Resource Database46 (http://www.ncbi.nlm.nih.gov/genomes/FLU/FLU.html). Unless otherwise noted, default settings were used. The ‘Protein’ option was set to either M1 or M2 as necessary. The ‘Full-length only’ option was set to exclude fragments. To ensure that an equal number of M1 and M2 sequences were included in the initial search, only those sequences that were part of a complete influenza genome were considered by checking the ‘Select all’ option in the ‘Required segments’ section. Identical sequences were culled from the list using the ‘Collapse identical sequences’ option. The two M1 sequence data sets were then merged, sorted and duplicate sequences removed. Finally, M1 and M2 sequences with undefined amino acids (‘X’) were removed. The resulting 742 M1 and 1282 M2 sequences represent a large time span (1925–2015) and diverse geographic locations, hosts, and strains (including highly pathogenic avian H5N1, pandemic-associated swine H1N1 and seasonal H3N2). Each set of sequences was then aligned in ClustalX 2.047 using default parameters. Percent identity was calculated in the usual way and percent similarity was calculated using the formula (I + S)/T, where I is the number of fully conserved (i.e. identical) positions, S is the number of positions that exhibit ‘strong’ conservation (as defined in ClustalX), and T is the total number of sequence positions (T = 252 for M1 and 97 for M2). The aligned sequences were analyzed using JProfileGrid 2.048. Virtual Screening The crystal structure of the M1 N-terminal N1–165 domain of H1N1A/WSN/33 determined at pH 5.5 (PDB = 4PUS; chain A)29 and the crystal structure of the M1 N-terminal N1–164 domain of H1N1 A/PR/8/34 determined at pH 7 (PDB ID = 1EA3; chain B)25 were used to virtually screen compound libraries. For the 4PUS structure, the conformation of the C-terminal residue Q158 side chain was modified by setting its torsion angles (χ1 = −177°; χ2 = 65°; χ3 = 60°) to those of a rotamer from the Penultimate Rotamer Library49 that allowed access to the hydrophobic pocket on the “H” face from the electronegative “N” face, similar to the 1EA3 structure (see main text for details). SYBYL-X 2.1 (Certara Inc., St. Louis, MO) was used to add hydrogen atoms to the crystal structures, generate Connolly surfaces and the corresponding electrostatic (Gasteiger–Hückel charges) and lipophilic (computation method = protein; Crippen table = Ghose et al.1998) potential maps (Fig. 1b). Virtual libraries of ready-to-dock structures representing the LOPAC and Maybridge databases were downloaded from ZINC (http://zinc.docking.org)50. Virtual screening was accomplished using GOLD Suite 5.151 and the Goldscore fitness function with default parameters; the top-scoring solution was retained for each ligand. The ligand binding site was defined to encompass a 12 Å radius about the Cα atom of E152, located at the center of the negatively charged surface on the “N” face of the M1 protein. This binding site definition covers major grooves on this side, as well as the hydrophobic pocket on the “H” face. Up to ten docking runs were performed for each ligand, with early termination enabled such that docking terminated when the best three solutions found were all within 1.5 Å RMSD. For the LOPAC library, a molecular weight filter was used to remove compounds larger than 500 Da. The top 20 highest-scoring compounds were considered, from which a final subset of ten were selected based on structural diversity (Supplementary Fig. 5). For the Maybridge library, the top 100 highest-scoring compounds were considered, from which a subset of seven were selected based on structural diversity; this list was further reduced by applying a ‘reactivity’ filter that removed compounds possessing a reactive thiol group, resulting in a final selection of four compounds (Supplementary Fig. 6). Selected compounds from the LOPAC and Maybridge libraries were subsequently ordered from MolPort. Blind Docking of PHE A blind docking technique was used to search for alternative PHE binding sites on the M1 surface. GOLD was used to dock PHE to overlapping binding sites over the entire surface of the N1–164 region of an M1 monomer (‘B’ chain of PDB entry 1EA3 with modified Q158 side chain as described above). A total of 41 potential binding sites were defined, each encompassing a 12 Å radius about the Cα atom of an amino acid residue whose side chain is a) basic, b) acidic, or c) hydrophobic and at the center of a surface-exposed hydrophobic patch or pocket (Supplementary Table 1). As such, these residues are important contributors to potential small-molecule binding “hot spots”. Ten docking runs were performed for PHE at each site and with four different scoring functions available in GOLD: ASP52, Chemscore5354, Goldscore5155 and ChemPLP56. The best-scoring docked PHE solution for each combination of site and scoring function was selected for further analysis. For each scoring function, the PHE-bound sites were ranked from best to worst, with 1 being the best. To remove the influence of bias in any given scoring function, a consensus rank was also assigned to each site by summing the ranks of the four individual scoring functions and ranking the resulting sums in ascending order (Supplementary Table 1). The top-ranked docked solutions and their corresponding M1 binding sites are depicted in Supplementary Figs 8 and 9. In vitro Inhibition of Virus Replication Madin-Darby Canine Kidney (MDCK) epithelial cells (80–90% confluence) were infected with H1N1 A/WSN/33 (WSN/33) at indicated multiplicity of infection (MOI) for 1 h. After removal of inoculum, MDCK cells were incubated with Opti-MEM medium containing 1 μg/ml of TPCK-treated trypsin and test compounds at various concentrations at 33 °C, 5% CO2. Forty eight hours later, supernatants were harvested for HA titer determination using 0.5% turkey erythrocytes. The ability of test compounds to inhibit WSN/33 plaque formation was determined using an improved plaque assay57. Briefly, MDCK cells confluent in 12-well plates were inoculated with 100 PFU WSN/33 per well at 33 °C, 5% CO2 for 1 h. After the virus inoculum was removed, MDCK monolayers were overlaid with 1.2% Avicel containing 1 μg/ml of TPCK-treated trypsin with or without testing compounds and were incubated without disturbance for another 48 h to allow plaque formation. MDCK monolayers were then fixed with methanol and WSN/33 plaques were counted after staining with 1% crystal violet. In a separate experiment, cell viability after compound treatment was determined using the MTT assay. Surface Plasmon Resonance (SPR) The interaction of M1 with M1 in the presence and absence of PHE was studied using a Reichert SR7500DC optical biosensor. NeutrAvidin sensor chips (Reichert Technologies, Depew, NY, USA) were used for capturing biotinylated M1 and Scrubber (Version 2.0c, 2008, BioLogic Software) was used for processing the data. Two biotinylated M1 protein chips were prepared utilizing recombinant M1 protein expressing the N1-165-domain of WSN/3329 and a biotin-avidin immobilization strategy. One chip was used to study M1–PHE interaction. Biotinylated M1 protein (50 μM) in 10 mM HEPES buffer, pH 7.4 containing 150 mM NaCl, 3.4 mM EDTA, and 0.05% Tween 80 was injected onto NeutrAvidin sensor chip for ~40 min with a constant flow of 5 μL/min at 10 °C. An immobilization level of ~700 μRIU was achieved. For M1–PHE interaction study, PHE at varying concentrations (1.67, 3.33, 12.5, 25 and 50 μM) was injected over the biotinylated M1 protein chip at flow rate of 20 μL/min and room temperature. Association and dissociation of PHE was monitored for 1–3 min. The increase in SPR signal was proportional to the PHE concentration. The association and dissociation rates were used to calculate the binding constant. To study M1-M1 interaction, biotinylated M1 of 10 μM was injected over the NeutrAvidin sensor chip for ~5 min with a constant flow of 30 μL/min at 10 °C. An immobilization response of 150 μRIU was achieved. For the M1-M1 interaction study, M1 at 71, 143, 300 and 570 nM concentrations was injected as described above for M1–PHE interaction at flow rate of 30 μL/min and room temperature. Association and dissociation kinetics was monitored for over 5 min and the affinity was calculated by averaging the affinities at each concentration. Bio-layer Interferometry (BLI) Octet Qke biolayer interferometer equipped with streptavidin biosensor tips (ForteBio, Inc., Menlo Park, CA, USA) was also used to assess the effects of PHE on the M1-M1 interactions. Biotinylated M1 was loaded onto streptavidin biosensor tips in pH 7.4 PBS solution containing 0.01% BSA and 0.002% Tween-20 (kinetics buffer) until the response reached 1 nm. The biotinylated M1 coated biosensor tips were then dipped in pH 7.4 kinetics buffer containing 10 μM unbiotinylated M1 with or without PHE at various concentrations for 1200 seconds. The entire measure cycle was maintained at 30 °C with orbital shaking at 1000 rpm. PHE Toxicity and Inhibition on in ovo Virus Replication All 10-day-old embryonic eggs were specific-pathogen-free and were candled to ensure viability and good quality before each inoculation. A DMSO solution of PHE in pH 7.4 PBS (1:25 v/v, final DMSO level was 4%) was injected into 10-day-old embryonic eggs at 0.1 ml/egg. The doses of PHE tested included 150, 372, 554 and 740 ng/g, which was normalized based on the average weight of 10-day-old embryonic eggs. Eggs injected with 0.1 ml/egg of vehicle (DMSO diluted in pH 7.4 PBS, 1:25 v/v) served as controls. Each PHE dose was tested in 5 eggs. Injected eggs were then incubated at 37 °C for three days. The viability of embryos was monitored daily. In separate experiments, representative IAV strains H1N1 A/WSN/33 (WSN/33), pandemic H1N1 A/Maryland/13/2012 (pdm H1N1 MD/12), H3N2 A/Switzerland/9715293/2013 (SWZ/13) and A/Fiji/2/2015 (Fiji /15), and H5N1 vaccine reassortants A/Indonesia/05/2005XPR8 (IN/05XPR8) and A/Egypt/N03072/2010XPR8 (EG/10XPR8) (both reassortants have the multibasic cleavage motif removed from H5 HA and are in A/PR8/34 backbone) were co-injected with PHE at different concentrations into 10-day-old embryonic eggs. Three days later, allantoic fluids were harvested from individual eggs and were tested for HA titers using 0.5% turkey erythrocytes (H1N1, pdm H1N1 and H5N1) or 0.75% guinea pig erythrocytes (H3N2)3. Transmission Electron Microscopy (TEM) WSN/33 was co-injected into 10-day-old embryonic eggs with or without PHE. Allantoic fluids were harvested and were subjected to purification by ultracentrifugation (30,000 rpm × 90 min, 4 °C)24. Purified viruses were fixed with 2% paraformaldehyde and 2% glutaraldehyde in PBS pH7.3 at room temperature overnight followed by three brief washes in PBS buffer and then post-fixation with 1% osmium tetroxide for another 1 h. After dehydration and infiltration, fixed viruses were embedded in epoxy resin and were subjected to ultra-microtome cutting. Ultrathin sections were then stained with uranyl acetate and lead citrate and were examined under a Zeiss Libra 120 Plus transmission electron microscope. TEM images were acquired using a Gatan US1000XP digital camera. Approximately 100 virions per treatment were randomly counted under TEM and % of fully spiked, partially spiked and completely stripped virions were determined. The M1 layer thickness of individual virions was determined by averaging the measures at 3, 6, 9 and 12 o’clock under TEM respectively24. Eleven to twelve representative virions per treatment were analyzed. Statistical Analysis One-way analysis of variance (ANOVA) was conducted using GraphPad Prism Version 6.02. A P value of < 0.05 was considered significant. Additional Information How to cite this article: Mosier, P. D. et al. Broad Spectrum Anti-Influenza Agents by Inhibiting Self-Association of Matrix Protein 1. Sci. Rep. 6, 32340; doi: 10.1038/srep32340 (2016). Supplementary Material Supplementary Information We thank Yingzi Jin of VCU for performing SPR experiments and Dr. Zhiping Ye of CBER/FDA for providing H5N1 vaccine reassortants. This work was supported by grants HL090586, HL107152 and HL128639 from the National Institutes of Health to URD. We also thank the computational facility provided by National Center for Research Resources to Virginia Commonwealth University through grant S10 RR027411. Author Contributions P.D.M. performed sequence alignments and analysis, designed and performed virtual screening and wrote the paper; M.-J.C., Z.L. and H.X. performed viral replication assays and biophysical studies; Y.G., M.-J.C. and Z.L. conducted TEM experiments; Q.Z. and H.X. analyzed viral replication and biophysical data; B.A. performed SPR analysis; F.M., M.K.S. and Q.Z. contributed insights into M1 oligomerization; H.X. and U.R.D. supervised study, wrote and finalized the paper. Figure 1 A putative mechanism of M1 layer disruption by small molecules. (a) Disruption of the M1 layer by a small-molecule ‘wedge’. Blue and green blocks represent adjacent M1 dimers, gray patches represent the binding site that extends across two faces of M1, and the red cone represents the disrupting small-molecule ‘wedge’. (b) The crystal structure of the M1 N-terminal domain at neutral pH (PDB ID = 1EA3). An M1 binding site consisting of the negatively charged (“N”) face and its adjacent hydrophobic pocket (“H”) face was studied for discovering wedges. Shown are electrostatic (blue = positive; red = negative) and hydropathic (blue = hydrophilic; brown = hydrophobic) surfaces. The nuclear localization signal (NLS; 101RKLKR105) motif is shown in magenta. (c) The virtual screening algorithm used to identify the lead compound PHE. Figure 2 In vitro inhibition of virus replication. (a) Among the top ten virtual screening hits, six compounds including PHE cause a dose-dependent reduction in HA geometric mean of titer (GMT) of H1N1 A/WSN/33 (WSN/33) replicated in MDCK cells (n = 2–6 replicates). (b) Only PHE significantly reduces WSN/33 plaque formation on MDCK monolayer (n = 3 replicates). See Methods for detailed procedure. Figure 3 PHE inhibits M1-M1 association. The interaction of M1 with PHE was followed by SPR using biotinylated M1 chips. Panels (a,b) show the association and dissociation phases of the M1–M1 interaction, respectively, while (c,d) show the association and dissociation phases of the M1–PHE interaction, respectively. (e) Bio-layer interferometry (BLI) response curves for M1 self-association with varying concentrations of PHE. (f) A plot of maximal BLI response versus PHE concentration projecting an IC50 value of ~6 μM. Figure 4 In ovo disruption of the M1 layer formation and inhibition of viral replication. TEM images of H1N1 A/WSN/33 (WSN/33) at low magnification in panels (a,c,e) and at high magnification in corresponding panels (b,d,f) show that the morphology of virions purified from vehicle-treated control eggs (a,b) is different from those purified from PHE (c,d: 36 ng/g; e,f: 73 ng/g) co-injected eggs. (g) Percent distributions of fully spiked, partially spiked and completely stripped WSN/33 virions purified from eggs with or without PHE treatments. (h) PHE reduces the thickness of the M1 layer in WSN/33 viral particles in a dose-dependent manner. PHE also induces a dose-dependent reduction in HA geometric mean of titer (GMT, black lines) of different IAV strains propagated in embryonic eggs, including (i) H1N1 A/WSN/33 (WSN/33), (j) pandemic H1N1 A/Maryland/13/2012 (pdm H1N1 MD/12), (k) H3N2 A/Switzerland/9715293/2013 (SWZ/13), and (l) H5N1 vaccine reassortant A/Indonesia/05/2005XPR8 (IN/05XPR8). One-way ANOVA was performed to compare the differences between vehicle only and PHE treatments. HA titers were log-transformed before the analysis. *Indicates P < 0.05; **indicates P < 0.01; ***indicates P < 0.001. ==== Refs Reed C. . Estimated Influenza Illnesses and Hospitalizations Averted by Vaccination—United States, 2013–14 Influenza Season . Morb. Mortal. Wkly. Rep. 63 , 1151 –1154 (2014 ). Shi Y. , Wu Y. , Zhang W. , Qi J. & Gao G. F. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3241010.1038/srep32410ArticleMitochondrial role in adaptive response to stress conditions in preeclampsia Vishnyakova Polina A. a12Volodina Maria A. 1Tarasova Nadezhda V. 1Marey Maria V. 1Tsvirkun Daria V. 1Vavina Olga V. 1Khodzhaeva Zulfiya S. 1Kan Natalya E. 1Menon Ramkumar 3Vysokikh Mikhail Yu. 12Sukhikh Gennady T. 11 Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Healthcare of the Russian Federation, 4, Oparina street, Moscow, 117513, Russia2 Belozerskii Institute of Physico-chemical Biology, Moscow State University, Moscow, Leninskie gory 1, 119992, Russia3 Department of Obstetrics and Gynecology, University of Texas Medical Branch at Galveston, TX, 77555, USAa vishnyakovapolina@gmail.com30 08 2016 2016 6 3241029 04 2016 09 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Preeclampsia (PE) is a pregnancy-specific syndrome, characterized in general by hypertension with proteinuria or other systemic disturbances. PE is the major cause of maternal and fetal morbidity and mortality worldwide. However, the etiology of PE still remains unclear. Our study involved 38 patients: 14 with uncomplicated pregnancy; 13 with early-onset PE (eoPE); and 11 with late-onset PE (loPE). We characterized the immunophenotype of cells isolated from the placenta and all biopsy samples were stained positive for Cytokeratin 7, SOX2, Nestin, Vimentin, and CD44. We obtained a significant increase in OPA1 mRNA and protein expression in the eoPE placentas. Moreover, TFAM expression was down-regulated in comparison to the control (p < 0.01). Mitochondrial DNA copy number in eoPE placentas was significantly higher than in samples from normal pregnancies. We observed an increase of maximum coupled state 3 respiration rate in mitochondria isolated from the placenta in the presence of complex I substrates in the eoPE group and an increase of P/O ratio, citrate synthase activity and decrease of Ca2+-induced depolarization rate in both PE groups. Our results suggest an essential role of mitochondrial activity changes in an adaptive response to the development of PE. ==== Body Preeclampsia (PE) is a pregnancy-specific syndrome, characterized by hypertension with proteinuria or thrombocytopenia, renal insufficiency, impaired liver function, cerebral or optical disorders or pulmonary edema after the 20th week of gestation12. PE affects 2–8% of all pregnancies worldwide and still remains the major cause of maternal and fetal death23. This disease is characterized by a decrease of trophoblast invasion and abnormal remodeling of spiral arteries4. Specialists distinguish two types of PE: early-onset and late-onset, depending on gestation age. Most investigators consider early-onset PE (eoPE) as that occurring before 34 weeks and late-onset PE (loPE) occurs after this time56. EoPE is typically characterized by intrauterine growth restriction, decrease of placental weight, low baby mass, perinatal death, and unfavorable outcomes. LoPE is marked by normal placenta weight, normal fetal growth, normal baby weight, and more favorable outcomes7. Despite the large body of data, PE etiology remains unclear. However, it is now known that placental insufficiency plays a key role in the progression of this disease. PE was first suggested to be a mitochondrial disorder at the end of 1980s8. Later, it was shown that mitochondrial dysfunction in the PE placenta induces oxidative stress91011. There is accumulating evidence for antioxidant system decline (down-regulation of superoxide dismutase and glutathione peroxidase) and up-rise of reactive oxygen species (ROS), mainly produced by mitochondria at PE121314. Loss of mitochondrial control of ROS levels in the cell makes a significant contribution to the pathophysiology of PE. Ultrastructural data, obtained with electron microscopy, showed mitochondrial swelling and vacuolation, along with the disappearance of cristae in mitochondria from trophoblast cells of PE placentas1516. Taken together, partial functional incompetence and altered morphology of mitochondria reflect common features of mitochondrial disorders presented in PE. Both morphology and function strongly depend upon the state of mitochondrial biogenesis, including fission, fusion and mitochondrial DNA (mtDNA) turnover, transcription and respiration rate. However, the number of studies that have investigated placental mitochondrial molecular machinery during PE is limited. Thus, the aim of our study was to identify mitochondrial structural and functional properties in placenta samples from three groups of pregnant women: eoPE, loPE, and normal pregnancies. In our work, we examined the bioenergetics of placental mitochondria, the expression level of factors that play a key role in mitochondrial fusion (mitofusin-1–MFN1, mitofusin-2–MFN2, mitochondrial dynamin like GTPase – OPA1), fission (dynamin-related protein 1–DRP1), biogenesis (nuclear respiratory factor 1–NRF1), mitochondrial permeability (voltage-dependent anion-selective channel protein 1–VDAC1) and activation of mtDNA transcription (mitochondrial transcription factor A–TFAM). Results Clinical characteristics of all women who took part in the study are shown in Table 1. Cell immunophenotype and viability To characterize cell viability and the cellular composition of placenta, we used flow cytometry analysis. Cells were analyzed after short-term cultivation at first passage and there were no significant differences in percentage of viability (%) between groups: CTRL 73.4 ± 3.5; eoPE 76.4 ± 2.9; loPE 68.8 ± 3.1, values shown as mean ± SD. To characterize cell population structure we chose five proteins: trophoblast-specific intracellular marker cytokeratin 7 (Cyt7)17, a transcription factor of tropho-ectoderm development SOX2, a marker of endothelial precursors–Nestin and also Vimentin and CD4418, markers of mesenchymal and stromal cells, respectively. In all cases, cells from short-term cultivated placental primary cultures were positive for the chosen markers, but there were no significant differences in the percentage of positive-stained cells between groups (Supplementary Table S1). Changes in mRNA level Mitochondrial fusion and fission play a key role in mitochondrial quality control and are controlled by the nuclear genome. We chose three genes essential for mitochondrial fusion (MFN1, MFN2, OPA1), biogenesis (NRF1) and the TFAM gene, which is an activator of mtDNA transcription. To determine whether there is a difference between mRNA expression among groups, we used quantitative RT-PCR, using the β-actin gene as internal reference (Fig. 1a). We observed a significant 2.5-fold increase of OPA1 relative expression level in the eoPE group in comparison with control placenta samples (p = 0.001), whereas there was no difference between control and loPE. Simultaneously, no changes were found either in MFN1, MFN2 or NRF1 relative expression levels for all investigated groups. However, we found that the TFAM level was 1.8-fold lower in loPE placentas (p = 0.005), while, in the eoPE group, expression had no difference compared to the control group. Protein expression of VDAC1, OPA1, DRP1, and TFAM in placentas from preeclamptic and normal pregnancies Protein expression level of VDAC1, a major protein found in the outer mitochondrial membrane, appeared to be the same in both preeclamptic and control placentas (Fig. 1b). For OPA1, an inner membrane fusion protein, we compared the level of two forms: cleaved (S-OPA1) and uncleaved (L-OPA1). We found that relative expression of both OPA1 forms was 3-fold higher (p < 0.0001 for S-OPA1 and p = 0.0004 for L-OPA1) in eoPE placentas than in normal ones (Fig. 2a,d). On the other hand, OPA1 level did not change in loPE compared to control. Interestingly, there was no difference in DRP1 expression level, an important protein responsible for mitochondrial fission (Fig. 1c). We obtained a 5-fold decrease of TFAM expression in eoPE group in comparison with normal pregnancies (p = 0.002). As Fig. 2b,e shows, a similar effect was observed in loPE samples, but this result was not significant (p > 0.05). Anti-OPA1 and anti-TFAM staining of all remaining samples from studied groups is available in Supplementary Information (Supplementary Fig. S1). Immunohistochemistry of placenta To verify OPA1 protein level changes we performed pilot immunohistochemical experiment with 3 placenta samples from each studied group. Representative images are shown in Fig. 3. Staining for OPA1 was 1.5-fold more intense in the placental tissue from eoPE compared with the normal placentas (Mean fluorescence intensity (MFI): isotype-matched control 15.0 ± 0.5; CTRL 33.3 ± 3.6; eoPE 48.2 ± 3.2*; loPE 33.8 ± 5.8, values shown as mean ± SD, *p < 0.01 versus control) and this result is consistent with Western blotting analysis. Staining in loPE was similar to control placentas. Determination of mtDNA quantity and citrate synthase activity mtDNA copy number was measured in frozen placenta samples by qPCR using primers for the D-loop region, the MT-ND2 gene, and the single copy nuclear gene–β-2-microglobulin. We observed a significant 1.5-fold increase (p = 0.04) of relative mtDNA copy number in the eoPE group. mtDNA copy number in control and loPE placentas were not significantly different from each other (Fig. 4a). To verify if increase in mtDNA content in eoPE is associated with increase in mitochondrial mass, we performed citrate synthase activity assay. We observed significant increase in citrate synthase activity in both PE groups (p < 0.05) (Fig. 4b). Mitochondrial respiration To estimate mitochondrial respiration, we used standard protocols, described in Methods section. The maximum coupled state 3 respiration rate in presence of complex I (CI) substrates was significantly increased in eoPE (p = 0.006 ), but not in loPE compared with the control group (CTRL 6.7 ± 3.8; eoPE 12.3 ± 4.2; loPE 7.3 ± 2.7) (Fig. 5a). The maximum coupled respiration rate in presence of complex II (CII) substrates slightly decreased in both PE groups, but the difference was not statistically significant. We also obtained a tendency to increase the ratio of maximum noncoupled respiration rate to coupled non-stimulated respiration rate (E/L ratio) in presence of CII substrate in the eoPE group (p = 0.07) and a tendency to decrease in the loPE group (p = 0.06) compared to control (CTRL 5.7 ± 1.7; eoPE 7.5 ± 2.7; loPE 3.4 ± 1.7) (Fig. 5b). Moreover, we determined the P/O ratio (phosphate/oxygen ratio)–the number of phosphate atoms incorporated as ATP per atom of oxygen consumed during oxidative phosphorylation. In the presence of CII substrate, the P/O ratio was increased both in eoPE and loPE groups (p = 0.002 and 0.04, respectively) compared to the control group (CTRL 1.1 ± 0.65; eoPE 3.0 ± 1.3; loPE 2.9 ± 0.3) (Fig. 5c). Mitochondrial membrane potential We measured changes in mitochondrial transmembrane potential caused by application of Ca2+ and carbonyl cyanide p-trifluoro-methoxyphenyl hydrazone (FCCP) to a mitochondrial suspension, followed by detection of fluorescence changes of safranin O. As shown in Fig. 6a, we found that calcium sensitivity in both PE groups was significantly lower than in control placentas (p < 0.05). However, we did not observe any significant difference in mitochondrial membrane potential (ΔΨ) during FCCP titration (Fig. 6b). Discussion Preeclampsia is a pregnancy-specific syndrome, characterized in general by hypertension with proteinuria or other systemic disturbances. An increase of oxidative stress in the preeclamptic placenta could be explained by a sequential chain of events including poor trophoblast invasion, failed spiral artery remodeling, and an ischemia-like state with further reperfusion caused by fluctuations of oxygen levels in conditions of reduced fetomaternal blood flow19. In our study, we estimated the condition of molecular machinery associated with fulfillment of mitochondrial function in placentas from pregnancies complicated with PE. An important aspect of our study was the characterization of placental biopsy primary cultures after short-term cultivation. There were no significant differences in the cell composition of placentas between the control, eoPE, and loPE groups, although all biopsy samples were stained positive for Cyt7, SOX2, Nestin, Vimentin, and CD44. Despite the result was not substantial we explain such a big difference in percent of Cyt7-positive cells between control and eoPE groups by early gestational age of placenta20. Taking together this data could mean that a reason of PE symptoms is not the changes in cellular composition, but rather alterations of cell functioning. Mitochondrial activity correlates with organelle state and depends on the degree of mitochondrial fragmentation, biogenesis and dynamic of mtDNA turnover rate and stability. The mitochondrial network is highly dynamic and is precisely regulated, especially in stressful conditions. Decreased activity of the antioxidant system and increased ROS could lead to induction of mitochondrial permeability transition (MPT) and, as a result, to the swelling of mitochondria, outer membrane rupture, and proapoptotic factors release21. It is well known that calcium homeostasis contributes to the proper functionality of mitochondria–low Ca2+ activates matrix dehydrogenases and respiration whereas high concentration of Ca2+ promotes MPT22. Surprisingly, we found a significant decrease of Ca2+-induced mitochondrial membrane depolarization rate in both PE groups in comparison to the control. This decrease of mitochondrial sensitivity to Ca2+ could be an adaptive response with aim to prevent excessive apoptosis in placenta caused by MPT opening, manifested in oxidative stress23, typical for PE. A recent study by Haché and colleagues24 also demonstrated a decrease in calcium transport in mitochondria from preeclamptic syncytiotrophoblasts. On the other hand, we did not find a difference in the rate of ΔΨ changes between groups when protonophore FCCP was added to mitochondria. The index of oxidative phosphorylation efficiency (P/O ratio) increased in both PE groups compared to control. It is known that high P/O corresponds to high value of proton motive force2526. However, correlation between proton motive force and mitochondrial membrane potential exists and this fact together with our observation led us to presume probable increased risk of ROS formation by PE placental mitochondria at high ΔΨ in state 427. In our case, it is manifested in high efficiency of energy production. Indeed, it is well known that oxidative stress appears in the PE placenta11142829. The high P/O ratio and ROS production seem to be positively coregulated2730. It should be noted, that results concerning mitochondrial bioenergetics were observed on isolated mitochondria derived mainly from placental cytotrophoblast, whereas the remaining results were obtained on placental tissue homogenate. In our study we made an assumption that we observed the same molecular changes in particular mitochondrial fraction and whole tissue homogenate. Furthermore, it is essential to recognize type and estimate the value of adaptive response of the mitochondria quality control system to PE oxidative stress conditions. Among other proteins, OPA1 is an essential component of the mitochondrial quality control system31. This nuclear encoded polypeptide is localized in the inner mitochondrial membrane and takes part in mitochondrial fusion processes. While mutations in the OPA1 gene induce autosomal dominant optic atrophy (ADOA), this protein also regulates apoptosis and takes part in mtDNA maintenance32. Müller-Rischart and colleagues33 demonstrated that the OPA1 gene is a target of NF-κB-responsive promoter elements (e.g. NEMO–NF-κB essential modulator) which is upregulated in stressful conditions, particularly in PE34. We observed that in the eoPE group, OPA1 expression was significantly higher compared to control, for both transcript and protein levels. Studies on mice showed that OPA1 overexpression protects mitochondria from apoptotic-related cristae remodeling and cytochrome c release events35. Thus, in cases of severe forms of pathology, up-regulation of OPA1 in eoPE could be an essential part of the protective mechanism with its role in stabilization of appropriate mitochondrial structures. Having analyzed mtDNA, we observed increase in copy number in the eoPE group. In maternal blood, mtDNA copy number was also significantly higher in samples from women with PE36. Simultaneous up-regulation of OPA1 and an increase in mtDNA copy number could be interrelated in eoPE. Previous works indicate that mtDNA copy number and exon 4b abundance in OPA1 transcripts are coregulated: exon 4b-encoded peptide could bind to mtDNA to make it available for replication or transcription37. Perhaps OPA1 up-regulation promotes increase of mtDNA copy number by stabilization of mitochondrial nucleoid. In addition, a decrease in mtDNA copy number in blood lymphocytes of ADOA-1 patients38 and in HeLa cells with OPA1 knockdown39 was shown. We hypothesize that OPA1-driven segregation and distribution of mitochondrial nucleoids between mitoplasts occurred before fission and selection of mitochondria/mtDNA are triggered by the mitochondrial quality control system. We observed an acceleration in coupled respiration on CI (state 3), which was in agreement with increased mtDNA copy number and probability of OPA1-driven cristae remodeling. Kushnareva and colleagues39 showed that OPA1 knockdown leads to a reduction of mtDNA copy number, deterioration of mitochondrial Ca2+ retention capacity and ADP-induced respiration (state 3) in HeLa cells. Our findings concerning the effect of Ca2+ on placental mitochondria, increase in mtDNA copy number and changes in mitochondrial bioenergetics in eoPE are consistent with observations of Kushnareva and colleagues. Since TFAM is an essential activator of mtDNA transcription, replication and participant of mtDNA packaging4041, changes in TFAM expression could generally affect mitochondrial functionality and production of subunits encoded in mtDNA42. In the present study, we observed a significant decrease of TFAM mRNA expression in the loPE group and a reduction of TFAM protein in eoPE samples, as compared to the control group. It was widely believed that TFAM expression and mtDNA copy number are co-regulated. Ekstrand and colleagues43 observed that TFAM knockout in mouse embryos caused a reduction in mtDNA copy number. In contrast, one study did not reveal the influence of TFAM expression on mtDNA copy number in cells44. To explain the increase of mtDNA copy number and low TFAM level in the eoPE group, we used the model of mtDNA titration by TFAM, proposed in review by Kang45. According to this model, bound TFAM is involved in architecturally maintaining mtDNA whereas mtDNA-free TFAM is unstable in mitochondria and degrades rapidly. Due to the active replication of OPA1-stabilized mtDNA, TFAM is dissociated and degraded. Then, increased phosphorylating potential and efficiency of mitochondrial respiration in eoPE are required to support the sufficient rate of ATP-dependent LONP1-driven degradation of TFAM46 and to ensure functioning of HSP70, up-regulated in PE12. In summary, we proposed that mitochondrial state changes in early-onset preeclamptic placentas are accompanied by OPA1 up-regulation, decrease of Ca2+-induced depolarization rate, active mtDNA replication and, as a consequence, a high respiration rate in presence of complex I substrate, high P/O ratio and down-regulation of TFAM. Mechanisms that lead to similar mitochondrial activity changes (Ca2+-induced depolarization rate, citrate synthase activity and P/O ratio) in loPE could be different and associated with other molecular pathways. For example, improvement of substrate phosphorylation in mitochondrial matrix based on the mitochondrial phosphoenolpyruvate carboxykinase and the succinate-CoA ligase activity could take place. This process is not dependent from proton motive force and not coupled to respiration, but leads to similar effect in ADP consumption and production of ATP or GTP at conditions of hypoxia47. Indeed, this could be indirect explanation of decrease in Ca2+-induced depolarization rate due to mitochondrial dehydrogenases are Ca2+-dependent enzymes. Last, observed increase of citrate synthase activity allows to suggest activation of substrate phosphorylation in loPE. These aspects are thoroughly investigated and will be described in our future work. Abnormal trophoblast invasion in the early stages of development results in perturbed gas exchange between the mother, placenta, and fetus. Placental mitochondria begin to work more effectively to compensate for reduced oxygen delivery by enhancing resistance to endogenous uncouplers. Increased calcium sequestering by mitochondria could lead to a decrease of NO production by nitric oxide synthase, which results in inhibition of vasculogenesis and further deterioration of feto-placental blood turnover. Thus, probably there are two processes that run simultaneously–the first is cristae remodeling and the second is the distribution of nucleoids. Both processes are required to ensure the quality of mitochondria. We assume that the probable segregation of mtDNA could precede mitoplast fragmentation, mitochondrial fission, and disruption of the whole mitochondrial reticulum. Such segregation occurs before mitoplast separation underneath the intact outer mitochondrial membrane and could be a prerequisite for further selection of mitochondria with intact mtDNA by the quality control system. Methods Ethics Statement All experiments involving placental tissue were conducted in accordance with the Declaration of Helsinki, guidelines for Good Clinical Practice and Commission of Biomedical Ethics at Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Healthcare of the Russian Federation. All experimental protocols were approved by the Commission of Biomedical Ethics at Research Center for Obstetrics, Gynecology and Perinatology. All the patients signed informed consent in accordance with the Ethics Committee requirements and Helsinki Declaration of the World Medical Association. Sample collection Placental tissues were sampled immediately after delivery via elective caesarean section (CS) proposed on clinical grounds from women with normal pregnancies, women with eoPE, and loPE in Research Center for Obstetrics, Gynecology and Perinatology in Moscow. Main indications for elective CS in the control group were uterine scar after previous CS, myomectomy and high myopia according to ophthalmologist conclusions. The central area of placental chorionic tissue was dissected, and the maternal decidua and amniotic membranes were removed. Samples were collected from the same area each time (1.5–2 cm next to the umbilical cord insertion, 1 cm in depth) for reducing the bias caused by differences in gene expression within the same placenta depending on sampling site48. After being washed in phosphate buffered saline (PBS), the tissue fragments were immediately placed in DMEM/F12 medium (PanEco, Russia) or frozen in liquid nitrogen and stored until use. PE and severity of PE were estimated according to common medical criteria149. Cell culture Primary cultures were obtained from the fetal part of placental villous tissue by enzymatic treatment. Full information could be found in Supplementary Information. Cell immunophenotype The cell immunophenotype was determined by flow cytometry with FACSCalibur (Becton Dickinson, USA) using monoclonal antibodies to Cyt7 (CBL194F, clone LP5K, Millipore, Germany), SOX2 (IC2018P, Clone 245610, R&D Systems, USA), Nestin (FCMAB313PE, clone 10C2, Millipore, Germany), Vimentin (ab128507, clone RV202, Abcam, USA), CD44 (555478, Clone G44-26, BD Pharmingen, USA), labeled with fluorescein isothiocyanate (FITC) or phycoerythrin. IgG of the corresponding class were used as isotype control antibodies (all – BD Pharmingen, USA). 10,000 cells were analyzed in each measurement. Immunohistochemistry Immunohistochemistry was performed according to Abcam IHC staining protocol for paraffin, frozen and free floating sections. Additional information is provided in Supplementary Information. RNA extraction and reverse transcription reaction Samples of placental tissues were homogenized in liquid nitrogen. The powder was dissolved in 1 ml of Extract RNA Reagent (Evrogen, Russia). All procedures were carried out according to the manufacturer’s protocol. RNA concentration and 260/280 ratio was measured with spectrophotometer DS-11 (DeNovix, USA). For the reverse transcription reaction, 0.5 μg of total RNA was reverse transcribed using MMLV-RT kits (Evrogen, Russia). Real-Time Quantitative RT-PCR Quantification of mRNA was performed using a DT-96 thermocycler (DNA-Technology LLC, Russia). Real-time PCR reactions were conducted in a reaction volume of 10 μl, containing 100 ng of cDNA, 300 nM of each primer and 2 μl of 5xSybrGreen-mix (Evrogen, Russia) in triplicate. All primer sequences (Supplementary Table S2) were generated and verified for specificity by Primer-BLAST. 1.5% agarose gel electrophoresis and melting curve analysis were used for amplicon size estimation and primer specificity. The PCR program consisted of an initial step at 95 °C for 5 min, followed by 45 cycles of denaturation at 95 °C for 10 s, annealing at 60 °C for 20 s and elongation at 67 °C for 20 s, followed by melting at a gradient from 65 °C to 95 °C. Relative gene expression was determined as the ratio of the target gene to the internal reference gene expression (β-actin) based on Ct values using QGENE software. mtDNA content measurement Total DNA extraction from placental tissue was performed using Nucleic Acid Extract kit (DNA-Technology, Russia) and precisely quantified with a spectrophotometer, DS-11. The mtDNA content was measured by Real Time PCR, normalizing the quantity of a non-polymorphic region of D-loop and mtDNA-encoded ND2 gene with a single copy nuclear gene (β-2-microglobulin). 100 ng of total DNA were analyzed in triplicate with the same PCR conditions as mentioned above. Relative quantification values were calculated by the 2−ΔCt method50. Activity of citrate synthase Citrate synthase activity was determined in placental tissue homogenate as described51 at a wavelength of 412 nm. Western blot analysis Western blots were carried out with standard protocol. Full experimental procedure is available in Supplementary Information. Mitochondria isolation Mitochondria were isolated by the method of differential centrifugation. A detailed protocol is located in Supplementary Information. Measurement of mitochondria activity We used the polarographic/amperometric technique to assess respiratory chain complexes efficiency. Full protocols are found in Supplementary Information. Determination of mitochondrial membrane potential and sensitivity of mitochondria to Ca2+ exposure Mitochondrial ΔΨ measurement was performed in mitochondrial suspension through fluorescence changes of lipophilic cationic dye safranin O. A detailed protocol could be found in Supplementary Information. Statistical analysis Data are presented as mean ± standard deviation (SD) as well as median and 25–75% IQR. The Shapiro-Wilk normality test was used to estimate distribution. One-way analysis of variance (ANOVA) followed by the Tukey’s post-hoc test was used to examine differences among multiple groups with normal distribution. One-way Kruskal-Wallis non-parametric ANOVA followed by the post-hoc Dunn test was used to calculate statistical differences for non-normal distributions. All calculations were performed in STATISTICA 6.0 software (StatSoft, USA), R programming language (The R Foundation) and Prism v6.0 software (GraphPad, USA). P-value < 0.05 was considered as significant and was indicative of the differences in comparison to control. Additional Information How to cite this article: Vishnyakova, P. A. et al. Mitochondrial role in adaptive response to stress conditions in preeclampsia. Sci. Rep. 6, 32410; doi: 10.1038/srep32410 (2016). Supplementary Material Supplementary Information We thank Dr. Trofimov D.Yu. for support in part of the experimental work, Vinogradov A.D. for discussion, Vysokikh Yu.M. for text editing and Shchegolev A.I. for support in immunohistochemistry. This work was supported by the Russian Foundation for Basic Research with grant RFBR No. 14-04-01617A and by Russian scientific foundation with grant 14-25-00179. All authors declare no conflict of interest. Author Contributions M.A.V. and G.T.S. designed research; P.A.V., M.A.V., N.V.T., M.V.M. and D.V.T. performed research; O.V.V., Z.S.K. and N.E.K. collected samples and analyzed clinical data; M.A.V., P.A.V., M.A.V., N.V.T., M.V.M. and R.M. analyzed data; P.A.V., M.A.V., N.V.T. and M.Y.V. wrote the paper. Figure 1 Comparison of mRNA and protein levels in control and PE groups. Relative expression levels of the genes, MFN1, MFN2, OPA1, TFAM and NRF1, normalized to β-actin (a). Relative protein expression level of VDAC1 (b) and DRP1 (c), normalized to α-tubulin. Values shown are mean ± SD. *p < 0.01 versus control. n(CTRL) = 14, n(eoPE) = 13, n(loPE) = 11. Figure 2 Expression of studied proteins in placental tissue. Anti-OPA1 (a), anti-TFAM (b), anti-tubulin (c) staining of placental homogenates. Relative protein expression level of OPA1 (d) and TFAM (e) normalized on α-tubulin. Values shown are mean ± SD. *p < 0.01 versus control. n(CTRL) = 14, n(eoPE) = 13, n(loPE) = 11. Figure 3 Immunohistochemical staining for OPA1 in control, eoPE and loPE placental tissues. Isotype control (a). Normal (b), eoPE (c) and loPE (d) placentas were stained with anti-OPA1 (red) antibody (40-fold magnification). Nuclei were visualized by DAPI (blue). Bars mean 50 μm. Figure 4 Distribution of relative mtDNA copy number and citrate synthase activity of placenta samples in control, eoPE and loPE groups. The mtDNA content (a) was measured by RT-qPCR normalizing the quantity of a not-polymorphic region of D-loop and MT-ND2 gene with a single copy nuclear gene (β-2-microglobulin). The median (line), mean (cross) and 25–75% interquartile range (IQR) are shown. n(CTRL) = 14, n(eoPE) = 13, n(loPE) = 11. Citrate synthase activity assay (b) was performed on placenta homogenates in studied groups. n(CTRL) = 5, n(eoPE) = 5, n(loPE) = 5. *p < 0.05 versus control. Figure 5 Respiration of placental mitochondria. Maximum rate of coupled respiration in presence of complex I (CI) and– complex II (CII) substrates (a). E/L is the ratio of respiratory electron transfer system capacity (E) of mitochondria in the experimentally induced noncoupled state to the leak proton flux (L) in presence of complex II substrate (b). P/O ratio (phosphate/oxygen ratio) signifies the amount of ATP produced per oxygen atom reduced by the respiratory chain (c). Values shown are mean ± SD. *p < 0.05 versus control. n(CTRL) = 12, n(eoPE) = 8, n(loPE) = 3. Figure 6 Mitochondrial membrane potential response to titration by Ca2+ and FCCP. Rate of Ca2+-induced depolarization was determined in mitochondrial suspensions from control and preeclamptic placentas (a). Effects of FCCP on ΔΨ in mitochondrial suspension from all studied groups (b). Values shown are mean ± SD. *p < 0.05 versus control. n(CTRL) = 12, n(eoPE) = 8, n(loPE) = 4. Table 1 Clinical characteristics of patients. Characteristics Control eoPE loPE Number 14 13 11 Maternal age, years 31.5 ± 4.3 34 ± 4.6 29 ± 4.2 Gestational age at delivery, weeks 39.2 ± 0.9 30.5 ± 2.9* 37.8 ± 1.0 Body mass index before delivery, kg/m2 26.7 ± 2.3 29.2 ± 4.9 29.8 ± 4.7 Systolic blood pressure, mm Hg 115.0 ± 5.8 161.0 ± 15.5* 149.0 ± 7.7* Diastolic blood pressure, mm Hg 73.0 ± 5.0 101.0 ± 9.5* 96.0 ± 7.0* Proteinuria, mg/dL n.d. 2080.3 ± 1393.1* 1312.3 ± 1440.2* Sex of the baby (Male/Female), % 50/50 30/70 36/64 Intrauterine growth restriction, % n.d. 61* 27* Severe form of PE, % n.d. 69* 9* Baby mass, g 3560.7 ± 405.6 1295.3 ± 586.2* 2828.5 ± 494.2* Data are listed as mean ± SD. *р < 0.01 versus control; n.d.–not detected. ==== Refs American College of Obstetricians and Gynecologists & Task Force on Hypertension in Pregnancy. Hypertension in pregnancy. Report of the American College of Obstetricians and Gynecologists’ Task Force on Hypertension in Pregnancy . Obstet. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3240210.1038/srep32402ArticlePdCo/Pd-Hexacyanocobaltate Hybrid Nanoflowers: Cyanogel-Bridged One-Pot Synthesis and Their Enhanced Catalytic Performance Liu Zhen-Yuan 1Fu Geng-Tao 12Zhang Lu 3Yang Xiao-Yu 1Liu Zhen-Qi 1Sun Dong-Mei 1Xu Lin a1Tang Ya-Wen b11 Jiangsu Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Centre of Biomedical Functional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210023, PR China2 Materials Science and Engineering Program & Texas Materials Institute, the University of Texas at Austin, Austin, Texas 78712, United States3 Department of Applied Chemistry, Graduate School of Engineering, Hiroshima University, Hiroshima 739-8527, Japana njuxulin@gmail.comb tangyawen@njnu.edu.cn30 08 2016 2016 6 3240218 03 2016 03 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Elaborate architectural manipulation of nanohybrids with multi-components into controllable 3D hierarchical structures is of great significance for both fundamental scientific interest and realization of various functionalities, yet remains a great challenge because different materials with distinct physical/chemical properties could hardly be incorporated simultaneously into the synthesis process. Here, we develop a novel one-pot cyanogel-bridged synthetic approach for the generation of 3D flower-like metal/Prussian blue analogue nanohybrids, namely PdCo/Pd-hexacyanocobaltate for the first time. The judicious introduction of polyethylene glycol (PEG) and the formation of cyanogel are prerequisite for the successful fabrication of such fascinating hierarchical nanostructures. Due to the unique 3D hierarchical structure and the synergistic effect between hybrid components, the as-prepared hybrid nanoflowers exhibit a remarkable catalytic activity and durability toward the reduction of Rhodamine B (RhB) by NaBH4. We expect that the obtained hybrid nanoflowers may hold great promises in water remediation field and beyond. Furthermore, the facile synthetic strategy presented here for synthesizing functional hybrid materials can be extendable for the synthesis of various functional hybrid nanomaterials owing to its versatility and feasibility. ==== Body Rational hybridization and nanostructure engineering allow for achieving optimized or diversified material functionalities and thus have attracted increasing research interests in nanochemistry community12345678910. Hybrid nanostructures with multi-components in one nanoscale entity could not only possess combined properties from the individual component, but also be capable of demonstrating new synergistic effects, which are induced by the nanoscale interactions and inaccessible from the isolated components or their physical mixtures. Therefore, a great number of nanocomposites have been synthesized and hold promising applications in various fields, including catalysis111213, energy conversion and storage14151617, optoelectronic devices181920, etc. Generally, the exceptional synergistic functionalities of the hybrid nanostructures are not only determined by the nature of each constituent component, but also more sensitively dependent upon the geometrical arrangement of the building units. Specifically, elaborate architectural manipulation of low dimensional (0D, 1D and 2D) primary building blocks into controllable 3D hierarchical structures is of great significance for both fundamental scientific interest and technological applications, and also provides a promising approach toward the future realization of functional nanodevices510. Owing to their unique structures, 3D hierarchical structures could possess the advantages of the pristine building blocks, and more importantly, also may exhibit even new physicochemical characteristics induced by coupling or ensemble effects, in comparison with their 1D or 2D counterparts2122232425. Hitherto, despite considerable achievements have been made in such interesting field, it still remains a great challenge to develop a facile and controllable route for the construction of hierarchical architectures. Especially, it is extremely difficult to integrate multi-components into a hybrid hierarchical nanostructure based on the protocols established before, because different materials with distinct physical/chemical properties could hardly be incorporated simultaneously into the synthesis process. Therefore, it is highly desirable to develop a straightforward synthetic approach to generate nanohybrids with hierarchical architectures. Cyanogel, pioneered by Bocarsly, is a kind of coordination polymer obtained from the reaction of aqueous solutions of a tetrachlorometalate ([RCl4]2−, R = Pd, Pt, Ir, Sn) and a transition metal cyanometalate ([M(CN)n]2−/3−, n = 4, 6; M = Co, Fe, Ru, Os, Ni, Cr), as illustrated in Equation (1) in Supplementary Information26272829. By taking advantages of the structural features of cyanogels, such as 3D characteristic backbones and uniform distribution of the two kinds of metal ions, we have developed a versatile cyanogel-based approach for the synthesis of various 3D noble metal-based nanostructures with improved catalytic performances3031323334. Our previous results demonstrate that the cyanogel-based approach has the capacity to address some of the challenges in controlled construction of hybrid nanomaterials. Herein, for the first time, we extend the capability of one-pot cyanogel-based hydrothermal approach to achieve 3D flower-like metal/Prussian blue analogue nanohybrids, namely PdCo/Pd-hexacyanocobaltate (PdCo/PdHCC), constructed by numerous radial 2D ultrathin nanosheets, by using K2PdCl4/K3Co(CN)6-PEG hybrid cyanogel as the reaction precursor (Fig. 1). Control experiments indicate that the elaborate co-existence of cyanogel and PEG is crucial for the generation of such interesting hierarchical architecture. Remarkably, due to the unique 3D hierarchical structure and the synergistic effect between hybrid components, the as-prepared PdCo/PdHCC hybrid nanoflowers exhibit an excellent catalytic activity and durability toward the reduction of Rhodamine B (RhB) by NaBH4, as compared with the Pd and PdHCC nanoparticles. Results and Discussion Physicochemical characterization of PdCo/PdHCC hybrid nanoflowers For a standard synthesis of PdCo/PdHCC hybrid nanoflowers, yellowish jelly-like K2PdCl4/K3Co(CN)6-PEG hybrid cyanogel was firstly generated by mixing K2PdCl4-PEG solution and K3Co(CN)6-PEG solution. Upon a hydrothermal treatment, the hybrid cyanogel could be readily converted to 3D nanostructures owing to its intrinsic 3D characteristic backbones and the structural-directing effect of PEG. Simultaneously, PdCo alloy nanoparticles could be in-situ generated thanks to the weak reducing ability of PEG. Thus, the as-synthesized hybrid cyanogel could be evolved to uniform 3D flower-like PdCo/PdHCC nanohybrids after a hydrothermal treatment (see Experimental section for details). X-ray diffraction (XRD) pattern in Fig. 2a indicates that both face-centered cubic (fcc)-phased PdCo alloy and Prussian blue analogue, Pd-hexacyanocobaltate, coexist in the obtained product35. Figure S1 schematically illustrates the possible crystal structure of PdHCC. Analogous to Prussian blue, it has a three-dimensional cyano-bridged bimetallic basic unit with alternating Pd(II) and Co(III) located in a fcc lattice363738. Fourier transform infrared (FTIR) analysis (Fig. 2b) shows the characteristic stretching peaks of C≡N around 2170 cm−1 and the absorption peak of Pd-CN-Co at 452 cm−1, confirming the successful formation of Prussian blue analogue3940. The thermal stability of the product was investigated by thermogravimetry analysis (TGA) under air atmosphere. As displayed in Figure S2, the weight loss from room temperature to ~115 °C is caused by the loss of free water41. The weight loss in the temperature range of 195–240 °C can be assigned to the removal of coordinating water for Prussian blue42. When the temperature is increased above 245 °C, the PdHCC species begin to thermally decompose in air40. A panoramic scanning electron microscopy (SEM) image shown in Fig. 3a demonstrates that the product is almost entirely composed of uniform nanoflowers with diameter of 320 ± 20 nm. No other morphologies could be detected, indicating a high yield of these hierarchical structures. It is clearly shown that these nanoflowers are actually built from 2D ultrathin flexible nanosheets with an average thickness around 7 nm (Fig. 3b). These flexible nanosheets are eradiated from the central region to form open porous hierarchical structures, which may give rise to a large surface area and thus improved physicochemical properties. As shown in Fig. 3c,d, the typical transmission electron microscopy (TEM) images reveal that the as-synthesized sample exhibits urchin-like structures with an average diameter ~320 nm, which further confirms that the sample is constructed by radial nanosheets, in good agreement with the SEM observation. These nanoflowers could maintain their integrity upon sonication treatment for 30 min, suggesting the existence of strong chemical bonds between the building blocks. From the TEM image of an individual nanoflower (Fig. 4a), it is obvious that the “petals” tend to bend and curl, reflecting the flexibility of the building blocks. The corresponding selected area electron diffraction (SAED) pattern (inset of Fig. 4a) implies a polycrystalline nature of the nanoflower and the diffraction dots are well consistent with the (111) and (220) planes of fcc-structured alloy phase. Magnified TEM image in Fig. 4b vividly reveals that uniform ultrafine nanoparticles are highly dispersed on the surface of the nanosheets. Figure 4c and d display the high-resolution TEM (HRTEM) images of the nanosheets and the homogeneously dispersed nanoparticles, respectively. The fringe spacing of 0.311 nm observed from the petal can be indexed to the (311) planes of PdHCC, while lattice fringes of 0.221 nm in nanoparticles can be attributed to the (111) planes of fcc-phased PdCo alloy. Notably, the measured lattice fringes of (111) planes in the nanoparticles are smaller than that of the pure Pd (0.225 nm, JCPDS 46-1043). Such shrinkage of the lattice fringe further verifies the formation of PdCo alloyed nanoparticles. Consistent with the SEM and TEM observations, high-angle annular dark-field scanning TEM (HAADF-STEM) shown in Figure S3 verifies that the as-prepared nanoflowers are built from 2D nanosheets. The elemental mapping further reveals the presence and uniform distributions of Pd and Co throughout the hybrid nanoflowers. The porosity and Brunauer-Emmett-Teller (BET) surface area of the as-synthesized PdCo/PdHCC nanoflowers were investigated through N2 adsorption-desorption measurements. As displayed in Fig. 5a, the N2 adsorption-desorption isotherms of PdCo/PdHCC nanoflowers can be categorized as type IV with a significant hysteresis loop observed in the relative pressure (p/p0) range of 0.5–1.0, which implies the presence of meso-pores (2–50 nm in size)43. This result can be further confirmed by corresponding pore-size distribution curve (Fig. 5b), in which a peak centred at 34 nm can be observed. As revealed by the SEM observation, these meso-pores can be attributed to the space between the intercrossed 2D nanosheets44. The BET surface area of the PdCo/PdHCC nanoflowers calculated from N2 isotherms is 32.8 m2 g−1. The valance states of Pd and Co in the hybrid nanoflowers were examined by X-ray photoelectron spectroscopy (XPS) technique, revealing that both metallic and oxidic states of Pd and Co exist in the hybrid nanoflowers (Fig. 5c,d)4546. These results further verify the hybrid compositions as PdCo/Pd hexacyanocobaltate. To develop an understanding of the mechanism behind the formation of PdCo/PdHCC nanoflowers, the chemical fate of each involved reagent has been considered. When PEG is absent from the reaction system while the other reaction parameters remain unchanged, although the yellowish jelly-like cyanogel could be still formed (Figure S4a), the resulting product achieved after the hydrothermal treatment is made of the isolated palladium hexacyanocobaltate nanoparticles with an average size of 70 nm, as confirmed by XRD and TEM images (Figure S4b–d). When there is no K3Co(CN)6 introduced, the reduction of K2PdCl4 by PEG could only produce irregular aggregated nanoparticles (Figure S5a). In comparison, the hydrothermal treatment of the mixture only containing K3Co(CN)6 and PEG could generate intercrossed nanochains (Figure S5b). Collectively, all these results unambiguously suggest that the presence of PEG and the formation of cyanogel are indispensable for the successful formation of 3D PdCo/PdHCC hybrid nanoflowers. Furthermore, time-dependent experiments have been carefully carried out to reveal the morphological evolution. Figure 6 illustrates the representative TEM images of the intermediate products collected at different reaction intervals. As shown in Fig. 6a, the sample consists of numerous flocculated agglomerates without a discernible morphology when the hybrid cyanogel was hydrothermally treated for 1 h. As the reaction time was prolonged to 2 h, the flocculation tended to aggregates together, forming a large number of nanoparticles (Fig. 6b). Interestingly, some nanosheets began to germinate from the surface of nanoparticles when the reaction time was increased to 3 h, as indicated by red arrows and inset of Fig. 6c. As a consequence of continuous growth, development and ripening, more and more nanosheets sprouted from the surface of nanoparticles and the obtained hierarchical architectures became ripening and plumy, accompanied by the gradual depletion of the flocculation (Fig. 6d). Eventually, uniform well-developed 3D PdCo/PdHCC hybrid nanoflowers constructed by 2D nanosheets were formed when the reaction time was proceeded more than 5 h (Fig. 6e). Based on the above TEM observations, the possible formation mechanism of the 3D PdCo/PdHCC hybrid nanoflowers could be proposed as follows. As we know, PEG is a kind of nonionic surfactant which possesses hydrophilic -O- and hydrophobic -CH2-CH2- radicals on its long chains, and usually serves as structure-directing agent or soft template for engineering ordered nanostructures due to its selective adsorption to inhibit crystal growth and thus modify the morphology of nanocrystallite4748. In this work, PdCo-based cyanogel will be enwrapped into the coil of intertwisted PEG and form flocculated agglomerates when the precursors are initially mixed. From the thermodynamic viewpoint, the flocculation has a tendency to self-aggregate into nanoparticles to minimize the total surface energy when hydrothermally treated. As the reaction proceeds, the formed nanoparticles continue to grow by combining with the remaining flocculated agglomerates and recrystallize. Meanwhile, PEG may selectively bind to certain specific crystallographic facets49. Such a preferential adsorption could effectively facilitate the anisotropic growth, leading to the formation of 2D nanosheets. Therefore, with the further increase of reaction time, more and more 2D nanosheets are germinated from the surface of nanoparticles, and the nanoparticles gradually evolve into hierarchical nanoflowers at a later stage. Therefore, the formation of 3D PdCo/PdHCC hybrid nanoflowers can be rationally expressed as a “nucleation-aggregation-dissolution-recrystallization” mechanism5051. During the formation of PdHCC nanoflowers with the assistance of PEG, the PdHCC could be partially reduced by PEG to form PdCo alloy nanoparticles which are simultaneously dispersed on the surface of PdHCC nanoflowers. The plausible formation process can be schematically illustrated in Fig. 7. Catalysis for the hydrogenation of RhB Such a hierarchical architecture and integrated multiple compositions in nanoscale might bring out some unusual physiochemical properties. As a proof-of-concept application of this intriguing hybrid nanostructure, the obtained 3D PdCo/PdHCC hybrid nanoflowers were employed as a catalyst for the hydrogenation of RhB in the presence of NaBH4. The catalytic reduction of RhB is schematically illustrated in Fig. 8a 52. The characteristic absorption peak of RhB at 554 nm was selected to monitor the catalytic reduction process. For comparison, a series of control experiments were also performed under different conditions: (1) without NaBH4 but in the presence of PdCo/PdHCC hybrid nanoflowers, (2) without any catalyst but in the presence of excess NaBH4, and (3) catalyzed by Pd or PdHCC nanoparticles. As shown in Figure S6a, the physical adsorption experiment demonstrates that the PdCo/PdHCC hybrid nanoflowers have a very weak adsorption capability toward RhB (only 2.2% in 24 h), precluding the physical adsorption of RhB by PdCo/PdHCC hybrid nanoflowers. The further control experiment (Figure S6b) indicates that RhB is slightly reduced (3.6% in 60 min) in the presence of excess NaBH4 but without any catalyst. Whereas, upon the introduction of PdCo/PdHCC hybrid nanoflowers into the reaction system, the color of RhB solution changed from pink to colorless rapidly. As displayed in Fig. 8b, the maximal absorption of the RhB dye decreased significantly as reaction time went on, and the reduction reaction completed in 13 min, indicating the excellent catalytic performance of the PdCo/PdHCC hybrid nanoflowers. No deactivation or poisoning of the catalyst could be observed during the reaction. Although PdHCC or Pd nanoparticles could also catalyze the reduction of RhB, the periods for the complete reaction of the two reference materials are much longer as compared with the case of PdCo/PdHCC hybrid nanoflowers (36 or 25 min vs. 13 min), revealing their much lower reaction rates (Figure S6c,d). As suggested by the previous studies, the hydrogenation reduction of RhB obeys a pseudo-first order kinetic law53. On the basis of the pseudo-first order kinetics, ln(C/C0) = kt, where C is the concentration of the RhB at time t, C0 is the initial concentration of the RhB solution, and the slope k is the apparent reaction rate, the ln(C/C0) is linearly dependent on the reaction time t. As shown in Fig. 8c, the calculated rate constant k with PdCo/PdHCC hybrid nanoflowers is 0.178 min−1, which is obviously larger than that in Pd (0.095 min−1) or PdHCC (0.084 min−1) case. The long-term stability of the prepared PdCo/PdHCC hybrid nanoflower sample was also evaluated through a cycling test. After each cycle of the 13-min test, the sample was washed and reused for reduction of RhB. As shown in Fig. 8d, no obvious decrease of catalytic activity was observed after five cycles, suggesting very high stability and long lifetime of PdCo/PdHCC hybrid nanoflowers during the hydrogenation process. As revealed by TEM and SEM images shown in Figure S7a,b, the 3D hierarchical flower-like structures could be well preserved without notable aggregation or detachment after five cycles. Moreover, as implied by the XPS results in Fig. 5c,d and Figure S7c,d, the valence states of Pd and Co in the hybrid nanoflowers almost kept consistent before and after cycling tests. All these results strongly manifest the excellent robustness of the 3D hierarchical nanoflowers. Generally, the catalytic hydrogenation mechanism of RhB via noble metal-based nanocatalysts in the presence of NaBH4 could be explained as follows. The dye of RhB is electrophilic while BH4− is nucleophilic as compared with the catalyst, demonstrating that the nucleophilic BH4− can donate electrons to the catalyst, from where electrophilic dyes would capture electrons. So the catalyst serves as an electron relay for catalytic reduction of dyes in the presence of NaBH45455. In the present study, the high dispersity of PdCo nanoparticles with ultrafine size in PdCo/PdHCC nanoflowers not only helps to provide more catalytic sites, but also could effectively prevent the agglomeration of PdCo nanoparticles during the reaction. Furthermore, the hierarchical nanoflowers offer a high surface-to-volume ratio and have plenty of open meso-pores, providing more molecular accessibility, efficient transport paths and thus improved catalytic activity toward the reduction of RhB565758. In summary, we have developed a novel cyanogel-bridged one-pot synthesis approach for the generation of 3D flower-like metal/Prussian blue analogue nanohybrid, namely PdCo/Pd-hexacyanocobaltate, for the first time. The judicious introduction of PEG and the formation of cyanogel are indispensable for the successful formation of such fascinating hierarchical nanostructures. Owing to the unique 3D hierarchical structure and the synergistic effect between hybrid components, the as-synthesized hybrid nanoflowers exhibit an excellent catalytic activity and durability toward the reduction of RhB by NaBH4, which indicates that the hybrid nanoflowers may hold great promise in water remediation field and beyond, such as electrocatalysis and sensor, etc. Furthermore, the novel method developed in this work for synthesizing functional hybrid materials with hierarchical structures can be extended to the fabrication of various functional hybrid nanomaterials thanks to its versatility and feasibility. Methods Synthesis of PdCo/PdHCC hybrid nanoflowers In a typical synthesis, 2.0 mL of 50 mM K2PdCl4 solution containing 340 mg PEG and 1.0 mL of 50 mM K3Co(CN)6 solution containing 170 mg PEG were mixed and kept still for 2 h at 30 °C, allowing for the formation of yellow jelly-like K2PdCl4/K3Co(CN)6-PEG hybrid cyanogel. Subsequently, the obtained cyanogel was transferred to a 20 mL Teflon-lined stainless autoclave and heated at 150 °C for 6 h. After being cooled to room temperature, the black product was separated by centrifugation, washed with 0.1 M HClO4 solution and water several times, and then dried at 40 °C in a vacuum oven for 12 h. The acid-wash process could ensure the removal of possible byproducts or impurities. For comparison, the single-component Pd nanoparticles were prepared by only using K2PdCl4 as reaction precursor under the similar experimental conditions. The PdHCC nanoparticles were also prepared using the mixture of K2PdCl4 and K3Co(CN)6 yet without PEG as reaction precursors under the identical experimental conditions. Characterization The morphology and particle size of the samples were investigated using a JEOL JEM-2010 transmission electron microscopy (TEM) operated at an accelerating potential of 200 kV. Scanning electron microscopy (SEM) images were captured on a Hitachi S-4800 scanning electron microscope, operating at 5 kV. X-ray diffraction (XRD) patterns were performed on Model D/max-rC X-ray diffractometer using Cu Kα radiation source (λ = 1.5406 Å) and operating at 40 kV and 100 mA. X-ray photoelectron spectroscopy (XPS) measurements were carried out on a Thermo VG Scientific ESCALAB 250 spectrometer with a monochromatic Al Kα X-ray source (1486.6 eV photons). The binding energy was calibrated with respect to C1s at 284.6 eV. The compositions of the catalysts were determined using the energy dispersive X-ray (EDX) technique. The Brunauer-Emmett-Teller (BET) specific surface area and pore size distribution were measured at 77 K using a Micromeritics ASAP 2050 system. Fourier transform infrared (FTIR) spectrum was recorded with a Nicolet 520 SXFTIR spectrometer. The UV-vis spectra were recorded at room temperature on a UV3600 spectrophotometer. Thermal analysis was performed on a Perkin Elmer thermogravimetric analyzer under air atmosphere with a heating rate of 10 °C min−1. Catalytic measurements The reduction of organic dye molecules, such as RhB, with NaBH4 was chosen as a model reaction to evaluate the catalytic performance of the as-obtained PdCo/PdHCC nanoflowers. A NaBH4 solution (0.20 mg/mL) was freshly prepared and stored in refrigerator in the dark. The reduction of the RhB dyes was carried out in a quartz cuvette having a path length of 1 cm. For a catalytic reaction, 2 mL of 3.33 × 10−5 M RhB dye solution was mixed with 0.5 mL of 0.20 mg/mL NaBH4, followed by gentle shaking. Subsequently, 0.5 mL of 0.40 mg/mL PdCo/PdHCC nanoflower solution was added, and the progress of the reduction was monitored spectrophotometrically using an in-situ UV-vis spectrophotometer. For comparison, the catalytic processes catalyzed by PdHCC and monometallic Pd nanoparticles were also performed under the identical conditions. Additional Information How to cite this article: Liu, Z.-Y. et al. PdCo/Pd-Hexacyanocobaltate Hybrid Nanoflowers: Cyanogel-Bridged One-Pot Synthesis and Their Enhanced Catalytic Performance. Sci. Rep. 6, 32402; doi: 10.1038/srep32402 (2016). Supplementary Material Supplementary Information The authors are grateful for the financial of the National Natural Science Foundation of China (21576139, 21503111, 21376122, and 21273116), United Fund of NSFC and Yunnan Province (No. U1137602), Natural Science Foundation of Jiangsu Province (No. BK20131395), China Scholarship Council (CSC, No. 201506860013), University Postgraduate Research and Innovation Project in Jiangsu Province (No. KYZZ15_0213), National and Local Joint Engineering Research Center of Biomedical Functional Material, and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, National and Local Joint Engineering Research Center of Biomedical Functional Materials. Author Contributions Z.-Y.L., G.-T.F., L.Z., X.-Y.Y., Z.-Q.L. and D.-M.S. designed the experiments and performed the materials synthesis, characterization and electrochemical measurements. L.X. and Y.-W.T. wrote the main manuscript text. L.X. and Y.-W.T. supervised the project, and all authors participated in the review of the manuscript. Figure 1 Schematic illustration of the formation of PdCo/PdHCC hierarchical nanoflowers using hybrid cyanogel as precursors. Figure 2 (a) XRD pattern and (b) FTIR spectrum of the synthesized PdCo/PdHCC hybrid hierarchical nanoflowers. Figure 3 (a,b) Representative SEM images and (c,d) typical TEM images of the obtained PdCo/PdHCC hybrid hierarchical nanoflowers. Figure 4 (a) TEM image of an individual PdCo/PdHCC hybrid nanoflower, (b) Magnified TEM of the “petals” from the nanoflower, and (c,d) HRTEM images performed on the petal. Figure 5 (a) N2 adsorption-desorption isotherms and (b) pore-size distribution curve of the PdCo/PdHCC nanoflowers. (c,d) XPS spectra of the Pd 3d and Co 2p regions for the PdCo/PdHCC nanoflowers. Figure 6 TEM images of the PdCo/PdHCC nanoflower intermediates collected at different reaction intervals. (a) 1 h, (b) 2 h, (c) 3 h, (d) 4 h and (e) 5 h. Figure 7 Schematic illustration of the proposed formation mechanism of PdCo/PdHCC hierarchical nanoflowers. Figure 8 (a) Schematic illustration of the catalytic reduction of RhB with NaBH4 in the presence of PdCo/PdHCC nanoflowers. (b) UV-vis absorption spectra of RhB during the reduction catalyzed by PdCo/PdHCC nanoflowers. (c) First-order kinetics, ln(C/C0) vs t, for the catalytic hydrogenation of RhB solution via nanocatalysts in the presence of NaBH4. (d) Cycling test of hydrogenation of RhB over 5 cycles by using PdCo/PdHCC hybrid nanoflowers. ==== Refs Bar-Elli O. , Grinvald E. , Meir N. , Neeman L. & Oron D. Enhanced third-harmonic generation from a metal/semiconductor core/shell hybrid nanostructure . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3235010.1038/srep32350ArticleSOX9-regulated cell plasticity in colorectal metastasis is attenuated by rapamycin Carrasco-Garcia Estefania 1Lopez Lidia 1Aldaz Paula 1Arevalo Sara 1Aldaregia Juncal 1Egaña Larraitz 1Bujanda Luis 2Cheung Martin 3Sampron Nicolas 1Garcia Idoia 14Matheu Ander a141 Cellular Oncology group, Biodonostia Institute, San Sebastian, Spain2 Department of Gastroenterology, Hospital Donostia and Instituto Biodonostia, University of the Basque Country, Centro de Investigacion Biomedica en Red en Enfermedades Hepaticas y Digestivas (CIBERehd), San Sebastian, Spain3 School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China4 IKERBASQUE, Basque Foundation, Bilbao, Spaina ander.matheu@biodonostia.org30 08 2016 2016 6 3235002 03 2016 08 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The cancer stem cell (CSC) hypothesis proposes a hierarchical organization of tumors, in which stem-like cells sustain tumors and drive metastasis. The molecular mechanisms underlying the acquisition of CSCs and metastatic traits are not well understood. SOX9 is a transcription factor linked to stem cell maintenance and commonly overexpressed in solid cancers including colorectal cancer. In this study, we show that SOX9 levels are higher in metastatic (SW620) than in primary colorectal cancer cells (SW480) derived from the same patient. This elevated expression correlated with enhanced self-renewal activity. By gain and loss-of-function studies in SW480 and SW620 cells respectively, we reveal that SOX9 levels modulate tumorsphere formation and self-renewal ability in vitro and tumor initiation in vivo. Moreover, SOX9 regulates migration and invasion and triggers the transition between epithelial and mesenchymal states. These activities are partially dependent on SOX9 post-transcriptional modifications. Importantly, treatment with rapamycin inhibits self-renewal and tumor growth in a SOX9-dependent manner. These results identify a functional role for SOX9 in regulating colorectal cancer cell plasticity and metastasis, and provide a strong rationale for a rapamycin-based therapeutic strategy. ==== Body Cancers display a high degree of heterogeneity between individual patients but also between cancer cells within the same tumor. Both types of heterogeneity affect clinical practice. During the last decade, it has been demonstrated that there is a population of cancer cells with stem-like properties, so-called cancer stem cells (CSCs), in several types of malignancies. CSCs are defined by their abilities to self-renew and generate differentiated progeny. These characteristics enable them to be the root of malignancies and to play a major role in tumor initiation and recurrence, therapy resistance and metastasis1. Colorectal adenocarcinoma is the second most commonly diagnosed type of cancer and constitutes the second leading cause of cancer-related mortality worldwide, causing nearly 700,000 deaths per year2. Colorectal cancer occurs sporadically in the majority of cases, being due to inherited mutations in less than 10% of patients. In most patients, death is not caused by the primary tumor, but rather by its metastasis in other organs and associated complications. Indeed, patients are generally diagnosed at an advanced stage, wherein the 5-year survival rate is only 11.7%2. Ten years ago, various research groups demonstrated the existence of colorectal cancer stem cells (CR-CSCs), and revealed these cells to be responsible for treatment resistance3. More recently, it has been identified that CR-CSCs have a role as drivers of the metastatic progression of colorectal cancer4. Moreover, the expression of the CD44v6 variant of CD44 or CD110 was shown to serve as a biomarker for this CR-CSC pool of colorectal metastasis drivers56. These studies started to unravel the mechanisms involved in the regulation of CR-CSCs associated with metastasis and showed that plasticity between CR-CSCs and non-CR-CSCs occurs at advanced stages of tumor progression. The transcription factor Sex-determining region Y (SRY)-box 9 (SOX9) plays a crucial role in stem cell maintenance and lineage commitment during embryonic development and also in adult tissue homeostasis. In the intestinal epithelium, lineage tracing and loss of function mouse models identified that Sox9 is a key regulator of tissue homeostasis, regeneration and tumor initiation, through its functions in stem/progenitor cell maintenance and Paneth cell differentiation7891011. These activities arise acting as an effector and at the same time regulator of Wnt signaling10, a pathway whose activation is sufficient to initiate colorectal tumors, that is relevant for the maintenance of CR-CSCs12. Moreover, it is the most frequently aberrantly activated pathway in colorectal cancer13. There is growing evidence of the impact of SOX9 in human malignancies14151617. In particular, several studies have revealed that SOX9 is commonly overexpressed in colorectal cancers181920212223, even in cases where the gene is mutated, event which happens in around 5–10% of cases1324. Clinico-pathologically, high SOX9 expression correlates with tumor progression and advanced tumor stage18 and has been associated with lower overall patient survival2021. Functional studies have supported the view that SOX9 plays a pro-oncogenic role in primary colorectal cancer cells1821, but under some circumstances it behaves as a tumor suppressor2526. The role of SOX9 in the regulation of CR-CSCs has not been previously explored. In this work, we found that SOX9 is sufficient and necessary for the acquisition and maintenance of CR-CSC and metastatic traits, properties linked to transcriptional and post-transcriptional regulation. Finally, we reveal that SOX9-mediated self-renewal and growth is impaired by the mTOR inhibitor rapamycin. Results and Discussion High levels of SOX9 correlate in CR-CSCs and metastatic cells SW480 and SW620 cell lines were derived from a primary colorectal adenocarcinoma and its lymph node metastasis, respectively27. We started by characterizing the expression of CR-CSC markers3, finding that metastatic SW620 cells had higher levels of BMI1, CD133 and SOX9 than SW480 primary cells (Fig. 1A). These differences were markedly strong in the case of the last two genes. When SOX9 levels were compared with CRC human samples and matched adjacent colon tissue, we found SOX9 expression significantly increased in CRC tissues (p < 0.05), with levels in SW620 being between the most highly expressed cancer tissues, whereas in SW480 were near the lowest cases (Fig. 1B). Therefore, the level of expression of SOX9 in SW480 and SW620 cell lines is within the range of overexpression observed in human colorectal samples, suggesting that their levels are of biological relevance. SOX9 protein levels were also strikingly elevated in SW620 cells as well as phosphorylated SOX9 at serine 181 (Fig. 1C). This site is known to stimulate SOX9 transcriptional and DNA-binding activity28, indicating that SOX9 upregulation in metastatic cells is associated with transcriptional and post-transcriptional modifications. In clinical samples, SOX9 expression is higher in liver metastasis than matched primary colorectal cancers, where it is part of an aggressive stem cell signature together with ASCL2, LGR5, EPHB3 and ETS229. Hence, our molecular identification of SOX9 is consistent with the clinical data, and together they show that SOX9 exhibits a dynamic expression in colorectal cancer, with high levels of SOX9 being associated with CR-CSCs and metastasis. Next, we observed that the metastatic cells exhibited greater capacity to form tumorspheres (primary) than SW480 cells (26.6 in SW620 vs. 6.7 in SW480). Moreover, the ability for self-renewal, measured in terms of the number of secondary tumorspheres, was also much higher in SW620 cells (Fig. 1D). In agreement with the enrichment in the CR-CSC pool, we detected elevated expression of CD133, CD44 and BMI1, as well as SOX9, in tumorspheres formed from both cell lines (Fig. 1E,F). The above information, together with the evidence that both cell lines belong to the stem-like subtype showing high Wnt activity30, postulates SW480 and SW620 as suitable models to study the role of SOX9 in cellular plasticity and metastasis. SOX9 overexpression provides stemness properties to colorectal cancer cells To determine whether SOX9 activity is involved in the plasticity between non-CR-CSCs and CR-CSCs, we used a lentiviral vector harboring a plasmid with the SOX9 coding sequence to produce SOX9-overexpressing SW480 cells, and compared their functional properties to control empty-vector transduced cells. Western blotting revealed the overexpression of SOX9 in SW480 cells (Fig. 2A). Importantly, the ability to form tumorspheres was markedly different between control and SOX9 overexpressing cells. Indeed, cells with SOX9 overexpression generated 4-fold greater number of primary tumorspheres and 2.5-fold higher secondary tumorsphere formation (Fig. 2B). Next, we determined the effect of SOX9 overexpression on tumor initiation, a distinctive feature of CSCs1. Notably, by 10 days, all immunodeficient Foxn1nu/Foxn1nu mice inoculated with SOX9 overexpressing cells had developed tumors, compared to just over half (58%) of tumors derived from control cells (Fig. 2C). These results indicate that SOX9 promotes the acquisition of CR-CSC characteristics, both in vitro and also in vivo. Given the differences observed in phosphorylated SOX9 between primary and metastatic cells, we wondered whether this activity might play a role in the gain of stemness. For this, we transduced SW480 cells with a construct containing point mutations at S64 and S181 phosphorylation sites (Sox9S64A,S181A) or WT-Sox931 and compared them to non-infected cells. We found that Sox9S64A,S181A cells formed fewer tumorspheres (0.65 fold) than WT-Sox9 and slightly more than controls (Fig. 2D). Another study has recently found that SLUG prevents SOX9 ubiquitin-mediated proteasomal degradation, thereby controlling its stability and maintaining lung CSC activity32. To our knowledge, these studies have provided the first proofs of a role for SOX9 post-translational modifications associated with cancer phenotypes. Since cancer cell motility and consequent invasion of the basement membrane have been associated with the gain of CSC properties and an epithelial mesenchymal transition (EMT) program33, we investigated the effect of ectopic SOX9 overexpression on these phenotypes. Stable overexpression of SOX9 resulted in a significant increase in the migratory potential of SW480 cells (Fig. 3A). Collagen invasion assays showed that high levels of SOX9 also enhanced their invasive potential (Fig. 3B). Moreover, migration ability (Fig. 3C) and invasive potential (Fig. 3D) were impaired in Sox9S64A,S181A cells, indicating that SOX9 phosphorylation is necessary, at least in part, for these processes. Next, we measured the expression of several EMT markers and detected a reduction in the expression of the epithelial adhesion protein E-Cadherin (Fig. 3E). In addition, SOX9 overexpression provoked a robust induction of the mesenchymal marker Vimentin (Fig. 3E,F), which was reduced in cells lacking the phosphorylation sites (Fig. 3G). A previous study found that ectopic SOX9 induced an epithelial mesenchymal transition (EMT) and led to the formation of more metastasis in vivo in an additional primary colorectal cell line21. Hence, high levels of SOX9 confer motility, invasive properties and a mesenchymal phenotype to primary colorectal carcinoma cells, all of them important features for the translocation of a cancer cell from the primary tumor to a distant tissue in metastasis. At a molecular level, we have previously described that Sox9 modulates proliferation directly regulating Bmi118, a stem cell marker which genetic or pharmacologic inhibition irreversibly impairs CR-CSC activity34. Since we observed higher levels of both of them associated to CR-CSCs population (Fig. 1E), and in clinical samples18, we reasoned that BMI1 may be involved in SOX9-mediated colorectal cancer cell plasticity. In agreement with our hypothesis, the expression of BMI1 was higher in SOX9 overexpressing SW480 cells (Fig. 2A). In contrast, SW620 SOX9 silencing cells displayed BMI1 downregulation (Fig. 4A). ChIP-seq experiments revealed that SOX9 binds to the promoter of BMI1 in colorectal cells35, supporting that this regulation is direct. Overall, these data indicate that SOX9 modulates colorectal cancer cell plasticity regulating the dynamics of BMI1 and postulate SOX9-BMI1 as a critical axis for maintaining CR-CSCs activity and colorectal cancer pathobiology. SOX9 is necessary for CR-CSCs maintenance Having demonstrated that SOX9 promotes the acquisition of self-renewal and metastatic traits in primary colorectal carcinoma cells, we next determined its function in metastatic cells. For this, we knocked down SOX9 in SW620 cells using a specific short hairpin RNA (shSOX9). Quantitative real-time PCR and Western blotting demonstrated the silencing of the endogenous expression of SOX9 by shSOX9 (Fig. 4A,B). Strikingly, SOX9 downregulation resulted in a significant decline in the formation of both primary and secondary tumorspheres relative to that in SW620 control cells (Fig. 4C). Therefore, SOX9 silencing abrogates the self-renewal ability of colon metastatic cells in vitro. To corroborate the functional need of SOX9 for CR-CSC maintenance, we moved onto in vivo experiments. The ability to initiate tumors was severely impaired in SOX9-silenced cells relative to control cells. Specifically, 41% of injections with shSOX9 cells developed tumors, while tumors were generated in all mice injected with control cells (Fig. 4D). Similarly, only 11% of inoculations developed tumors when injected with an additional short hairpin targeting a different SOX9 sequence (shSOX9-2) (Fig. 4D). Furthermore, tumors originating from shSOX9 and shSOX9-2 cells grew more slowly than those from control cells (Fig. 4E,F). Strikingly, the impaired tumorigenic activity of SOX9 knockdown cells (Fig. 4G) was further corroborated in vivo by reduced cell proliferation in the tumors. shSOX9 derived xenografts displayed lower number of Ki67 positive cells than tumors derived from control cells (p = 0.00049) (Fig. 4G,H). Together, these results show that the expression of SOX9 acts as a pleiotropic regulator maintaining self-renewal but also governing the proliferative capacity of colorectal cancer cells. Next, we studied whether SOX9-mediated loss of stemness properties could affect phenotypes necessary for metastatic colonization in distant organs36. Thus, the invasive potential of metastatic cells in vitro was impaired as a consequence of SOX9 silencing (Fig. 5A). Moreover, immunofluorescence and Western blot analysis revealed that the levels of the mesenchymal markers Vimentin and N-Cadherin were lower in SW620 cells in the absence of SOX9 in vitro (Fig. 5B,C). These results were further validated in tumors originated from shSOX9 cells (Fig. 5D). In line with these findings, genome-wide chromatin immunoprecipitation with DNA sequencing ChIP-seq analysis identified genes involved in EMT and quiescence as targets of SOX9 in colorectal cancer cells35. In summary, our results demonstrate that SOX9 activity is required for retaining metastatic CR-CSC functional properties. SOX9 mediates rapamycin anti-tumorigenic effect In CRC SOX9 overexpression is a strong predictor of shorter survival in 5-FU-treated patients and enhanced vascular invasion in biopsies22, whereas intestine stem cells expressing high levels of Sox9 are more resistant to irradiation in mice37. Since activation of CR-CSC signaling is central to acquired resistance to therapy in colorectal cancer, our results suggest that pharmacological inhibition of SOX9 might be a novel therapeutic approach for this type of cancer. It has been shown that rapamycin inhibits the early stages of colorectal tumorigenesis, concomitantly with decreasing Sox9 in the Apcfl/fl mouse model38. Similarly, we have recently identified that rapamycin impairs glioma stem cell activity through silencing of SOX2 and SOX9 expression39. Given that the mammalian target of rapamycin (mTOR) is frequently activated in human colorectal cancers, and its natural inhibitor rapamycin and rapalogs are promising antitumor agents, whose efficacy is currently being tested in clinical trials with promising results40, we explored a potential relationship between the mTOR pathway and SOX9 in human colorectal cells. We observed that, in parallel to SOX9, the endogenous levels of phosphorylated S6 Ribosomal protein, downstream target and likely physiological effector of the mTOR pathway, were higher in SW620 than in SW480 cells (Fig. 6A). Next, we sought to establish whether rapamycin would be able to regulate metastatic cell activity through SOX9 activity. To answer this question, we first treated SW480 and SW620 cells with increasing concentrations of rapamycin (0.1, 10 and 100 nM) or vehicle (DMSO). SOX9 levels were not affected after cells cultured with the indicated concentrations of rapamycin (Fig. 6A). Given that the highest concentrations decreased the expression of SOX9 in glioma cells39, the effect of this agent on SOX9 expression seems to be context dependent. On the contrary, 10 and 100 nM concentrations of rapamycin decreased phosphorylated S6 more strongly in SW620 than in SW480 cells (Fig. 6A). This evidence supports the idea of enhanced impairment of mTOR signalling pathway in the metastatic cells. Moreover, we found that 10 nM of rapamycin was sufficient to cause a severe reduction in the formation of primary (66% decrease in rapamycin vs. vehicle treated) and secondary (90% reduction) tumorspheres in SW620 cells, without affecting that capacity in SW480 cells (Fig. 6B,C). Next, we checked the response of CR-CSCs with modulated levels of SOX9 to rapamycin treatment. For this, we treated gain and loss of SOX9 expression SW480 and SW620 cells with rapamycin (10 nM) or vehicle and cultured them under CSC conditions. Strikingly, SOX9-induced tumorsphere formation and self-renewal in SW480 cells was markedly attenuated by the presence of a 10 nM dose of the mTOR inhibitor (Fig. 6D). In contrast, that low dose of rapamycin promoted a decrease of 66 and 90% in primary and secondary tumorspheres in SW620 control cells, whereas the decline was only of 32 and 18% respectively in shSOX9 cells (Fig. 6E). These observations confirm that SOX9 levels sensitize CR-CSCs to rapamycin treatment, an effect likely mediated by the impairment of the mTOR signaling pathway, rather than the decline in SOX9 levels themselves. In order to validate the antitumor activity of rapamycin in cells with different SOX9 expression in vivo, we injected SW620 and SW480 cells subcutaneously in nude mice and treated animals with 5 mg/Kg of rapamycin twice a week. This treatment resulted in delayed tumor initiation and a significant decrease in tumor growth in SW620 cells (p < 0.01) compared to that observed with the vehicle control treatments (Fig. 7A–C). In contrast, the mTOR inhibitor did not affect tumor growth of SW480 cells (Fig. 7C). As shown in in vitro studies, phosphorylated S6 Ribosomal protein was markedly decreased whilst SOX9 showed similar expression in rapamycin compared to vehicle treated SW620 tumors (Fig. 7D). Finally, we also evaluated molecular markers for cell proliferation and apoptosis by immunohistochemistry. The expression of Ki67 was exclusively reduced (p < 0.05) in tumors obtained from SW620 cells treated with rapamycin (Fig. 7E and data not shown), whereas immunohistochemical staining for the apoptosis marker, fragmented PARP-1, was increased by rapamycin treatment (p = 0.004) (Fig. 7E). Together, these results show that rapamycin treatment attenuates CSC characteristics in colorectal cancer cells in a SOX9 expression dependent manner. There is considerable focus nowadays studying the impact of cancer cell plasticity and metastasis. It is hint towards a complex network concerning heterogeneous pools of cells, which might interact within them or dynamically switch their characteristics41. These activities may be regulated in response to intracellular stress or microenvironmental stimuli via not well established molecular mechanisms yet. Our data indicate that the dynamics of SOX9 expression regulate colorectal cancer cell plasticity in a cell-autonomous manner. SOX9 directs cancer cell self-renewal and proliferation programs, governing the transition between CR-CSCs and non-CSCs. These functions are important for metastatic spread (Fig. 7F). Importantly, SOX9 inhibition impairs self-renewal and invasive potential, indicating that it might be considered as a novel therapeutic target for advanced colorectal cancers. In relation to this, we reveal that SOX9 levels define the antitumor action of the mTOR inhibitor rapamycin in colorectal cells, providing preclinical evidence to justify further research into therapeutic strategies based on this agent, using SOX9 levels as a biomarker for patient stratification. Materials and Methods Patients and tumor samples Human colorectal carcinoma samples were provided by the Basque Biobank for Research-OEHUN (http://www.biobancovasco.org). The methods and experimental protocols in human samples were carried out in accordance with relevant guidelines, and all study participants signed informed consent form. The study was approved by the ethic committee of Biodonostia Institute and Hospital Donostia. Cell lines culture conditions SW480 and SW620 cell lines were obtained from the ATCC (American Type Culture Collection) and cultured as adherent monolayers in DMEM medium (Invitrogen) supplemented with 10% fetal bovine serum. Tumorspheres were cultured in DMEM/F12 medium (Sigma) supplemented with 20 ng/mL of EGF and bFGF (Sigma) growth factors, in the presence of N2 and B27. For tumorspheres studies, 0.5·103 cells/well were seeded in non-treated 12-well flat bottom plates and fresh medium was added every 3 days. After 10 days, primary (1ry) tumorspheres were counted. Then, spheres were disaggregated with Accutase, seeded for secondary (2ry) tumorspheres and maintained for another 10 days in culture. Viral infections Lentiviral infections were performed as previously described42. For gene knockdown, cells were transduced with two independent constructs; shSOX9 (a gift from Dr. Bob Weinberg, Addgene plasmid #40644)43 and shSOX9-2 (Sigma TRCN0000342824). For SOX9 overexpression, we used the plasmid #36979 from Addgene, a gift from Bob Weinberg43. Plasmids with point mutations in S64 and S181 (Sox9S64A,S181A) or WT forms of Sox9 were gifts from Dr. Cheung. Cells were infected for 6 hours with a multiplicity of infection of 10. mRNA expression analysis Total RNA was extracted with TRIzol (Life Technologies). Reverse transcription was performed using a High-Capacity cDNA Archive Kit (Life Technologies). Quantitative real-time PCR was performed using Power SYBR® Green Master Mix (Thermo Scientific), in an ABI PRISM 7300 thermocycler (Applied Biosystems). Variations in RNA input were corrected using the expression of the GAPDH housekeeping gene. The ΔΔCT method was used for relative quantification. Western blot and immunofluorescence analysis Immunoblot and immunofluorescence analysis were performed as previously described18. Primary antibodies used were: SOX9 (AB5535, Millipore), phospho-SOX9 (ab59252, abcam), BMI1 (05-637, Millipore), E-cadherin (BD610181, BD Transduction Laboratories), Vimentin (M7020, DAKO), N-Cadherin (BD610920, BD Transduction Laboratories), phospho-S6 Ribosomal protein (Cell Signaling Technology®, #4858) and β-actin (AC-15, Sigma). For Western blot detection of primary antibodies, we used HRP-linked antibodies (Santa Cruz Biotechnology) and detection was performed by chemiluminescence using NOVEX ECL Chemi Substrate (ThermoFisher). For immunofluorescence, secondary antibodies conjugated with fluorochromes were used and nuclear DNA was stained with Hoechst 33342 (Sigma). Images were obtained at a 40x magnification. Migration and invasion assays For wound healing (scratch) assays, cells were seeded at a confluence of 90% in 24-well flat-bottom plates and 12 hours later a linear artificial gap (scratch) was made in serum-deprived conditions for 48 hours. The non-filled area (i.e., not covered by cell migration) was quantified using Scion image software (Scion Corporation). Transwell cell migration was evaluated using 6.5-mm Transwell® chambers with 8.0-μm pore polycarbonate membrane inserts (Corning #3422). Invasion assays were performed using the QCM™ Collagen Cell Invasion Assay (ECM551, Millipore). Invading cells were quantified 24 hours after the seeding. In vivo carcinogenesis assays For subcutaneous injection, SW480 and SW620 cells were harvested with trypsin/EDTA and resuspended in PBS. Cells (1·106) were injected subcutaneously into both flanks of Foxn1nu/Foxn1nu nude mice (8 weeks old). Mice were examined twice a week and external calipers were used to measure tumor size at the indicated time points from which tumor volume was calculated according to the formula ½(length × width2). For rapamycin experiments, SW620 and SW480 cells were treated for 48 h with rapamycin 10 nM before subcutaneous implantation (1·106 cells in PBS). Five days later, mice were injected intraperitoneally with rapamycin (5 mg/kg) or vehicle twice a week during the experiment. Tumor volume was estimated as described above. Immunohistochemistry Tumors generated in mice were dissected, fixed in 10% formalin for 48h and embedded in paraffin. 4 micrometer-thick sections were incubated with primary antibodies (SOX9, AB5535 (Millipore); Ki67, ab15580 (Abcam); Vimentin, M7020 (DAKO); phospho-S6 Ribosomal protein (Cell Signaling Technology®, #4858), and fragmented PARP-1, 32064 (Abcam) at 37 °C for 2 hours. The sections then were washed and incubated with MACH 3 Rabbit/Mouse Probe and MACH 3 HRP-Polymer (M3R531, Biocare Medical). Immunostaining was developed with 3,3′Diaminobenzidine (DAB, SPR-DAB-060, Spring Bioscience). Data analysis Data are presented as mean values ± S.E.M. with the number of experiments (n) in parenthesis. Unless otherwise indicated, statistical significance (p-values) was calculated using the Student’s t test. Asterisks (*, **, and ***) indicate statistical significance (p < 0.05, p < 0.01, and p < 0.001, respectively). Additional Information How to cite this article: Carrasco-Garcia, E. et al. SOX9-regulated cell plasticity in colorectal metastasis is attenuated by rapamycin. Sci. Rep. 6, 32350; doi: 10.1038/srep32350 (2016). PA was recipient of a predoctoral fellowship from the Spanish Association Against Cancer (AECC Gipuzkoa), and JA from SuperH foundation. We thank the Histology Platform staff of the Biodonostia Health Research Institute for their help. This work was supported by grants from Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (CP10/00539, PI13/02277), European Union (Marie Curie CIG 2012/712404) to AM, the Department of Health of the Basque Government to SA, and the Department of Industry of the Basque Government (SAIO13-PC11BN002 to AM, SAIO13-PC13BN010 to ECG and SAIO13-PC13BN011 to IG). Author Contributions E.C.-G., L.L., P.A., L.E., J.A. and I.G. performed the experimental research; S.A., N.S. and L.B. collected patient samples, M.C. contributed with design and production of reagents and all of them revised the manuscript; S.A., N.S., E.C.-G. and I.G. helped to support the project; A.M. designed the research, directed the work and wrote the manuscript. Figure 1 High levels of SOX9 correlate with CR-CSCs. (A) Higher expression of stem cell markers in SW620 than in SW480 cells (n ≥ 3). (B) SOX9 mRNA expression relative to GAPDH in normal and tumoral colonic paired human samples and in SW480 and SW620 cell lines. (C) Higher SOX9 protein expression and phospho-SOX9 (S181) in SW620 cells than in SW480 cells. (D) Number of tumorspheres derived from SW480 and SW620 cells (n = 6). (E) SOX9 and BMI1 protein expression in tumorspheres and in parental SW480 and SW620 cells (n = 3). (F) Stem cell marker mRNA expression levels in tumorspheres relative to the corresponding parental cells (n ≥ 3). Figure 2 SOX9 overexpression provides self-renewal ability. (A) Representative immunoblots of SOX9 and BMI1 in SW480 cells transduced with SOX9 (SOX9) or empty vector (control) (n = 3). (B) Number of primary and secondary tumorspheres in control and SOX9 overexpressing SW480 cells (n ≥ 3). (C) Tumor initiation ability of indicated genotypes. Frequency of tumors formed in immunocompromised mice after subcutaneous injection of 1·106 cells. (D) Number of tumorspheres formed in control (−), Sox9S64A,S181A and WT Sox9 SW480 transduced cells (n = 3). Figure 3 SOX9 contributes to gain of metastatic traits in CRC cells. (A) Representative image and quantification of non-filled area in wound healing assays of SW480 control and SOX9 overexpressing cells (n = 4). (B) Representative images and quantification of transwell invasion for the indicated genotypes (n ≥ 3). (C) Representative images and quantification of transwell migration of SW480 control (−) compared to cells transduced with Sox9S64A,S181A or a WT form of SOX9 (WT-Sox9) (n = 2). (D) Quantification of transwell in vitro invasion for the indicated conditions (n = 2). (E) Representative images of immunofluorescence studies of E-Cadherin and Vimentin in control and SOX9 overexpressing SW480 cells (n ≥ 2). (F) Representative Western blot of Vimentin in the indicated genotypes (n = 2). (G) Vimentin expression detected by immunofluorescence in SW480 cells transduced with the wt (WT Sox9) or the Sox9S64A,S181A mutant form of SOX9 (n = 2). Figure 4 SOX9 silencing impairs self-renewal of SW620 cells. (A) Representative immunoblots of SOX9 and BMI1 protein expression in empty vector (pLKO) and shSOX9 SW620 cells (n ≥ 3). (B) SOX9 mRNA levels in shSOX9 SW620 relative to pLKO cells (n = 3). (C) Plot of the number of primary and secondary tumorspheres in the indicated conditions (n ≥ 5). (D) Tumor initiation ability of the indicated cellular genotypes. Frequency of tumors formed in immunocompromised mice after subcutaneous injection of 1·106 cells per injection. (E) Tumor volume calculated at the indicated time points in nude mice injected with pLKO or two independent shSOX9 constructs (shSOX9 and shSOX9-2) (1·106 cells per injection). (F) Representative image showing the generated tumors per genotype. (G) Immunohistochemistry of SOX9 and Ki67 staining in SW620 derived tumors from pLKO or shSOX9 conditions (n = 4). (H) Quantification of percentage of Ki67 positive cells in SW620 derived tumors from pLKO or shSOX9 conditions (n = 4). Figure 5 SOX9 silencing impairs metastatic phenotypes of SW620 cells. (A) Transwell invasion in SW620 shSOX9 cells relative to SW620 control cells analyzed 24 hours after seeding (n = 3). (B) Vimentin and N-Cadherin mesenchymal markers expression analyzed by immunofluorescence in SW620 pLKO and shSOX9 cells (n ≥ 2). (C) Representative western blot of Vimentin and N-Cadherin in SW620 pLKO and shSOX9 cells (n ≥ 2). (D) Vimentin expression detected by immunohistochemistry in subcutaneous tumors generated by pLKO and shSOX9 cells (n = 4). Figure 6 High SOX9 levels sensitize colorectal cancer cells to rapamycin. (A) Representative immunoblot of phospho-S6 Ribosomal protein (Ser235/Ser236) (p-S6), SOX9 and β-actin protein expression in SW480 and SW620 cells treated with the indicated concentrations of rapamycin for 24 hours (n = 2). (B) Number of primary tumorspheres in SW480 and SW620 cells treated with vehicle (−) or rapamycin 10 nM (Rap) (n = 4). (C) Number of secondary tumorspheres derived from SW480 and SW620 primary tumorspheres treated with vehicle (−) or rapamycin 10 nM (Rap) (n = 4). (D) Number of tumorspheres formed by control and SOX9 overexpressing SW480 cells in the presence or absence of rapamycin 10 nM (Rap) (n = 3). (E) Number of tumorspheres formed by pLKO and shSOX9 SW620 cells in the presence or absence of rapamycin 10 nM (Rap) (n = 3). Figure 7 Rapamycin impairs tumor growth in SW620 metastatic cells. (A) Percentage of nude mice harbouring SW620 derived tumors at the indicated time points after intraperitoneal treatment with vehicle (−) or rapamycin 5 mg/Kg (Rap) twice a week (n = 8). Log-rank test (*p ≤ 0.05) (B) Representation of tumor volume formed by SW620 cells in immunocompromised mice treated with vehicle (−) or rapamycin 5 mg/Kg (Rap) (n = 8). (C) Representative image of tumors formed from SW620 and SW480 cells treated with vehicle (−) or rapamycin 5 mg/Kg (Rap). (D) Representative images of Ki67, fragmented PARP-1, p-S6, and SOX9 immunostaining in SW620 derived tumors in the indicated conditions (n = 4). (E) Quantification of percentage of Ki67 and fragmented PARP positive cells (n = 3). (F) Illustrative image of the role of SOX9 in CRC cell plasticity. The expression of SOX9 regulates stemness activity and EMT plasticity in CRC cells mediating the pro-metastatic abilities of migration and invasion. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3240910.1038/srep32409ArticleFunction of RSKS-1-AAK-2-DAF-16 signaling cascade in enhancing toxicity of multi-walled carbon nanotubes can be suppressed by mir-259 activation in Caenorhabditis elegans Zhuang Ziheng a12Li Min 13Liu Hui 1Luo Libo 2Gu Weidong 2Wu Qiuli 3Wang Dayong b31 School of Pharmaceutical Engineering and Life Sciences, Changzhou University, Changzhou 213164, China2 Changzhou No. 7 People’s Hospital, Changzhou 213011, China3 Key Laboratory of Environmental Medicine Engineering in Ministry of Education, Medical School, Southeast University, Nanjing 210009, Chinaa cczuzzh@163.comb dayongw@seu.edu.cn30 08 2016 2016 6 3240912 04 2016 04 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Caenorhabditis elegans is an important non-mammalian alternative assay model for toxicological study. Previous study has indicated that exposure to multi-walled carbon nanotubes (MWCNTs) dysregulated the transcriptional expression of mir-259. In this study, we examined the molecular basis for mir-259 in regulating MWCNTs toxicity in nematodes. Mutation of mir-259 induced a susceptible property to MWCNTs toxicity, and MWCNTs exposure induced a significant increase in mir-259::GFP in pharyngeal/intestinal valve and reproductive tract, implying that mir-259 might mediate a protection mechanisms for nematodes against MWCNTs toxicity. RSKS-1, a putative ribosomal protein S6 kinase, acted as the target for mir-259 in regulating MWCNTs toxicity, and mutation of rsks-1 suppressed the susceptible property of mir-259 mutant to MWCNTs toxicity. Moreover, mir-259 functioned in pharynx-intestinal valve and RSKS-1 functioned in pharynx to regulate MWCNTs toxicity. Furthermore, RSKS-1 regulated MWCNTs toxicity by suppressing the function of AAK-2-DAF-16 signaling cascade. Our results will strengthen our understanding the microRNAs mediated protection mechanisms for animals against the toxicity from certain nanomaterials. ==== Body Multi-walled carbon nanotubes (MWCNTs), one member of the carbon nanotubes (CNTs), have numerous unique physicochemical properties. So far, MWCNTs have been produced in bulk for diverse purposes. With the increase in MWCNTs manufacture, it is likely that the increasing exposure of human and environmental organisms to MWCNTs will occur12. The potential toxic effects of ENMs including the MWCNTs on organisms have received the great attentions345. It has been shown that exposure to CNTs can lead to several aspects of toxicity on organisms through the induction of oxidative stress and/or inflammation and crossing the biological barriers6789. To determine the underlying molecular mechanisms of MWCNTs toxicity, some dysregulated genes or microRNAs (miRNAs) have been identified in mice or NIH/2Ts cells1011. miRNAs, a class of short noncoding RNAs, usually exhibit their biological functions by post-transcriptionally inhibiting the expression of targeted genes12. Due to the properties of short lifespan, ease of manipulation, and especially the well-described genetic background131415, the important non-mammalian alternative toxicity assay model of Caenorhabditis elegans has been recently used in the toxicological study of MWCNTs. In nematodes, MWCNTs exposure could cause the damage on the functions of both primary targeted organs such as intestine and secondary targeted organs such as neurons and reproductive organs16171819. MWCNTs could be further translocated into the secondary targeted organs such as the reproductive organs in nematodes161720. Moreover, based on the SOLiD sequencing, some dysregulated miRNAs have been identified in MWCNTs exposed nematodes21. Biological functions of some dysregulated miRNAs in regulating MWCNTs toxicity have been confirmed with the aid of the available mutants21. Nevertheless, the molecular signaling pathways mediated by these candidate miRNAs in regulating MWCNTs toxicity are still largely unclear in nematodes. Previous study has demonstrated that MWCNTs exposure increased the expression of mir-259 in nematodes21. In nematodes, mutation of mir-259 induced a susceptible property to MWCNTs toxicity21. The MWCNTs (1 mg/L) exposed mir-259(n4106) mutant exhibited a more significant reduction in brood size, decrease in locomotion behavior, and induction of intestinal autofluorescence or reactive oxygen species (ROS) production than MWCMTs exposed wild-type nematodes21. However, the underlying epigenetic mechanism for mir-259 in regulating MWCNTs toxicity is still unclear. In this study, we investigated the molecular signaling mediated by mir-259 in regulating MWCNTs toxicity in the in vivo assay system of C. elegans. In nematodes, rsks-1 gene encodes a putative ribosomal protein S6 kinase (S6K) that is required for the longevity control22, aak-2 gene encodes a catalytic alpha subunit of AMP-activated protein kinases (AMPKs), and daf-16 gene encodes a FOXO transcriptional factor in the insulin signaling pathway. We raised a RSKS-1-AAK-2-DAF-16 signaling cascade mediated by mir-259 in the control of MWCNTs toxicity in nematodes. Our study reveals the key function of mir-259 mediated signaling cascade in encoding a protection mechanism for nematodes against the MWCNTs toxicity. Results Effects of MWCNTs exposure on lifespan and locomotion behavior during aging in mir-259 mutant nematodes Lifespan can reflect the long-term effect of certain toxicants on animals. mir-259(n4106) has the similar lifespan to that in wild-type nematodes (Fig. 1a). After prolonged exposure, MWCNTs (1 mg/L) exposed mir-259(n4106) mutant exhibited the significantly reduced lifespan than MWCNTs (1 mg/L) exposed wild-type nematodes (Fig. 1a). Moreover, we selected the endpoint of locomotion behavior to assess the change of aging-related property during aging in MWCNTs exposed nematodes23. mir-259(n4106) has the similar head thrash and body bend to those in wild-type nematodes (Fig. 1b). After prolonged exposure, MWCNTs (1 mg/L) exposed mir-259(n4106) mutant showed the significantly decreased head thrash or body bend at adult day-8 than MWCNTs (1 mg/L) exposed wild-type nematodes (Fig. 1b). Therefore, MWCNTs exposure may cause the adverse effects on lifespan and aging related properties such as locomotion behavior during aging in nematodes. Effect of MWCNTs exposure on spatial expression of mir-259 in nematodes With the aid of transgenic strain of maIs268[mir-259::GFP], we investigated the effect of MWCNTs exposure on spatial expression of mir-259::GFP. In nematodes, mir-259 is expressed in pharyngeal/intestinal valve and reproductive tract24. After prolonged exposure, MWCNTs (1 mg/L) significantly increased the fluorescence intensity of mir-259::GFP in pharyngeal/intestinal valve and reproductive tract compared in nematodes (Fig. 2). Tissue-specific activity of mir-259 in regulating MWCNTs toxicity in nematodes With the aid of tissue-specific promoters, we next investigated the tissue-specific activity of mir-259 in regulating MWCNTs toxicity in nematodes. Rescue assay by expression of mir-259 in intestine, pharynx, or reproductive tract did not significantly influence the susceptible property of mir-259(n4106) mutant nematodes to MWCNTs toxicity on lifespan (Fig. 3). In contrast, expression of mir-259 in pharynx/intestinal valve could significantly suppress the susceptible property of mir-259(n4106) mutant nematodes to MWCNTs toxicity on lifespan (Fig. 3). These results imply that mir-259 may act in the pharynx/intestinal valve to regulate MWCNTs toxicity in nematodes. rsks-1 might act as the potential targeted gene for mir-259 in nematodes Using the TargetScan tool, we found that mir-259 may function as an upstream regulator for rsks-1 gene by binding its 3′-UTR. In the loss-of-function mir-259(n4106) mutant, the expression of rsks-1 gene was significantly increased compared with that in wild-type nematodes (Fig. 4a), implying that mir-259 may inhibit the expression of rsks-1 gene. RSKS-1 was involved in the control of MWCNTs toxicity in nematodes Using the loss-of-function rsks-1(ok1255) mutant, we investigated the potential function of RSKS-1 in the control of MWCNTs toxicity in nematodes. The rsks-1(ok1255) mutant has the similar lifespan and locomotion behavior to those in wild-type nematodes (Fig. 4b,c). After prolonged exposure, the MWCNTs (1 mg/L) exposed rsks-1(ok1255) mutant exhibited the similar lifespan and locomotion behavior at adult day-8 to those in rsks-1(ok1255) mutant or wild-type nematodes without MWCNTs exposure (Fig. 4b,c). That is, the rsks-1(ok1255) mutant had the resistant property to MWCNTs toxicity in nematodes. Genetic interaction between mir-259 and rsks-1 in regulating MWCNTs toxicity in nematodes To confirm the interaction between mir-259 and rsks-1 in regulating MWCNTs toxicity, we compared the MWCNTs toxicity in double mutant of rsks-1(ok1255);mir-259(n4106) with that in single mutant of mir-259(n4106) or rsks-1(ok1255). After MWCNTs (1 mg/L) exposure, the lifespan and locomotion behavior at adult day-8 in double mutant of rsks-1(ok1255);mir-259(n4106) were similar to those in single mutant of rsks-1(ok1255) (Fig. 5), implying that the susceptible property of mir-259(n4106) mutant to MWCNTs toxicity on lifespan and aging-related properties could be suppressed by rsks-1 mutation in nematodes. Therefore, mir-259 may inhibit the function of RSKS-1 in positively regulating the MWCNTs toxicity in nematodes. Tissue-specific activity of rsks-1 in regulating MWCNTs toxicity in nematodes In C. elegans, rsks-1 gene is expressed in pharynx and hypodermis16. Using the tissue-specific promoters, we investigated the tissue-specific activity of rsks-1 in regulating MWCNTs toxicity in nematodes. Rescue assay by expression of rsks-1 in hypodermis did not significantly influence the lifespan in MWCNTs (1 mg/L) exposed rsks-1(ok1255) mutant nematodes (Fig. 6). In contrast, expression of rsks-1 in pharynx could significantly decrease the lifespan in MWCNTs (1 mg/L) exposed rsks-1(ok1255) mutant nematodes (Fig. 6). These results suggest that RSKS-1 may act in the pharynx to regulate MWCNTs toxicity in nematodes. Genetic interaction between rsks-1 and aak-2 in regulating MWCNTs toxicity in nematodes Previous study has implied that AAK-2 may act as an important molecular target for RSKS-1 in regulating longevity22. To determine whether RSKS-1 can act though the AAK-2 mediated signaling to regulate MWCNTs toxicity, we compared the MWCNTs toxicity in double mutant of rsks-1(ok1255);aak-2(ok524) with that in single mutant of rsks-1(ok1255) or aak-2(ok524). After MWCNTs (1 mg/L) exposure, the lifespan and locomotion behavior at adult day-8 in double mutant of rsks-1(ok1255);aak-2(ok524) were similar to those in aak-2(ok524) mutant nematodes (Fig. 7), suggesting that the resistant property of rsks-1(ok1255) mutant to MWCNTs toxicity on lifespan and aging-related properties could be inhibited by aak-2 mutation in nematodes. These results imply that RSKS-1 may genetically act upstream of AAK-2 to regulate MWCNTs toxicity in nematodes. Genetic interaction between aak-2 and daf-16 in regulating MWCNTs toxicity in nematodes Previous study has further suggested AAK-2 may function upstream of DAF-16 in insulin signaling pathway to regulate biological processes such as longevity in nematodes22. To determine the genetic interaction between aak-2 and daf-16 in regulating MWCNTs toxicity, we compared the MWCNTs toxicity in double mutant of daf-16(mu86);aak-2(om524) with that in single mutant of daf-16(mu86) or aak-2(om524). After MWCNTs (1 mg/L) exposure, we found that the lifespan and locomotion behavior at adult day-8 in double mutant of daf-16(mu86);aak-2(om524) were similar to those in single mutant of aak-2(om524) or daf-16(mu86) nematodes (Fig. 8), implying that AAK-2 can act together with DAF-16 in the same genetic pathway to regulate the MWCNTs toxicity in nematodes. Distribution and translocation of MWCNTs in mir-259, rsks-1, aak-2, and daf-16 mutant nematodes Biodistribution and translocation are crucial factors for the toxicity formation of ENMs in nematodes15. With the aid of molecular probe of Rhodamine B (Rho B), we prepared the MWCNTs/Rho B. After MWCNTs/Rho B exposure, we observed a more pronounced MWCNTs/Rho B distribution in the body of mir-259(n4106), aak-2(ok524), and daf-16(mu86) mutants compared with wild-type N2 (Fig. 9). In contrast, mutation of rsks-1 gene significantly suppressed the distribution of MWCNTs/Rho B in the body of nematodes compared with wild-type N2 (Fig. 9). Exposure to Rho B caused the relatively equal distribution of fluorescence in the tissues of wild-type N2, mir-259(n4106), rsks-1(ok1255), aak-2(ok524), or daf-16(mu86) mutant nematodes (Fig. S1). Therefore, mutation of the mir-259, aak-2, or daf-16 enhanced the biodistribution and translocation of MWCNTs in the body, whereas mutation of rsks-1 suppressed the accumulation of MWCNTs in the body of nematodes. Discussion Our previous study has demonstrated that, after MWCNTs exposure, loss-of-function mutation of mir-259 could cause the more significant reduction in brood size, decrease in locomotion behavior, and induction of intestinal autofluorescence or ROS production compared with wild-type nematodes21. In this study, after MWCNTs exposure, we further observed that mutation of mir-259 could result in the more reduced lifespan, and more severely decreased locomotion behavior during the aging (Fig. 1). Therefore, our results suggest that, besides the functions of primary and secondary targeted organs, MWCNTs exposure may further potentially adversely affect the longevity and aging related phenotypes in organisms. Using the transgenic strain of maIs268, we observed that MWCNTs could significantly increase the expression of mir-259::GFP in both the pharyngeal/intestinal valve and the reproductive tract (Fig. 2). Meanwhile, we found that the loss-of-function mir-259 mutant was susceptible to MWCNTs toxicity in nematodes21 (Fig. 1). These data imply that mir-259 may mediate a protection mechanism for nematodes against the MWCNTs toxicity. That is, MWCNTs may induce a protection mechanism encoded by the activated mir-259 in nematodes. Similarly, previous study has demonstrated that the activated mir-360 may encode a protection mechanism for nematodes against the toxic effects of graphene oxide (GO) in inducing germline apoptosis25. Previous studies have suggested that some important signaling pathways can act in certain tissues to regulate the toxicity of ENMs in nematodes. For example, acs-22 gene encoding a protein homologous to mammalian fatty acid transport protein 4 could act in the intestine to regulate MWCNTs toxicity20, and insulin signaling pathways could act in the intestine to regulate the GO toxicity26. unc-30 gene encoding a homeodomain transcription factor could act in the RMEs or D-type GABAergic motor neurons to regulate the neurotoxicity of quantum dots (QDs)2728. In this study, using the tissue-specific promoters, we found that the mir-259 acted in the pharynx/intestinal valve to regulate MWCNTs toxicity in nematodes (Fig. 3), implying the potential important function of mir-259 in affecting the function of pharynx/intestinal valve. We observed that mutation of mir-259 enhanced the distribution of MWCNTs/Rho B in the body of nematodes (Fig. 9). Moreover, our results further imply the possible important role of pharynx/intestinal valve in the control of toxicity and translocation of certain ENMs in nematodes. In this study, we provide several lines of evidence to indicate the potential role of RSKS-1 as the target for mir-259 in regulating the MWCMTs toxicity in nematodes. We observed that the phenotypes in MWCNTs exposed rsks-1 mutant were opposite to those in MWCNTs exposed mir-259 mutant. The rsks-1 mutant was resistant to the MWCNTs toxicity on longevity and aging related phenotypes (Fig. 4). Moreover, we found that mutation of the rsks-1 gene could suppress the susceptible property of mir-259(n4106) mutant to MWCNTs toxicity on lifespan and aging-related properties (Fig. 5). Therefore, although we did not exclude the possible involvement of other targets in the control of MWCNTs toxicity, our results indicated that mir-259 can negatively regulate the MWCNTs toxicity by inhibiting the function of RSKS-1, one of its important targets. For the tissue-specific activity, our results suggest that rsks-1 gene acted in the pharynx to regulate the MWCNTs toxicity on longevity and aging related phenotypes in nematodes (Fig. 6). Based on the distribution pattern of MWCNTs/Rho B, we also found that mutation of rsks-1 significantly suppressed the deposition of MWCNTs in the body of nematodes (Fig. 9). Considering the fact that RSKS-1 acted in the pharynx to regulate the MWCNTs toxicity, the MWCNTs uptake by feeding might be altered in the rsks-1 mutant nematodes. In contrast, the altered MWCNTs translocation into the secondary targeted organs through the intestinal barrier might be not directly due to the rsks-1 mutation in nematodes. That is, our data suggest the important role of rsks-1 gene in the pharynx in regulating the toxicity and accumulation of MWCNTs. Meanwhile, our data also imply the possible crucial role of pharynx in the control of toxicity and accumulation of certain ENMs in nematodes. In this study, we identified the downstream signaling cascade for RSKS-1 in regulating the MWCNTs toxicity. In C. elegans, aak-2 can function downstream of stressors and energy level signals to positively regulate the adult lifespan29. Here we further showed that AAK-2 functioned downstream of RSKS-1 to regulate the MWCNTs toxicity, since mutation of the aak-2 gene suppressed the resistant property of rsks-1(ok1255) mutant to MWCNTs toxicity on the longevity and the aging related phenotypes (Fig. 7). Moreover, our results suggest that AAK-2 may further regulate the MWCNTs toxicity on longevity and aging related phenotypes by acting with the transcriptional factor DAF-16 in the same genetic pathway (Fig. 8). Therefore, RSKS-1 may act upstream of the AAK-2-DAF-16 signaling cascade to regulate the MWCNTs toxicity in nematodes. The AAK-2-DAF-16 signaling cascade was also shown to be involved in the longevity regulation in nematodes22, implying that the AAK-2-DAF-16 signaling cascade may be a conserved signaling cascade involved in the control of biological processes in nematodes. Nevertheless, RSKS-1, AAK-2, and DAF-16 may not regulate the MWCNTs toxicity by forming a complex, because RSKS-1 acted in the pharynx to regulate the MWCNTs toxicity and DAF-16 normally acted in the intestine to regulate the nanotoxicity and innate immunity2630. In addition, previous studies have only shown that AAK-2 can physically interact with ICD-1, ICD-2, F49E8.7, or UNC-42 to regulate biological processes in nematodes (http://www.wormbase.org/species/c_elegans/gene/WBGene00020142#01-9g8-10). In C. elegans, the insulin receptor DAF-2 can reduce the longevity or enhance the toxicity of certain toxicants such as MWCNTs by suppressing the expression and function of DAF-16313233. Our recent study has demonstrated that MWCNTs exposure would inhibit the expression of mir-355, which further induced the toxic effects of MWCNTs on nematodes by suppressing the function of DAF-233. Therefore, on the one hand, MWCNTs may suppress the function of DAF-16 in inducing the toxicity of MWCNTs on nematodes by inhibiting the expression of mir-355; on the other hand, MWCNTs may be also able to potentially enhance the function of DAF-16 in decreasing the toxicity of MWCNTs on nematodes by increasing the expression of mir-259 (Fig. 10). In conclusion, in this study, we investigated the molecular basis for mir-259 in regulating MWCNTs toxicity. In nematodes, activation of the mir-259 mediated a protection mechanism for animals against the MWCNTs toxicity on longevity and aging related phenotypes. During the control of MWCNTs toxicity, RSKS-1 acted as an important target for mir-259. mir-259 acted in the pharynx-intestinal valve and rsks-1 acted in the pharynx to regulate MWCNTs toxicity. Moreover, RSKS-1 functioned upstream of the AAK-2-DAF-16 signaling cascade and suppressed the function of this signaling cascade to regulate MWCNTs toxicity. The C. elegans mir-259 is the homologue of human miR-21634. Our results highlight the important role of miRNAs mediated protection mechanisms for animals against the adverse effects from environmental toxicants. Methods Characterization of MWCNTs MWCNTs (diameter: 10–20 nm, length: 6–15 μm) were from Shenzhen Nanotech. Port Co. Ltd (Shenzhen, China). MWCNTs morphology in K-medium (50 mM NaCl, 30 mM KCl, 10 mM NaOAc, pH 6.0) was examined by transmission electron microscopy (TEM, JEM-200CX, JEOL, Japan) (Fig. S2a). Length distribution of MWCNTs was shown in Fig. S2b. Fourier transform infrared spectroscopy (FTIR) of MWCNTs was determined (Avatar 370, Thermo Nicolet, USA). The peak at 3367 cm−1 in the spectra of MWCNTs was attributed to -OH groups, the peak at 2850 cm−1 in the spectra of MWCNTs was attributed to C-H (sp3), the peak at 1629 cm−1 in the spectra of MWCNTs was attributed to C-H stretching, the peak at 1053 cm−1 in the spectra of MWCNTs was attributed to C-O stretching, and the peak at 2916 cm−1 in the spectra of MWCNTs was attributed to the stretching vibrations of alkyl groups (Fig. S2c). The FTIR spectra of MWCNTs implies the normal chemical structure on the surface of MWCNTs after sonication. Zeta potential of MWCNTs was analyzed by Nano Zetasizer (Nano ZS90, Malvern Instrument, UK). Zeta potential of MWCNTs in K-medium was −33.4 ± 2.5 mV. C. elegans strains and exposure Nematode strains used in this study contain wild-type N2, mutants of mir-259(n4106), rsks-1(ok1255), aak-2(ok524), daf-16(mu86), aak-2(ok524);rsks-1(ok1255), daf-16(mu86);aak-2(om524), and rsks-1(ok1255);mir-259(n4106), and transgenic strains of maIs268[mir-259::GFP], mir-259(n4106)Ex(Pmyo-2-mir-259), mir-259(n4106)Ex(Pges-1-mir-259), mir-259(n4106)Ex(Ppie-1-mir-259), mir-259(n4106)Ex(Pref-1-mir-259), rsks-1(ok1255)Ex(Pmyo-2-rsks-1), and rsks-1(ok1255)Ex(Pdpy-7-rsks-1). mir-259(n4106) is a loss-of-function mutation with the deletion. The deletion breakpoints are: GATTATAATGCAAACAACCTGGGGGATC/CAGTATCTTCA…AAGAGCGAAAGT/ACAGTCTCCTCCTTCTTTGCTCACTTCT. rsks-1(ok1255) is a loss-of-function mutation with the deletion of 1700 bp. aak-2(ok524) is a loss-of-function mutation with the deletion of 409 bp. daf-16(mu86) is a loss-of-function mutation with an 11 kb daf-16 genomic deletion that removes nearly all of the winged-helix domain and ~1 kb upstream of the 5′ UTR. Some strains were purchased from Caenorhabditis Genetics Center (funded by NIH Office of Research Infrastructure Programs (P40 OD010440)). Gravid nematodes were maintained on nematode growth medium (NGM) plates seeded with Escherichia coli OP50, and were lysed with a bleaching mixture (0.45 M NaOH, 2% HOCl) after washing animals off the plates into centrifuge tubes13. Synchronous L1-larvae nematodes were prepared as described35. Exposure and toxicity assessment MWCNTs were dispersed in K medium to prepare a stock solution (1 mg/mL). The stock MWCNTs solution was sonicated for 30 min (40 kHz, 100 W), and diluted to the used concentration (1 mg/L) with K medium just prior to exposure. Prolonged exposure to MWCNTs was performed from L1-larvae to young adults in 12-well sterile tissue culture plates at 20 °C in the presence of food (OP50). After MWCNTs exposure, the nematodes were used for the toxicity assessment using endpoints of lifespan and locomotion behavior. Lifespan was assayed at 20 °C basically as described3637. During the lifespan assay, the hermaphrodite nematodes were transferred daily for the first 7 days of adulthood. Nematodes would be checked every two-day, and were scored as dead if they did not move even after repeated taps with a pick. Sixty nematodes were examined per treatment, and three replicates were performed. Endpoints of head thrash and body bend were used to reflect the locomotion behavior of nematodes as described3839. Head thrash and body bend were assessed under the dissecting microscope by eyes. A head thrash is defined as a change in the direction of bending at the mid body. A body bend is defined as a change in the direction of the part of the nematodes corresponding to the posterior bulb of the pharynx along the y axis, assuming that nematode was traveling along the x axis. Adult day-1 was used as a control for assay of locomotion behavior during aging. Twenty nematodes were examined per treatment, and six replicates were performed. Bioinformatics analysis for targeted gene prediction of mir-259 The corresponding targeted genes for mir-259 were predicted using TargetScan version 6.2 (http://www.targetscan.org/worm_52/). TargetScan is a tool for searching for the presence of conserved sites that match seed region of a miRNA so as to predict the biological targets of certain miRNA. Reverse-transcription and quantitative real-time polymerase chain reaction (qRT-PCR) Total RNAs extracted using RNeasy Mini kit (Qiagen) were reverse transcribed using PrimeScript™ RT reagent kit (Takara, Otsu, Shiga, Japan). Purity and concentration of RNAs were evaluated by OD260/280 in a spectrophotometer. cDNA synthesis was performed in a 12.5 μL reaction volume containing 625 ng total RNA, 0.5 mM reverse-transcript primers, 50 mM Tris-HCl, 75 mM KCl, 3 mM MgCl2, 10 mM dithiothreitol, 20 units ribonuclease inhibitor, and 100 U reverse transcriptase (Takara, China). After cDNA synthesis, real-time PCR was performed using SYBR Premix Ex Taq™ (Takara) for the amplification of the examined gene. Real-time PCR was performed using primers for target gene of rsks-1 (forward primer, 5′-CCGTTTGTGGGATTCACC-3′; reverse primer, 5′-TGGCTTTCTCGGGCTCTT-3′), and reference gene of tba-1 (forward primer, 5′-TCAACACTGCCATCGCCGCC-3′; reverse primer, 5′-TCCAAGCGAGACCAGGCTTCAG-3′). Relative quantification of targeted gene of rsks-1 in comparison to reference tba-1 gene was determined, and the final results were expressed as relative expression ratio between targeted gene and reference gene. All reactions were performed in triplicate. DNA constructs and germline transformation To generate entry vector carrying promoter sequence, promoter region for ges-1 gene specially expressed in the intestine, myo-2 gene specially expressed in the pharynx, pie-1 gene expressed in the reproductive tract, ref-1 gene specially expressed in the valve between pharynx and intestine, or dpy-7 gene specially expressed in the hypodermis was amplified by PCR from wild-type C. elegans genomic DNA. These promoter fragments were inserted into pPD95_77 vector in the sense orientation. rsks-1/Y47D3A.16 cDNA or mir-259 was amplified by PCR, and inserted into corresponding entry vector carrying the ges-1, myo-2, pie-1, ref-1, or dpy-7 promoter sequence. Germline transformation was performed by coinjecting testing DNA at the concentration of 10–40 μg/mL and marker DNA of Plin-44::gfp at the concentration of 60 μg/mL into the gonad of nematodes as described40. Distribution and translocation of MWCNTs To investigate the distribution and translocation of MWCNTs, Rho B was loaded on MWCNTs by mixing Rho B (1 mg/mL, 0.3 mL) with MWCNTs (0.1 mg/mL, 5 mL) as described previously20. The unbound Rho B was removed by dialysis against the distilled water over 72-h. The prepared MWCNTs/Rho B was stored at 4 °C before use. Nematodes were incubated with MWCNTs/Rho B at the concentration of 1 mg/L for 3-h. After incubation, nematodes were washed with M9 buffer for three times. The exposed nematodes were analyzed under a fluorescence microscopy. Rho B treatment was used as the control. Twenty nematodes were examined per treatment. Statistical analysis Data were expressed as means ± standard deviation (SD). Graphs were prepared with Microsoft Excel software (Microsoft Corp., Redmond, WA). Statistical analysis was performed using SPSS 12.0 software (SPSS Inc., Chicago, USA), and the differences between groups were determined using analysis of variance (ANOVA). The probability levels of 0.05 and 0.01 were considered to be statistically significant. The lifespan data were analyzed using a 2-tailed 2 sample t-test (Minitab Ltd, Coventry, UK). Additional Information How to cite this article: Zhuang, Z. et al. Function of RSKS-1-AAK-2-DAF-16 signaling cascade in enhancing toxicity of multi-walled carbon nanotubes can be suppressed by mir-259 activation in Caenorhabditis elegans. Sci. Rep. 6, 32409; doi: 10.1038/srep32409 (2016). Supplementary Material Supplementary Information This work was supported by the grant from Fundamental Research Funds for the Central Universities in China (no. 2242016K41059). Author Contributions D.W. designed the project. Z.Z., M.L., H.L., L.L., W.G. and Q.W. carried out the experiments. D.W. wrote the manuscript. All authors discussed the results and reviewed the manuscript. Figure 1 Effects of MWCNTs exposure on lifespan and locomotion behavior during aging in nematodes. (a) Effects of MWCNTs exposure on lifespan in nematodes. (b) Effects of MWCNTs exposure on locomotion behavior during aging in nematodes. Exposure concentration of MWCNTs was 1 mg/L. Prolonged exposure was performed from L1-larvae to young adults. Bars represent means ± SD. **P < 0.01 vs control (if not specially indicated). Figure 2 Effects of MWCNTs exposure on mir-259::GFP expression in nematodes. Arrowheads indicate pharyngeal/intestinal valve in the head and reproductive tract in the mid-region, respectively. Exposure concentration of MWCNTs was 1 mg/L. Prolonged exposure was performed from L1-larvae to young adults. Bars represent means ± SD. **P < 0.01 vs control. Figure 3 Tissue-specific activity of mir-259 in regulating MWCNTs toxicity on lifespan in nematodes. Exposure concentration of MWCNTs was 1 mg/L. Prolonged exposure was performed from L1-larvae to young adults. Bars represent means ± SD. **P < 0.01 vs N2 (if not specially indicated). Figure 4 Effects of rsks-1 mutation on MWCNTs toxicity in nematodes. (a) Effect of mir-259 mutation on expression of rsks-1 gene. Bars represent means ± SD. **P < 0.01 vs N2. (b) Effects of rsks-1 mutation on MWCNTs toxicity in reducing lifespan in nematodes. Bars represent means ± SD. **P < 0.01 vs control (if not specially indicated). (c) Effects of rsks-1 mutation on MWCNTs toxicity in decreasing locomotion behavior in nematodes. Bars represent means ± SD. **P < 0.01 vs control (if not specially indicated). Exposure concentration of MWCNTs was 1 mg/L. Prolonged exposure was performed from L1-larvae to young adults. Figure 5 Genetic interaction between mir-259 and rsks-1 in regulating MWCNTs toxicity in nematodes. (a) Genetic interaction between mir-259 and rsks-1 in regulating MWCNTs toxicity in reducing lifespan in nematodes. (b) Genetic interaction between mir-259 and rsks-1 in regulating MWCNTs toxicity in decreasing locomotion behavior in nematodes. Exposure concentration of MWCNTs was 1 mg/L. Prolonged exposure was performed from L1-larvae to young adults. Bars represent means ± SD. **P < 0.01 vs N2 (if not specially indicated). Figure 6 Tissue-specific activity of rsks-1 in regulating MWCNTs toxicity on lifespan in nematodes. Exposure concentration of MWCNTs was 1 mg/L. Prolonged exposure was performed from L1-larvae to young adults. Bars represent means ± SD. **P < 0.01 vs N2 (if not specially indicated). Figure 7 Genetic interaction between rsks-1 and aak-2 in regulating MWCNTs toxicity in nematodes. (a) Genetic interaction between rsks-1 and aak-2 in regulating MWCNTs toxicity in reducing lifespan in nematodes. (b) Genetic interaction between rsks-1 and aak-2 in regulating MWCNTs toxicity in decreasing locomotion behavior in nematodes. Exposure concentration of MWCNTs was 1 mg/L. Prolonged exposure was performed from L1-larvae to young adults. Bars represent means ± SD. **P < 0.01 vs N2 (if not specially indicated). Figure 8 Genetic interaction between aak-2 and daf-16 in regulating MWCNTs toxicity in nematodes. (a) Genetic interaction between aak-2 and daf-16 in regulating MWCNTs toxicity in reducing lifespan in nematodes. (b) Genetic interaction between aak-2 and daf-16 in regulating MWCNTs toxicity in decreasing locomotion behavior in nematodes. Exposure concentration of MWCNTs was 1 mg/L. Prolonged exposure was performed from L1-larvae to young adults. Bars represent means ± SD. **P < 0.01 vs N2. Figure 9 Distribution and translocation of MWCNTs/Rho B in nematodes. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3235110.1038/srep32351ArticleForced co-expression of IL-21 and IL-7 in whole-cell cancer vaccines promotes antitumor immunity Gu Yang-Zhuo a1*Fan Chuan-Wen 234*Lu Ran 4Shao Bin 1Sang Ya-Xiong 1Huang Qiao-Rong 4Li Xue 4Meng Wen-Tong 4Mo Xian-Ming b4Wei Yu-Quan c11 State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan 610041, PR China2 Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China3 Institute of Digestive Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China4 Laboratory of Stem Cell Biology and Department of Pediatric Surgery, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan 610041, PR Chinaa yangzhuo_gu@163.comb xmingmo@scu.edu.cnc yuquanwei@scu.edu.cn* These authors contributed equally to this work. 30 08 2016 2016 6 3235114 03 2016 08 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Genetic modification of whole-cell cancer vaccines to augment their efficacies has a history of over two and a half decades. Various genes and gene combinations, targeting different aspects of immune responses have been tested in pursuit of potent adjuvant effects. Here we show that co-expression of two cytokine members of the common cytokine receptor γ-chain family, IL-21 and IL-7, in whole-cell cancer vaccines boosts antitumor immunity in a CD4+ and CD8+ T cell-dependent fashion. It also generates effective immune memory. The vaccine-elicited short-term effects positively correlated with enhanced infiltration of CD4+ and CD8+ effector T cells, and the long-term effects positively correlated with enhanced infiltration of effector memory T cells, especially CD8+ effector memory T cells. Preliminary data suggested that the vaccine exhibited good safety profile in murine models. Taken together, the combination of IL-21 and IL-7 possesses potent adjuvant efficacy in whole-cell vaccines. This finding warrants future development of IL-21 and IL-7 co-expressing whole-cell cancer vaccines and their relevant combinatorial regimens. ==== Body Vaccination with irradiated tumor cells that are genetically modified to express genes targeting different aspects of immune responses to promote antitumor immunity has been a focus in the field of tumor immunotherapeutics for decades123. Cancer vaccines are somewhat different from conventional vaccines, they are meant to treat cancer in most cases, rather than to prevent the onset of cancer. Therefore, immediate effectiveness is viewed as a priority. However, memory immunity should never be neglected, since long-term immunosurveillance and effective response to recurrent disease are also key to prolonged survival. Memory is an essential feature of adaptive immunity, and T cells play uniquely important part in adaptive immunity against cancer. Various signals stimulate T cell to boost the potency of adaptive immune responses, a subset of which is conducted by common cytokine receptor γ-chain family cytokines, comprising IL-2, IL-4, IL-7, IL-9, IL-15 and IL-21. Their receptors, sharing a common γ subunit, transduce signals through the Jak-STAT pathway among others, on binding to their respective ligands. Different receptors preferentially activate different subsets of STATs, which bind different cis-acting elements, thus assume diverse functions. The differential expression patterns of these receptors on T cells, as well the balance between different activated STATs, along with other factors, dictate the outcome of T cell responses. IL-21 receptor, expressed on naïve, effector and memory T cells, albeit at varied levels, signals mainly through STAT3, which is a distinctive bias from other members of this receptor family. While IL-7 receptor, expressed on naïve and memory T cells, almost absent on effector T cells though, signals mainly through STAT545. IL-21 is mainly produced by activated CD4+ T cells. By promoting a memory phenotype in activated T cells and suppressing regulatory T cells (Tregs), it exhibits the ability to strengthen T cell response4678910. IL-7 is mainly produced by stromal cells and considered to be present in limiting amounts in vivo11. It has been shown to promote the survival and proliferation of naïve and memory T cells, thereby increasing the specificity repertoire and improving the capability of T cells to react to weak antigens1213141516. Moreover, accumulating data point to a synergizing role of IL-21 with IL-7 in boosting immunity171819. In this study, adjuvant activity of the IL-21 and IL-7 combination was tested in transplanted murine tumor models using lentivirally transduced whole-cell vaccines. Antitumor effects were evaluated in both prophylactic and therapeutic settings. Memory responses were also assayed. We investigated which immune cell compartment(s) played important roles in the antitumor immunity generated by the vaccine, and what changes taking place in the tumor microenvironment contributed to the immunity. In addition, the vaccine formulation were examined for safety concerns in murine models. Results Generation of vaccine cell lines and verification of cytokine production As shown in Fig. 1A, four lentiviral vectors, in which transgenes are driven by CMV immediate early promoters, were constructed. Transgenes included Il-21 (hereafter 21), Il-7 (hereafter 7), Il-21 fusion with Il-7 via a self-cleavable furin-P2A linker (hereafter 21/7)2021, as well as Il-7 signal peptide coding sequence, serving as a control (hereafter Ctrl). Respective lentiviruses were packaged in 293T cells from these vectors, and used to transduce target tumor cell lines. Transduction efficiency were adjusted to <10%, so that the majority of transduced cells harbor only one copy of transgene22. The cells were selected for blasticidin resistance to establish vaccine cell lines. These B16F10 or CT26-derived cell lines were named in abbreviated formats as “16-trangene” or “26-transgene” hereafter. Cytokine production were confirmed by western blot analysis of vaccine cell-conditioned media (Fig. 1B). The functionality of secreted cytokines were validated in murine splenocytes by prominent induction of phosphorylated STAT3 (Tyr705) and phosphorylated STAT5 (Tyr694) (Fig. 1C), characteristic of IL-21 and IL-7 signaling, respectively. Vaccination with IL-21 and IL-7 co-expressing cells protects mice from tumor challenge in a prophylactic B16F10 model To assess the contribution of IL-21 and IL-7 to antitumor immunity as potential vaccine adjuvants, transduced B16F10 melanoma cell lines expressing either of the two cytokines alone or together were put to test in a prophylactic B16F10 model, along with the control cell line. Mice were subcutaneously (s.c.) primed with 106 lethally irradiated vaccine cells or PBS only, boosted one week later, and then challenged contralaterally (c.l.) with 105 viable B16F10 cells. 85% of mice in the 16-21/7 group stayed tumor-free, while only 40% and 20% of mice in the 16–21 group and the 16-7 group were immune to lethal tumor challenge (Fig. 2C–E), which suggested a synergy between IL-21 and IL-7 when co-expressed in whole-cell vaccines. Mice of the Ctrl group and PBS group all developed tumors several days after challenge, showing very limited antitumor efficacy (Fig. 2A,B). Vaccination of 16-21/7 cells significantly improved the survival of mice, compared to other formulations (Fig. 2F). To further determine whether the co-presence of the two cytokines in the vaccine formulation is a necessity for the generation of an optimal immune protection, mice were vaccinated with 16–21 and 16-7 cells together or in temporally and spatially separated fashions (Fig. 2H–J). In all three regimens, mice were given a total of 106 16–21 cells and 106 16-7 cells. Administration of 16–21 and 16-7 cells in mixture outperformed other regimens, yielding more tumor-free mice and improved survival (Fig. 2K). These data demonstrated that whole-cell vaccine co-expressing IL-21 and IL-7 could elicit efficacious antitumor responses in a prophylactic setting. Vaccination with IL-21 and IL-7 co-expressing cells inhibits growth of established tumor in therapeutic models The efficacy of IL-21 and IL-7 co-expressing cells were further verified against established tumors. Mice were first challenged s.c. with 5 × 104 viable B16F10 cells, two doses of 107 irradiated transduced B16F10 cells were c.l. administrated three days later. Treatment with 16-21/7 cells retarded growth of B16F10 tumors (Fig. 3A–C), resulting in significantly smaller tumor burdens on day 19 postchallenge (Fig. 3D), as well as significantly prolonged survival of challenged mice (Fig. 3E). In addition to weakly immunogenic B16F10 melanoma in C57BL/6 mice, the vaccines were also tested in the treatment of moderately immunogenic CT26 colon carcinoma in Balb/c mice23. Mice were first challenged s.c. with 105 viable CT26 cells, two doses of 107 irradiated transduced CT26 cells were c.l. administrated three days later. Treatment with 26-21/7 cells elicited more prominent responses in CT26 model, retarded the growth of CT26 tumors (Fig. 3F–H), and registered complete regression of established tumor in two cases, resulting in significantly smaller tumor burdens on day 19 postchallenge (Fig. 3I), as well as significantly prolonged survival of challenged mice (Fig. 3J). These results suggested that vaccination of tumor cells expressing both IL-21 and IL-7 efficiently inhibited tumor growth in therapeutic models. Antitumor immunity elicited by IL-21 and IL-7 co-expressing tumor cell vaccine relies heavily on CD4+ and CD8+ T cells As T cells and/or NK cells are previously suggested as effectors in antitumor immunity induced by IL-21 vaccine and IL-7 vaccine242526, we next set to unveil which cell compartment(s) support this immune protection conferred by vaccination with IL-21 and IL-7 co-expressing cells. Prophylactic vaccination with IL-21 and IL-7 co-expressing B16F10 cells and tumor challenge were repeated in wild-type, CD4 knockout and CD8 knockout (KO) mice, as described previously in this study. While wild-type mice showed similar (80%) protection effects to previous experiments in this study, antitumor immunity was severely compromised in both CD4 KO and CD8 KO mice, with tumor-free rate dropped sharply to 0% and 10%, respectively (Fig. 4A–F). Tumors in CD4 KO and CD8 KO mice developed faster, thus resulting in worsened survivals (Fig. 4G). NK1.1 antibody (clone PK136), isotype control and PBS were administrated intraperitoneally (i.p.) as previously described27 in mice prophylactically vaccinated with the standard protocol. NK 1.1 depletion was efficient (>94%), as detected by flow cytometry. NK1.1-depleted mice exhibited no significant difference in terms of tumor-free ratio and survival from the mock-depleted counterparts (Fig. 4I–L). These facts suggested that CD4+ and CD8+ effector T cells were important participants in the antitumor immunity triggered by IL-21 and IL-7 co-expressing tumor cell vaccine, while NK cells are dispensable in such a process. Vaccination with IL-21 and IL-7 co-expressing tumor cells increases tumor-infiltrating CD8+ and CD4+ effector T cells as well as effector/regulatory cell ratios As elucidated previously, CD4+ and CD8+ T cells take center stage in bolstering the antitumor immunity elicited by IL-21 and IL-7 co-expressing tumor cell vaccine. In clinical practice, the intratumoral ratio of effector T cells versus regulatory T cells, especially the CD8+/Treg ratio, is a widely accepted prognostic index for many cancer types, including melanoma282930313233. In light of this, we analyzed the composition of tumor-infiltrating T cells from each vaccine group with flow cytometry. Vaccination of IL-21 and IL-7 co-expressing B16F10 cells resulted in marked increased infiltration of both CD8+ and CD4+ effector (CD4+Foxp3−) T cells, especially the former population, compared to vaccination with PBS and 16-Ctrl cells (Fig. 5A,B). Treg (CD4+Foxp3+) infiltration was also increased, but not significantly different from the control groups (Fig. 5C). CD8+/Treg ratios were sharply raised by the IL-21 and IL-7 co-expressing vaccine, CD4+ Teff/Treg ratios were also significantly raised, but to a lesser extent (Fig. 5D,E). Thus, enhanced infiltration of CD8+ and CD4+ effector T cells in tumors and altered balance between effector T cells and regulatory T cells in favor of immunity contributed to the augmented efficacy of IL-21 and IL-7 co-expressing tumor cell vaccine. Vaccination with IL-21 and IL-7 co-expressing cells induces memory antitumor immunity Immune memory, pivotal for prevention of both incipient and recurrent tumors, is a desired feature of vaccine-induced anti-tumor immune responses. We tested whether the vaccination was able to sustain long-lasting responsiveness. Tumor-free mice from 16-21/7 group that survived day 0 challenge with 105 viable B16F10 cells were rechallenged on day 90 with higher dose of 2 × 105 viable B16F10 cells, and no interventions were implemented afterwards. 20% of mice were still completely protected from tumor challenge, and the rest of mice that did develop tumors exhibited retarded tumor progression (Fig. 6A,B) and achieved significantly improved survival (Fig. 6C). We also analyzed the presence of CD8+ (CD8+CD44hi CD62L−) and CD4+ (CD4+FOXP3−CD44hiCD62L−) effector memory T cells (Tem) in tumors transplanted when the primary anti-tumor responses induced by the vaccination waned. Tumors from the 16-21/7 group were significantly more densely infiltrated with CD8+ Tems, compared to tumors from control groups (Fig. 6D). They were also infiltrated by higher densities of CD4+ Tems, but the increase was not statistically significant (Fig. 6E). These data suggested that vaccination with IL-21 and IL-7 co-expressing cells generated immune memory. Infiltrating effector memory T cells were positively correlated with memory immunity against tumor. These facts were in accordance with the forementioned rationale that IL-21 and IL-7 support memory immune responses. Vaccination with IL-21 and IL-7 co-expressing tumor cells is safe in preliminary safety study Mice vaccinated with IL-21 and IL-7 co-expressing tumor cells exhibited no side effects on gross features, such as weight loss, ruffling of fur, behavior, etc., except for vitiligo, probably resulting from T cell reaction to shared antigens of melanoma cells and melanocytes34. About 40% of vaccinated mice gradually developed vitiligo of varied extent, ranging from small patch of depigmentation at challenge site (Fig. 7Aa) to large patches at both secondary vaccination site and challenge site (Fig. 7Ab). All of mice that did develop vitiligo were immune to B16F10 challenge in this study, which is consistent with currently held concept that vitiligo is a sign of good prognosis for melanoma35, thus this side effect of depigmentation should be more than acceptable. Hematoxylin and eosin (H&E) staining of organ sections of vaccinated mice was also performed. No histopathological changes in internal vital organs, including the heart, liver, spleen, lung and kidney, were detected (Fig. 7B). These preliminary data suggested that vaccination with IL-21 and IL-7 co-expressing tumor cells exhibited good safety profile, with negligible, if any, side effect. Discussion In the present study, we have shown that vaccination with tumor cells co-expressing IL-21 and IL-7 elicited potent antitumor responses in both prophylactic and therapeutic tumor models. The vaccine generated immune responses that depended on both CD4+ and CD8+ T cells. Memory antitumor responses elicited by the vaccine were also validated. The vaccine-elicited short-term effects positively correlated with enhanced infiltration of CD4+ and CD8+ effector T cells, and the long-term effects positively correlated with enhanced infiltration of effector memory T cells, especially CD8+ Tems. Last but not the least, preliminary data suggested that the vaccine was safe in murine models. To our knowledge, this is the first report showing that combining IL-21 with IL-7 in cancer vaccines generates enhanced antitumor immunity compared to either cytokine alone. Actually, this cytokine combination has not been described in any previous vaccine formulations. A proportion of mice receiving melanoma vaccine co-expressing IL-21 and IL-7 developed vitiligo over time, which possibly suggested that breaking of topical peripheral tolerance to self-antigens, in this case melanocyte-associated antigens, could be achieved using this new vaccine formulation. This is a phenomenon not seen with the commonly used GM-CSF-expressing vaccine alone36. Breaking the tolerance to self-antigens has always been a hotly pursued goal in cancer immunotherapy37, as cancers of nonviral etiology, covering the majority of all cancers, harbor no potential antigens other than mutated or re-arranged self-antigens, tissue-specific self-antigens and aberrantly expressed self-antigens. The present study might offer a new way to break such tolerance without causing additional problems. The sustenance of adaptive memory against cancer is also a feature worth noting for IL-21 and IL-7 co-expressing cancer vaccines, since immune memory is responsible for long-lasting protection from cancer recurrences38. Previously, Croce et al. stated that the efficacy of IL-21-expressing whole-cell vaccine depends on CD8+ T cells26, while Ma et al. asserted that it is both CD8+ T cell and nature killer cell-dependent24. In addition, Schroten et al. found that the efficacy of IL-7-expressing whole-cell vaccine relies on NK1.1+ cells25. However, our observations indicated that IL-21 and IL-7 co-expressing whole-cell vaccine exerts its antitumor function mainly by CD4+ and CD8+ T cells, and that NK cells are dispensable in such a process. This disagreement with previous study might reflect the advantage of combining IL-21 and IL-7 in driving effective immunity by mobilizing both CD4+ and CD8+ cells. The efficacy of whole-cell vaccines can be further boosted by introducing various cytokines, co-stimulatory molecules, pattern recognition receptor agonists, checkpoint blockers, etc. Blockade of checkpoint, namely, co-inhibitory molecules, such as CTLA-4, PD-1, LAG-3 and TIM-3, have shown great prospect in cancer treatment in both preclinical and clinical researches. By depleting and suppressing the function of regulatory T cells and augmenting the function and proliferation of effector T cells, checkpoint blocking antibodies can rescue the otherwise anergized or exhausted effector T cells, increase the infiltration of effector T cells, raise the Teff/Treg ratio in tumor microenvironment, and ultimately, bring about optimal immune responses against cancer363940414243. As common cytokine receptor γ-chain family cytokines, including IL-21 and IL-7, induce the expression of PD-1 and its ligands44, blockade of PD-1 signaling pathway should be particularly instrumental to further improving the efficacy of IL-21 and IL-7 co-expressing vaccines presented in this study, especially in therapeutic settings. Tumor-reactive T cells, readily activated by the present vaccine formulation, might be susceptible to co-inhibition, thus are overwhelmed by the consummated immunosuppression in the microenvironment of established tumors. Checkpoint blockade should restore the function of these effector T cells, thus render the regression of established tumors more efficient. This notion should be verified in future study. In conclusion, our data demonstrate that forced co-expression of IL-21 and IL-7 in whole-cell cancer vaccines promote antitumor immunity. The vaccine formulation stimulates CD4+ and CD8+ T cell-dependent adaptive responses, and generates immune memory. These facts warrant future development of IL-21 and IL-7 co-expressing whole-cell cancer vaccines and their relevant combinatorial regimens. Materials and Methods Animals and cell lines Female C57BL/6 and Balb/c mice were purchased from Vital River (Beijing, China). CD4 knockout and CD8 knockout mice (C57BL/6 background) were purchased from the Jackson Laboratory (Bar Harbor, ME USA) and bred in our facility. Animal experiments were approved by the Animal Care and Use Committee of Sichuan University, and performed in compliance with the guidelines. Murine melanoma B16F10 cells and colon carcinoma CT26 cells were maintained in RPMI 1640 medium. 293T cells were maintained in DMEM medium. Both culture media were supplemented with fetal bovine serum (10%). Plasmid construction Coding sequences of murine Il-21 and Il-7 genes were amplified from C57BL/6 spleen cDNA. The two fragments were either directly cloned into a lentiviral vector, pLVX-IRES-Bsd, which was derived from pLVX-IRES-ZsGreen1 (Clontech, Mountain View, CA USA) by replacing ZsGreen1 coding sequence with that of the blasticidin resistance gene, or first joined by coding sequences of a furin cleavage site and a P2A peptide, and then cloned into the same vector. IL-7 signal peptide coding sequence was cloned as forementioned to create the control vector. Lentiviral packaging and vaccine cell line establishment 293T cells were co-transfected with psPAX2, pMD2.G, and respective lentiviral vectors. To achieve single-copy integration of provirus in the majority of cell population, virus-containing supernatants of 293T cells were filtered through 0.45 μm filters and diluted to ensure that transduction efficiencies were <10%. The transduced cells were placed under the selection of 10 μg/mL blasticidin for 2 weeks to obtain respective vaccine cell lines. Western blotting For verification of cytokine secretion, vaccine cell-conditioned media were collected and filtered through 0.45 μm filters. For validation of cytokine activity, mouse splenocytes incubated for 90 min with conditioned media were collected. Proteins from collected samples were resolved by SDS-PAGE, and transferred to PVDF membranes. The membranes were blocked and incubated with primary antibodies against IL-21, IL-7 (PeproTech, Rocky Hill, NJ USA), phospho-STAT3 (Tyr705), phospho-STAT5 (Tyr694) (Cell Signaling Technology, Danvers, MA USA) and GAPDH (Sigma-Aldrich, St. Louis, MO USA), then incubated with HRP-conjugated secondary antibodies. The blotted proteins were visualized by chemiluminescence detection. Animal experiments Vaccine cells were collected, washed with PBS and lethally irradiated (100 Gy) to make whole-cell vaccines. In the prophylactic setting, C57BL/6, CD4 KO, or CD8 KO mice were vaccinated s.c. with 106 irradiated B16F10 vaccine cells twice at a one week interval, and then challenged c.l. with 105 viable B16F10 cells one week after the last vaccination. For NK cell depletion, the mice were vaccinated and challenged as forementioned, and administrated i.p. with doses of NK1.1 antibody, isotype controls (Bio X Cell, West Lebanon, NH USA) or PBS as previously described27. Tumor-free mice were rechallenged 90 days after the initial B16F10 challenge with 2 × 105 viable B16F10 cells to assay for memory responses. In the therapeutic setting, mice were challenged s.c. with viable tumor cells, 5 × 104 B16F10 cells for C57BL/6 strain, and 105 CT26 cells for Balb/c strain, respectively. Three days later, mice were treated with two doses of 107 irradiated vaccine cells c.l. and left without further intervention. Tumors were measured in two perpendicular dimensions for length (L) and width (W), and their volumes (V) were calculated with the following formula, V = 0.5 × L × W2. Tumor-bearing mice were sacrificed when either of the following criteria was met: 1) Tumor volumes exceeded 800 mm3 and 1600 mm3 for prophylaxis and therapeutics, respectively. 2) Tumors ulcerated or mice became moribund. To obtain tumors for TIL analysis, mice were challenged with 3 × 106 viable tumor cells one week after the last vaccination, or with 4 × 105 viable tumor cells six weeks after the last vaccination. TIL analysis Tumor tissues were digested with Liberase TM and Dnase I (Roche, Basel, Switzerland) and filtered through 40 μm cell strainers. Cells were initially incubated with CD16/32 antibody to block Fcγ receptors, then stained with 1) the combination of APC-Cy7-conjugated CD45 antibody (BD Biosciences, Franklin Lakes, NJ USA), FITC-conjugated CD4 antibody and APC-conjugated CD8a antibody (BioLegend, San Diego, CA USA), or 2) the combination of FITC-conjugated CD44 antibody, PE-Cy7-conjugated CD62L antibody and APC-conjugated CD4 or CD8a antibody (BioLegend). For Treg discrimination, cells were further fixed and permeabilized (eBioscience, San Diego, CA USA) according to manufacturer’s instructions, stained with PE-conjugated anti-FOXP3 antibody (eBiosciences), and analyzed with FACSAria cytometer (BD Biosciences). Histopathological study Hematoxylin and eosin-stained paraffin sections of heart, liver, spleen, lung and kidney tissues from vaccinated mice were scrutinized for possible histopathological changes. Statistical analysis Data were analyzed with GraphPad Prism 6. Statistical significances were determined by the log-rank test and one-way ANOVA with Tukey post hoc tests. Comparisons with P < 0.05 were deemed as statistically significant. Additional Information How to cite this article: Gu, Y.-Z. et al. Forced co-expression of IL-21 and IL-7 in whole-cell cancer vaccines promotes antitumor immunity. Sci. Rep. 6, 32351; doi: 10.1038/srep32351 (2016). Supplementary Material Supplementary Information This work was supported by the National Basic Research Program of China (No. 2010CB529900). Author Contributions Y.-Q.W. conceived and coordinated the study. X.-M.M. supervised the study. Y.-Z.G. designed and performed experiments, analyzed data, and wrote the paper. C.-W.F. performed experiments and analyzed data. R.L., B.S. and Y.-X.S. performed animal experiments. Q.-R.H. and X.L. and performed flow cytometry analysis. W.-T.M. provided critical technical support. All authors reviewed the manuscript. Figure 1 Establishment of vaccine cell lines by lentiviral transduction. (A) Lentiviral constructs used in this study. LTR, long terminal repeat. Ψ, packaging signal. RRE, Rev response element. cPPT, central polypurine tract. CMVp, CMV promoter. IRES, internal ribosome entry site. Bsd, blasticidin resistance gene. WPRE, woodchuck hepatitis virus posttranscriptional regulatory element. Sp, Signal peptide of IL-7. FA, furin cleavage site and P2A peptide. (B) Western blot analysis of secreted IL-21 and IL-7 in vaccine cell-conditioned media. Note that the two bands of IL-21 in the 21/7 CM lane represented two possible cleavage products: cleavage at furin site resulted in IL-21 + 4AA, while cleavage at P2A site resulted in IL-21 + 25AA. CM, conditioned medium. AA, amino acids. (C) Western blot analysis of STAT proteins activated in response to secreted IL-21 and IL-7. SC, splenocytes. MC, medium control. Full-length blots are presented in Supplementary Figure S1. Figure 2 Vaccination with IL-21 and IL-7 co-expressing B16F10 cells prevented tumorigenesis of B16F10 melanoma in prophylactic setting. (A–E) Individual tumor growth curves of B16F10 tumors. Mice were vaccinated s.c. on day −14 and day −7 with 106 irradiated tumor cells, then challenged c.l. on day 0 with 105 viable B16F10 cells. Fractions in the parentheses indicate the proportion of tumor-free mice in totals. Data were pooled from two independent repeats. (F) Cumulative survival curves of two independent repeats. **P < 0.01. ****P < 0.0001. (G–J) Individual tumor growth curves of B16F10 tumors. Mice were vaccinated s.c. on day −14 and day −7 with PBS or 106 irradiated tumor cells following one of the following regimens. 1) prime with 16–21 cells, boost with 16-7 cells in (H). 2) prime with 16-7 cells, boost with 16–21 cells in (I). 3) prime and boost with a mixture of 5 × 105 16–21 and 5 × 105 16-7 cells in (J). mice were then challenged c.l. on day 0 with 105 viable B16F10 cells. Fractions in the parentheses indicate the proportion of tumor-free mice in totals. Data were pooled from two independent repeats. (K) Cumulative survival curves of two independent repeats. Figure 3 Vaccination with IL-21 and IL-7 co-expressing cells inhibited tumor progression in two therapeutic models. (A–C) Individual tumor growth curves of B16F10 tumors. Mice were challenged s.c. on day 0 with 5 × 104 viable B16F10 cells, then vaccinated c.l. on day 3 with two doses of 107 irradiated tumor cells. Data were pooled from two independent repeats. (D) Cumulative tumor volumes on day 19 of two independent repeats. Horizontal bars represent means. (E) Cumulative survival curves of two independent repeats. (F–H) Individual tumor growth curves of CT26 tumors. Mice were challenged s.c. on day 0 with 105 viable CT26 cells, then vaccinated c.l. on day 3 with two doses of 107 irradiated tumor cells. Fractions in the parentheses indicate the proportion of cured mice in totals. Data were pooled from two independent repeats. (I) Cumulative tumor volumes on day 19 of two independent repeats. Horizontal bars represent means. (J) Cumulative survival curves of two independent repeats. ***P < 0.001. ****P < 0.0001. Figure 4 Antitumor efficacies of IL-21 and IL-7 co-expressing tumor cell vaccine depended highly on CD4+ and CD8+ T cells, rather than NK cells. (A–F) Individual tumor growth curves of B16F10 tumors. Wild-type, as well as CD4 KO and CD8 KO mice were vaccinated s.c. on day −14 and day −7 with 106 irradiated tumor cells, then challenged c.l. on day 0 with 105 viable B16F10 cells. Fractions in the parentheses indicate the proportion of tumor-free mice in totals. Data were pooled from two independent repeats. (G) Cumulative survival curves of two independent repeats. ***P < 0.001. ****P < 0.0001. (H–K) Individual tumor growth curves of B16F10 tumors. Mice were vaccinated s.c. on day −14 and day −7 with 106 irradiated tumor cells, then challenged c.l. on day 0 with 105 viable B16F10 cells. PBS, isotype control, or NK1.1 antibody were administrated i.p. following the protocol described in Methods. Fractions in the parentheses indicate the proportion of tumor-free mice in totals. Data were pooled from two independent repeats. (L) Cumulative survival curves of two independent repeats. Figure 5 Vaccination with IL-21 and IL-7 co-expressing tumor cells enhanced CD8+ and CD4+ effector T cell infiltration in tumors and raised infiltrating effector/regulatory cell ratios. (A–C) Frequencies of CD8+, CD4+ effector and regulatory cells in total cells of B16F10 tumors generated by challenge s.c. with 3 × 106 viable cells at day 0. Data were pooled from two independent repeats. (D,E) CD8+/Treg and CD4+ Teff/Treg ratios in B16F10 tumors. Data were pooled from two independent repeats. Horizontal bars represent means. *P < 0.05. **P < 0.01. Figure 6 Vaccination with IL-21 and IL-7 co-expressing B16F10 cells elicited memory responses. (A,B) Individual tumor growth curves of B16F10 tumors. Mice remaining tumor-free were rechallenged with 2 × 105 viable B16F10 cells on day 90. Fractions in the parentheses indicate the proportion of tumor-free mice in totals. Data were pooled from two independent repeats. (C) Cumulative survival curves of two independent repeats. ****P < 0.0001. (D,E) Frequencies of CD8+, CD4+ effector memory T cells in total cells of B16F10 tumors generated by challenge with 4 × 105 viable cells at day 35. Data were pooled from two independent repeats. Horizontal bars represent means. *P < 0.05. **P < 0.01. Figure 7 Vaccination with IL-21 and IL-7 co-expressing tumor cells exhibited good safety profile with trivial side effect. (A) Vaccination with IL-21 and IL-7 co-expressing tumor cells induced depigmentation. Upper arrows in (a) and (b) indicate vitiligo at challenge sites. Lower arrow in (b) indicates vitiligo at boost site. (B) H&E staining of vital organs of vaccinated mice. Scale bar, 100 μm. ==== Refs Tepper R. I. , Pattengale P. K. & Leder P. Murine interleukin-4 displays potent anti-tumor activity in vivo . Cell 57 , 503 –512 (1989 ).2785856 Watanabe Y. . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3234310.1038/srep32343ArticleDynamic transition of neuronal firing induced by abnormal astrocytic glutamate oscillation Li Jiajia 1Tang Jun 2Ma Jun 3Du Mengmeng 1Wang Rong 1Wu Ying ab11 State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi’an Jiaotong University, Xi’an 710049, China2 College of Science, China University of Mining and Technology, Xuzhou 221116, China3 Department of Physics, Lanzhou University of Technology, Lanzhou 730050, Chinaa wying36@163.comb wuyinggroup@gmail.com30 08 2016 2016 6 3234328 06 2016 05 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The gliotransmitter glutamate released from astrocytes can modulate neuronal firing by activating neuronal N-methyl-D-aspartic acid (NMDA) receptors. This enables astrocytic glutamate(AG) to be involved in neuronal physiological and pathological functions. Based on empirical results and classical neuron-glial “tripartite synapse” model, we propose a practical model to describe extracellular AG oscillation, in which the fluctuation of AG depends on the threshold of calcium concentration, and the effect of AG degradation is considered as well. We predict the seizure-like discharges under the dysfunction of AG degradation duration. Consistent with our prediction, the suppression of AG uptake by astrocytic transporters, which operates by modulating the AG degradation process, can account for the emergence of epilepsy. ==== Body The neuronal system is composed of a large number of neurons and astrocytes, and it is confirmed that astrocytes can play important role in regulating the electric modes of activities1234. Most of the neuronal models mainly emphasize the dynamical properties of electric activities, and often bifurcation parameters are carefully adjusted to trigger possible mode transition in electrical activities. These models are helpful to understand the synchronization problems of neurons. Gu et al. proposed a neuronal model to detect the possible dynamical behavior of a sciatic nerve chronic constriction injury model5. Multiple modes can be observed in neuronal activities, Gu et al. investigated the dependence of model selection on bifurcation parameter and initials selection6. Furthermore, Ma et al. proposed an improved model to describe the emergence and transition of multiple modes in electric activities by introducing magnetic flux in the original Hindmarsh-Rose neuron according to electromagnetic induction effect78. Some intermediate neurons are connected with autapse, a specific autapse connected to the body of neuron, which counts the emergence of intrinsic time delay in neuron9. The previous works confirmed that autapse connection plays important biological function by regulating the electric activities of isolate neuron and collective behaviors of neuronal network as pacemakers1011121314151617. Particularly, coupling between neurons and astrocytes could be more reliable to understand the complex behavior of neuronal systems. Over the past decades, our understanding of astrocytes has fundamentally changed: they were first considered as passive cells before being subsequently recognized as biologically excitable cells12. One form of excitability is a change in intracellular Ca2+ concentration, which occurs both spontaneously and in response to the neuronal activity34. Consequently, an elevation of Ca2+ concentration can induce a release of gliotransmitters from astrocytes in a Ca2+ -dependent manner1819. Here, astrocytic glutamate (AG) is one of the major gliotransmitters and exerts its signal transducing effect on neurons via N-methyl-D-aspartic acid (NMDA) receptors2021. Finally, astrocytes can “listen” and respond to neurons in a “tripartite synapse” loop (i.e., an astrocyte-neuron feedback loop)2223. Recent studies showed that the normal function of astrocytes is to support some physiological functions, such as neuronal synaptic information processing24252627 or synaptic plasticity28. In an experimental study by Tian et al. in 200529, the authors suggested that astrocytes may contribute to the neuronal depolarization underlying epilepsy. Also, Fellin et al. challenged the traditional concept that synchronous neuronal activity during seizures arises from an entirely neuronal origin, since they found that astrocytes can also induce synchronous neuronal activity3031. Therefore, some scientists have proposed that astrocytes are likely to be potential targets for anti-epileptic therapeutic strategies32. Although astrocytes have been reported to play a potential role in epileptic seizure, the underlying causes are diverse and not completely understood3334. Computational modeling has been widely used for understanding the dynamics of neurons and neuronal networks353637, and those dynamic characteristics of neurons predicted by modeling analysis were also proved in experimental results3839, which verifies the significance of modeling analysis of neurons. These computational methods are also used to identify the impaired neurons underlying epilepsy404142, and in recent years some models have been developed to study the astrocyte-induced epilepsy4344454647. In the study of Nardkarni et al., a two-compartment neuron-astrocyte model was established to account for epilepsy in these experiments, when the astrocytic neurotransmitter receptors were over-expressed4344. Some other neuron-astrocyte models have been developed to investigate the synchrony network epilepsy which is induced by an AG release45. However, few studies have paid attention to the relation between the different dynamic phases of the AG and epilepsy. Recent experiments have shown that a large amount of glutamate transporters are located in the astrocyte to uptake the AG4849, and that a low-efficiency hydrolysis may trigger an epileptic seizure50. However, to the best of our knowledge, this effect has not been considered in previous modeling studies. Thus we investigated how the uptake-related AG decay process can affect the seizure dynamics. In this paper, we incorporated the dynamics model of AG, which could well describe the decay process of AG, into a classical astrocyte-neuron feedback loop model44 in order to investigate how a low-efficiency AG decay affects the generation of seizure-like discharge. With this model, we explored how an increase of AG equilibrium concentration and decay period changes the regular neuronal spiking into a seizure-like discharge. In addition, we also analyzed different phases of seizure-like discharge and the corresponding AG concentration states. Finally, we also adopted the energy cost theory of Hodgkin-Huxley model51 to distinguish seizure-like discharge from normal spiking. Model and Method The reduced “tripartite synapse” is a three-compartment model of a somatic neuron, a dendrite and the neighboring astrocyte developed by Nardkarni and Jung44. In this model, a somatic neuron transfers its firing to the dendrite through electrical coupling. Subsequently, the action potential generated at the activated dendrite elicits the release of neurotransmitters that bind to the astrocyte receptors; as a consequence, the level of IP3 (inositol 1, 4, 5-triphosphate) in the astrocyte increases, which excites the Ca2+ oscillation in the astrocyte. Finally, the Ca2+ oscillation accelerates the glutamate increase in the extracellular space, which in turn depolarizes the somatic firing. In this paper, we focused on the dynamic model of astrocytic glutamate, which is defined in Eq. (9). To model of the pyramidal cell and the dendrite, the well-known Pinsky-Rinzel (PR) model52 has been used in the classical “tripartite synapse” model. This model can well describe the main features of Na+ and K+ ion conductance of the soma and the calcium dependence of the dendrite. The action potentials of the soma (Vs) and the dendrite (Vd) are described by the following set of equations: where Cm = 3.0 μFcm−2 represents the membrane capacitance of the soma and the dendrite. VNa = 115.0 mV, VK = −15.0 mV, VCa = 140.0 mV, VL = 0.0 mV respectively denote the Nernst potentials of the sodium, potassium, calcium and the leakage channels. The maximal conductance of the sodium channel, the three types of potassium channels, calcium channel and the leakage channel are given as follows: gNa = 30.0 mS cm−2, gK-DR = 15.0 mS cm−2, gK-AHP = 0.8 mS cm−2, gK-C = 15.0 mS cm−2, gCa neuron = 10.0 mS cm−2 and gL = 0.1 mS cm−2. gc = 2.1 mS cm−2 represents the coupling intensity between the soma and the dentdrite, and the parameter p = 0.5 denotes the fraction of the cell volume taken up by the soma. For the PR model, the rest-to-spiking rheobase current for the soma and the dendrite are −0.3 μA cm−2 and −0.25 μA cm−2, Is = 0 μA cm−2 representing the external stimulating current on the pyramidal soma, and Id = 0 μA cm−2 representing the external stimulating current for the dendrite. The slow inward current Iastro that is induced by the astrocytic glutamate shows to be proportional to the concentration of astrocytic glutamate5354, and therefore Iastro gives the form: where [AGlu]o denotes the extracellular AG concentration, and λ = 2.11 μA cm−2 μM−1 represents the expression level of the NMDA receptors in the soma. The kinetic equations for the gating variables h, n, s, c, w give the form: where [Caneuron] denotes the dimensionless free calcium concentration in the dendrite44 When the dendrite fires, the neurotransmitters released from the dendrite can trigger the production of IP3 in the neighboring astrocyte, which is modeled by Nardkarni and Jung4344 as where [IP3]* denotes the equilibrium concentration of IP3, which is a secondary messenger molecule used in astrocytes to bind receptors in the endoplasmic reticulum (ER) membrane and elicit a Ca2+ efflux from ER. Predetermined values of [IP3]* = 160.0 μM and τip3 = 7 s were used according to previous experiments55. Subsequently, the elevation of the IP3 concentration induces an increase in intracellular Ca2+ in the astrocyte. The Li-Rinzel model has been used to describe the calcium exchange in the astrocyte434456, which contains three fluxes across the ER membrane: an IP3-dependent calcium ion channel, a pump channel, and a leaky channel. They are described as follows: where The parameters of the classical Li-Rinzel model are c1 = 0.185, v1 = 6 s−1, v2 = 0.11 s−1, v3 = 0.9 μM.s, a2 = 0.2 μM.s−1, d1 = 0.13 μM, d2 = 1.049 μM, d3 = 0.9434 μM, d5 = 0.08234 μM. The conservation of calcium in astrocyte implies the constraint [Ca2+]ER = (c0-[Ca2+])/c1 with c0 = 2.0 μM. The parameter q denotes the gating variable of calcium channel in the ER membrane of the astrocyte. The experimental evolution of AG shares similarities with astrocytic IP3: 1) a transient increase by the pulse of the astrocytic Ca2+ signal (for IP3, this corresponds to the voltage signal); the decaying process by the uptake of astrocytic transporters (for IP3, this corresponds to the IP3 enzyme in the astrocyte). Regarding the dynamics aspects, we proximately use the framework of the IP3 model to describe the AG dynamics. Therefore, the characteristics of the AG dynamics ([AGlu]o) can be described as follows: where the first term describes the degradation of AG with a degradation rate of 1/τaglu and an equilibrium concentration of [AGlu]*. When considering a normal uptake function of the astrocytic transporters, [AGlu]* is assumed to be approximately 0. However, when the AG uptake is suppressed, [AGlu]* would increase. In fact, experimental results showed that astrocytes could contribute to the neuronal depolarization underlying epilepsy through an accumulation of extracellular AG293031. Also, an abnormal AG uptake due to dysfunctional astrocytic transporters could accelerate the AG accumulation50. In Eq. (9), both high AG equilibrium concentration ([AGlu]*) or long degradation time constant (τaglu) could be typical characteristics of an abnormal AG uptake state. The second term in Eq. (9) is activated when astrocytic Ca2+ concentration is larger than a threshold of 0.2 μM5354 via the step function. The parameter raglu = 1.0 μM s−1 represents the quantized production of extracellular AG as [Ca2+] remains over 0.2 μM. Numerical Results and Discussion Figure 1 shows neuronal discharges with AG equilibrium concentration ([AGlu]*) at 0.0 μM (a), 0.1 μM (b), 0.3 μM (c), 0.5 μM (d) and 0.7 μM (e). As shown in Fig. 1(a–c), the neuronal discharge shows regular spiking when the equilibrium concentration stays lower than 0.5 μM. However, with higher level of equilibrium concentrations, such as 0.5 μM and 0.7 μM, a seizure-like discharges are present in the soma, as it can be observed in Fig. 1(d,e) respectively. Both the “depolarization block” (DB) discharge and the “refractory status epilepticus”(RSE)-like discharge are present in the time series of neuronal discharge. The DB discharge, observed in Fig. 1(d), shows a short period of hyper-resting state, and has been observed in the time series of epileptic seizure575859. Besides, the RSE-like discharge shown in Fig. 1(f) is an enlarged version of that shown in the red box in Fig. 1(d). It can be seen in Fig. 1(g) that this discharge period shows long-period and high-rate mixed-mode oscillations (MMO). The high-rate feature can be determined from the comparison between Fig. 1(f) and Fig. 1(g). It can be seen that the neuronal firing frequency in Fig. 1(g) is much higher than the neuronal firing frequency observed in Fig. 1(f). In fact, Tian et al. in experiments have reported that the accumulation of AG has been a major source of neuronal epilepsy293031, AG uptake by astrocytic transporters in some experimental results was shown to be an efficient pathway to protect neurons from epilepsies3334. Furthermore, Hubbard et al.50 even reported various epilepsies that were induced by abnormal AG clearance process. In the present study, an elevated [AGlu]* corresponds to an abnormal AG clearance process, which could also predict the epileptic phenomena. In order to describe the hyper-high firing rate characteristics of seizure-like discharges that differ from regular discharges, we introduced the notion of an average energy cost <H>5160: where we consider the average energy cost <H> in the time scale with T = 100000 ms. The first three terms in Eq. (11) represent the energy cost of three ion channels, the last term denoting the energy supply from the total external current, which arises from the coupling current between the soma and the dendrite. The constant stimulating current in the soma and astrocytic current is due to AG. Figure 2 shows the average energy cost versus the AG equilibrium concentration, It can be observed that when [AGlu]* < 0.5 μM, the average energy cost stays about 200–400 nJ/(cm2*ms). When [AGlu]* increases above 0.5 μM, the average energy cost shows an abrupt elevation of <H>, until the neuron start to generate seizure-like discharge. This suggests that the emergence of seizure-like discharges is accompanied by an “energy explosion”. In fact, the transition of brain electric activities corresponds to changes in multiple forms, such as characteristics of the neuronal network random matrix61 and presentations of the neuronal network spatiotemporal patterns62. In this paper, we used statistical measurement energy consumption <H> and successfully described a special transition of brain electric activities, i.e., the generation process of an epileptic seizure. In fact, experimental results have also shown that a brain seizure corresponds to a high-level energy expenditure6364. Figure 3 shows AG oscillations and the corresponding neuronal discharges during the same time period with an equilibrium concentration of [AGlu]* = 0.5 μM. It can be seen that when the AG concentration stays at a low level, the corresponding neuronal discharges show regular spiking, However, when AG oscillations reach higher levels, the neuron starts to fire with seizure-like discharges. An interesting point is that the DB discharge is present when AG oscillations peak. Because AG offers excitable stimulus on neurons, hyper-high concentration of AG can therefore induce a neuronal electric shock. On the other hand, as AG concentration decreases from the peak, the neuronal discharge resembles RSE-like discharge. The astrocyte, as a source of AG, can be activated by the increase of [IP3] concentration. Figure 4 shows the bifurcation diagram of astrocytic caclium oscillation of the Li-Rinzel model56. It can be seen that a periodical repetitive calcium oscillation coexists with a steady-state limit cycle for 0.345 μM < [IP3] < 0.664 μM. For [IP3] > 0.664 μM or [IP3] < 0.345 μM, the repetitive calcium oscillation is transformed into resting state. In Fig. 5, we show the time course of [IP3] and the corresponding calcium oscillation for [AGlu]* = 0.0 μM and 0.5 μM respectively. When [AGlu]* = 0 μM in Fig. 5(a), the [IP3] keeps lower than 0.345 μM along the entire period of time. Therefore, [Ca2+] stays in a resting state with small amplitude oscillation. However, when [AGlu]* = 0.5 μM in Fig. 5(b), [IP3] builds up over the threshold line and calcium oscillations are induced. As a consequence, the high-AG-modulated seizure-like discharge is induced, as shown in Fig. 3. This suggests that the excitable calcium oscillation is a fundamental element for the induction of an epileptic seizure, which has already been proved by experimental results65666768. Figure 6 shows the neuronal discharges for τaglu = 2 s, τaglu = 4 s, τaglu = 6 s and τaglu = 8 s when [AGlu]* = 1.0 μM. We can observe that the regular spiking is transformed into seizure-like discharge when the time constant increases from 2.0 s to 8.0 s, as seen in (d). Besides, Fig. 6(c) shows a “transition state” discharges: the neuronal discharge is a mixture of high-amplitude and low-amplitude phases. The “transition state” discharge has been the prelude of the seizure-like discharges. From the enlargement presented figure in Fig. 6(e), we can see that the low-amplitude phase observed in the “transition state” discharge shows a much higher firing frequency than that of the high-amplitude phase. By comparing the “transition state” discharge with the seizure-like discharges in (d), we concluded that the low-amplitude phase in the “transition state” discharge may directly evolve into the DB state when τaglu increases. In fact, a long time constant of AG clearance process represents another abnormal state of the AG clearance process. Therefore, a prolonged τaglu could also predict the epileptic phenomena, which is shown in the results presented above. In fact, the discharge pattern of soma alternates between seizure-like discharges, transition state activity and regular firing. Figure 7 shows the discharge-pattern distribution of soma in the 2- parameter space, [AGlu]* and τaglu. We can see that the seizure-like discharges are present when [AGlu]* or τaglu is high. But if [AGlu]* ≤ 0.5 μM (or τaglu ≤ 5.5 s), increasing the other parameter (τaglu or [AGlu]*) fails to induce the seizure-like discharges. Indeed, the neuronal system often shows some robustness to disordered states (e.g., epilepsy), through mechanisms such as autapse1011121314151617. Therefore, the epileptic generation thresholds in vivo may be higher than the thresholds predicted in our results. Conclusions Prior experimental studies have documented the significant role of astrocytes and their releasing gliotransmitter in epileptic seizure of neurons. In this study, we introduced a model describing the dynamic changes of astrocytic glutamate and we mainly discussed abnormal degradation of extracellular astrocytic glutamate dynamics and its underlying seizure-like discharges in soma. We found that when the equilibrium concentration of the astrocytic glutamate is elevated or when the degradation time constant is lengthened, a seizure-like discharge pattern can be observed in soma action potentials. Besides, the transition from a seizure-like discharge pattern to a regular discharge pattern cannot be induced if one of these two parameters is small enough, as shown in this two-parameter space for the firing-state distribution (Fig. 7). In addition, by comparing the astrocytic glutamate with the corresponding action potential of soma during the same time window, we found that when the equilibrium concentration is high, the astrocytic glutamate shows an oscillation with a high-level concentration. The peak of astrocytic glutamate concurs with a short period of hyper-resting discharge of the neuron, i.e., a “depolarization block”. Moreover, a lower astrocytic glutamate concentration phase contributes to the high-rate mixed-mode oscillation discharges, i.e., a “refractory status epilepticus” (RSE)-like discharge. Moreover, by analyzing the energy cost of somatic firing, we found that the somatic firing pattern transition from regular discharges to seizure-like discharges coexists with an “energy explosion”, that is, the seizure-like discharges consume much more energy than regular discharges. Our modeling work predicts the seizure-like discharge pattern when the astrocytic glutamate degradation process is abnormal. This suggests a pathway for epilepsy when the actual activity of astrocytic transporters is suppressed. Finally, our results provide a better understanding of the role of astrocytes in the induction of epileptic seizure, which could also offer valuable references for experimental and clinical antiepileptic process. However, due to the lack of experimental data describing the oscillation of astrocytic glutamate concentration, we only developed a linear model describing the dynamics of astrocytic glutamate concentration. Given the complex evolution process of astrocytic glutamate concentration, the non-linearity and/or stochastic processes should also be taken into account in future studies. Additional Information How to cite this article: Li, J. et al. Dynamic transition of neuronal firing induced by abnormal astrocytic glutamate oscillation. Sci. Rep. 6, 32343; doi: 10.1038/srep32343 (2016). This work is supported by the National Natural Science Foundation of China (Grant No. 11472202, No.11272242). Author Contributions J.L. and Y.W. conceived the idea and supervised the project; J.L., J.T., J.M., M.D., R.W. and Y.W. conducted the simulation experiment(s). All authors assisted in writing the manuscript. Figure 1 Epileptic discharge induced by the increase of [AGlu]* with τaglu = 10 s. The AG equilibrium concentration [AGlu]* is (a) 0.0 μM; (b) 0.1 μM; (c) 0.3 μM; (d) 0.5 μM; (e) 0.7 μM. Additionally, (f,g) show the neuronal discharge between 60000 ms and 70000 ms, zoomed from panels (c,d) respectively. Figure 2 The average energy cost <H> versus the equilibrium concentration [AGlu]*. The micro-figures of neuronal discharges correspond to the cases when [AGlu]* = 0.1 μM and 0.5 μM. Figure 3 The gliotransmitter AG regulates the epileptic seizure with τaglu = 10 s. (a) AG time concentration when [AGlu]* = 0.5 μM; (b) the neuronal discharge when [AGlu]* = 0.5 μM. Figure 4 Bifurcation diagram of astrocytic [Ca2+] versus the parameter [IP3]. Figure 5 Phase variables of astrocyte system ([IP3], [Ca2+]) responses to the increase of [AGlu]* with τaglu = 10 s. (a) [AGlu]* = 0.0 μM; (b) [AGlu]* = 0.5 μM. Figure 6 Epileptic discharges induced by increase of time constant τaglu with [AGlu]* = 1.0 μM. Neuronal discharges from top to the bottom with time constant (a) τaglu = 2.0 s; (b) τaglu = 4.0 s; (c) τaglu = 6.0 s; (d) τaglu = 8.0 s respectively; (e) the partial neuronal discharge zoomed from red square in (c). Figure 7 The discharge- state- distribution of the soma in the parameter space of τaglu and [AGlu]*. The black part denotes the regular discharge, the grey part represents the transition state, and the blue part denotes the seizure-like discharge. ==== Refs Charles A. C. , Merrill J. E. , Dirksen E. R. & Sanderson M. J. Intercellular signaling in glial cells: calcium waves and oscillations in response to mechanical stimulation and glutamate . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3234610.1038/srep32346ArticlePhysiological basis for low-temperature survival and storage of quiescent larvae of the fruit fly Drosophila melanogaster Koštál Vladimír a1Korbelová Jaroslava 1Štětina Tomáš 12Poupardin Rodolphe 13Colinet Hervé 4Zahradníčková Helena 1Opekarová Iva 1Moos Martin 1Šimek Petr 11 Institute of Entomology, Biology Centre CAS, Branišovská 31, 37005 České Budějovice, Czech Republic2 Faculty of Science, University of South Bohemia, Branišovská 31, 37005 České Budějovice, Czech Republic3 Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria4 Université de Rennes 1, UMR CNRS 6553 ECOBIO, 263 Avenue du Général-Leclerc, 35042 Rennes, Francea kostal@entu.cas.cz30 08 2016 2016 6 3234604 07 2016 05 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The cryopreservation techniques proposed for embryos of the fruit fly Drosophila melanogaster are not yet ready for practical use. Alternative methods for long-term storage of D. melanogaster strains, although urgently needed, do not exist. Herein, we describe a narrow interval of low temperatures under which the larvae of D. melanogaster can be stored in quiescence for up to two months. The development of larvae was arrested at the pre-wandering stage under fluctuating thermal regime (FTR), which simultaneously resulted in diminishing the accumulation of indirect chill injuries. Our physiological, metabolomic, and transcriptomic analyses revealed that compared to larvae stored at constant low temperatures, the larvae stored under FTR conditions were able to decrease the rates of depletion of energy substrates, exploited brief warm episodes of FTR for homeostatic control of metabolite levels, and more efficiently exerted protection against oxidative damage. ==== Body The potential to store insects for a long term at low temperatures would procure considerable benefits. Long-term storage could supplement, or even replace, tedious and expensive continuous rearing practices currently used in mass rearing facilities that produce insects for pest management purposes, or in large Drosophila centres that preserve valuable genetic lines and mutant strains. Two basic strategies for low-temperature insect storage are known: (i) cryopreservation of embryos at cryogenic temperatures, most often in liquid nitrogen at −196 °C1, and (ii) long-term storage at temperatures below the threshold for development, which is typically applicable for insects in diapause2. The methods for long-term storage of fruit flies (Drosophila melanogaster) although urgently desired, currently produce unsatisfactory results. Despite the growing list of successfully cryopreserved insect embryos in liquid nitrogen1, the attempts to cryopreserve embryos of D. melanogaster have been only partially successful in the past34. The theoretical possibility of cryogenic technique use for the conservation of complex tissues or whole organisms appeared mostly unsuccessful or very problematic in practice56. We previously described a protocol for cryopreservation of larvae of another drosophilid fly, Chymomyza costata7. Thereafter, in an attempt to adapt this protocol for D. melanogaster, we could ensure survival of fruit fly larvae after conversion of the freezable fraction of body water into ice (freeze tolerance), yet such larvae had no capacity to survive in liquid nitrogen8. Here, we extend our previous effort, and analyse whether the larval stage possess some capacity for long term storage at moderately low temperatures. A strategy of long-term storage at temperatures slightly below the threshold for development, exploiting the natural features of insect diapause, presents itself as a useful alternative to cryopreservation in many insects1. However, D. melanogaster adults show very weak capacity to enter reproductive diapause910, and larvae possess absolutely no capacity for diapause. D. melanogaster is a fly of tropical origin, its larval stage is evolutionarily adapted for rapid growth and development under warm conditions, and all ontogenetic stages are highly susceptible to cold1112. In insect species that lack diapause, the potential for practical long-term storage at low temperatures could be limited unless the host of problems linked to development of indirect chill injury is solved. The causes of indirect chill injury are insufficiently understood but likely involve a complex of detrimental changes: metabolic disorder, oxidative stress, depletion of free chemical energy, and disturbance of ionic and osmotic homeostasis1314151617. The first goal of our study was to determine the temperature conditions that are sufficiently cold to halt the developmental processes (inducing quiescence), but warm enough to avoid/slow down accumulation of indirect chill injury. Based on previous reports1819 and our previous results11, we focused on constant low temperatures (CLTs) in the range from +3 to +9 °C and assessed the time limits of larval storability. Next, we attempted to extend the storage time by applying fluctuating thermal regimes (FTRs). In FTRs, relatively long periods of cold are alternated, most often on a daily basis, with relatively short periods at high/optimal temperature. In various insects, a brief exposure to high temperature allows repair of chill injury accrued during preceding cold periods and, consequently, extends storage at low temperatures (for a recent review, see ref. 20). Using a combination of low temperature-induced quiescence and FTR-based suppression of chill injuries, we were able to store viable larvae for up to 2 months. Next, we conducted metabolomic and transcriptomic analyses of CLT- and FTR-exposed larvae in order to describe the physiological basis of long-term survival of the chill susceptible larvae in quiescence. We identified developmental failures, depletion of energy substrates, loss of metabolite homeostasis and oxidative damage as potential mechanisms responsible for accumulation of indirect chill injury, which sets physiological limits on D. melanogaster low-temperature storability. Results and Discussion D. melanogaster larvae can be stored in quiescence for up to 2 months We assayed survival and storability of fully grown 3rd instar larvae of D. melanogaster at different thermal regimes for various periods ranging from 1 d to 60 d. Five constant low temperatures (CLTs: 3 °C, 5 °C, 6 °C, 7 °C, and 9 °C) and two fluctuating thermal regimes (FTRs: 5 °C/11 °C and 6 °C/11 °C; for more explanations, see Methods and Fig. S1a) were assessed. Upon transfer to low temperatures, larvae halted ontogeny at the pre-wandering stage and entered into quiescence. The ‘temperature-window’ for successful quiescence is theoretically delimited by the temperature of the upper limit of cold injury zone (ULCIZ) from below21 and the temperature of the lower developmental threshold (LDT) from above22. Although diapausing insects are often able to shift their ULCIZ to deep sub-zero temperatures (even to −196 °C in extreme cases7), the temperature-window for quiescence in D. melanogaster larvae is relatively narrow. It spans approximately from 6 °C (ULCIZ11) to 10 °C (LDT1819). We confirmed this narrow quiescence window by observing the rapid occurrence of chilling injury and mortality in larvae at CLTs of 3 °C (Fig. S1b) and 5 °C (Fig. 1a). Conversely, most larvae continued developing, wandered, and pupariated, but were not able to proceed further in development and died at CLT 9 °C, (Fig. S1d) (‘pupariation mortality,’ see grey lines in survival diagrams). At CLTs 6 °C and 7 °C, i.e. at optimum temperatures for quiescence, larval survival was relatively high and small proportions of larvae (up to 13%) succumbed to pupariation mortality. The survivor larvae, however, showed impaired capacities to form puparia and emerge as fit adults. Thus, only 0.9% and 2.1%, adults emerged after 60 d-storage at CLT 6 °C (Fig. 1b) and CLT 7 °C (Fig. S1c), respectively. Application of FTR protocol significantly improved survival at low temperatures. The positive effect of FTR was especially apparent in the experiment comparing survival at CLT 5 °C (Fig. 1a) vs. FTR 5 °C/11 °C (Fig. 1c). The highest long-term survival was recorded at FTR 6 °C/11 °C where 54.5% larvae were still alive after 60-d-long storage and 13.1% healthy adults emerged (Fig. 1d). The general rationale used to explain the positive effect of FTR on insect survival at low temperature is based on the assumption that brief, periodic exposures to high temperature allow repair of indirect chill injury accrued during preceding cold periods20. During warm episodes, insects could re-establish the ion balance that was partially lost during preceding chilling episodes23. In addition, the insects probably can exploit the warm episodes for: repair/degradation of damaged proteins via heat shock protein-assisted processing2425; replenishment of potentially depleted ATP26; management of oxidative damage27; or synthesis of cryoprotectants that would be useful in subsequent cold spells (for detailed discussion, see ref. 20). We will discuss some of these mechanisms later. We observed (Koštál et al., unpublished observations) that a small fraction of larvae survived at FTR 6 °C/11 °C even after 3 months, but these larvae were not able to metamorphose into adults. We also observed that increasing the temperature of warm episodes of FTR by just a single degree C (from 11 °C to 12 °C) or extending the duration of the warm episode of FTR by just 2 h (from 4 h to 6 h) allowed slow continuation of larval development resulting in high pupariation mortality (Koštál et al., unpublished observations). Practical applicability of the FTR 6 °C/11 °C storage protocol to other strains (other than Oregon R that was used in this study) or mutant strains of D. melanogaster is not straightforward, but would require careful assessment. Physiological limits of low temperature storability in D. melanogaster larvae The insect cold tolerance literature recognizes three basic types of cold-associated injury (for review see ref. 28): freezing of body water resulting in cellular dehydration, osmotic concentration of solutes, and mechanical damage to cells29; direct chilling injury upon exposure to severe cold shock, which causes dissociation of multimeric proteins, protein denaturation, and membrane lipid phase transitions303132; and indirect chilling injury upon chronic exposures to relatively mild low temperatures, which causes gradual accumulation of various metabolic disorders including oxidative stress, depletion of energy substrates and/or ATP, and disturbance of ionic and osmotic homeostasis1314151617. Our analysis focused on indirect chilling injuries as we exposed the larvae to temperatures slightly above the ULCIZ. The survival data were best-fitted using two-phase exponential decay curves (Fig. 1b–d and Fig. S1c). The first phase of fast decay of survival was observed in both CLT and FTR conditions during the early part of storage (approximately 1–2 weeks). We speculated that this high initial mortality could be linked to developmental failures in larvae that were out of the optimal ontogenetic stage for entry into quiescence (too early or too late in development) when being transferred to storage conditions. We defined the developmental failure as an inability to proceed correctly through the specific ontogenetic stage when the blockade of morphogenetic processes was incomplete during quiescence. The developmental failure was most clearly expressed in our experiments at constant 9 °C, when all larvae proceeded successfully to wandering and pupariation stages but were not able to form and proceed through the pupal stage. Later during storage, the rate of decrease in survival was much slower (second, slow decay phase). This meant that the larvae that managed to arrest their ontogeny at an optimal stage for quiescence were able to survive until a combination of accumulated indirect chill injuries killed them. The nature of chill injuries will be discussed next. Alterations in metabolomic profile linked to entry into quiescence Our metabolomic analysis revealed variations in the levels of 37 different metabolites (see complete list in Table S1) linked to storage at CLT 6 °C (will be abbreviated as CLT in next text) and FTR 6 °C/11 °C (will be abbreviated as FTR in next text). We subjected these data to between-class PCA analysis, which clustered the treatments and found statistically significant differences between them (Monte Carlo test, P < 0.001). The plot of PC1 and PC2 components, collectively accounting for 64.80% of total inertia, is presented in Fig. 2a. Exposure to 6 °C for a period as short as 18 h exerted a strong influence on metabolite composition, as witnessed by clear separation of the treatment Start from the treatment CLT1. The PCA analysis further revealed that the metabolomic response occurred in two phases. During the first phase (from Start to day 3, green arrow in Fig. 2a), the clusters of all treatments gradually moved along the PC1 and PC2 axes in negative directions. According to the projection of individual metabolites on the correlation circle (Fig. 2b), this gradual shift was driven mainly by increasing concentrations of some aromatic amino acids (phenylalanine, tyrosine, tryptophan, DOPA) and of methionine, whereas the concentrations of most organic acids (except citrate and aconitate), and fructose and alanine, decreased. The shift proceeded ‘faster’ under CLT than under FTR conditions. That was because numerous metabolites showed characteristic staircase-like trends under FTR conditions, where the concentrations were driven to opposite directions during the cold and warm episodes (see four examples in Fig. 2c). These results indicated that loss of initial metabolite homeostasis proceeded faster under CLT than under FTR. Collectively, the first phase was characterized by metabolite changes suggesting a slowdown of intermediary metabolism, including glycolysis and TCA turnover: (i) glucose slightly decreased and fructose was rapidly depleted despite that very high concentrations of both sugars were present in the larval diet11. These results indicated that food intake/digestion was severely compromised; (ii) pyruvate, the end-product of glycolysis, decreased and two end-products of fermentation, lactate and alanine, decreased as well; (iii) two upstream intermediates of TCA, citrate and aconitate, increased, whereas the others decreased (ketoglutarate, succinate, fumarate, and malate) suggesting a blockade of TCA at the locus of isocitrate dehydrogenase, which converts isocitrate to ketoglutarate. The samples taken on day 7 of exposure shifted far along the PC2 axis in the positive direction. Again, the direction of this shift was similar in CLT and FTR treatments, whereas the distance shifted was longer in CLT than in FTR. During this second phase (blue arrows in Fig. 2a,b), metabolic suppression probably continued, but the metabolite composition partially recovered (the concentrations of TCA intermediates showed a trend toward initial conditions) and/or new homeostatic conditions were established. Under the new homeostatic conditions, metabolism probably shifted toward higher exploitation of proteins and lipids as energy substrates: (i) the concentrations of trehalose, a principle sugar in insect circulation33, were maintained high and almost constant; (ii) the breakdown of proteins was indicated by increasing concentrations of free amino acids. For instance, glutamine concentrations increased from 10.4 nmol mg−1 FM at Start to 29.7 nmol mg−1 FM (day 7 of CLT) or 34.8 nmol mg−1 FM (day 7 of FTR). Glutamine may serve as a sink and deposit of amino-groups released from other amino acids during their degradation; and (iii) the lipid breakdown was indicated by increasing glycerol concentrations. The changes in metabolite profiles were broadly similar at CLT and FTR. This similarity probably reflects the fact that temperatures were favourable for survival (above ULCIZ) in both treatments. Nevertheless, larvae survived longer at FTR than at CLT and our metabolomics analysis confirmed that the warm episodes of FTR may generally serve the purpose of re-setting the homeostatic conditions, reverting potentially detrimental trends, and removal of potentially toxic intermediates (Fig. 2c; see also refs 20 and 23). Alterations of gene expression linked to entry into quiescence Gene expression patterns changed profoundly in response to cold exposure irrespective of whether it was applied as the FTR or CLT regime. All details on identity of differentially expressed (DE) sequences, including exact log2-fold changes and the results of statistical analysis, are summarized in Table S2, parts A–F. The Fig. 3a shows that 1,737 and 1,962 sequences were significantly up- and down-regulated, respectively, when comparing the transcriptomes analysed on day 7 of cold exposure to the Start of experiment (three different end points: CLT7 and FTR7 sampled at the end of the cold [C] and warm [T] episode vs. single start point [S]). Direct validation using qRT-PCR analysis in 11 selected genes confirmed high reliability of our RNAseq results (Fig. 3b). The Venn’s diagrams in Fig. 3a suggested that a large part of the gene expression response to cold was common to FTR and CLT regimes. White ovals delimit numbers of cold-responding DE-genes shared between FTR and CLT conditions: 819 up-regulated and 833 down-regulated in total. We performed the enrichment analysis of these shared DE sequences (Table S3, parts A, B) and found that the gene categories associated with catabolic processes of carbohydrates, lipids, and amino acids, respiration, and energy production were significantly under-represented. Diverse glycosyl hydrolases, and among them specifically mannosidases, formed the most down-regulated category. Mannosidases are enzymes degrading yeast cell walls containing polymannose chains34. These results indicated, in agreement with metabolomics, that digestion of food, catabolism, and energy production were not only severely compromised, but probably also actively down-regulated (as indicated by relatively low abundances of relevant transcripts) upon transfer to low temperatures. Conversely, the gene categories associated with activity of glutathione transferases and metabolism of xenobiotics were significantly over-represented under CLT and FTR conditions compared to Start. These results identify metabolic disorders (accumulation of potentially toxic intermediates), loss of redox balance, and oxidative damage as potential sources of indirect chill injury linked to storage at low temperatures (see also refs 27,35 and 36). The global difference in gene expression between FTR and CLT regimes was relatively small. When comparing two treatments with the same end-temperature of 6 °C, i.e. FTR7C vs. CLT7, 295 sequences were up-regulated, whereas 217 sequences were down-regulated (see red ovals in the Venn’s diagrams associated with Table S3, parts C, D). The enrichment analysis of these DE-genes identified that some GO terms associated with chitin metabolism and cuticle formation were differently regulated between CLT and FTR. Such differences might be related to slow development in cuticle, the dynamism of which was probably suppressed more at CLT than at FTR (see our previous discussion on incomplete developmental arrest in quiescence). Other differences between CLT and FTR concerned the GO terms associated with either glycosyl hydrolases on one side or iron binding, redox reactions, and glutathione transferases on the other side, i.e. the processes that were generally either down- or up-regulated, respectively, under both CLT and FTR conditions (Table S3, parts C, D). To further document the overall similarity in expression trends under two thermal regimes, CLT and FTR, we performed an extended qRT-PCR validation analysis of mRNA transcripts in four selected genes, maltase A8, glutathione transferase D5, larval cuticular protein 1, and amyrel. Results of extended validation exemplify that relatively small differences in gene transcript abundances on day 7 might arise simply as a result of slightly different rates of generally similar trends under CLT and FTR conditions (Fig. 3c). Only 116 sequences were up-regulated and 126 sequences were down-regulated in the T vs. C episode of FTR (Table S3, parts E, F). The effect of altering the warm and cold episodes during FTR was analysed using enrichment analysis of these DE-genes. No significantly warm-over-represented gene category was found. We found only one significantly warm-under-represented category that included four cysteine-rich genes with unknown function (described by two different terms: SM00689 and IPR006611). In addition, the category of stress genes, including several heat shock factors (hsr omega and hsf) and genes coding for proteins involved in response to extreme temperatures (DnaJ, Hsp60, Hsc2, and Hsp83), was found to be marginally significantly warm-under-represented (meaning: cold-over-represented). Differences in physiology between the larvae stored at CLT vs. FTR We compared the mass parameters, hydration, basic biochemical composition, selected metabolites, total ATP content, potassium concentration in haemolymph, and two biomarkers of oxidative damage in the larvae collected at the Start of the experiment and after 30 days of storage at CLT or FTR. We found that larvae experienced significant losses of fresh mass (FM, 26.8%), dry mass (DM, 37.0%), and water mass (WM, 23.2%) at CLT, which was in striking contrast to FTR-stored larvae that were able to maintain all these parameters practically constant (Fig. 4a, Table S4). The most plausible explanation for this difference was that the larvae stored at FTR ingested food during warm episodes, whereas the larvae stored at CLT were starving. Therefore, the CLT-stored larvae probably had to rely on their internal reserves much more than FTR larvae. Consequently, CLT-stored larvae exhibited massive depletions of energy substrates: 69.0% of glycogen, 31.3% of proteins, and 29.5% of lipids were lost within 30 days (Fig. 4b, Table S4). Extrapolating these decreasing trends to longer durations of storage, it is reasonable to expect that the depletion of energy substrates, especially of glycogen, will limit storage time at CLT at some point lying close to the empirically observed limit of 60 days. Interestingly, the FTR-stored larvae were able to maintain their lipid reserves constant for 30 days, similar to diapausing larvae of C. costata stored at 4 °C7. In holometabolous insects, the fat stores accumulated during the larval stage are brought forward to the pupa and serve as energy stores for metamorphosis and early adult life37. D. melanogaster pupae consumed 35% and 27% of their initial lipid and carbohydrate reserves, respectively, to fuel metamorphosis into the adult form38. Therefore, even a partial depletion of energy stores during the larval stage may critically limit survival during future ontogenetic steps. The alteration of metabolic pathways during larval quiescence, either at CLT or FTR, resulted in depletion of specific intermediary metabolites (pyruvate, ketoglutarate, and glutamate), whereas other metabolites were accumulated (glutamine, proline, and arginine) (Fig. 4b, Table S4). Interestingly, we recently showed that all three accumulated metabolites could stimulate high freeze-tolerance in larvae of D. melanogaster when applied as food additives39. In theory, the accumulated proline and glutamine, probably in combination with trehalose and some other amino acids, could stabilize cells by preventing or reducing partial unfolding of proteins and membrane fusion in the larvae exposed to thermal stress linked to quiescence4041. The cryoprotective function of arginine is probably exerted specifically during freeze dehydration, which is not relevant for storage in quiescence (for discussion on cryoprotective roles of metabolites, see ref. 39). Natural accumulation of proline has been observed in various insects during cold acclimation424344. The cryoprotective role of proline was directly proven in plants4546 and proline was found to be essential for cryopreservation of C. costata larvae in liquid nitrogen7. It seems likely that the cold-induced accumulation of proline, and its metabolic associates, has been bolstered in the process of evolutionary adaptation to cold in some cold-hardy organisms. No, or only a weak, evolutionary adaptation to cold, however, is expected in larvae of D. melanogaster. These larvae were designed by evolution for rapid growth and development under warm conditions of tropics12. Our results strongly support the view that the accumulation of proline is a widespread feature resulting from redirecting the metabolic pathways during metabolic suppression. As such, the accumulation of proline might serve as pre-adaptation in natural selection of organisms forced into dormancy during cooling of their habitats47. The two metabolites that specifically accumulated only in CLT-stored larvae were lactate and alanine (Fig. 4b, Table S4). These results suggested that CLT-stored larvae had to rely more than FTR-stored larvae on ATP production via the anaerobic glycolytic pathway, and/or that CLT-larvae were not able to effectively metabolize the end products of the fermentation pathways. Despite this difference, the larvae were similarly balancing the processes of ATP production and consumption at both regimes, CLT and FTR. Relatively small and similar decreases of total ATP levels were observed during 30 days of storage at CLT (18.9% of ATP lost) and FTR (17.7% of ATP lost) (Fig. 4b, Table S4). The balanced supply of ATP is critically needed to secure basic metabolic and homeostatic processes during quiescence. For instance, the quiescent larvae proved their ability to maintain relatively low concentrations of potassium in their haemolymph for at least 30 days at both CLT and FTR conditions (Fig. 4c). In contrast, the characteristic increase of extracellular potassium concentration (hyperkalaemia) occurred in the larvae when we transferred them from 25 °C to 0 °C (Fig. 4d). Within 30-min of exposure at 0 °C, the potassium concentration significantly increased, almost 2-fold, compared to initial conditions and the insects died. Cold-induced hyperkalaemia was shown to be strongly correlated with the degree of chilling injury in different insects14154849. The cold-induced hyperkalaemia is believed to stem from an inability to energize the primary ion pumping systems in the hind gut and/or Malpighian tubules and, consequently, to maintain organismal osmotic and ionic homeostasis. Hyperkalaemia leads to cell membrane depolarization, which probably initiates a cascade of detrimental processes, including uncontrolled activation of cellular proteases and lipases that ultimately destroy cell integrity135051. Results of previous studies273536 and those of our enrichment gene expression analysis (Table S3) have suggested that metabolic disorder and oxidative stress might be important causes of indirect chilling injury. Therefore, we assessed the levels of lipid hydroxyperoxides (LPOs) and protein carbonyls (PLs) in the quiescent larvae stored at CLT and FTR. Indeed, we found that CLT-stored larvae might suffer from oxidative stress as the levels of both biomarkers of oxidative damage were slightly elevated. Although these elevations were only marginally significant in statistical terms, they may represent actual tolerable limits, as suggested by a parallel analysis of stress biomarkers in control larvae exposed to paraquat-augmented diet (for more details, see Table S4). No elevations of LPO and PL levels were observed under FTR conditions. These results suggest that while the detoxification and anti-oxidant systems were transcriptionally bolstered in quiescent larvae at both CLT and FTR conditions, the systems were functioning more efficiently at FTR than at CLT conditions. Methods Insects, thermal conditions and survival/storability assays All experiments were conducted with Oregon R strain of Drosophila (Sophophora) melanogaster52. The stock strain has been maintained for decades in our laboratory in glass tubes (12 cm high, 2.5 cm in diameter) at constant 18 °C with 12-h/12-h light/dark (L/D) cycle in incubators MIR 154 (Panasonic Healthcare, Gunma, Japan). Each tube contained 5–10 g of artificial diet composed of agar (1%), sugar (5%), yeast (4%), cornmeal (8%), and methylparaben (0.2%). In order to obtain synchronously developing cohorts of larvae for experiments, approximately 50 pairs of flies (25 females) were allowed to lay eggs for 24 h at the conditions specified above. Next day, embryos were transferred to constant 15 °C with 12-h/12-h light/dark (L/D) cycle and reared until the first wandering larvae occurred, typically on day12 of larval age. Next, all wandering larvae were removed and the tubes with remaining larvae were transferred to constant darkness and experimental thermal regimes. Using the larval stage, rather than adult stage, of D. melanogaster for experiments was based on our earlier experience with this model. In previous papers, we compared cold- and freeze-tolerance in the larvae of two drosophilid flies, sub-arctic diapausing C. costata7 and tropical non-diapausing D. melanogaster811. We have assayed survival and storability of larvae exposed to different thermal regimes for different periods of time ranging from 1 d to 60 d. Five constant low temperatures (CLTs: 3 °C, 5 °C, 6 °C, 7 °C, 9 °C) and two fluctuating thermal regimes [FTRs: 20-h of 5 °C/4-h of 11 °C (in brief: FTR 5 °C/11 °C) and 20-h of 6 °C/4-h of 11 °C (in brief: FTR 6 °C/11 °C)] were tested (Fig. S1a). The thermal conditions were set in incubators MIR 154. The random fluctuations around the set point were not exceeding ± 0.2 °C, which was verified by direct temperature recordings inside the larval diet using the datalogger S0122 equipped with external Pt1000 temperature probe (Comet System, Roznov pod Radhostem, Czech Republic). The chosen thermal conditions for experiments were based on: (i) literature data showing that the lower developmental threshold temperature for larval and pupal development is 10–11 °C (Loeb and Northrop, 1917; Bliss, 1927); (ii) our earlier observations showing that temperatures below a threshold of 6 °C rapidly caused mortality11; and (iii) our preliminary assays showing that higher temperatures of warm period (12 °C) and/or longer warm periods (6 h, 12 h at 11 °C) allow most larvae continuing into wandering stage and making unsuccessful attempts to pupariate (called ‘pupariation mortality’ in this study) within 2–4 weeks. After the exposure to given thermal conditions, tubes containing insects were moved to room temperature (at the end of warm period) and allowed to equilibrate for 1 h. Then, all insects were inspected under binocular microscope (larvae still inside diet were washed out) and scored to three categories: live larva in the diet or on glass wall (classified as ‘larva’), dead larva in the diet (counted to total n but not classified), and malformed puparium on glass wall (classified as ‘pupariation mortality). All live larvae were moved to fresh diet and kept for another 30 d at constant 18 °C with L12/D12 photoperiod to check their ability to continue development. Pupariation and eclosion of fit adults were scored as ultimate survival criterions. Based on results of survival assays, two regimes were selected: CLT 6 °C and FTR 6 °C/11 °C (Fig. S1a) and subjected to more detailed metabolomic, transcriptomic and physiological analyses. In order to sample only living larvae for analyses, we observed the larvae under binocular microscope for short time (up to 5 min) after washing them out of diet using cold water (11 °C) and selected only those specimens showing spontaneous movements. The general abbreviations CLT and FTR will mean CLT 6 °C and FTR 6 °C/11 °C regimes, respectively, in the following text unless specified otherwise. Metabolomics Larvae were sampled after 0, 1, 2, 3 and 7 d- exposures to thermal regimes CLT vs. FTR. In case of FTR, larvae were sampled twice a day, first time at the end of cold period (6 °C, labelled as C) and second time at the end of warm period (11 °C, labelled as T) (see Fig. S1a). Whole larvae (pools of 4 larvae in 6 replications) were homogenized twice in 400 μl of 70% ethanol and the extracts were subjected to complex analysis of major metabolites using a combination of mass spectrometry-based analytical methods as described earlier11. Low-molecular-weight sugars and polyols were determined after o-methyloxime trimethylsilyl derivatization using gas chromatograph (GC) with flame ionization detector GC-FID-2014 equipped with AOC-20i autosampler (both from Shimadzu Corporation, Kyoto, Japan). Profiling of acidic metabolites was done after the treatment with ethyl chloroformate under pyridine catalysis and simultaneous extraction in chloroform53 using Trace 1300 GC combined with single quadrupole mass spectrometry (ISQ-MS) (both from Thermo Fisher Scientific, San Jose, CA, USA) and liquid chromatograph Accela LTQ XL with linear ion trap combined with high resolution mass spectrometers Q Exactive Plus coupled with Dionex Ultimate 3000 (all from Thermo Fisher Scientific). The metabolites were identified against relevant standards and subjected to quantitative analysis by using an internal standard calibration method. All standards used were purchased from Sigma-Aldrich (Saint Luis, MI, USA). Metabolite profiles were analysed using a between-class principal component analysis (PCA)54 to test clustering effects according to the experimental modalities. The between-class PCA focuses on differences among the classes defined as qualitative instrumental variables. A Monte-Carlo test (number of iterations = 1,000) was used to determine whether the samples were randomly distributed in variable space according to their experimental modality. All data were scaled and mean-centered prior to the PCA. All analyses were performed using the ade4 library in the statistical software R 3.0.3 (R Development Core Team, Vienna, Austria). RNAseq and gene expression enrichment analysis Whole larvae were sampled (pools of 8 larvae in 3 replications) at the start of experiment (Start) and after 7 d-long exposure to thermal regimes CLT vs. FTR and subjected to transcriptomic analysis. The total RNA was extracted using the RiboZol RNA Extraction Reagent (Amresco, Solon, OH, USA). Pellet of total RNA was dissolved in 20 μl of DEPC-treated water and an aliquot of 5 ul was taken for total RNA quality assessment on denaturing agarose gel and concentration measurement using NanoDrop 2000 (ThermoFisher Scientific, Waltham, MA, USA). The total RNA concentrations were levelled exactly to 0.5 ug/ul and the samples were either sent to the EMBLGenomics Core Facilities (GeneCore, Heidelberg, Germany) for cDNA library production and Illumina RNAseq or used for direct qRT-PCR validation of RNAseq results. The cDNA libraries were prepared using Covaris S2 (Covaris, Woburn, Massachusetts, USA) for fragmentation aiming for an insert size of about 150 nt and TruSeq RNA sample prep kit (Illumina, San Diego, California, USA). The cDNA libraries were then sequenced using 50 nt single end sequencing on HiSeq2000 sequencer (Illumina, San Diego, California, USA). The quality of RNAseq results was first assessed using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The raw reads were trimmed and all adapters and overrepresented sequences were removed with Trimmomatic software55. The resulting reads were filtered with a Phred quality score of at least 28. Reads were then mapped to Drosophila melanogaster genome (dm3) using TopHat 256 with default parameters. Aligned reads were then assembled into transcripts defined by coordinates using Cufflink (-I 300000 -F 0.1 -j 0.15 -p 6)57. Finally, the transcript differential expressions were calculated using Cuffdiff (geometric normalization, pooled dispersion estimation, 10 minimum alignment count, and cufflinks effective length was applied)58. Transcripts were considered significantly differentially expressed (DE) when the Benjamini-Hochberg-corrected p-value (q-value) was below 0.05 and the absolute log2-fold change was above 0.55. To detect if any particular ontology was enriched in our comparisons, we conducted an enrichment analysis using David software59. Gene categories or gene classification terms [GO term, InterPro classification, KEGG ID, Cluster of Orthologous Genes (COG), PIR superfamily, SMART accession, etc.] were considered significantly enriched when a corrected Bonferroni p-value was below 0.05. qRT-PCR validation of RNAseq results The aliquots of total RNA that was subjected to the RNAseq experiment were taken for direct validation of the RNAseq results. The 5 uL (2.5 ug) aliquots of total RNA were treated with DNase I (Ambion, Life Technologies) followed by the first strand cDNA synthesis using Superscript III (Invitrogen, Carlsbad, CA, USA). The cDNA products (20 μL) were diluted 25 times with sterile water. Relative abundances of mRNA transcripts for selected transcripts were measured by quantitative real time PCR (qRT-PCR) using the CFX96 PCR light cycler (BioRad, Philadelphia, PA, USA) and the LA Hot Start Master Mix (Top-Bio, Vestec, Czech Republic). PCR reactions were primed with a pair of oligonucleotide primers specific for 11 selected genes (Table S2, part G). Emission of a fluorescent signal resulting from SYBR Green binding to double-stranded DNA PCR products was detected with increasing PCR cycle number. Quantitation cycle (CQ) for each sample was automatically calculated using the algorithm built in the CFX96 PCR light cycler software. The levels of mRNA transcripts of Ribosomal protein L32 (Rpl32) and beta-tubulin 56D (β-tub) served as endogenous reference standards for relative quantification of the target transcript levels (See Figure associated with Table S2, part G and60). Each sample was run as a doublet (two technical replicates) of which the mean was taken for calculation. Relative ratios of the candidate mRNA levels (CQ) to geometric mean of the levels (CQ) of two reference gene mRNAs were calculated according to61. Next, we performed an extended validation of our RNAseq results using qRT-PCR of four selected genes: Amyrel, Gst D5, Maltase A8, and Lcp 1. For this validation, we added total RNA extracted from larvae that were sampled on days 1, 2 and 3 of storage at CLT or FTR regimes. The processing of larval samples to cDNA was equal as described above. Physiology We sampled the larvae at the start of experiment (Start, S) and after 30 d-long exposure to thermal regimes CLT vs. FTR (the FTR sample was taken at the end of cold period). Fresh mass (FM) was measured individually in 20 larvae in each treatment using Sartorius balance with sensitivity of 0.01 mg. Dry mass (DM) was measured after drying the specimens at 65 °C for 3 days. Water mass (WM) and hydration were calculated from gravimetric data. Total water soluble proteins were measured in a sample pooled of 5 larvae (3 replications for each treatment) by the bicinchoninic acid protein assay62 after extraction in 50 mM Tris, pH 7.2. Glycogen was extracted from a sample pooled of 5 larvae (3 replications) in hot alkali63 from the pellet remaining after removal of simple sugars using homogenization twice in 400 μl of 70% ethanol and centrifuging at 20,000 g/4 °C/10 min. Glycogen was assayed using the colorimetric determination with phenol and concentrated sulphuric acid64. Total lipids were measured in a sample pooled of 5 larvae (3 replications) using spectrophotometric analysis with phosphoric acid-vanillin solution65 after extraction of lipids by using chloroform:methanol solution (2/1, v/v)66. Total ATP concentration in muscle tissue dissected from a pool of 10 larvae (3 to 6 replications) was measured using enzymatic assay of luciferase that consumes ATP for convertion of beetle luciferin to oxyluciferin (CellTiter-Glo Luminescent Cell Viability Assay, Promega, Madison, WI, USA). Based on results of metabolomic analysis, we selected 10 most important metabolites (pyruvate, lactate, ketoglutarate, arginine, glutamine, aspargine, alpha alanine, proline, glutamate and trehalose, together representing more than 75% of the total metabolite pool on day 7) and conducted their targeted quantification using methods described above. Pools of 5 larvae were sampled in 3 biological replicates for each treatment. The concentration of potassium ions was measured using MI-442 K+ Ion Microelectrode in combination with reference electrode MI-402 (both from Microelectrodes Inc., Bedford, NH, USA). A sample of hemolymph was collected from a pool of 10–20 larvae (to reach ca. 3 μl in total) into calibrated micro-capillary tube (Broomall, PA, USA). Exactly 2.5 μl of hemolymph was then diluted 3 times with 5 μl of deionized water in order to obtain sufficient volume for microelectrodes (7.5 μl). Three to six biological replicates (pools of 10–20 larvae) were measured in each treatment. Manipulation with 10–20 larvae (removal out of diet, tearing, collecting the hemolymph into capillary) took approximately 2–3 min, during which the larvae were maintained at the same temperature as in the treatment (Start, 15 °C; CLT, 6 °C; FTRC, 6 °C; FTRT, 11 °C). Voltage was measured using pH/mV Hand-Held Meter pH 330 (WTW, Weilheim, Germany) and converted to [K+] using semilog line regression calibration curve. The calibration samples (1 mM, 10 mM, 100 mM KCl solution) were measured just prior to measuring the samples on every occasion. The levels of two biomarkers of oxidative stress were analyzed in larval muscle tissue dissected from 10 larvae in three biological replicates for each treatment. Lipid hydroxyperoxides (LPOs) were quantified using colorimetric assay utilizing redox reaction of LPOs with ferrous ions (LPO Kit ab133085, Abcam, Cambridge, UK). The amount of LPO was expressed as percentage of total phospholipids extracted from larval muscle in chloroform:methanol (2:1, v/v) followed by acetonitrile/hexane phase separation as described earlier67. Protein carbonyls (PCs) were analyzed after their tagging with DNPH followed by colorimetric assay of DNP hydrazones formed in the reaction provided in the Protein Carbonyl Assay Kit (ab126287, Abcam). PCs were expressed in nmols per total protein extracted from larval muscle as described above. Additional Information How to cite this article: Koštál, V. et al. Physiological basis for low-temperature survival and storage of quiescent larvae of the fruit fly Drosophila melanogaster. Sci. Rep. 6, 32346; doi: 10.1038/srep32346 (2016). Supplementary Material Supplementary Information Supplementary Table S1 Supplementary Table S2 Supplementary Table S3 Supplementary Table S4 We thank I. Vacková and A. Heydová for technical support. This work was supported by the Czech Science Foundation (grant 13-01057S to V.K.). R.P. received his salary from Modbiolin grant no. 316304 sponsored by European Union Seventh Framework Programme (FP7/2007–2013). Author Contributions V.K. designed the reseach, directed the project, adjusted and validated experimental procedures, analyzed data, assembled all figures, and wrote the manuscript. J.K. conducted survival assays, sampled and processed insects for metabolomic and transcriptomic analyses, and measured most physiological parameters. T.Š. performed qRT-PCR validation analysis and measured potassium concentrations. R.P. analyzed RNAseq data and performed enrichment analysis. H.C. analyzed metabolomic data. H.Z. and I.O. performed metabolomic analyses. M.M. and P.Š. developed and assessed metabolomic analyses. All authors read and approved the paper. Figure 1 Survival under selected CLT and FTR regimes. (a–d) Survival of quiescent larvae of Drosophila melanogaster stored at two constant low temperatures (CLTs) of 5 °C (a) and 6 °C (b), and two fluctuating thermal regimes (FTRs) of 5 °C/11 °C (c) and 6 °C/11 °C (d).Three different levels of survival were scored: live larvae (blue circles, larvae showing spontaneous movements); puparia (orange circles, formation of morphologically normal puparium); and adults (red circles, eclosion of morphologically normal adult). In addition, we counted numbers of malformed puparia on the wall of the glass tube (grey circles) and scored them as ‘pupariation mortality.’ Numbers within parentheses are the total number of all individuals (n, including dead larvae) recovered at each time. The two-phase exponential decay curves (Prism 6.0, GraphPad, San Diego, CA, USA) were fit to survival data with a goodness of fit, R2: (a) 0.9778, larvae; 0.9800, puparia; 0.9795, adults; (b) 0.9871, larvae; 0.9940, puparia; 0.9952, adults; (c) 0.8406, larvae; 0.9219, puparia; 0.951, adults; (c) 0.9544, larvae; 0.9682, puparia; 0.9863, adults. Figure 2 Cold-induced changes in metabolite composition. (a) The plot of PC1 and PC2 derived from principal component analysis shows clustering of treatments according to metabolite global composition analysed in quiescent larvae of Drosophila melanogaster stored at CLT 6 °C and FTR 6 °C/11 °C for 7 days. The inset schematically depicts CLT and FTR thermal regimes (for more information, see Fig. S1a). Six replicates of each treatment are linked to a common centroid by line segments; the ovals represent 95% confidence intervals around the centroid. (b) The projection of individual metabolites on the correlation circle helps to identify major drivers in cold-induced alteration of metabolite composition during the first 3 days (green arrow) and later (blue arrow). (c) examples of cold-induced concentration changes in four metabolites. For complete metabolite dataset, see Table S1. Figure 3 Cold-induced changes in transcriptome identified using RNAseq. (a) Venn’s diagrams showing the numbers of significantly (log2-fold change > ± 0.55, q value < 0.05) up- and down-regulated mRNA transcripts in quiescent larvae of Drosophila melanogaster stored at CLT 6 °C and FTR 6 °C/11 °C for 7 days compared to Start of the experiment (S). For complete dataset, see Table S2, parts A–F. White ovals in Venn’s diagrams show cold-responding differentially expressed sequences shared between CLT and FTR that were later subjected to enrichment analysis (Table S3, parts A–F). (b) the reliability of RNAseq results was validated using qRT-PCR analysis of mRNA abundances in 11 selected sequences relative to two reference sequences, Ribosomal protein L32 and beta Tubulin 56D (Table S2, part G). Heat maps code for log2-fold changes in RNAseq and qRT-PCR analyses of the same total RNA samples. (c) examples of cold-induced changes in four sequences identified in the extended validation of RNAseq results using qRT-PCR. Additional samples of total RNA were collected on days 1, 2, and 3 of storage at CLT and FTR to describe the dynamics of transcriptomic changes during cold storage. Figure 4 Changes in physiological parameters during 30-d-long storage at CLT and FTR. (a) Differences in fresh mass (FM), dry mass (DM), and water mass (WM) in quiescent larvae of Drosophila melanogaster stored at CLT 6 °C and FTR 6 °C/11 °C for 30 days compared to Start of the experiment. Differences were analysed using an ANOVA followed by Bonferroni’s post hoc test. (b) Schematic depiction of major processes, catabolic and energy production pathways, selected energy substrates, metabolites, and ATP. Metabolomic and transcriptomic analyses collectively suggest that processes of food intake, digestion, catabolism, and energy metabolism are generally suppressed during quiescence (dashed black arrows). The growth and development, and associated anabolic processes, are arrested. In contrast, the metabolic pathways resulting in accumulation of some amino acids, and the processes linked to homeostasis and cell protection are relatively bolstered in quiescent larvae (dashed red arrows). The small diagrams represent fold-differences in levels of selected compounds between larvae collected at the Start of experiment and after 30 days of storage at FTR (red columns and numbers) and CLT (blue columns and numbers). Some of the accumulated amino acids may stabilize cells of quiescent larvae (proline, dashed green arrow). For complete dataset, see Table S4. (c) Homeostasis of potassium concentration in haemolymph during 30-d-long quiescence at FTR and CLT (C and T, samples collected at the end of cold and warm episodes, respectively, of FTR; numbers within parentheses above data points represent total number of all individuals) Differences were analysed by Student’s t-test. (d) Rapid development of hyperkalaemia (failure of homeostasis) upon transfer of the 25 °C-acclimated larvae to 0 °C. The lethal times Lt50 and Lt90 for mortality of 50% and 90%, respectively, larvae exposed to 0 °C are taken from our earlier study11. ==== Refs Leopold R. A. & Rinehart J. P. A template for insect cryopreservation in Low Temperature Biology of Insects (eds. Denlinger D. L. & Lee R. E. ) 325 –341 (Cambridge University Press, 2010 ). Denlinger D. L. Why study diapause? Entomol. Sci. 38 , 1 –9 (2008 ). Steponkus P. L. et al. Cryopreservation of Drosophila melanogaster embryos . Nature 345 , 17 –172 (1990 ). Mazur P. , Cole J. W. , Schreuders P. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3241110.1038/srep32411ArticleBacterial community structure and function shift across a northern boreal forest fire chronosequence Sun Hui a12Santalahti Minna 2Pumpanen Jukka 3Köster Kajar 45Berninger Frank 4Raffaello Tommaso 4Asiegbu Fred O. 4Heinonsalo Jussi 21 Collaborative Innovation Center of Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing, 210037, China2 Department of Food and Environmental Sciences, University of Helsinki, Helsinki, 00790, Finland3 Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, 70210, Finland4 Department of Forest Sciences, University of Helsinki, Helsinki, 00790, Finland5 Institute of Forestry and Rural Engineering, Estonian University of Life Sciences, Tartu, 51014, Estoniaa hui.sun@njfu.edu.cn30 08 2016 2016 6 3241105 05 2016 09 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Soil microbial responses to fire are likely to change over the course of forest recovery. Investigations on long-term changes in bacterial dynamics following fire are rare. We characterized the soil bacterial communities across three different times post fire in a 2 to 152-year fire chronosequence by Illumina MiSeq sequencing, coupled with a functional gene array (GeoChip). The results showed that the bacterial diversity did not differ between the recently and older burned areas, suggesting a concomitant recovery in the bacterial diversity after fire. The differences in bacterial communities over time were mainly driven by the rare operational taxonomic units (OTUs < 0.1%). Proteobacteria (39%), Acidobacteria (34%) and Actinobacteria (17%) were the most abundant phyla across all sites. Genes involved in C and N cycling pathways were present in all sites showing high redundancy in the gene profiles. However, hierarchical cluster analysis using gene signal intensity revealed that the sites with different fire histories formed separate clusters, suggesting potential differences in maintaining essential biogeochemical soil processes. Soil temperature, pH and water contents were the most important factors in shaping the bacterial community structures and function. This study provides functional insight on the impact of fire disturbance on soil bacterial community. ==== Body Wildfire is a prevalent natural disturbance across the boreal forest region1, and its frequency and intensity are expected to increase with climate warming2. Forest fire directly affects soil carbon (C) cycling via immediate and high CO2 emissions from biomass combustion, and indirectly through long-term changes in ecosystem C dynamics and in soil organic matter chemical composition that occur during post-fire forest recovery and succession3. Soil microbial communities play essential roles in forested ecosystems via nutrient cycling and decomposition of organic matter4. Bacteria are the most abundant group of soil microorganisms in terms of species5 and are among the first organisms to colonize dead wood after disturbance event and metabolize the easily accessible substrates6. Fire dramatically reduces the biodiversity of the microbial community and biomass of soil microorganisms278. The effect of fire on soil microbial community is the greatest closest to the soil surface in the organic horizon and in the top few centimeters of mineral soil where heating is most intense9. Therefore, even low-intensity non-stand replacing fires may affect microbial communities through heat-induced mortality89. Soil microbial responses to fire are likely to change over the course of forest recovery after disturbance, and may only persist until aboveground plant communities regenerate10. Fire disturbances often cause changes in soil temperature due to loss of canopy cover and increases soil pH, both of which are likely to have large direct and indirect effects on soil microbial communities1112. The increase in soil pH after fire favors bacterial growth13. The alteration of soil physical and chemical properties, like hydrophobicity, nutrient concentrations, and C quality by fire, may in turn have negative consequences for microbes7. Therefore, it is important to understand how microbial communities respond to the post fire environment. Fungi are considered to be important decomposers in forest soil and have been studied for fire-mediated changes141516. Bacterial changes following fire have been studied more extensively than fungi12171819. However, investigations of bacterial dynamics over the course of a century and a half following fire are rare. There is also need to determine how fire affects bacterial communities and their ecosystem functions using molecular biological tools. The advanced sequencing technology (e.g. Illumina MiSeq sequencing) allows us to better understand the environmental microbial community structure20. Functional gene arrays, such as the Geochip, are efficient for assessing the functional attributes of microbial communities in different environments2122. The present study is part of a larger project investigating the microbial community structure and gene function across a 152-year boreal forest fire chronosequence. In this study, we characterized the responses of soil bacterial communities across three different periods of time post fire in a 152-year fire chronosequence (2-year, 60-year and 152-year after fire) by Illumina MiSeq sequencing, coupled with a high-throughput functional gene arrays, GeoChip 4.0. The aims of the study were 1) to evaluate the short- and long-term effect of forest fire and post-fire succession on soil bacterial communities; 2) to assess the functional potential of bacterial communities across the three times ranging from a few years after fire to over hundred years after fire. We hypothesized that the bacterial community after fire will differ with increasing time period since the last fire, and the community functions involved in different biochemical processes will change correspondingly. Results Information on the MiSeq sequencing A total of 312 301 high quality sequences were generated across the nine soil samples after sequence de-noising and quality filtering, covering the three burned sites. The number of sequence per sample ranged from 27 699 to 42 617 with average of 34 700 ± 4 953 (mean ± SD) sequence. All the sequences were classified to domain bacteria. Bacterial diversity after fire A total of 3 692 OTUs (7 995 OTUs including singletons) were estimated across the three burned sites. The 2y site harbored the most OTUs of bacteria (2 369 OTUs) followed by 60y (2 027 OTUs) and 152y (1 728 OTUs) sites (Table 1). The 60y site showed the highest diversity (H′, 5.3) and evenness (0.72). The regression analysis indicated that the estimate of species richness (Chao 1 and observed OTUs) decreased over time since fire (P = 0.03, R2 = 0.74). No significant difference in diversity was observed among the three burned sites. Bacterial community structure after fire The three sites shared 32% of the 3 692 OTUs (1 192 OTUs) (Fig. 1a). The number of unique OTUs to each site ranged from 233 to 602, accounting for 37% of the total number of OTUs (Fig. 1a). The 2y site had the highest number of unique OTUs (602) and the 152y site had the least number of unique OTUs (233). The 2y and 60y sites shared most of the OTUs (48%, 1767 OTUs). The PCoA based on the relative OTUs abundance indicated that the three sites with different fire history formed distinct communities (Fig. 2a). The PCoA plot explained 43.1% of the observed variation, where the first axis explained 25.1% of the variations and separated the 152y site from the 2y and 60y sites. The second axis explained only 18.1% of the variation and separated the 2y and the 60y sites. Subsequent analysis of PERMANOVA confirmed that the community structure differed significantly among the three sites (P < 0.004). Interestingly, further analysis by separating abundant (>0.1% of total sequences) and rare (<0.1% of total sequences) OTUs indicated that the rare OTUs contributed to the difference in community structure between sites (Figure S1). The OTUs from all the samples were classified to 10 bacterial phyla (Fig. 3). The majority of the OTUs belonged to the Proteobacteria (41.3%), followed by Actinobacteria (15.4%), Acidobacteria (10.4%), Bacteroidetes (6.9%), Planctomycetes (5.8%), Armatimonadetes (3.9%), TM7 (2.2%), Verrucomicrobia (1.7%), Gemmatimonadetes (0.6%) and Firmicutes (0.2%) (Fig. 3). Protecobacteria was the most abundant phylum across all the samples (38.6%) followed by Acidobacteria (34.4%) and Actinobacteria (17.8) (Fig. 3). A small percentage of the sequences (4%) could not be classified to any phylum. The abundance of Proteobacteria increased over time since fire (Figure S2). The three most abundant phyla (Proteobacteria, Actinobacteria and Acidobacteria) accounted for more than 90% of the total sequence reads. The relative abundance of the detected phyla remained relatively stable in each site (Figure S2). No difference in the abundance was observed for each phylum between sites. Among the 3 692 OTUs, 83% of them were assigned down to 33 classes, representing 95.4% of total sequence reads and 37% were assigned down to 132 genera, representing 52.3% of total sequence reads. Similar to phylum level, most of the classes did not show differences in the abundances between the sites. Only the class of Sphingobacteria and TM7 showed higher abundance at the 2y site than at the 152y and 60y sites (P = 0.03 and P = 0.04), respectively. Five genera showed significant differences in the abundance between the sites (Aciditerrimonas, Acidocella, Methylobacterium, Rudaea, Sphingomonas) and seven genera were represented only at the 2y site (Amnibacterium, Rhizobium, Spirosoma, Subtercola, Humicoccus, Kaistia, Marmoricola) (Table S1). Genus Sphingomonas had higher abundance at the 2y site than at the 152y site (P = 0.03). The abundance of Methylobacterium at the 2y site were also higher than that at the 60y site (P = 0.046, P = 0.03, respectively). The 152y site had higher abundance of Aciditerrimona and Acidocella than the 2y site (P = 0.034, P = 0.032, respectively). Relationship between environmental factors and bacterial community structure The soil bacterial community after fire was correlated with soil biogeochemical variables (R2 = 0.74, P = 0.01) (Table 2). The Distance Based Linear Model (DistLM) tests showed that the community structure was significantly correlated with soil temperature (P = 0.011), soil water content (P = 0.015) and soil pH (P = 0.017) (Table S2). Subsequent partitioning analysis showed that each of the three variables explained more than 20% of the observed total variation. Soil temperature and soil pH were positively correlated with the community at the 2y site, while soil water content was positively correlated with the community at the 152y site. The tree root biomass (TRootBiom), fungal ergosterol, soil C and soil N did not show significant correlation to bacterial community. Bacterial gene diversity and structure after fire In total, we detected 62 860 probes that originated from bacteria in the GeoChip 4.0 in all samples, representing 748 functional genes (Table 3, Tables S3 and S4). These genes were classified into 11 functional categories (Table 3), including metal homeostasis (17 208), secondary metabolism (10 439), C cycling (9 443), sulfur (9 415), organic remediation (5 571), nitrogen (N) (2 598), stress (1 748), secondary metabolism (1 479), phosphorus (1 430), electron transfer (382) and others (3 153). Gene probes originating from fungi, archaea and virus were excluded from this analysis to match the bacterial taxonomic analysis. Among the 748 functional genes, 92% of them (688) were shared between the three sites (Fig. 1b). Only a few genes detected were unique to each site. The highest gene diversity (H′) was observed at the 2y site followed by 152y and 60y site (Figure S3). The 2y site also had the highest number of detected probes (51 582 ± 432; mean ± standard deviation) (Table 3). The 60y site had the lowest gene diversity (H′) and the least number of probes detected (46 800 ± 2487; mean ± standard deviation). The gene diversity and the number of detected probes at the 2y site was significantly higher compared to the 60y site (P = 0.04, P = 0.03). The PCoA analysis based on the intensity of detected probes revealed that the three sites formed separate gene profiles (Fig. 2b). Subsequent PERMANOVA analysis confirmed that the composition of functional genes between the sites differed significantly (P = 0.001 in all pairs). To visualize the pattern of detected functional probes among the sites, a cluster analysis was performed. The hierarchical cluster analysis revealed a difference in functional genes among the three sites (Fig. 4). The 2y and 152y sites were clustered together, indicating similar functional gene profiles, whereas both differed from the 60y-B site (P = 0.003, P = 0.003, respectively). Functional genes involved in different processes Among the 11 gene categories, the number of detected probes in each category at the 2y site was significantly higher compared to the 60y site (Table 3). The signal intensity in each category was also significantly higher at the 2y site than that at the 60y site (Table S4). The genes involved in C, N and P cycling with significant difference in signal intensity between sites were shown in Fig. 5a–d. The genes involved in carbon degradation (6 359 probes), carbon fixation (2961 probes) and methane oxidation and methanogenesis (123 probes) were detected in all samples. The genes involved in degradation of chitin (chitinase), lignin (glx, vdh), hemicellulose (ara), pectin (pme), starch (amyA, nplT) were detected at the 2y site with higher signal intensity than that at the 60y site (P = 0.05) (Fig. 5a). Higher signal intensity of several genes involved in carbon fixation of calvin cycle (FBPase, pgk and TIM), multiple systems (pcc) and reductive acetyl-CCoA pathway (codH, fthFs) were also detected with higher intensity at the 2y site compared to the 60y site (P = 0.05) (Fig. 5b). For N cycling, genes involved in denitrification (1 135 probes), nitrification (471 probes), dissimilatory N reduction (389 probes), assimilatory N reduction (150 probes), N fixation (303 probes) and ammonification (110 probes) were detected in all samples and most of the genes showed similar signal intensity between the sites. Only the genes for N fixation (nifH) and denitrification (narG, nirS) showed higher signal intensity at the 2y site compared to the 60y site (P < 0. 05) (Fig. 5c). In total, 1430 phosphorus cycling probes were detected, involved in polyphosphate degradation (1122 probes), polyphosphate synthesis (212), phytic acid hydrolysis (88) and phosphorus oxidation (8) were detected. However, only polyphosphate degradation gene (5f1_ppk2) and polyphosphate synthesis (ppk) gene showed higher intensity at the 2 y site than that at the 60y site (P < 0.05) (Fig. 5d). Relationship between environmental factors and bacterial gene structure Similarly to the taxonomic structure, the bacterial gene structure was also correlated to environmental variables (R2 = 0.81, P = 0.003) (Fig. 2b, Table 2). DistLM tests indicated the bacterial gene structure were significantly correlated to soil temperature (P = 0.031), soil water content (P = 0.022), soil pH (P = 0.026) and soil N (P = 0.005) (Table S2). Each of the variables explained more than 20% of the total observed variation. Soil pH and temperature were positively correlated with the gene structure at the 2y site, whereas soil water content and soil N were positively correlated to the gene structure at both 60y and 152y sites (Fig. 2b). The tree root biomass (TRootBiom) and soil C and did not show significant correlation to bacterial community. Discussion We investigated the bacterial community composition and gene structure across a 152-year chronosequence after forest fire. The recently burned site (2y) harbored the most bacterial OTUs with the highest number of detected gene probes. Both phylogenetic and functional structures of bacterial communities differed between the sites with different fire histories that were clearly correlated to the environmental factors. The pH and temperature affect mostly the community composition 2y after fire, whereas later soil moisture, soil N and N content and root biomass had greater impact to the bacterial communities. The recently burned site (2y) site had the highest OTU richness and the richness decreased significantly over time after fire. Increased quantities of decomposable and burned material after the fire increase soil pH due to the production of K- and Na-oxidase, hydroxides and carbonates via ash deposition and accumulation23. The increased soil pH can favor bacterial growth over fungal growth13. Fire typically increases soil pH and other studies have shown decreases or no change in soil pH24. Similarly, the 2y site also harbored the highest number of gene probes, suggesting a positive correlation between biological richness and functional potential. Bacterial diversity has been reported to decrease with decreasing soil pH, in which a large variation of soil pH value was included2526. However, we did not observe a difference in the diversity indices among the sites with different fire history. After the fire, a relatively small pH ranges (3.8–4.0) was evident, which might make it difficult to determine the impact on changes in diversity. In addition, the changing environmental factors after the fire led to a shift in community composition and resulted in a change in the evenness of each group. For example, due to a more even community composition, the diversity in the 60y old site was higher than that in the 2y old site, although the species richness was lower at the latter site. These could be possible reasons explaining no observed differences in diversity between sites. As seen also in our study, it appears that environmental factors (e.g., soil temperature, pH, water content and soil N) have fundamental impacts on bacterial community structure72728. A shift in temperature would lead to changes in microbial community structure and function29. Soil pH has been a key factor driving soil bacterial community across a large range of ecosystems2530, and soil water content, organic C and N availability are also major determinants of soil microbial community composition31. Fire seems therefore to affect the soil bacterial community via altering the soil properties1132. The loss of vegetation cover after fire disturbance can also contribute to other factors (i.e. loss of water, organic matter, etc.) and lead to higher soil temperatures in fire disturbed areas1133. Higher soil temperatures also favor the enzymatic activity of microbes34. Our previous study conducted at the same sites showed that the fungal diversity was significantly affected by the fire and had long succession from 2 to 152 years after the fire16. These results indicate that bacterial community might recover more rapidly after the fire than fungi as fire does not seem to have any negative significant impact on bacterial diversity. Fire also reduced the biomass of trees and ground vegetation in our study sites and Köster et al.33 observed a significant reduction of fungal biomass 2y after fire in the same chronosequence. The decline in biomass was associated with an increase in the relative abundances of saprophytic fungi16. These findings support the conclusion that due to lower competition by mycorrhizal fungi, free living saprophytic organisms, both bacteria and fungi, become more abundant and dominate the communities after fire. Many OTUs (1 381, ~37%) were unique to a specific site, suggesting an overall high beta-diversity. The sites with different fire histories formed distinct communities. Interestingly, the rare OTUs (<0.1%) significantly contributed to the community structural differences. The most abundant OTUs (>0.1%) showed similar distribution across the sites. This pattern has been observed also in other studies35 indicating that the dominant OTUs are not sensitive to environmental changes whereas the high number of OTUs with low abundance are critical when bacterial community responses are evaluated. Phylogenetically, Proteobacteria, Actinobacteria and Acidobacteria were the main phyla across the sampling sites, which accounted for 90% of the total sequences. Similar results were also observed in a Chinese boreal forest after wildfire36 and also in subalpine soil environments28. The relative abundances of bacterial phyla have earlier been shown to differ significantly from 4 and 16 weeks37 as well as from 1 and 11 years36 following a fire. In our study, however, there was no significant difference in the relative abundance of each detected phyla or class among the sites with different fire histories. The relative abundance of bacteria at high taxonomic scale remained its temporal stability. Only few genera showed differences in the relative abundance between sites, while most of them were present only in 2y site. These differences compared to previous studies could be due to the length of time between the fires as previous studies were conducted several weeks to 11 years after the fire occurred. In our study, we sampled much longer time after the fire occurred (2y to 152y). The GeoChip data analysis demonstrated that the bacterial community gene structures were clearly separated among the three sites with different fire histories. The three replicates from each site clustered closely together indicating consistency of the biological replication. Overall, more than 90% of the detected genes probes were present in all samples. The minor remaining genes unique to each site suggested a low beta gene diversity in the study site. Notably, genes corresponding to nearly all major pathways of C (C degradation, C fixation and methane) and N (denitrification, nitrification, assimilatory and dissimilatory N reduction, N fixation and ammonification) were identified by GeoChip analysis, which might indicate large gene pool at all the sites irrespective the fire history. Microbial C cycling plays an important role in the forest ecosystem. The number of detected genes involved in C cycle was higher at the 2y site after the fire compared to older sites. Several genes (chitin, lignin, hemicellulose and pectin) involved in carbon degradation had higher signal intensity at the 2y site. Fire leads to the loss of readily degradable C and a corresponding decrease in soil moisture content38. The higher number and signal intensity of genes related to carbon degradation in recently burned sites might indicate that the potential for expression of carbohydrate-degrading enzymes was not affected or reduced despite the large reduction in C content caused by fire33. Nitrogen is typically the limiting nutrient in northern forest soils39. Wildfire can cause long-term changes in N-cycling40. The nifH gene encoding nitrogenase reductase has been used as molecular marker for N fixation for a wide range of heterotrophic bacteria41. After the fire, the N content was reduced in forest soil, but the relative abundances for genes involved in N fixation (nifH) were not significantly impacted by fire12. On the other hand, Yeager et al.42 found the number of dominant nifH sequence types was greater in fire-impacted soils and Cobo-Díaz et al.43 also showed that the burned rhizosphere showed increased number of nifH gene copies. In our study, the nifH gene had higher signal intensity and number of probes detected in recently burned site compared to older sites. We propose that this finding indicate N fixation is involved in the compensation for N loss from the soil after burning. Differences between young and older forests were observed in the gene probe number of the phosphorous cycling enzymes (Table 3). Fires are supposed to increase the availability of phosphorous due to mineralization7 and it seems that post-fire bacterial communities process the available phosphorous more actively. However, in litter bags analyzed at the same sites the phosphatases activities were higher in old sites44 which indicate that competitive replacement of bacteria by fungi affects also the function of bacterial communities. Altogether, the high activities of phosphorous cycling enzymes show that it is likely that early succession post-fire bacterial communities use actively the newly mineralized phosphorus. The redundancies in the genes represented in the array compromised our ability to detect functional differences. The profiles of gene probes at all sites are diverse as the majority of them are present in all sites. Only a few differences are due to the presence/absence of certain genes or their abundance. It is important to bear in mind that the DNA-based GeoChip array reflects only the functional potential of microbial communities, but does not allow conclusions on how these genes are expressed and to what extend the actual function of the microbial population differs. To validate the functional process and population, other in-depth analysis (e.g., RNA-based transcriptome and functional activity assays) are needed. Similarly, most of the functional genes involved in organic C and N degradation pathways in our study were present in all sites. The activity of these genes and the bacteria involved need to be further validated. In conclusion, the number of bacterial OTUs decreased over time since fire. However, fire did not show significant impact on bacterial diversity between 2- and 152-year after the fire. This observation differed clearly from the fungal diversity after fire at the same sites16. However, shifts in bacterial community structure and function among the sites with different fire histories were observed. Soil temperature, pH, water and C and N contents were the most important factors in shaping the bacterial community structures and function, suggesting that the fire-mediated changes in the soil biogeochemistry were strong drivers of the observed shifts in bacterial structure. Interestingly, the sites with different fire history formed separate bacterial gene clusters despite very long recovery time. This may indicate small differences in the potential to maintain essential biogeochemical processes in soil. This study provides functional insight on the impact of fire disturbance on soil bacterial community dynamics. Materials and Methods Study site and sample collection The study site was located in a northern boreal subarctic coniferous forest of the Värriö Strict Nature Reserve in northeastern Finland (N 67°46, E 29°35). The detailed information on the sites and the soil sampling have been previously described1633. Briefly, the site was dominated by Scots pine (Pinus sylvestris L.), with scattered downy birch (Betula pubescens Ehrh.) and Norway spruce (Picea abies (L.) Karst) trees. The ground vegetation consists mostly of bilberry (Vaccinium myrtillus L.), lingonberry (Vaccinium vitis-idaea (Lodd.) Hulten), black crowberry (Empetrum nigrum L.) and reindeer lichen (Cladina) species. The study was carried out at three sampling sites with different time since the last fire: 2 years (2y), 60 years (60y) and 152 years (152y) after fire (Table 2). The fire events on all the sites were not completely stand-replacing44. At each sampling site, two plots were chosen with a distance of 100 m. Five consecutive soil samples with distance of 4 m each plot were collected, resulting in 10 samples per site. The humus layer samples (0.5 to 1.0 cm thick) were collected from a 0.25 m by 0.25 m quadrat of soil at after removing the litter33. The samples were mixed well and transferred to 1.5-ml Eppendorf vials. The samples were frozen at −180 °C in liquid nitrogen within a few hours after collection and transported to the laboratory in dry ice for subsequent DNA isolation. Continuous soil temperature and soil water content measurements were taken from the same location at 15-min intervals in the field. Soil temperature was measured using silicon temperature sensors (Philips KTY81-110, Philips semiconductors, Eindhoven, the Netherlands) and water content was measured using soil moisture sensors (Thetaprobe ML2x, Delta-T De-vices Ltd., Cambridge, UK) connected to a datalogger (DataTaker DT80, Thermo Fisher Scientific Australia Pty Ltd., Victoria, Australia). 10 soil cores (100 mm in length and 50 mm in diameter) from the same locations in each of the sites were also collected and transferred to the lab for the measurement of soil pH, soil C and N content, and root biomass in humus layer. The analysis of the soil properties in the laboratory have been previously described and published by Köster et al.33 (Table 2). Briefly, the soil humus layers were separated from the soil cores. Soil pH (H2O) of the humus horizons was determined using a glass electrode to stir the soil suspensions in demineralized water with a ratio of 10 ml of sample and 25 ml of water. The soil C and N content of the soil (including roots less than 2 mm in diameter) was measured with an elemental analyzer (varioMAX CN elemental analyzer, Elementar Analysensysteme GmbH, Germany) after the soils were dried in an oven at 105 °C for 24 h, sieved through a 2-mm sieve and ground with a ball mill (Retsch, Han, Germany). The soil C and N stocks were calculated for humus layers based on soil C and N concentration of the fraction and bulk density, respectively. For root biomass analyses, both the understory and tree roots were separated from the soil by washing, and sorted into living and dead fractions based on elasticity and toughness. The roots were identified as Scots pine, birch or other broad-leaved species, and understory (mainly dwarf shrubs and grasses) roots and rhizomes based on microscopic morphology and color. The ergosterol was extracted from soil samples by cyclohexane and 10% KOH in methanol. The amount of ergosterol was measured with high-performance liquid chromatography (HPLC) (HP Agilent 1100, Hewlett Packard, USA) using a Kinetex 2.6u C18 100A reverse-phase column 75 × 4.6 mm (Phenomenex ApS, Allerød, Denmark). All samples were collected in mid of August 2011. DNA extraction, amplification of 16S rRNA gene, and Illumina MiSeq sequencing Genomic DNA was extracted from 0.25 g (fresh weight) homogenized humus soil sample using the PowerSoil DNA isolation kit (Mo Bio Laboratories, Carlsbad, CA, USA), according to the manufacturer’s instructions. The genomic DNA was purified using the Gene Clean Turbo kit (MPBiomedicals, LLC, France), quantified with Qubit 2.0 fluorometer (LifeTechnologies, Eugene, OR, USA), and adjusted to a final concentration of 10 ng μl−1. Three individual extracted DNA in each site were randomly pooled together, representing three biological replicates per site (9 samples in total) and used for further Illumina MiSeq sequencing and GeoChip 4.0 microarray. 16S region V1-V3 was amplified in a 2-step PCR using the primers pA and pD45 containing partial TruSeq adapter sequences at their 5′ end, ATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT and GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT, respectively. The first PCR was done in two replicate 25 μl reactions using Phusion Hot Start II polymerase (Thermo Fischer) and cycling conditions consisted of an initial denaturation step at 98 °C for 30 s, followed by 15 cycles at 98 °C for 10 s, 65 °C for 30 s, 72 °C for 10 s, and a final extension for 5 minutes. After PCR the two replicates were combined and treated with Exonuclease I (Thermo Scientific) and Thermosensitive Alkaline Phosphatase (FastAP; Thermo Scientific). A second PCR was performed with full-length TruSeq P5 and Index containing P7 adapters and 1–5 μl from the first PCR as template. Cycling conditions were similar to the first amplification but with 18 cycles and 50 μl reactions with no replicates. Final purification was performed with Agencourt AMPure XP magnetic beads from Agencourt Bioscience (Beckman Coulter Inc, MA, USA). DNA concentration and quality were verified with Qubit (Invitrogen) and Bioanalyzer 2100 (Agilent), respectively. The final PCR fragments were pooled in equal concentrations and run on a MiSeq Sequencer (Illumina) using v2 600 cycle kit paired-end (325 bp + 285 bp). Illumina MiSeq sequence data processing The sequence data were analyzed using the mothur standard operation pipeline (SOP, Version 1.31.2)46. Briefly, pair-end reads were combined to contigs with minimum overlap 25 bp. Data were pre-processed to reduce sequencing and PCR errors, remove poor quality sequences, and preclustered with a distance of 2 bp using a pseudosingle-linkage algorithm implemented in mothur to minimize sequences that contain pyrosequencing errors47. All potentially chimeric sequences were identified using the mothur-embedded UCHIME program48 and removed. Unique sequences were aligned against SILVA database using the Needleman method49. The aligned distance matrices were clustered into operational taxonomic units (OTUs) using the average neighbor algorithm and 97% sequence similarity. OTUs with one sequence (singleton) were not included in downstream analysis. The sequences were classified to taxa using the RDP Naïve Bayesian rRNA Classifier tool version 2.0 with an 80% bootstrap confidence thresh-old50 on the RDPII and filtered to exclude chloroplast, mitochondria, eukaryotic and unknown sequences. Bacterial richness was estimated by chao151 and diversity was assessed using Shannon indices (H′)52. To correct the difference in sample size, we used a randomly selected subset of 27 699 sequences per sample (minimum number of sequences recovered among all samples) to compare relative difference between samples. The OTUs were arbitrarily defined as ‘abundant’ when the relative abundances were above 0.1% and as ‘rare’ when the abundances below 0.1%. The analysis was done using mothur programme46. All sequence data are available through the European Bioinformatics Institute (EBI) with project accession number PRJEB12433. GeoChip hybridization and data processing GeoChip hybridization and data processing were carried out by following the protocol described previously16. Briefly, 100 ng of genomic DNA from the triplicates in each of the three sites was amplified by rolling circle amplification using the TempliPhi kit (GE Healthcare) and a modified protocol22. Approximately 2 μg of amplified genomic DNA was mixed with random primers (3 μg/μl random hexamers; Life Technologies) and then labeled with 15 μl of labeling master mix (2.5 μl of dNTP [5 mM dATP, dGTP, and dCTP and 2.5 mM dTTP], 0.5 μl of Cy-3 dUTP [25 nM; GE Healthcare], 1 μl of Klenow fragment [40 U m1−1; Imer, San Diego, CA], 5 μl of Klenow buffer, 2.5 μl of water)53. The labeled genomic DNA was purified using the QIAquick purification kit (Qiagen), according to the manufacturer’s instructions, and then dried in a SpeedVac at 45 °C for 45 min (Thermo Savant). Labeled genomic DNA was hybridized on the GeoChip 4.0 microarray, as previously described2153. The signal intensity of each spot was scored as positive and retained if the signal-to-noise ratio (SNR), calculated as (signal mean - background mean)/background standard deviation, was ≥2.0. Data normalization and pre-processing to remove poor quality spots (SNR < 2.0), normalization of the signal intensity of each spot based on the mean signal intensity across all genes on the arrays and transformation of the data using the natural logarithmic form were carried out as described previously21. The normalized signal intensities per gene were calculated as the sum of intensities of the probes per gene, divided by the total number of the probes detected in each gene, and averaged across the three replicates per sample54. Statistical analysis The bacterial OTUs were defined as the abundant OTUs (>0.1% relative abundance) and rare OTUs (<0.1% relative abundance). One-way ANOVA tests (Non-parametric Kruskall-Wallis) with Hodges-Lehmann estimate were used to identify differences in diversity and species richness between sites with different fire histories. The individual OTUs (Table S1) and gene categories (Table S4) that differ quantitatively between sites were also tested by ANOVA analysis. The bacterial community and gene structure was visualized as Principle Coordinate Analysis (PCoA) plot with Bray Curtis similarity using relative abundances of OTUs or normalized gene intensity in PRIMER v.6 34 with the add-on package of PERMANOVA+55. Prior to PCoA analysis the data were square root transformed to meet PCoA criteria. A PERMANOVA test was used to assess the significant difference in community structure between sites with different fire histories. The process and functions used for the Geochip analysis were performed in the R56 gplots package57 for hierarchical cluster analysis (HCA). The gene diversity of each sample was estimated using Shannon’s index (H′). To determine which environmental parameter (i.e. water content, soil pH, soil temperature, soil C and soil N) could significantly partition the variation in bacterial community and gene structure, a Distance Based Linear Model (DISTLM) analysis was used after PERMDISP procedure, and its significance was assessed by PERMANOVA (analysis of similarities; 999 Monte Carlo permutation tests). The values of the environmental parameters corresponding to each DNA samples (3 samples) in each site were calculated as average of the value of the three pooled subsamples, which was matching to each of the three DNA samples per site (Table 2). Additional Information How to cite this article: Sun, H. et al. Bacterial community structure and function shift across a northern boreal forest fire chronosequence. Sci. Rep. 6, 32411; doi: 10.1038/srep32411 (2016). Supplementary Material Supplementary Information This research was supported by grants from the Academy of Finland (project no. 1286685, 263858, 130984, 218094, and 255576), ICOS project (grants ICOS 271878, ICOS-Finland 281255, and ICOS-ERIC 281250), the Estonian Research Council grant (PUT715), the Research Funds of the University of Helsinki (grant 490127), the research funding for Jiangsu Specially-Appointed Professor (project 165010015) and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). In addition, this study was part of the Academy of Finland Finnish Centre of Excellence program (project 1118615), Academy of Finland FiDiPro (project no. 138116) and the European Social Fund and Estonia Research Council grant Mobilitas (MJD94). Author Contributions J.P. and J.H. designed the study. K.K. and F.B. collected the samples in the field and provided the soil property data. H.S. and M.S. performed the molecular work in the lab. T.R. and F.O.A. performed the Geochip data analysis. H.S. performed all other data analysis and wrote the manuscript. All authors contributed to review the manuscript. Figure 1 Venn diagram showing the unique and shared OTUs from MiSeq sequencing (a), and presence/absence of functional genes identified by GeoChip (b) between the three burned sites. A total of 3 692 OTUs and 748 genes were detected across the three sites, respectively. Abbreviation: 2y: 2-year after fire; 60y: 60-year after fire; 152y: 152-year after fire. Figure 2 Principle Coordinate Analysis (PCoA) plot (environmental variables as vectors) showing differences in bacterial community structure (a) and gene structure (b) with time since fire. Figure 3 Bar chart showing the phylum-level assignment for operational taxonomic units (OTUs) from three sites differing in fire histories as the relative proportions of OTUs and sequence reads. Figure 4 Hierarchical cluster analysis of functional gene probes in the three sites differing in fire histories based on the signal intensity of detected probes. The numbers after the site name represent replicates 1 to 3 at each site. Figure 5 Normalized average signal intensity of genes involved in carbon cycling (a,b), nitrogen cycling (c) and phosphorus cycling (d) showing significant difference between sites. Data were presented as the mean ± standard deviation. The bars represent the standard deviations, and different letters in each panel represent Tukey’s significance at a P value of 0.05. Table 1 Bacterial richness and diversity index for 16S region libraries in the soil from each site after fire. Years after fire No. of Sequencesa OTUs coverage (%) Normalizationb Observed OTUs Estimated OTUs Shannon Shannon evenness 2 39762 ± 3799 0.98 1641 ± 34c 2369 ± 54c 5.2 ± 0.2c 0.69 ± 0.03c 60 32269 ± 1974 0.98 1524 ± 124d 2027 ± 138d 5.3 ± 0.1c 0.72 ± 0.01c 152 32069 ± 4704 0.99 1195 ± 112e 1728 ± 153e 4.8 ± 0.2c 0.67 ± 0.01c aAverage number of sequence obtained from the three replicates in each site with standard deviation. bData were calculated at 3% genetic distance level with standard deviation based on the same number of sequences from each replicate (27699/sample) in Mothur. OTUs containing singleton sequence were discarded. Different letters (c, d and e) in each column represent significant difference level at 0.05 between each site. Table 2 The description of fire age characteristics and soil properties of the study sitesa. Age Replicate Soil textural classification Tree species composition (%) Age of the treesb Year of last fire Trees/ha Soil pH (humus layer) Soil temperature (growing season) (°C) Soil gravimetric water content (%) SoilN (g m−2) SoilC (C g m−2) TRootBiom (kg m−2) Ergosterol (μg g−1SOM) 2y 1 Loamy sand 92 Pi, 8 Bi 35/40/258 2009 1550 4.0 (±0.08) 11.3 (±0.0) 34 (±3.2) 53.988 (±14.87) 1364.730 (±377.59) 0.340 (±0.00) 219.821 (±13.78) 2 Loamy sand 95 Pi, 5 Bi 21/52/143 2009 900 4.1 (±0.10) 11.6 (±0.0) 37 (±2.2) 38.791 (±3.56) 1596.566 (±93.29) 0.301 (±0.007) 217.972 (±7.24) 3 Loamy sand 96 Pi, 5 Bi 25/42/144 2009 950 4.1 ( (±0.10) 11.3 (±0.0) 34 (±2.0) 40.857 (±11.98) 1531.788 (±104.87) 0.223 (±0.00) 222.433 (±2.36) 60y 1 Loamy sand 95 Pi, 5 Bi 43/61/155 1951 625 3.8 (±0.21) 10.8 (±0.0) 49 (±4.9) 61.635 (±20.05) 2227.050 (±286.91) 0.236 (±0.00) 279.935 (±28.88) 2 Loamy sand 99 Pi, 1 Bi 43/61/169 1951 1150 3.8 (±0.13) 10.6 (±0.0) 50 (±6.4) 70.751 (±27.83) 2518.135 (±99.71) 0.260 (±0.04) 265.077 (±31.20) 3 Loamy sand 97 Pi, 2 Bi 43/60/170 1951 710 3.8 (±0.15) 10.8 (±0.0) 51 (±5.4) 78.475 (±9.82) 2092.943 (±294.64) 0.307 (±0.00) 255.367 (±6.55) 152y 1 Loamy sand 96 Pi, 4 Bi 104/150/272 1859 200 3.7 (±0.17) 10.4 (±0.0) 57 (±4.2) 53.299 (±4.31) 2252.368 (±42.69) 0.292 (±0.00) 268.976 (±18.47) 2 Loamy sand 98Pi, 2 Bi 84/150/341 1859 225 3.8 (±0.11) 10.5 (±0.0) 56 (±4.9) 63.466 (±8.57) 2670.151 (±66.80) 0.318 (±0.05) 276.662 (±13.86) 3 Loamy sand 98Pi, 2 Bi 90/145/310 1859 211 3.7 (±0.14) 10.4 (±0.0) 57 (±4.5) 62.396 (±3.57) 2590.029 (±28.43) 0.371 (±0.00) 304.662 (±25.49) aAll the data were derived from Köster et al.33. bRepresenting the age of youngest living tree/average age of the stand/oldest living tree on the study site. Pi — Scots pine, Bi — Birch. Standard errors of the means are in parentheses (n = 3). Table 3 Number of gene probes detected in each gene category from the sites with different fire histories. Gene category No. of gene probe detected (mean ± SD)a No. of gene probe in each category 2-year after fire 60-year after frie 152-year after fire Carbon Cycling 7710 ± 53b 6986 ± 346c 7439 ± 90bc 9443 Electron transfer 302 ± 6b 267 ± 12c 289 ± 4bc 382 Metal Homeostasis 14093 ± 125b 12653 ± 771c 13385 ± 147bc 17208 Nitrogen 2109 ± 9b 1895 ± 99c 2039 ± 26bc 2592 Organic Remediation 4601 ± 42b 4200 ± 199c 4467 ± 21bc 5571 Phosphorus 1168 ± 7b 1085 ± 58c 1121 ± 8bc 1430 Secondary metabolism 1262 ± 11b 1170 ± 52c 1224 ± 15bc 1479 Stress 8515 ± 72b 7703 ± 415c 8183 ± 119bc 10439 Sulfur 1395 ± 13b 1261 ± 81c 1348 ± 12bc 1748 virulence 7939 ± 95b 7339 ± 319c 7627 ± 73bc 9415 Other 2488 ± 18b 2239 ± 141c 2343 ± 44bc 3153 Total 51582 ± 432b 46800 ± 2487c 49465 ± 539bc 62860 aThe values represent the mean and standard deviation of three replicates from each age after fire. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3239510.1038/srep32395ArticleIntroducing Mg-4Zn-3Gd-1Ca/ZnO nanocomposite with compressive strengths matching/exceeding that of mild steel Chen Y. 1Tekumalla S. 1Guo Y. B. 1Gupta M. a11 Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576, Singapore.a mpegm@nus.edu.sg30 08 2016 2016 6 3239527 06 2016 08 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/This work introduces Mg-4Zn-3Gd-1Ca/2ZnO (wt.%) nanocomposite fabricated using the technique of disintegrated melt deposition and extrusion. Addition of ZnO nanoparticles enhanced the compressive strengths of alloy by ~100 MPa. Nanocomposite samples display high strength and good ductility: 0.2% compressive yield stress of 355 MPa, ultimate compressive stress of 703 MPa, and compressive failure strain of 10.6%. The significant enhancement of compressive yield stress is mainly attributed to the grain refinement by adding nanoparticles. The strength levels exceed that of commercial magnesium alloys (i.e. WE43, WE54, ZK60, and ME21) and mild steels (i.e. S275 and S355), making Mg-4Zn-3Gd-1Ca/2ZnO a very promising material for multiple engineering and biomedical applications. ==== Body Magnesium is the lightest structural metal – only two thirds the density of aluminum. The light weight of Mg and its alloys endows them with tremendous potential for weight reduction in transportation sector including reduction in green house emission and energy consumption. However, the low strength and poor ductility at room temperature of Mg alloys hinder their engineering applications. Adding rare earth (RE) elements into Mg is one effective way to improve mechanical properties1. The extruded alloy Mg-1Zn-2.5Gd (at.%) reported by Yamasaki et al.2 exhibited a good balance of tensile yield strength (345 MPa) and elongation (6.9%) due to refined grains and well dispersed long period stacking ordered (LPSO) phase. Rolled Mg-1Zn-Gd (2 and 3 wt.% for Gd) sheet studied by Wu et al.3 displayed a high tensile failure strain (~50%) as a result of texture weakening by adding Gd. Addition of Ca element into Mg alloys can also improve strength effectively through grain refinement. Extruded Mg-5.25Zn-0.6Ca (wt.%) alloys presented by Tong et al.4 and Mg-1.8Zn-0.3Ca (at.%) presented by Somekawa and Mukai5 showed good tensile yield strength (~300MPa) with ultrafine grains. Recently, work done by Wen et al.6 showed that with increasing the amount of Ca element (0–1 wt.%), the ultimate tensile strength of extruded Mg-4Zn-2Gd-Ca alloys increased. With increase of Gd addition (0–2.52 wt.%), the creep properties of as-cast Mg-3.8Zn-2.2Ca-Gd alloys were improved7. However, reports on alloy Mg-Zn-Gd-Ca and compressive properties are extremely limited4. Addition of nano-size reinforcements to Mg alloys is another effective way to improve the mechanical properties beyond that of alloying elements. Studies by Nguyen et al.8 and Chen et al.9 demonstrated that addition of Al2O3 nanoparticles into AZ31 improved tensile ductility and strength simultaneously, while the compressive strength was also enhanced. Similar results were reported for adding ZnO nanoparticles to Mg matrix10. In literature, some studies1112 estimated that the transition from twinning to slip may happen when the grain size of magnesium alloy is smaller than 3 μm. However, the results from work by Li et al.13 for AZ60 with grain size of 0.8 μm and work by Chen et al.14 for AZ31-based nanocomposite with grain size of 1.5 μm, showed that tension twinning remained the predominant deformation mode for the initial plastic flow under uniaxial compression. Results that are available in open literature remain contradictory. Thus, it needs further research work. Accordingly, the present study investigates the effect of addition of ZnO nanoparticles in a new Mg-Zn-Gd-Ca alloy emphasizing particularly on the compressive response. Results Compressive mechanical properties and microstructure Figure 1(a) shows typical engineering stress-strain plots of three materials subjected to quasi-static compression. Compressive mechanical properties and grain size of three materials studied are given in Table 1. Compared to pure Mg, the alloy Mg4Zn3Gd1Ca exhibits high strength and good ductility: 0.2% compressive yield stress σYS of 260 MPa, ultimate compressive stress σUCS of 585 MPa and failure strain εFS of 12.6%. The 0.2% compressive yield stress of the alloy is almost 3.5 times that of pure Mg. Furthermore, addition of 2 wt.% ZnO nanoparticle into the alloy enhanced the strength by ~100 MPa; σYS of 355 MPa, σUCS of 703 MPa were obtained. In addition, failure strain of the nanocomposite is 10.6%, only slightly lesser than that of the alloy. It indicates that addition of nanoparticles can maintain the ductility of the alloy, while it increases strength significantly. Figure 2 presents the comparison of compressive mechanical properties of the materials in this study and the extruded Mg alloys in literature; Table 1 gives the corresponding specific values. The compressive yield stress of mild steel S275 and S355 is also given in Table 1. It is evident that with a comparable elongation, the nanocomposite Mg4Zn3Gd1Ca-2ZnO exhibits significant higher strength than other extruded Mg alloys shown in Fig. 2, and the compressive yield strength levels either matches or surpasses that of mild steel. Compared to pure Mg, significant grain refinement was observed in the alloy Mg4Zn3Gd1Ca. The grain size reduces from 24. 6 μm for Mg to 1.42 μm for the alloy. Further reduction of grain size was achieved by addition of ZnO nanoparticle – grain size of the nanocomposite is ~0.9 μm, ~60% that of the alloy, as shown in Fig. 1(b). XRD results Two types of specimens of three materials – before compression and after yielding (at a strain of 2%) – were subjected to XRD scanning. The results for the nanocomposite are given in Fig. 3. In Fig. 3(a), corresponding to the basal plane (0002), the highest density peak is observed for scanning along the extrusion direction and the negligible density peak for scanning perpendicular to the extrusion direction. This indicates that specimens of the nanocomposite have a typical basal texture, as commonly observed for the extruded magnesium-based material. In Fig. 3(b), after yielding (at a strain of 2%), significant increment of peak density for the basal plane (0002) is observed for scanning perpendicular to the extrusion direction. This is attributed to activation of tension twinning, because this twinning mode can rotate the grain lattice by ~90o. The fraction of basal plane perpendicular to the extrusion direction can be expected to increase with activation of this twinning mode. In addition, the low strain hardening for the initial plastic flow, as highlighted by the circle in Fig. 1, also indicates the activation of tension twinning. Therefore, although the nanocomposite has ultrafine grains (~0.9 μm), tension twinning still plays a dominant role in the initial stage of plastic flow. Similar XRD results were obtained for the alloy and pure Mg. For brevity, these XRD spectrums are not presented. Discussion The well-known Hall-Petch relation19 defines the relationship between grain size and yield stress for polycrystalline materials as follows: where σ is the 0.2% yield stress; σ0 is a material constant, k the strengthening coefficient and d is the grain size. Figure 4 shows the relationship of σ and d−1/2 for Mg-based materials. All materials in the figure were fabricated by DMD method and extruded with the same extrusion ratio (20.25:1). The red marks, from the left bottom corner to the right up corner, denote respectively: pure Mg, Mg reinforced with ZnO nanoparticles10, Mg added with alloying elements – Zn and Gd20, Mg added with alloying elements – Zn, Gd and Ca, and Mg containing both alloying elements – Zn, Gd and Ca, and ZnO nanoparticles. All the data fitted very well into a linear line because the value of fitting parameter R-square is 0.97. In Fig. 4, several salient points can be noted: (1) significant enhancement (~100 MPa) of yield stress by addition of ZnO nanoparticles is mainly due to grain refinement; (2) as discussed for Fig. 3, when the grain size reduces to 0.9 μm, tension twinning still plays a predominant role for yield stress. That is to say, the activation stress of tension twinning follows Hall-Petch relation even when the grain is significantly refined; (3) the blue squares in Fig. 4 denote results for Mg Alloy AZ31 and its nanocomposites14, which is reinforced by Al2O3 nanoparticles. It is apparent that the yield stress of these materials follows Hall-Petch relation, as indicated by the blue linear fitting line. However, the slope (or the strengthening coefficient k) of the blue line is much smaller than that of the red line. It means that the combination of alloy elements – Zn and Gd, generates much higher slope than that of Zn and Al. This notable contrast demonstrates that alloying elements display varied strengthening effect on the activation stress of tension twinning. The fundamental mechanism for the discrepancy needs further investigation. In summary, an alloy Mg4Zn3Gd1Ca and its nanocomposite Mg4Zn3Gd1Ca-2ZnO were synthesized by DMD method followed by hot extrusion. Addition of 2 wt.% ZnO nanoparticles into the alloy generates significant strength enhancement – i.e. ~100 MPa, and maintains good ductility; σYS of 355 MPa, σUCS of 703 MPa and εFS of 10.6% were obtained. Significant increment in strength by adding ZnO nanoparticles is mainly attributed to its grain refinement effect. The XRD results and compressive stress-strain curves demonstrate that at initial stage of plastic flow, tension twinning plays a predominant role for the ultrafine-grained nanocomposite. Superior-performance nanocomposite presented in this study has the capability to replace commercial magnesium alloys and certain mild steels when compressive strength is the material selection criterion. Methods Materials synthesis An alloy Mg-4Zn-3Gd-1Ca (wt.%) and its nanocomposite Mg-4Zn-3Gd-1Ca-2ZnO (ZnO nanoparticle with diameters in 90–200 nm) were synthesized by a disintegrated melt deposition (DMD) technique9, which includes melting, mixing, disintegrating and deposition steps. Pure Mg, as a reference, was synthesized using the same technique. The cast ingots with 36 mm in diameter and 45 mm in length were homogenized at 400 °C for 4 hours and extruded at 300 °C into 8 mm diameter rods. Mechanical testing and microstructure characterization The 6 mm diameter cylinder specimens with a length-to-diameter ratio of 1, were prepared for room temperature uniaxial compression tests at a strain rate of 5 × 10−3 s−1, using an Instron 8874 universal testing machine. An extensometer was used to measure plastic deformation. Three specimens were tested for each material. The microstructures of three materials were observed using an Olympus optical microscope and a field emission scanning electron microscope (FESEM). X-ray diffraction (XRD) analysis was carried out on specimens before compression and after yielding, using an automated Shimadzu Lab-X XRD-6000 diffractometer (Cu Kα, λ = 1.54056 Ǻ) operating at a scanning speed of 2 deg/min. The specimens were etched with a mixture of 1 g oxalic, 1 ml nitric acid, 1 ml acetic acid and 150 ml distilled water. Additional Information How to cite this article: Chen, Y. et al. Introducing Mg-4Zn-3Gd-1Ca/ZnO nanocomposite with compressive strengths matching/exceeding that of mild steel. Sci. Rep. 6, 32395; doi: 10.1038/srep32395 (2016). The financial support of Singapore Ministry of Education Academic Research Funding (WBS# R-265-000-498-112) is gratefully acknowledged. Author Contributions S.T. and Y.C. fabricated the materials and did microstructure observation under supervision of M.G. XRD testing was done by Y.C.; sample fabrication and mechanical testing were conducted by Y.B.G. and Y.C., and supervised by M.G. All authors commented on the manuscript. Figure 1 Mechanical properties and grain morphology. (a) Engineering stress-strain curves for compression on three materials; (b) FESEM image for grain morphology of the nanocomposite. Figure 2 Comparison of compressive properties of the materials in this study and in literature. (a) Compressive yield stress against elongation; (b) ultimate compressive stress against elongation. Figure 3 X-ray diffraction patterns of the nanocomposite. (a) Before compression; (b) after yielding (at a strain of 2%). (ED: extrusion direction). Figure 4 Hall-Petch Relation. Plots of compressive yield stress against inverse of square root of grain size for Mg-based materials synthesized by DMD method. Table 1 Compressive mechanical properties and grain size of three materials in this study and other materials in literature. Materials Compressive yieldstress (MPa) UCS (MPa) FS (%) Grain size (μm) Mg 75.2 ± 3.6 335.4 ± 13.8 25.6 ± 2.2 24.6 ± 4.0 Mg4Zn3Gd1Ca 260.5 ± 2.9 585.4 ± 18.9 12.6 ± 0.3 1.42 ± 0.20 Mg4Zn3Gd1Ca-ZnO 355.4 ± 5.0 703.4 ± 39.8 10.6 ± 0.4 0.91 ± 0.47 ME2115 (extruded) 87 260 25 NR ZK6016 (extruded) 159 472 12.4 NR WE4317 (extruded) 183 305 11.3 NR WE5415 (extruded) 210 325 27 NR S27518 (≤16 mm plate) 275 NR NR NR S35518 (≤16 mm plate) 355 NR NR NR *NR denotes not reported. ==== Refs Emley E. F. Principles of magnesium technology . (Oxford, New York, Pergamon Press, 1966 ). Yamasaki M. , Anan T. , Yoshimoto S. & Kawamura Y. Mechanical properties of warm-extruded Mg-Zn-Gd alloy with coherent 14H long periodic stacking ordered structure precipitate . Scr. Mater . 53 , 799 –803 (2005 ). Wu D. , Chen R. S. & Han E. H. Excellent room-temperature ductility and formability of rolled Mg-Gd-Zn alloy sheets . J. Alloys Compd. 509 , 2856 –2863 (2011 ). Tong L. B. et al. Room-temperature compressive deformation behavior of Mg-Zn-Ca alloy processed by equal channel angular pressing . Mater. Sci. Eng. A 528 , 672 –679 (2010 ). Somekawa H. & Mukai T. High strength and fracture toughness balance on the extruded Mg-Ca-Zn alloy . Mater. Sci. Eng. A 459 , 366 –370 (2007 ). Wen Q. , Deng K. K. , Shi J. Y. , Zhang B. P. & Liang W. Effect of Ca addition on the microstructure and tensile properties of Mg-4.0Zn-2.0Gd alloys . Mater. Sci. Eng. A 609 , 1 –6 (2014 ). Yang M. , Guo T. & Li H. Effects of Gd addition on as-cast microstructure, tensile and creep properties of Mg-3.8 Zn-2.2Ca (wt%) magnesium alloy . Mater. Sci. Eng. A 587 , 132 –142 (2013 ). Nguyen Q. & Gupta M. Enhancing compressive response of AZ31B magnesium alloy using alumina nanoparticulates . Compos. Sci. Technol . 68 , 2185 –2192 (2008 ). Chen Y. , Guo Y. B. , Gupta M. & Shim V. P. W. Dynamic tensile response of magnesium nanocomposites and the effect of nanoparticles . Mater. Sci. Eng. A 582 , 359 –367 (2013 ). Sankaranarayanan S. et al. Nano-ZnO particle addition to monolithic magnesium for enhanced tensile and compressive response . J. Alloys Compd. 615 , 211 –219 (2014 ). Meyers M. A. , Vohringer O. & Lubarda V. A. The onset of twinning in metals: a constitutive description . Acta Mater 49 , 4025 –4039 (2001 ). Yang Q. & Ghosh a. K. Deformation behavior of ultrafine-grain (UFG) AZ31B Mg alloy at room temperature . Acta Mater . 54 , 5159 –5170 (2006 ). Li B. et al. Rate-dependent hardening due to twinning in an ultrafine-grained magnesium alloy . Acta Mater . 60 , 1818 –1826 (2012 ). Chen Y. , Guo Y. B. , Gupta M. & Shim V. P. W. A study of the dynamic compressive response of AZ31/Al2O3 nanocomposites and the influence of nanoparticles . Int. J. Impact Eng. 89 , 114 –123 (2016 ). Lentz M. et al. Analysis of the Deformation Behavior of Magnesium-Rare Earth Alloys Mg-2 pct Mn-1 pct Rare Earth and Mg-5 pct Y-4 pct Rare Earth by In Situ Energy-Dispersive X-ray Synchrotron Diffraction and Elasto-Plastic Self-Consistent Modeling . Metall. Mater. Trans. A 45 , 5721 –5735 (2014 ). Xiong Y. , Yu Q. & Jiang Y. An experimental study of cyclic plastic deformation of extruded ZK60 magnesium alloy under uniaxial loading at room temperature . Int. J. Plast . 53 , 107 –124 (2014 ). Available at: http://www.magnesium-elektron.com/sites/default/files/Elektron-43-Extruded Products.pdf. EN10025:2004 European Hot-Rolled Structural Steel Standard (2004). Petch N. J. The Cleavage Strength of Polycrystals . J. Iron Steel Inst 174 , 25 –28 (1953 ). Seetharaman S. et al. Microstructure And Mechanical Properties New Magnesium- Zinc-Gadolinium Alloys . Magnes. Technol . 2016 159 –163 doi: 10.1002/9781119274803.ch32 (2016 ).

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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3237610.1038/srep32376ArticleThe use of Haemostatic Agents does not impact the rate of hemorrhagic complications in patients undergoing partial nephrectomy for renal masses Abu-Ghanem Yasmin a12Dotan Zohar 12Kaver Issac 12Zilberman Dorit E. 12Ramon Jacob 121 Dept. of Urology, Sheba Medical Center, Israel2 Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israea ag.yasmin@gmail.com30 08 2016 2016 6 3237630 03 2016 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Hemostatic agents(HAs) have gained increasing popularity as interventions to improve perioperative haemostasis and diminish the need for allogeneic red cell transfusion(PBT) despite a paucity of data supporting the practice. The aim of the current study is to examine the efficacy of HAs in reducing the rate of hemorrhagic complications during partial nephrectomy(PN). Data on 657 patients, who underwent elective PN between 2004–2013, were analyzed. The impact of HAs and SURGICEL was evaluated by comparing four sequential groups of patients: Group1 = Sutures alone, Group2 = sutures and HA, Group3 = sutures and SURGICEL, Group4 = both HA and SURGICEL. Complications included post-operative urinary leak(UL), PBT rate, delayed bleeding and post-operative renal failure. Results showed that the use of HAs did not engender a statistically significant difference in overall complications rate. Specifically, the addition of HAs did not reduce the rate of PBT, delayed bleeding or UL. Further analysis revealed that patients who received SURGICEL had significantly higher PBT rate and higher prevalence of UL cases. Addition of HAs to SURGICEL had no effect on the rate of these complications. In the current study, the use of HAs during open and laparoscopic PN did not reduce the rate of negative outcomes. Adequate suture renorrhaphy may be sufficient to prevent hemorrhagic complications. ==== Body In recent years, partial nephrectomy (PN), and specifically laparoscopic PN (LPN) has become the standard of care in the management of selected renal lesions1. Initially, LPN was proffered only in the case of a small, peripheral, exophytic tumor. However, with increasing experience, the application of LPN has extended to tumors invading more deeply into the renal parenchyma up to the collecting system or renal sinus23. Nevertheless, as laparoscopic surgeons approach more difficult tumors, the complexity of tumors requiring Open PN (OPN) is even further magnified. In both approaches, the excision of such deeply infiltrating tumors routinely necessitates division of major intrarenal vessels and precise entry into the collecting system to ensure an adequate margin of resection. Such resections are therefore associated with significant risks of bleeding and urinary leak3. Despite the relatively low incidences of hemorrhagic complications requiring transfusion after PN, it remains one of the most serious complications4. With many reports suggesting that allogeneic blood transfusion is associated with an adverse outcome567, several attempts have been made to reduce the risk of bleeding. In the past decades, a wide variety of haemostatic agents (HAs) has been developed as surgical tools, in order to reduce the rate of such complications. Different tissue adhesives (also called glues) have been used to assist in haemostasis and collecting system closure during open and laparoscopic PN289101112. Yet, despite the growing clinical application of HA during PN, there is little data regarding their cost-effectiveness in preventing major complications13. In this study, we present an analysis of the effectiveness of using HAs and glues in laparoscopic and open PN. Patients and Methods A total of 657 consecutive patients underwent PN at our institution between 2004 and 2013. All operations were performed in the same surgical environment (four surgeons operating in one medical center). Patient demographics and surgical details were collected retrospectively, following an approval given by the Sheba Medical Center Institutional Review Board (IRB)/Ethics (Helsinki) Committee, in accordance with relevant guidelines and regulations. The need for informed consent was waived by our IRB. All patients were considered for a comparative study, and four groups were defined on the basis of the method of haemostasis used during the procedure. Group 1 = renorrhaphy was completed using sutures alone in 147 patients (22.4%); Group 2 = both sutures and HA were used in 26 patients (3.9%); group 3 = sutures and SURGICEL (Ethicon, Somerville, NJ, USA), without HA in 183 (27.8%) patients; and group 4 = sutures, HA and SURGICEL in 301 (45.8%) patients. Altogether, 327 patients received HA (with or without SURGICEL). Of those, 290 (88.6%) received cryoprecipitate, prepared from a single allogeneic donor, combined with commercially prepared thrombin. The remaining patients received commercial sealants (bovine serum albumin–based adhesive, BioGlue; Kennesaw, GA, USA). In all cases, HA were used by covering the renal injury immediately after performing sutured renorrhaphy. Patient demographics and operative details were collected retrospectively. Clinicopathologic variables recorded included: age, gender, height, weight and Body Mass Index (BMI), preoperative hemoglobin and creatinine levels, receipt of perioperative blood transfusion (PBT) and number of units transfused. Pathology related variables included: tumor location, multifocal mass, central or hilar tumor, mass size, as well as tumor pathology- malignant tumor (i.e, Renal Cell Carcinoma (RCC), malignancies other than RCC were excluded) and benign lesion (AML, Oncocytoma, benign cyst). Other pathological features as Adrenal Invasion and Perinephric Fat Extension were documented in less than 2% of the patients and therefore were not included. Operative variables included the type of operation (open or laparoscopic), renal ischemia (clamping of the renal artery, Yes/No) and ischemia time data. Complications included post-operative urinary leak, delayed bleeding (hematuria or flank hematoma), post-operative renal failure, development of pseudoaneurysm and PBT administration. PBT was defined as transfusion of allogeneic red blood on the day of operation or within the postoperative hospitalization. Post-operative renal failure was defined by any increase in serum creatinine of ≥1.5-fold from the pre-operative baseline. Statistical analysis was performed using Statistical Package for Social Sciences (SPSS, Version 18.0, Chicago, IL, USA). One-way ANOVA was used for analysis of continuous variables and the chi-square test was used for analysis of categorical variables. A P-value of less than 0.05 was considered statistically significant. Result Six hundred and fifty seven patients underwent partial nephrectomy during the study period. Table 1 lists baseline demographics for the entire study cohort. Of the 657 patients, 87 patients (13.3%) received perioperative blood transfusion. The median number of RBC units was 2. Urinary leak was observed in 17 patients (2.6%). Sutures alone vs Sutures and HA The demographic data of the two groups were comparable in terms of age, gender, Body Mass Index (BMI), kidney side, tumor location along the kidney (i.e, upper or lower pole) and tumor size. Both groups had a similar number of patients with central and hilar tumors, rate of malignant tumors (RCC) and similar proportion of patients undergoing renal artery clamping. The use of a HA did not show a statistically significant difference in warm ischemia time (14.5 vs 19.7 minutes, p =C NS). Furthermore, overall complications did not differ between groups. Specifically, addition of HA did not reduce the rate of PBT (4.1% vs 7.7%, p = NS), delayed bleeding or flank hematomas (2 patients in HAs group and 5 in the parallel group, p = NS). No case of pseudoaneurysm was recorded in any of the patients receiving HAs in comparison to only one case in the parallel group (p = NS). No differences were observed in the rate of post-operative renal failure (Table 2). Sutures alone vs Sutures and SURGICEL Univariate analysis revealed that the two groups were comparable in age, gender, BMI, preoperative HB levels and rate of RCC. However, patients who received SURGICEL had significantly larger tumors in comparison to sutures alone (3.8 cm and 3.08 cm respectively, p = 0.03), higher rate of central renal lesions (43.2% vs 23.8%, p < 0.001) and lower rate of renal vascular clamping (69.5% vs 85.5%, p = 0.004). The majority of patients in the SURGICEL group were operated upon by an open approach (89.6% vs 36.7%, p = 0.001). In regards to complications, analysis of these sub-groups revealed that patients in the SURGICEL group had significantly higher PBT rate (p < 0.001) and higher prevalence of urinary leak cases (p < 0.05). No differences were observed in regards to delayed bleeding (including hematuria or flank hematoma). Notably, a higher incidence rate of pseudoaneurysm events was recorded in the SURGICEL group in comparison to sutures alone (3.3% vs 0.7% respectively, p = NS). No differences were observed in the rate of post-operative renal failure (Table 2). Sutures, HA and SURGICEL vs Sutures and SURGICEL The two groups were comparable in age, gender, BMI, preoperative HB levels and rate of RCC. The group of patients who received HA in addition to SURGICEL had significantly smaller tumors in comparison to the ‘HA free’ patients (3.21 and 3.8 cm respectively, P = 0.001), lower prevalence of central renal lesions (P = 0.03) and higher rate of renal vascular clamping (P = 0.001). The majority of patients in this group were operated upon by a laparoscopic approach. The addition of HA to SURGICEL did not show a statistically significant difference in the rate of PBT (14.6% and 19.1%, P = NS), the prevalence of urinary leak (2.3% and 4.9%, P = NS) or the rate of delayed bleeding including the rate of hematuria, flank hematomas and pseudoaneurysms. Additionally, no differences were observed in the rate of post-operative renal failure (Table 3). Analysis based on surgical approach (Open vs. Laparoscopic) In subgroup analysis of the laparoscopic approach alone, the two groups of patients were similar in all clinicopathological variables, including mass size, prevalence of central tumors, tumor location and rate of RCC. The only different variable was rate of renal vascular clamping. The majority of patients who received both SURGICEL and HAs, had significantly higher rate of clamping in comparison to SURGICEL alone (88.6% vs 52.6%, P = 0.001), yet no differences were observed in ischemia time. Comparison of the complication rate did not reveal any advantage to the addition of HA to SURGICEL in regards to PBT rate or post-operative bleeding. However, in the laparoscopic group, the addition of HA to SURGICEL decreased significantly the rate of leaks requiring stent insertion (P = 0.002). Yet, no advantage to HAs in comparison to sutures alone in regards to hemorrhagic complications (including rate of PBT) or the rate of urinary leak was found (Table 4). Similar results were observed when clinical features and outcomes were compared in patients operated upon by an open approach. Since the number of patients in the ‘Sutures and HA’ group that were operated by an open approach was too small (n = 5), this group was not compared to sutures alone (Table 5). Further analysis of the complication rate only in patients in which renal artery clamping was not performed revealed no advantage in the use of HA, both in comparison to sutures alone or sutures combined with SURGICEL. Cryoprecipitate Thrombin vs commercially prepared sealants This Study included 263 patients treated with Cryoprecipitate thrombin and SURGICEL whereas 38 were treated with both commercial HA and SURGICEL. No differences were found in regards to PBT rate or incidence of urinary leak between the 2 groups. Patients were further divided based on the type of HA used. Eighteen patients were treated with Cryoprecipitate thrombin alone and 8 with commercial sealants. No differences were observed in regards to PBT rate or incidence of urinary leak between the 2 groups. Discussion The use of tissue sealants and glues as HAs while operating or in the operation of PN has gained popularity. However, despite their growing clinical application, their significance in preventing hemorrhage and urinary leak is not evidence based and the decision of using it depends mainly on individual experience. In 2007, Breda et al.13, reported the results of a large multi-institutional survey, examining the usage patterns of HAs in LPN. The study included 18 centers from Europe and the United States in 1347 LPN cases. Breda and colleagues demonstrated, that up to 80% of urologists used the assistance of one or more HAs intraoperatively. Moreover, of the 18 centers, parenchymal suturing over a bolster of SURGICEL was consistently used by 16 centers. The investigators concluded that although there appears to be some advantage in the use of these agents, they should be limited to control minor bleeding in conjunction with other measurements, including parenchymal suturing over a bolster. However, despite these recommendations, it seems that the use of HAs is still vast, even though there is limited data supporting their effectiveness. In the current study we tried to examine the value of using HAs in PN. Following Breda et al., we further analyzed its value with and without the use of SURGICEL. In this study, the use of HAs did not improve or alter the rate of perioperative or post-operative bleeding as well as the rate of urinary leak when compared to sutures alone. When compared to SURGICEL (Table 3) despite the “advantages” in the tumor features (smaller tumors, less centrally located, laparoscopic approach) the addition of HA to the SURGICEL did not reduce the rate of complications, including urinary leak or the need for PBT. Moreover, since vascular clamping was previously associated with decreased hemorrhagic complications, and specifically lower PBT rate12, we further analyzed the theoretical advantage of HA to sutures and SURGICEL in patients in which renal artery clamping was not performed. Such analysis revealed no advantage with the use of HA, both in comparison to sutures alone or sutures combined with SURGICEL. In regards to surgical approach, most studies thus far have examined the beneficial effects of these agents, specifically in LPN. In the current study, we included also patients undergoing OPN. LPN is technically challenging and requires advanced laparoscopic skills. Hence, the laparoscopic approach is often reserved for small, peripheric, exhophitic tumors. In this study, patients operated via an open approach had significantly larger, centrally located tumors and significantly lower rate of vascular clamping (data not shown). Interestingly, even in this “high risk” subgroup of patients, the addition of HAs over a bolster of SURGICEL did not reveal even a slight advantage in any of the examined outcomes. In addition to the main theoretical benefit of HAs in minimizing postoperative bleeding and decreasing the rate of postoperative blood transfusion, HAs were also suggested to limit warm ischemia time by decreasing the amount of intracorporeal suturing and in some cases potentially promote collecting system healing and reduce postoperative urinary leak13. The lack of advantages in any of these aspects in the current cohort, raises the question as to whether HAs should still be used in patients undergoing PN. Supporting these conclusions, a recent study by Cohen et al., analyzed the use of a specific type of HAs, Fibrin sealants, during robot-assisted partial nephrectomy (RAPN). Cohen and colleagues demonstrated that the addition of Fibrin glue to hemostatic suture closure does not decrease the rate of complications, blood loss, or hospital stay. Furthermore, no impact was seen on operative time, ischemia time, or other negative outcomes. Consequently, the authors suggested that omitting these agents during RAPN could be safe and cost-effective1415. The absolute cost per case may vary between $100–$500, depending on the agent used. At high capacity centers where PNs are routinely performed, the overall cost can be significant. Taking the economic burden into consideration, along with the lack of proven benefits, lead us to the conclusion that the use of HAs, on the whole, is unnecessary in PN patients. We believe that if haemostasis is done well with stitches alone, there is no need for additional adhesive agents. The lack of standardized indications for using HAs vs sutures alone represents some weakness in our study design. However, we believe that this weakness is partly overcome by the fact that all operations were performed in the same surgical environment (four surgeons operating in one medical center) and thus it is reasonable to assume that the decision of using HAs was derived from similar clinical judgment and services routines. Prospective trials would be helpful in interpreting the practicality of these agents. Limitations of this study include the sample size and the inherent bias associated with its retrospective design. Moreover, the lack of definitive indications for the use of HA’s represent some weakness in our study design. However, we believe that this flaw is partly overcome by the fact that all operations were performed in the same surgical environment, in a high-volume tertiary care institute and thus it is reasonable to assume that the decision on using HA’s was derived from similar clinical judgment and service routines. Conclusions In the current study, there was no difference in complication rates using HAs compared with those without. The use of HAs during open and laparoscopic PN does not impact negative outcomes. A proper suture renorrhaphy during partial nephrectomy may be enough to prevent hemorrhagic complications and urine leak. Further study is necessary to support these findings. Additional Information How to cite this article: Abu-Ghanem, Y. et al. The use of Haemostatic Agents does not impact the rate of hemorrhagic complications in patients undergoing partial nephrectomy for renal masses. Sci. Rep. 6, 32376; doi: 10.1038/srep32376 (2016). Author Contributions Y.A.-G. Data collection or management, Data analysis, Manuscript writing/editing. Z.D. Manuscript writing/editing. I.K. Manuscript writing/editing. D.E.Z. Manuscript writing/editing. J.R. Protocol/project development, Manuscript writing/editing. Table 1 Clinicopathologic demographics of 657 patients included in the study. Variable No. (%) Age (years) (median ± sd) 61.85 ± 12.6 Gender  Male 437 (66.5)  Female 220 (33.5) BMI 27.1 ± 4.8 Preoperative HB (g/dL) 13.6 ± 1.50 Preoperative Serum Creatinine 1.02 ± 0.37 Central renal lesion 216 (32.9) Mass location   Upper Pole 168 (25.6)   Middle aspect 120 (18.3)   Lower Pole 206 (31.4)   Mixed 163 (24.7) Kidney side   Left Kidney 329 (50.2)   Right Kidney 326 (49.8) Tumor size 3.0 ± 1.49   <4 cm 517 (78.7)   >4 cm 140 (21.3) Pathology Malignant (RCC) 493 (75) Non-malignant* 164 (25) Operative method   Open 269 (40.9)   Laparoscopic 388 (59.1) Renal vascular clamping 519 (78.9) Ischemia time 20.0 ± 8.6 Renorrhaphy   Sutures alone 147   Sutures and HA 25   Sutures and SURGICEL 183   Suture, HA and SURGICEL 301 PBT 87 (13.3) Leak 17 (2.6) Delayed bleeding  Hematuria 10 (1.5)  Flank hematoma 6 (0.91) Pseudoaneurysm 16 (2.4) Renal Failure 12 (1.8) DVT/PE 5 (0.76) Values in parentheses are percentages; Abbreviations: PBT = Perioperative blood transfusion; BMI = Body Mass Index; HB = Hemoglobin; RCC = Renal Cell Carcinoma; HA = Hemostatic agents; DVT = deep vein thrombosis; PE = pulmonary embolism. *Angiomyolipoma (AML), Oncocytoma, simple cyst. Table 2 Univariate analysis - clinical, demographic, operative, and perioperative data of patients undergoing Partial Nephrectomy with only parenchymal suture vs: parenchymal suture with hemostatic agents and SURGICEL, suture with only HA and sutures with only SURGICEL. Variable Sutures alone(n = 147) Sutures and HA(n = 26) P value Sutures and SURGICEL(n = 183) P value Age (years) 58.7 ± 13.5 64.3 ± 9.7 0.112 61.6 ± 13.5 0.887 Gender   Male 97 (66) 19 (73.1) 0.761 117 (63.9) 0.698   Female 50 (34) 7 (26.9)   66 (36.1)   BMI 26.1 ± 5.6 25.9 ± 4.02 0.164 27.7 ± 4.7 0.612 Mass location   Upper Pole 42 (28.6) 3 (11.5) 0.071 53 (29) 0.135   Middle aspect 22 (15) 5 (19.2)   38 (20.8)     Lower Pole 38 (25.9) 12 (46.2)   55 (30.1)     Mixed 45 (30.6) 6 (23.1)   37 (20.2)   Multifocal mass 16 (10.9) 3 (11.5) 0.922 32 (17.5) 0.091 Kidney side   Left Kidney 71 (48.3) 16 (61.5) 0.213 87 (47.5) 0.887   Right Kidney 76 (51.7) 10 (38.5)   96 (52.5)   Central renal lesion 35 (23.8) 9 (34.6) 0.243 79 (43.2) <0.001 Hilar renal lesion 16 (10.9) 3 (11.5) 0.922 31 (16.9) 0.118 Mass size 3.01 ± 1.43 2.47 ± 1.1 0.727 3.83 ± 1.62 0.003   <4 cm 135 (91.8) 24 (92,3)   117 (63.9)     >4 cm 12 (8.2) 2 (7.7)   66 (36.1)   Pathology Malignant (RCC) 104 (70.7) 20 (76.9) 0.59 140 (76.5) 0.61 Non-malignant* 43 (29.3) 6 (23.1)   43 (23.5)   Operative method             Open 54 (36.7) 5 (19.2) 0.083 164 (89.6) <0.001   Laparoscopic 93 (63.3) 21 (80.8)   19 (10.4)   Renal vascular clamping   Yes 107 (72.8) 21 (80.8) 0.393 127 (69.4) 0.004   No 40 (27.2) 5 (19.2)   56 (30.6)   Ischemia Time (min) 19.7 ± 10.9 14.5 ± 8.5 0.283 15.8 ± 10.6 0.87 Preoperative HB (g/dL) 13.6 ± 1.5 13.8 ± 1.1 0.09 13.5 ± 1.55 0.899 Discharge HB (g/dL) 11.4 ± 1.5 11.8 ± 1.5 0.845 11.45 ± 1.35 0.261 PBT 6 (4.1) 2 (7.7) 0.419 35 (19.1) <0.001 Leak 1 (0.7) 0 (0) 0.673 9 (4.9) 0.026 Delayed bleeding   Hematuria 3 (2.04) 1 (3.8) 0.576 2 (1.6) 0.867   Flank hematoma 0 (0) 0 (0) 0.773 1 (0.5) NA Pseudoaneurysm 1 (0.7) 0 (0) NA 5 (2.7) 0.836 Renal Failure 3 (2.04) 0 (0) NA 6 (3.3) 0.718 DVT/PE 0 (0) 1 (3.8) NA 3 (0.55) NA Values in parentheses are percentages; Abbreviations: PBT = Perioperative blood transfusion; BMI = Body Mass Index; HB = Hemoglobin; RCC = Renal Cell Carcinoma; HA = Hemostatic agents; DVT = deep vein thrombosis; PE = pulmonary embolism. *Angiomyolipoma (AML), Oncocytoma, simple cyst. Table 3 Univariate analysis - clinical, demographic, operative, and perioperative data of patients undergoing Partial Nephrectomy with only parenchymal suture, or parenchymal suture with SURGICEL and Hemostatic agens. Variable Suture, HA and SURGICEL(n = 301) Sutures and SURGICEL(n = 183) P value Age (years) 61.5 ± 11.6 61.6 ± 13.5 0.079 Gender   Male 204 (67.8) 117 (63.9) 0.386   Female 97 (32.2) 66 (36.1)   BMI 28.1 ± 4.8 27.7 ± 4.7 0.853 Mass location     0.368   Upper Pole 53 (29) 70 (23.2)     Middle aspect 38 (20.8) 55 (18.3)     Lower Pole 55 (30) 101 (33.5)     Mixed 37 (20.2) 75 (25)   Multifocal mass 14 (4.7) 32 (17.5) 0.123 Kidney side     0.359   Left Kidney 156 (51.8) 87 (47.5)     Right Kidney 145 (48.2) 96 (52.5)   Central renal lesion 101 (33.6) 79 (43.2) 0.034 Hilar renal lesion 40 (13.3) 31 (16.9) 0.271 Mass size 3.21 ± 1.4 3.8 ± 1.6 <0.001   <4cm 241 (80.1) 117 (63.9)     >4cm 60 (19.9) 66 (36.1)   Pathology Malignant (RCC) 229 (76.1) 140 (76.5) 0.92 Non-malignant* 72 (23.9) 43 (23.5)   Operative method     <0.001   Open 46 (15.3) 164 (89.6)     Laparoscopic 255 (84.7) 19 (10.4)   Renal vascular clamping     <0.001   Yes 269 (89.4) 127 (69.4)     No 32 (10.6) 56 (30.6)   Ischemia Time (min) 22.5 ± 10.3 14.8 ± 10.6 0.950 Preoperative HB (g/dL) 13.6 ± 1.5 13.5 ± 1.55 0.722 Postoperative HB (g/dL) 11.86 ± 1.5 11.45 ± 1.35 0.473 PBT 44 (14.6) 35 (19.1) 0.193 Leak 7 (2.3) 9 (4.9) 0.122 Delayed bleeding   Hematuria 4 (1.3) 4 2 (1.6) 0.794   Flank hematoma (1.3) 1 (0.5) 0.832 Pseudoaneurysm 10 (3.3) 5 (2.7) 0.798 Renal Failure 3 (1.0) 6 (3.3) 0.153 DVT/PE 2 (0.67) 3 (0.55) 0.462 Values in parentheses are percentages; Abbreviations: PBT = Perioperative blood transfusion; BMI = Body Mass Index; HB = Hemoglobin; RCC = Renal Cell Carcinoma; HA = Hemostatic agents; DVT = deep vein thrombosis; PE = pulmonary embolism. *Angiomyolipoma (AML), Oncocytoma, simple cyst. Table 4 Transfusion rates among different variables in patients undergoing laparoscopic PN. Variable Suture, HA and SURGICEL (n=255) Sutures and SURGICEL (n = 19) P value Suture and HA (n = 21) Sutures alone (n = 93) P value Age (years) 62 ± 11.3 61.9 ± 15.3 0.347 63.1 ± 9.8 57.6 ± 13.4 0.229 Central renal lesion 74 (29) 2 (10.5) 0.083 5 (23.8) 10 (10.8) 0.110 Mass size 3.04 ± 1.3 3.03 ± 1.6 0.127 2.43 ± 1.2 2.7 ± 0.96 89 0.333   <4cm 218 (85.5) 15 (78.9)   19 (90.5) (95.7)     >4cm 37 (14.5) 4 (21.1)   2 (9.5) 4 (4.3)   Pathology Malignant (RCC) 198 (77.6) 12 (63.2) 0.15 15 (71.4) 66 (71.0) 0.97 Non-malignant* 57 (22.4) 7 (36.8)   6 (28.6) 27 (29.0)   Renal vascular clamping     <0.001     0.095   Yes 226 (88.6) 10 (52.6)   19 (90.5) 68 (73.1)     No 29 (11.4) 9 (47.4)   2 (9.5) 25 (26.9)   Ischemia Time (min) 25.6 ± 7.8 21.1 ± 13.6 0.496 17.5 ± 6.5 24.8 ± 9.3 0.123 PBT 31 (12.2) 3 (15.8) 0.643 1 (4.8) 3 (3.2) 0.730 Leak 6 (2.4) 3 (15.8) 0.002 0 0 NA Delayed bleeding   Hematuria 7 0 NA 0 2 NA   Flank hematoma 6 0 NA 1 0 NA Pseudoaneurysm 2 0 NA 0 0 NA Renal Failure 3 0 NA 0 1 NA DVT/PE 2 0 NA 0 0 NA Values in parentheses are percentages; Abbreviations: PBT = Perioperative blood transfusion; RCC = Renal Cell Carcinoma; HA = Hemostatic agents; DVT = deep vein thrombosis; PE = pulmonary embolism. *Angiomyolipoma (AML), Oncocytoma, simple cyst. Table 5 Transfusion rates among different variables in patients undergoing open PN. Variable Suture, HA and SURGICEL (n = 46) Sutures and SURGICEL (n = 164) P value Age (years) 58.9 ± 13 61.6 ± 13.3 0.735 Central renal lesion 27 (58.7) 77 (47) 0.159 Mass size 4.1 ± 1.59 3.9 ± 1.6 0.799   <4cm 23(50) 102 (62.2)     >4cm 23 (50) 62 (37.8)   Pathology Malignant (RCC) 32 (69.6) 128 (78) 0.16 Non-malignant* 14 (30.4) 36 (22)   Renal vascular clamping     0.005   Yes 42 (91.3) 47 (28.7)     No 4 (8.7) 117 (71.3)   Ischemia Time (min) 18.8 ± 7.5 18.2 ± 7.96 0.813 PBT 13 (28.3) 33 (20.1) 0.238 Leak 1 (2.2) 6 (3.7) 0.620 Delayed bleeding   Hematuria 1 (2.17) 5 (3.05)     Flank hematoma 0 2 (1.22) NA Pseudoaneurysm 1 (2.17) 2 (1.22)   Renal Failure 0 6 (3.66) NA DVT/PE 0 3 (1.83) NA Values in parentheses are percentages; Abbreviations: PBT = Perioperative blood transfusion; RCC = Renal Cell Carcinoma; HA = Hemostatic agents; DVT = deep vein thrombosis; PE = pulmonary embolism. *Angiomyolipoma (AML), Oncocytoma, simple cyst. ==== Refs Uzzo R. G. & Novick A. C. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3238610.1038/srep32386ArticleIn vivo mutagenesis of miRNA gene families using a scalable multiplexed CRISPR/Cas9 nuclease system Narayanan Anand 1*Hill-Teran Guillermina 1*Moro Albertomaria 1Ristori Emma 1Kasper Dionna M. 1A. Roden Christine 23Lu Jun 23Nicoli Stefania a11 Yale Cardiovascular Research Center, Section of Cardiology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06510, USA2 Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA3 Yale Stem Cell Center and Yale Cancer Center, Yale University, New Haven, CT, 06520, USAa stefania.nicoli@yale.edu* These authors contributed equally to this work. 30 08 2016 2016 6 3238631 05 2016 08 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/A large number of microRNAs (miRNAs) are grouped into families derived from the same phylogenetic ancestors. miRNAs within a family often share the same physiological functions despite differences in their primary sequences, secondary structures, or chromosomal locations. Consequently, the generation of animal models to analyze the activity of miRNA families is extremely challenging. Using zebrafish as a model system, we successfully provide experimental evidence that a large number of miRNAs can be simultaneously mutated to abrogate the activity of an entire miRNA family. We show that injection of the Cas9 nuclease and two, four, ten, and up to twenty-four multiplexed single guide RNAs (sgRNAs) can induce mutations in 90% of the miRNA genomic sequences analyzed. We performed a survey of these 45 mutations in 10 miRNA genes, analyzing the impact of our mutagenesis strategy on the processing of each miRNA both computationally and in vivo. Our results offer an effective approach to mutate and study the activity of miRNA families and pave the way for further analysis on the function of complex miRNA families in higher multicellular organisms. ==== Body A miRNA gene is transcribed by RNA polymerase II into a primary miRNA transcript (pri-miRNA), which folds upon itself forming a hairpin structure with a precise sequence and structural motif that is then cleaved by the RNAse enzyme Drosha and its co-factor DGCR8. The processed stem-loop intermediate, known as the precursor miRNA (pre-miRNA), is exported from the nucleus and cleaved by the RNAse enzyme Dicer in the cytosol to produce a ~22 nucleotide (nt) duplex. Upon loading of one strand of the RNA duplex into the RNA-induced silencing complex (RISC), the Argonaute protein in RISC mediates pairing between the miRNA ‘seed’ sequence (nucleotides 2–8 from the 5 prime end of the mature miRNA) and the 3 prime untranslated region (3′UTR) of the target messenger RNA (mRNA), inducing mRNA degradation and protein destabilization1234. miRNA regulation is an important mechanism to control the expression of numerous key genes involved in development, morphogenesis, and disease pathogenesis567. Consequently, there has been great interest in cataloguing the function of every miRNA in vivo, however, these efforts have been hindered by the complex genomic organization of miRNA genes. During the evolution of higher organisms, genomic duplication events generated miRNA families comprised of multiple miRNAs with high sequence homology and identical seed regions8. Local duplication events have produced clusters of miRNA genes that are often transcribed as a single RNA transcript, while non-local gene duplication events have created related miRNA genes on separate chromosomes. As a result, vertebrates such as zebrafish, mouse, and human have the greatest and most intricate repertoire of miRNA genes8. In fact, nearly 40% of vertebrate miRNAs belong to families. Because of this genomic complexity, it has been difficult to generate vertebrates that lack multiple miRNA family members. Unfortunately, the current genetic approaches in vertebrates only allow for the mutagenesis of single or clustered miRNA genes, but not of miRNA families originating from non-local duplication. These technologies include classical gene ablation strategies and transcription activator-like effector nucleases (TALEN)-based strategies91011. In previous studies using TALEN mutagenesis, one TALEN pair was designed to target a single miRNA locus, while a strategy using two TALEN pairs was used to remove miRNAs within the same RNA transcript encoding for the miR-430 miRNA family12. More recently, a CRISPR/Cas9 approach was successfully used to target single miRNA loci in mammalian cells1314. In these reports, customizable single guide (sg)RNAs can recognize miRNA genomic targets in close proximity to the protospacer-adjacent motif (PAM) sequence, NGG, and generate insertions and/or deletions (indels) with mutation rates that can reach up to 75–99% with minimal off-target activity15161718. While these approaches can efficiently mutagenize miRNA loci one at a time, they have not been adapted to rapidly and comprehensively generate loss-of-function models for entire miRNA families. Here, we optimized a scalable multiplexed CRISPR/Cas9 strategy to induce heritable loss-of-function mutations of miRNA family members. We present a comprehensive survey of mutations within pri-miRNA genes encoding 45 miRNAs. Our data showed 99% of CRISPR/Cas9 mutations alter critical sequences within each hairpin pri-miRNA structure that impairs recognition by the miRNA biogenesis machinery, and thus prevents miRNA family expression in vivo. Results A scalable multiplexed CRISPR/Cas9 strategy to generate zebrafish miRNA mutants Here, we multiplexed the injection of sgRNAs to generate mutants for miRNAs present in the genome as part of the same family, which predominantly originated from non-local duplication (Fig. 1A). First, we chose three miRNAs present as single copies and seven miRNA families as reported in miRBase v21 (Supplementary Figure 1). We tested our approach in zebrafish by targeting three miRNA families consisting of 2 miRNA members, three families consisting of 4 to 5 miRNA members, and the let-7 family consisting of 18 known members. Second, we designed two sgRNAs to target both arms of the genomic sequence of the pri-miRNA hairpin structure based on proximity to the NGG region and the mature and complementary miRNA sequences. We used the previously described 5′GG-X20 sgRNA architecture (where X20 represents the 20 nt gene specific sequence), a design that effectively discriminates off-target sites19. Third, we generated the DNA templates for the sgRNAs using a cloning-independent method20. This strategy is based on the annealing of a forward DNA oligonucleotide containing the T7 promoter sequence upstream to the GG-X20-N15, where N15 represents the 15 nt region that anneals with a common universal reverse primer containing crRNA and tracrRNA sequences (see Materials and Methods and ref. 21)(Fig. 1A). To generate a pool of sgRNAs that recognize many target miRNA sequences, several T7-GG-X20-N15 forward primers were added to the PCR reaction (Fig. 1A). After annealing and PCR amplification, sgRNAs were generated by T7 in vitro reverse transcription (IVT) and injected together with Cas9 mRNA into zebrafish embryos at the one-cell stage. F0 lesion frequency was tested for each miRNA locus in five individually injected fish using a T7 Endonuclease I assay (T7EI). Finally, we out-crossed F0 adults to generate F1 progeny and tested for miRNA indel transmission and miRNA functionality (Fig. 1B). In the somatic tissue of individual F0 adults, we found 90% of the injected sgRNA pairs induced mutations across multiplexed conditions including 15 out of the 18 let-7 members (Fig. 1C). These targeting efficiencies were similar to a previous report showing the targeting of a single miRNA by the injection of 2 multiplexed sgRNAs led to a high targeting efficiency, close to 80% (Fig. 1D)15. Importantly, the progressive multiplexing of sgRNAs to target an increasing number of miRNA loci maintained a successful rate of mutagenesis for up to 24 sgRNAs (Fig. 1D). Furthermore, the analysis of F1 progeny from F0 outcrosses established that the miRNA-multiplexed mutations were heritable, demonstrating that our strategy can successfully induce miRNA mutations in the germline (Fig. 1E). CRISPR/Cas9 multiplexing effects on off-target sequences Several groups have shown that CRISPR/Cas9 induces off-target mutations at sites that differ in as little as one nt compared to the target site mutations1922. Genomic sequences encoding miRNAs share high sequence similarities, as they are critical for secondary structure formation and recognition by the miRNA biogenesis machinery23. Therefore, it was critical to assess the off-target effects of our mutagenesis strategy. To address this point, we first used a computational algorithm24 to search for sequences that have 1 or 2 nt mismatches with our target miRNA genomic sequences and thus had a high likelihood of being targeted by the sgRNAs. We then tested F0 mutant fish for these potential off-target lesions using the T7EI assay. Importantly, the frequency of off-target mutations was minimal (between 1–10%) in the majority of sequences analyzed (Fig. 2). We detected ubstantial off-target effects only in the let-7 multiplex experiment, in which one out of the eleven off-target sequences was mutated at a frequency higher than 10% (Fig. 2). Therefore, our data provide the proof-of-principle that using a high number of multiplexed sgRNAs with a 5′GG-X20 structure and assembled with a cloning-independent method showed high on-target efficiency with little off-target effects. Multiplexed miRNA mutations block miRNA family activity We tested whether the induced miRNA mutations disrupted miRNA family activity in vivo. We cloned and sequenced 10 miRNA genomic sequences from F0 zebrafish injected with 2, 4, 10, or 24 multiplexed sgRNAs. Multiple sequence alignment analysis of sequenced PCR clones indicated that all sgRNAs induced substantial indels, independent of the multiplexing condition (Fig. 3A). Consistent with previous reports, all the mutations occurred at or near the NGG region1525. To test if the mutations reduced miRNA activity, we employed a miRNA gene reporter assay26 (Fig. 3B) in which the coding sequence for green fluorescent protein (GFP) was cloned upstream and in frame with a 3′UTR containing three miRNA responsive elements (MRE) that were perfectly complementary to miR-24 (GFP-miR-24-MRE). We chose miR-24 for the reporter assay because all miR-24 loci generate the same mature miRNA. In vitro transcribed GFP-miR-24-MRE and mCherry mRNAs were co-injected into one-cell stage embryos with and without the miR-24 multiplexed sgRNAs and Cas9 mixture. Although wild type GFP-miR-24-MRE positive embryos showed overall homogenous expression of the GFP and mCherry proteins, mosaic derepression of the GFP-miR-24-MRE was only observed after co-injection of the multiplexed sgRNAs-Cas9 against the four miR-24 loci (Fig. 3B, arrows). We also generated a GFP-let-7-MRE sensor by cloning three different let-7 MREs recognized by let-7 a, b and c miRNAs in the 3′UTR of the GFP reporter construct. The co-injection of GFP-let-7-MRE and mCherry mRNAs, and the M24 let-7 sgRNA pool with Cas9 induced derepression of GFP protein expression (Fig. 3B, arrows). Mosaic cells showed GFP derepression consistent with the detected indel frequency (Fig. 1D). Therefore, these data show that multiplexed miRNA mutations can significantly disrupt the activity of an entire miRNA family. Multiplexed mutations abrogate miRNA activity by interfering with miRNA biogenesis Intrigued by our results on the analysis of miR-24 and let-7 mutations, we reasoned that a comprehensive analysis of our mutagenized miRNA sequences would establish the most successful mutations to functionally perturb miRNA expression in vivo (Fig. 4A). We first used a computational algorithm, RNAfold27, to predict the maximum free energy structure of an RNA sequence and HairpIndex (Roden C. et al. submitted) to annotate structure and sequence features of the hairpin. Structural features such as the number and position of bulges, stem length28, and loop size2930 are critical for pri-miRNA recognition and cleavage by the Drosha/DGCR8 complex. Then we compared the resulting RNA structure predictions between wild type and mutant pri-miRNA genes and identified that the majority of our insertions and deletions (indels) alter the length of the hairpin stems and the number of left bulges (Fig. 4B). To assess the impact of mutations in the miRNA genomic sequence on miRNA biogenesis, we developed an mCherry reporter assay. We cloned the wild type or the mutant pri-miRNA sequence into an mCherry reporter construct, the pTol2-Bact-pri-miRNA-mCherry biogenesis assay vector (Fig. 4C)31. Upon injection of this transgenic vector in embryos, the beta-actin promoter drives the ubiquitous expression of the pri-miRNA-mCherry transcript. Following the splicing of this ectopic transcript, mCherry is expressed and the pri-miRNA is available for processing by the endogenous miRNA machinery into the mature miRNA (Fig. 4C). Using this strategy, we isolated embryos at 24 hpf that were mCherry positive and expressed wild type or mutant pri-miRNA. These embryos were processed for northern blot analysis to compare the respective mature miRNA levels between the wild type or mutant pri-miRNA. Strikingly, our quantification revealed that ~90% of the CRISPR/Cas9-induced mutations disrupted the biogenesis of ectopically expressed mutant pri-miRNAs (Fig. 4C,D). Interestingly, we found one case, miR-30c, in which mutations within this pri-miRNA gene produced an RNA hairpin that was more efficiently processed by the miRNA biogenesis machinery (Fig. 4D). Analysis of the secondary structure revealed that this mutation reduces the size of the apical loop on the RNA hairpin of miR-30c and increases stem length from 32 nt to 33 nt, thus indicating that particular modifications of the miRNA gene sequence may increase the efficiency of miRNA biogenesis (Fig. 4E). Finally, in agreement with each specific genotype, mature miRNA expression was diminished or lost in our miRNA single, double, and quintuple F2 mutant founders selected from our screening (Fig. 4F). Taken together, our data show that mutations within the miRNA gene resulted in alterations in the hairpin structure and consequently in the miRNA expression, confirming that our scalable mutagenesis strategy enables the study of miRNA family activity. Discussion Here, we describe a successful strategy to multiplex the CRISPR/Cas9 system to target miRNA gene families. This method can generate in vivo heritable mutations in multiple miRNA loci to abrogate the activity of an entire miRNA family and enables the functional analysis of miRNA gene families in biological processes (such as development). In addition, our system can advance the understanding of the critical structural rules of a miRNA gene and how they impact miRNA expression levels. Our strategy represents a significant improvement from the preexisting protocols. First, we used multiplexed CRISPR/Cas9 to target multiple non-coding genomic sequences in an in vivo model. Second, we showed that multiplexed mutations were transmittable to the F1 generation. Finally, we analyzed the impact on miRNA biogenesis of a significant number of mutations within the pri-miRNA genes. Our data showed that the multiplexing strategy simultaneously generates mutations in up to 14 miRNA loci with minimal off-target effects. Additionally, we provide the proof-of-principle that F0 and F1 miRNA family mutants can result in loss of miRNA activity. Indeed, the injection of our CRISPR/Cas9 against the let-7 superfamily or miR-24 was sufficient to disrupt mature miRNA activity leading to derepression of a GFP sensor containing miRNA-binding sites. As our mutagenesis was successfully applied to several different miRNA families, our data represent the largest collection of compound miRNA family mutants generated by CRISPR/Cas9. Our strategy enables the analysis of more complex biological questions related to miRNA function, such as the functional redundancy between miRNAs that share the same seed region, are expressed within the same cell type, or are part of the same signaling pathways. Therefore, our protocol can be applied to address critical questions related to miRNA functional complexity in vivo. We analyzed the effects of a comprehensive number of indels generated in the pri-miRNA genome family sequences on miRNA biogenesis. We discovered that most of the changes affecting predicted nucleotide pairing and overall length of the pri-miRNA stem length are sufficient to impair mature miRNA biogenesis. This may be due in part to the fact that many of our sgRNAs were designed to target mature miRNA sequences within the pri-miRNA. Indeed, sequence regions and features within the stem of the pri-miRNA (bulge size, bulge position, stem length) would be preferentially disrupted by indels in this region. Interestingly, we found a mutation within a miRNA that can also enhance miRNA expression. We identified a mutation in miR-30c that reduces the size of the apical loop and increases the stem length of the pri-miRNA. Apical loop size has previously been reported to control microprocessor cleavage efficiency in mammalian cells with optimal apical loop size ranges of 3–23 nt29 or >10 nt30. The miR-30c (−) 6 mutation reduces the predicted apical loop size from 13 nt to 5 nt which may disrupt this feature. The likely mechanism of processing enhancement is the change in stem length. Optimal stem length of 35 ± 1 nt in mammalian cells has been reported to enhance microprocessor cleavage28. The miR-30c (−) 6 mutation increases the stem length from 32 to 33 nt which is closer to optimal stem length. Thus, further analysis in which changes in stem length and apical loop size are independently assessed will be necessary to understand this result on miR-30c biogenesis. Overall, our data showed that mutations that are not restricted to miRNA mature sequences are sufficient to alter miRNA expression. This is consistent with recent evidence provided by genome wide analysis of hundreds of human pri-miRNA gene sequences and suggests that there are evolutionarily conserved structural and sequence features that miRNA genes require for miRNA expression1428. Altogether, the application of our strategy will allow not only the generation of models to study miRNA family expression and function, but also the identification of novel and critical sequences within a miRNA gene essential for miRNA biogenesis in vivo. In light of studies showing that polymorphisms in human miRNA genes are strongly associated with disease susceptibility such as schizophrenia and diabetes323334, strategies such as ours are critical to improve our current understanding of the impact that genetic variants have on miRNA gene sequence affecting miRNA regulation and activity. Experimental Procedures Fish husbandry Zebrafish (strain WTCF)26 were raised and maintained according to protocols approved by the Yale University Institutional Animal Care and Use Committee (IACUC). All methods were carried out in accordance with the relevant guidelines and approved under IACUC protocol number 2015-11473. Generation of sgRNA, Cas9 mRNA and zebrafish injections To generate sgRNA we purchased forward primers with the following architecture: 5′-TAATACGACTCACTATA-GG-X20-GTTTTAGAGCTAGAA-3′ (X corresponds to the nucleotides of the sgRNA sequence, see Supplementary Table 1) (IDT and Keck Oligos, Yale). 10 μmols of each forward primer and 50 μmols of universal reverse primer 5′-AAAAGCACCGACTCGGTGCCACTTTTTCAAGTTGAT AACGGACTAGCCTTATTTTAACTTGCTATTTCTAGCTCTAAAAC-3′ (PAGE purified from IDT) were used in an annealing and dNTP filling PCR reaction (95 °C for 3 minutes, 95 °C for 30 sec, 45 °C for 30 sec, 68 °C for 20 sec, cycle to step 2 for 34 cycles, 72 °C for 5 minutes and hold at 4 °C). The PCR product was purified using a PCR purification kit and in vitro transcription was performed with the T7 Flash kit. The transcript was treated with 0.5 μl DNAse Turbo at 37 °C for 20 minutes, precipitated with sodium acetate and 100% EtOH, and washed twice with 70% EtOH. Zebrafish codon optimized pT3TS:nCASn plasmid15 was linearized with XbaI and in vitro transcribed using mMESSAGE mMACHINE T3 Transcription Kit. The RNA was purified using an RNeasy Mini Kit. Zebrafish embryos at the one-cell stage were injected with 2 nanoliters of solution containing 100 ng/μl of multiplexed sgRNA with 150 ng/μl of Cas9 mRNA and Phenol Red. Higher doses of gRNA (200 ng/μl gRNA and 300 ng/μl of Cas9) yielded similar mutation efficiencies but had higher toxicity. Determination of on-target and off-target mutations Genomic DNA was isolated using a DNeasy Blood and Tissue kit from a clutch of 15–20 embryos at 24 hpf injected with sgRNA and Cas9. Genomic DNA (50 ng/μl) was used to amplify an approximately 200–400 bp region surrounding the intended target (see Supplementary Table 1). Mutations were detected through a T7 endonuclease I (T7E1) assay19. Once the mutation was detected, the rest of the embryos from the same clutch were raised. One-month old, F0 founder fish were screened for on-target and off-target mutations through fin clipping or isolated sperm cells from individual fish using the T7EI assay or PCR Fragment Analysis. ImageJ64 software was used to quantify the T7EI digested PCR band detected in the represented agarose gels. Indels were confirmed by cloning each PCR reaction into a pGEM-T vector and sequence analysis was performed through T-Coffee Multiple Sequence Alignment35. Pri-miRNA Computational Structure Predictions Predicted mutant and wild type pri-miRNA maximum free energy structures were predicted using RNAfold version 2.1.92736 and annotated using HairpIndex Matlab code (Roden et al. submitted). Briefly, hairpin structures were predicted based on the initial identification of the apical loop position. Primary hairpin stem length was determined by counting the number of bases within the stem starting at the first paired base after the apical loop and stopping at the basal unpaired region. Primary sequence motifs (CNNC, basal UG, apical UGU/UGUG23 and secondary structure motifs (e.g., apical loop size, internal bulge position, single stranded regions) were then annotated on each candidate hairpin. Comparisons were then made between WT and mutant structure annotations. A number of structural features were frequently impacted in mutant pri-miRNA hairpins including right bulge size (count of unpaired bases on the 5′ side of hairpin), left bulge size (count of unpaired bases on the 3′ side of hairpin), right bulge number (count of unpaired regions on the 5′ side of hairpin), left bulge number (count of unpaired regions on the 3′ side of hairpin), size of stem (length of the hairpin stem), loop size (count of unpaired bases within the loop), and loop number (count of predicted loops). miRNA Sensor and Biogenesis Assay The miRNA gene reporter assay was constructed as previously described26. sgRNA (100 ng/μl), Cas9 (150 ng/μl) with or without the corresponding GFP-miR-24-MRE or GFP-Let-7-7-MREs (50 ng/μl) and mCherry (50 ng/μl) with Phenol Red were injected. 48 hpf embryos were imaged with a confocal microscope (SP5 Leica Microsystems) and captured using Leica application software suite. Mutant and wild type miRNA genome sequence were cloned as previously described31. Northern blots were performed using 3 micrograms of total RNA extracted from mCherry positive injected embryos and developed as reported previously in26. Additional Information How to cite this article: Narayanan, A. et al. In vivo mutagenesis of miRNA gene families using a scalable multiplexed CRISPR/Cas9 nuclease system. Sci. Rep. 6, 32386; doi: 10.1038/srep32386 (2016). Supplementary Material Supplementary Information We thank Marie Élise Schwartz and Meredith Cavanaugh for technical support and zebrafish husbandry and colony maintenance. We also thank Antonio Giraldez and his laboratory for sharing protocols and reagents. Finally, we thank Melanie Trombly for critical review of the manuscript. This work was supported by grants from the NIH (R56HL123988 and R01HL130246 to S.N. and F32HL132475 to D.K.). Author Contributions A.N. and G.H.-T. performed the experiments in Figures 1–3. A.M. analyzed the data in Figures 2 and 4 and Supplementary Figure 1. E.M. contributed to the experiments in Figure 1 and performed the experiments in Figure 4. D.M.K. contributed to the experiments in Figures 1 and 4. C.A.R. and J.L. performed the RNA hairpin analysis in Figure 4. S.N. conceived and designed the experiments, analyzed the data, and wrote the manuscript. All authors helped to edit the manuscript. Figure 1 Multiplex CRISPR/Cas9 strategy to target miRNA families. (A) Diagram indicating the design of multiplexed sgRNAs against the miRNA family members. Pairs of forward gRNA primers were customized for each target miRNA and consisted of a 5′-T7 RNA sequence followed by GG-X20 (X20 represents the 20 nt gene specific sgRNA and the black line represents a generic 15 nt sequence for annealing with the universal reverse primer). Double-stranded DNAs containing sgRNA sequences were assembled using annealing and PCR amplification with a universal reverse primer containing crRNA and tracrRNA sequences. Pooled sgRNAs were synthetized in a single in vitro transcription reaction (IVT). Multiplexing (M) was accomplished to target a miRNA family and/or duplicates, consisting of 1, 2, 5, and 18 miRNAs. For the let-7 family, 24-multiplexed sgRNAs were sufficient to target 36 loci since multiple let-7 members share an identical pre-miRNA genome sequence. (B) Schematic representing the strategy to generate miRNA family mutants. (C) F0 fish injected with the respective multiplexed sgRNAs and Cas9 mRNA were genotyped using gene specific primers that amplified a 200-400 nt genomic region for one, two, and up to 18 miRNA loci. CRISPR/Cas9 mutagenesis was determined by the T7EI assay. Cleaved PCR fragments revealed the presence of indels as indicated with arrowheads. Uninjected wild type fish (minus sign) were used as negative controls. Mutation frequencies were determined by T7EI assay in genotyped F0 adult zebrafish (D) and F1 progeny (E) and quantified as previously described1922. Each data point represents the average mutation frequency of miRNA target loci analyzed by T7E1 assay in an individual F0 adult zebrafish (D) or F1 embryo (E). At least five individual adult F0 fish (D) and twenty-five F1 embryos (E) were screened for each multiplexed sgRNA pool (Mn). Figure 2 Off-target analysis of the multiplexed miRNA mutants. Off-target gene sequences were identified as previously described1924. Off-target sequences containing 1–2 nt mismatches (indicated by a lowercase letter highlighted in red) with each of the target sgRNA sequences are shown. Off-target activity was determined using a T7EI assay after PCR amplification of the off-target loci. miRNA on-target mutations were also amplified and processed with the T7EI assay as a positive read-out of the analysis. Black arrowheads indicate mutations in both on- and off-target PCR products with a frequency ≥10%. Mutation frequencies were quantified for each on-target and off-target sequence and plotted in the chart. Figure 3 Multiplexed miRNA mutations induced efficient disruption of the miRNA family function. (A) Sequences of miRNA loci mutated after multiplexed CRISPR/Cas9 injection. PCR fragments were cloned and sequenced from F0 embryos. Sequences were aligned using the T-Coffee multiple sequence alignment program. The alignments are colored according to their similarity to the wild type sequence (top sequence) (high = red to low = green). The two gRNAs designed for each miRNA hairpin arm are highlighted by a solid dark blue and light blue line. Arrows point to the PAM sequence. Dashed lines indicate insertions in the wild type (wt) sequence and dashed lines in the mutant (m) sequences indicate deletions. DNA sequences within the black box correspond to the mature miRNA. (B) The top panel shows the diagram of the miRNA sensor assay to establish miRNA loss of function. The bottom panel shows confocal images of the lateral trunk of 48 hpf embryos injected as indicated. Caudal is to the right. Arrows indicate the presence of cells with GFP derepression in embryos after the injection of the respective multiplexed sgRNAs and Cas9. Figure 4 Impact of CRISPR/Cas9 mutations on miRNA processing. (A) Schematic representation of a pri-miRNA hairpin highlighting the position of important secondary structures and sgRNA-mediated mutagenesis sites. (B) Computational analysis of predicted RNA hairpin structures of wild type and mutant miRNA genome sequences analyzed. Percentile is indicative of the number of miRNA mutants falling in the indicated categories compared to the wild type structures. (C) Schematic representation of zebrafish miRNA biogenesis assay (top). Northern blot of miR-125 mature sequence expression obtained upon biogenesis assay of miR-125-a1, -a2, -b1, -b2 and -b3 mutants and wild type pri-miRNA genes (bottom). (D) Chart shows the quantification (pixel intensity) of northern blots in (C) normalized to the respective total RNA and the ectopic expression of wild type pri-miRNA injection. (E) Predicted RNA structure obtained with the ViennaRNA Software Package2 miRBase v2136 of the wild type and mutant sequence. Colored in red are the sequences of the respective mature miRNAs. (F) Average level of mature miRNA expression of the indicated miRNAs. qRT-PCRs were performed on adult fin clipped F2 miRNA founders genotyped accordingly (n = 3). 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3237710.1038/srep32377ArticleIncorporation of non-canonical amino acids into the developing murine proteome Calve Sarah a1Witten Andrew J. 1Ocken Alexander R. 1Kinzer-Ursem Tamara L. b11 Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA.a scalve@purdue.edub tursem@purdue.edu30 08 2016 2016 6 3237721 03 2016 09 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Analysis of the developing proteome has been complicated by a lack of tools that can be easily employed to label and identify newly synthesized proteins within complex biological mixtures. Here, we demonstrate that the methionine analogs azidohomoalanine and homopropargylglycine can be globally incorporated into the proteome of mice through facile intraperitoneal injections. These analogs contain bio-orthogonal chemical handles to which fluorescent tags can be conjugated to identify newly synthesized proteins. We show these non-canonical amino acids are incorporated into various tissues in juvenile mice and in a concentration dependent manner. Furthermore, administration of these methionine analogs to pregnant dams during a critical stage of murine development, E10.5–12.5 when many tissues are assembling, does not overtly disrupt development as assessed by proteomic analysis and normal parturition and growth of pups. This successful demonstration that non-canonical amino acids can be directly administered in vivo will enable future studies that seek to characterize the murine proteome during growth, disease and repair. ==== Body Significant advances in proteomics technology have been made over the past decades facilitating the identification and quantification of proteins within complex biological samples. In particular, the bottom-up approach in which proteins are digested into peptides and analyzed using a combination of chromatographic separation, mass spectrometry and automated database matching of peptides has greatly increased the volume of data that can be used to describe complex systems1. However, there are only few studies that have employed these techniques to assess protein turnover during embryogenesis2345. As many developmental biologists are interested in what happens during a defined stage, it is critical to be able to specifically label proteins that are synthesized within a narrow time window. One way in which MS-based analysis can reveal synthesis and turnover rates is through stable isotope tracer incorporation (SILAC)67. Utilization of this method for proteomic analysis of adult and embryonic murine tissues was recently demonstrated8; however, it takes weeks and specialized chow to generate these mice. Another significant limitation of SILAC labeling is that proteins in low abundance can be missed9. To overcome the drawbacks of current proteomic methods, and to create a means for selective enrichment of newly synthesized proteins, bioorthogonal non-canonical amino acid labeling (BONCAT) labeling was developed10. The Met analogs azidohomoalanine (AHA) and homopropargylglycine (HPG) carry azide and alkyne functional groups, respectively (Fig. 1A), and are incorporated into sites normally occupied by Met during protein synthesis (Fig. 1B)11. Importantly, these functional groups are bioorthogonal; they do not cross react with natural biological chemistries. Azides can react specifically with alkynes using copper-catalyzed azide-alkyne cycloaddition (CuAAC)12, allowing for the selective targeting of proteins containing AHA and HPG within complex mixtures of biomolecules (Fig. 1C). In this way AHA- and HPG-containing proteins can be reacted with fluorophores for imaging or affinity tags for enrichment10131415. The different functional groups of AHA and HPG make these reagents useful for pulse-chase experiments within the same system16. AHA and HPG have been successfully utilized to label newly synthesized proteins in vitro and have proven to be nontoxic in zebrafish and Xenopus in vivo131718. It had been hypothesized that global in vivo labeling of newly synthesized murine proteins using AHA and HPG would be infeasible due to the 390–500-fold higher affinity of methionine for the Met tRNA192021. However, recent studies showed local incorporation from intraocular injections in the rat and global incorporation by feeding mice a specialized chow in which methionine was replaced with AHA2223. Here, we extend these studies by demonstrating that AHA and HPG can be globally incorporated into the proteome of mice through facile intraperitoneal injections. These non-canonical amino acids (ncAAs) are incorporated into all tissues investigated in juvenile mice and are robustly integrated into the embryo, without disrupting development, when injected into pregnant dams. Our results indicate that ncAA labeling is a promising new tool that can be used to characterize the dynamics of protein synthesis and turnover at particular time points during embryonic development. Results In vivo incorporation of AHA and HPG into murine tissues To establish the feasibility of BONCAT labeling in vivo, juvenile mice (25–35 days old; 14–20 g) were injected intraperitoneally (IP) with 0.1 mg/g per day AHA, HPG or vehicle alone (PBS; Fig. 1D). Tissue lysates were reacted with either a AF555-conjugated alkyne or azide using CuAAC and resolved using SDS-PAGE (Fig. 1D). All murine tissues investigated incorporated AHA and HPG (Fig. 2). In addition, the rate of AHA and HPG incorporation was dose dependent. Mice were injected with 0.1, 0.05 and 0.025 mg/g per day and there was a clear dosage-dependent increase in AHA and HPG incorporation (Fig. 2). Metabolic labeling of embryos in situ To test if methionine analogs could be used to label newly synthesized proteins in developing embryos, time-mated females were injected IP with 0.1 mg/g per day AHA or vehicle alone (PBS) for two days, starting at E10.5. Lysates of E12.5 embryos showed strong AHA incorporation compared with lungs from the dam (Fig. 3A). Embryos from AHA-injected dams were viable as indicated by a persistent heartbeat after removal from the uterus (Fig. 3B). The intensity profiles of the total protein content of AHA and PBS samples were compared by line trace intensity analysis to qualitatively evaluate if protein expression was altered (Fig. 3C). There did not appear to be a substantial change in total protein expression as a result of AHA administration. To assess if AHA was homogenously incorporated into the proteome, a line trace (Fig. 3C) of the fluorophore-conjugated lysates was compared with the total protein (lane 2, Fig. 3A). While the baseline intensity of the line trace for the fluorescent and total protein was not consistent along the lane, the peak intensities occurred at the same molecular weights. Additional dams injected with AHA between E10.5–12.5 were allowed to carry their litters to term. Parturition occurred when expected and P10 and P22 pups displayed the appropriate weight and physical markers (Fig. S1). As the pups matured, no behavioral or physical differences between AHA and control litters were noted (casual observation). Indeed, mice from AHA and control litters continued to develop as expected beyond 6th months (as of submission date). Overall, these data indicate that AHA administration does not perturb development during this time window in which many critical tissues are actively assembling (Fig. 3). AHA administration does not substantially change the proteome of developing mice Biological replicates from PBS and AHA pregnancies were compared to determine if the proteome of the developing embryo was affected by 2 days of AHA treatment. Two bands corresponding to robust fluorescent labeling were chosen from AHA samples and the PBS controls (Fig. 3A), and analyzed using LC-MS/MS. Only proteins present in both technical replicates were considered for subsequent analysis. Of the 246 unique proteins found in band 1, 89% (220) were present in both the AHA and PBS samples, and only 10% of those 220 proteins showed significantly different levels of expression (p > 0.05; Fig. 4). Similarly, for band 2, 88% (246) of proteins were present in both the AHA and PBS samples, and only 5.7% showed significantly different levels of expression (p > 0.05; Fig. 4). When considering a more stringent threshold, *p > 0.01, the number of proteins in bands 1 and 2 that were significantly drops to 2.7% and 1.7%, respectively (Fig. 4B, Table S1). Discussion Due to the low propensity of AHA and HPG for the Met tRNA compared with endogenous Met, it has been thought that it would not be feasible to supply enough for in vivo incorporation192021. However, we demonstrate that AHA and HPG administered IP will globally incorporate into the proteome of juvenile mice and developing embryos. To estimate how much more AHA than Met was in our test animals, we first calculated the total amount of Met in the body fluid of a mouse. The concentration of free Met in the plasma of C57BL6 mice ranges from 20–80 μM2425. If it is assumed that the concentration of free Met is the same in all body fluids, and taking in to account that 58% of the weight of a mouse is water26, a 20 g mouse will be comprised of 11.6 mL of fluid that contains 50 μM Met. Using the MW of free Met (149.21 g/mol), there is approximately 4.4 μg free Met per gram of total mouse weight. Therefore, when injecting 0.1 mg/g, there will be 20-fold more AHA/HPG than Met. How AHA/HPG is metabolized, and the identity of the resultant degradation products, remains unknown and will warrant further investigation as these ncAAs become more widely implemented in vivo. Excess systemic ncAAs and their metabolites have the potential to induce pathological states similar to what has been shown with naturally occurring amino acids such as hyperhomocysteinemia (excess Met)27. Nevertheless, data from numerous in vitro and in vivo reports910131718, in addition to our in vivo demonstration that AHA does not disrupt mammalian development (Fig. 3), indicate that short term administration of ncAAs has minimal adverse effects. Protein banding patterns between AHA/HPG and control tissue lysates were consistent, suggesting normal physiological function was maintained. It appears that HPG is incorporated to a lower extent than AHA, which correlates with previous findings in vitro that HPG charges onto the Met tRNA at a slower rate than AHA21. Overall, our data demonstrate the feasibility of systemic administration and labeling of other ncAAs that can be utilized by endogenous tRNA synthetases, such as homoallylglycine28. When the proteomes of control and AHA-treated embryos were analyzed, components involved in protein folding and ER stress were found in the AHA only replicates (Pdia6, Nap1l4, Cct3, Cct7) or showed significant upregulation when compared with PBS injected controls (Dnaja2, Ruvbl2, Psmd5, Pdia6) (Table S1). One differentially expressed protein, Pdia6, a member of the protein disulfide isomerase family, was identified in band 1 in the AHA sample only, and in band 2 as a significantly upregulated protein in AHA compared with PBS. Pdia6 is expressed during times of ER stress and is thought to help attenuate the unfolded protein response via mechanisms independent of disulfide bond forming activity2930. However, the differential expression may be due to interspecimen variability as Pdia6 is found in the E11.5 murine lung and has been shown to be essential during C. elegans development3031. It is not unexpected that components involved in protein folding show a difference in expression between the two treatments, given the differences in side chain chemistry between Met and AHA (Fig. 1A). What is surprising is the how little overall effect AHA treatment has on the identity and quantity of proteins. This corroborates our observation that AHA treatment does not overtly disrupt embryogenesis or subsequent development after parturition. Additional biochemical tools that have been shown to label newly synthesized proteins in vivo include stable isotope labeling with amino acids in cell culture (SILAC) and incorporation of puromycin derivatives into nascent proteins193233. SILAC uses amino acids with stable isotopes that can be used to resolve newly synthesized proteins using LC-MS/MS; however, it is not possible to identify proteins in low abundance without additional costly protein/peptide fractionation. Comparative experiments have shown that SILAC-based measurements identify approximately an order of magnitude fewer newly synthesized proteins than when enriched using BONCAT934. Incorporation of puromycin derivatives can be used for enrichment with antibody pull-down or CuAAC1932. A limitation of these methods is that protein synthesis stops upon puromycin incorporation, reducing the biological activity of the truncated proteins and preventing their utility for long term labeling. In contrast to these methods, BONCAT enables the enrichment of newly synthesized proteins within complex mixtures91034 and does not overtly perturb protein synthesis levels as demonstrated in vitro10, in vivo13 and in this study. Our successful demonstration that AHA and HPG can be directly administered in vivo for labeling of newly synthesized proteins will enable future studies that seek to characterize the dynamics of protein synthesis and turnover as a function of development and disease in a mammalian system. Materials and Methods Unless otherwise specified, all reagents were of chemical grade from Sigma-Aldrich. Animal care Wild-type C57BL6 mice were used in this study, derived from animals obtained from The Jackson Laboratory. All experimental protocols were performed in accordance with the guidelines established by the Purdue Animal Care and Use Committee, and all methods were approved by this committee (PACUC; protocol# 1209000723). PACUC ensures that all animal programs, procedures, and facilities at Purdue University adhere to the policies, recommendations, guidelines, and regulations of the USDA and the United States Public Health Service in accordance with the Animal Welfare Act and Purdue’s Animal Welfare Assurance. IP injection of AHA/HPG AHA and HPG (Click Chemistry Tools) were diluted in PBS, raised to pH 7.4 with NaOH, sterilized with a 0.22 μm filter and stored at −20 °C. Newly weaned male and female pups (21–35 days old; 14–20 g) were injected IP daily for two days with 0.1 mg/g, 0.05 mg/g or 0.025 mg/g AHA or HPG in a volume of 50–200 μL. Females were time mated, where noon of the day of the recorded plug was considered to be E0.5 and injected with 0.1 mg/g per day AHA for two days, starting at E10.5. Mice were euthanized via CO2 inhalation, and samples from heart, lung, brain, skeletal muscle, kidney and whole embryos were obtained. BONCAT Labeling of AHA/HPG injected tissues Tissues (10–50 mg) were homogenized in 2 mL ice cold lysis buffer (150 mM NaCl, 1% Triton X-100, 0.1% SDS and 50 mM Tris in H2O) using a Qiagen Tissue Ruptor and rocked at 4 °C for 2 hours. Lysates were centrifuged at 18,000 × g for 10 min at 4 °C and the soluble fraction was removed for analysis and stored at −80 °C. Protein concentration was quantified using the Pierce 660 nm Protein Assay. AHA and HPG incorporated proteins within the lysates were labeled selectively with AF555-conjugated alkyne or azide using CuAAC, following353637. Soluble protein lysate from AHA, HPG, and PBS samples (60 μL of 1.5–4 μg/μL lysate) was combined with 10 μL 400 mM sodium ascorbate, alkylated by the addition of 20 μL 0.5 M iodoacetamide and incubated for 5 min. The following were added, with vortexing after each addition: 0.5 μL 8 mM alkyne/azide-labeled fluorophore, 16 μL 25 mM CuSO4, 40 μL 50 mM tris(3-hydroxypropyltriazolylmethyl)amine (Click Chemistry Tools), and 40 μL 100 mM aminoguandine (pH 7). The final mixture was rotated end-over-end for 15 min at room temperature and protected from light. Unreacted dye was removed using methanol-chloroform precipitation and the protein pellets were air dried for at least 30 min. Pellets were resolubilized in 1X Laemmli Sample Buffer (Bio-Rad, CA) with 5% β-mercaptoethanol and boiled at 95 °C for 5 min, then desalted with 0.5 mL 7K MWCO Zeba Spin Desalting Columns (ThermoFisher). Samples were brought to a 1X concentration of Laemmli buffer and protein concentration was again determined using Pierce 660 nm Protein Assay to ensure equal loading before resolving by SDS-PAGE on 4–20% polyacrylamide gels (BioRad, CA) and imaged using an Azure Biosystems c400. Images were false-colored green to facilitate visualization. Loading consistency was confirmed by staining the gels with Coomassie Blue-based GelCode Blue Protein Stain (Pierce) after fluorescent imaging. LC-MS/MS analysis of embryo lysates Proteins were size separated with SDS-PAGE and bands were carefully cut out to ensure that the same bands for AHA and PBS samples were excised with no cross contamination. Bands were subject to in gel digestion with trypsin and the resultant peptides were desalted and pre-concentrated using C18 StageTips. Proteomic analysis was performed with LC-MS/MS using the ABSciex Triple TOF 5600 coupled to the Eskigent Nano425 LC. Protein identification was performed using the MaxQuant and Protein Pilot algorithms along with manual validation. Additional Information How to cite this article: Calve, S. et al. Incorporation of non-canonical amino acids into the developing murine proteome. Sci. Rep. 6, 32377; doi: 10.1038/srep32377 (2016). Supplementary Material Supplementary Information Supplementary Table S1 The authors want to thank Dr. Uma Aryal and the Purdue Proteomics Facility for assistance in LC-MS/MS analysis and Gabrielle Mitchell for lab assistance. This work was supported by the National Institutes of Health [R03 AR065201 to S.C.] and the Indiana Clinical and Translational Sciences Institute [#106564 to S.C.]. Author Contributions S.C. and T.L.K.-U. conceived of the experiments. S.C., T.L.K.-U. and A.W. designed the experiments. S.C., T.L.K.-U., A.W. and A.O. performed the experiments and analyzed and interpreted the data. S.C. and T.L.K.-U. wrote the manuscript. All authors critically reviewed the manuscript. Figure 1 Metabolic labeling with non-canonical amino acids. (A) Amino acids in use in this study: Methionine (Met), Azidohomoalanine (AHA), Homopropargylglycine (HPG). (B) Peptides and proteins that naturally contain Met will instead be synthesized with AHA or HPG in the place of Met. (C) Newly synthesized proteins that have incorporated HPG (blue ribbon) are labeled with a fluorophore-conjugated azide (red star). Copper-catalyzed azide/alkyne cycloaddition results in a stable triazole adduct. (D) Mice were injected with varying amounts of ncAA for two days. Tissues were harvested, solubilized, reacted with azide- or alkyne-conjugated fluorophore then analyzed with SDS-PAGE. Figure 2 Systemic and dose-dependent incorporation of non-canonical amino acids (ncAA) in murine tissues. (A) Juvenile mice were injected IP with 0.1 mg/g per day with AHA, HPG or PBS for two days and heart (H), lung (L), brain (B), skeletal muscle (M) and kidney (K) lysates were compared. (B) Brain lysates from juvenile mice injected with 0.025–0.1 mg/g AHA, HPG or PBS. Tissue lysates were labeled with fluorophore-conjugated azide or alkyne, resolved using SDS-PAGE, fluorescently imaged then stained for total protein with Coomassie Blue to confirm equal loading. Representative results from N ≥ 3 independent experiments. Figure 3 AHA is robustly incorporated into the developing murine proteome. (A) Dams injected with 0.1 mg/g per day for 2 days incorporated AHA into the developing embryos and their own tissues; however, the latter was much lower as indicated by the need for contrast enhancement (L = lung). Tissue lysates were labeled with fluorophore-conjugated alkyne, resolved using SDS-PAGE, fluorescently imaged then stained for total protein with Coomassie Blue to confirm equal loading. Representative results from N ≥ 3 independent experiments. Arrows indicate the bands excised for proteomics analysis described in Fig. 4. (B) Age matched embryos from control and AHA-injected dams show no difference in size and protein banding pattern (A). (C) Intensity tracings of the total protein bands in lanes 2 (AHA) and 3 (PBS) show that overall protein expression was not changed by AHA administration. Fluorescence intensity of proteins in lane 2 (dotted line) reveals that peaks occur in the same locations as in the total protein (solid lines). Representative results from N ≥ 3 pregnancies. Figure 4 AHA administration minimally impacts the embryonic proteome. Two bands at ~42kDa and 48kDa with high levels of AHA labeling (arrows Fig. 3A) were digested in-gel and analyzed using LC-MS/MS. (A) The majority of proteins present in AHA and PBS samples were identified in both populations (top, Table S1). Of the proteins expressed in both AHA and PBS, only 5–10% showed significantly different levels of expression as analyzed using MaxQuant (p < 0.05, bottom). (B) Heat map indicating the identities and log2-fold difference in expression of all proteins differentially expressed in bands 1 and 2. ==== Refs Choudhary C. & Mann M. Decoding signalling networks by mass spectrometry-based proteomics . Nat Rev Mol Cell Biol 11 , 427 –439 (2010 ).20461098 Sun L. . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3235510.1038/srep32355ArticleFormation of oxygen vacancies and Ti3+ state in TiO2 thin film and enhanced optical properties by air plasma treatment Bharti Bandna 1Kumar Santosh 2Lee Heung-No 3Kumar Rajesh a11 Jaypee University of Information Technology, Waknaghat, Solan-173234, H.P., India2 School of Materials Science and Engineering, Gwangju Institute of Science and Technology (GIST), 123 Cheomdangwagi-ro Buk-gu, Gwangju, 61005, South Korea3 Gwangju Institute of Science and Technology (GIST), 123 Cheomdangwagi-ro Buk-gu, Gwangju, 61005, South Koreaa rajesh.kumar@juit.ac.in30 08 2016 2016 6 3235503 05 2016 03 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/This is the first time we report that simply air plasma treatment can also enhances the optical absorbance and absorption region of titanium oxide (TiO2) films, while keeping them transparent. TiO2 thin films having moderate doping of Fe and Co exhibit significant enhancement in the aforementioned optical properties upon air plasma treatment. The moderate doping could facilitate the formation of charge trap centers or avoid the formation of charge recombination centers. Variation in surface species viz. Ti3+, Ti4+, O2−, oxygen vacancies, OH group and optical properties was studied using X-ray photon spectroscopy (XPS) and UV-Vis spectroscopy. The air plasma treatment caused enhanced optical absorbance and optical absorption region as revealed by the formation of Ti3+ and oxygen vacancies in the band gap of TiO2 films. The samples were treated in plasma with varying treatment time from 0 to 60 seconds. With the increasing treatment time, Ti3+ and oxygen vacancies increased in the Fe and Co doped TiO2 films leading to increased absorbance; however, the increase in optical absorption region/red shift (from 3.22 to 3.00 eV) was observed in Fe doped TiO2 films, on the contrary Co doped TiO2 films exhibited blue shift (from 3.36 to 3.62 eV) due to Burstein Moss shift. ==== Body Among various metal oxide semiconductors, TiO2 is considered as a prime candidate due to its many peculiar properties12 for diverse applications. It is the most suitable candidate for photocatalytic applications due to its biological and chemical inertness, strong oxidizing power, non-toxicity and long term stabilization against photo and chemical corrosion3. The films of TiO2 have valuable applications in LEDs, gas sensors, heat reflectors, transparent electrodes, thin film photo-anode to develop new photovoltaic, photo-electrochemical cells, solar cells and water splitting45678910. In anodic applications, it is a preferred material because of its low density/molar mass and structural integrity over many charge and discharge cycles11. However, the efficiency of pure TiO2 is substantially low because of its wide band gap and fast recombination of photo-generated electrons and holes. The key issue to improve the performance of TiO2 relies on efficient light harvesting, including the increase of its photo-efficiency and expansion of photo-response region, and to ensure efficient number of photo-generated electrons and holes reaching to the surface before their recombination. In order to meet these desired performances the bands structure modification of TiO2 is preferred. Generally, three fundamental approaches are implemented for band structure modification viz. doping with metallic/non-metallic elements or co-doping of metallic and non-metallic elements1121314, modification via introducing defects such as oxygen vacancies and Ti3+ in the band gap1516, and surface modification by treatment methods11171819. In metallic doping, among the range of dopants such as Ni, Mn, Cr, Cu, Fe etc.320212223, the Fe is found most suitable due to its half filled electronic configuration. Similarly, from non-metallic dopants S, C, F, N etc.24252627, the N is preferred. In the case of metallic dopants, there are some contradictory reports that show disadvantages of thermal and chemical instability of TiO2. Also, their high doping although enhances the band gap but at the same time reduces optical/photocatalytic activity because of increasing carrier recombination centers28293031. What is the mechanism of observed photo-response of doped/modified TiO2; it is still a question, however a generally accepted concern states that the photo absorption of a material is explained better by introducing the defects in the lattice of TiO2. For example, Ti3+ and oxygen vacancies32 create trap centers, rather than the recombination centers unlike the high doping case, and results in the variation of band gap of pristine TiO2. On the other hand, surface modification methods including surface hydrogenation33, vacuum activation32 and plasma treatment34 are also practiced. In the hydrogenation method, the surface of TiO2 is terminated with hydrogen leading to an enhanced photocatalytic activity35 in visible region; however, it is still unknown that how does the hydrogenation modify a surface to enhance its optical performance (photocatalytic activity)36. The drawback of the hydrogenation method is that it requires high temperature and the obtained TiO2 sample/film are black35, which makes the films unable for many optoelectronic applications, such as a transparent electrode in optoelectronic devices. Both the vacuum activation and plasma treatment methods create highly stable Ti3+ and oxygen vacancies3234. In vacuum activation method, the sample may exhibit higher absorption intensity but it appears brown in color35, that makes it unable for transparent electrode applications. Finally, in case of plasma treatment methods, generally hydrogen gas is used to create Ti3+ and oxygen vacancies in TiO2, but it is always avoidable to use such a hazardous and expensive gas. Except hydrogen there are few reports on the use of argon37, oxygen38 and nitrogen plasma39 for surface modification of TiO2. We know that the implementation of gas in the treatment chamber may be hazardous and cost effective; therefore, it is always required to avoid the use of hazardous gas, and to implement a simple and low cost approach to meet the requirements. In this regard, treatment by air plasma may be an effective approach. However, to the best of our knowledge there is no report on the application of air plasma for the surface modification of TiO2 film. In this report, the band structure modification of thin transparent films of TiO2 was done by implementing simply the air plasma and thus creating Ti3+ and oxygen vacancies in TiO2 films. The effect of air plasma treatment was studied in conjunction with metallic doping. First, Fe and Co doped TiO2 thin films were formed on glass substrate, which were subsequently treated in air plasma. Considering the drawback of high metallic doping (formation of recombination centers), in this study, a moderate amount of dopants were used to enhance the optical properties of TiO2 thin film and thereafter the air plasma was applied to enhance them further. The moderate amount of metallic dopant not only favors the separation of electrons and holes but also narrows the band gap of TiO23. We observed that simultaneous effect of the joint approaches increases photo absorbance as well as expends photo response region of the films towards both the visible and UV spectrum. The doped films of TiO2 were treated in plasma with varying treatment time. The moderate doping of Fe and Co elements reduces band gap minutely in both the cases, but when treated with air plasma a significant change in the optical properties was observed due to the formation of Ti3+ and oxygen vacancies in the band gap. Results and Discussion After fabricating, the thin films of pure TiO2, Fe and Co doped TiO2 were treated in air plasma for 0, 10, 30 and 60 seconds, which were analyzed for surface morphology and crystal structure variations using SEM (see Supplementary Information; Figure S1) and XRD. Here we show XRD pattern of doped thin films for extreme treatment time 0 and 60 seconds (for XRD spectra of samples treated at other treatment time, please see Supplementary Information; Figure S2). Figure 1(a,b) represents XRD pattern of Fe doped, and Fig. 1(c,d) represents XRD pattern of Co doped TiO2 thin films for 0 (untreated) and 60 seconds of plasma treatment time. Since there is no detection of Fe and Co signals, it indicates that all the Fe and Co ions in the respective samples gets incorporated into the structure of TiO2 by replacing some of Ti ion, and occupying the interstitial sites40. Absence of sharp peak in XRD patterns represents amorphous phase of TiO2 thin films41. After plasma treatment 2θ angle and FWHM of the peaks remain almost unchanged, indicating negligible effect on the film structure. XRD indicates that plasma treatment does not create any change in the crystal structure of Fe and Co doped TiO2 thin films. The obtained low signal-to-noise ratio in the above XRD spectra is due to the low crystallinity of the films and small crystallite size; such observations have been reported by others as well42. The presence of atomic percentage of the dopants in TiO2 thin films was detected by EDX signals (see Supplementary Information; Figure S3). The EDX of Fe doped TiO2 film shows the atomic percentage of Fe, Ti and O as 1.66%, 12.93% and 85.41%, respectively, which closely matches to the stoichiometry of elements in Ti0.95Fe0.05O2. Similarly, in case of Co doped TiO2, the obtained atomic percentage of Co, Ti and O in EDX are 1.33%, 23.33% and 75.35%, respectively, which confirms the stoichiometry of elements of Ti0.95Co0.05O2 thin film. Variation in optical properties of TiO2 thin films by doping and subsequent air plasma treatment was analyzed by UV-Vis spectrophotometer. The change in absorption edge and corresponding band gap is mentioned in Table 1. Pure TiO2 film (undoped and untreated) showed absorption edge at 367 nm and band gap 3.37 eV, whereas Fe doped TiO2 film showed a shift in the absorption edge to 385 nm, with a decreasing in the band gap to 3.22 eV. Similarly, Co doping shifts the absorption edge from 367 nm to 369 nm with a reduction in the band gap to 3.36 eV. The observed red shift in absorption edge and narrowing band gap in both dopants cases is similar to other reports on metallic doping3. In both the cases, samples were doped with a moderate (5%) concentration of Fe and Co forming Ti0.95Fe0.05O2 and Ti0.05Co0.05O2, respectively. We could have tuned the optical properties further by increasing the dopant concentration but that would form recombination centers28; therefore, to avoid the formation of recombination centers, a further tuning in the optical properties was done by treating these moderately doped TiO2 films in air plasma. The films were treated in air plasma for treatment time (0, 10, 30 and 60 seconds), and investigated for the shift in absorption edge and band gap variation. With increasing treatment time, the absorption edge of Fe doped TiO2 films shifts continuously from 385 nm (for 0 seconds treatment time) to 413 nm (for 60 seconds treatment time), with a corresponding band gap change from 3.22 eV to 3.00 eV, showing a significant increase in the absorption region. In case of Co doped TiO2 films, the absorption edge shifts from 369 nm to 342 nm (for 60 seconds treatment time) with a corresponding band gap change from 3.36 to 3.62 eV, which shows an increase in the optical band gap/UV absorption region probably due to the Burstein-Moss effect43, explained latter. From the Table, it is observed that the change in optical properties of TiO2 films appears at two levels; first by the doping of Fe and Co, and then by plasma treatment. However, here it should be noted that the change in the band gap due to the doping is smaller as compared to the subsequent band gap change by plasma treatment. While discussing the effect of doping on the change of band gap, we know that the reduction may take place due to either by the increasing grain size of highly crystalline sample44 or the formation of electronic energy levels within energy band gap45. In our study, since the XRD results showed the samples to be amorphous, thus the first reason can be discarded. Therefore, Fe3+ and Co2+ ions substitute Ti4+ ions in TiO2 matrix and cause a change in the band gap by forming their mid gap energy levels in the respective samples along with the formation of Ti3+ and oxygen vacancies. The electronic transition from valance band to dopant level and then from dopant level to conduction band, and/or from valance band to oxygen level and then form oxygen level to Ti3+ level/dopant level effectively cause a red shift in the absorption edge, showing reduced band gap464748. In many cases, the localized level of t2g state of the doping element even lies in the middle of band gap (in case of, Cr, Mn or Fe as the doping materials), and at the top of the valance band (when Co is used as a dopant)49. Next, the variation in the absorption edge/band gap with plasma treatment time is due to the increase of Ti3+ and oxygen vacancies, detailed discussion is given under XPS studies in the following section. Figure 2 shows variation in the absorption spectra of Fe doped TiO2 thin film treated for 60 seconds of time (Fig. 2(b)) with respect to untreated one (Fig. 2(a)) (to see the increase in the absorption edge and reduction in band gap, please refer to Supplementary Information; Figure S4). There is a continuous change in the absorbance, absorption edge and band gap of the films with plasma treatment time. The absorbance of the film increased from 60% (untreated film) to 87% (treated for 60 seconds) along with a red shift in the absorption edge and band gap narrowing by 0.22 eV (Tauc plot shown in the inset of Fig. 2(b)). The band gap and absorption edge were estimated using the following equations50: where α is absorption coefficient and Eg is band gap energy. Similarly, the variation in absorption spectra of Co doped TiO2 thin film treated for 0 and 60 seconds is shown in Fig. 3(a,b) (details of other samples is given in Supplementary Information; Figure S5). In this case, doping shows a red shift due to the presence of Co levels in the energy gap of TiO2, whereas after plasma treatment the film shows continuous blue shift with increasing treatment time. This overall shift (due to treatment in plasma for 60 seconds) in the band gap is 0.26 eV. The observed blue shift can be explained by Burstein-Moss effect43, resulted by the change in the position of Fermi level into the conduction band. General equation representing enhancement in the band gap energy is given by: where and are the effective mass of hole and electron in the respective bands, and KFis Fermi wave vector. In our case, the shift of Fermi level into the conduction band leads to the energy band widening. Absorption edge shifts to shorter wavelength region due to the increase in the carrier concentration, which is discussed in XPS studies section. The overall variation in the absorption edge and band gap of TiO2 thin film due to the doping (Fe and Co) and air plasma treatment is plotted in Fig. 4. In the plasma treatment region, a remarkable change in the band gap values can be observed with treatment time. XPS study In order to understand the mechanism resulting the change in the band gap of Fe and Co doped TiO2 films with plasma treatment time, the films were investigated by XPS. The XPS being surface sensitive technique provides information about the change in chemical state of film constituting species. Here, the variation in the chemical state of elements ‘O’ and ‘Ti’ with plasma treatment time was analyzed in detail to correlate it with the observed variations in the band gap of the films. Figure 5(a,b) shows XPS survey spectra of untreated and plasma treated Fe and Co doped TiO2 thin films, respectively. In these spectra, C1s is probably an instrumental impurity. The intensities of O1s and Ti2p peaks increase with the increasing plasma treatment time, indicating an increase in these states with treatment time. Figure 6(a) shows high resolution XPS spectrum of pure TiO2 film. In this spectrum, the doublet ‘Ti2p3/2 (binding energy 458.6 eV) and Ti2p1/2 (binding energy 464.4 eV)’ arises from spin orbit-splitting. These peaks are consistent with Ti4+ in TiO2 lattice51. Also, the shoulder Ti2p1/2 at binding energy 460.2 eV is corresponding to Ti3+ 52 in Ti2O3. This indicates that both TiO2 and Ti2O3 are formed in the film (Without deconvolution, the XPS spectra are shown in Supplementary Figure S6). After doping with Fe, the high resolution XPS spectrum (Fig. 6(b)) shows a slight shift in the position along with a variation in the area of the original peaks. The peaks in the Fe doped samples are now located at binding energies 458.4 (Ti2p3/2), 464.3 eV (Ti2p1/2) and 459.0 eV (Ti2p1/2), respectively (see Supplementary Information; Table S1). The shift in the position of these peaks indicates an influence of Fe addition on the electronic state of Ti element; probably some of the Ti ions get substituted with Fe ions in the lattices. After doping, the area of Ti3+ peak increased by 81% and that of the peak Ti4+ decreased by 19%. The increase in the area of Ti3+ peak indicates that either Ti2O3 is formed in large amount or some mixed oxide structure with Fe (having oxidation state Ti3+) is formed after doping. Meanwhile, the decreasing area of Ti4+ indicates a reduction of TiO2 in the sample, and probably formation of Ti-O-Fe structure in the TiO2 lattice through the substitution of transition metal ions. Observed shift in the peaks also indicates interaction between Ti and Fe atoms and an overlapping of their 3d orbital53. This causes an electronic excitation from Fe to Ti in the optical absorption experiment, which shows a reduction in the band gap of Fe doped TiO2 film (as observed in the optical analysis). After doping, the film was treated in air plasma. In the XPS results, only the sample which was treated for 60 seconds in plasma is demonstrated. The XPS shows a further increase in the peak corresponding to Ti3+ at 459.0 eV (Fig. 6(c)) and a decrease in the peak area of Ti4+. The change in stoichiometry was estimated by the change in the area of relative peaks. The peak area of Ti3+ increases by 20% and that of Ti4+ decreases by 12%. The increase in the peak area of Ti3+ indicates that after plasma treatment there is removal of oxygen from the lattice, which shows a relative increase in Ti3+ in the XPS spectrum. On the other hand decreasing peak area of Ti4+ is inferred due to the reaction of Ti4+ with electrons coming either from plasma or due to the formation of oxygen vacancies in the surface layer generated by the plasma treatment41. Now, as observed in optical analysis, the band gap of Fe doped films (3.22 eV) decreased to 3.00 eV (for 60 seconds of treatment time), this is correlated with the increasing career/electrons density due to plasma treatment. As we know that in the doped samples, the possible reasons of red shift/decreasing band gap is the introduction of donor states in the energy gap (here oxygen vacancies and Ti3+, Table 1). In the present case, the band gap decreases further with increasing treatment time, while the concentration of the dopant was kept constant, which is due to the change in the surface states of the constituents i.e. Ti element and oxygen vacancies. Next, the O1s spectrum of pure TiO2 thin film is shown in Fig. 6(d), which is fitted with three peaks. The peaks at binding energies 529.9 eV, 530.3 eV and 531.3 eV are attributed to lattice oxygen, Ti2O3 and non-lattice oxygen5455. Similarly, for the doped sample, O1s spectrum of Fe doped TiO2 thin film fitted with two peaks is shown in Fig. 6(e). In this spectrum, only two peaks at binding energies 529.8 eV, and 531.9 eV are observed which are attributed to lattice oxygen and surface adsorbed OH group, whereas the peak 530.3 eV corresponding to Ti2O3, disappears. This indicates that in the doping process TiO2 is formed along with some mixed oxide. Again, the change in stoichiometry was estimated by the change in area of relative peaks. In case of Fe doped TiO2 film, the area of the peak at 529.7 increases by 64% and that of the peak at 531.5 eV increases by 54%. After plasma treatment, the binding energy of lattice oxygen (O in TiO2) shifts slightly from 529.8 eV to 529.7 eV (Fig. 6(f)), whereas its area increases by 35%. Also, the area of the peak at 531.5 eV (non-lattice oxygen/OH) increases by 15% (see Supplementary Information; Table S1). The increase in the area of non-lattice oxygen indicates the formation of oxygen vacancies in the lattice. This result is analogues to the XPS spectrum of Ti2p (Fig. 6(c)). Fe doping results in a minor shift in the binding energy, indicating that Fe ions are better dispersed in the substitutional sites of TiO2 lattice and produce more mixed oxide structure, probably Fe-O-Ti. Figure 7(a) shows high resolution XPS spectrum (for Fe2p3/2) of Fe doped TiO2 film. After plasma treatment, the high resolution XPS spectrum of Fe2p3/2 is shown in Fig. 7(b). These spectra are fitted with Gauss–peak shapes as shown in Fig. 7(c,d). The deconvoluted XPS spectrum of Fe2p3/2 (Fig. 7(c,d)) contains main peaks at 710.1 eV and 724.6.1 eV corresponding to Fe2p3/2 and Fe2p1/2, respectively (see Supplementary Information; Table S2). The appearance of these peaks supports the presence of Fe in Fe3+ ionic state55. Further, after plasma treatment the shift in the binding energy of Fe2p3/2 from 710.1 eV to 711.3 eV also indicates the presence of Fe3+ species, irrespective of the particular oxide (i.e., Fe2O3, Fe3O4, and FeOOH). Shake up satellite at 716.9 eV also supports that Fe is presented in Fe3+ state (oxide)56. These shake-up satellites are associated with Fe3d-O2p hybridization. Thus XPS analysis confirmed that Fe ions are doped into TiO2 matrix in the form of Fe-O-Ti. From the XPS analysis, we confirmed that by increasing the plasma treatment time the concentration of Ti3+ and oxygen vacancies also increases. The Co doped samples after treating in plasma show adverse effect on the band gap of the doped TiO2 film. In this case, band gap increases with the increasing treatment time as observed in optical studies. To investigate this divergent behavior, the samples were analyzed via XPS, Fig. 8 shows high resolution spectra. Figure 8(a) shows the XPS spectrum of pure TiO2, and Fig. 8(b) shows XPS for Co doped sample. As discussed above in the case of Fe doped sample, the XPS of pure TiO2 is also fitted with three peaks corresponding to titanium dioxide (Ti4+) and titanium sub oxide (Ti3+) in Ti2p1/2 and Ti2p3/2, respectively. These peaks are fitted as Ti4+2p1/2 at 464.4 eV, Ti4+2p3/2 at 458.6 eV, and Ti3+2p3/2 at 460.2 eV. The line separation between Ti2p1/2 and Ti2p3/2 is 5.8 eV, which is consistent with the standard binding energy of TiO251. However, in this case the Ti2p spectrum (Fig. 8(b)) is fitted with four peaks as 464.4 for Ti4+2p1/2, 458.6 eV for Ti4+2p3/2, 460.4 for Ti3+2p3/2 and 457.9 eV for Ti3+2p1/257, respectively (see Supplementary Information; Table S1). In comparison to the pure TiO2, the area of Ti3+ peak in Co doped TiO2 increases by 26%, while that of the peak Ti4+ decreases by 7%, indicating a reduction in the formation of TiO2, which is similar to the case of Fe doped samples. After the plasma treatment (Fig. 8(c)), binding energies of the mentioned peaks are shifted slightly to the positions such as 464.3 eV (Ti4+2p1/2), 458.5 eV (Ti4+2p3/2), 460.6 eV (Ti3+2p3/2) and 457.4 eV (Ti3+2p1/2), respectively. The change in stoichiometry was estimated by the change in peak area of respective peaks. After plasma treatment, while investigating for peak area, we observed that the peak area of Ti3+ increases by 30%, whereas the peak area of Ti4+ decreases by 12%. Again, this is expected due to the reaction of Ti4+ with the electrons coming either from plasma or due to the formation of oxygen vacancies in the surface layer by the plasma treatment. Further, the high resolution O1s XPS spectrum obtained for Co doped sample is shown in Fig. 8(d–f). The spectrum is fitted with three peaks i.e. 529.9 eV, 530.3 eV and 531.6 eV that correspond to lattice oxygen of TiO2, oxygen in Ti2O3 and non-lattice oxygen, respectively. The change in stoichiometry was estimated by change in the peak area of relative peaks. With the doping of Co, the lattice oxygen (corresponding to TiO2) peak at 529.9 shifts to the position 530.3 eV, and the area of the peaks at 530.3 eV and 531.6 eV increases by 51% and 24%, respectively. The original peak at 530.3 eV (Fig. 8(d)) corresponding to Ti2O3 disappears after doping (Fig. 8(e)), which is due to the formation of mixed oxide structure. Further, with the increasing treatment time, the areas of the peaks at 530.3 eV and 531.6 eV ((Fig. 8(f)) also increases by 24% and 25%, respectively. (To explain in a more quantitative manner we have tabulated all the data in a table by comparing all the peaks at different plasma treatments time, see Supplementary Information; Table S1). Next, Fig. 9(a) corresponds to high resolution XPS spectra of Co2p region of Co doped TiO2 thin films and Fig. 9(b) shows high resolution XPS spectra with plasma treatment. Figure 9(c,d) represent deconvoluted XPS spectra of doped TiO2 and plasma treated TiO2 thin films, respectively. The core level binding energies of peaks Co2p1/2 and Co2p3/2 are 796.9 eV and 781.0 eV, respectively. The satellite peaks at 787 eV and 802 eV reveal high spin Co(II) state with complex transitions58. These results are an indication that Co does not precipitate as metallic Co on the film surface. After plasma treatment, the satellites peaks shifts slightly to the 785.3 eV and 802.3 eV. Also, the binding energies of Co2p1/2 and Co2p3/2 are shifted to 796.6 eV and 781.2 eV, respectively (see Supplementary Information; Table S1). These spectra are typical of compounds containing high-spin Co2+ ions5960, reveling the presence of CoO(Co2+), CoTiO3 (Co2+), Co2O3 (Co3+) or mixed valence Co3O4 (Co2+ and Co3+) in the surface. The presence of strong satellites indicates that Co atoms in the doped TiO2 film are in 2+ oxidation state, referring the possible formation of CoO or CoTiO3 inside the film. Now we discuss the probable reason of band gap narrowing in TiO2 film with Fe doping, and widening in the case of Co doping after plasma treatment. As reported, the iron dopant acts as an acceptor impurity in TiO2 lattice61. Thus when the TiO2 film is doped with Fe, the acceptor levels of Fe along with oxygen vacancies are created in the band gap of TiO262. In our case, as discussed above Ti3+ is also formed which creates energy level in the band gap, contributing to the reduction of band gap. Next, when this Fe doped TiO2 film was treated in air plasma, the Ti3+ levels and oxygen vacancies increases further with the treatment time, whereas no change in the dopant levels occurs as the dopant concentration was kept constant. The increase in Ti3+ levels and oxygen vacancies would further reduce the band gap of Fe doped TiO2 film. In case of Co doping, there is a formation of Co acceptor levels along with Ti3+ and oxygen vacancies levels in the band gap which reduces the band gap of Co doped TiO2 film. But when the film was treated with plasma we observed continuous widening in the band gap with treatment time. The observed increase in the band gap can be explained by Burstein-Moss effect. The probable reason for Burstein-Moss shift in this case is that with the treatment time the Ti3+ levels and oxygen vacancies increases more as compared to Fe doped case. By plasma treatment for 60 seconds the Ti3+ increases by 20%, oxygen vacancies increases by 15% in case of Fe doped TiO2, whereas Co doped TiO2 Ti3+ increases 30%, oxygen vacancies increases 25%. These created levels donate more electrons and thus shift the Fermi level to the conduction band, which increases the band gap of Co doped TiO2 film. The exact reason for this divergent behavior is unclear as of now but the most appropriate reason seems to us is, the on-site coulomb interaction/repulsion that are occurring only in case of Co doped TiO2 films63. When Co2+ ion substitutes Ti4+ ions, the imbalance positive charge inside the lattice is compensated by the formation of oxygen vacancies located near Co ion. The formation of oxygen vacancies is equivalent to the addition of two electrons per Co ion6465. The oxygen vacancies produced in case of Co doped TiO2 thin films are higher as compared to Fe doped TiO2 films as observed by XPS. Suppose both Fe and Co doped films increase by same values of Ti3+ levels and oxygen vacancies, but due to Columbian interactions, which are only in case of Co doped TiO26465, the optical transition results in the blue shift of the absorption spectra. The proposed mechanism for both the Fe and Co doped TiO2 is illustrated in Fig. 10. Conclusion Treatment by air plasma leads to significant change in the optical properties of TiO2 thin films. Unlike other treatment methods, in this approach the transparency of TiO2 thin film remains invariant. The charge separation centers i.e. oxygen vacancies and Ti3+ is created with the doping of metallic Fe and Co elements; however, they are significantly enhanced by the air plasma treatment. In Fe doped TiO2 thin film, the formation of oxygen vacancies and Ti3+ causes enhances absorbance and red shift due to the formation of energy levels in the band gap, whereas in Co doped TiO2 the Burstein-Moss shift is effective to make blue shift in the absorption spectra. Conclusively, we can say that the joint approaches i.e. low level/moderate doping and safe and low cost air plasma treatment resulted in enhanced optical properties of transparent TiO2 thin films, making them efficient candidate for transparent electrode applications. Experimental Methods Thin films of TiO2, Fe doped TiO2 (Ti0.95Fe0.05O2) and Co doped TiO2 (Ti0.95Co0.05O2) were fabricated on glass substrate using dip-coating method. Titanium (IV) isopropoxide (TTIP, Ti[OCH (CH3)2]4, 97%, Aldrich) was used as precursor solution. First of all triethanolamine C6H15NO3, a stabilization agent was dissolved in C2H5OH, which resulted in a colorless solution. In this solution, the precursor solution Ti[OCH (CH3)2]4 was added dropwise to form a pale yellow solution with a continuous stirring. To avoid the precipitation of TiO2, C2H5OH and H2O was added in a ratio 9:1. Now during the sol gel synthesis the solutions of ferric nitrate (Fe (NO3)3.9H2O), and cobalt nitrate (Co (NO3)2.6H2O) were added separately as the dopant in TiO2. These solutions were stirred for two hours and allowed for ageing overnight. Then glass substrates cleaned with H2O, detergent, C3H6O and C2H5OH were coated with the aged solution. Coated films were dried and annealed at 400 °C to form transparent thin films. The fabricated films were treated in air plasma, generated in a vacuum coating unit (Hindhivac model: 12A4D), for varying treatment time; 0, 10, 30, and 60 seconds, respectively. The air plasma was generated at reduced pressure of 10−3 mbar in the vacuum chamber. During the treatment process the applied bias voltage was 30 volts with a power of 22.7 watt. After treating in plasma, the samples were analyzed for optical, structural, morphological and surface properties. Materials Characterization The optical (absorbance, shift in absorption edge and band gap) properties of the films were studied by UV-Vis spectrophotometer (Perkin-Elmer Lambda 750). The band gap of Fe and Co doped thin films was calculated by using the absorbance spectra by plotting (αhv)1/2 against hv, where hv being incident photon energy. Surface morphology was studied using scanning electron microscopy (SEM), and elemental confirmation was done using energy dispersive X-ray (EDX). The structural analysis of the samples was done using X-ray diffractometer (XRD) (company name Rigaku, with Cu kα radiation, λ = 1.5406 Å), and to observe the effect of plasma treatment on surfaces states, X-ray photoelectron spectroscopy (XPS: VG Multilab 2000, Thermo electron corporation, UK) studies were performed. Additional Information How to cite this article: Bharti, B. et al. Formation of oxygen vacancies and Ti3+ state in TiO2 thin film and enhanced optical properties by air plasma treatment. Sci. Rep. 6, 32355; doi: 10.1038/srep32355 (2016). Supplementary Material Supplementary Information This work was supported by research grant for Nanotechnology Lab of Jaypee University of Information Technology, also by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (NRF-2015R1A2A1A05001826). Author Contributions B.B. fabricated and characterized the entire sample and wrote the manuscripts. S.K. carried out XPS studies of the samples. H.L. helped in the revision of the manuscript. R.K. supervised the work, reviewed and corrected the manuscript. All the authors participated in the discussion and commented on the paper. Figure 1 X-ray diffraction spectra of (a) Fe doped/untreated TiO2 film; plasma treatment time 0 second, (b) Fe doped/treated TiO2 film; plasma treatment time 60 second, (c) Co doped/untreated TiO2 film; plasma treatment time 0 second and (d) Co doped/treated TiO2 film; plasma treatment time 60 second. Figure 2 Optical absorption spectra and Tauc plot ((αhv)1/2 versus hv plot) in the inset for (a) Fe doped/untreated TiO2 film; plasma treatment time 0 second and (b) Fe doped/treated TiO2 film; plasma treatment time 60 second. Figure 3 Optical absorption spectra and Tauc plot ((αhv)1/2 versus hv plot) in the inset for (a) Co doped/untreated TiO2 film; plasma treatment time 0 second and (b) Co doped/treated TiO2 film; plasma treatment time 60 second. Figure 4 Plots for variation of optical band gap of Fe and Co doped TiO2 thin film with plasma treatment time. Figure 5 XPS survey spectra in a(i) pure TiO2 film indicating all the peaks of elements present in the sample, here the appeared carbon peak is instrumental impurity, a(ii) Fe doped/untreated TiO2 film; plasma treatment time 0 seconds, a(iii) Fe doped/treated TiO2; plasma treatment time 60 seconds, b(i) pure TiO2 film which is similar to a(i), and b(ii) Co doped/untreated TiO2 film; plasma treatment time 0 seconds, b(iii) Co doped/treated TiO2 film; plasma treatment time 60 seconds. Figure 6 High resolution XPS spectra of Ti2p and O1s in (a) pure/untreated TiO2 film, (b) Fe doped/untreated TiO2 film; plasma treatment time 0 second, (c) Fe doped/treated TiO2 film; plasma treatment time 60 seconds, (d) O1s for pure/untreated TiO2 film, (e) O1s for Fe doped/untreated TiO2 film; plasma treatment time 0 second, and (f) O1s for Fe doped/treated TiO2 film; plasma treatment time 60 seconds. Figure 7 High resolution XPS spectra of Fe2p in (a) Fe doped/untreated TiO2 film; plasma treatment time 0 second, (b) Fe doped/treated TiO2 film; plasma treatment time 60 seconds, (c,d) are Gaussian fit of (a,b). Figure 8 High resolution XPS spectra of Ti2p and O1s in (a) pure/untreated TiO2 film, (b) Co doped/untreated TiO2 film; plasma treatment time 0 second, (c) Co doped/treated TiO2 film; plasma treatment time 60 seconds, (d) O1s for pure/untreated TiO2 film, (e) O1s for Co doped/untreated TiO2 film; plasma treatment time 0 second, and (f) O1s for Co doped/treated TiO2 film; plasma treatment time 60 seconds. Figure 9 High resolution XPS spectra of Co2p in (a) Co doped/untreated TiO2 film; plasma treatment time 0 second, (b) Co doped/treated TiO2 film; plasma treatment time 60 seconds, (c,d) are Gaussian fit of (a,b). Figure 10 Schematic diagram of the energy levels of (a) pure/untreated TiO2 films, (b) Fe doped/untreated TiO2 film, (c) Fe doped/treated TiO2; for 60 seconds of treatment time, (d) Co doped/untreated TiO2 film, (e) Co doped/treated TiO2 film; for 10, 30 and 60 seconds of treatment time, indicating Burstein Moss effect. (Ov represents oxygen vacancies). 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3234910.1038/srep32349ArticleDesign for strong absorption in a nanowire array tandem solar cell Chen Yang 1Pistol Mats-Erik 1Anttu Nicklas a11 Division of Solid State Physics and NanoLund, Lund University, Box 118, 22100 Lund, Swedena nicklas.anttu@ftf.lth.se30 08 2016 2016 6 3234926 01 2016 08 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Semiconductor nanowires are a promising candidate for next-generation solar cells. However, the optical response of nanowires is, due to diffraction effects, complicated to optimize. Here, we optimize through optical modeling the absorption in a dual-junction nanowire-array solar cell in terms of the Shockley-Quessier detailed balance efficiency limit. We identify efficiency maxima that originate from resonant absorption of photons through the HE11 and the HE12 waveguide modes in the top cell. An efficiency limit above 40% is reached in the band gap optimized Al0.10Ga0.90As/In0.34Ga0.66As system when we allow for different diameter for the top and the bottom nanowire subcell. However, for experiments, equal diameter for the top and the bottom cell might be easier to realize. In this case, we find in our modeling a modest 1–2% drop in the efficiency limit. In the Ga0.51In0.49P/InP system, an efficiency limit of η = 37.3% could be reached. These efficiencies, which include reflection losses and sub-optimal absorption, are well above the 31.0% limit of a perfectly-absorbing, idealized single-junction bulk cell, and close to the 42.0% limit of the idealized dual-junction bulk cell. Our results offer guidance in the choice of materials and dimensions for nanowires with potential for high efficiency tandem solar cells. ==== Body The use of III-V nanowires for p-i-n junction solar cells is an emerging avenue for photovoltaics123456. Both single wire467 and large-area nanowire array589 devices show promise for next generation solar cells. Already for single nanowire systems, diffraction of light can lead to resonant coupling of light into the nanowire with several absorption peaks as a function of wavelength1011. Optimization of the geometry of the single-nanowire geometry is necessary to obtain maximum photocurrent12 and open circuit voltage412. The resonances can lead to a 20 times stronger absorption per volume semiconductor material in a III-V nanowire as compared to a bulk sample13. An array of nanowires gives in turn access to large-area devices when higher output power is needed. For such arrays, an efficiency of 13.8% has been demonstrated using InP nanowires with a single p-i-n junction in the axial direction5, and an efficiency of 15.3% has been reached with GaAs nanowires9. However, the use of a single material gives an upper limit for the amount of sun light that can be converted into electrical energy14, due to two reasons. First, the energy of photons with energy below the band gap energy of the semiconductor cannot be utilized since those low-energy photons cannot be absorbed. Second, a large part of the energy of absorbed high-energy photons is wasted due to thermalization. In this thermalization process, the photogenerated electrons and holes relax in energy to their respective band edges. To reach higher efficiencies in solar cells, an avenue is to use multiple semiconductors, epitaxially grown on top of each other15. See Fig. 1 for a system with two different semiconductor materials, where one material is used in the top cell and a different material in the bottom cell. The idea in such a tandem device is to absorb high energy photons in a high band gap top cell. In that top cell, the thermalization loss of the high energy photons is decreased compared to the single junction cell. The lower energy photons continue to the bottom cell where they are absorbed. Due to the lower band gap of the bottom cell than in the single junction cell, more photons are absorbed than in the single junction cell. In this way, the tandem cell can absorb more photons than the single junction cell, while at the same time having reduced thermalization losses. However, in planar cells, the crystal lattice constant between materials in adjacent subcells/layers should be matched to yield high-quality materials without performance limiting dislocations. Such requirements on crystal-lattice matching limit strongly the choice of materials for tandem cells. Nanowire structures offer a clear benefit for multi-junction solar cells compared with planar cells. Efficient strain relaxation in nanowires allows for the fabrication and combination of dislocation-free, highly lattice-mismatched materials16171819. Furthermore, III-V semiconductor nanowire arrays can in principle be fabricated on top of a Si substrate19, giving the prospect of using the Si substrate as the bottom cell220212223. Thus, nanowires offer freedom for the material choice in multi-junction solar cells, making it easy to reach optimum material combinations to match the solar spectrum. Furthermore, the resonant absorption by designing the nanowire geometry holds the prospect of lower material usage than in thin-films13. Therefore, to enable high-efficiency nanowire tandem solar cells, we need to understand the optimum choice of materials for the subcells as well as the optimum nanowire geometry to have the best absorption characteristics for photovoltaics. Already for single junction nanowire-array cells, we know that both the array pitch and the nanowire diameter need to be optimized simultaneously. At the same time, the optimum diameter depends on the band gap of the solar cell, that is, on the material choice8. Here, we perform optical modeling to calculate and optimize the absorption of light in a dual junction tandem nanowire solar cell (Fig. 1) with the scattering matrix method18132425. This modeling allows us to perform a Shockley-Queisser detailed balance analysis to study and optimize the efficiency potential of the nanowire solar cell as a function of material choice and geometrical design of the nanowires. We show that an efficiency limit above 40% can be reached in the band gap optimized Al0.10Ga0.90As/In0.34Ga0.66As system when we allow for different diameter Dtop and Dbot for the top and the bottom subcell. However, for experiments, the case of Dtop = Dbot might be easier to realize. In this case, we find a 1–2% drop in the efficiency. In the experimentally relevant Ga0.51In0.49P/InP system, an efficiency limit of η = 37.3% is reached for a nanowire length of 13 μm when using equal diameters of Dtop = Dbot = 160 nm and a pitch P = 380 nm (we analyze also the effect of varying nanowire length, with results summarized in Table 1). These efficiencies for nanowire tandem cells are well above the 31.0% limit of an idealized, perfectly absorbing single-junction bulk cell and close to the 42.0% limit of the idealized, band gap optimized dual-junction bulk cell. Material choice for the top and the bottom cell in a nanowire tandem solar cell To choose the materials for the top and the bottom nanowire subcell, we perform the well-known Shockley-Queisser detailed balance analysis14 assuming first perfect absorption of above band gap photons in each subcell2226. This analysis corresponds to the case when each subcell absorbs optimally, without reflection losses. The specific assumption and technical details of the analysis can be found in the Supplementary Information. Importantly, we assume that cell 1 absorbs all photons of energy above E1, the band gap energy of cell 1. Cell 2 absorbs in turn all photons with energies between E1 and E2, the band gap energy of cell 2. We assume that A1(λ) = 1 for λ < λ1,bg and A1(λ) = 0 otherwise. Here, A1(λ) [A2(λ)] is the absorption spectrum of cell 1 (2), that is, the fraction of incident light of wavelength λ absorbed in cell 1 (2). Similarly, we assume that A2(λ) = 1 for λ1,bg < λ < λ2,bg and A2(λ) = 0 otherwise. Here, λ1,bg = 2πћc/E1 and λ2,bg = 2πћc/E2. In this way, we find the materials that maximize the efficiency limit of the nanowire solar cell when the geometry is designed for optimum absorption (Fig. 2). Note that below, in the section Geometry Design, when considering the effect of the nanowire geometry on the absorption, we model the absorption spectra A1(λ) ≤ 1 and A2(λ) ≤ 1 for each choice of the geometry, which includes sub-optimal absorption and varying reflection losses. We find a maximum efficiency of 42.0% when the band gaps of the top and the bottom cell are E1 = 1.58 eV and E2 = 0.95 eV respectively (Fig. 2). Note that the results in Fig. 2 are in good agreement with previous detailed-balance calculations of multi-junction bulk cells2226. In our case, for the modeling of the emission to the substrate, we use a refractive index of n = 3.5 to represent the InP substrate. We note that the emission of photons into this high-refractive index substrate has caused a 3% decrease in this maximum efficiency. To choose the III-V materials for the nanowire subcells, we calculated first the band gap for varying ternary compounds27. After this, we investigated which ternary compounds have tabulated, experimentally determined, reliable refractive index values available for the optics modelling. Among the ternaries for which such refractive index data were readily available, we identified Al0.10Ga0.90As (band gap of 1.55 eV27, and refractive index from ref. [28]) for the top cell and In0.34Ga0.66As (band gap of 0.95 eV27, and refractive index from ref. [29]) for the bottom cell as a good material combination with an efficiency limit of 40.7%. However, we could imagine that the fabrication of a dual-junction nanowire solar cell could benefit from the knowledge and control of the fabrication of single-junction nanowire solar cells. In this case, the natural candidates are the well-performing InP5 and GaAs9. The band gaps of both these materials work well for the bottom cell (see inset in Fig. 2 for an InP bottom cell and Supplementary Figure S1 for a GaAs bottom cell). However, the surface recombination velocity of unpassivated GaAs can be five orders of magnitude higher than that of unpassivated InP30. Therefore, GaAs nanowires need dedicated surface passivation schemes,9 whereas the requirement on surface passivation is relieved for InP nanowires5. Therefore, we chose to concentrate on an InP bottom cell. Here, a maximum efficiency of 38.6% is found with a top cell band gap energy of 1.86 eV (inset of Fig. 2). We note that Ga0.51In0.49P, for which refractive index data is available31, has a band gap energy of 1.85 eV31, giving an efficiency limit of 38.5% in the tandem configuration with InP. Depending on the surface properties of the GaInP, this GaInP/InP system could perhaps even provide the prospect of high efficiency without dedicated surface passivation schemes. Thus, we study the efficiency limit of both the AlGaAs/InGaAs and the GaInP/InP system. Geometry Design After choosing the materials for the top and the bottom cell as described above (the nearly band gap optimized Al0.10Ga0.90As/In0.34Ga0.66As system as well as the technologically relevant Ga0.51In0.49P/InP system), we turn to consider the geometry of the nanowire subcells (Fig. 1). There are five geometry parameters: the length of each subcell (Ltop and Lbot), the diameter of each subcell (Dtop and Dbot), and the pitch (P) of the square array, which need to be optimized with respect to the absorption (A1(λ) and A2(λ)) of light in each subcell. Different computational methods, such as the finite-element method (FEM)33233, the rigorous coupled wave analysis (RCWA)46 and the scattering matrix method18132425, have been used for studying the diffraction and absorption of light in nanostructures through the solution of the Maxwell equations, which give results in good agreement with experiments13. We chose to employ the scattering matrix method to solve the Maxwell equations for normally incident light in order to calculate the absorption spectrum A1(2)(λ) of the nanowire top and bottom cells. We use tabulated refractive index values n(λ) for the Al0.10Ga0.90As28, In0.34Ga0.66As29, Ga0.51In0.49P31, and InP34. We then calculate the Shockley-Queisser detailed balance efficiency (see Supplementary Information Eqs. (S1)–(S6) for technical details). Note that the optics modeling is done with the nanowires on top of an InP substrate (see Fig. 1). However, absorption of light in the substrate does not contribute to the current or voltage of the solar cell in our analysis. Thus, the substrate functions optically merely to partially reflect the light that reaches the substrate. Therefore, a change to a different substrate, like the less-expensive Si19, with similar n ≈ 3.5 as the InP would give very similar absorption spectra. We start by considering the case of Al0.10Ga0.90As (band gap of E1 = 1.55 eV) for the top cell and In0.34Ga0.66As (band gap of E2 = 0.95 eV) for the bottom cell, which was found to be a good band gap combination with efficiency limit of 40.7% for perfectly absorbing subcells. It is known that the nanowire diameter affects strongly the absorption of light15781335. Therefore, to study the effect of the nanowire diameter on the absorption in the tandem cell, we fix P = 530 nm, Ltop = 2000 nm, and Lbot = 2900 nm [Fig. 3(a)]. As a main feature: the efficiency appears to be a function of just Dtop when Dbot is large enough (typically when Dbot > 250 nm). In this case of large Dbot, two local maxima show up in the efficiency as a function of Dtop. To show these maxima clearly, we set Dbot to a fix value of 470 nm. Here, these two efficiency peaks show up at a top cell diameter of Dtop = 150 nm and Dtop = 345 nm, respectively [Fig. 3(b)]. To understand the origin of these two efficiency maxima, we study the number of incident photons as a function of wavelength [blue line in Fig. 3(c,d)]. In the region 600 nm to 800 nm, the solar spectrum shows the highest number of incident photons as a function of wavelength. Since we assume that each absorbed photon contributes one charge carrier to the photogenerated current, strong absorption in this wavelength region is very important for j and consequently to the efficiency. Therefore, we study the absorption spectrum in the top cell as a function of the diameter in the top cell around Dtop = 150 nm and Dtop = 345 nm, respectively, where the two local maxima in η show up. In Fig. 3(c), when the diameter increases from 120 nm to 150 nm, we find an absorption peak in the spectrum, and it moves from about 600 nm to 700 nm83637. This peak can be explained as resonant coupling of incident light into the HE11 waveguide mode of the individual nanowires. This resonant coupling leads to enhanced absorption in nanowire arrays36. When Dtop increases further to 180 nm [red dotted line in Fig. 3(b)], the absorption peak has started to vanish since it red-shifts beyond the bandgap wavelength. This shifting and disappearance of the absorption peak leads consequently to a small decrease in the efficiency as Dtop increases from 150 nm to 180 nm. Similarly, in the case of Dtop = 345 nm we find again an absorption peak at λ ≈ 700 nm [Fig. 3(d)]. This time, the absorption peak originates from the higher order HE12 waveguide mode. This absorption peak has red-shifted beyond the band gap wavelength when Dtop has increased to 375 nm [Fig. 3(d)], leading to a slight decrease in the efficiency. Thus, we find an efficiency maximum for the nanowire tandem solar cell [Fig. 3(a)] when Dtop is optimized to place the HE11 or the HE12 absorption peak just below the band gap wavelength. Very similar results have been reported for the diameter optimization of a single junction InP nanowire solar cell8. To understand why the efficiency does not noticeably depend on Dbot for Dbot > 250 nm [Fig. 3(a)], we study the photogeneration of charges in the top cell (jph1) and the bottom cell (jph2) [Fig. 3(e,f)]. Since j = j1 = j2, and j1 ≤ jph1 and j2 ≤ jph2 (see Supplementary Information for details), the smaller one of jph1 and jph2 is expected to limit the solar cell efficiency [Fig. 3(a)]. When Dtop < 100 nm, the total current of the tandem cell is strongly limited by jph1. As the diameter of the top cell increases, jph1 can increase to about 20 mA/cm2. However, when the bottom cell diameter is larger than 250 nm, jph2 > 20 mA/cm2. Thus, for Dbot > 250 nm, jph2 > jph1 and the efficiency follows the absorption properties of the current-limiting top cell and therefore depends mainly on Dtop and only very weakly on Dbot. We note that for the bottom cell, we find a pronounced maximum in jph2 as a function of Dbot for Dbot ≈ 250 nm when Dtop ≈ 0. We assign this maximum in jph2 to the HE11 resonance in the bottom cell. We notice that in Fig. 3(f), that maximum is to a large degree overshadowed for Dtop > 0 by the strong dependence of jph2 on Dtop. When we study the dependence of the efficiency on Dbot for a fixed Dtop (see Supplementary Figure S2), we find that the maximum at Dbot ≈ 250 nm shows up also for Dtop > 0 and broadens with increasing Dtop. Thus, we have found above two clear local maxima for η, one for Dtop = 150 nm and one for Dtop = 345 nm that originate, respectively, from resonant absorption through the HE11 and HE12 modes in the top cell. However, the results above were derived for a fixed Ltop, Lbot, and P. Next, we optimize the efficiency limit for all these five parameters (Dtop, Dbot, Ltop, Lbot, and P) simultaneously. To make the optimization numerically feasible, we introduced a numerically efficient iteration process (See Supplementary Information for details). We choose to show the results in Fig. 4 as a function of top cell length Ltop. For tabulated values of the optimized geometry, see Supplementary Information Table S1. For a more complete dependence of the efficiency on the geometrical parameters, see Supplementary Figures S3–S14. Notably, with proper design, an efficiency limit above 40% can be reached by the use of Al0.10Ga0.90As for the top cell and In0.34Ga0.66As for the bottom cell [blue line, when Ltop > 6 μm, in Fig. 4(a)]. In this optimization, we can identify maxima in η to originate from the above discussed HE11 and HE12 resonances in the top cell [Fig. 4(a)]. In the region of Ltop > 600 nm, the HE11 resonance of the top cell leads to a higher efficiency limit than that of the HE12 resonance. These results are in agreement with those for a single junction nanowire array solar cell where the HE11 resonance usually leads to the highest efficiency8. For the dual junction cell here, we call these maxima for brevity the HE11 and HE12 maxima/optima. For a single junction nanowire cell8, rough values for the optimum diameter were estimated as Here, is the real part of the refractive index (at the band gap wavelength) and DHE11(HE12) is the diameter that optimizes the wavelength position of the HE11 and HE12 resonance in order to maximize η. The value for the constant cHE11(12) can be extracted from the work on the single-junction nanowire solar cells8. The diameter for the HE11 (HE12) resonance of the top cell in Fig. 4(b) is Dtop ≈ 150 nm (Dtop ≈ 345 nm) in qualitative agreement with values from Equation (1) [about 169 nm for HE11 and 394 nm for HE12 resonance]. We find that Dbot fluctuates only slightly when Dtop ≈ 150 nm to yield the HE11 maximum (blue dotted line in Fig. 4(b)). In contrast, Dbot fluctuates more at the HE12 maximum (green dotted line in Fig. 4(b)). This fluctuation in Dbot is understood from the fact that for the HE12 maximum at Dtop ≈ 345 nm, the efficiency shows a very broad maximum in Dbot (black dashed line in Fig. 3a and Supplementary Figure S2), which allows for large variations in Dbot when Ltop, Lbot, and P are optimized. Similarly as for the single nanowire case8, we find that the optimum pitch P [solid lines in Fig. 4(b)] tends to increase with increasing nanowire length, that is, with increasing Ltop and Lbot. This behavior can be understood as a competition between increased absorption and increased reflection with decreasing P8. With increasing nanowire length, the absorption increases, and we can allow for a larger P to decrease reflection losses. In our results, we find that Lbot > Ltop [Fig. 4(f)]. However, the efficiency tends to increase as a function of Lbot (see Supplementary Figures S3–S14), and therefore whether we end up in the case of Lbot > Ltop or in the case of Lbot < Ltop depends on how heavily we maximize the efficiency η at the cost of increasing Lbot. We allowed the optimization to stop with respect to Lbot when we reached a value of dη/dLbot < 0.001 μm−1 in our geometry optimization (see Supplementary Information). In this case, for all the considered Ltop, the optimized value for Lbot ended up slightly larger than Ltop. For fabrication purposes, it could be a benefit to consider Dtop = Dbot, that is, nanowires of a single diameter D throughout (see the red dashed line in Fig. 4a for the resulting efficiency). We found in this case large fluctuations in the optimum value of Lbot when Ltop is increasing (the fluctuation in Lbot could be larger than the value of Ltop). To be able to analyze this case as a function of Ltop, we set an upper limit of Ltop+1000 nm for Lbot. We find an interesting behavior for the optimized diameter D for these single-diameter nanowires [red dashed line in Fig. 4(b)]. For the smallest considered Ltop of 500 nm, D starts close to the Dtop ≈ DHE11 ≈ 150 nm of the HE11 maximum for the case in which we allow for Dtop ≠ Dbot. When Ltop increases toward the largest considered value of 8000 nm, D increases toward the value of the Dbot ≈ 200 nm which optimizes the HE11 maximum in the Dtop ≠ Dbot case. This behavior can be understood as follows. When Ltop is small, the absorption in the top cell is weak in relative terms, and photons also in the short wavelength region can reach the bottom cell due to insufficient absorption in the top cell. As a result, the current, and therefore the efficiency, of the solar cell is limited by absorption in the top cell. As a consequence, the optimum D occurs when the absorption in the top cell is optimized for, which happens at D ≈ DHE11. In contrast, when Ltop is large, the absorption in the top cell is instead strong, and the performance of the solar cell becomes limited by the current-generation in the bottom cell, which is optimized for D in a similar way as when Dtop ≠ Dbot. Thus, for large Ltop, D goes toward the Dbot that optimizes the HE11 maximum. Since we find the optimum for D close to the diameters found for the HE11 maximum in the Dtop ≠ Dbot case, we find, not completely surprisingly, values for P close to those of the HE11 case of Dtop ≠ Dbot. As an end result, we find that the efficiency for this case of D = Dtop = Dbot is typically 1 to 2% lower than when we allow for Dtop ≠ Dbot [Fig. 4(a)]. We have also studied the efficiency of the InP based Ga0.51In0.49P/InP nanowire tandem system [Fig. 4(d–f)], with maximum efficiency of 38.5% for perfectly absorbing subcells, which should be set in relation to the limit of 42.0% for the idealized, perfectly absorbing, band gap optimized dual-junction bulk cell. Also for this material choice we reach an efficiency within 2% of this maximum, with Ltop > 6 μm and Lbot > 7 μm, when we allow for Dtop ≠ Dbot. Also here, an additional drop by about 1% occurs with the constraint Dtop = Dbot. With Ga0.51In0.49P and InP as the material and Dtop = Dbot, we reach η = 35.5% when Ltop = 2000 nm and Lbot = 3000 nm, considerably higher than the maximum 31.0% possible in the single junction bulk solar cell case. To aid the reader, we show in Table 1 the values extracted from Fig. 4 for this case of Dtop = Dbot (for the HE11 and HE12 maximum, we refer the reader to Supplementary Information Table S1). Conclusion We performed electromagnetic modeling to investigate theoretically the absorption properties of a dual junction nanowire array solar cell. We used then the Shockley-Queisser efficiency limit as a metric for optimizing the materials and geometry of the nanowires. The optimized geometries are presented in Fig. 4, Table 1, and Supplementary Information Table S1. The drop in efficiency limit when moving away from such an optimized geometry is presented in Supplementary Information Figures S3–S14. These results present a guideline for choosing a nanowire geometry that has promise for optimized absorption in a dual-junction nanowire array solar cell. In this way, our results can be used as a starting point for theoretical studies on the optimization of the electrical properties of dual-junction nanowire array solar cells. Our results can also guide in the choice of materials and dimensions for the fabrication of nanowires aimed for tandem solar cells. Additional Information How to cite this article: Chen, Y. et al. Design for strong absorption in a nanowire array tandem solar cell. Sci. Rep. 6, 32349; doi: 10.1038/srep32349 (2016). Supplementary Material Supplementary Information This work was performed within NanoLund and received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7-People-2013-ITN) under REA grant agreement No. 608153, PhD4Energy, and the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 641023, NanoTandem. This article reflects only the author’s view and the Funding Agency is not responsible for any use that may be made of the information it contains. Author Contributions Y.C. performed the simulations, analyzed and interpreted the results, and wrote the paper. M.E.P. and N.A. initiated and supervised the study and interpreted the results. All authors contributed to writing and editing the manuscript. Figure 1 (a) Schematic diagram and geometry parameters of a dual junction nanowire array on an inactive substrate. (b) Schematic of a possible realization of the electrical design with axially configured p-i-n junction subcells with a tunnel junction to connect the top and the bottom subcell. Figure 2 Shockley-Queisser detailed balance efficiency as a function of material band gaps for perfectly absorbing subcells. The maximum efficiency η = 42.0% shows up at E1 = 1.58 eV and E2 = 0.95 eV for the top and the bottom cell band gap, respectively. Notice that in this analysis for the perfectly absorbing subcells, for E1 < E2 the bottom cell (cell 2) does not absorb any photons. Thus, j2 = 0 and consecutively the current through this current-matched series-connected solar cell is zero, leading to η = 0. The inset shows the efficiency limit for varying top cell band gap for the case of an InP bottom cell, that is, when E2 = 1.34 eV. Figure 3 (a) Efficiency limit as a function of Dtop and Dbot for P = 530 nm, Ltop = 2000 nm, and Lbot = 2900 nm. Here, the top cell is of Al0.10Ga0.9As and the bottom cell of In0.34Ga0.66As. (b) Efficiency limit as a function of top cell diameter as extracted from the dashed black line in (a). (c,d) Absorption spectra (red and green lines) for the diameters marked by the vertical lines in (b). Here, the diameter increases in the order of dashed, solid, and dashed dotted line. We show also the normalized number of available incident photons as a function of wavelength (blue line). (e,f) Photogenerated current jph1(ph2) in (e) the top cell and (f) the bottom cell, respectively. Figure 4 (a,d) Optimized Shockley-Queisser detailed balance efficiency as a function of Ltop. Here, values for the HE11 maximum (blue line) and the HE12 maximum (green line) are shown. These resonances show up when the HE11/HE12 waveguide resonance enhances absorption in the top cell for wavelengths close to the bandgap wavelength of the top cell. We show also the maximum efficiency (dashed red line) when we force a single diameter throughout the nanowire (Dbot = Dtop). The dashed black line shows the efficiency limit for the dual-junction cell under the assumption of perfect absorption in both the top and the bottom subcell. (b,e) P (solid line) Dtop (dashed line) and Dbot (dotted line) at the maximum efficiency point. The color of the lines denotes the corresponding maximum as in (a,d), that is, blue for HE11, green for HE12, and red for Dbot = Dtop. (c,f) Similar as (b,e) but for Lbot. The material of the top and the bottom subcell is shown in the title of each subfigure. Table 1 Optimized efficiency for varying L top for the Ga0.51In0.49P/InP dual-junction solar cell when the nanowire has a single diameter (D top = D bot), together with the corresponding geometrical parameters, as extracted from Fig. 4(d–f). Ltop (nm) Dtop (nm) Dbot (nm) Lbot (nm) P (nm) η(%) 500 130 130 1500 190 29.7 1000 140 140 2000 220 33.6 2000 150 150 3000 270 35.5 4000 150 150 5000 360 36.6 8000 160 160 8800 420 37.5 ==== Refs Anttu N. Shockley-queisser detailed balance efficiency limit for nanowire solar cells . ACS Photonics 2 , 446 –453 (2015 ). Bu S. et al. Optical and electrical simulations of two-junction III-V nanowires on Si solar cell . Appl. Phys. Lett. 102 , 031106 (2013 ). Kupec J. , Stoop R. L. & Witzigmann B. Light absorption and emission in nanowire array solar cells . Opt. Express 18 , 27589 –27605 (2010 ).21197033 Sandhu S. , Yu Z. & Fan S. Detailed balance analysis and enhancement of open-circuit voltage in single-nanowire solar cells . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3219210.1038/srep32192ArticlePrevalence and Abundance of Florfenicol and Linezolid Resistance Genes in Soils Adjacent to Swine Feedlots Zhao Qin 1*Wang Yang 1*Wang Shaolin 1Wang Zheng 1Du Xiang-dang 2Jiang Haiyang 1Xia Xi 1Shen Zhangqi 3Ding Shuangyang 1Wu Congming 1Zhou Bingrui 4Wu Yongning a15Shen Jianzhong b11 Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China2 College of Animal Husbandry and Veterinary Medicine, Henan Agricultural University, Zhengzhou 450002, China3 Department of Veterinary Microbiology and Preventive Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA4 Shanxi Key Laboratory of Ecological Animal Science and Environmental Medicine, Shanxi Agricultural University, Taigu 030801, China5 The Key Laboratory of Food Safety Risk Assessment, Ministry of Health and China National Center for Food Safety Risk Assessment, Beijing 100021, Chinaa wuyongning@cfsa.net.cnb sjz@cau.edu.cn* These authors contributed equally to this work. 30 08 2016 2016 6 3219203 02 2016 04 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Florfenicol is extensively used in livestock to prevent or cure bacterial infections. However, it is not known whether the administration of florfenicol has resulted in the emergence and dissemination of florfenicol resistance genes (FRGs, including fexA, fexB, cfr, optrA, floR, and pexA) in microbial populations in surrounding farm environments. Here we collected soil samples for the detection of FRGs and the residue of florfenicol from six swine farms with the record of florfenicol usage. Quantitative polymerase chain reaction and metagenomic sequencing revealed a significantly higher relative abundance of FRGs in the soils adjacent to the three swine farms where florfenicol was heavily used compared with the other sites. Meanwhile, the detectable levels of florfenicol were also identified in soils from two of these three farms using ultra-performance liquid chromatography tandem mass spectrometry. It appears that amount of florfenicol used on swine farms and the spreading of soils with swine waste could promote the prevalence and abundance of FRGs, including the linezolid resistance genes cfr and optrA, in adjacent soils, and agricultural application of swine manure with florfenicol may have caused a residual level of florfenicol in the soils. ==== Body The growing number of bacterial strains carrying antibiotic-resistance genes (ARGs) poses a significant risk to both animal and human health. It is widely believed that the increased abundance of ARGs in the environment is contributing to the emergence of multidrug-resistant pathogens, which might lead to the failure of antibiotic treatment of bacterial infections1. In China, approximately 210,000 metric tons of antibiotics are produced per year, of which, 97,000 metric tons are used for therapy and growth promotion in animal husbandry2. It is estimated that approximately more than half of antibiotics are not absorbed in the animal gut, and subsequent selection has given rise to increasing numbers of resistant bacteria in the gastrointestinal tract, providing a potential reservoir for antibiotic resistance genes3. Furthermore, it is likely that many of the unabsorbed antibiotics, along with bacterial antibiotic resistance genes, are excreted into the environment via feces from livestock animals3. These antibiotics and their associated antibiotic resistance genes may accumulate in soils after repeated application of manure34. The residue of antibiotics even at low concentrations in the environment is likely to impose selective pressures on environmental microorganisms, which might induce the emergence of diverse ARGs and promote the evolution of novel genes conferring certain antibiotic resistance mechanisms45678. Soil is the predominant reservoir for bacteria harboring genes associated with the antibiotic resistance, with a number of antibiotic resistance determinants identified from soil bacteria9 and various resistance bacteria were cultured from soil samples10. Growing evidence shows that antibiotics, along with considerable numbers of antibiotic-resistant bacteria, ARGs, and associated mobile genetic elements, are being disseminated into agricultural soils through frequent manure waste application and contamination111213. Fang et al. reported that the contamination of antibiotics and ARGs were detected in soils and the samples were collected from the actual field which had been treated with chicken manure for long term6. Moreover, the abundance of antibiotics and ARGs increased with the extension of greenhouse planting years6. This is likely to result in the ubiquitous pollution of antibiotic resistance in agricultural soils, while posing significant potential risks to the environment and public health. In addition, an ever-increasing number of novel functional resistance genes are being identified from environmental samples using widely available functional metagenomic methodologies14151617. Florfenicol, a fluorinated thiamphenicol derivative, is a broad-spectrum antimicrobial agent exclusively approved for use in veterinary medicine18. It has been licensed in China since 1999 for the control of respiratory tract diseases and enteric infections in food-producing animals. However, the excessive use of florfenicol as an antimicrobial chemotherapeutic agent has resulted in bacterial species acquiring resistance to this agent. Since the identification of florfenicol resistance gene floR in the fish pathogen Pasteurella piscicida in 199619, several specific phenicol resistance genes have been reported in florfenicol-resistant bacteria of animal origin. These genes include the phenicol-specific exporter genes fexA, fexB, and floR, and the multidrug resistance gene cfr, which encodes a 23S rRNA methyltransferase that confers resistance to phenicols as well as four other structurally unrelated antimicrobial groups (lincosamides, oxazolidinones, pleuromutilins, and streptogramin A)20. More recently, a novel ATP-binding cassette (ABC) transporter gene, optrA, which confers resistance to phenicols and oxazolidinones, was identified in Enterococcus and Staphylococcus species of both animal and human origin2122. It is noteworthy that both cfr and optrA confer transferable resistance to linezolid. Linezolid was the first oxazolidinone to be introduced into clinical medicine to treat infections caused by vancomycin-resistant enterococci and methicillin-resistant Staphylococcus aureus23. optrA also confers resistance to tedizolid, which is a newly approved oxazolidinone for the management of human infections associated with Gram-positive pathogens, including linezolid-resistant strains (especially those carrying cfr)24. Although oxazolidinones have not been approved for use in the livestock or aquaculture industries, cfr and optrA are commonly detected in florfenicol-resistant bacteria of animal origin2125. In addition to fexA, fexB, cfr, optrA, and floR, phenicol exporter gene pexA was identified in metagenomic libraries of cloned DNA isolated from Alaskan soils14. Interestingly, all of these genes, apart from pexA14, coexist with bacterial mobile genetic elements such as plasmids, transposons, or integrons2125262728, which aid the horizontal transfer of florfenicol resistance genes (FRGs) to numerous bacterial species and genera. Previous publications have reported the occurrence of chloramphenicol resistance genes, including fexA, fexB, cfr, and floR, in association with chloramphenicol residue in wastewater effluent from swine farm operations and corresponding wastewater-irrigated agricultural fields29. However, more than one decade ago, the usage of chloramphenicol in the livestock and aquaculture industries has been completely banned and florfenicol became the only available antimicrobial agent from the phenicol class in China. It is not clear whether the use of florfenicol in agriculture has contributed to the environmental accumulation of florfenicol and FRGs, especially the cfr and optrA genes also conferring resistance to other antimicrobial agents, which are critically important in the human medicine. It is very likely that the frequency of florfenicol usage in swine farms could affect the abundance and prevalence of FRGs and the accumulation of florfenicol in adjacent soils. Thus, we quantified six FRGs (fexA, fexB, cfr, optrA, floR and pexA) using quantitative polymerase chain reaction (qPCR) via a culture-independent method and detected the florfenicol residue concentrations using ultra performance liquid chromatography-tandem mass spectrometry (UPLC–MS/MS) in soils from different farms. Results Abundance of FRGs The florfenicol had been used to treat respiratory diseases only in farms HN-S-4, HN-S-5, and HN-S-6, while the florfenicol had been extensively used for prevention purposes in long-standing farms HN-S-1, HN-S-2, and HN-S-3. The approximate annual dosage of florfenicol used in farms HN-S-1, HN-S-2, and HN-S-3 in past three years is much more than that in farms HN-S-4, HN-S-5, and HN-S-6 (Table 1). Correspondently, our quantitative PCR result showed the relative abundance of FRGs from the farms HN-S-4, HN-S-5, and HN-S-6 was much lower than that from the farms HN-S-1, HN-S-2, and HN-S-3 (Fig. S1) and no FRGs was detected in control samples. Of the six farms, the abundance of cfr, optrA, and fexA was significantly higher in soils from HN-S-2 and HN-S-3 compared with the other four farms (p < 0.001). Interestingly, fexB was only detected in soils from HN-S-2 and HN-S-3 (Fig. 1), the only two farms with detectable florfenicol residue. Significantly higher levels of floR were detected in samples from the three long-standing farms compared with samples from the newly established farms (p < 0.001), with the highest abundance of floR detected in soils from HN-S-1 (Fig. 1). Additionally, the newly identified gene optrA, which confers transferable resistance to florfenicol and linezolid, was present across all soils adjacent to swine feedlots. Conversely, phenicol exporter gene pexA was not detected in any of the soil samples. Importantly, the relative abundance of the multidrug-resistance genes cfr and optrA was significantly higher in soils from HN-S-2 and HN-S-3 than in the other farms analyzed (p < 0.001). Metagenomic Analysis The absolute abundance of the six FRGs was further validated using high-throughput sequencing-based metagenomic analysis. In these six soil samples adjacent to swine farms, the number of reads identified as florfenicol resistance gene sequences was used to determine the absolute abundance. There was a significant difference in the log2 values for transformed FRG reads between the two different groups of farms (p < 0.05), which was consistent with the qPCR assays (Fig. 2a,b). Pearson correlation analyses were conducted to investigate potential relationships between the abundance of FRGs and transposases in these soil samples. Transposases, including IS256, IS6100, IS26, IS1216, ISEnfa4, and ISEnfa5, which play an important role in the horizontal transfer of FRGs between animal-associated bacteria and human clinical isolates, were identified in all soil samples. The total number of FRGs in each sample and the abundance of these genes were highly correlated with the levels of transposases in the soil samples (Fig. 2c, r2 = 0.9833, p < 0.0001). Furthermore, the phenicol exporter gene floR was highly correlated with the insertion sequence IS6100 (Fig. 2d, r2 = 0.9912, p < 0.0001). Florfenicol Concentrations in Soil Samples Methods were validated prior to sample analysis. To conform with the relevant validation criteria, the following parameters were used: (a) the matrix-matched calibration curves were linear in the concentration range of 0.25–20 ng g−1, with correlation coefficients (r2) greater than 0.999; (b) the limits of detection (LOD) and quantification (LOQ) were 0.08 ng g−1 and 0.25 ng g−1, respectively; (c) the average recoveries for florfenicol were in the range of 94.20–96.28% with relative standard deviation less than 10.5% (n = 6). Following method validation, florfenicol was detected in the soil samples from farms HN-S-2 (3.730 ± 0.327 ng g−1) and HN-S-3 (0.359 ± 0.028 ng g−1), while concentrations were below the LOQ for all other samples. Discussion Our results indicated that the usage of florfenicol in the farms affect the prevalence of FRGs in the soil irrigated with the farm waste. This conclusion could be supported by the following observations: first, both the metagenomic and qPCR via culture-independent methods revealed that FRGs can be detected in the soils adjacent to the farms with florfenicol usage, but not in the control samples. Second, the prevalence and abundance of FRGs maybe affected by the amount of florfenicol used in the farms, as the farms consumed more florfenicol resulted in more detected FRGs in soils. The detectable level of florfenicol in the soils adjacent to farms HN-S-2 and HN-S-3 imply that the unabsorbed florfenicol could be excreted into the environment via manure from livestock animals. In addition to the usage of florfenicol, many other factors could contribute to prevalence of ARGs in soils. It has been reported that the variety of ARGs and antibiotic residues in agricultural soils are correlated with soil type, manure application rate and environment conditions3031. The long-term fertilization of antibiotic-contaminated chicken manure in greenhouse soils led to higher levels of ARGs and antibiotic residues in greenhouse soils compared with field soils6. The occurrence of chloramphenicol resistance genes as environmental pollution were found in manured soils29. Several studies also have reported that the abundance and diversity of ARGs have a marked increase in soils after repeated manure application63233, such as multidrug resistance (MDR) genes, macrolide-lincosamide-streptogramin (MLS) genes, and sulfonamide resistance genes. Interestingly, following the use of florfenicol in these swine farms, the linezolid resistance gene optrA was detected in all soil samples; and the abundance of optrA was greater in soil samples obtained from farms HN-S-2 and HN-S-3. These were also the only two farms with florfenicol soil concentrations above the limit of quantification. However, oxazolidinones have not been approved for veterinary applications worldwide, and florfenicol is the only phenicol-derived antimicrobial agent exclusively used in selected swine farms21. In addition, the results imply that prior to being introduced to the farm environment, in vivo florfenicol can directly select for the propagation of optrA in bacterial isolates of animal origin. This is supported by the finding that this gene is more frequently detected in enterococci isolated from animals than from humans21. Meanwhile, a rapid UPLC-MS/MS method with a lower LOD (0.08 ng g−1) and LOQ (0.25 ng g−1) values compared with previous methods3435 was established to determine the levels of florfenicol in soil samples. To date, a number of reports have described the detection of various antibiotic residues, including tetracyclines, (fluoro)quinolones, and sulfonamides, in agricultural soils3031. However, none of these studies described a method that is suitable for the determination of florfenicol in soil using UPLC-MS/MS. To the best of our knowledge, this is the first study to quantify florfenicol residue in soil samples collected from swine production facilities using UPLC-MS/MS. The results showed that florfenicol levels were above the LOQ on two of the long-standing farms (HN-S-2 and HN-S-3). However, the observed lower concentrations of florfenicol in soils was consistent with that published previously35, may be due to the adsorption, biodegradation, photolysis, infiltration of florfenicol6 and the dilution of florfenicol by swine manure in soils. Notably, Subbiah et al. confirmed that the biologically active of florfenicol could remain long-time in soils36 and exert a selective pressure for resistance genes in the environment. In addition, a previous study34 looking at the relative robustness of florfenicol showed that the half-life of florfenicol in native soil is approximately 8 days and the degradation behavior of florfenicol in the soils was connected with the activity of microbe community. Considering the rapid degradation rate of florfenicol in native soils, it is possible that the detection of florfenicol in these soil samples depend on whether the sampling sites were irrigated with florfenicol contaminated manure or not in recent days. In general, the emergence and spread of antibiotic resistance genes are associated with mobile genetic elements, such as plasmids, integrases, and transposases373839. To date, several insertion sequences responsible for the mobility of FRGs, including IS6100, IS26, IS1216, IS256, ISEnfa4, and ISEnfa5, have been widely detected in different Gram-positive and Gram-negative bacteria2125262728. This has likely allowed the translocation of resistance genes between different plasmids, as well as mediating their integration into chromosomal DNA25. Importantly, in this current study, according to metagenomic analysis, the abundance of total FRGs (fexA, fexB, cfr, optrA, and floR) was significantly correlated with the abundance of insertion sequences (Fig. 2a,c). Of the transposases investigated as part of this study, IS1216 is commonly located adjacent to the linezolid resistance gene optrA in enterococci40, while IS26, IS1216, ISEnfa4, and IS256 have been reported to play an important role in the mobility of the multiresistance gene cfr25. In addition, the most frequently detected transposase, the IS6100 family element, commonly coexists with complex integrons in Gram-negative bacteria, and is typically located in the flanking regions of several resistance genes, including floR and tetR273841. We also observed a strong positive correlation between the abundance of floR and the presence of IS6100 in soil samples from each of the tested farms (Fig. 2b,d). All of these results suggest that the amount of florfenicol used in the farm not only play a considerable role in the abundance and diversity of FRGs, but also simultaneously leads to the enrichment of horizontally mobile genetic elements in adjacent soils. Therefore, the effects of the application of biogas slurry and the build-up of manure generated through livestock maintenance on the microbiota of agricultural soils should not be ignored when considering the spread of antibiotic resistance genes and insertion sequences (e.g. IS6100). Indeed, these factors are likely to assist in the migration of FRGs through soil-dwelling bacteria and horizontally transferred mobile genetic elements, facilitating the spread to human-associated bacteria. In this study, the strong correlation between transposase enrichment and the abundance of FRGs suggests that horizontal gene transfer may have aided in the enrichment of resistance genes through the transfer of mobile genetic elements among soil bacteria. To the best of our knowledge, this is the first study revealing the impact of florfenicol administration on the occurrence of FRGs in soil samples collected from swine farms. Our findings indicate that the amount of florfenicol used in swine husbandry could have played a considerable role in the abundance and diversity of FRGs in adjacent soils via application of swine waste. It is also the first report detailing the occurrence of the florfenicol and linezolid resistance gene optrA in soil samples. The results of this study suggest that soils containing optrA, cfr, and other phenicol resistance genes may act as a reservoir for florfenicol resistance. Therefore, the transfer of FRGs is also likely to affect humans that come into contact with the affected livestock, either through the food chain or through further environmental dissemination. It should be note that the selection of florfenicol and linezolid resistance genes optrA and cfr in soils, following the application of manure in swine farms with a history of administration of florfenicol, pose a significant risk to public health. Methods Sample Collection Soil samples were collected from agricultural fields surrounding six swine feedlots in November 2014. The antibiotic use records of the six farms indicated that florfenicol had been used at each of the farms. All of the field soils were irrigated with manure every few days and had been planted with vegetable crops for human consumption. The swine farms were located in six different cities in Henan Province, China (Fig. S2) and general information regarding these pig farms is listed in Table 1. Of the six farms analyzed, HN-S-4, HN-S-5, and HN-S-6 were relatively new farms (less than 3–4 years old), while HN-S-1, HN-S-2, and HN-S-3 had been producing sows for almost two decades. Overall, the long-standing farms HN-S-1/2/3 used more florfenicol (ranging from 0.63–2.88 metric tons per year) for preventing usually once a month in the past three year than other farms HN-S-4/5/6 (ranging from 0.11–0.30 metric tons per year) for treating respiratory diseases but not prevention (Table 1). Five soil samples were collected from different locations (near the pigsty) at each farm at depths of 5–10 cm4 and the soils were irrigated with manure repeatedly in the past few years. Additionally, control soil sample was collected at sites >5km away from the swine farm which was manure/antibiotic free. All samples were stored in an icebox during transfer to the laboratory, and were then stored at −20 °C long term. Soil samples collected from the same farm were mixed to form a composite sample, and subsequently sieved through a 2.0-mm mesh and frozen at −80 °C for further processing. Quantification of FRGs Metagenomic DNA was extracted from 0.25 g of homogenized soil using a PowerSoil DNA Isolation Kit (MO BIO Laboratories Inc., CA, USA) according to the manufacturer’s instructions, and stored at −20 °C until use. The DNA extracted from three independent replications of soil samples from each site to minimize any potential DNA extraction bias. qPCR assays were used to detect the presence of six FRGs (fexA, fexB, cfr, optrA, floR, and pexA), along with 16S rRNA, as described previously42. The specific primers used to amplify these gene fragments were designed using Primer 3 Plus (Table S1). Positive and negative controls were performed for each PCR reaction. The positive products were purified and ligated into vector pMD19-T (Takara, Dalian, China), and then transformed into Escherichia coli DH5α (Takara). DNA from recombinant plasmids containing target gene inserts was extracted using a Qiagen DNA Mini Kit (Qiagen, Hilden, Germany). The presence of the desired inserts was verified by PCR and sequencing, and then the positive plasmids were used to generate a standard curve for qPCR analysis. The qPCR assay was conducted using a QuantStudio 7 Flex Real-Time PCR System (Life Technologies, Carlsbad, CA, USA) with SYBR Premix Ex Taq II (Takara). The 20-μL reaction volume contained the following: 10 μL of SYBR Premix Ex Taq II (Til RNaseH Plus) 2*, 0.8 μL of each primer (10 nmol L−1), 1 μL of template DNA, and 7.4 μL of RNase-Free H2O (Takara). The qPCR conditions were: 95 °C for 3 min, followed by 40 cycles of 30 s at 95 °C, 30 s at 60 °C, and 30 s at 72 °C. The qPCR amplification efficiency was examined using R2 values (>0.999) for each calibration curve (Table S2). The amplification specificity was verified by performing a melting curve analysis (95 °C for 15 s, 60 °C for 1 min, 95 °C for 15 s) for each qPCR reaction, along with gel electrophoresis. The copy numbers of the target FRGs were quantified using a standard curve. Presence of the 16S rRNA gene was also quantified on the same plate, and the results are shown as relative abundance. To ensure reproducibility, three technique replicates for each sample were performed in parallel in each qPCR assays. Metagenomic Analyses For the metagenomic analysis, six prepared soil DNA samples were sent to Berry Genomics Company (Beijing, China) for high-throughput sequencing using the HiSeq 2500 platform. The raw data were filtered following removal of low-quality reads. The filtered data were then searched against the nucleotide sequences of six florfenicol resistance genes (fexA, fexB, cfr, optrA, floR, and pexA) with a minimum 50-bp overlap length and 95% identity using BLAT software43. The reads that matched the florfenicol resistance gene sequences were extracted, counted, and normalized from the total reads for each sample. The reads matching major transposase genes such as IS6100, IS26, IS256, ISEnfa5, ISEnfa4, and IS1216 were also extracted25272838. The flanking insert sequences were measured following metagenomic sequencing and analysis, as was florfenicol resistance gene abundance. Extraction Procedures and Sample Preparation In this study, a method was developed to quantify florfenicol residues in the soil using UPLC-MS/MS. First, soil samples were thawed at room temperature. A 5-g aliquot of soil was then weighed, and 4 mL of ammonia-ethyl acetate (2 + 98, v/v) were added to extract the drug. The mixture was mixed vigorously for 2 min using a vortex and then centrifuged at 10,000 rpm for 10 min at 4 °C. The supernatant was then transferred to a 10-mL centrifuge tube containing 500 μL of an acetic acid-water solution (5 + 95, v/v) and the extraction was repeated. The supernatants were subsequently combined and evaporated at 45 °C using a gentle stream of nitrogen until the combined volume was less 500 μL. The residue was reconstituted in 2 mL of an acetic acid-water solution (5 + 95, v/v). After vortexing for 1 min, the solution was transferred to an MCX cartridge (60 mg, 3 cc, Waters, Milford, MA, USA), which was sequentially preconditioned with 3 mL of methanol and 3 mL of water. The cartridge was washed with 1 mL of the acetic acid-water solution and eluted in 3 mL of ammonia-methanol (1 + 9, v/v). The eluate was collected and evaporated completely using a gentle stream of nitrogen. The residue was subsequently reconstituted in 500 μL of acetonitrile-water (1 + 1, v/v) and centrifuged at 12,000 rpm for 15 min at 4 °C. The supernatant was filtered through a 0.22-μm nylon membrane filter and transferred into a 2-mL vial. Finally, 10 μL of the solution were injected into the UPLC-MS/MS system. UPLC-MS/MS Analysis An UPLC system coupled with a Quattro LC triple quadrupole tandem mass spectrometer (Waters) equipped with electrospray ionization (ESI) was used to determine the presence, and subsequently quantify, florfenicol in the soil samples. Chromatographic separation was achieved using an Acquity UPLC BEH Shield RP18 column (50 mm × 2.1 mm, 1.7 μm) at 35 °C. Samples were separated using a mobile phase consisting of 0.1% formic acid in water (eluent A) and acetonitrile (eluent B) at a flow rate of 0.3 mL min−1. A linear gradient of eluent B (5–100%) was used in the total run time of 4 min (Table S3). The mass spectrometer was operated in the negative ESI mode with the following parameters: capillary voltage, 3.2 kV; cone voltage, 25 V; source temperature, 100 °C; desolvation temperature, 300 °C. Direct infusion was performed to optimize multiple reaction monitor transitions and associated acquisition parameters. The optimized conditions were as follows: m/z 356 > 336.1 (quantitative transition, collision energy, 13 eV), m/z 356 > 185.1 (qualitative transition, collision energy, 11 eV). Each sample was replicated three times for the determination of florfenicol residues. Statistical Analysis The difference in the relative abundance of FRGs (target gene copies/16S rRNA gene copies) was tested in all of the soil samples using t-test (non-parametric test), with further comparison of each soil sample carried out using Unpaired t-test. Additional Information How to cite this article: Zhao, Q. et al. Prevalence and Abundance of Florfenicol and Linezolid Resistance Genes in Soils Adjacent to Swine Feedlots. Sci. Rep. 6, 32192; doi: 10.1038/srep32192 (2016). Supplementary Material Supplementary Information This research was financially supported by grants from the National Natural Science Foundation of China (31370046) and the National Basic Research Program of China (2013CB127200). Author Contributions Q.Z., Y. Wu, Y. Wang and J.S. designed the experiment. Q.Z., Z.W., B.Z. and X.-d.D. performed experiments. Q.Z., S.W and Z.S. contributed to analysis the experimental data. Q.Z., Y. Wu and S.W. wrote the manuscript. Y. Wu, Y. Wang and J.S. supported and designed the project; Z.S., H.J., C.W., X.X., S.D., Y. Wang and J.S. critically revised the manuscript. All authors reviewed the manuscript. Figure 1 Relative abundance of five florfenicol resistance genes (a: fexA, b: fexB, c: cfr, d: optrA, and e: floR) in the six soil samples (target gene copies/16S rRNA gene copies). Bars represent the relative abundance of a single florfenicol resistance gene, and values shown are mean ± SE of three analytical replicates. Figure 2 Abundance of florfenicol resistance genes (fexA, fexB, cfr, optrA, floR) and transposases. (a) Number of total reads of each of the genes in different soil samples. Red bars represent the sum of florfenicol resistance genes, and purple represents transposases. (b) Reads associated with floR and IS6100 gene sequences in each soil sample. Red bars represent floR genes, and purple represents IS6100. (c) Correlation between total abundance of florfenicol resistance genes and associated transposases. (d) Correlation of the abundance of floR and IS6100. Sequences were analyzed using BLAT software. All figures and correlation analyses were generated using GraphPad Prism. Table 1 General information regarding the six pig farms sampled in this study. Farm Duration of operation Breeding information Florfenicol usage Total number of animals Annual hog output Sows Duration of usage Purposes Approx. Annual dosage in past three years (metric ton) Farm 1/HN-S-1 19 years 158000 150000 8000 8 years prevention 2.88 Farm 2/HN-S-2 18 years 58000 55000 3000 9 years prevention 0.63 Farm 3/HN-S-3 20 years 37000 35000 2000 10 years prevention 0.72 Farm 4/HN-S-4 4 years 8480 8000 480 4 years therapy 0.11 Farm 5/HN-S-5 4 years 25600 24000 1600 4 years therapy 0.28 Farm 6/HN-S-6 3 years 52500 50000 2500 3 years therapy 0.30 ==== Refs Jechalke S. , Heuer H. , Siemens J. , Amelung W. & Smalla K. Fate and effects of veterinary antibiotics in soil . Trends Microbiol 22 , 536 –545 (2014 ).24950802 Li C. . Occurrence of antibiotics in soils and manures from greenhouse vegetable production bases of Beijing, China and an associated risk assessment . Sci Total Environ 521–522 , 101 –107 (2015 ). Chee-Sanford J. C. . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3229410.1038/srep32294ArticleFirst record of Podocarpoid fossil wood in South China Li Long 1Jin Jian-Hua a1Quan Cheng b2Oskolski Alexei A. 341 State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources, and School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China2 Research Center of Paleontology & Stratigraphy, Jilin University, Changchun 130026, China3 Department of Botany and Plant Biotechnology, University of Johannesburg, Auckland Park 2006, Johannesburg, South Africa4 Komarov Botanical Institute of the Russian Academy of Sciences, Prof. Popov str. 2, St. Petersburg 197376, Russiaa lssjjh@mail.sysu.edu.cnb quan@jlu.edu.cn30 08 2016 2016 6 3229424 05 2016 04 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/A new species of fossil conifer wood, Podocarpoxylon donghuaiense sp. nov., is described from the late Eocene of Nadu Formation in Baise Basin of the Guangxi Province, South China. This fossil wood is characterized by distinct growth rings, circular to oval tracheids in cross section, 1–2-seriate opposite pits on radial tracheid walls, uniseriate (rarely biseriate) rays, smooth end walls of ray parenchyma cells, and the absence of resin ducts, suggesting its affinity to Podocarpaceae. The new species is distinctive from other Cenozoic woods ascribed to this family by the combination of distinctive growth rings, the absence of axial parenchyma, the occurrence of bordered pits on tangential tracheid walls, and the occurrence of 3–4 cuppressoid or taxodioid pits on cross-fields. This represents the first record of podocarpoid fossil wood in South China and provides fossil evidence for the early dispersal and diversification of Podocarpaceae in eastern Asia as well as for mild temperate seasonal climate in this region during the late Eocene. ==== Body As the second largest family within the conifers, the modern Podocarpaceae largely comprises evergreen trees and shrubs belonging to 194 species within 19 genera1. This family is mainly distributed in tropical and subtropical regions from central to South America, Africa (include Madagascar), Indochina through Malesia to Australia and Oceania12, extending as far north as China and Japan as well as to Mexico and the Caribbean345. Podocarpaceae are most abundant in montane tropical rainforests, but occasionally occur in lowland forests6. In comparison with extensive investigations on extant phylogenetics and geography of the family, its early evolution and migration in deep time are still poorly known, mainly due to the lack of megafossils, especially of Cenozoic age. Fossil records of podocarps from the Mesozoic were well documented in both the Northern and Southern hemispheres. Molecular and fossil evidence suggests that the podocarps originated during Triassic-Jurassic time in Gondwana and apparently spread to the Northern Hemisphere during the Jurassic7. Although the family appears to be of ancient origin, molecular dating analysis suggests that the majority of extant genera have arisen relatively recently in the Upper Cretaceous to Cenozoic8. Although modern Podocarpaceae are widespread mostly in the Southern Hemisphere, there are numerous reports of Cenozoic megafossils and palynomorphs attributable to this family from the Northern Hemisphere. Podocarpus shoots were found in Eocene deposits of Tennessee9, whereas pollen seemingly belonging to this genus is known from the Miocene of Oregon and Idaho10 and late Eocene of Colorado11. In Europe, leaves of Prumnopitys have been reported from the Eocene of England12, while leaf fossils assigned to Podocarpus have been found in Eocene to Oligocene deposits of Ukraine1314 and of the southeastern regions of European Russia15. A phylloclade of Phyllocladus has also been described by Krasnov13 from Eocene deposits of the Kharkov region (Ukraine). The assignment of these fossils to Podocarpus and Phyllocladus need special examination, however. In particular, several records of Podocarpus-like leaves from Eocene to Miocene localities of central and eastern Europe ascribed to the species Podocarpus eocenica Ung. have been reconsidered by Ferguson et al.16 as members of Amentotaxus, a genus of the Taxaceae. In addition, podocarpoid fossil wood has been reported from the Oligocene-Miocene of southern Ural17. Podocarpaceae palynomorphs occur widely in Europe from the Paleocene to the Miocene181920, whereas the records of Podocarpus pollen from the Pliocene of Iceland21 and Pleistocene of Belgium2122 possibly result from redeposition from older beds19. In Asia, several fossil woods attributed to Podocarpoxylon are known from the early Tertiary to Pliocene of India23. Podocarpus leaves have been reported from the Oligocene of Assam24, while Nageia leaves have also been described from Eocene deposits of Hainan Island and Guangdong Province, South China2526. Podocarpaceae fossil wood of Cenozoic age has not been recorded in China before but several apparent podocarpaceous woods, including Podocarpus (Nageia) nagi Pilger27 have been reported from Lower Cretaceous deposits2829. As for microfossils, Paleocene palynological records of Podocarpaceae locally occur in India, but they are very poorly represented in Southeast Asia where the pollen of Podocarpus sensu lato appears in the late Eocene7. In northern Kazakhstan, Podocarpaceae pollen grains have also been reported from the Eocene, but they disappear there in the late Oligocene30. Here we describe a new fossil wood of Podocarpoxylon from the late Eocene Nadu Formation of Baise Basin, Guangxi Province of South China, and review the phytogeographic and ecological implications of our finding. This is the first occurrence of fossil Cenozoic Podocarpaceae wood from South China. Results Systematics Order: Araucariales Gorozh. Family: Podocarpaceae Endl. Genus: Podocarpoxylon Gothan, 1908. Species: Podocarpoxylon donghuaiense Li, Jin, Quan et Oskolski, sp. nov. Etymology The specific name “Donghuai” is the locality name where the fossils were collected. Holotype DHW006. Paratypes DHW001 to DHW005, DHW007 to DHW0013. Repository Fossil wood samples and microscopic slides are deposited in the Museum of Biology, Sun Yat-sen University, Guangzhou, China. Type locality and horizon Nadu Fm., late Eocene. Specimens were collected in Donghuai coal-mine. Baise City, Guangxi Province (Fig. 1). Diagnosis Growth rings with prominent latewood, transition from earlywood to latewood gradual; circular pits on radial tracheid walls uniseriate, sometimes biseriate opposite, circular pits rarely occur in tangential walls of tracheids; cross-field pits cupressoid and taxodioid, circular to oval, 1–4 pits (mean 2) in opposite 1–2 rows per cross-field; axial parenchyma absent; rays predominately uniseriate, rarely partially biseriate; ray cells with smooth horizontal and tangential walls; ray tracheids absent; resin ducts absent. Description Growth rings distinct, 5.2–7.9 mm wide, with prominent latewood, transition from earlywood to latewood gradual (Fig. 2A). Earlywood tracheids thin-walled, circular to oval in cross-sectional outline, 23–40 μm (mean 32 μm) in tangential diameter and 23–56 μm (mean 37 μm) in radial size (Fig. 2B). Latewood tracheids moderately thick-walled, circular to oblong in cross-sectional outline, 7–23 μm (mean 13 μm) in tangential diameter and 11–21 μm (mean 15 μm) in radial size. Pits in radial tracheid walls uniseriate, occsionally also biseriate opposite (Fig. 2E). Pits bordered, circular (11–17 μm in diameter with the average of 15.7 μm) to oval (14–20 μm in size) in outline. Crassulae absent. Bordered pits of 8.2–15.0 μm in diameter rarely occur also on the tangential walls of latewood tracheids. Well-developed tightly spaced spiral and branched thickenings present on radial and tangential walls of latewood tracheids (Fig. 2D,F), with angles to the tracheid axes ranging from 40° to 60°. Axial parenchyma absent. Rays 42–331 μm (mean 100 μm) in height, predominately 1-seriate (Fig. 2C,D) and rarely partially 2-seriate (Fig. 2G), completely composed of parenchyma cells, 1–16 cells (mean 5 cells). Ray cells oval or elliptical in tangential section, both vertical and horizontal walls of ray parenchyma cells smooth, indentures absent. Cross-field pits possibly cupressoid or taxodioid type, circular to oval of 6–12 μm in size, with 1–4 pits (mean 2) per cross-field (Fig. 2H–J). Crystals not found. Resin ducts absent. Discussion Comparison with modern materials Within the conifer families, the fossil wood from Donghuai may not be placed into Pinaceae, Cupressaceae or Cephalotaxaceae, as it has no resin ducts, axial parenchyma and ray tracheids. This late Eocene wood is also distinctive both from Araucariaceae by the absence of two or more seriate alternate intertracheary pitting and by the lacking crowded araucarioid cross-field pits, and from Sciadopityaceae by the absence of window-like cross-field pits. Therefore, it remains for us to consider the relationships of this fossil wood to Taxaceae or Podocarpaceae31323334. The presence of spiral and branched thickenings on the walls of latewood tracheids in combination with smooth horizontal and tangential walls of ray cells suggests the fossil wood from Donghuai may be considered as a member of Taxaceae31323334. After careful examination of the thickenings on tracheid walls in this sample we suggest, however, that these structures are not of the same nature as the spiral tertiary thickenings that occur in all modern genera of this family, with the exception of Austrotaxus R.H. Compton3134. Extant Taxaceae show finer spiral thickenings, more widely spaced and tilted at lower angles (usually not exceeding 45°) in respect to the tracheid axes than the thickenings observed in the late Eocene wood from Donghuai. Such features of the fossil wood as tracheids bearing spiral thickenings confined only to the latewood and their absence in the earlywood has also not been reported in any modern Taxaceae31323334. Therefore, the spiral and branched structures occurring in tracheids of the Donghuai wood are more likely artifacts (probably, effects of wood compression) than true tertiary thickenings. The occurrences of similar artifacts in fossil woods seemingly belonging to Taxaceae have been surveyed by Afonin & Philippe35. In fossil woods assigned to Podocarpaceae these structures have been reported by Chudajberdyev17 in tracheids of Podocarpoxylon uralense Chudajb. As far the thickenings on tracheid walls are recognized as artifacts rather than diagnostic traits, the suite of other characters (smooth horizontal and tangential walls of ray cells without indentures, cupressoid and taxodioid pits on cross fields) indicates that the fossil wood reported here has greatest affinity to the Podocarpaceae31323334. This family, however, shows considerable diversity of wood structure that does not allow distinction between its genera using wood anatomical traits. The late Eocene wood from Donghuai is different from most modern Podocarpaceae in growth rings with conspicuous latewood, lacking axial parenchyma and the occurrence of 1–4 pits on the cross-field. However, the presence of prominent latewood portion has been reported in growth rings of Podocarpus acutifolius Kirk, Podocarpus macrophyllus (Thunb.) D. Don., Lagarostrobus (Dacrydium) franklinii (Hook. f.) Quinn, Halocarpus (Dacrydium) bidwillii (Hook. f. ex T. Kirk) Quinn, Phyllocladus glaucus Carr. and P. trichomanoides D. Don3234363738. Axial parenchyma is also lacking in Dacrydium elatum (Roxb.) Wall. ex. Hook., D. colensoi Hook., D. biforme (Hook.) Pilg., D. kirkii F. Muell. ex Parl., D. intermedium Kirk, D. taxifolium Banks & Sol. ex D. Don, Halocarpus bidwillii Lepidothamnus intermedius (Kirk) Quinn., Manoao colensoi (Hook.) Molloy., Microcachrys tetragona (Hook.) Hook., Phyllocladus alpinus Hook.f., P. glaucus, P. trichomanoides, Podocarpus elongatus (Aiton) L’Hér. ex Pers., Prumnopitys harmsiana (Pilg.) de Laub., and P. taxifolia (Sol. ex D.Don) de Laub31323336373940. Although cross-fields with 1–2 pits are the most common condition in Podocarpaceae, the occurrence of cross-fields with up to 4 cupressoid or taxodioid pits has been reported for Dacrydium pierrei, D. intermedium, Podocarpus hallii, Microcachrys tetragona and Retrophyllum minor (Carrière) C. N. Page3234363739. Therefore, the fossil wood from Donghuai shows most resemblance to some species of Prumnopytis (especially P. taxifolia) as well as to some members of Podocarpus, Dacrydium and Microcachrys, but it cannot be convincingly placed in any extant genus of Podocarpaceae on the basis of its anatomical traits. Comparison with fossil materials The fossil wood described here is characterized by an absence of axial parenchyma and by the cross-fields with cupressoid and/or taxodioid pits. Within fossil woods ascribed to Podocarpaceae, these traits are found in some species of the genus Podocarpoxylon Gothan313241, as well as in the monospecific genus Prumnopityoxylon Franco & Brea that was recently described from the Upper Cenozoic of Argentina42. Moreover, this combination of wood traits has also been reported for Phyllocladoxylon annulatus Patton from the Oligocene of Australia43. The fossil sample from Donghuai exhibits similarities to Cenozoic species of Podocarpoxylon as well as with Prumnopityoxylon gnaedingerae Franco & Brea and Phyllocladoxylon annulatus Patton (Table 1). Within seven species that have no axial parenchyma (Prumnopityoxylon gnaedingerae Franco & Brea, Podocarpoxylon aparenchymatosum Gothan, P. dusenii Kräusel, P. latrobensis Greenwood, P. sahnii (Ramanujam) Trivedi & Srivastava, P. tiruvakkaraianum (Ramanujam) Trivedi & Srivastava, and Phyllocladoxylon annulatus Patton), cross-fields with more than two pits occur only in P. aparenchymatosum and P. gnaedingerae. Podocarpoxylon aparenchymatosum from the Eocene deposits of Antarctica4445 differs, however, from the Donghuai wood in possessing 3-seriate pitting on radial tracheid walls. Unlike Prumnopityoxylon gnaedingerae, the Donghuai wood sample shows distinct growth rings, and by higher rays height with the occasional occurrence of bi-seriate portions. It follows from its unique character combinations that the late Eocene wood from Donghuai can be recognized as a new species named here as Podocarpoxylon donghuaiense. Although this fossil wood shows certain similarity to Prumnopityoxylon, Franco & Brea’s42 diagnosis of this genus lacks sufficient detail to separate it from Podocarpoxylon. Any of the wood traits, that have been considered by these authors as diagnostic for Prumnopityoxylon (i.e. “slightly distinct or indistinct growth rings; absence of axial parenchyma; uniseriate and homocellular rays; uniseriate or biseriate, opposite or sub-opposite, separate or contiguous tracheid pitting; taxodioid or cuppressoid cross-field pitting, with 1–5 bordered pits per field”)42, can be also found elsewhere in Podocarpoxylon, and their occurrences are consistent with Gothan’s44 diagnosis of this genus. For this reason, we ascribe the new species to Podocarpoxylon rather than to Prumnopityoxylon. Biogeographic implications Podocarpoxylon donghuaiense sp. nov. is the first record of podocarpoid fossil wood in China. Coeval macrofossils assigned to Podocarpaceae have already been reported from the South China: well-preserved leaves of Nageia have recently been described from the Eocene Changchang Formation of Hainan Island, and the Eocene Youganwo and Huangniuling formations of Guangdong Province2526. Podocarpoxylon donghuaiense is distinct, however, from the wood of extant Nageia species by the absence of axial parenchyma323334. Thus it is very unlikely that the fossil wood from Guangxi belonged to the same plant taxon as the fossil leaves from Hainan and Guangdong, despite the geographical proximity and nearly the same age of these three findings. Jin et al.’s25 and Liu et al.’s26, as well as our data confirm that the common occurrence of the Podocarpaceae species in the late Eocene vegetation of South China, that is consistent with the age of initial appearance of this family in Southeast Asia estimated by palynological records7. As the results of molecular dating suggest8, diversification of Podocarpaceae during Eocene gave rise to such modern genera distributed now in this region, as Dacrydium, Podocarpus and Nageia. Although Podocarpoxylon donghuaiense shares some wood traits with some extant species of Podocarpus and Dacrydium, this fossil wood can be convincingly ascribed to neither of them, probably because these taxa had not yet been emerged as distinct entities in the late Eocene. Most modern species of Podocarpaceae have growth rings with indistinct to very narrow latewood, or growth rings lacking. Contrastingly, the growth rings of Podocarpoxylon donghuaiense show relatively high proportion of latewood with gradual transition from earlywood to latewood. These traits are indicative for plants with long growing period without rapid shift to seasonal dormancy that are encountered mainly in the middle latitudes of both hemispheres464748. Within modern Podocarpaceae, this type of growth rings has been reported only in six species (Podocarpus macrophyllus ranged from Myanmar through mainland China and Taiwan to Japan, Podocarpus acutifolius, Halocarpus bidwillii, Phyllocladus glaucus and P. trichomanoides from New Zealand, and Lagarostrobus franklinii from Tasmania49) which are restricted to the temperate regions without dry season, with hot or warm summer (Cfa and Cfb climate types of Köppen’s classification)50. The occurrence of Podocarpaceae wood with prominent latewood in distinctive growth rings may therefore be an indicator that South China had mild temperate seasonal climate during the late Eocene. Conclusion A new species of fossil conifer wood, Podocarpoxylon donghuaiense sp. nov., is described from the late Eocene of Baise Basin of Southern China. This is the first Cenozoic record of podocarpoid fossil wood in Southern China. The new species is distinguished from other Cenozoic woods ascribed to Podocarpaceae by the unique combination of distinctive growth rings, the absence of axial parenchyma, the lack of bordered pits on tangential tracheid walls, and the occurrence of 3–4 cuppressoid or taxodioid pits on cross-fields. The tightly spaced thickenings on latewood tracheid walls of the fossil wood are recognized as artifacts (probably, effects of wood compression) rather than true tertiary thickenings. Therefore, Podocarpoxylon donghuaiense sp. nov. provides the first robust physical evidence for the early steps of dispersal and diversification of Podocarpaceae in eastern Asia, as well as for warm and wet climate in this region, and the presence of clear growth rings also suggest this was a seasonal climate during the late Eocene. Methods The fossil woods described here were collected from the Nadu Formation outcropping at Donghuai Coal-mine in the west part of the Baise Basin (transliterated also as the Bose Basin by some authors), Guangxi, South China (23° 52′ 14.84″N, 106° 34′ 49.27″E, Fig. 1). The geological age of the formation is believed to be late Eocene based on the well-studied Nadu Mammalian Fauna51. The well-preserved wood specimens examined represent portions of a main trunk (DHW001-013). The holotype DHW006 is about 10 cm diameter by 15 cm in length. Thin-sections were prepared according to standard methods of cutting, grinding, and polishing using different grades of carborundum powder52. Wood slides were examined using a Carl Zeiss Axio Scope A 1 light microscope. Microphotographs were taken using a Cool Snap digital camera fitted with QCapture Pro 6.0 photographic software. Wood anatomical characters were measured and described according to the IAWA list of microscopic features for softwood identification53. The systematic position of the fossil wood was determined by consulting the key to morphogenera of fossil conifer woods54 and by carefully comparing with similar modern and fossil woods. Fossil wood generic nomenclature and circumscription followed the criteria of Philippe & Bamford54. Fossil wood specimens and thin sections are housed in the Museum of Biology, Sun Yat-sen University, Guangzhou, China. Additional Information How to cite this article: Li, L. et al. First record of Podocarpoid fossil wood in South China. Sci. Rep. 6, 32294; doi: 10.1038/srep32294 (2016). This study was supported by the National Natural Science Foundation of China (Grant nos 41572011, 41528201, 41210001, 41372002), the joint Project of the National Natural Science Foundation of China and the Russian Foundation for Basic Research (Grant nos 41611130044, 16-55-53007), the Fundamental Research Funds for the Central Universities (Grant no. 16lgjc28), and the Scientific Research Fund, Hongda Zhang, Sun Yat-sen University. We thank the University of Johannesburg and the Komarov Botanical Institute (institutional research project no. 01201456545) for financial support for A.A.O. We thank graduate students majoring in Plant Science at Sun Yat-sen University for participating in the field collection of the fossils. We also thank Dr. Xin-Xin Feng for his helpful suggestions on this study, and Yang Zeng, librarian of Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences for references. We also offer our sincere gratitude to Prof. R.A. Spicer for editing. Author Contributions C.Q., J.-H.J. and L.L. collected the fossil wood from Donghuai. J.-H.J., C.Q. and L.L. participated in the design of the study. L.L. and A.A.O. photographed specimens and arranged figures. L.L. and A.A.O. carried out the data analyses. J.-H.J., L.L. and A.A.O. conducted taxonomic treatments, phytogeographic and ecological interpretation. L.L. and A.A.O. wrote the manuscript and formatted the text. All authors read and approved the final manuscript. Figure 1 Location of the study area. Location of Baise Basin, Guangxi Province, South China. (drawn by L.L., using Adobe Photoshop CS5). Figure 2 Wood structure of Podocarpoxylon donghuaiense sp. nov. (DHW006). (A) Transverse section showing distinct growth rings (arrow). Scale bar = 400 μm. (B) Transverse section of early wood showing circular to oval tracheids. Scale bar = 100 μm. (C) Tangential section showing the predominately uniseriate rays. Scale bar = 100 μm. (D) Tangential section of late wood showing spiral thickenings in tracheids (arrow). Scale bar = 100 μm. (E) Radial section showing 1–2 seriate opposite pits in radial tracheid walls (arrow). Scale bar = 20 μm. (F) Radial section showing spiral and branched thickenings on tracheid walls. Scale bar = 20 μm. (G) Tangential section showing partially 2-seriate rays (arrow). Scale bar = 50 μm. (H) Radial section showing cupressoid and taxodioid pits on cross-fields. Scale bar = 20 μm. (I) Radial section showing cupressoid pits on cross-fields. Scale bar = 10 μm. (J) Radial section showing taxodioidpits on cross-fields. Scale bar = 10 μm. Table 1 Comparison of the fossil wood from Baise Basin with Cenozoic species of Podocarpoxylon and other selected taxa Species Age Locality Growth rings Axial parenchyma Pitting on radial walls, diameter of pits Pitting on tangential walls Ray width (cells) Ray height (cells) Number and diameter of pits on cross-field Reference Wood from Donghuai Eocene China distinct absent 1(2)-seriate 11–20 μm + 1(2) 1–16 1–4 6–12 μm   Phyllocladoxylon annulatus Patton Oligocene Australia distinct absent 1(2)-seriate 12–18 μm + 1 1–7 1–2 8–13 μm Patton43 Podocarpoxylon aegyptiacum Kräusel Oligocene Egypt distinct abundant 1-2-seriate ? 1 3-6 1-few Kräusel55 P. angustiporosum E. Schönfeld Eocene Germany distinct sparse 1-2-seriate <18 μm + 1 ? 1–2(4) 9–12 μm Schönfeld56 P. aparenchymatosum Gothan Eocene Antarctica distinct absent 1-3-seriate 11–19 μm − 1 1–20 1–2(3) Gothan44 Pujana et al.45 P. articulatum Süss & Velitzelos Lower Miocene Greece distinct sparse 1(2)-seriate 20–25 μm ? 1–2(3) 1–20 (100) 1–3 10 μm Süss & Velitzelos41 P. australe Kräusel Tertiary Australia indistinct to absent sparse 1(2)-seriate 12–18 μm + 1(2) 1–12 1–3 5–12 μm Kräusel57; Patton43 P. bruxellense Stockmans Eocene Belgium distinct abundant 1(2)-seriate ? 1(2) 2–26 1 Stockmans58 P. dacrydioides Zalewska Tertiary Poland indistinct abundant 1–2(3)-seriate 13 μm + 1(2) 1–31 1(2) 8 μm Zalewska59 P. dusenii Kräusel Tertiary Argentina distinct absent 1-seriate − 1(2) 1–20 (40) 1–2 Kräusel60 P. graciliradiatum Süss & Velitzelos Lower Miocene Greece distinct relatively abundant 1(2)-seriate 18–20 μm ? 1 1–30 (70) 1–3 10–12 μm Süss & Velitzelos41 P. jurii Blokhina Eocene-Oligocene Russia (Kuril islands) distinct sparse 1(2)-seriate ? 1(2) 1–21 1–5 Blokhina61 P. aff. javanicus Merrill. Pliocene Georgia distinct sparse 1-seriate ? 1 1–12 1 Shilkina62 P. kubarti Rössler Pliocene Austria indistinct sparse 1-seriate ? 1(2) < 23 1–4 Rössler63 P. kurilense Blokhina Eocene-Oligocene Russia (Kuril islands) distinct sparse 1-seriate ? 1 1–17 1–2 Blokhina61 P. kutchensis Lakhanpal, Guleria & Awasthi Pliocene India indistinct sparse 1(2)-seriate ? 1(2) 1–41 1–2 Lakhanpal, Guleria & Awasthi64 P. latrobensis Greenwood Miocene Australia indistinct scanty to absent 1-2-seriate 15 μm − 1 2–18 1 (2) Greenwood65 P. mahabalei (Agashe) Trivedi & Srivastava Miocene-Pliocene India distinct abundant 1-seriate ? 1 1–30 1 Trivedi & Srivastava66 P. mazzonii (Petriella) Müller-Stoll & Schultze-Motel Paleocene Argentina indistinct sparse 1-2-seriate + 1(2) 1–38 1–2 Müller-Stoll & Schultze-Motel67 P. minor Patton Oligocene Australia indistinct sparse 1-seriate 8–13 μm + 1 1–7 1–3 2.5–7.5 μm Patton43 P. sahnii (Ramanujam) Trivedi & Srivastava Miocene-Pliocene India distinct absent 1-seriate ? 1(3) 1–20 1–2 Trivedi & Srivastava66 P. schmidianum Sahni Tertiary India indistinct sparse 1-2-seriate ca. 20 μm ? 1(2) 2–36 (100) 1–2 Sahni68 P. speciosum (Ramanujam) Trivedi & Srivastava Miocene-Pliocene India distinct abundant 1-2-seriate ? 1(2) 1–18 2–4 Trivedi & Srivastava66 P. tiruvakkaraianum (Ramanujam) Trivedi & Srivastava Miocene-Pliocene India indistinct absent 1-2-seriate ? 1 3–50 1 Trivedi & Srivastava66 P. turoviense Zalewska Tertiary Poland distinct abundant 1-2-seriate 15–17 μm + 1(2) 1–45 1–2 Zalewska59 P. uralense Chudaib. Oligocene_Miocene Russia (south Ural) distinct   1-seriate 13–14 μm − 1 1–12 2–3 (5) Chudajberdyev17 P. vikramii Bande & Prakash Tertiary India indistinct sparse 1(2)-seriate 15–20 μm ? 1 1–42 1–2 10–15 μm Bande & Prakash69 P. welkittii Lemoigne & Beauchamp Tertiary Ethiopia distinct ? 1(2) –seriate ca. 15 μm ? 1 1–18 1–3 Lemoigne & Beauchamp70 P. yallournensis Patton Oligocene Australia indistinct relatively abundant 1(2) –seriate 12–18 μm + 1 1–6 1–3(5) 3–10 μm Patton43 Podocarpus falcatus R. Br. ex Mirb. Cenozoic South Africa indistinct sparse 1(2) -seriate ? 1 3- >12 1 Adamson & Currin71 Podocarpus sp. Pliocene Columbia indistinct to absent abundant 1-seriate 8–17 μm ? 1 1–7 1 9–13 μm Wijninga72 Prumnopityoxylon gnaedingerae Franco & Brea Pliocene-Pleistocene Argentina indistinct absent 1(2)-seriate 13–17 μm + 1 2–8 1–5 3–9 μm Franco & Brea42 ==== Refs Farjon A. World checklist and bibliography of conifers . Richmond: Royal Botanic Gardens, Kew, 2 edition (2001 ). Conran J. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3220710.1038/srep32207ArticleMammalian non-CG methylations are conserved and cell-type specific and may have been involved in the evolution of transposon elements Guo Weilong a1*Zhang Michael Q. 23Wu Hong b11 The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing, People’s Republic of China2 Department of Biological Sciences, Center for Systems Biology, The University of Texas at Dallas, Richardson, United States of America3 Bioinformatics Division, TNLIST and Center for Synthetic & Systems Biology, Tsinghua University, Beijing, People’s Republic of Chinaa guoweilong@pku.edu.cnb hongwu@pku.edu.cn* Present Address: Department of Crop Genomics and Bioinformatics, China Agricultural University, Beijing, People’s Republic of China. 30 08 2016 2016 6 3220705 04 2016 03 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Although non-CG methylations are abundant in several mammalian cell types, their biological significance is sparsely characterized. We gathered 51 human and mouse DNA methylomes from brain neurons, embryonic stem cells and induced pluripotent stem cells, primordial germ cells and oocytes. We utilized an unbiased sub-motif prediction method and reported CW as the representative non-CG methylation context, which is distinct from CC methylation in terms of sequence context and genomic distribution. A two-dimensional comparison of non-CG methylations across cell types and species was performed. Unambiguous studies of sequence preferences and genomic region enrichment showed that CW methylation is cell-type specific and is also conserved between humans and mice. In brain neurons, it was found that active long interspersed nuclear element-1 (LINE-1) lacked CW methylations but not CG methylations. Coincidentally, both human Alu and mouse B1 elements preferred high CW methylations at specific loci during their respective evolutionary development. Last, the strand-specific distributions of CW methylations in introns and long interspersed nuclear elements are also cell-type specific and conserved. In summary, our results illustrate that CW methylations are highly conserved among species, are dynamically regulated in each cell type, and are potentially involved in the evolution of transposon elements. ==== Body In mammals, CG methylations have been extensively studied for decades and have been found to be conserved12 and dynamically regulated in development3. CG methylations play important roles in regulating gene transcription4 and silencing transposon element (TE) activities5. Mammalian non-CG methylations, also known as CH (H can be A, C, T) methylations, were reported to be abundant only in specific cell types and low in most somatic cell types678. Although CH methylation (mCH) has been well studied in Arabidopsis9, it is still unclear whether mCH has a similar function in mammals10. Taking advantage of the accumulating DNA methylomes across multiple cell types and species, we aimed to shed light on the potential functions of mammalian mCH. Based on current knowledge, mammalian mCH-enriched cell types can be categorized into two main categories: brain neurons1112 and germline cells. The mCH-enriched germline cells consist of embryonic stem cells (ESCs)13, induced pluripotent stem cells (iPSCs)14, oocytes151617, and male and female primordial germ cells (PGCs)1819202122. Unlike in oocytes15, mCH rarely occurs in sperm cells2324. Most differentiated cells, such as fibroblast cells13, blood cells7, are low in mCH. A recent study reported that mCH was abundant in myocytes25, extending our understanding of somatic mCH. Although several reports have described potential roles for mCH, the explicit biological functions of mCH remain a mystery6. Comparing mCH across different cell types or species is an efficient way to characterize such modifications. Chen and colleagues performed inter-sample comparisons of mCH in human ESCs and demonstrated that mCH is conserved in TACAG contexts26. Lister et al. compared human ESCs and iPSCs, showing that mCH is increased during reprogramming but in an incomplete manner14. Subsequently, Ziller et al. performed a comparison of a panel of human DNA methylomes7 and confirmed the abundance of mCH in pluripotent cell types and found that mCH was significantly dependent on DNMT3 expression. Varley et al. generated 82 human methylomes and found that brain mCH is similar among individuals but has a different motif as in ES27. By comparing brain methylomes from humans and mice, Lister and colleagues illustrated that mCH is enriched in neurons and glias and the neuronal mCH is also highly conserved between the species12. Until now, there have been no studies investigating mCH across both cell types and species at the same time. We investigated mCH by collecting 51 mCH-enriched DNA methylomes in both humans and mice using data previously published by multiple groups. In this cohort, the cell types included brain neurons, ESCs/iPSCs, oocytes, and male and female PGCs. Our previous study showed that the two contexts CHG and CHH are not necessary to be studied separately in human pluripotent cells28. We designed a computational method to predict the most significant bi-partition of the motif of highly methylated CH sites. Interestingly, almost all of the samples support CW and CC as the most independent sub-context. Context and spatial studies demonstrated that CW is the representative context for mCH. Our unsupervised clustering based on sequence preferences revealed that mCW is more closely related among cell types than among species. This result extended our understanding of mCW as a dynamically regulated DNA modification within different cell types, which is also highly conserved among species. Furthermore, we evaluated mCW enrichment in genes and in TEs, uncovering features of conservation and cell-type specificities. Closer inspections of mCW distribution led us to several novel findings. In brain neurons, long interspersed nuclear element-1 (LINE-1) lacks mCW, especially young LINE-1. Simple repeats are enriched with mCW in all cell types but are particularly pronounced in PGCs. Coincidentally, both human Alu elements and murine B1 elements showed several loci preferred higher mCW during evolution, extending current knowledge beyond their CG methylation (mCG) patterns2930. Additionally, we found a peak of mCG at the promoter of young LINE-1 elements in PGCs, but not in other cell types. Our previous finding that intronic mCH was strand-skewed in human ES cells28 was also found in mouse ES cells. Further results revealed strand-specific distributions of mCW in certain TEs that are shared by the two species. In general, our work has advanced the knowledge of mammalian non-CG methylations and provided interesting clues for future investigations. Results mCH abundance DNA methylomes across species and cell types To study mammalian mCH, we collected 51 bisulfite-sequencing libraries for both humans and mice (Table 1; Supplementary Table S1) and regenerated most of the methylomes from raw sequencing data using BS-Seeker231. Investigated cell types included brain neurons, ESCs, iPSCs, oocytes, and male and female primordial germ cell (MPGCs and FPGCs, respectively). For each cell type, multiple samples from different groups were collected to eliminate inter-sample differences. In this cohort, average methylation levels of CG and CH among samples are discordant (Supplementary Fig. S1a). Also, the contributions of mCH to overall DNA methylation in the selected samples are inevitable (Supplementary Fig. S2). CW and CC are two different mCH contexts in mammals In plants, non-CG methylations have been studied separately in CHG and CHH contexts1. Our previous study showed that CHG and CHH methylations are highly correlated and not necessary to be separated in human pluripotent cells28. To unbiased identify any different sub-contexts of mCH in mammals, we developed a computational method named minimum dependence decomposition (MiDD) (see Methods). Considering the entropy at each position of previously reported mCH motifs6, we used the 6-mers (NNmCHNN, N = A, C, G, T) to characterize the sequence preference of mCH. Utilizing MiDD, the most significant bipartitions of the 6-mers were used for building a hierarchical motif tree for mammalian mCH (Fig. 1a). Interestingly, MiDD reported CW and CC as the most significantly independent bipartition of mammalian mCH (Fig. 1b). The average methylation levels of CW and CC are also discordant among all samples (Fig. S1b), and the conserved motifs of mCW and mCC were markedly different (Supplementary Fig. S3). For example, in the sample hBrain_Mfg12y_Lis, the mCW motif is TNmCACC (Fig. 1c), whereas the mCC motif is NNmCCNN (Fig. 1d). To confirm our prediction from a spatial distribution perspective, we profiled the distributions of mCA, mCC, mCG and mCT levels across chromosomes. The distribution of mCC is apparently discordant with those of mCW and mCG (Fig. 1e–f). Although mCA and mCT were predicted to be the secondary significantly independent context decomposition of mCH (Fig. 1b), the chromosome-wide profiles of mCA and mCT were concordant (Fig. 1e, Supplementary Fig. S4) and highly correlated (Fig. 1f). In terms of bulk methylation levels, mCW was confirmed to be independent from mCG (Supplementary Fig. S5a), and mCHG and mCHH were generally concordant (Supplementary Figs S5e and S6), whereas mCC was weakly correlated with the other contexts (Supplementary Fig. S6). Considering all of these results, we decided to use the representative context CW in subsequent analysis. Context preferences of mCW are cell-type specific and conserved among species Currently, non-CG methylations are considered as context-dependent in mammals2628. As mCW levels are different among samples, we used the ranks of the methylation levels of 6-mers (NNmCWNN) to represent the context preferences of mCW so that the samples are comparable. Thus to evaluate the motif similarities in mCW among samples, we performed an unsupervised clustering, where distance is defined according to Spearman’s rank correlation coefficients of the average methylation levels of the 6-mers (see Methods). To avoid the bias related to transcriptional activities or library types, we excluded annotated genetic regions, repeats and CpG islands when calculating average methylation levels. Interestingly, the results showed that the sequence preferences of mCW are more similar among cell types, rather than among species (Fig. 2a), indicating that the mCW motif is cell-type specific and is also conserved between humans and mice. Based on the clustering results, the oocytes and brain neurons samples are grouped closely with similar motif, TNmCACC (Fig. 2b), which is in line with results from the previous studies1532. The ESC and iPSC samples are grouped into two sub-clusters (Fig. 2a) with different mCW motifs (Fig. 2b). Samples in one group are all from mice, harbouring the motif of NNmCAN. The other group has the motif TAmCAG, which includes all of the human ESCs/iPSCs and the mouse ESCs from Smith et al.33. Differences between human ESCs and mouse ESCs have been extensively discussed34. It has been proposed that mouse ESCs have the following two pluripotent states: a naïve ICM-like state and a primed pluripotent state. Human ESCs are in a primed pluripotent state35, and making it difficult to stably maintain a naïve human pluripotent stem cell line34. Our results indicate there may be distinct mCW signatures at different stages of pluripotency. The majority of PGC samples fell into one group with a relatively weak motif of mCA. The large distances between samples from different laboratories indicated a strong bench effect in gathering PGC samples or preparing libraries. Additionally, most of the MPGCs and all of the FPGCs are clustered together. Interestingly, two mouse MPGC samples, both of which are at E16.5, fell together within oocytes, with a motif of TNmCACC. Moreover, they were from different laboratories, ruling out the possibility of a bench effect. A previous study showed that MPGCs at E16.5 gained de novo CG methylation compared with earlier MPGC stages21. Our study provides additional evidence supporting the notion that the mouse MPGCs at E16.5 already gained epigenetic signatures comparable to mature oocytes. Although DNMT3a, DNMT3b and DNMT3L have been reported to be responsible for non-CG methylations in mammals715, the three together are not necessary for a specific cell type6. As a reflection of biological orientation, mCW motifs are conserved between humans and mice, and are cell-type specific, indicating that mCW is elaborately maintained and regulated in different cell types. Enrichments of mCW are cell-type specific and conserved among species To investigate the possible functions of mCW, we quantified the enrichment of mCW in transposon elements, which make up approximately 45% of the human genome36. For each cell type, we used recurrent mCW sites among different samples versus randomly selected CW sites to calculate the fold enrichments of mCW in interrogated regions (see Methods). Interestingly, enrichments of brain neuronal mCW are consistent between humans (Fig. 3a) and mice (Fig. 3b). Brain LINE-1 elements and long terminal repeats (LTRs) lack mCW, but mCW is enriched in mammalian interspersed repetitive (MIR) elements and LINE-2 elements. Both primate Alu and murine B1 elements are thought to be derived from 7SL-RNA37, and their evolutionary histories are independent30. In the brain, the Alu and B1 elements consistently lack mCW. In ESCs and iPSCs, mCW is significantly deficient in LINEs and LTRs, whereas mCW is significantly enriched in human Alu (Supplementary Fig. S7a) and mouse B1 (Supplementary Fig. S7b). In PGCs, mCW is mainly enriched in simple repeat regions (Supplementary Figs S7c,d, and S11). In oocytes of both species, mCW is consistently deficient in LTRs and MIRs but enriched in SINE elements (Supplementary Fig. S7e,f). The results in human oocytes were not significant, probably as a result of the limited sample numbers for analysis. We also investigated gene-related regions. The results showed that gene bodies of ESCs and oocytes are enriched in mCW, whereas in the brain, mCW is depleted in the gene body (Fig. 3c,d; Supplementary Figs S8 and S9); these results were consistent between the two species. mCW and mCG are concordant across gene bodies in brain neurons, ESCs and oocytes. However, in PGCs, mCG is lower in the promoter than in the gene bodies (Supplementary Fig. S9), and the distribution of mCW is almost flat across the gene bodies and flanking regions (Supplementary Fig. S10). Our results present a general picture that enrichments of mCW in genomic regions are cell-type specific, and are also conserved. Young LINE-1 elements prefer low mCW levels in brain neurons We generated DNA methylation profiles across genes and transposons. Consistent with the enrichment analysis, all brain samples showed that the LINE-1 elements are devoid of mCW (Fig. 4a,b), but not mCG (Supplementary Fig. S14). It is known that LINE-1 elements constitute approximate 20% of the mammalian genome and are regulated by methyl-CpG-binding protein 2 (MeCP2)38. Additionally, mCH in neurons can be bound by MeCP232. Our results indicate that LINE-1 activities in the brain may be regulated by mCW. We further investigated methylation distribution within the sub-groups of LINE-1 elements. In humans, L1ME (most ancient), L1MD, L1MC, L1MB, L1MA, L1PB and L1PA (youngest) were investigated. Interestingly, the younger sub-groups prefer lower mCW levels (Fig. 4c, Supplementary Fig. S12). The ancient LINE-1 elements (from L1ME to L1MB) demonstrated higher mCW levels in the transcription region than in the flanking region. In mice, L1ME (most ancient), L1MD, L1MC, L1MB, L1MA, L1_Mur, L1_Mus and L1Md_T (youngest) were studied, and a similar phenomenon (Fig. 4d, Supplementary Fig. S12) was observed. Additionally, in mice, oocytes and two oocyte-similar MPGC samples lack mCW in LINE-1 elements, especially in younger LINE-1 elements (Supplementary Fig. S12). In additional to pre-existing knowledge that LINE-1 RNA is abundant in neurons39, our results indicated that LINE-1 elements are under the regulation of mCW, rather than mCG. Promoters of young LINE-1 elements prefer high mCG levels in PGCs We also profiled the distributions of classical mCG in LINE-1 elements. Interestingly, both humans and mice showed a peak in mCG at the promoters of LINE-1 elements in PGCs (Fig. 4e,f), but not in other cell types (Supplementary Fig. S14). Specifically, the youngest LINE-1 sub-groups, human L1PA and mouse L1Md_T, showed the highest mCG levels in each PGC sample (Fig. 4g,h, Supplementary Fig. S13). At the PGC stage, CG dinucleotides are known to be globally demethylated18, and Tang et al. showed that younger LINE-1 elements tend to be less active19. Our results implied that, the young LINE-1 elements in PGCs are suppressed by the high mCG in the promoter region. Loci in human Alu and murine B1 elements prefer higher mCW levels during evolution Alu elements have an important role in shaping the primate genome, and their retrotransposition rates are ten times higher than those of LINE-1 elements29. We observed several loci of human Alu elements that preferred higher mCW levels throughout evolution. Three main Alu sub-groups, including AluJo (ancient), AluSx and AluY (young), were studied. The mCW profile across the Alu elements showed a cell-type specific signature (Fig. 5). In ESCs/iPSCs, the highest peak of mCW was observed at the 5′ ends of Alu elements, which is consistent with our previous finding28. Interestingly, in human ESCs/iPSCs, we found an increase in mCW levels at the 5′ end peak position from the ancient AluJo to the younger AluSx (Fig. 5). In brain neuron and oocyte samples, we also found loci showing increased mCW levels from ancient to young Alu elements. Upon a closer investigation, we found that the antisense sequence from 102 bp to 107  bp is CTmCGCT in AluJo, and was mutated to TTmCACC in AluSx by transitions at three nucleotides, becoming a brain neuron and oocyte preferred mCH context, TNmCACC (Fig. 5). B1 elements are the largest short interspersed nuclear element (SINE) family in rodents, with lengths of approximately 150 bp30. Similar to humans, we also found several loci in murine B1 elements with increased mCW levels during evolution (Supplementary Fig. S15). However, the mCW peak at the 5′ end of the B1 element is not as high as in human Alus (Fig. 5, Supplementary Fig. S15). Based on the conserved sequence backbone, the 5-mer context at 25 bp from the 5′ end of the B1 element in the TAAAG context, which is one nucleotide different from the corresponding cytosine site in the TACAG context in human Alu (Fig. 5). This different nucleotide may partially explain mouse ES does not prefer TAmCAG as does the human ES and as it may be under selection pressure of SINE elements. Strand-specific mCW is cell-type specific and is conserved among species Our previous work reported that mCH in human pluripotent cells is strand-skewed in introns and in SINE and LINE elements28. We then characterized the strand-specific distribution of mCW in gene-related regions and TEs. Human and murine ES/iPS samples also showed significantly higher mCW in the antisense strands in all of the intronic regions (Fig. 6a). The higher mCW in the sense strands of LINE-1 elements in ESC and LINE-2 elements in the oocyte and brain neuron samples are also consistent between the two species (Fig. 6b). Human Alu elements showed higher mCW in the antisense strand in all human samples. MIR showed higher antisense-strand mCW in most samples. Although the biological meaning of the strand-skewed mCW is unclear, our results indicate that the skewed distributions of mCW in SINEs and LINEs are conserved, and are also cell-type specific. Discussion Previous studies of mammalian non-CG methylations either considered CH contexts as a whole12, or separated CH into CHG and CHH11. We developed new method, MiDD, and reported that CW and CC were the most significantly independent sub-contexts of mammalian mCH (Fig. 1). We also found that mCW was the representative context for non-CpG methylation. Carrying out a two-dimensional comparison across both cell types and species, we found the sequence preference of mCW is cell-type specific and is also conserved between humans and mice (Fig. 2). Our subsequent enrichment studies of recurrent mCW in genes and repeat elements also confirmed this conclusion (Fig. 3, Supplementary Figs S7 and S8), and led to many novel findings. First, we found that the LINE-1 elements in brain neurons preferred lower mCW (Fig. 4a,b), indicating a regulation mechanism dependence on mCW rather than mCG. Second, younger LINE-1 elements in brain neurons preferred lower mCW in both humans and mice (Fig. 4c,d), suggesting a conserved roles for mCW in the evolution of LINE-1 elements. Third, we found several loci in Alu and B1 elements retaining higher mCW during evolution (Fig. 5 and 19), and we also found a local region with mCW-prone mutations from ancient AluJo to younger AluSx elements (Fig. 5). Fourth, in genes, we also found that mCW in ES intronic regions had the most significant skewness (Fig. 6). Fifth, mCW in mouse E16.5 MPGCs has an oocyte-like motif and distribution (Fig. 2, Supplementary Figs S9 and S16), which was confirmed by data from different laboratories. Taken together with the previous knowledge of increased mCG in mouse E16.5 MPGCs compared with E13.5 MPGCs21, the epigenetic signature suggested that late MPGCs may undergo an epigenetic regulation process similar to that of maturing female oocytes. Finally, beyond mCW, we also found that promoters of young LINE-1 elements in PGCs retained high mCG (Fig. 4e–h, Supplementary Fig. S13), whereas CG is globally demethylated in this stage. Until recently, the functions of mammalian non-CG methylations are largely unclear, many of our findings suggest that mCW may guide the evolution of TEs. Our sequence preference analysis showed that brain and oocyte samples share a similar mCW motif, TNmCAC (Fig. 2). However, the distributions of mCW across chromosomes are largely different (Supplementary Fig. S4). Additionally, MIR elements showed significant enrichment of mCW in brain neuron samples (Fig. 3a,b) but were significantly deficient of mCW in oocytes (Supplementary Fig. S7f). Together, these results indicate that sequence preference can not fully explain the distributions of mCW. We showed that the mCW motif is TAmCAG in human ES/iPS samples, and mCA in most mouse ES samples. Although the mCW motifs of the mouse ES samples from Smith et al.33 are TAmCAG, the results lacks confirmation from independent work. One possibility is that the mCW motif is dynamically regulated during embryological development. It would be interesting to profile the DNA methylomes of different cell types in the early embryo. Our finding that the 5′ ends of B1 elements lost the TACAG pattern due to a C to T mutation involving human Alu elements, suggests that there may be weaker selection pressure on the TAmCAG motif in mouse ESCs. In our cohort, the number of oocyte methylomes was limited, especially for humans. In the future, a larger number of samples would increase the statistical power. The recurrence phenomenon involving different samples and different species provides us with advantages to discriminate batch effects and inspect recurring mCW characteristics. For mCC, we did not find any regular pattern as for mCW. Majority samples in our cohort have very low mCC levels (around 0.01), with a few exceptions (Supplementary Fig. S1b). The mCC-high samples are not specific in cell-type, in library type, or in species. We did not found any conserved sequence preference other than the CC dinucleotides (Fig. 1d, Supplementary Fig. S3). And the distribution of mCC across chromosomes are almost flat for most samples (Fig. 1e, Supplementary Fig. S4). It is still unclear whether the mCC is biological significant. But it is wise to discard mCC, and use mCW as the representative non-CG methylation pattern. Our results demonstrate many highly conserved properties of mCW in humans and mice (Supplementary Table S2), and as well as evidence of cell-type specific distributions. We still have a limited understanding of mammalian non-CG methylations. There are far more cell types and species whose non-CG methylations remain to be explored. In the future, we hope to draw a full picture of mammalian non-CG methylations with DNA methylomes with more cell types and species. Methods Rebuilding DNA methylomes DNA methylomes were downloaded from multiple resources (DRA000484, DRA000570, DRA000607, DRA003802, ERP001953, GSE11034, GSE16256, GSE30199, GSE30206, GSE34864, GSE37202, GSE42923, GSE46644, GSE46710, GSE49828, GSE51239, GSE52331, GSE56650, GSE61457, GSE63394, GSE63394, GSE63818, SRP057098) (Supplementary Table S1). Human methylomes were prepared based on hg18, and mouse methylomes were prepared based on mm9. The majority of the DNA methylomes were generated by realignment with raw sequences using BS-Seeker231. We used Bowtie as the base aligner, trimmed the adapters, allowed up to 4% mismatches for one read and selected uniquely aligned reads for methylation calling. To avoid biased context calls proximal to mutated sites, we called single nucleotide variants (SNVs) from the ATCGmap files in the same way as described in Luz et al.40 and discarded the cytosines within 1 bp distance from the SNVs. Minimum dependence decomposition (MiDD) An alternative to the maximum dependence decomposition (MDD) method41, MiDD was developed to study the subgroups of a motif. To find the novel context partition of mCH, we applied MiDD to the 6-mer context, NNmCHNN. As shown in Fig. 1a, we enumerated all 6-mer bipartitions based on each position. For each bipartition, we performed a chi-squared test on the methylation frequencies (numbers of occurrences in 1000 cases) of the 6-mer lists in the two subgroups. For each sample, the partition with the most significant p-value was selected. We selected the bipartition reported as the top significant bipartition by at least half of the samples. Then, MiDD method was applied within each sub-group hierarchically, until no significant bipartition was found (p-value < 0.05). Finally, the hierarchical motif tree was constructed. Normalized motif logo based on 6-mers Given that the frequencies of 6-mers (NNmCNNN) were unbalanced throughout the genome, we applied a normalization method for estimating the nucleotide frequencies at each position of the 6-mers. The 6-mers containing the CCGG sub-context were discarded so as to make RRBS and WGBS comparable on non-CG context. First, the average methylation levels of the 6-mer patterns were independently calculated throughout the genome, noted as Mw, where w is one 6-mer. At each position (p) in the 6-mer, we calculated the weight of each nucleotide (n, n∈{A, C, G, T}) as where wp indicates the nucleotide at position p of the 6-mer pattern w. The normalized frequency of each nucleotide was calculated as Logo plots were generated by WebLogo42. Enrichment study of recurrent methylated CW sites in specific regions The recurrent mCW sites among multiple non-RRBS samples were prepared for each cell type. For the brain neuron, ESC/iPSC and PGC samples, the recurrent CW sites were defined as coverage ≥4 reads for at least 4 samples (background). Within all of the background sties, the recurrent methylated CW sites (foreground) were defined as the top 10% methylated mCW in each sample for at least 75% of the samples. Given the low number of oocyte samples in each species, we merged sites from multiple samples together as a single meta-methylome. The sites with the top 80% coverage were used as background. Within the background the top 10% methylated sites were used as foreground. Then, the fold enrichment of mCW in specific regions was measured by the log2 odd-ratios by comparing both foreground and background sites in the region. Strand-specific study of mCW As shown in Fig. 6, we calculated the strand-specific distribution of mCW as previously described28. The signed log2 p-values are used to represent the significance of skewness. Positive numbers indicate higher methylation levels on the sense strand, and vice versa. Investigated genomic regions The intergenic region is defined as the region in length of 1 k bp, which is 10 k bp upstream of transcription starting sites (TSS). The gene-related regions include the promoter (from 500 bp upstream of the TSS to 100 bp downstream of the TSS), 1st exon (1stExon), posterior (2nd and later) exon (postExon), posterior 5′SS region (post5SS), posterior MI (middle intron) region (postMI) and posterior 3′SS region (post3SS). The 5′SS, MI and 3′SS regions are defined as in our previous study28. The transposon regions include SINE, LINE, LTR and other DNA repeat families, annotated in the RepeatMasker dataset from UCSC (http://genome.ucsc.edu/). Additional Information How to cite this article: Guo, W. et al. Mammalian non-CG methylations are conserved and cell-type specific and may have been involved in the evolution of transposon elements. Sci. Rep. 6, 32207; doi: 10.1038/srep32207 (2016). Accession Code: The DNA methylomes are available in the Gene Expression Omnibus repository [GSE77019]. Supplementary Material Supplementary Information We thank Hongshan Guo, Dr. Fan Guo and Dr. Chengqi Yi of Peking University for discussion. We thank Prof. Minping Qian (Peking University) for providing suggestions for MiDD method. This work was funded by a General Financial Grant from the China Postdoctoral Science Foundation [2015M570010] (to WG), and in part by the Postdoctoral Fellowship (to WG) and grant support (to HW) of Peking-Tsinghua Center for Life Sciences, and also by National Basic Research Program of China [2012CB316503] (to MZ), National Natural Science Foundation of China [91519326] (to MZ). The work was partially carried out at Peking University High Performance Computing Platform, and the calculations were performed on CLS-HPC. Author Contributions W.G., M.Q.Z. and H.W. initiated the project. W.G. directed and conceived the study, gathered the raw data, performed the analyses and wrote the manuscript. M.Q.Z. and H.W. revised the manuscript. Figure 1 CW and CC are the major independent non-CG contexts. (a) Schematic of the MiDD (minimum dependence decomposition) method. Enumeration of all bipartitions at each base of the 6-mer (NNmCHNN) was conducted and the most significantly independent bipartition for at least half of the samples was adopted. The selection processes were performed for each sub-context recurrently until no significant bipartition was found. (b) The hierarchical motif tree of mCH built by MiDD. The numbers “n/m” beside the branches indicate that m samples report significant bipartition and that n samples report the represented division as the most significant bipartition. The red nucleotide indicates the position for bipartition. W = {A, T}. B = {C, G, T}. (c,d) The normalized logo plots for mCW (c) and mCC (d) in the sample hBrain_Mfg12y_Lis. (e) An example showing the methylation level profiles in four contexts (CA, CC, CG and CT) across chromosome 17. Lines are smoothed based on the average methylation levels in bins. Bin size, 20 k bp. (f) Heatmap showing the spatial correlation coefficients of the methylation levels among the four contexts (CA, CC, CG and CT) as in (e). Number in each cell, Pearson’s r. Distance is defined as (1−r2) for hierarchical clustering. Figure 2 Comparison of the sequence preferences of mCW. (a) Unsupervised hierarchical clustering based on the ranking of the average methylation levels of 6-mers (NNmCWNN). Colours indicate cell types. Distance is defined as (1−ρ2), where ρ is Spearman’s correlation coefficient, measuring the similarity of the sequence preferences based on the bulk methylation levels of 6-mers for each sample pair. Clustering method, complete. (b) Logo plots of the normalized mCW motifs. Figure 3 Enrichments of brain neuron mCW in genomic regions are consistent between humans and mice. Enrichment studies of the recurrent brain mCW sites in multiple samples in humans (a,c) and mice (b,d). The repeat elements investigated include SINEs, LINEs, LTRs and others (a,b). The gene related regions are separated as the promoter, gene body, intergenic regions, first exon (1stExon) and posterior exons (postExon), introns (postIntron), 5′ splicing site region (post5SS), middle intron (postMI) and 3′ splicing site region (post3SS). Y-axis, enrichment score, defined as the log2 fold changes between observed high mCW site count and expected high mCW site count. The mean (bar height), s.d. (error bar), and p-values (by two tailed t test; *p < 0.01; **p < 1e-6) are calculated based on the enrichment scores in all autosomes. Figure 4 Young LINE-1 elements prefer lower mCW in brain and higher mCG at promoters in PGCs. Profiles of brain mCW across LINE-1 elements in humans (a) and mice (b). Examples of mCW profiles across subtypes of LINE-1 elements, including L1PA (youngest), L1PB, L1MA, L1MB, L1MC, L1MD, and L1ME (most ancient) in humans (c) and L1Md_T (youngest), L1_Mus, L1_Mur, L1MA, L1MB, L1MC, L1MD, and L1ME (most ancient) in mice (d), showing that young LINE-1 elements prefer lower mCW. Profiles of PGC mCG across LINE-1 elements in humans (e) and mice (f). Examples of mCG profiles across subtypes of LINE-1, from young to ancient in humans (g) and mice (h), showing that young LINE-1 elements prefer higher mCG at promoters. Figure 5 Young human Alu elements prefer mCW. Profiles of mCW across the sub-groups of human Alu elements from 500 bp upstream to 500 bp downstream in brain neuron, ES and oocyte. The mCW levels are shown for the sense strand (red) and antisense strand (green) separately. AluJo is the most ancient, and AluY is the youngest Alu elements. Yellow blocks mark the loci of Alu elements, where mCW levels increase with the evolution of Alu elements. The corresponding sequence mutations are shown below the profiles, and the nucleotides at the mutated positions are marked in red. Figure 6 Strand-specific mCW in genes and TEs. (a) Heatmap for skewness of mCW in gene related regions, showing that intronic mCW is significant in both human and mouse ES samples. The colour index indicates the signed log2 p value, by two-tailed t test. Negative value, higher mCW on antisense strand; and vice versa. (b,c) Heatmaps for skewness of mCW in multiple transposon regions, including SINEs, LINEs and LTRs, in both humans (b) and mice (c). Table 1 All the gathered DNA methylomes. Human (26) Brain ESC/iPSC* FPGC MPGC Oocyte 7 6 5 5 3 AdFront_Wen H1_Lis 10wE1_GuoF 10wE2_GuoF AmpMinus_Okae FcF53yNeun_Lis H9_Lis 11wE1_GuoF 19wE1_GuoF AmpPlus_Okae FcM55yNeun_Lis PBAT_Tang 17wE1_GuoF 19wE2_GuoF Rrbs_GuoHS FCN_Zill Ads_Lis* 7w_Tang 9w_Tang   Hs1570_Zeng Ff_Lis* UW160_Gkoun UW165_Gkoun   Hs1832_Zeng Imr90_Lis*       Mfg12y_Lis Mouse (25) Brain ESC FPGC MPGC Oocyte 8 8 2 3 4 129_Xie 2line_Kob E13p5_Seis E13p5_Seis GV_Kob Cast_Xie J1_Seis E16p5_Seis E16p5_Kob GV_Shira F1i_Xie p01Rrbs_Smith   E16p5_Seis Rrbs_GuoF FcF6wNeun_Lis p02Rrbs_Smith     Rrbs_Shen FcM7wNeun_Lis p032Rrbs_Smith       Rrbs_Meis P0_Ficz       Rrbs_Smith Wt_Stad       Wt_GuoJU Wt_Li       26 human methylomes and 25 murine methylomes were collected. Cell types include brain neurons (Brain), embryonic stem cell (ESC), induced pluripotent stem cell (iPSC), female PGC (FPGC), male PGC (MPGC), and oocyte. The iPS cell lines are marked with asterisk. Samples in RRBS libraries are marked in italic. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3215810.1038/srep32158ArticleMicroRNA393 is involved in nitrogen-promoted rice tillering through regulation of auxin signal transduction in axillary buds Li Xiang 1Xia Kuaifei 1Liang Zhen 2Chen Kunling 2Gao Caixia 2Zhang Mingyong a11 Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement & Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China2 State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, Chinaa zhangmy@scbg.ac.cn30 08 2016 2016 6 3215831 05 2016 03 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Rice tillering has an important influence on grain yield, and is promoted by nitrogen (N) fertilizer. Several genes controlling rice tillering, which are regulated by poor N supply, have been identified. However, the molecular mechanism associated with the regulation of tillering based on N supply is poorly understood. Here, we report that rice microRNA393 (OsmiR393) is involved in N-mediated tillering by decreasing auxin signal sensitivity in axillary buds. Expression analysis showed that N fertilizer causes up-regulation of OsmiR393, but down-regulation of two target genes (OsAFB2 and OsTB1). In situ expression analysis showed that OsmiR393 is highly expressed in the lateral axillary meristem. OsmiR393 overexpression mimicked N-mediated tillering in wild type Zhonghua 11 (ZH11). Mutation of OsMIR393 in ZH11 repressed N-promoted tillering, which simulated the effects of limited N, and this could not be restored by supplying N fertilizer. Western blot analysis showed that OsIAA6 was accumulated in both OsmiR393-overexpressing lines and N-treated wild type rice, but was reduced in the OsMIR393 mutant. Therefore, we deduced that N-induced OsmiR393 accumulation reduces the expression of OsTIR1 and OsAFB2, which alleviates sensitivity to auxin in the axillary buds and stabilizes OsIAA6, thereby promoting rice tillering. ==== Body Rice tillering (branching) is an important agronomic trait, as the number of tillers per plant determines the panicle number, which is a key factor of the rice grain yield12. The rice tiller represents a form of shoot branching that only exists in monocotyledonous plants at the jointing stage. Unlike in Arabidopsis, the dominance of the apical meristem in rice is weak, so tillering occurs during the vegetative stage upon inhibition by the apical meristem or in previously activated buds, which is not sufficiently strong. However, when the panicles of the main stems begin to differentiate, the buds formed at the elongated upper internodes become dormant3. The dormant bud is activated and later transformed into an activated, growing tiller. This process is complicated and intricate. Rice tillering is mediated by the interplay of the environment and endogenous signals such as phytohormones. It is already known that auxin, cytokinin (CK), and strigolactones (SLs) are specific regulators involved in bud outgrowth regulation4. Auxin and SLs inhibit bud outgrowth, whereas CK activates and promotes this process56. Nitrogen (N) can considerably increase CK levels in rice tiller buds and nodes, and can augment IAAs (early auxin responsive genes) in rice nodes7. The tiller number per plant is strongly affected by N fertilizer availability. High N fertilizer allows rice to produce more tillers7, and the Arabidopsis root system architecture is mediated by N availability8. More is known of the mechanism by which limited N reduces branching than how abundant N promotes branching. In Arabidopsis, nitrate limitation reduces shoot branching by both inhibiting bud initiation and weakening the basipetal sequence of bud initiation that is caused by flowering9. Auxin was the first phytohormone to be identified as an important regulator of plant branching. Bud outgrowth is strongly inhibited by the apex of a whole plant. If the apex is removed, previously inactivated axillary buds become active and plant branching is initiated10. However, auxin cannot enter axillary meristem cells and therefore, its inhibitory functions are deemed to be indirect11. Auxin suppresses bud development through at least two different processes. First, auxin is synthesized in the plant apex and is transported basipetally towards the root, which is known as polar auxin transport (PAT), and this inhibits bud outgrowth12. Because auxin cannot enter the axillary meristem cells, the second mechanism is regarded as the regulation of other signalling molecules (CK and SLs) by auxin; these proteins can enter axillary meristem cells and regulate axillary bud initiation and outgrowth1314. The PAT model suggests that polar auxin transport and high auxin concentrations inhibit axillary bud development1415. The second messenger model suggests that auxin regulates the distribution and activity of CKs and SLs in the axillary meristem to control plant branching. Both of these models are supported by recent studies16. Several genes have been identified as regulators that control rice tillering and branching. MOC117 controls initiation and outgrowth of axillary meristems at both the vegetative and reproductive stages. LAX1 is a regulator that controls axillary meristem initiation and/or maintenance during rice reproductive development18. OsMADS57 was reported to interact with OsTB1, and targets D14 (Dwarf 14) to control the outgrowth of axillary buds19. OsmiR156 targets OsSPL14 and mediates its degradation to control rice tillering20. In Arabidopsis, auxin and SL signalling are required to coordinate shoot branching with respect to N supply9. MicroRNAs (miRNAs) are a class of oligonucleotides, 20 to 24 nucleotides long, and are endogenous small RNAs that are involved in post–transcriptional gene regulation in multicellular organisms, through influencing both the stability and translation of mRNAs21. miRNAs have important regulatory roles in the uptake, assimilation, and translocation of nutrients in plants22. miR395 and miR399 can regulate the distribution and homeostasis of sulphur and phosphate, respectively, in Arabidopsis and rice2324. miR169 has specific roles in the plant’s response to N deficiency25. miR167 and miR393 were reported to regulate NO3− signalling during lateral root development826. MIR393 is conserved among different plant species27, and recent studies revealed that it has multiple functions in plant growth and development, such as controlling root architecture8, regulation of leaf development28, antibacterial resistance to pathogen attack27, tolerance to stress29, and maintenance of normal plant growth30. In Arabidopsis, miR393 is encoded by two distinct loci: MIR393a and MIR393b. In aerial tissues such as leaves, miR393 is mainly transcribed from MIR393b, suggesting distinct roles for MIR393a and MIR393b28. Moreover, miR393-guided target cleavage processes generate secondary small interfering RNAs (siRNAs) from miR393 target transcripts. Feedback regulates the targeting of neo-generated siRNA, guiding the cleavage of miR393 targets28. Similar to that in Arabidopsis, the rice OsmiR393 family is encoded by two loci, OsMIR393a and OsMIR393b3132. Rice OsMIR393a and OsMIR393b also showed different expression patterns, which suggests that conserved mechanisms were adopted in monocots and eudicots during plant development32. To date, the exact mechanism of rice tillering regulation by OsmiR393 has not been reported. miR393 was shown to target auxin (IAA) receptor genes TIR1 and AFB in different plants, including Arabidopsis and rice313334. TIR1 and AFBs encode F-box proteins, which combine with three other proteins, ASK1, CUL1, and RBX, for assembly into the ubiquitin degradative complex (SCFTIR1) to degrade specific substrates during auxin signaling353637. AUX/IAAs represent a class of proteins that represses auxin signalling. AUX/IAA proteins can bind to and repress ARFs (auxin response factor) to activate downstream auxin-responsive genes. TIR1 and AFBs recognize and bind IAA and degrade AUX/IAA proteins via the SCFTIR1 complex37 to ensure correct auxin signalling. Here, we present findings showing that N-induced rice tillering is caused by attenuating the sensitivity of tiller buds to auxin through microRNA OsmiR393-mediated auxin signal transduction. Results Nitrogen supply promotes OsmiR393 accumulation in rice In Arabidopsis, miR393, which targets AFB3, is a unique nitrogen (N) responsive module that mediates root system architecture in response to external and internal N availability8. To investigate whether OsmiR393 expression also responds to exogenous N fertilizer in rice, we analysed the accumulation of OsmiR393 with various levels of NH4NO3 fertilizer as the N source. The level of NH4NO3 (1.43 mM) in the IRRI nutrient solution38 was set to the normal level (1 N) of N fertilizer. OsmiR393 accumulation increased following exposure to elevating levels of N fertilizer, from 0 mM (0 N) to 5.72 mM (4 N) NH4NO3, as assessed by a quantitative reverse transcription polymerase chain reaction (qRT–PCR) (Fig. 1A) and by a small RNA gel blot (Supplemental Fig. S1). Under conditions of 1 N and 4 N NH4NO3, OsmiR393 expression increased by 1.4- and 3.5-fold, respectively, compared to that of the 0 N condition (Fig. 1A). These results showed that OsmiR393 accumulation in rice is induced by high N fertilizer levels, similar to that observed in Arabidopsis8. Overexpression of OsmiR393 mimics N-promoted rice tillering High N fertilizer can promote tillering in rice, and we found that OsmiR393-overexpressing rice produced more tillers than wild type rice with normal levels of N fertilizer39. Given that high N fertilizer promotes OsmiR393 accumulation (Fig. 1A, Supplemental Fig. S1), we hypothesized that OsmiR393 is involved in mediating N-mediated rice tillering. To test this hypothesis, we first measured the tiller number in wild type japonica rice cultivar Zhonghua 11 (ZH11) with different levels of N fertilizer (Fig. 1B,C). Tiller numbers in ZH11 were increased with elevating levels of NH4NO3. When grown under low N conditions, specifically, 0 and 0.18 mM NH4NO3 (0 N and 1/8 N, respectively), ZH11 produced 2.6 tillers on average. At normal N levels (1.43 mM NH4NO3; 1 N), it produced 5.5 tillers, which is 2-fold greater than that of the 0 N condition. The tiller number reached approximately 10 when plants were cultivated with high N (5.72 mM NH4NO3; 4 N), which is 4-fold greater than that of the 0 N condition. Furthermore, tillering was analysed in three OsmiR393-overexpressing rice lines39, relative to N content. A small RNA gel blot assay confirmed that OsmiR393 accumulated in the three lines (OX393-6, OX393-10, and OX393-31) compared to expression in wild type ZH11, under normal N conditions (1 N) (Fig. 1D). When grown under normal N (1 N), all three OsmiR393-overexpressing lines produced more tillers than ZH11 (Fig. 1E,F). At 1 N, tiller numbers in the three OsmiR393-overexpressing lines reached approximately 8.3, which was about 1.5-fold higher than that observed in ZH11. These results demonstrate that tillering with OsmiR393 overexpression at normal N levels mimics that of ZH11 at higher N levels. Third, to investigate whether OsmiR393 overexpression at different N levels increases tillers as in ZH11, we treated OX393-6 with a gradient of N levels (Supplemental Fig. S2A,B). Although the tiller number in OX393-6 increased with elevating N levels, it did not reach the maximum observed with ZH11 (Fig. 1B,C). With 4 N conditions, the tiller number reached 7.4 in ZH11, but averaged only 5 in OX393-6. Moreover, at each N level (except 4 N), OX393-6 produced more tillers than ZH11. However, OX393-6 and ZH11 reached approximately the same tiller numbers when they were grown at 4 N. At the 1/8 N level, OX393-6 produced on average 5.2 tillers, whereas ZH11 produced 3.8 tillers. At the 1 N level, OX393-6 produced on an average 6.8 tillers and ZH11 produced 4.4 tillers. At the 4 N level, the tiller number for both OX393-6 and ZH11 reached approximately 9.5. In summary, our data suggests that OsmiR393 overexpression is sufficient to increase tillering at almost all N concentrations, indicating that it is involved in N-promoted tillering. However, OsmiR393 overexpression cannot fully mimic N-induced tillering at 4 N, suggesting that other factors/signalling pathways are involved in this process. N fertilizer cannot restore the reduced tiller phenotype of an OsMIR393 mutant To confirm that OsmiR393 is involved in N-mediated rice tillering, OsMIR393 mutants were generated using a clustered regularly interspaced short palindromic repeats (CRISPR) approach4041. An sgRNA sequence was designed to target the mature OsmiR393 sequence and ultimately disrupt this gene. Next, the sgRNA was linked to the sgRNA-Cas9 vector42 and transformed into ZH11. Three knock-out OsMIR393 mutant lines were selected and designated as CRP-9, CRP-15, and CRP-18. A small RNA gel blot assay showed that OsmiR393 accumulation was significantly decreased (Fig. 2A). To inspect the tillering phenotype in these OsMIR393 mutants, we grew them in a controlled paddy that was managed conventionally. Contrary to OsmiR393 overexpressing lines, which produced more tillers (Fig. 1E,F), OsMIR393 mutants produced fewer tillers than ZH11 (Fig. 2B,C). ZH11 produced on average 12.2 tillers, whereas all OsMIR393 mutants (CRP-9, CRP-15, and CRP-18) produced approximately 6–7 tillers, approximately half that of ZH11. Combining these results, we concluded that OsmiR393 regulates rice tillering. To investigate whether OsmiR393 is associated with N fertilizer in rice tillering, and if tillering could be restored in OsMIR393 mutants by N fertilizer, we grew OsMIR393 mutants at a 4 N fertilizer level (Fig. 2E,F). OsMIR393 mutants were planted in a controlled paddy with the aforementioned fertilizer level. A high N level (4 N) did not restore OsmiR393 accumulation in OsMIR393 mutants (Fig. 2D), and the tiller number in ZH11 was still much higher than that in OsMIR393 mutants (Fig. 2E,F). This indicated that N fertilizer and OsmiR393 have overlapping functions in rice tillering. However, tiller numbers in OsMIR393 mutants grown at 4 N were still much higher than in those grown at 1 N. OsMIR393 mutants produced on average 11 tillers at the 4 N level (Fig. 2F), and produced approximately 6 tillers at the 1 N fertilizer level (Fig. 2C). This implies that OsmiR393 is required, but not sufficient, for N-mediated rice tillering. Thus, there could be some other mechanisms, distinct from OsmiR393, involved in rice tillering in the presence of N. Auxin signal transduction, mediated by OsmiR393, is involved in N-mediated rice tillering Two auxin receptors OsAFB2 and OsTIR1 have been verified as target genes of OsmiR393, and seven genes were predicted to be candidate OsmiR393 targets in rice3239. To better understand the actual targets of N fertilizer involved in rice tillering, plant materials were collected comprising regions between the shoot and root containing the SAM (shoot apical meristem), an area of the plant where tillers are formed, for RNA extraction and qRT–PCR detection. qRT-PCR results showed that OsAFB2 and OsTIR1 were down-regulated in the tillering region of OX393-6, and dramatically up-regulated in CRP-9, when compared to levels in ZH11, at N levels of 1 N (Fig. 3A). To determine whether OsAFB2 and OsTIR1 also decreased with elevating N levels, qRT-PCR assays were conducted in wild type ZH11 (Fig. 3B). In contrast to over-expression of OsmiR393 with elevating N levels (Fig. 1A), OsAFB2 and OsTIR1 transcripts decreased (Fig. 3B). This demonstrated that the two target genes (OsAFB2 and OsTIR1) and OsmiR393 are reciprocally expressed with elevating N levels, indicating that OsAFB2 and OsTIR1 are involved in the response to N supply in rice. However, the expression of another putative target gene (LOC_Os03g52320) was up-regulated in response to high N fertilizer levels in ZH11, suggesting that it was not a target of OsmiR393. LOC_Os03g52320 was predicted to encode a GRF1-interacting factor involved in various aspects of tissue differentiation and organ development4344. We speculated that its expression was enhanced, either directly or indirectly, by N fertilizer to control rice seedling growth. One putative target, LOC_Os10g39790 was not amplified by PCR, indicating that it was not expressed in the region that we collected. During auxin signal transduction, TIR1 and AFB2 perceive the auxin signal and degrade repressors of auxin signalling via the SCF (SKP1-CULLIN/cdc53-F-box) complex mediated by the 26S proteasome45. OsmiR393 overexpression and high levels of N, with OsmiR393 accumulation, might desensitize rice plants to exogenous auxin. In contrast, OsMIR393 mutants should become hypersensitive under these conditions. To test this hypothesis, we treated ZH11, OX393-6, and CRP-9 with NAA and observed their responses. The application of 5 mg L–1 NAA typically inhibited the outgrowth of rice tiller buds (Supplemental Fig. S3A, ZH11, and ZH11 mock). However, OX393-6 and 4 N-treated ZH11 plants showed obvious resistance. Tiller buds in CRP-9 were dramatically inhibited, exhibiting hypersensitivity (Supplemental Fig. S3A). This result further confirmed N-mediated rice tillering resulting from attenuated auxin signalling through OsmiR393-mediated cleavage of OsTIR1/OsAFB2. The callus induction rate is an important index reflecting auxin/cytokinin cross-interactions46. To further substantiate our hypothesis, ZH11, OX393-6, and CRP-9 plants were induced to form calluses, and their callus induction rates were compared (Supplemental Fig. S3B). Calluses were induced in ZH11 at a faster rate than in OsmiR393-overexpressing lines, but at a slower rate than in the OsMIR393 mutants. Moreover, adventitious root development is a typical process involved in auxin signaling3247. The OsmiR393-overexpressing line, OX393-6, showed a significant reduction in adventitious roots, whereas that in CRP-9 increased (Supplemental Fig. S3C,D). The above results implied that auxin signalling interferes with adventitious root formation in OsmiR393-overexpressing lines, but is attenuated in OsMIR393 mutants. N fertilizer supply and OsmiR393 overexpression promote axillary bud outgrowth To further investigate the relationship between OsmiR393 overexpression and N-mediated rice tillering, we explored the axillary bud formation process in ZH11 in response to different N levels and in the OsmiR393-overexpressing line, OX393-6, by tissue section (Fig. 4A–E; Supplemental Table S2). After 12 d of cultivation with different levels of N fertilizer, the axillary meristem numbers in ZH11 were inspected. No axillary meristems were observed when ZH11 was grown without N fertilizer (0 N, Fig. 4A), one was observed when ZH11 was grown at 1 N (Fig. 5B), and two were found with 4 N fertilizer (Fig. 4C). With an excessive N level (8 N), only one axillary meristem was observed, while the other had already formed an axillary bud (Fig. 4D). In contrast, the axillary meristem number for OX393-6 grown in 1 N fertilizer was 2 (Fig. 4E), which resembled that of ZH11 with 4 N fertilizer (Fig. 4C). This suggests that OsmiR393 overexpression has the same effect on axillary bud growth as growth with 4 N fertilizer, in ZH11 plants, and that both N fertilizer supply and OsmiR393 expression promote outgrowth of the axillary bud. OsmiR393 expression in rice organs was also analysed by qRT–PCR (Fig. 4G). The results showed that OsmiR393 was expressed in all rice organs, and at a higher level in the roots and booting panicle, indicating that OsmiR393 might play a role in booting panicle development and lateral root growth. To investigate whether OsmiR393 is expressed in the axillary meristem, in situ RNA hybridization experiments were performed (Fig. 4F). The results showed that OsmiR393 was strongly expressed in the lateral axillary meristem (Fig. 4F). These results demonstrate that N fertilizer and OsmiR393 overexpression promote outgrowth of axillary buds, and that OsmiR393 is involved in axillary bud formation. N fertilizer facilitates rice tillering through preventing the degradation of OsIAA6 TIR1 and AFB2 are two members of the SCF complex, which degrades auxin signalling repressors, to ensure correct auxin signaling4548. To determine which proteins are degraded by the SCFTIR1 complex, a construct with cMYC fused to OsTIR1 was generated and transformed into ZH11. Subsequently, a co-immunoprecipitation assay was employed and the precipitated proteins were analysed by mass spectrometry. We found that levels of OsIAA6, a protein belonging to the AUX/IAA class of auxin signalling repressors, changed tremendously between 35S:cMYC–TIR1 and OX393-6 plants. OsIAA6 was reported to enhance rice drought tolerance and regulate tiller outgrowth49. Furthermore, AUX/IAA proteins are a substrate of the SCFTIR1 complex50. We suspected that OsmiR393 might block degradation of OsIAA6 by the OsTIR1 and OsAFB2-mediated SCFTIR1 complex to control rice tillering. To investigate whether OsIAA6 expression changed following altered OsmiR393 expression, or in N-treated ZH11, we generated a construct containing an OsIAA6 full-length protein fused to a MYC epitope tag. This construct was transformed into protoplasts of OsmiR393-overexpressing rice plants, OsMIR393 mutants, and N-treated ZH11. Western blot analysis showed that OsIAA6 was remarkably increased in the three OsmiR393 overexpressing lines (Fig. 5A), and in ZH11 with elevating N levels (Fig. 5B), but was reduced in OsMIR393 mutants (Fig. 5C). These results suggest that OsmiR393 might affect auxin signal transduction through regulation of OsIAA6 accumulation. Discussion Availability of N fertilizer strongly affects rice tillering7, which is a major determinant of grain yield. In the past decades, several key regulators of rice tillering have been cloned and characterized, including MOC117, TAD151, LAX1 and SPA18, OsTB152, OsmiR15620, and genes in the strigolactone signalling pathway53545556. However, the mechanisms through which N fertilizer contributes to rice tiller formation remains elusive. In this study, we revealed a novel role for OsmiR393 in affecting rice tillering in response to N fertilizer. Our results show that adding N fertilizer increases the tiller number in rice (Fig. 1B). This is achieved by enhancing the initiation and activation of tiller bud outgrowth (Fig. 4A–D). High N fertilizer causes OsmiR393 accumulation in tiller bud (Figs 1A and 4F; Supplemental Fig. S1). OsmiR393 accumulation then decreases the transduction of auxin signalling (Figs 3 and 5), resulting in decreased sensitivity to auxin in the tiller buds (Supplemental Fig. S3). Consequently, dampening the response to auxin signalling in the tillers with high N fertilizer might promote initiation and outgrowth of the tiller bud. OsmiR393 responses to N fertilizer Arabidopsis miR393 is induced by nitrate, and the nitrate-responsive miR393/AFB3 regulatory module mediates root system architecture8. In this study, the addition of N fertilizer also caused the accumulation of OsmiR393 in rice seedlings (Fig. 1A; Supplemental Fig. S1). This result suggests that in plants, a similar mechanism has been adopted in monocots and dicots, to respond to environmental changes in N levels. Over time, expression of its target genes (OsTIR1 and OsAFB2) was repressed (Fig. 3B). This suggests that OsmiR393 is also involved in the response to exogenous N in rice. However, unlike Arabidopsis miR393, wherein expression induced by NO3− was specifically localized to the root8, the expression of OsmiR393 in rice was induced by NH4NO3 in the leaf and root tissue (Figs 1A and 4F). This discrepancy between rice and Arabidopsis might be due to different N treatments, or it might imply that there are functional differences for miR393 between dicots and monocots. OsmiR393 affects rice tillering miR393 is a plant-conserved miRNA that participates in many processes during plant development. Recent studies have demonstrated that miR393 plays a role in the establishment of root system architecture in response to nitrate8, the regulation of leaf development28, and auxin signaling57, and is involved in antibacterial resistance in response to pathogens27. In this study, overexpression of OsmiR393 resulted in an increased number of tillers, compared to that in wild type plants (Fig. 1), which was similar to previous findings39. In contrast, an OsMIR393 mutant produced fewer tillers than wild type rice (Fig. 2). Furthermore, supplementation with N did not rescue this defect in OsMIR393 mutants. These results suggest that OsMIR393 is a regulator that participates in modulating rice tillering. In addition, OsmiR393 altered tillering in response to N Fertilizer. OsmiR393 was induced by NH4NO3 treatment in rice (Fig. 1A), and was highly expressed in the bud meristem (Fig. 4F). When OsmiR393 was overexpressed, the increase in tiller numbers induced by N fertilizer (Supplemental Fig. 2) was not as high as that observed in wild type rice (Fig. 1B,C). However, with the same N level, OsmiR393-overexpressing rice produced more tillers than wild type rice (Fig. 1E,B compared to Supplemental Fig. S2). In contrast, the mutation of OsMIR393 resulted in fewer tillers than that in wild type with high and normal N fertilizer levels (Fig. 2). These results suggest that OsMIR393 is involved in the regulation of rice tillering in response to N fertilizer. Rice varieties exhibit high diversity with respect to N response. According to the degree of responsiveness, rice varieties were classified into two groups, less-responsive varieties (such as, ZH11, QZL2, and Balila) and highly-responsive varieties (such as Minghui 63 and Nanjing 6)58. Highly-responsive rice varieties tend to produce more tillers than less-responsive varieties under the same level of N fertilizer58. OsmiR393 expression was compared (Supplemental Fig. S4) in these two groups. However, the expression of OsmiR393 was not obviously different. Different DEP1 alleles confer variable N responses among less responsive and highly responsive rice cultivars, and DEP1 has been the subject of artificial selection during Oryza sativa spp. japonica rice domestication58. This result might imply that OsmiR393 is a general regulator of rice tillering that responds to N fertilizer, but is not involved in the N-response variability observed among different rice varieties. OsmiR393 affects auxin signal transduction in response to N fertilizer treatment Plants synthesize auxin in the growing apex, wherein most of their energy is expended59. Auxin flows from the stem towards the root, basipetally, a phenomenon known as polar auxin transport (PAT). This PAT inhibits axillary bud growth in terms of apical dominance60. It is well known that plants establish their architecture and apical dominance through the effects of PAT. In this study, we revealed that N-fertilizer promotes OsmiR393 accumulation (Fig. 1A) and decrease expression of OsTIR1 and OsAFB2 (Fig. 3B), and increases tiller number (Fig. 1B) in wild type ZH11 rice. This N-promoted tillering is mimicked by OsmiR393 overexpression (Fig. 1E). Moreover, high N-treatment in wild type ZH11 and overexpression of OsmiR393 resulted in a decrease in OsmiR393-target gene (OsTIR1 and OsAFB2) expression (Fig. 3). The reduced expression of OsTIR1 and OsAFB2 might attenuate auxin perception and signalling, and alleviate the effects of apical dominance. TIR1 and AFB2 are two important substrate recognition subunits of the well-known SKP1-CULLIN-F-box (SCF) ubiquitin ligase complex, which functions in auxin perception to promote the 26S proteasome-mediated degradation of Aux/IAA transcriptional repressors47. In addition, the response of MIR393 to environmental signals is conserved across plant species, through the auxin signalling pathway6162. It has been shown that auxin cannot enter axillary meristem cells11; however, auxin from the top buds could inhibit export of auxin that is synthesized in the axillary buds1112. This would increase the auxin concentration in the axillary buds, and inhibit bud outgrowth. High OsmiR393 accumulation after N treatment (Fig. 1A) might decrease sensitivity in the axillary buds to high levels of auxin. We proved that OsmiR393 overexpression and N treatment prevents degradation of OsIAA6 (Fig. 5), which is an important regulator of axillary bud formation4963. This strongly supports the hypothesis that OsmiR393 influences axillary bud formation following N fertilizer treatment through auxin signal transduction. Auxin signalling components have been conserved throughout land plant evolution, and have evolved to control specific developmental processes32. Plant genomes encode large numbers of F-box proteins (FBPs), and there are approximately 700 FBPs in Arabidopsis64. The role of miR393/TIR1/AFBs in the plant’s response to auxin represents a ubiquitous model for adaption and acclimation. Therefore, we concluded that N fertilizer promotes OsmiR393 accumulation, which interferes with auxin signalling, finally triggering tiller production in rice. N fertilizer can promote cytokinin biosynthesis/signalling and stimulates rice to produce more tillers6566. There is evidence to suggest that exogenous application of N fertilizer can promote cytokinin biosynthesis67 and stimulate lateral bud outgrowth68. In Arabidopsis, the expression of AtIPT3 and AtIPT5 is in response to N6970; these genes are key determinants of CK biosynthesis that respond to rapid changes in NO3− availability. Our present results showed that OsmiR393 also responds to N fertilizer, interferes with auxin signalling, and attenuates apical dominance, ultimately leading to tiller production in rice. We did not analyse whether these two N-mediated tillering pathways overlap. Thus, the effect of N fertilizer on rice tillering might be through these two pathways, or in parallel, or through other undiscovered pathways. This also explains why exogenous N-treated OsMIR393 mutants still produced more tillers than wild type plants in normal N conditions (Fig. 2B,C,E,F). Materials and Methods Plant materials and growth conditions Oryza sativa japonica Zhonghua11 (ZH11) was used as the wild type and the source for transgenic plants. Plant materials used in this study were ZH11, three OsmiR393 overexpressing lines (OX393-6, OX393-10, and OX393-31)39, three OsMIR393 knock-out lines (CRP-9, CRP-15, and CRP-18), and the distinct N responsive varieties (QZL2, Balila, Minghui 63, and Nanjing 6)58. Seeds were dried at 37 °C for 24 h before germination at 25 °C, and were supplemented with water in the dark for 48 h. For phenotypic observations, germinated seeds were grown under controlled field conditions or in boxes filled with sand supplemented with hydroponic medium. For nutrient treatments, plants were grown in hydroponic cultures using the International Rice Research Institute (IRRI) liquid culture medium recipe (IRRI nutrient solution)38. Except for modified NH4NO3, all nutrients were kept at the same concentration in all cultures. The NH4NO3 content was based on that of the IRRI nutrient solution, which was designated as the normal level; other N fertilizer levels were based on this concentration. For example, NH4NO3 content in 4-fold N fertilizer was quadruple that of the normal level. For paddy culture, seeds were germinated and sown on soil and then conventionally managed. Vector construction for rice transformation To generate the cMYC-OsTIR1 construct, the coding region of OsTIR1 was amplified by PCR, cloned into the pEASY–Blunt vector (Transgene, China), and subcloned into the pE3n vector71. The cMYC-OsTIR1 fragment was then inserted into the pCAMBIA2300 vector downstream of the maize (Zea mays) Ubiquitin promoter after KpnI and BamHI digestion. To generate the cMYC-OsIAA6 construct, the coding region of OsIAA6 was amplified by PCR, cloned into the pEASY-Blunt vector (Transgene, China), and subcloned into the pE3n vector. The cMYC-OsIAA6 fragment was then inserted into the pCAMBIA2300 vector downstream of the maize (Zea mays) Ubiquitin promoter after BamHI and NotI digestion. All of the primers used to generate the aforementioned constructs are listed in Supplemental Table S1, and all of the constructs were confirmed by sequencing. The constructed vectors were transformed by Agrobacterium tumefaciens strain EHA105. Wild type ZH11 calli were used as the recipients for Agrobacterium-mediated transformation as described72. RNA extraction and quantitative RT–PCR Total RNA was extracted using an RNA extraction kit (Invitrogen, China) and digested with DNase I (Takara, China) according to the manufacturers’ instructions. The RNA quality and integrity were analysed by agarose gel electrophoresis and the RNA concentration was determined using a biophotometer (METASH, B–500, China). cDNA was synthesized from total RNA using AMV Reverse Transcriptase (Promega, China). Small RNA was extracted using an RNAiso kit for small RNA (Takara, China) and digested with DNase I (Takara, China) according to the product manuals. Reverse transcription was performed with a cDNA Synthesis Kit (Promega, China) in combination with a stem-loop RT-PCR technique73. Quantitative RT-PCR was performed on a 7500 RT-qPCR system (Applied Biosystems, USA) with SYBR Green Real-time PCR Master Mix (Toyobo, China) according to the manufacturer’s instructions. Gene expression was normalized to that of rice ACTIN1. Primers used for qRT-PCR are presented in Supplemental Table S1. Small RNA gel blot assay Small RNA gel blot analysis was performed as described in Liu et al.74. Briefly, total RNA was extracted from rice seedlings, and total RNA samples (approximately 20 μg) were separated on denaturing 15% polyacrylamide gels and transferred electrophoretically to Hybond-N+ membranes (http://www.gelifesciences.com/). The gel was stained with ethidium bromide before transfer to confirm equal loading. Hybridizations were performed at 42 °C in PerfectHyb Plus buffer with DNA oligonucleotide probes labelled by T4 polynucleotide kinase (New England Biolabs, https://www.neb.com/). Hybridization signals were detected with a phosphorimager (GE Healthcare Life Sciences, http://www.gelifesciences.com). The sequences of the probes are provided in Supplemental Table S1. Tissue sectioning and in situ hybridization Seedlings of ZH11 plants were grown with different N fertilizer levels, and OX393-6 was grown with normal levels of N fertilizer for 15 d, after which SAM tissues and axillary buds were fixed and sectioned at a thickness of 7 mm. The sections were then stained with toluidine blue for light microscopic analysis (Zeiss, Germany). In situ hybridization was performed as described75. The OsmiR393 probe was synthesized and labelled with digoxigenin. Shoots containing SAM and axillary meristems were used for hybridization assays. Slides were photographed under a microscope (Zeiss, Germany). CRISPR-mediated mutation of OsMIR393 An sgRNA: AAGGATCAATGCGATCCCTTTGG was designed to target OsmiR393. The sgRNA was inserted into the AarI site of the p2300-rCas9-U3-gRNA vector, which contains a rice-codon optimized Cas9 driven by a 2× 35S promoter42, and the sgRNA was activated by an OsU3 promoter. The primer used for cloning is shown in Supplemental Table S1 (CRISPR-F and CRISPR-R). After introducing the CRISPR/Cas plasmid into rice varietal ZH11 through Agrobacterium-mediated transformation72, the T0 generation mutants were screened with G418 (Invitrogen). All regenerated T0 transgenic plants were genotyped using the primer (CRISPR-g-F and CRISPR-g-R) to select positive transgenic lines, and a small RNA gel blot analysis was performed to subsequently detect OsmiR393 expression and confirm the knock-out of OsmiR393 in mutated lines. Co–IP and mass spectrum analysis To validate the protein interaction profile of OsTIR1 in vivo, a Co-IP assay was employed using an immunoprecipitation kit (Sigma-Aldrich, China). The cDNA for OsTIR1 was amplified using the primers cMYC-TIR1-F and cMYC-TIR1-R. Amplified cDNA was inserted into pRT107–6XMyc between the BamHI and KpnI sites to generate the expression vector 2×35S:6XMyc-OsTIR1. The co–immunoprecipitation procedure was performed in accordance with the manufacturer’s instructions using an anti-c-Myc antibody (Sigma-Aldrich, China). Mass spectrum analysis was performed by the Boxin biotechnology company in Guangzhou. Primers used are listed in Supplemental Table S1. Protoplast isolation and western blot analysis To generate the cMYC-OsIAA6 sequence, the OsIAA6 coding sequence was amplified with the gene specific primers, cMYC-OsIAA6-F and cMYC-OsIAA6-R containing the restriction enzyme sites BamHI and NotI, and ligated into a rice transformation vector for constitutive expression. Constructs were introduced into rice protoplasts of 2-week seedlings as previously reported76. The generated constructs were then transfected into the isolated protoplasts using polyethyleneglycol-mediated transformation76. To examine OsIAA6 protein expression, a western blot was performed as described in Niu et al.77. Tiller bud and callus induction with NAA treatments Five-leaf seedlings were sprayed with 5 mg/L of NAA, and the length of tiller buds was measured as indicated. Callus induction with 2 mg/L of NAA was performed as previously described39. Tiller count and data analysis Rice plants were planted in previously described conditions and grown for approximately 30 days before the headings and tillers were counted; all data were analysed in Excel using a t–test. Sequence data from this study can be found in the GenBank/EMBL data libraries under accession numbers OsAFB2 (LOC_Os04g32460), OsTIR1 (LOC_Os05g05800), OsIAA6 (LOC_Os01g53880), and ACTIN1 (LOC_Os03g50885). Additional Information How to cite this article: Li, X. et al. MicroRNA393 is involved in nitrogen-promoted rice tillering through regulation of auxin signal transduction in axillary buds. Sci. Rep. 6, 32158; doi: 10.1038/srep32158 (2016). Supplementary Material Supplementary Information This work was supported by Guangdong Science and Technology Department of China (grant nos. 2015B020231009 and 2014A020208081), Guangdong Agriculture Department of China (grant no. 2014492), and the National Natural Science Foundation of China (grant no. 31371604/31272240). We thank Xiexiu Zhang of the South China Botanical Garden (SCBG) for technical support. We also thank Dr. Hao Chen, Ze Yun and Dr. Xun Zeng of SCBG for comments on the manuscripts. Author Contributions X.L. and K.X. performed most of the experiments; Z.L., K.C. and C.G. provided CRISPR technical assistance to X.L. X.L. and M.Z. designed the experiments and analyzed the data; X.L. and M.Z. conceived the project and wrote the article with contributions of all the authors. Figure 1 Nitrogen fertilizer triggers OsmiR393 accumulation and overexpression resulting in an increased number of tillers. (A and D), qRT-PCR (A) and small RNA gel blot (D) analysis of OsmiR393 expression level in ZH11 with elevating NH4NO3 levels (A) and in OsmiR393-overexpressing rice lines (OX393) under normal nitrogen (N) levels (1 N) (D). The level of NH4NO3 (1.43 mM) in the IRRI nutrient solution38 was set as the normal (1 N) level of N fertilizer; other N levels represent multiples of the 1 N level. Vertical bars in (A) indicate standard error from three individual repeats. Rice U6 was used as an internal control. The asterisk in (A) indicates a mean fold change of greater than 2 vs the 0 N condition. (B,C) and (E,F), Tiller numbers of ZH11 with elevating NH4NO3 levels (B,C) and in OsmiR393-overexpressing rice plants with a normal N concentration (1 N) (E,F) respectively, when plants were grown in a pot. Scale bar = 2 cm in (B) and (E). Tiller numbers in (C) and (F) were counted and analysed in excel. Vertical bars in (C) and (F) indicate standard error (n ≥ 15 plants for every sample and each experiment was repeated three times). The asterisk indicates significant differences (*P ≤ 0.05 and **P ≤ 0.01) compared to ZH11 at 0 N (C), and at 1 N (F) as determined by a t-test. Figure 2 OsMIR393 mutants develop fewer tillers (A–C) under 1 N condition and external application (4N) of NH4NO3 does not restore tillers in OsMIR393 mutants (D–F). (A and D), Small RNA gel blot analysis of OsmiR393 expression in OsMIR393 mutants under normal nitrogen (N) levels (1 N) (A) and with 4 N levels of N fertilizer (D). (B and C) Tiller numbers for the OsMIR393 mutant grown in a controlled field and supplied with 1 N fertilizer (NH4NO3). (E and F) Tiller numbers of OsMIR393 mutants grown in a controlled field and supplied with 4 N fertilizer (NH4NO3). Vertical bars in (C) and (F) indicate standard error (n ≥ 15 plants for every sample and each experiment was repeated three times). The asterisk indicates significant differences (*P ≤ 0.05 and **P ≤ 0.01) compared to the ZH11 control, as assessed by a t-test. Scale bar = 3 cm in (B) and (E). Figure 3 Inverse expression of OsmiR393 and its target genes (OsAFB2 and OsTIR1) with elevating nitrogen (N) levels. (A) qRT-PCR verification of OsmiR393 targets in OsmiR393 overexpressing line (OX393-6), and OsMIR393 mutant (CRP-9) with 1 N fertilizer. (B) qRT–PCR expression analysis of putative OsmiR393 target genes in wild type rice ZH11 with elevating N levels. Results are presented as the means of three experiments. Vertical bars indicate standard error. The asterisk mark indicates a mean fold change greater than 2 or less than 0.5 between ZH11 and the mutants (A), or the elevating N treated ZH11 (B). Figure 4 OsmiR393 affects axillary bud outgrowth and is expressed at a high level in the lateral axillary meristem. (A–D) Tissue section of wild type ZH11 rice grown with different nitrogen (N) levels using an NH4NO3 fertilizer. (E) Tissue section of OsmiR393-overexpressing line (OX393-6) under normal N levels (1 N) using NH4NO3 fertilizer. Red arrows in (A–E) indicate the formed axillary meristem. Pictures are representative of sections from 20 plants. (F) In situ hybridization of OsmiR393 in the ZH11 stem base with 1 N NH4NO3 fertilizer. The red arrow in (F) indicates intense OsmiR393 expression. Bar = 100 μm in (A–F). (G) qRT–PCR detection of OsmiR393 levels in different organs of ZH11 under normal N levels (1 N) using NH4NO3 fertilizer. Vertical bars indicate standard error from three repeats. 1L, the first leaf; 2L, the second leaf; 3L, the third leaf; FL, flag leaf; R, root; C, culm; BP, booting panicle; SS, shoot sheath. Figure 5 OsIAA6 protein level in ZH11 plants with different nitrogen (N) levels and in different transgenic rice with 1 N levels. (A–C) Western blot analysis of OsIAA6 in the protoplast of OsmiR393-overexpressing lines (OX393) (A) N-treated ZH11 (B) and OsMIR393 mutants (CRP) (C). Protoplasts were prepared from 2-week old seedlings. HSC70 was used as a loading control. ==== Refs Xing Y. & Zhang Q. Genetic and molecular bases of rice yield . Annu. Rev. Plant Biol. 61 , 421 –442 , 10.1146/annurev–arplant–042809–112209 (2010 ).20192739 Liang W. H. , Shang F. , Lin Q. T. , Lou C. & Zhang J. Tillering and panicle branching genes in rice . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3218010.1038/srep32180ArticleHigh Mobility Group Box Protein 1 Boosts Endothelial Albumin Transcytosis through the RAGE/Src/Caveolin-1 Pathway Shang Dan 1Peng Tao 2Gou Shanmiao 2Li Yiqing 1Wu Heshui 2Wang Chunyou 2Yang Zhiyong a21 Department of Vascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, Wuhan, Hubei Province 430022, China2 Department of Pancreatic surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, Wuhan, Hubei Province 430022, Chinaa zhiyongyang@hust.edu.cn30 08 2016 2016 6 3218028 01 2016 03 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/High-mobility group box protein 1 (HMGB1), an inflammatory mediator, has been reported to destroy cell-cell junctions, resulting in vascular endothelial hyperpermeability. Here, we report that HMGB1 increases the endothelial transcytosis of albumin. In mouse lung vascular endothelial cells (MLVECs), HMGB1 at a concentration of 500 ng/ml or less did not harm cell-cell junctions but rapidly induced endothelial hyperpermeability to 125I-albumin. HMGB1 induced an increase in 125I-albumin and AlexaFluor 488-labeled albumin internalization in endocytosis assays. Depletion of receptor for advanced glycation end products (RAGE), but not TLR2 or TLR4, suppressed HMGB1-induced albumin transcytosis and endocytosis. Genetic and pharmacological destruction of lipid rafts significantly inhibited HMGB1-induced albumin endocytosis and transcytosis. HMGB1 induced the rapid phosphorylation of caveolin (Cav)-1 and Src. Either RAGE gene silencing or soluble RAGE suppressed Cav-1 Tyr14 phosphorylation and Src Tyr418 phosphorylation. The Src inhibitor 4-amino-5-(4-chlorophenyl)-7-(t-butyl) pyrazolo[3,4-d] pyrimidine (PP2) blocked HMGB1-induced Cav-1 Tyr14 phosphorylation. PP2 and overexpression of Cav-1 with a T14F mutation significantly inhibited HMGB1-induced transcytosis and albumin endocytosis. Our findings suggest that HMGB1 induces the transcytosis of albumin via RAGE-dependent Src phosphorylation and Cav-1 phosphorylation. These studies revealed a new mechanism of HMGB1-induced endothelial hyperpermeability. ==== Body High mobility group box 1 (HMGB1), a member of the high mobility group (HMG) protein family named after its fast migration property in PAGE, is a non-histone chromosomal protein that is widespread in eukaryotic cells1. Structurally, HMGB1 is composed of a 215 amino acid single-chain polypeptide and has a molecular weight of approximately 25 kDa. It is highly conserved and contains an N-terminus with a basic (positively charged) lysine residue and an acidic (negatively charged) C-terminus with a high amount of aspartic and glutamic acid residues1. HMGB1 has been formerly known for its intracellular functions in contributing to the stabilization of the nucleosome and bent DNA formation as well as repair2. Recent studies have shown that HMGB1 is also involved in the control of mitochondrial quality and the regulation of cell autophagy34. HMGB1 can either be passively released from necrotic cells or secreted actively by a variety of cells into the extracellular environment. Extracellular HMGB1 acts as a pro-inflammatory cytokine in the inflammatory response and attracts stem cells to home into areas of inflammation, promoting the regeneration process5. In addition, it is considered to be associated with the growth and proliferation of multiple types of tumours6. In the past, for the first time, it was found that HMGB1 was released into the extracellular environment as an important late pro-inflammatory cytokine during sepsis7. Since then, a large number of studies have shown that HMGB1 is involved in the progression of burns, severe acute pancreatitis, haemorrhagic shock, disseminated intravascular coagulation, rheumatoid arthritis, systemic lupus erythaematosus, and other diseases58. Early studies have demonstrated that HMGB1 exhibits typical pro-inflammatory cytokine activity and activates inflammatory cells (e.g., monocytes or macrophages, neutrophils, vascular endothelial cells) to release cytokines and chemokines (e.g., tumour necrosis factors and interleukins)58910. The main receptors of HMGB1 include receptor for advanced glycation end products (RAGE), TLR4 and TLR25. A severe systemic inflammatory response can cause endothelial injury and high capillary permeability, in turn resulting in severe capillary leakage during the initial stages of extensive burns, severe acute pancreatitis, and severe sepsis1112. High capillary permeability is associated with water, electrolyte, and albumin leakage into the tissue interspace. Albumin leakage occurs through two pathways, i.e., the paracellular pathway and transcytosis13. Albumin leakage via the paracellular pathway is a result of damage to cell-cell junctions13, whereas albumin transcytosis results from endocytosis after binding with the receptor gp60 and subsequent basolateral excretion14. Albumin endocytosis occurs via the caveolin (Cav)-1-dependent endocytic pathway14. In the absence of Cav-1, vascular endothelial cells can transfer albumin through the clathrin-dependent endocytic pathway15. It has been reported that high concentrations of HMGB1 (≥5 μg/mL), resulting in vascular barrier damage, quickly destroy the junctions between pulmonary vascular endothelial cells16, whereas lower concentrations of HMGB1 (200 ng/mL) for less than 12 h caused no destruction of the cell-cell junctions1617. Several studies showed that although the HMGB1 level was elevated in patients with severe acute pancreatitis or sepsis, it remained far less than 200 ng/mL181920. It was observed that exposure to lower concentrations (<200 ng/ml) of HMGB1 for a shorter time period could not affect the integrity of endothelial cell-cell junctions. However, the effect of HMGB1 on albumin transcytosis remains unclear. In vascular endothelial cells, Cav-1 phosphorylation by Src (the signalling protein associated with Cav-1) can lead to the increased transcellular transport of albumin21. In addition, after binding with its ligand, RAGE activates Src and downstream signals22. We speculated that HMGB1 induces endothelial albumin transcytosis through Src activation. In the present study, the results showed that a lower concentration (100 ng/ml) of HMGB1 did not damage the integrity of the junctions between mouse lung vascular endothelial cells (MLVECs) but boosted albumin transcytosis via RAGE-dependent Src and Cav-1 phosphorylation, resulting in vascular endothelial hyperpermeability to albumin. Results HMGB1 induced pulmonary vascular endothelial hyperpermeability to albumin We examined the effects of HMGB1 on the permeability of the pulmonary vascular endothelium using a Transwell chamber assay. After a 1-h treatment of MLVEC monolayers with 0, 50, 100, and 500 ng/mL HMGB1 and 125I-albumin, the radioactivity of the liquid in the lower chamber was tested. We found that the permeability of MLVEC monolayers to 125I-albumin increased with increasing concentrations of HMGB1 (Fig. 1A). To verify the role of HMGB1 at the organ level, we performed the experiment with mouse lungs that were treated via pulmonary vascular perfusion with HMGB1 (100 ng/mL) and 125I-albumin for 30 min. We found that the lung W/D weight ratio (Fig. 1B) and the extravascular 125I-albumin level (Fig. 1C) were significantly higher in the HMGB1 group than in the control group. These results suggested that lower concentrations of HMGB1 resulted in the hyperpermeability of the pulmonary vascular endothelium to albumin as well as pulmonary oedema. Lower concentrations of HMGB1 did not damage the endothelial barrier Albumin leakage can occur through the paracellular pathway or through transcytosis13. Studies have shown that HMGB1 stimulation destroys the integrity of endothelial cell junctions either at high concentrations or when exposed to cells for a longer period of time1617. The integrity of the cell-cell junctions was measured to further clarify the mechanism through which lower concentrations of HMGB1 affect the albumin hyperpermeability of the vascular endothelium. MLVEC monolayers were treated using 0, 50, 100 and 500 ng/mL HMGB1, with thrombin and 15 μg/mL HMGB1 as positive controls. The resulting changes in TER were evaluated, and the results showed that the TER in MLVEC monolayers rapidly decreased after thrombin administration but remained unchanged after HMGB1 stimulation (Fig. 2A). Indirect immunofluorescence staining of VE-Cadherin was used to confirm the changes in cell-cell junctions, and 15 μg/mL HMGB1 and Thrombin was used as a positive control. Addition of 0–500 ng/mL HMGB1 caused no increase in the intercellular gaps between MLVECs (Fig. 2B). Collectively, these results indicated that 0–500 ng/mL HMGB1 caused no rapid destruction of the cell-to-cell junctions of MLVECs. HMGB1 increased the endothelial transcytosis of albumin Albumin endocytosis was assayed to evaluate whether HMGB1 results in increased transcytosis of albumin by vascular endothelial cells. Endothelial cells were stimulated with HMGB1 (0, 50, 100, and 500 ng/mL) and 125I-albumin. 125I-albumin endocytosis by MLVEC monolayers increased with increasing concentrations of HMGB1 (Fig. 3A). AlexaFluor 488-labeled albumin was also used in the endocytosis assay. Under a confocal microscope, green fluorescence in MLVECs increased with the increase of HMGB1 concentration (Fig. 3B). Combined with the results of the Transwell-based 125I-albumin permeability assay (Fig. 1A), these data suggested that increasing concentrations of HMGB1 caused albumin hyperpermeability by inducing the transcytosis of albumin in vascular endothelial cells. HMGB1-induced endothelial transcytosis of albumin was dependent on RAGE but not on TLR2/4 At the surface of vascular endothelial cells, the three main receptors of HMGB1 are RAGE, TLR2, and TLR45. After silencing of these three genes (Fig. 4A), we observed that only RAGE depletion blocked HMGB1-induced endocytosis and albumin transcytosis (Fig. 4B,C). To verify the role of RAGE on HMGB1-induced albumin transcytosis at the organ level, we evaluated the lungs of RAGE−/− and RAGE+/+ mice after pulmonary vascular perfusion with HMGB1 and 125I-albumin for 30 min. We found that the extravascular 125I-albumin level (Fig. 4D) and the W/D weight ratio (Fig. 4E) was lower in RAGE−/− lungs. Thus, it can be concluded that HMGB1-induced albumin transcytosis was dependent on RAGE but not on TLR2/4. HMGB1 induced Cav-1-dependent endothelial transcytosis of albumin Endocytosis and transcytosis of albumin in vascular endothelial cells are thought to be Cav-1-dependent14, although studies have shown that in the absence of Cav-1, transport of albumin in the vascular endothelial cells takes place via the clathrin-dependent endocytic pathway15. To further clarify whether the albumin endocytic pathway affected by HMGB1 is dependent on Cav-1 or clathrin, we used methyl-β-cyclodextrin (MβCD) and clathrin depletion to block the Cav-1-dependent and clathrin-dependent endocytic pathways, respectively23. It was found that MβCD, rather than clathrin siRNA, blocked HMGB1-induced endocytosis and albumin transcytosis (Fig. 5A–D). As described above, HMGB1 mediated the albumin hyperpermeability of endothelial cells via its receptor RAGE (Fig. 4A–E). We thus studied the positional relationship of RAGE and Cav-1 in the cell membrane. The results of co-immunoprecipitation and immunofluorescence staining showed that Cav-1 bound with RAGE on the membrane of MLVECs, and HMGB1 stimulation seemed not to alter their colocalization (Fig. 5E,F). Furthermore, we silenced the expression of Cav-1 in MLVECs and found that HMGB1-induced endocytosis and transcytosis of albumin was blocked (Fig. 5G,H). These data showed that HMGB1 induced the Cav-1-dependent endothelial transcytosis of albumin. HMGB1 induced the endothelial transcytosis of albumin via Cav-1 phosphorylation Induction of Cav-1 expression24 or phosphorylation21 can increase the transendothelial transport of albumin. A western blot assay showed that HMGB1 did not affect the Cav-1 expression level in MLVECs (Fig. 6A). Cav-1 tyrosine phosphorylation (Y14) initiates the endocytosis and transcytosis of albumin14. The next experiment was based on the effects of HMGB1 on Cav-1 phosphorylation. HMGB1 was found to induce Cav-1 Y14 phosphorylation in MLVECs in a dose-dependent manner (Fig. 6B,C). Furthermore, overexpression of a Cav-1 Y14 phosphorylation-defective mutant (Cav-1 Y14F) in MLVECs (Fig. 6D) resulted in significantly reduced endocytosis and transcytosis of albumin compared to the wild-type group (Fig. 6E,F). These results indicated that Y14 phosphorylation of Cav-1 mediated the HMGB1-induced endothelial transcytosis of albumin. Src phosphorylation mediated the HMGB1-induced Cav-1 phosphorylation and endothelial transcytosis of albumin Cav-1 Y14 phosphorylation is catalysed by both Src, the major catalysing enzyme14 and c-Abl2125. We measured the phosphorylation-mediated activation of Src in MLVECs after HMGB1 stimulation and found that Src was activated rapidly via phosphorylation in a dose-dependent manner by exposure to HMGB1 (Fig. 7A,B). However, the use of an inhibitor of Src activation, 4-amino-5-(4-chlorophenyl)-7-(t-butyl) pyrazolo[3,4-d] pyrimidine (PP2), blocked HMGB1-induced Cav-1 phosphorylation (Fig. 7D) and the transcytosis of albumin (Fig. 7E,F). In addition, after exposure to HMGB1, the activation of c-Abl via phosphorylation was not observed in MLVECs (Fig. 7C). Hence, HMGB1-induced Cav-1 phosphorylation and albumin transcytosis were dependent on Src phosphorylation. RAGE mediated HMGB1-induced Src phosphorylation and Cav-1 phosphorylation We next sought to further confirm the role of RAGE in HMGB1-induced Src phosphorylation and Cav-1 phosphorylation was studied. The results were consistent with the previous findings and confirmed that RAGE gene silencing (Fig. 8A,C) or sRAGE (Fig. 8B,D) blocked HMGB1-induced Src Y418 phosphorylation and Cav-1 Y14 phosphorylation. All-thiol HMGB1, but not disulfide HMGB1, induced the endothelial transcytosis of albumin The redox state of HMGB1 modulates its extracellular functions26. All-thiol HMGB1 uses RAGE signalling, while disulfide HMGB1 recognizes TLR4. We found that all-thiol HMGB1, but not disulfide HMGB1, induced the endocytosis and transcytosis of albumin (Fig. 9A,B). Discussion Our study is the first report on vascular endothelial hyperpermeability induced by pathophysiological concentrations of HMGB1. The results showed that 100 ng/mL of HMGB1 increased albumin transcytosis. Huang et al.17 found that there were no effects of HMGB1 (100 ng/mL) on the permeability of HUVEC monolayers because they did not study the effects of HMGB1 on the transcellular pathway. Similarly, Wolfson et al.16 only focused on the effects of HMGB1 on cell-cell junctions. In our study, TER and VE-Cadherin staining results showed that 100 ng/mL HMGB1 did not destroy the cell-cell junctions of MLVECs but still induced 125I-albumin hyperpermeability. As was confirmed in the endocytosis assays of 125I- and AlexaFluor 488-labeled albumins, this endothelial hyperpermeability was achieved by increasing the endocytosis and transcellular transport of albumin. The three receptors of HMGB1 are RAGE, TLR4, and TLR2, among which RAGE seems to be altered when HMGB1 performs different functions in various cells. Animal experiments have shown that knockout of RAGE had a protective effect on mice with sepsis induced by caecal ligation puncture, and this protective effect was eliminated by exogenous RAGE expression in the endothelial cells and bone marrow cells of RAGE knockout mice22. This result suggested that RAGE is involved in the progression of sepsis in mice. RAGE knockout is more effective in reducing the HMGB1-induced release of pro-inflammatory cytokines than TLR2 knockout in bone marrow–derived macrophages, suggesting that RAGE is the main receptor of HMGB1 recognized by macrophages22. RAGE seems to be more important for the function of HMGB1 in vascular endothelial cells. Activation of HUVECs by HMGB1 can be inhibited by more than 50% with RAGE-neutralizing antibodies9. Huang et al.17 and Wolfson et al.16 showed that the damage caused by HMGB1 to cell-cell junctions was dependent on RAGE but was independent of TLR4 and TLR2. The present study showed that the HMGB1-induced transcytosis of albumin was dependent on RAGE but not TLR4 and TLR2. These data are consistent with reports that RAGE KO protected mice from acute lung injury27. Albumin can be endocytosed through the clathrin-dependent and Cav-1-dependent pathways15. After MβCD or siRNA were used to destruct lipid rafts and to silence Cav-1 expression, respectively, we found that HMGB1-induced albumin endocytosis and transcytosis were significantly inhibited; however, clathrin knockdown did not block HMGB1-induced albumin endocytosis or transcytosis. These results indicated that HMGB1 increased vascular endothelial permeability to albumin by upregulating the Cav-1-dependent transcytosis of albumin. Upregulated Cav-1 expression allows increased endocytosis and transcytosis of albumin24. Our data showed that HMGB1 did not increase the expression level, but raised the phosphorylation level, of Cav-1 in endothelial cells. Phosphorylation of Cav-1 Tyr14 is considered to be a key step to initiate the endocytosis of albumin. A study has shown that hydrogen peroxide increased the transcytosis of albumin by inducing Cav-1 Tyr14 phosphorylation21. In the present study, HMGB1-induced Cav-1 Tyr14 phosphorylation was mediated by RAGE, as either RAGE gene silencing or sRAGE blocked Cav-1 Tyr14 phosphorylation. Overexpression of Cav-1 with a Tyr14 phosphorylation-defective mutant significantly inhibited the HMGB1-induced transcytosis and endocytosis of albumin, strongly suggesting that HMGB1 increases endothelial permeability by regulating Cav-1 Tyr14 phosphorylation. It has been reported that Cav-1 Tyr14 phosphorylation is regulated by Src and c-Abl2125. We found that HMGB1 induced Src phosphorylation, but c-Abl was not activated by phosphorylation. Redox modulates the extracellular functions of HMGB126. All-thiol HMGB1 used RAGE signalling, while disulfide HMGB1 recognized TLR4. We found that all-thiol HMGB1, but not disulfide HMGB1, induced the endocytosis and transcytosis of albumin. This is consistent with our findings that RAGE mediates HMGB1-induced albumin transcytosis. HMGB1 requires additional factors to exert its inflammatory activity, including LPS, IL-1, and nucleosomes28. In a real pathophysiological environment, HMGB1 co-exists with these inflammatory mediators. In the presence of these mediators, the effect of HMGB1 on vascular permeability may have additional features that need to be studied. Materials and Methods Materials Recombinant HMGB1 was purchased from R&D Systems (Minneapolis, MN). All-thiol HMGB1 and disulfide HMGB1 were obtained from HMGBiotech. Protein A+G Agarose beads, HRP-conjugated secondary Abs, and anti-GAPDH, TLR4 and TLR2 Abs were from Santa Cruz Biotechnology. Anti-Cav-1, p(Y14)Cav-1, p(Y418)Src, RAGE, c-Abl, and phospho-tyrosine Abs, normal rabbit IgG and normal mouse IgG were from Cell Signalling Technology. TLR2, TLR4, RAGE, clathrin and Cav-1 siRNA, sc siRNA and Dharmafector 1 transfection reagent were obtained from Thermo Scientific. AlexaFluor 488-conjugated albumin was from Molecular Probes. TLR2- and TLR4-neutralizing Abs were from Abcam. Recombinant soluble RAGE (sRAGE) was from Biotrend. 125I-albumin was purchased from PerkinElmer, Inc. Amaxa basic nucleofector kits for primary endothelial cells were obtained from Lonza. RIPA buffer and ECL reagents were from Pierce Biotechnology. Bicinchoninic acid kits and sample buffer were from Bio-Rad. AlexaFluor 568- and AlexaFluor 488-conjugated secondary Abs were from Invitrogen. MEM D-Val medium and FBS were from Gibco. Biotin-conjugated rat anti-mouse CD31 (PECAM-1) monoclonal antibody and BD IMag Streptavidin Particles Plus-DM were from BD Pharmingen. All other reagents were obtained from Sigma unless otherwise specified. Animals C57BL/6 mice weighing 25–30 g were obtained from the Experimental Animal Centre of Tongji Medical College, Huazhong University of Science and Technology (Wuhan, China). RAGE KO mice were generated on a C57BL/6 background29. The mice were housed under specific pathogen-free conditions, fed with autoclaved food, and used in experiments at 8–12 wks of age. Animal protocols received the approval of the Institutional Animal Care and Use Committee of Huazhong University of Science and Technology. The methods were carried out in accordance with the approved guidelines. Isolation and identification of MLVECs MLVECs were isolated according to the literature with slight modifications23. Mice were anesthetized, and then 50 units of heparin were injected via the jugular vein. An incision was made into the chest to insert a pulmonary artery catheter, and blood in the vasa publica was removed by perfusion with PBS. The edge of the lung tissues was excised and cut into 1-mm3 small pieces, which were placed in 60-mm petri dishes containing culture medium (MEM D-Val medium containing 2 mM glutamine, 10% FBS, 5% human serum, 50 μg/ml penicillin/streptomycin, 5 μg/ml heparin, 1 μg/ml hydrocortisone, 80 μg/ml endothelial cell growth supplement from bovine brain, 5 μg/ml amphotericin, and 5 μg/ml mycoplasma removal agent). After 60 h of incubation at 37 °C in 5% CO2, tissue blocks were removed, and adherent cells were continuously cultured for another 3 d. Endothelial cells were then purified using biotin-conjugated rat anti-mouse CD31 (PECAM-1) monoclonal antibody, BD IMag Streptavidin Particles Plus-DM, and an immunomagnetic separation system (BD Biosciences Pharmingen, San Diego, CA). The purified 3D cell culture was identified by cell morphology, Dil-Ac-LDL uptake and factor VIII staining before passaging. Generations 3–5 of the identified cells were used for experiments. Immunoblotting and immunoprecipitation Cells were lysed in RIPA buffer supplemented with 1 mMol PMSF, 1 mMol Na4VO3 and protease inhibitor cocktail. The lysates were sonicated and centrifuged at 10,000 g for 10 min at 4 °C. The protein concentrations were measured with bicinchoninic acid kits. The samples were loaded equally for PAGE and then transferred onto nitrocellulose membranes. After blocking with 5% non-fat milk in TBST, the membranes were probed with primary antibodies for 2 h at room temperature or overnight at 4 °C and then incubated with HRP-conjugated secondary antibodies at room temperature for 1 h. The bands were determined using ECL reagent and quantified using ImageJ software (NIH). For immunoprecipitation, the cell lysates were pre-cleared with 1 μg of normal IgG and 20 μl Protein A+G Agarose beads for 2 h at 4 °C. After centrifugation at 1000 g for 5 min, the supernatants were transferred to new tubes and incubated with 40 μl of Protein A+G Agarose beads and anti-Cav-1 or anti-RAGE antibodies overnight at 4 °C. The beads were collected for immunoblotting after 3 washes with PBS. Immunofluorescence Cells plated on coverslips were fixed with 2% paraformaldehyde for 15 min and then washed 3 times with 100 mM glycine in HBSS for 10 min and once with HBSS for 10 min. After permeabilization with 0.1% Triton X-100 in HBSS for 30 min, the cells were incubated with primary antibodies (diluted with HBSS containing 5% horse serum and 0.2% BSA at a 1:200 dilution) overnight at 4 °C. Three washes with HBSS were followed by incubation with fluorescence-conjugated secondary Abs (1:200) for 1 h. After another 3 washes with HBSS, the cells were mounted on glass slides using Prolong Gold antifade reagents (Molecular Probes). Images were acquired with a confocal microscope (Zeiss LSM 510 Meta). Knockdown A total of 5 × 105 MLVECs were plated in 6-well plates and cultured overnight. A pool of three target-specific 20–25 nt siRNAs was used to knock down TLR2, TLR4, RAGE, clathrin or Cav-1 at a concentration of 25–50 nmol/l according to the protocol of Dharmacon. Forty-eight hours after transfection, the depletion of the target protein was confirmed by immunoblotting, and the cells were used in subsequent experiments. Electrotransfection Transient transfection of MLVECs was performed according to the manufacturer’s instructions (Lonza). Briefly, 5 × 105 MLVECs were resuspended in 100 μl of nucleofector solution mixed with 2 μg cDNA. Nucleofection was performed using programme M-003. Then, the cells were rapidly transferred to pre-equilibrated culture medium and incubated for 24–96 h at 37 °C. The viability of the cells was measured by vital dye exclusion. Successful transfection was confirmed by immunoblotting. Endocytosis assay with 125I-albumin Endocytosis of 125I-albumin was assayed based on protocols from the literature1430. Six-well plates were used to culture MLVECs until the cells formed confluent monolayers. HBSS containing unlabelled albumin was added at final concentrations of 0.1 mg/mL (in four wells) and 100 mg/mL (in two wells). Then, 125I-albumin (1 × 106 cpm) was added to each well, and the plates were incubated for 30 min at 37 °C. The cells were washed successively with ice-cold acetate buffer (0.5 M NaCl and 0.2 M acetate, pH 2.5) and HBSS thrice to remove cell surface-bound 125I-albumin. The cells were lysed with 1 mL of Tris-HCl buffer (0.05 M Tris-HCl, 1% Triton X-100 and 0.5% SDS, pH 7.4), and the radioactivity of the cell lysates was detected using a γ counter (PerkinElmer, Inc.). The intake of specific 125I-albumin was calculated as total radioactivity (detection value of a sample containing 0.1 mg/mL unlabelled albumin) minus non-specific cell-related activity (detection value of a sample containing 100 mg/mL unlabelled albumin) and then corrected by the total cellular protein and expressed as cpm/mg cellular protein. Endocytosis assay of fluorescently labelled albumin MLVECs were grown on cover slips until the cells formed confluent monolayers. AlexaFluor 488-labeled BSA (50 μg/mL) and unlabelled albumin (500 μg/mL) were added to the cell culture, and the culture was then incubated at 37 °C for 30 min. The cells were washed thrice with HBSS and examined under a confocal microscope (Zeiss LSM 510 Meta) to quantify the amount of fluorescence-labelled albumin endocytosed1430. Transendothelial permeability assay with 125I-albumin MLVECs were grown on fibronectin-coated microporous polyester Transwell membranes (12 wells, 1 cm2 growth area, 0.4 μm pore size; Corning Costar, Cambridge, MA) until the cells formed confluent monolayers. The upper chamber was supplemented with 0.5 mL of HBSS containing 125I-albumin (1 × 106 cpm) and unlabelled albumin (0.1 or 100 mg/mL). The lower chamber was supplemented with 1.5 mL of HBSS containing the same amount of unlabelled albumin used for the upper chamber. The reaction time was 1 h, after which 200 μL of liquid sample was removed from the lower chamber and used for a radioactivity assay with a γ counter (PerkinElmer Inc.). The transendothelial permeability to 125I-albumin was calculated and expressed as μL/min.cm2 in accordance with the literature1430. Transepithelial electrical resistance (TER) detection TER detection was performed in accordance to the previous literature1431. MLVECs were grown in culture plates containing gold-plated microelectrodes until the cells formed confluent monolayers. The positive and negative poles were connected to a synchronous phase sensitive amplifier. Computerized recording of the data related to voltage changes in HMGB1-treated cells was performed, and the data were expressed as the relative value to the initial reading of zero. Detection of permeability-surface area product (PS) Mouse lungs were prepared as described previously32. In brief, mice were anesthetized, intubated, and ventilated. For pulmonary artery catheterization, the chests of the mice were surgically dissected, followed by perfusion with a modified Krebs-Henseleit solution at flow rate of 2 mL/min, a venous pressure of 3 cm H2O, and a pulmonary artery pressure of 8 ± 2 cm H2O. Albumin PS was determined as previously described14 with slight modification. In brief, lung artery lavage was performed with a fluid containing 80000 counts/mL 125I-albumin and 0 or 100 ng/mL HMGB1. After 30 min, the lungs were irrigated with Krebs solution (containing 5% unlabelled albumin) for 6 min to remove excess 125I-albumin on the cell surface and within the cycling. Then, the attached tissues were quickly removed from the lung. The sample was weighed and used for γ radioactivity measurement. The PS value was calculated with the formula A/(Cp · t), where A and Cp are concentrations of tracer albumin in the tissue (in counts/g) and in the perfusate (in counts/mL), respectively, and t is the perfusion time for tracer albumin (30 min). The PS product was expressed as μL/(min·g) dry lung. Determination of lung tissue wet-dry weight ratio (W/D) The wet lungs were weighed and then oven-dried at 60 °C for 72 h. The final weight was measured to calculate the W/D weight ratio. Statistical Analysis The data are expressed as the mean ± SEM. One-way ANOVA with post-tests for individual treatments and Student’s Newman-Keuls test for post hoc comparisons were used to determine differences. Differences were considered significant when p < 0.05. Additional Information How to cite this article: Shang, D. et al. High Mobility Group Box Protein 1 Boosts Endothelial Albumin Transcytosis through the RAGE/Src/Caveolin-1 Pathway. Sci. Rep. 6, 32180; doi: 10.1038/srep32180 (2016). The authors thank Dr. Guochang Hu (Department of Pharmacology, University of Illinois College of Medicine) for presenting Cav-1 Tyr14 phosphorylation-defective mutant and wild type plasmid. This work was supported by the National Natural Science Foundation of China (Grants No. 81171840 and No. 30972899). Author Contributions D.S. conducted most of the experiments, analyzed the results, and wrote most of the paper. T.P. performed TER and confocal microscope. S.G. and Y.L. isolated MLVECs. H.W. conducted experiments for detection of permeability-surface area product. C.W. provided technical assistance and contributed to the preparation of the figures. Z.Y. conceived the idea for the project and wrote the paper with D.S. All authors analyzed the results and approved the final version of the manuscript. Figure 1 HMGB1 induced pulmonary vascular endothelial hyperpermeability to albumin. (A) HMGB1 induced albumin hyperpermeability of MLVEC monolayers. 125I-albumin and different concentrations of HMGB1 (0, 50, 100, 500 ng/mL) were added into the upper chamber of a Transwell chamber containing MLVEC monolayers. After 1 h of incubation, 200 μL of liquid sample was removed from the lower chamber for radioactivity detection (n = 4 to 6 for each group). (B,C) HMGB1 induced mouse pulmonary vascular hyperpermeability to albumin (B) and pulmonary oedema (C). The mouse lung samples were irrigated with a solution containing 0 or 100 ng/mL HMGB1 and 125I-albumin via pulmonary artery perfusion. After 30 min, the lungs were perfused with Krebs solution, weighed and used for radioactivity detection (n = 6/each group). After oven-drying at 60 °C for 72 h, the final weight was measured to calculate the wet/dry (W/D) weight ratio. *Compared with the control group, p < 0.05. Figure 2 Low concentrations of HMGB1 do not affect the barrier function of endothelial cells. (A) Effect of HMGB1 on the TER in MLVEC monolayers. MLVEC monolayers were treated using 0, 50, 100, and 500 ng/mL HMGB1, with thrombin and 15 μg/mL HMGB1 as positive controls. Quantitative analysis of the data at 60 min after the treatment is shown on the right. (B) After MLVEC monolayers were treated with 0, 50, 100, 500 and 15000 ng/mL HMGB1 and Thrombin for 30 min, indirect immunofluorescence staining of VE-cadherin showed no continuous interruption of fluorescence or formation of intercellular gaps (yellow arrows) except in the positive control. For each group, n = 4 to 6. *Compared with the control group, p < 0.05. Figure 3 HMGB1 induced albumin endocytosis by vascular endothelial cells. (A) MLVEC monolayers were treated with HMGB1 and 125I-albumin. After 30 min, the cells were lysed for radioactivity detection. *Compared with the control group, p < 0.05. (B) MLVEC monolayers were treated with HMGB1 and AlexaFluor 488-labeled albumin. After 30 min, the cells were examined by confocal microscopy to quantify the amount of albumin endocytosed. For each group, n = 4 to 6. Figure 4 RAGE mediated the HMGB1-induced transcytosis of albumin. (A) RAGE, TLR2, and TLR4 expression was silenced successfully in MLVECs. The efficiency of gene silencing was tested by immunoblotting assay. (B,C) RAGE gene silencing decreased the HMGB1-induced endothelial transcytosis of albumin. After silencing the expression of the target gene, MLVECs were grown in 6-well plates (B) or in Transwell chambers (C). When the cells formed confluent monolayers, 0 or 100 ng/mL HMGB1 and 125I-albumin were added for assays of albumin endocytosis (B) and transendothelial permeability (C). (D,E) The RAGE+/+ and RAGE−/− mouse lung samples were irrigated with a solution containing 0 or 100 ng/mL HMGB1 and 125I-albumin via pulmonary artery perfusion. After 30 min, the lungs were perfused with Krebs solution, weighed and used for radioactivity detection (n = 6/each group). Then, the lungs were oven-dried. *Compared with the HMGB1-treated RAGE+/+ group, p < 0.05. Figure 5 HMGB1 induced the Cav-1-dependent endothelial transcytosis of albumin. (A,B) Effect of MβCD on the HMGB1-induced endocytosis and transcytosis of albumin. Prior to exposure to 100 ng/mL HMGB1, MLVECs were pretreated with 2 mM MβCD or DMSO for 30 min. (C,D) Effect of clathrin knockdown on the HMGB1-induced endocytosis and transcytosis of albumin. (E) Co-IP results showed the binding of Cav-1 and RAGE in MLVECs. MLVECs were cultured with or without 100 ng/mL HMGB1 for 1 h. (F) Co-localization of Cav-1 with RAGE on the cell membrane of MLVECs. MLVECs were cultured with or without 100 ng/mL HMGB1 for 1 h. Double staining of Cav-1 (red) and RAGE (green) in MLVECs was performed using indirect immunofluorescence. (G,H) Effect of Cav-1 knockdown on the HMGB1-induced endocytosis and transcytosis of albumin. After clathrin expression (C,D) or Cav-1 expression (G,H) was silenced, MLVECs were grown in Transwell chambers (C,G) or 6-well plates (D,H). When the cells formed confluent monolayers, 0 or 100 ng/mL HMGB1 and 125I-albumin were added for assays of albumin endocytosis (D,H) and transendothelial permeability (C,G). n = 4 to 6 for each group. *Compared with the non-HMGB1-treated control (A,B) or the sc siRNA group (C,D,G,H), p < 0.05. †Compared with the HMGB1-treated control (A,B) or the sc siRNA group (C,D,G,H), p < 0.05. Figure 6 Cav-1 Y14 phosphorylation mediated HMGB1-induced albumin hyperpermeability. (A) HMGB1 did not affect Cav-1 expression. (B) Effect of HMGB1 on Cav-1 Y14 phosphorylation. MLVEC monolayers were exposed to 100 ng/mL HMGB1. The cells were lysed at the indicated times for immunoblotting assays of Cav-1 (A) and p(Y14)Cav-1 expression (B). (C) MLVEC monolayers were exposed to different concentrations of HMGB1 for 15 min. The cells were lysed for immunoblotting to evaluate p(Y14)Cav-1 expression. (D) Cav-1 Y14F and wild-type Cav-1 were overexpressed in MLVECs. The expression efficiency was detected by immunoblotting assay. All blots are representative of 3 separate experiments. Overexpression of a Y14 phosphorylation-defective Cav-1 mutant significantly inhibited HMGB1-induced 125I-albumin endocytosis (E) and transcellular transport (F). The concentration of HMGB1 used in the experiment was 100 ng/mL. (E,F) n = 4 to 6 for each group. Figure 7 Src phosphorylation mediated HMGB1-induced Cav-1 phosphorylation and endothelial albumin transcytosis. (A,B) Effect of HMGB1 on Src Y418 phosphorylation. (C) Effect of HMGB1 on c-Abl phosphorylation. MLVEC monolayers were exposed to different concentrations of HMGB1 for 10 min and then lysed for immunoblotting assays of p(Y418)Src expression (A); MLVEC monolayers were exposed to 100 ng/mL HMGB1, and the cells were lysed at the indicated times for immunoblotting to evaluate p(Y418)Src expression (B); or anti-c-Abl specific antibody was used for immunoprecipitation, and anti-tyrosine phosphorylation antibody was then used for the detection of the protein phosphorylation level (C). (D) Effect of pp2 on HMGB1-induced Cav-1 Y14 phosphorylation. MLVEC monolayers were pretreated with 15 μM pp2 for 15 min and then treated with 100 ng/mL HMGB1 for 15 min. The cells were finally lysed for immunoblotting to evaluate p(Y14)Cav-1 expression. All blots are representative of 3 separate experiments. (E,F) pp2 inhibited HMGB1-induced 125I-albumin endocytosis and transcytosis. MLVEC monolayers were pretreated with 15 μM pp2 for 15 min and then treated with 100 ng/mL HMGB1 for 1 h (n = 4 to 6 for each group). Figure 8 RAGE mediated HMGB1-induced Src and Cav-1 phosphorylation. RAGE gene silencing inhibited HMGB1-induced Src Y418 (A) and Cav-1 Y14 (C) phosphorylation. RAGE expression in MLVECs was silenced using siRNA, and the cells were then stimulated with 100 ng/mL HMGB1. After 10 (A) or 15 min (C), the cells were lysed to extract the proteins. sRAGE inhibited HMGB1-induced Src Y418 (B) and Cav-1 Y14 (D) phosphorylation. MLVEC monolayers were pretreated with sRAGE for 15 min, and the cells were then treated with 100 ng/mL HMGB1. After 10 (B) or 15 min (D), the cells were lysed for protein extraction. The p(Y418)Src and p(Y14)Cav-1 levels were detected by immunoblotting assays. n = 3/each group. Figure 9 All-thiol HMGB1, but not disulfide HMGB1, enhanced the endocytosis and transcytosis of albumin. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3219310.1038/srep32193ArticleUncovering representations of sleep-associated hippocampal ensemble spike activity Chen Zhe a1Grosmark Andres D. 23Penagos Hector 4Wilson Matthew A. 41 Department of Psychiatry, Department of Neuroscience & Physiology, New York University School of Medicine, New York, NY 10016, USA2 The Neuroscience Institute, New York University School of Medicine, New York, NY 10016, USA3 Department of Neuroscience, Columbia University Medical Center, New York, NY 10019, USA4 Picower Institute of Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USAa zhe.chen3@nyumc.org30 08 2016 2016 6 3219304 02 2016 01 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Pyramidal neurons in the rodent hippocampus exhibit spatial tuning during spatial navigation, and they are reactivated in specific temporal order during sharp-wave ripples observed in quiet wakefulness or slow wave sleep. However, analyzing representations of sleep-associated hippocampal ensemble spike activity remains a great challenge. In contrast to wake, during sleep there is a complete absence of animal behavior, and the ensemble spike activity is sparse (low occurrence) and fragmental in time. To examine important issues encountered in sleep data analysis, we constructed synthetic sleep-like hippocampal spike data (short epochs, sparse and sporadic firing, compressed timescale) for detailed investigations. Based upon two Bayesian population-decoding methods (one receptive field-based, and the other not), we systematically investigated their representation power and detection reliability. Notably, the receptive-field-free decoding method was found to be well-tuned for hippocampal ensemble spike data in slow wave sleep (SWS), even in the absence of prior behavioral measure or ground truth. Our results showed that in addition to the sample length, bin size, and firing rate, number of active hippocampal pyramidal neurons are critical for reliable representation of the space as well as for detection of spatiotemporal reactivated patterns in SWS or quiet wakefulness. ==== Body Sleep is critical to hippocampus-dependent memory consolidation123. Analyzing hippocampal ensemble spike data during both slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep has been an important yet challenging research topic45678910. During awake active exploration, hippocampal pyramidal cells exhibit localized spatial tuning11. During sleep, in the absence of external sensory input or cues, the network is switched into a different state that engages in internally-driven computation. An important hallmark of sleep, the hippocampal sharp wave (SPW)-ripples, lasting between 50 to 400 milliseconds, is typically accompanied with an increased hippocampal network burst and population synchrony of pyramidal cells1. A central hypothesis is that the hippocampus and neocortex interact with each other during SPW-ripples12, and that hippocampal neurons fire such that the information transferred to the hippocampus during previous awake run behavior is reactivated at a fast timescale during SPW-ripple bursts, encoding information of spatial topology of familiar or novel environments, and goal-directed behavioral paths1013141516171819. During run behavior, hippocampal place cells fire in sequences that span a few seconds as animals run through location-dependent receptive fields. During sleep, the same place cells fire in an orderly manner at a faster timescale within SPW-ripple events. While some sequences have been shown to reflect temporally-compressed spatial sequences corresponding to previous experiences by the rat89101819, the spatial content of a large fraction of SPW-ripple events remains unknown. Therefore, uncovering the neural representation of hippocampal ensemble spike activity or spatiotemporal firing patterns during sleep becomes critical for improving our understanding of the mechanism of memory consolidation and, in general, information processing during sleep. To date, several statistical methods have been developed to analyze sleep-associated hippocampal ensemble spike activity, including pairwise correlation45, template matching15, sequence ranking8920, and Bayesian population decoding21222324. A few observations of sleep data analysis are noteworthy. First, the SPW-bursts during sleep are sparse (low occurrence) and individual events are statistically independent. Second, the magnitude of neuronal population synchrony, measured as the spiking fraction of all recorded neurons during each network burst, follows a lognormal distribution: strongly synchronized events are interspersed irregularly among many medium and small-sized events25. Third, different brain states or experiences may induce changes in firing rate and firing timescale152627. Fourth, there is no ground truth or behavioral measure. The pairwise correlation method ignores the spiking information at fine timescales and population synchrony; the template matching and sequence ranking is more sensitive to exact spike timing order and the number of active neurons. In contrast, Bayesian population decoding methods are more suited to tackle these issues in the presence of large neural ensembles16171823. However, to our knowledge, there is no precedent for a systematic investigation of these issues using any of these methods. In this work, we investigate these important statistical issues in greater detail by applying two neural population decoding methods to rat hippocampal ensemble spike data recorded in different states. One decoding method is based on topographic or receptive field representations2122, while the other is based on topological representation without a priori measure of place receptive fields282930. We first create “synthetic” sleep data by binning and resampling spike trains obtained during active locomotion to simulate important factors that characterize SPW-ripple events, and then compare the resulting decoded spatial representations to the animal’s actual run trajectory. This allows us to test two important questions of hippocampal population codes related to sleep and memory replay: representation power (“how reliably is the spatial environment represented?”) and detection power (“how can one detect significant spatial or behavioral state sequences?”). We use rat hippocampal ensemble recordings in two- and one-dimensional spaces to investigate these questions separately, and we further compare the performance of topographic vs. topological representation-based decoding methods to SPW-ripple associated spike data. Results Data We analyzed five datasets (Table 1) derived from experimental hippocampal ensemble spike data, recorded from multiple Long-Evans rats under different environments, behaviors and brain states. The animals’ behavioral trajectories from Datasets 1 to 4a are shown in Supplementary Fig. 1. To analyze rat hippocampal ensemble spike data, we considered two model-based Bayesian decoding methods based on different statistical assumptions (Methods, Supplementary Fig. 2). One decoding method is based on topographic or receptive field representations (termed DecodewRF—population decoding method using neuronal receptive fields, see Supplementary Fig. 3). The other is based on topological representation that aims to discover latent structures of sequential or spatiotemporal pattern of activity of cells without the assumption of behavioral measures (termed DecodewoRF—population decoding method without using neuronal receptive fields). The first method is supervised in that it requires training data for constructing place receptive fields in the encoding phase. The second method is purely unsupervised, which is developed based on an m-state hidden Markov model (HMM), with an inherent m × m state-transition matrix P. Sleep-associated hippocampal ensemble spike data are characterized by several important features: (1) shorter epochs (separated by periods of non- or low-spike activity); (2) small active cell ratio within each epoch; (3) different timescales from behavior. One fundamental assumption is that many sleep-associated hippocampal ensemble spikes preserve the order of temporal firing sequences experienced in behavior. In the following analyses, we first created “synthetic” sleep-like hippocampal ensemble spike data (derived from awake run behavior) and systematically investigated the issues of the length of data epochs, the number of participated neurons, temporal bin size and spike rate. The use of synthetic data allowed us to quantitatively assess the representation power (or decoding accuracy) in hippocampal ensemble representations. We then extended the analyses to experimental sleep data in complete absence of behavior measure and assessed the question of detection power. All reported statistics are shown in mean ± SEM. We used two established criteria for quantitative assessment: one is the decoding error with respect to the animal’s position, and the other is the weighted correlation1718 and the associated Z-score or equivalent Monte Carlo P-value of detected significant replay events (Methods). The first criterion, which assesses the representation power (i.e., how does the population spike activity reliably represents the environment, ref. 29), was tested on two-dimensional environments (Datasets 1 and 2, see an illustration in Supplementary Fig. 4). The second criterion assesses the detectability issue (Datasets 3, 4a and 4b, ref. 31). Impact of random splitting Unlike awake behavior, hippocampal neuronal populations fire in a sporadic manner during sleep, either within or outside the period of SPW-ripples. During awake run behavior, rat hippocampal ensemble spike data were binned with a temporal bin size of Δ = 250 ms into T discrete bins (i.e., TΔ corresponds to total recording time). We applied a speed filter of 15 cm s−1 to exclude immobile periods. As a first step to create sleep-like data structure (Supplementary Fig. 5A), we evenly split the run-associated ensemble spike into epochs. Each epoch was comprised of bins per epoch (bpe) and provided an independent measurement for further statistical analysis. Within each epoch, the temporal order of spiking sequences within cell assembly was preserved or reversed (with equal probability 0.5). The special case when and T0 = T bpe corresponds to the run-associated spike data; when T0 = 1 bpe, all spike bins are independent. Generally, the greater the T0 value, the more temporal information is available within each epoch (which are used to infer the state-transition matrix P in DecodewoRF). In analogy to sleep, T0 = 10 bpe roughly reflects the typical number of temporal bins of 200-ms hippocampal ripple-associated spike data with 20 ms bin size. Using all available neuronal ensemble spike activities from Datasets 1 and 2, we systematically varied T0 and computed the median decoding error (mean ± SEM). At each T0 configuration, analyses were repeated n = 50 independent Monte Carlo runs, with each run encountering different realization of simulated data. Assuming no temporal prior, the decoding performance of DecodewRF remained unchanged for varying T0 (horizontal dashed line, Fig. 1A,B). This is because the receptive filled is computed based upon the average spike activity over the entire or part of the behavioral episode. Once the receptive field is identified and the likelihood model is fixed, the temporal information becomes irrelevant for estimating the position at each temporal bin. In contrast, the population representation capacity and decoding accuracy of DecodewoRF changed as a function of T0. Our analysis suggested that the mean decoding error (green curves, Fig. 1A,B) was relatively stable with varying T0 < T, but the result variability within the same T0 configuration was relatively high (except for T0 = T bpe). The source of variability was contributed by at least two factors: First, because of random data splitting, breaking the temporal relationship in a spike train also destroy the spatial-temporal relationship (i.e., spike patterns with respect to animal’s run behavior during those periods). For instance, a given position is associated with different spike patterns that depend on the actual trajectory leading to it, such as animal’s heading, speed, and previous location. Second, the intrinsic Monte Carlo optimization nature of DecodewoRF induces additional variance (e.g., slow convergence of Markov chains)30. The inferred number of states m derived from DecodewoRF was relatively stable (m ∈ [33, 37] for Dataset 1; m ∈ [46, 53] for Dataset 2). As a qualitative assessment, we transformed and depicted the matrix P (Fig. 1C) via a topology graph (Fig. 1D), which describes the connectivity between the state (“spatial location”) and the topological representation of the environment2829. The topology graph is in arbitrary unit (a.u.): each note represents a state or virtual location, and the strength between two nodes indicates the pairwise connectivity (Pij + Pji, with dark color representing high strength). We also assessed the distribution of connectivity strengths and associated statistics (Fig. 1E). A detailed examination of the inferred 49 × 49 matrix P showed that the majority of nodes had more than one pair of significant nonzero connectivity. For instance, if we used a conservative high connectivity strength threshold 0.2–60% percentile of the empirical distribution, then 44/49 nodes had at least two connected nodes, whereas nearly half (24/49) of nodes had between 3 and 5 connected nodes. Combining the quantitative assessment and qualitative visualization, we reached the interpretation that the topology graph in Fig. 1D resembles a two-dimensional grid; its shape was invariant to the permutation of states in P. Although the exact values of P might be quantitatively different in random Monte Carlo simulations, the derived two-dimensional topology graphs were qualitatively similar with respect to with varying T0 configurations (data not shown) and varying subsets of neurons29. Impact of the number of cells Compared to awake experiences, firing rates of hippocampal neurons during post-run sleep episodes were reduced but highly correlated1525. However, the participation of the active hippocampal cells during sleep can be highly variable. More importantly, only a small subset of pyramidal neurons are active during individual SPW-ripple events15. To simulate such conditions, we used a fixed value of T0 = 10 bpe and randomly sampled a subset of cells from the neuronal population (ρ = 30–100%, with a minimum of 10 cells being active); only those selected neurons were used in subsequent decoding analyses. We found that the decoding error monotonically decreased as the increasing fraction of active neurons (Fig. 2A,B; see also the evolution of error distribution in Supplementary Fig. 6). When the number of cells fell below a certain percentage (~50%), DecodewoRF outperformed DecodewRF, yet the exact statistics varied between the two tested datasets. The slope of error curve in DecodewoRF was flatter, consistent with our previous finding that the topology-based coding may be more robust for spatial representation29. This is possibly because the DecodewoRF does not require a precise receptive field representation; in contrast, DecodewRF method is more dependent on the neurons that have a well-described place receptive field representation; when the receptive field characterization is less accurate due to the finite sampling issue, it may produce a large error. To test specific relationship between population representation and the cell physiological properties, we evenly split the neurons of Dataset 1 into two groups (upper vs. lower 50% percentile) according to their normalized spatial-information rates (Methods, Fig. 3A). Under the same configuration (T0 = 10, ρ = 50%), we compared the decoding accuracy of two population methods based on Monte Carlo simulations. The result (Fig. 3B) indicated that the information-rich neuron subpopulation had a greater influence on representation or decoding accuracy (P < 0.001, Wilcoxon signed rank test). In experimental sleep recordings, different subsets of neurons often fire at individual, isolated sleep episodes. To simulate this situation, we introduced additional level of randomness by assuming that distinct neuronal subpopulations (but with identical ratio ρ) are randomly active at individual epochs—this was in direct contrast to the previous assumption that the same subpopulations were engaged in all episodes. As a demonstration, we fixed T0 = 100 and applied DecodewoRF to Dataset 1. As expected, the decoding accuracy further degraded: for ρ = 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, the median errors were 9.07 ± 0.18, 10.02 ± 0.14, 10.25 ± 0.13, 11.51 ± 0.12, 11.99 ± 0.12, 12.53 ± 0.16 cm (n = 50 Monte Carlo runs), respectively. The error was not only greater than the error in the case of ρ = 1 (8.51 ± 0.18 cm, Fig. 1B), but also greater than the error with fixed subpopulations (T0 = 100 vs. T0 = 100* bpe, Table 2). Impact of bin size, spike rate and conjunctive factors During different sleep stages, hippocampal neurons fire at different timescales1523. To examine the influence of temporal bin size, we fixed ρ = 1 and T0 = 10 bpe, and varied bin size Δ (20, 50, 100, 150, 200, 250 ms) to repeat the decoding analysis. Note that a decreasing Δ would increase the number of discrete bins T. For DecodewRF, the decoding accuracy reduced with a decreasing Δ. This might be due to violation of Poisson assumption while using a small bin size or due to the presence of theta sequences (i.e., the decoded position may be systematically ahead of actual animal’s position). In contrast, the decoding performance of DecodewoRF (blue curve, Fig. 2D) was relatively stable for various Δ, possibly because its Bayesian inference procedure is less sensitive to the Poisson firing assumption30. Next, we thinned the spike train data by downsampling such that there was no more than one spike per time bin, which was aimed to simulate the sparse spiking in a finer timescale during sleep. As a result, the instantaneous firing rate reduced to 25–50% of the original rate. We found that the spike thinning procedure further degraded the decoding performance, and the decoding accuracy also dropped with decreasing number of neurons (Fig. 2C vs. Fig. 2A). Lastly, we jointly varied two parameters (such as T0 and ρ, or T0 and Δ), and repeated the decoding analysis. As shown in Table 2, we obtained consistent findings as in Fig. 2 (see also Supplementary Fig. 7): (1) For fixed Δ and ρ, there was a decreasing trend in decoding error with increasing T0, but the performance was relatively stable; (2) Regardless of T0, decoding error decreased with increasing ρ; (3) For fixed T0, there was a decreasing trend in decoding error with increasing Δ. Impact of non-place cells Next, we investigated if and how the presence of non-place cells would affect the decoding accuracy. A non-place cell implies that the putative pyramidal cell is not significantly modulated by spatial location, or its spatial tuning curve is flat. A high ratio of non-place cells implies a low signal-to-noise ratio (SNR) for fixed number of cell population. To simulate such a condition, we randomly selected a small subset of place cells (Dataset 1, many of which have overlapping place fields, see Supplementary Fig. 3) and evenly distributed spikes in time proportional to animal’s space occupancy (such that their average firing rates remained unchanged). Under the same configuration (T0 = 100 bpe), we found the decoding error of two methods increased with growing number of non-place cells (Supplementary Fig. 8). At first, DecodewoRF was slightly worse than DecodewRF, but the gap gradually reduced with decreasing SNR (Supplementary Fig. 8A, red vs. blue solid lines); and DecodewoRF outperformed DecodewRF significantly (P = 6 × 10−5, Wilcoxon signed rank test) in the worst scenario. This result confirmed the robustness of DecodewoRF under a low SNR. Significance testing via randomly shuffled data We tested our population decoding methods by comparing their estimate statistics derived from experimental data with those derived from randomly shuffled data (Supplementary Fig. 5B). Specifically, we used the hippocampal ensemble spike activity collected during animal’s run behavior (speed >15 cm s−1) in a circular track environment (Dataset 3). Upon completion of unsupervised learning (DecodewoRF), we recovered the state trajectory, which correlated with the animal’s run trajectory (Pearson’s correlation ∈ [0.73, 0.79] derived from 10 Monte Carlo runs, P = 1.5 × 10−15, Supplementary Fig. 9A). In addition, we obtained the state transition matrix and state field matrix, which were both qualitatively similar to the behavior-derived ground truth (Supplementary Fig. 9B,C). The average maximum a posteriori (MAP) probability score derived from DecodewoRF was 0.8814, and the weighted correlation was 0.8848. These statistics were also similar to those from DecodewRF, except that DecodewRF required receptive fields or behavioral measure a priori. We further constructed 1000 shuffled datasets. Each randomly shuffled dataset was subject to both temporal bin and cell identity shuffles (Methods). The Monte Carlo weighted correlation R and average MAP probability scores derived from the shuffled data than those derived from the raw data were significantly lower (Monte Carlo P < 10−7, Supplementary Fig. 10). These results demonstrated that, in the absence of behavioral measures (therefore no decoding error can be computed), theses metrics can be used as quantitative measures to assess the quality of reconstructed event for detection purpose. In the remaining analyses, we used R and its associated Z-score (or equivalent Monte Carlo P-value) for assessment. To compare the detection reliability and specificity between DecodewRF and DecodewoRF, we selected a random segment of run trajectory (T0 = 20 bpe, Fig. 4A), and systematically manipulated the ensemble spike activity during that time interval as follows: (1) We randomly removed 20–80% of cells from the population (i.e., ρ = 0.2–0.8). (2) Using all active cells (ρ = 1), we randomly removed spikes in selected temporal bins from each cell, with the number of bins ranging from 2 to 10 (i.e., 10–50% of T0)—which would sparsify and remove certain temporal structures in the ensemble spikes. We simulated each condition with 100 Monte Carlo runs, and each run produced an independent test set. We applied DecodewRF and DecodewoRF to those test sets and computed their R and Z-scores. The result comparison is shown in Fig. 4 (see also Supplementary Fig. 11 for scatterplot comparison). As the number of active cells dropped, the detection power of both methods decreased accordingly (Fig. 4B). In this specific example, the |R| value was below 0.5 when ρ = 0.2 (i.e., 10 cells). In terms of the Z-score, majority of simulated events were non-significant when ρ < 0.8. Removing spikes also degraded the detection power (Fig. 3C; see also Supplementary Fig. 12). Together, these results suggest that the detection power of DecodewoRF was more favorable in those tested conditions. Analysis of ripple-associated spike data in quiet wakefulness We also tested our methods on ripple-associated hippocampal ensemble spike data during quiet wakefulness (QW)—the awake brain state involved in memory replay similar to SWS16171819233233. In a long recording (Datasets 4a and 4b), hippocampal ensemble spikes were collected in the 4-hr pre-run and 4-hr post-run periods (inside a rest box in a familiar environment), separated by 40-min run period on a circular track in a novel setting (see Supplementary Fig. 13 for brain state classification). From Dataset 4b, we identified off-the-track candidate events based on hippocampal local field potential (LFP) and multi-unit activity (Methods), and further excluded the epochs with low fraction of active cells (<10%). See Table 3 for the summary statistics of candidate events in different states. The ratio of active cells across all selected epochs was ρ = 0.181 ± 0.002 (maximum 0.68, median 0.16). We binned each epoch with Δ = 20 ms, resulting in T0 = 11.5 ± 0.2 bpe (maximum 39, median 10). We then reconstructed the spatial (or state) trajectory based on the place field (or state field) λc(S) (where the state field was inferred by DecodewoRF from the run-associated ensemble spikes alone). For each epoch, we computed the weighted correlation R and its associated Z-score, and compared them with those obtained from randomly shuffled data. Figure 5 shows some examples of detected significant replays during post-QW epochs. Qualitative and quantitative assessment of those replay events indicated diverse (forward vs. reverse) spatiotemporal structures. Analysis of SWS-associated spike data At last, we applied our population decoding methods to experimental SWS-associated hippocampal ensemble spike activity (Dataset 4b). The candidate events with >10% active cells were selected for analysis (Table 3), and each event was treated as an independent epoch. Specifically, there was no difference in ρ between pre- and post-SWS (P = 0.31, rank-sum test; pre-SWS: ρ = 0.175 ± 0.003, maximum 0.45, median 0.16; post-SWS: ρ = 0.178 ± 0.003, maximum 0.53, median 0.16). With Δ = 20 ms, the number of bins per epoch was slightly longer in pre-SWS than in post-SWS epochs for Dataset 4b (P = 0.006, rank-sum test; pre-SWS: T0 = 12.7 ± 0.3 bpe; post-SWS: T0 = 11.9 ± 0.2 bpe). Hippocampal neurons’ mean firing rate remained stable between pre-SWS and wake as well as between post-SWS and wake (Supplementary Fig. 14), although the mean firing rate in wake was significantly higher (Wilcoxon signed rank test, P < 1.3 × 10−5). To examine significant pre- and post-SWS reactivation events, we used the inferred λc(S) during RUN to estimate the state trajectory and posterior probability scores of candidate events during respective pre- and post-SWS periods. Some detected reactivation examples are shown in Fig. 6A,B, respectively. In comparison, the quality of detected post-SWS replay events was qualitatively better in terms of trajectory continuity than that of detected pre-SWS events. We identified statistically significant events based on their computed R and Z-score statistics (Table 3). The absolute number and the ratio of significant events increased from pre-SWS to post-SWS. In addition, the Z-score among the significant events was greater in post-SWS (P < 0.01, rank-sum test). These results suggested that the neuronal ensemble patterns shared more similar structures between post-SWS and RUN than between pre-SWS and RUN—a finding consistent with the pairwise correlation method (ref. 4, see Supplementary Fig. 15) and another independent investigation31. We further examined the nonstationarity of sleep epochs by comparing the results derived from the first and second-half of post-SWS candidate events (i.e., SWS(1) and SWS(2) have the same epoch number that had no less than 10% active cells, defined by in Table 3). For DecodewoRF, we found that the T0, ρ and R statistics were similar between SWS(1) and SWS(2), but the numbers that aim to assess the significance of detected events ( and in Table 3) all decreased in SWS(2). This could be due to the fact that memory reactivation was more frequent in SWS(1) than in SWS(2), or the representation power decreased in SWS(2). To test the predictive power of SWS(1) to SWS(2), we applied DecodewoRF to SWS(1) and inferred the SWS-state field λSWS (which was distinct from estimated from spikes alone in run behavior). We then used to assess the R statistic for SWS(2), and compared that with the R statistic obtained from . A scatterplot comparison (Fig. 6C,D) showed a decrease trend in |R| (P = 10−15) and Z-score (P = 1.1 × 10−4, both Wilcoxon signed rank test) from using to using , suggesting a reduction of predictive power in SWS(1) → SWS(2). Discussion Interrogating the temporal structure and content of sleep-associated hippocampal ensemble spikes can reveal important mechanisms of hippocampal sequence generation343536 or diverse contributing roles of hippocampal neurons in plasticity31. However, analysis of such spike data has posed a great challenge. In this study, we applied two population decoding methods (DecodewRF and DecodewoRF) to rat hippocampal ensemble spikes recorded in different brain states, aiming to infer the animal’s actual or virtual spatial location based on their spatiotemporal firing patterns. In terms of representation and detection power, population decoding methods are more powerful than the conventional correlation or sequence methods for discovering inherent structures of the ensemble spike data. Moreover, since the latent state corresponds to an abstract or virtual behavioral correlate in DecodewoRF, detecting statistical significance of temporal sequences is not restricted by the line fitting procedure23, which may become an issue for DecodewRF in the presence of cursive trajectories (e.g., in a two-dimensional environment) or in the presence of discontinuity in spatial trajectory (see an example in Supplementary Fig. 16). Moreover, our Bayesian inference procedure automatically identifies the model order in DecodewoRF to allow optimal choice of spatial resolution given observed ensemble spikes. From the analyses of both synthetic and experimental data, we found that the representation and detection power of both population decoding methods were strongly dependent on the number of active place cells. Since place cells did not contributed evenly in representation (Fig. 3 and Supplementary Fig. 6), fast-firing neurons did not always contain the most spatial information (bits/spike). In fact, recent findings suggested that slow-firing neurons may contribute more to neuronal sequences from pre to post-sleep31. Considering the low fraction of active hippocampal cells in sleep and the lognormal distributed phenomenon25, a large number of recorded place cells are necessary to secure the statistical power for sleep data analysis. Population decoding methods have been proven useful in studying information transmission and sensory coding of neural systems3738. Here, our model-based decoding approach offers a statistical framework to assess the content of sleep-associated hippocampal ensemble spikes, which may reveal important mechanism insights on hippocampal neurons in memory consolidation. Similar to other reports1831, we found that the reactivated spatial trajectories or sequences in hippocampal ensemble representations were better correlated and more sharply defined in post-SWS than in pre-SWS. Nevertheless, several statistical questions still remain unanswered. One puzzle is how can we extract significant non-spatial information encoded in sleep? Another pressing issue is to design statistical methods that can adapt to specific temporal (e.g., inhomogeneous, nonstationary, and heteroscedastic) structure of ensemble spike data. Thus far, we have used a uniform temporal bin size throughout SWS, yet finding the optimal timescale is critical for decoding analyses. Our current study has focused on hippocampal ripple-associated ensemble spike activity and ignored other spike activities outside of ripples. Analyzing continuous sleep-state spike activity would be the next goal. Notably, hippocampal and cortical neurons operate at a different timescale in REM sleep from SWS. The question of interpreting sparse and sporadic REM-associated hippocampal spike activity remains unresolved. A recent report has revealed similar geometric structure in neural correlations of hippocampal neurons between active navigation and REM sleep39. It would be interesting to test the population decoding methods on such independent recordings. In addition, these methods can be tested to evaluate brain state transition. In principle, our unsupervised population decoding framework can be applied to hippocampal-cortical or thalamocortical ensemble spikes in sleep10404142. Joint investigation of spatiotemporal sequences in these circuits during sleep replay events are crucial to infer the communications and information transfer between these circuits during memory consolidation. Given a large neuronal ensemble, the DecodewoRF method is appealing since it requires no explicit measure of behavior or receptive fields, where the latent states may represent non-spatial features of experiences or distinct behavioral patterns that cannot be measured directly. Ultimately, it is critical to discover nonlinear interactions and extract spatiotemporal organization among neuronal ensembles, integration of such principles and data-driven neuronal models will be the key to revealing intrinsic structures of neuronal ensemble spikes. Methods Animal behavior and neurophysiological recordings Long-Evans rats were freely foraging in familiar spatial environments for a period of 30–45 minutes (Datasets 1–3). In Datasets 4a and 4b, rats were first put in a sleep box of a familiar environment for 4 hours, and then moved to a circular track (novel environment) for running about 45 minutes, and then put back to the sleep box for another 4 hours (ref. 31). All procedures were approved by the MIT and NYU Institutional Animal Care and Use Committee and carried out in accordance with the approved guidelines. Custom microelectrode drive (Datasets 1–3) or silicon probe arrays (Datasets 4a and 4b) were implanted unilaterally or bilaterally in the animal’s dorsal hippocampal CA1 area. Spikes were acquired with a sampling rate of 31.25 kHz and filter settings of 300 Hz–6 kHz. Two infrared diodes alternating at 60 Hz were attached to the drive of each animal for position tracking. We used a custom manual clustering program for spike sorting to obtain well-isolated single units. Details are referred to previous publications2331. Putative interneurons were identified based on the spike waveform width and average mean firing rate. In addition, all putative pyramidal neurons selected for analysis had peak firing rate >1 Hz. Bayesian decoding The Bayesian decoding algorithms is formulated within a state-space model framework2122282930. Let St represent the animal’s spatial position label at discrete time t, and let yt represent the observed neuronal population spike count between ((t − 1)Δ, tΔ], where Δ is the temporal bin size. The state variable St is assumed to follow a first-order Markovian dynamics and characterized by p(St|St − 1). The goal of Bayesian decoding is to infer the posterior probability p(St|y1:t) given all the spike history up to time t. Here we assumed that conditional on the state St, the population firing of C hippocampal place cells follows a Poisson likelihood model where denotes the spike count from the c-th neuron at the τ-th temporal bin. In light of Bayes’ rule, the posterior distribution of the state St is given by where p(St|St−1) denotes the temporal prior and p(y1:t) is a normalizing constant. For decoding analysis, we used two population decoding methods. In the first method (DecodewRF, Supplementary Fig. 2A), the animal’s spatial position was measured during run behavior, which was further used to estimate neuronal receptive fields λc(S) (note: S is continuous-valued and can be finite or infinite, with proper dimensionality depending on the spatial environment). Hippocampal place fields were estimated using a spatial bin size of 10 cm for one-dimensional tracks, and bin size of 5 × 5 cm2 or 15 × 15 cm2 for two-dimensional space, and further smoothed using a Gaussian template (5 × 1 for one-dimensional or 3 × 3 for two-dimensional environment) with a half SD. This method consists of both encoding and decoding phases, where the encoding phase is supervised. In the second method (DecodewoRF, Supplementary Fig. 2B), the animal’s behavioral measures are assumed inaccessible, therefore no place fields can be estimated from the behavioral data. The second method only consists of decoding phase, and it is purely unsupervised. In this case, St represents a discrete-state label for the spatial position, and it can be either finite or infinite depending on the statistical assumption, spatial resolution, and the size of data. In this special case, the state space model is a hidden Markov model (HMM); trajectories across spatial locations (“states”) were associated with consistent hippocampal ensemble spiking patterns, which were characterized by a stationary state transition matrix defining p(St|St−1) (e.g., Fig. 1C). The observed spike count data was defined by a Poisson probability distribution p(yt|St) in equation (1). Unlike DecodewRF, the state of DecodewoRF was subject to permutation ambiguity due to the lack of behavior measure. The goal of inference is to estimate the maximum a posteriori (MAP) state sequences S1:T and the unknown state transition matrix and rate parameters λc(S) with respect to the state space S = {Si} (where Si ∈ {1, 2, …, m} are categorical variables). See refs 28, 29, 30 for details of model description and inference procedure. Briefly, first, we applied a Bayesian nonparametric version of the HMM: hierarchical Dirichlet process (HDP)-HMM, combined with advanced Markov chain Monte Carlo (MCMC) inference methods30. The number of latent states, m, was automatically inferred from the MCMC inference procedure (Supplementary Fig. 17A). Second, we constructed a “state space map” between the discrete state and the spatial position (see Supplementary Fig. 17B for illustrations). For one-dimensional environment, the ideal state space map shall have a one-to-one mapping. Third, to visualize the inferred state transition matrix (Fig. 1C), we applied a force-based algorithm to derive a scale-invariant topology graph that defines the connectivity between different states (nodes) (Fig. 1D), which provided intuitive result interpretation and qualitative assessment. In the testing phase, two population decoding methods were operated in a similar way, except with different λc(S) (one constructed from behavior and the other estimated from spikes alone). We applied these two methods to reconstruct the spatial position or state S at each time bin, and computed the average MAP probability score from multiple bins. Information rate of hippocampal neurons Information-theoretic measures have been used to characterize the information of hippocampal neurons43. We define the spatial information rate of the c-th hippocampal neuron as follows where λc(S) denotes the mean firing rate at spatial location S, and λc = ∫λc(S)p(S)dS denotes the total average firing rate (spikes/s). The unit of Ic is measured by bits/s. To account for the total firing rate effect, we compute the normalized information rate, measured by bits/spike. Statistical assessment For DecodewRF, we computed the median decoding error between the estimated animal’s position and the actual position. For DecodewoRF, the animal’s actual position was solely used for result assessment. Based on the state space map, we estimated animals spatial trajectories and computed the median decoding error2930. Statistically significant reactivation events were determined by three established criteria1718: (1) The absolute “weighted correlation” R (which measures the strength of correlation between the changes in probability values across time and spatial position) greater than 0.5. (2) The time length is greater than five temporal bins (i.e., 100 ms for QW or SWS epochs). In addition, the MAP probability score equal or less than the threshold (5/total number of position bins; below which is just a chance level) is also regarded non-significant. In addition, we generated shuffled candidate events from each pre-identified candidate event, and computed the Rshuffle from randomly shuffled population spike data. Two types of shuffling operations were considered: temporal shuffling and cell shuffling. Algebraically, the spike count matrix was subject to both row (temporal) and column (cell) shuffle operations. A total of 1000 shuffled samples were constructed. From the raw and shuffled statistics, we computed the Z-score for R as follows31: Z = (R − mean of Rshuffle)/(SD of Rshuffle). (3) The Z-score of R is greater than 1.65 (equivalent to one-side P-value 0.05 assuming the null distribution is normally distributed). A high positive Z-score indicates that the raw data statistic is much greater than those obtained by chance (null hypothesis), and therefore is highly significant in a statistical sense. If the null distribution (of shuffle statistics) is non-normally distributed (Shapiro-Wilk test or Anderson-Darling test), we derived the Monte Carlo P-values from the sample distribution. Identification of hippocampal ripple candidate events during sleep and quiet wakefulness During sleep, we focused on SWS epochs, which were primarily determined by the low EMG amplitude and high delta/theta power ratio in EEG activity (REM sleep is associated with low EMG, low delta/theta power ratio and high theta power). For screening the candidate events, we used hippocampal LFP ripple band (150–300 Hz) power combined with hippocampal multi-unit activity (threshold > mean + 3SD). We also imposed a minimum cell activation criterion (>6 or 10% of cell population, whichever is greater). Similar LFP and multi-unit activity criteria were also applied to QW periods, when the animal was in an immobile wake state (speed <2 cm s−1). Additional Information How to cite this article: Chen, Z. et al. Uncovering representations of sleep-associated hippocampal ensemble spike activity. Sci. Rep. 6, 32193; doi: 10.1038/srep32193 (2016). Supplementary Material Supplementary Information We thank S.W. Linderman for data analysis assistance and G. Buzsáki for support. This work is supported by an NSF-CRCNS (Collaborative Research in Computational Neuroscience) award IIS-1307645 (to Z.C. and M.A.W.) from the US National Science Foundation, an NIH-CRCNS award R01-NS100065 from the NINDS (Z.C.), the Office of Naval Research MURI grant N00014-10-1-0936 and an NIH grant TR01-GM10498 (to M.A.W.). This material is also based upon work supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216. Author Contributions Z.C. and M.A.W. designed research; Z.C. performed research; A.D.G. and H.P. collected some of experimental data; Z.C. analyzed data; Z.C. wrote the paper with contributing input from all other authors. Figure 1 Illustration and decoding performance of population decoding methods. (A,B) Box plots of median decoding error from DecodewoRF with varying values of T0 (bins per epoch), for Datasets 1 and 2, respectively. The green curves are the averaged median decoding error. The median decoding error of DecodewRF was independent of T0 (horizontal dashed line; 7.02 for Dataset 1, 7.73 for Dataset 2). Representative examples of inferred state-transition matrix (C) from DecodewoRF and the derived topology graph (D) from Dataset 2 (dark color represents high connectivity strength). The percentage of nonzero entries in (C) is 14.8%. (E) Histogram of nonzero connectivity strengths (Pij + Pji, i ≠ j) for panel (C) (mean: 0.23; SD: 0.32). Figure 2 Comparison of median decoding error between DecodewRF and DecodewoRF. (A,B) Decoding error decreased with increasing numbers of cells in neuronal population. (C) Decoding error changed with respect to varying fractions of active neurons (under thinning) and (D) changed with respect to varying temporal bin size. Error bar denotes SEM (n = 50 Monte Carlo runs). Figure 3 Specificity of hippocampal neurons in cell population on the decoding error. (A) Cumulative distribution of normalized spatial information rate (bits/spike) of 49 hippocampal neurons (Dataset 1). (B) Comparison of median decoding error by using spatial-information high vs. low subpopulations (T0 = 10 bpe, ρ = 0.5; error bar denotes SEM, n = 50 Monte Carlo runs). Figure 4 Comparison of detection reliability between DecodewRF and DecodewoRF. (A) Segment of a spike count matrix with 20 temporal bins. (B,C) Weighted correlation (Left) and Z-score (Right) for varying active cell ratio ρ (B) and for removing spikes across different number of bins (C). Error bar denotes SEM (n = 50 Monte Carlo runs). Figure 5 QW-associated ensemble spike data analysis. (A) Example of spike rasters and the associated decoded spatial trajectories in quiet wakefulness. The number at the top of each panel indicates the absolute weighted correlation |R|. (B) Examples of detected significant replays. X-axis represents time bin (bin size Δ = 20 ms). Figure 6 SWS-associated ensemble spike data analysis. (A,B) Examples of detected significant pre-SWS (A) and post-SWS (B) reactivation events. The number at the top of each panel indicates |R|. X-axis represents time bin (bin size Δ = 20 ms). (C,D) Testing predictability of RUN and SWS(1) data for SWS(2): scatterplot comparison of weighted correlation (C) and Z-score (D) between RUN → SWS(2) and SWS(1) → SWS(2). Lower left corner marked by dashed line indicates the non-significance zone. Table 1 Summary statistics of ensemble recordings in the rat hippocampus. Dataset # Place cells Rate (Hz) (mean ± SEM) Recording, run time (min) Recording environment 1 49 1.48 ± 0.45 24.3, 9.8 open field 2 37 1.32 ± 0.13 22.9, 12.3 open field 3 50 0.64 ± 0.07 28.9, 10.2 circular track 4a 77 1.11 ± 0.08 44.6, 25.4 circular track 4b 77 0.66 ± 0.05 480, N/A rest/sleep box Note that the mean firing rates of the same set of neurons reduce by nearly 50% from wake (4a) to sleep (4b). Table 2 Comparison of median decoding error (mean ± SEM, n = 50 Monte Carlo runs) between DecodewRF and DecodewoRF for Dataset 1. T0 (bpe) DecodewRF DecodewoRF ρ = 0.3 ρ = 0.5 ρ = 0.8 ρ = 0.3 ρ = 0.5 ρ = 0.8 10 13.97 ± 0.07 10.49 ± 0.06 7.78 ± 0.02 12.56 ± 0.07 11.37 ± 0.06 10.61 ± 0.05 20 15.35 ± 0.12 11.03 ± 0.04 7.80 ± 0.01 12.39 ± 0.05 10.65 ± 0.04 9.71 ± 0.04 50 14.40 ± 0.08 10.87 ± 0.06 7.88 ± 0.02 11.15 ± 0.05 9.78 ± 0.05 8.51 ± 0.03 100 14.50 ± 0.09 10.78 ± 0.05 7.93 ± 0.02 11.49 ± 0.05 10.04 ± 0.04 8.84 ± 0.04 100* 15.97 ± 0.18 10.78 ± 0.09 7.93 ± 0.04 12.53 ± 0.16 11.51 ± 0.12 9.07 ± 0.18   Δ = 50 ms Δ = 150 ms Δ = 250 ms Δ = 50 ms Δ = 150 ms Δ = 250 ms 10 14.53 ± 0 8.58 ± 0 7.01 ± 0 16.21 ± 1.23 11.12 ± 0.32 10.52 ± 0.16 20 14.53 ± 0 8.58 ± 0 7.01 ± 0 16.35 ± 1.68 12.10 ± 0.31 10.02 ± 0.15 50 14.53 ± 0 8.58 ± 0 7.01 ± 0 16.68 ± 1.20 12.47 ± 0.32 10.17 ± 0.19 100 14.53 ± 0 8.58 ± 0 7.01 ± 0 15.40 ± 1.19 10.90 ± 0.34 8.38 ± 0.19 When varying ρ, we fixed Δ = 250 ms; when varying Δ, we fixed ρ = 1. Except for T0 = 100* bpe, the same active cells were used in each epoch. Table 3 Summary statistics of candidate events (Dataset 4b). State |R| Z pre-QW 338 165 87 15 15 0.56 1.83       46 15 15 0.54 1.86 pre-SWS 984 471 256 33 31 0.60 1.93       186 58 58 0.55 1.93 post-QW 1755 1015 627 100 100 0.62 2.05       468 223 218 0.58 2.06 post-SWS 1519 764 440 62 60 0.59 2.02       343 142 139 0.56 2.10 Notations: : total epoch number; : epoch number that had no less than 10% active cells; : epoch number with |R| > 0.5; : epoch number with Z > 1.65; : number of significant events based on three significance criteria. The last two columns show the median |R| and Z-score statistics derived from the group. Two numbers in the last five columns show the results derived from DecodewRF (top) and DecodewoRF (bottom), respectively. ==== Refs Buzsáki G. Memory consolidation during sleep: a neurophysiological perspective . J Sleep Res 7 , 17 –23 (1998 ).9682189 Stickgold R. Sleep-dependent memory consolidation . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3248010.1038/srep32480ArticleFunctionalized chitosan electrospun nanofiber for effective removal of trace arsenate from water Min Ling-Li 12Zhong Lu-Bin 1Zheng Yu-Ming a1Liu Qing 12Yuan Zhi-Huan 1Yang Li-Ming b31 CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China3 Department of Chemical & Biomolecular Engineering, National University of Singapore, 21 Lower Kent Ridge Road, 119077, Singaporea ymzheng@iue.ac.cnb cheylm@nus.edu.sg30 08 2016 2016 6 3248025 04 2016 08 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/An environment-friendly iron functionalized chitosan elctrospun nanofiber (ICS-ENF) was synthesized for trace arsenate removal from water. The ICS-ENF was fabricated by electrospinning a mixture of chitosan, PEO and Fe3+ followed by crosslinking with ammonia vapor. The physicochemical properties of ICS-ENF were characterized by FESEM, TEM-EDX and XRD. The ICS-ENF was found to be highly effective for As(V) adsorption at neutral pH. The As(V) adsorption occurred rapidly and achieved equilibrium within 100 min, which was well fitted by pseudo-second-order kinetics model. The As(V) adsorption decreased with increased ionic strength, suggesting an outer-sphere complexation of As(V) on ICS-ENF. Freundlich model well described the adsorption isotherm, and the maximum adsorption capacity was up to 11.2 mg/g at pH 7.2. Coexisting anions of chloride and sulfate showed negligible influence on As(V) removal, but phosphate and silicate significantly reduced As(V) adsorption by competing for adsorption sites. FTIR and XPS analysis demonstrated –NH, –OH and C–O were responsible for As(V) uptake. ICS-ENF was easily regenerated using 0.003 M NaOH, and the removal rate remained above 98% after ten successively adsorption-desorption recycles. This study extends the potential applicability of electrospun nanofibers for water purification and provides a promising approach for As(V) removal from water. ==== Body Arsenic, existing as various complex forms in the aquatic environment12, has been identified as one of the most harmful and toxic contaminants found in the environment34567, because the exposure to arsenic species can lead to lung and bladder cancer, skin lesions, and even death in humans8. The sources of arsenic contamination in groundwater are both natural and anthropogenic28. The elevation of arsenic concentration in groundwater has been reported in many countries throughout the world, which has direct consequences to pose great threat to human health. Arsenic poisoning of groundwater was first reported in Taiwan in 19682. It is estimated that there were 19.6 million people at risk of being affected by the consumption of arsenic contaminated groundwater in China9. To minimize the health problems associated with arsenic in water, the World Health Organization (WHO) had recommended a strict permissible limit of 10 μg/L as maximum arsenic contaminant level in drinking water1. Various technologies have been developed for arsenic removal, including precipitation, membrane processes, ion exchange, and adsorption2. Adsorption has been regarded as the most promising method owing to its cost effectiveness and simplicity in operation1011, especially when the arsenic concentration is low. Recently, biosorption has been attracted more attention because the biosorbents are eco-friendly and capable of extracting trace toxic elements from a large volume of solution11213. Many biosorbents have been reported for arsenic adsorption, such as bacteria cells14, plant biomass15 and chitosan based materials1617. Recently, the development of chitosan based adsorbents for metal ions removal has been becoming a hot topic due to its special physical and chemical properties. Chitosan is a transformed polysaccharide obtained by the deacetylation of chitin and can be easily prepared in many different physical forms such as nanoparticles, gel beads, membranes and fibers1819. Chitosan flakes20, molybdate-impregnated chitosan beads21, chitosan-coated biosorbent8, iron coated chitosan flakes22, chitosan-immobilized sodium silicate23, TiO2-impregnated chitosan beads24 and magnetic nanoparticles impregnated chitosan beads25 have been reported for the adsorptive removal of arsenic from water. It is well known that larger specific surface area for a particular adsorbent means higher adsorption capacity, and the fabrication of chitosan porous or fibrous structure will definitely enlarge its specific surface area. This could be obtained via electrospinning, an emerging technique to prepare continuous and ultrafine nanofibers2627. Nanofibers produced by electrospinning combines the advantages of nanomaterial (high specific surface area) and bulk material (easy separation from water), which has been recently employed as one of the most effective absorbents2829. However, chitosan has rigid D-glucosamine repeat units with regularly arranged hydroxyl and amino groups, which leads to poor electrospinnability30. Our previous study indicated that the addition of a compatible polymer, poly(ethylene oxide) (PEO), could enhance the spinnability of chitosan and yield faultless nanofibers31. The fabricated chitosan based electrospun nanofiber (CS-ENF) has been employed for arsenic removal. The results indicated that it could be an effective arsenic absorbent at acidic condition, however, the CS-ENF showed little affinity towards As(V) with the circumstance of pH around 7.031. It has been reported that some metal-based material have been incorporated into electrospun nanofibers, which could significantly enhance the composite fibers to achieve desired functional properties28. Additionally, iron-based materials were frequently considered as adsorbent for arsenic removal from water under neutral pH323334. Therefore, in this work, Fe3+ was selected as the additive to modify the properties of CS-ENF, and the iron functionalized chitosan based elctrospun nanofiber (ICS-ENF) was successfully fabricated in an environment-friendly way. The physicochemical properties and sorption mechanism were systematically explored using a variety of characterization tools, including FESEM, TEM-EDX, XRD, FTIR and XPS. Additionally, the arsenic removal performance of ICS-ENF was examined by both adsorption kinetics and isotherm study, and the influences of various experimental parameters, such as pH, ionic strength and competitive anions were also investigated. Finally, the regeneration and column tests were carried out to verify the potential reusability and reliability. Results and Discussion Characterization of nanofibers The color of chitosan electrospun nanofiber changed from white to light yellow after the addition of FeCl3. The morphologies and fiber diameter distributions of both ICS-ENF and CS-ENF are shown in Fig. S1. The FESEM images show that the electrospun nanofibers were beadless, continuous and highly porous, which is also supported by TEM observed in Fig. 1. The fiber diameter distributions demonstrated that the average fiber diameter increased from 128 nm to 153 nm due to the incorporation of iron to chitosan matrix (Fig. S1a,b). The tensile modulus of the chitosan electrospun nanofiber didn’t change with the addition of 3 wt.% FeCl3 (Fig. S1c). However, a small decrease in the elongation was observed with the addition of FeCl3. Additionally, Fig. 1 represents corresponding elemental analysis of the nanofibers, which indicates that the relative content of nitrogen in ICS-ENF significantly increased after crosslinking by ammonia vapor (Fig. 1b). Furthermore, the EDX elemental mapping (Fig. 1c) demonstrated the fairly uniform distribution of Fe in the entire nanofibers which indicates that iron was successfully impregnated into the chitosan nanofiber. Figure S2 illustrates the typical XRD patterns of CS-ENF and ICS-ENF. Two characteristic peaks of 2θ between 5 and 25° for CS-ENF were observed. The peak around 2θ = 7.5° was related to chitosan amorphous structure due to the presence of random amino groups (–NH2), while the peak in the 2θ region between 17 and 25° was corresponding to the biopolymer structure resulting from packing of the polymer chain and their inter-chain interactions35. Similar with CS-ENF nanofiber, ICS-ENF also contains two peaks, but it presented a higher crystallinity than that of CS-ENF in terms of the relatively sharp peak around 2θ = 10.1° (Fig. S2). Moreover, after doped with iron, the peak corresponding to 2θ = 21° was shifted from 20.5° to 22.5°. This is because the interactions between chitosan and metal ions such as Cr, Mn and Fe could affect the crystallinity via new covalent bonds between the biopolymer and the metal ions36. Although several diffraction peaks could be observed in the XRD patterns, the largely widen peaks and weak peak signals demonstrate the amorphous property of these nanofibers. Effect of solution pH Solution pH could affect the surface charge of adsorbent/adsobate, thus it could play a crucial role in determining the behavior of adsorption system. Figure 2a demonstrates the influence of equilibrium solution pH (from 4.5 to 11.5) on the arsenic adsorption by ICS-ENF. Under the acid and weak basic conditions, ICS-ENF shows effective adsorption of As (more than 90% removal), and adsorption performance decreased slightly from 4.5 to 7.3. This indicates that ICS-ENF (with iron) represented better adsorption capability than that of CS-ENF (without iron), which showed little affinity towards As(V) with the circumstance of pH around 7.031. In addition, ICS-ENF has high adsorption capability at pH = 7, which is very desirable because most natural water bodies are at near neutral condition. However, with the further increasing pH value from a turning-point at 7.3, the adsorption of As(V) dramatically declines and even no adsorption process was observed upon pH up to 11.3. Similar phenomenon has been reported for the adsorption of As(V) by Zr(IV) loaded orange waste gel1 and the adsorption of As37 by Fe-Mn binary oxide38. Such behavior could be explained in terms of pHpzc of the adsorbent in the solution (pHpzc = 6.3, Fig. 2b), as As(V) adsorption would be facilitated by electrostatic interaction between negatively charged As(V) species (H2AsO4− and HAsO42− are predominant in the experimental pH range) and positively charged absorbent surface. In this case, the higher removal efficiency was due to the abundant protonation of the adsorption sites on ICS-ENF, which interacted with negatively charged arsenate species at pH < pHpzc. With the increasing pH, the net surface charge on the adsorbent became less positive and even negative, and repulsive forces between anionic adsorbate and adsorbent which consequently resulted in a decrease of the As(V) adsorption capacity. Additionally, we also conducted Fe release experiments under various initial pH conditions (Fig. 2c). It is worthwhile to note that no leakage of iron from the implanted nanofiber was observed from pH 5.2 to 10.7, and even at initial pH 3.2, only 17 μg/L of Fe was detected, which is far less than the MCL of Fe in drinking water (300 μg/L). Thus, the results of pH screening and Fe release experiments suggest that this ICS-ENF adsorbent could be suitable for arsenic contaminated ground water treatment. Adsorption kinetics and effect of ionic strength It is very important to be able to predict the adsorption kinetics rate, at which arsenic is removed from contaminated water in order to design appropriate sorption units. Figure 3a shows As(V) adsorption kinetics onto both of ICS-ENF and CS-ENF. It is apparent that the whole adsorption processes could be divided into two stages, a rapid stage at the very beginning following by a gradually slower stage until the adsorption equilibrium was achieved. Typically, the adsorption was nearly reached equilibrium after 100 min and more than 87% of the total adsorption occurred within the first 50 min for ICS-ENF, which was much higher than that of CS-ENF (only 12%, Fig. 3a), and the corresponding maximum adsorption capacities were 0.87 and 0.11 mg/g for ICS-ENF and CS-ENF, respectively. This confirms again that the ICS-ENF with implanted iron significantly improved the As(V) adsorption performance. The arsenic adsorption mechanism on IC-ENF was first investigated by evaluating the effect of ionic strengths on the adsorption behavior. Figure 3b exhibited that the arsenic adsorption decreased with the increase of solution ionic strength. It implies an outer-sphere adsorption mechanism for As(V) on ICS-ENF, because anions such as NO3− as one of potential adsorption competitors, which has been believed to be adsorbed via outer-sphere complexation, are strongly sensitive to ionic strength39. In order to have a better knowledge of the mechanism of arsenate adsorption, the adsorption kinetics data was fitted using different models. Generally, the pseudo-first-order and pseudo-second-order rate equations were frequently employed to analyze the kinetics adsorption data. A linear form of pseudo-first-order kinetics and the pseudo-second-order kinetics model based on the adsorption equilibrium capacity can be mathematically expressed as35 where, qe and qt (mg/g) are the adsorption capacity at equilibrium and at any time t, respectively; and k1 (min−1) and k2 (g mg−1 min−1) are the rate constants for pseudo-first-order and pseudo-second-order adsorption kinetics model, respectively. Figure 3a,b illustrate the fitting curves of these two models for As(V) adsorption onto ICS-ENF under different ion strength conditions, and the corresponding parameters for pseudo-first-order and pseudo-second-order kinetics models are summarized in Table 1. Based on Table 1, the slightly higher correlation coefficients were observed for pseudo-secondary-order model than that of the pseudo-first-order equations. This indicates chemisorption occurred during As(V) adsorption on the ICS-ENF involving the specific interactions with surface functions group40, which will be elucidated more in the following later sections. Additionally, to further verify the contribution of intra-particle diffusion on the adsorption dynamics process, Weber and Morris model41 was also used to analyze the kinetics data of As(V) sorption onto the ICS-ENF (Fig. 3c), where kp (min−1) is the intra-particle diffusion rate constant. If intra-particle diffusion is the rate controlling step, the plot of qt against t1/2 should give a straight line passing through the origin. However, multi-linearities were clearly observed over the whole time range (Fig. 3c), showing that the three steps could govern adsorption processes. The first linear section exhibited one steep slope refereeing to the rate controlling as the pore diffusion, and the second linear portion was a relatively moderate sorption stage, which indicates the intra-particle diffusion controlling in the pore structure. Finally, the last linear section for slow sorption stage was relating to the stereo-hindrance effect derived from the adsorbed species42. Adsorption isotherms The arsenic adsorption isotherms for both ICS-ENF and CS-ENF at different initial arsenic concentrations are exhibited in Fig. 4a. ICS-ENF exhibited a maximum capacity of 13.3 mg/g at initial As (V) concentration of 3.1 mg/L (Ce 448 μg/L), which was much higher than that (0.5 mg/g) of CS-ENF. This further demonstrates that the doped Fe remarkably improved the As(V) adsorption capacity even under neutral pH conditions. Additionally, Fig. 4b represents the equilibrium As(V) concentration vs. initial As(V) concentration for ICS-ENF adsorption experiments and it indicates that the residual As(V) concentration at equilibrium could be easily decreased to below 10 μg/L (maximum arsenic contaminant level) at initial As(V) concentrations ranging from 100 μg/L to 750 μg/L. Moreover, two well known adsorption isotherm models namely Langmuir and Freundlich are used to analyze the equilibrium data8. Langmuir isotherm assumes monolayer adsorption on a homogeneous surface and the equation is where qmax (mg/g) is the maximum amount of arsenate per unit weight of adsorbent, and b (L/mg) is a Langmuir constant which is related to the affinity of the binding sites. qe is the amount of As(V) adsorption corresponding to monolayer coverage. The Freundlich model, which assumes a heterogeneous surface and multilayer adsorption with an energetic non-uniform distribution, is expressed as where KF and n are the Freundlich constants. The adsorption constants obtained from the isotherms for Langmuir and Freundlich models were given in Table S1. As shown in Table S1, both of Langmuir and Freundlich represent well fitting, and the slightly higher regression coefficient suggests that the Freundlich model is more suitable for describing the adsorption behavior of As(V) by ICS-ENF, which indicates that it might be in favor of heterogeneous surface and multilayer adsorption mechanism. Whereas, it is worthwhile to note that the maximum adsorption capacities (qmax) as estimated by the Langmuir model for ICS-ENF could be up to 11.2 mg/g. Table 2 summarizes the reported adsorption capacities of various adsorbent on arsenic adsorption and ICS-ENF showed a much higher adsorption capacity compared with many other chitosan related adsorbents. In this case, the high arsenic adsorption capacity at low equilibrium arsenic concentrations could benefit the applications of ICS-ENF in real water environment, especially where most contaminated water sources have relatively low arsenic concentrations. Therefore, it can be concluded that ICS-ENF is a promising absorbent for the treatment of low arsenate-containing water including drinking water. Effect of coexisting anions Anions ubiquitously present in natural and polluted waters, and can affect the arsenic removal over adsorbent due to the competitive binding to the same adsorption sites between arsenate and anions, thus reducing the arsenate removal. In this study, the representative anions (Cl−, SO42−, SiO32− and PO43−) with concentrations of 0.1, 0.5 or 1.0 mM for each ion were selected as competition anions to study the influence on the adsorption capacity of As(V) with its initial concentration of 0.003 mM (much lower than that of the co-ions). The experimental results (Fig. 5a) indicate that Cl− and SO42− even up to 1.0 mM concentration didn’t have a negative effect on the adsorption of As(V), whereas SiO32− and PO43− could significantly interfere the sorption on ICS-ENF nanofiber. With the concentration of SiO32− and PO43− to 1.0 mM, the removal efficiency decreased up to 34.6% and 26.3%, respectively. The similar adverse effects have been also observed by previous studies4344. While it has been reported that the decrease of As(V) sorption for the presence of phosphate might be due to the strong competition as the similar chemical structure with the arsenate43, the influence from silicate could be because of itself polymerization which can inhibit arsenate adsorption via steric effects or by decreasing the surface potential of absorbent (Tuutijärvi et al.44). In this case, the further development of a remediation method for ICS-ENF nanofiber is necessary to overcome the phosphate and silicate negative influence on arsenic adsorption. Regeneration and column tests Regeneration and reusability could be considered as the most important indicators for a potential adsorbent. Generally, it is rather difficult to desorb the arsenate from an aqueous medium, and high concentration sodium hydroxide solution (i.e. 0.1 M) was desirable for stripping arsenic from the adsorbent8. However, in the present study, we employed only 0.003 M sodium hydroxide as the desorption solution, and meanwhile the reusability of ICS-ENF was investigated via ten sorption–desorption cycles simultaneously with Fe release monitoring throughout the recycles. As Fig. 5b shown, ICS-ENF still represented the powerful reusability performance with above 98% of As(V) removal efficiency even after ten successive cycles. No obvious change was found in the color, size, weight and shape of the ICS-ENF after 10 cycles of batch adsorption. Furthermore, it is worth to note that no leachable iron was detected during the whole cycling processes. However, a small decrease in the tensile modulus was observed after 10 cycles of batch adsorption, which might be attributed to the partially degradation of chitosan for long time immersion in water. More study should be carried out to further improve the mechanical strength and stability of the ICS-ENF in the future. Additionally, continuous flow column studies were further employed to examine the ability of ICS-ENF to remove the arsenic from water, which was obtained by pressuring the As(V) solution in an upward flow at a flow rate of 3.6 mL/min and by determining the concentration of arsenic ions at different time intervals in the effluent. The breakthrough curve for As(V) (Fig. S3a) indicates that no arsenic was found in the effluent up to about 300 bed volumes (BV) and even with a fast empty bed contact time (EBCT) of 1.4 min, the ICS-ENF demonstrated a high breakthrough BV of 805 for the treatment of 200 μg/L As(V) under the requirement of the arsenic MCL for drinking water at 10 μg/L. Moreover, by using 0.003 M NaOH stripping, our column regeneration test (Fig. S3b) shows maximum desorption could take place within 4 BV, and about 70 fold enrichment was attained to accomplish the column recycling. Therefore, the results indicate that 0.003 M sodium hydroxide solution could be effective for stripping arsenate from ICS-ENF; and additionally ICS-ENF owns an excellent durability, which can be extensively utilized in water treatment. Spectroscopic analysis The arsenic adsorption mechanism was first investigated by spectroscopic technique of FTIR spectroscopy. Figure S4 demonstrates the FTIR spectra of ICS-ENF before and after batch arsenic adsorption, respectively, where the characteristic absorption bands around at 3364 cm−1 (N–H and –OH stretching), 2876 cm−1 (C–H stretching), 1642 and 1595 cm−1 (N–H bending), 1383 cm−1 (–NH deformation), and 1083 cm−1 (C–O stretch) conform well to pure chitosan, one of the main components of ICS-ENF8454647. Compared with ICS-ENF alone, the FTIR spectra after arsenic adsorption indicated that the peaks at 3364, 1642, 1383 and 1083 cm−1 have weakened, and a new weak band, which is corresponding to As–O stretching vibration, appeared at 844 cm−1 48. This may result from the replacement of Fe bound −OH groups with −OAsO(OH)2 moieties14. All these observations indicate that confirmed the adsorption of As(V) on the sorbent, and –NH, –OH and C–O could make the dominant contributions for the adsorption of As(V) on ICS-ENF. In order to further investigate the mechanism of As(V) sorption onto ICS-ENF, binding energy shifts of carbon, nitrogen, oxygen, iron and arsenic were examined using XPS. XPS wide scan spectra of the virgin and arsenate loaded ICS-ENF are illustrated in Fig. S5. Three major peaks at binding energies of 286, 399 and 533 eV, designated for the C 1s, N 1s, and O 1s, respectively, were observed for the adsorbent of ICS-ENF. However, after arsenate adsorption, two new weak peaks at binding energy of about 44.8 eV for As 3d, and 1327.1 eV for As 2p3 appear (Fig. S6), which confirmed the As(V) adsorption onto the ICS-ENF. To have a better knowledge of the structural changes which could be involved in the adsorbent of ICS-ENF during the As(V) adsorption process, we conducted high resolution scan of C 1s, N 1s and Fe 2p XPS spectra (Fig. 6), and the binding energy as well as the relative contents of C 1s, N 1s and Fe 2p were analyzed (Table S2). Based on the Fig. 6 and Table S2, it can be seen that after the As(V) adsorption, the intensity of C–N, NH–C = O and Fe(III)tet increased, while that of C–OH and Fe(III)oct decreased. Therefore, the XPS analysis again suggests that –NH, –OH, C–O and Fe implantation should play important roles in the uptake of As(V), which is in accordance with the above mentioned results during kinetic and FTIR studies37. When Fe3+ was first dissolved in the chitosan solution, Fe-chitosan complex would formed49. And it was concluded that Fe3+ was usually coordinated with the functional groups of chitosan, i.e. –NH and –OH50. After electrospinning, the nanofibers were dried in air and crossliked by ammonia vapor, and the Fe3+ would be converted into iron oxide. When metal oxides were used as As(V) adsorbent, the metal–OH on the surface of the sorbent were formed due to protonation, followed by bonding of anionic As(V)145152. On the basis of all the above analyses, the mechanism of adsorptive removal of As(V) by ICS-ENF is proposed as shown in Fig. S7. Conclusions In summary, an environment-friendly adsorbent, iron doped chitosan nanofiber (ICS-ENF), was successfully synthesized by electrospinning for trace As(V) removal from water. The imagines analysis via XRD, FESEM and TEM coupled with EDX showed the electrospun nanofibers were amorphous, highly porous and fairly uniform. Under acid and weak basic conditions, ICS-ENF shows highly effective As(V) adsorption (more than 90%). Compared with CS-ENF, ICS-ENF demonstrated exceptional adsorption performance in terms of adsorption capacity at neutral pH. The kinetics study exhibited the adsorption was nearly reached equilibrium after 100 min and more than 87% of the total adsorption occurred within 50 min, which could be well fitted by the pseudo-second-order kinetics model. While the arsenic adsorption decreased with increasing solution ionic strength, the coexisting anions of Cl− and SO42− even up to 1.0 mM didn’t cause negative effect on the As(V) adsorption, whereas SiO32− and PO43− could significantly interfere with the sorption on ICS-ENF. The ICS-ENF has a high maximum adsorption capacity of up to 11.2 mg/g at neural pH, and Freundlich model is more suitable for describing the adsorption isotherm Additionally, the spectroscopic analysis implied that –NH, –OH and C–O could make the dominant contributions for the As(V) adsorption on ICS-ENF. Finally, the regeneration and column tests represent that ICS-ENF could be easily regenerated by 0.003 M NaOH solution, and the powerful reusability performance with above 98% of As(V) removal efficiency even after ten successive adsorption-desorption cycles indicated that ICS-ENF could be extensively utilized in arsenic containing water treatment. Experimental Materials All chemicals were used as received. Ammonium hydroxide (NH3·H2O), acetic acid (CH3COOH), sodium arsenate (Na3AsO4·12H2O), and ferric chloride (FeCl3·6H2O) of analytical grade were obtained from Sinopharm Chemical Reagent Co. Ltd. (Shanghai, China). Chitosan with average Mw of 150,000 was supplied by Aoxing Biotechnology Co. Ltd. (Zhejiang, China), and PEO particle with average Mw of 1000,000, was purchased from Changchun Dadi Co. Ltd. (Changchun, China). Preparation of adsorbents The chitosan (4% w/v) and PEO (4% w/v) solutions were separately prepared by dissolving in acetic acid (50% v/v). The chitosan/PEO blend solution for CS-ENF fabrication was obtained by mixing the two master solutions at 14:1 ratios, which was further adjusted for ICS-ENF synthesis with the addition of FeCl3 at the ratio of 3 wt% and kept stirring for 5 h prior to the electrospinning. The dosage of FeCl3 were determined through a preliminary study. In the preliminary experiments, the amount of FeCl3 ranged from 1 wt% to 5 wt%. The result showed that the ICS-ENF with 1 wt% FeCl3 doping exhibited a low As(V) adsorption capacity, while 5 wt% FeCl3 doping led to poor spinnability of the iron doped chitosan solution. Therefore, 3 wt% FeCl3 was chosen as the optimized dosage to fabricate the ICS-ENF. Nanofiber was fabricated using a simple electrospinning process described previously31. Briefly, the as-prepared polymer solution was transferred into a 20 mL syringe coupled with a needle tip (21G), and electrospun under the voltage, tip-collector distance and solution feeding rate of 16 kV, 15.5 cm and 0.9 mL/h, respectively. The fabricated nanofibers were expelled in an air dry oven at 50 °C for 6 h and then crosslinked by ammonia vapor for another 0.5 h. Finally, the CS-ENF and ICS-ENF were obtained after rinsed with deionized water and dried at 30 °C, which were used as adsorbents for arsenate adsorption. Characterization of the nanofibers The surface morphology of the nanofibers was obtained by a Field Emission Scanning Electron Microscopy (FESEM, Hitachi S4800, Japan). The transmission electron micrographs (TEM) and the selected area electron diffraction micrographs were taken with a Tecnai F20 transmission electron microscope (Phillips, USA) operating at 200 kV. Mechanical strength of the electrospun nanofibers was determined using a tensile machine (AGS-X, Shimadzu, Japan). X-ray diffraction (XRD) patterns were recorded with an XRD System model X’ Pert PRO (PANalytical, Netherlands) using a Ni filter, Cu Ka radiation (λ = 1.54060A) and angular variation of 570° (2θ). The functional groups on the surface of ICS-ENF were characterized by Fourier transform infrared spectroscopy (FTIR, Thermo NICOLET iS10, USA) measurements using transmission mode, with wavelengths in the range from 200 to 4000 cm−1. XPS (PHI Quantum 2000, USA) with X-ray source of Mg Ka was used to determine the chemical composition of the nanofiber adsorbent before and after arsenic uptake. For wide scan XPS spectra, an energy range from 0 to 1200 eV was used with pass energy of 80 eV and step size of 1.6 eV. The high resolution XPS scans were conducted according to the peak being examined with pass energy of 40 eV and step size of 0.125 eV. The XPS results were collected in binding energy forms and fitted using a nonlinear least squares curve fitting program. Meanwhile, the carbon 1s electron binding energy corresponding to graphitic carbon at 284.8 eV was used as reference for calibration purposes. The point of zero charge (pHpzc) of the ICS-ENF was determined via batch equilibration technique. NaNO3 solution with the concentration of 0.1 M was used as the electrolyte maintaining the constant ionic strength in all experiments which was adjusted to various pH values from 3.0 to 10.0 by diluted HCl or NaOH. After the 48-hour agitation, the final pH values (pHfinal) were measured and the pHpzc of the nanofiber adsorbent was accordingly yielded based on the plot of ΔpH (pHfinal–pHinitial) against pHinitial. Batch adsorption experiments All the batch adsorption experiments were performed with a fixed absorbent dosage of 0.2 g/L at 25 °C. Arsenate stock solution (1000 mg/L) was prepared by dissolving exact amount of Na3AsO4·12H2O into ultrapure water, which is further diluted for the desired concentration. After shaking for a predetermined time, the equilibrium arsenate solution, was filtered through 0.45 μm filter membranes, and then determined by ICP-MS (Agilent 7500cx, USA). In this case, the amount of As(V) adsorbed53 per unit mass of adsorbent (g), qe (mg/g), was obtained by the following equation: where C0 and Ce denote the initial and equilibrium concentration of As(V) (mg/L), respectively. VL is the volume of the adsorption solution (L), and m is the weight of dry adsorbents (g). To examine the effect of pH on the adsorption process, 8 mg of adsorbent was mixed with 40 mL As(V) solution at the initial pH values of 3.2–11.4 (adjusted by 0.1 M HCl and 0.1 M NaOH) for 48 hour agitation, and the final equilibrium As(V) concentration and pH values were accordingly analyzed. Kinetics studies coupled with the effect of ionic strength, which was adjusted via NaNO3 solution at the concentration ranging from 0 to 0.5 M, were conducted by adding 40 mg ICS-ENF into 200 mL arsenic solution (200 μg/L). The samples were withdrawn at appropriate time intervals and analyzed by the ICP-MS. The adsorption isotherm experiments were performed by using initial arsenic concentrations ranging from 0.1 to 3.1 mg/L. Additionally, four representative anions (Cl−, SO42−, SiO32− and PO43−) with concentration ranging from 0.1 to 1.0 mM were used to investigate the effect of competing anions on arsenate adsorption. Regeneration and column adsorption experiments The adsorption-desorption (regeneration) experiments were undertaken by mixing 10 mg of ICS-ENF with 50 mL As(V) solutions (200 μg/L). After 3 h of agitation, the adsorbent was extracted, washed and transferred to a new bottle. Then, 50 mL of the 0.003 M NaOH solution was added and shaken for another 3 h. The solution was filtered and the arsenic concentration was determined in the filtrate. Additionally, followed by the above mentioned regeneration protocols, ten cycles of adsorption-desorption experiment were carried out to evaluate the reusability of ICS-ENF for arsenic removal. Continuous flow column tests were conducted to examine the performance of arsenic removal by ICS-ENF for its potential applications. A glass tube with 0.9 cm inner diameter and 10 cm length packed with 0.7 g ICS-ENF was used to conduct the flow column experiment with an up-flow pattern. The flow rate was kept at 3.6 mL/min and the pH of the influent solution was 7.2. Elution test was conducted by 0.003 M NaOH and the concentration of arsenic and iron concentration were analyzed for the effluent solutions from the column. Additional Information How to cite this article: Min, L.-L. et al. Functionalized chitosan electrospun nanofiber for effective removal of trace arsenate from water. Sci. Rep. 6, 32480; doi: 10.1038/srep32480 (2016). Supplementary Material Supplementary Information This work was partially funded by the National Natural Science Foundation of China (No. 51578525 and No. 5153000136), the Hundred Talents Program of Chinese Academy of Sciences, and the Science and Technology Innovation and Collaboration Team Project of the Chinese Academy of Sciences. Author Contributions L.-L.M., Y.-M.Z. and L.-M.Y. conceived the idea and designed the experiments; L.-L.M. performed the major experiments and wrote the manuscript; L.-B.Z., Q.L. and Z.-H.Y. helped in characterization and analysis; Y.-M.Z. contributed to the planning and coordination of the project; Y.-M.Z. and L.-M.Y. performed critical revision of the article. Figure 1 (a) TEM image, (b) line scan, and (c) EDX elemental mappings of C, Fe, O, and N on the surface of ICS-ENF. Figure 2 (a) Effect of pH on As(V) adsorption by ICS-ENF, (b) pHpzc plot of ICS-ENF, and (c) iron release during As(V) adsorption (C0 = 200 μg/L, adsorbent dose = 0.2 g/L, temperature = 25 °C, contact time = 48 h). Figure 3 (a) As(V) adsorption kinetics on ICS-ENF and CS-ENF, (b) Ionic strength effect on As(V) adsorption on ICS-ENF (Adsorbent dose = 0.2 g/L, temperature = 25 °C, final pH = 7.1–7.2), and (c) Intra-particle diffusion model for As(V) adsorption on ICS-ENF. Figure 4 (a) As(V) adsorption isotherms on ICS-ENF and CS-ENF, (b) Equilibrium As(V) concentration vs. initial As(V) concentrations of ICS-ENF (Final pH = 7.1–7.3, adsorbent dose = 0.2 g/L, temperature = 25 °C, contact time = 48 h). Figure 5 (a) Effect of coexistence ions on As(V) removal by ICS-ENF (C0 = 200 μg/L (0.003 mM), adsorbent dose = 0.2 g/L, temperature = 25 °C, pH = 7.2, contact time = 48 h. (b) Regeneration of ICS-ENF over ten adsorption-desorption cycles with 0.003 M NaOH (C0 = 200 μg/L, adsorbent dose = 0.2 g/L, temperature = 25 °C). Figure 6 High resolution scan of C 1s XPS spectra of (a) fresh ICS-ENF and (b) As(V) loaded ICS-ENF, N 1s XPS spectra of (c) fresh ICS-ENF and (d) As(V) loaded ICS-ENF; Fe 2p XPS spectra of (e) fresh ICS-ENF and (f) As(V) loaded ICS-ENF (The condition for sample preparation of As(V) loaded ICS-ENF is as below: C0 = 10 mg/L, adsorbent dose = 0.2 g/L, temperature = 25 °C, contact time = 48 h). Table 1 Parameters of pseudo-first-order, pseudo-second-order & intro-particle diffusion model of adsorption kinetics of arsenic on ICS-ENF. [NaNO3] Pseudo-first-order Pseudo-second-order Particle diffusion model qe (mg/g) k1 (min−1) R2 qe (mg/g) k2 (g/(mg min)) R2 Kp (mg/(g min0.5)) R2 0 mM 0.860 0.047 0.992 1.026 0.052 0.994 0.111 0.992 0.1 mM 0.706 0.022 0.968 0.806 0.035 0.986 0.063 0.992 0.5 mM 0.507 0.013 0.982 0.616 0.023 0.993 0.034 0.991 Table 2 Maximum adsorption capacity (mg/g) of As(V) on chitosan related adsorbents reported in literature. Adsorbent Max [As]0 (mg/L) pH q (mg/g) Ref. CS* 0.5 5.0 0.5 54 CS/Clay/Magnetite 336 5.0 6.5 35 TiO2/CS beads 10 7.0 4.9 55 Magnetite/Graphene 7 7.0 5.8 34 Zero valent iron/CS fiber 25 6.0 2.3 17 CS-ENF 0.7 7.2 0.5 This work ICS-ENF 1.8 7.2 11.2 This work *Chitosan. ==== Refs Jiang W. , Chen X. B. , Niu Y. J. & Pan B. C. Spherical polystyrene-supported nano-Fe3O4 of high capacity and low-field separation for arsenate removal from water , J. Hazard. Mater. 243 , 319 –325 (2012 ).23131498 Mondal P. , Majumder C. B. & Mohanty B. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3153610.1038/srep31536ArticleKnowledge discovery from high-frequency stream nitrate concentrations: hydrology and biology contributions Aubert Alice H. a1*Thrun Michael C. 2Breuer Lutz 13Ultsch Alfred 21 Institute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig University Giessen, Heinrich-Buff-Ring 26, D-35392 Giessen, Germany2 Databionics, Mathematics and Computer Science, Philipps University Marburg, Hans-Meerwein-Strasse 6, D-35032 Marburg, Germany3 Centre for International Development and Environmental Research (ZEU), Justus Liebig University Giessen Goethestrasse 58, D-35390 Giessen, Germany.a alice.aubert@eawag.ch* Present address: Eawag - Swiss Federal Institute of Aquatic Science and Technology, Ueberlandstrasse 133, 8600 Duebendorf, Switzerland 30 08 2016 2016 6 3153623 02 2016 21 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/High-frequency, in-situ monitoring provides large environmental datasets. These datasets will likely bring new insights in landscape functioning and process scale understanding. However, tailoring data analysis methods is necessary. Here, we detach our analysis from the usual temporal analysis performed in hydrology to determine if it is possible to infer general rules regarding hydrochemistry from available large datasets. We combined a 2-year in-stream nitrate concentration time series (time resolution of 15 min) with concurrent hydrological, meteorological and soil moisture data. We removed the low-frequency variations through low-pass filtering, which suppressed seasonality. We then analyzed the high-frequency variability component using Pareto Density Estimation, which to our knowledge has not been applied to hydrology. The resulting distribution of nitrate concentrations revealed three normally distributed modes: low, medium and high. Studying the environmental conditions for each mode revealed the main control of nitrate concentration: the saturation state of the riparian zone. We found low nitrate concentrations under conditions of hydrological connectivity and dominant denitrifying biological processes, and we found high nitrate concentrations under hydrological recession conditions and dominant nitrifying biological processes. These results generalize our understanding of hydro-biogeochemical nitrate flux controls and bring useful information to the development of nitrogen process-based models at the landscape scale. ==== Body Human activities modify the global nitrogen cycle, particularly through farming1. These practices have unintended consequences; for example, nitrate lost from terrestrial runoff to streams and estuaries can impact aquatic life2. Thus, studying nitrate export, i.e., nitrate concentrations at the outlet of a watershed, is a major concern. Existing labor-intensive monitoring strategies that have been in place for several decades have recently been complemented by the development of in-situ technologies that allow for high-frequency (sub-hourly) sampling. High-frequency monitoring has been shown to be a beneficial addition to the previous lower frequency monitoring schemes3. A decade ago, high-frequency monitoring was expected to bring new insights into watersheds functioning4, and indeed, it has helped5 identify sources and transport pathways of nutrients6 and quantify processes and metabolisms of coupled nutrients7 across multiple time scales8. This has allowed researchers to disentangle the effects of multiple processes9. Now, the availability of several year-long high-frequency datasets invites the application of data mining techniques10. Catchments are dynamic systems, and present observations rely on previous hydrological states. In water sciences, data are mostly analyzed with respect to time. Analyses focus on either long-term, seasonal, or short-term variations, including fluctuations resulting from flood events or diurnal cycles. Temporal data structure is regularly analyzed in the time and frequency domain by time series decomposition1112 and spectral analysis8131415, respectively. These methods are used to identify cycles and variability in the main transfer processes. Time-variant process modelling also allows us to explain the old water paradox161718. In this study, we look at nitrate concentration data differently by neglecting its temporal component in the data analysis. This approach is now possible and worth considering given the availability of datasets large enough to mine and expand our general knowledge. Data structures have already been studied independently of time, e.g., plotting a variable of interest against another variable. For example, correlating observed nitrate concentration with a simulated index based on the watershed wetness state19 refined the flushing hypothesis, and relating production of nitrogen gaseous species to the percent of the soil’s pore volume filled by water20 defined a conceptual model of nitrogen oxide emissions from soil. These non-temporal data structure analyses have brought new insights in watershed functioning and the nitrogen cycle. Non-temporal data structure analysis was also used to compare high- and low-frequency monitoring data3. There, probability density functions (PDF, a function describing the likelihood a variable can take a given value) were estimated using kernel density estimators. However, as in any PDF estimation method, one of the critical parameters, the kernel width, was left undetermined. If too large of a kernel width is chosen, important structures may be undetected. Likewise, if the kernel width is too small, random fluctuations are overemphasized. To avoid an unclear choice in kernel width, we used the Pareto Density Estimation (PDE), in which kernel width has proved to be particularly suitable for detecting modes in continuous data. PDE is particularly suitable for the discovery of mixtures of Gaussians21, but in the case of skewed distributions, transforming the data is required beforehand. In other scientific domains, thorough analysis of data structure focused primarily on the estimation of the PDF using the Pareto Density Estimation (PDE) of a variable of interest2122. The objective of this study is to generalize–or cast doubt on–the current understanding of nitrate fluxes at the catchment scale. At this point, in-stream nitrate concentrations in an agricultural catchment are mainly described in relation to time. Seasonal and event-related variations in nitrogen sources and transport processes throughout the year or during a wetting-drying cycle confer seasonal and short-term fluctuations to nitrate concentrations. To avoid the tendency of reinforcing the understanding of already described relationships, we included all measured variables from the catchment23. This naïve look at the data is common in data mining. We focused on the shape of the PDFs from high-frequency nitrate concentrations monitored in a 3.7-km2 mixed-land use catchment. Environmental variables (discharge, groundwater depth, soil moisture, soil temperature, stream temperature, stream conductivity, rainfall, air temperature and solar radiation) were considered as potential explanatory variables and were used in the process of knowledge discovery to identify the drivers of nitrate fluctuations in the catchment. Particularly, we were interested in whether these drivers are the same for low and high nitrate concentrations, as this result may assist in refining mechanistic models of nitrate fluxes. Results The large dataset The available dataset contained in total 32,196 data points for each of the 14 variables (in total, 4% missing data), making it suitable for data mining (pp. 243 of 24). The raw time series for each year are presented in Fig. 1. For technical reasons, no nitrate data were available during winter, so the actual time span of nitrate monitoring was 05 March 2013 12:45 to 24 September 2013 12:30 and 27 April 2014 00:00 to 23 October 13:15. Data were analyzed as a whole, without differentiating between the hydrological years. To do this, we filtered out the seasonal variation (see methods). Hereafter, when referring to sub-daily high-frequency fluctuations (after seasonal variation removal) a tilde (~) superscript will be added to the variable names. High-frequency nitrate data: a composite of the three modes The PDF of the empirical values of nitrate~ concentration from the Vollnkirchener Bach watershed was modelled using PDE, resulting in three distinctive modes (see methods). The estimation of the empirical distribution (black curve) was modelled (red curve) using a Gaussian mixture model (GMM) composed of three Gaussians (blue curves) (Fig. 2). The goodness of fit was visualized with a quantile-quantile plot (Supplementary Fig. S1) and verified statistically with the Xi-Quadrat test (p = 1e-05) and Kolmogorov–Smirnov test (p < 1e-10). The central Gaussian represented typical nitrate~ concentrations, while the left and right Gaussians described the lower and higher concentrations of nitrate~, respectively. Bayes Theorem was used to calculate the class posterior probabilities. This calculation classified nitrate~ into the three classes: low (5% of the data), typical (89% of the data), and high nitrate~ concentrations (6% of the data). Modes characterized by environmental conditions We compared the concurrently measured environmental variables for each mode of nitrate~. Lower nitrate~ was characterized by more superficial groundwater depth (GW32~), higher soil moisture (Smoist24~) and, on average, lower solar radiation (Sol71~) (Fig. 3, Table 1). High nitrate~ was characterized by deeper groundwater depth (GW32~), moderate soil moisture (Smoist24~) and, on average, higher solar radiation (Sol71~) than the low nitrate~ Gaussian curves. The typical nitrate~ class was quite similar to the high nitrate~ class, but the high nitrate~ was associated with more humid soils. Discussion Variables driving rapid nitrate fluctuations The three depths of groundwater (GW3~, GW25~ and GW32~) represent the typical range in the spatial variability of the groundwater table conditions. They are located in the mid-reach lowland meadow (GW3), the cultivated land on the hillslope (GW25), and in a riparian meadow where a temporary tributary joins the stream (GW32)25. The riparian meadow groundwater depth was always selected as a driver of nitrate~. This result supports the importance of near-stream zones that are often reported as having a major impact on stream water quality2627. GW32~ shows little seasonal fluctuation; most of the time, this groundwater depth remains high, which reflects connectivity to the stream network. This location is also more reactive than the other piezometers (Fig. 1). Conversely, the hillslope and lowland meadow groundwater depths are less reactive and fluctuate seasonally with a high amplitude. These locations have little influence on nitrate~ concentrations. The short-term nitrate fluctuations support the assumption that the constantly connected landscape elements are a major determinant of the high-frequency variability of solutes. Landscape elements for which connectivity exhibits low frequency fluctuation of a high amplitude are not predominant for stream water chemistry at the fine time scale2829. Soil moisture (Smoist24~) was determined to be another major driver of nitrate~ concentrations in the high nitrate mode, supporting the results of previous studies3031. Discharge also impacted nitrate~. Last, electric conductivity (cond47~) generally follows nitrate~ concentrations: when nitrate~ is low, conductivity (which also accounts for nitrate salts) is low. Generally, air-, soil- and stream- temperatures~ are not meaningful to explain the high frequency fluctuations in water chemistry. Air, soil and stream temperatures showed primarily low-frequency fluctuations, aligning with variables such as groundwater depth in the agricultural hillslope, and the temperature data formed almost perfect Gaussians. Perfect Gaussians characterize variables with a clear combination of sinusoidal patterns, for both seasonal and diurnal time scales. Rainfall intensity (rain~) was not meaningful to explain the high frequency fluctuations in nitrate~ either. The lack of relation between rainfall and nitrate~ supports the findings of a previous study32 performed in the catchment using isotopic signatures. In the isotopic study, stream water was found to be more similar to groundwater than to rain water or soil water, illustrating the “old water paradox”1633 once more, where old water flows during storm events. Rain and high celerity (the speed at which the perturbation wave is transmitted) lead to a reactive stream water level; however, it does not imply that rainwater is transported directly to the stream, where it could affect nitrate. Stream flow velocity, defining chemical transport, is, by definition, lower than celerity34. Combined effect of hydrology and biology on nitrate~ The low nitrate~ mode (left curve, Fig. 2) is driven by groundwater depth close to the surface and high soil moisture (Fig. 3), indicating the subsurface is saturated and hydrologically connected. Moreover, under such wet conditions, denitrification might be the most active biological process, adding to the importance of the hydrological state. We conclude that the low nitrate~ mode is defined by hydrological connectivity and a dominance of the denitrifying biological activity, that is, by a saturated catchment. The high nitrate~ mode (right curve, Fig. 2) is driven by high solar radiation and deep groundwater, but soils are still moist. High solar radiation could suggest high evapotranspiration, given that moist soil indicates water is sufficiently available to plants. This behavior is typical for drying conditions. The drying phase has been linked to biological changes in the microbial community of soil aggregates35. Microbial diversity should increase with drying. When nutrient transport is reduced because of limited diffusion and the gaseous phase in the pores becomes important, anaerobic and aerobic communities will likely coexist. Thus, the denitrifying community is no longer the only one active; nitrification can occur. This balance between nitrification and denitrification could lead to the production and build-up of nitrate in the soil. This nitrate can then be mobilized during low intensity rain events. We interpret that high levels of nitrate~ are defined by hydrological recession and biologically active soils, where nitrification dominates. The tipping-point, threshold or “hot moment”26, when biological drivers over-take hydrological drivers, is still unclear and needs to be determined in future work. The shift from denitrification to nitrification dominance also needs further data-based research. These interpretations align with models based on hydrological storage, distinguishing celerity and velocity17363738; however, these hydrological models were developed for conservative tracers, such as chloride. Our work highlights the need to add biological processes to hydrological models to allow for the production and consumption of chemicals, such as nitrate, known to strongly affect our environment in some regions. A method for initial data exploration Our goal is to draw attention to the benefits of thorough analyses of large environmental datasets. In this case study, we show that new knowledge can be mined from empirical PDEs, thus we recommend data mining as a first step to understanding the driving forces in a catchment because it can provide a simplified, non-temporal view of solute export. This approach provides a glimpse of the catchment’s behavior, which is the compilation of many processes, by making use of low-flow data as well as storm-flow data27. By considering the variable of interest, in this case nitrate~, as non-temporal, the system was simplified and data structuration was observed21. Data mining revealed a differentiation in nitrate~ modes and differences in underlying conditions. The roles of hydrology and soil microbiology in controlling nitrate~ were highlighted. Low nitrate~ occurred under hydrological connectivity and microbial denitrification. High nitrate~ occurred under hydrological recession and nitrifying conditions. The highly fluctuating component of the nitrate concentrations seems to be influenced by the saturation state of the catchment, although the seasonal component, which is known to be driven by saturation state, was removed. We are confident that other datasets analyzed with the described methods herein will produce strong advances in the interpretation of catchment hydro-biogeochemical processes. In future high frequency monitoring work, it will be important to monitor variables that allow the identification of the various biological processes occurring in the soil and in-stream, as the latter are reported to dampen terrestrial signals39. The difficulty will be to find variables that can be easily and cost-effectively measured at high temporal resolution. Potential biological variables include in-stream measurements of biological oxygen demand (BOD) and soil redox potential. We showed that connectivity plays an important role in nitrate concentrations; therefore, the identification of contributing (or connected) areas as well as the spatial identification of controlling variables would shed further light on solute export40. In the future, the development of networks of sensors41 or the use of high-temporal sensing distributed throughout a catchment42 could help to overcome these limitations. Methods Nitrate concentration data were collected for two years in the Vollnkirchener Bach watershed, which is nested in the Critical Zone Observatory of the Schwingbachtal, in central Germany (references and data available at http://fb09-pasig.umwelt.uni-giessen.de:8081/). Technical issues and data checking reduced the time span to two growing seasons (05 March 2013 to 24 September 2013, n = 15,475 measurements and 27 April 2014 to 23 October 2014 n = 16,721 measurements, in total n = 32,196 measurements). Land-use is dominated by agricultural land and forests, covering 44 and 48% of the catchment, respectively. An in-situ hyperspectral UV-spectrometer (ProPS, Trios, Rastede, Germany, wavelength range 200–360 nm, path length 5 mm, solar panel supplied) measured absorption spectra every 15 min after a 5 s air blast to prevent the optics from biofouling. Wavelengths of 200–220 nm allowed the calculation of nitrate concentration, using a calibration adapted to the stream water’s baseline chemical composition. More detailed information on the calibration and the nitrate data checking is reported in ref. 43. Other variables were monitored at high-frequency and used to explain the variations in nitrate, as they depicted the catchment state. Discharge (q, l s−1) and water temperature (Wt, °C) were measured at two gauging stations q13/Wt13 at the outlet and q18/Wt18 upstream and were measured every 5 min by pressure transducers (Diver DCX, Schlumberger Water Services, ON, Canada). Groundwater depth (GW, m) at three wells (GW25 on the hillslope, GW3 in lowland and GW32 in the riparian zone) were measured every 10 min by pressure transducers. Meteorology, i.e., air temperature (At47, °C), solar radiation (Sol71, W m2) and rainfall intensity (rain, mm), was captured every 5 min at a climate station 4 km from the outlet (Campbell Scientific Inc., CR1000 data logger, Loughborough, UK). Soil moisture (Smoist24, m3 m−3) and soil temperature (St24, °C) were measured hourly at 0.1 m depth, in the riparian zone, by electromagnetic induction (5TE sensors, EM50 data logger, Decagon, Labcell LTD, Alton, UK) beginning on 14 June 2013. Some of these variables are expected to directly influence nitrate in-stream concentrations, such as groundwater depths or rainfall intensity. Others are considered as proxies for biological activity, such as temperature and soil moisture, and evapotranspiration, the variable solar radiation43. All time series were detrended to create a joint data set for both years. This process allowed the analysis of rapid fluctuations in the variables and considered both growing seasons at once. A two-component model with the variable-baseline subtracted from the raw time series was applied to obtain the high-frequency component of the variables. The variable-baseline was calculated using a low pass filter as a Fourier Transformation; the filter was set to 50 days. Thus, the high-frequency component is composed of fluctuations below the monthly time scale, down to 15 min. This residual time series is interpreted as a rapid and high-temporal fluctuation and is marked with a tilde (~) throughout the manuscript. Discharges and rainfall, which were typical of a reactive catchment, presented a seasonal baseline set to zero. We then focused on our variable of interest: nitrate. First, we modelled the nitrate with three distinctive modes using the Adapt Gauss toolbox22 as shown in Fig. 2. The Adapt Gauss17 toolbox in R package allows for the modelling and verification of possible multimodal distributions as a mixture of Gaussian components. This approach is called Gaussian Mixture Modelling (GMM). Verification of the model was performed visually using a QQplot (Fig. S1A) and statistically with a Xi-Quadrat test (p < 1e-05) and a Kolmogorov–Smirnov test (p < 1e-10). In other words, GMM was constructed to fit the nitrate’s empirical PDF. The number of modes was calculated as the minimum of the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC)44. AIC and BIC were computed for the GMM with one to ten modes using an Expectation-Maximization (EM) optimization in the R package mclust45 (Fig. S1B). AIC and BIC were both in agreement. EM fitting, using a user-defined starting point in the Adapt Gauss toolbox22, resulted in better values for AIC and BIC. The GMM was supported by goodness-of-fit checks. These checks resulted in three different Gaussians for high-frequency nitrate~ (Fig. S1B). Bayes Theorem was used to calculate the class posterior probabilities. The data were then mined to address if there were different drivers for the high and low nitrate~ concentrations. All data points for the potentially related variables were grouped according to the synchronous nitrate mode into the same three distributions: low, typical and high with respect to nitrate. We compared the three distributions for each variable visually using the PDE21 (Supplementary Information, Fig. S2), using boxplots resulting from the PDE (Fig. 3), and statistically using a Bonferroni corrected two-sample t-test for unequal sample sizes and unequal variances (Table 1). We only considered the variables that showed visually and statistically significant (p-values > 0.01) differences between modes in our interpretation. Additional Information How to cite this article: Aubert, A. H. et al. Knowledge discovery from high-frequency stream nitrate concentrations: hydrology and biology contributions. Sci. Rep. 6, 31536; doi: 10.1038/srep31536 (2016). Supplementary Material Supplementary Information Authors warmly thank Ina Plesca, Tobias Houska, Nicole Werstein for their field work (i.e., data collection) and data checking. Author Contributions A.H.A. and L.B. developed the broad goals of this study. M.C.T. and A.U. completed the computational analyses, supporting the methodological component. A.H.A. and L.B. interpreted the results. A.H.A., M.C.T., L.B. and A.U. wrote the paper. Figure 1 Times series of data, including nitrate, groundwater depth (GW) (lowland GW3 (black dotted curve), hillslope GW25 (red dashed), and riparian zone GW32 (green solid)), discharges (at the outlet q13 (black solid curve) and up-stream q18 (red dashed)), water temperature (Wt) (at the outlet (black solidcurve) and up-stream (red dashed)), soil temperature (St24), air temperature (At47), soil moisture (Smoist24), solar radiation (Sol71) and precipitation (rain) for 2013 (a) and 2014 (b). Figure 2 Component Gaussian Mixture Model (GMM) (blue lines), superposition of the Gaussians (GMM) (red line), and the PDF describing sub-daily nitrate~ in-stream concentrations (black line). The three modes (blue lines) of the GMM describe low (left, mean = −0.59, SD = 0.23), typical (centered, mean = 0.0053, SD = 0.21) and high (right, mean = 0.46, SD = 0.26) nitrate~ concentrations. Prior to data analysis nitrate concentrations were split by applying a two-component model, which describes seasonal and sub-daily fluctuations. Figure 3 Boxplots of each nitrate~ concentration mode for the following environmental variables (a) solar radiation (Sol71~), (b) groundwater head in the riparian zone (GW32~), (c) conductivity (Con47~), (d) soil moisture (Smoist24~), (e) discharge (q18~) and (f) rainfall intensity (rain~). The white dot shows the arithmetic mean that was statistically tested using the t-test (Table 1). Original PDE curves for all variables are presented in the Supplementary Information (Fig. S2). Table 1 The p-values of the differences between environmental conditions corresponding to each nitrate~ mode (low-typical, low-high, typical-high) are calculated by the Bonferroni corrected two-sample t-test with unequal variances, where “n.s.” indicates a non-significant result. Variable Low-typical Low-high Typical-high GW3~ n.s. 5.7e-10 2.9e-10 GW32~ 1.9e-137 2.8e-57 n.s. Wt13~ n.s. 3.4e-09 n.s. Sol71~ 5.1e-111 2.5e-81 n.s. Con47~ 1.3e-205 6e-198 n.s. Smoist24~ 3.5e-220 1.2e-125 1.5e-15 q13~ n.s. 2.3e-31 3.2e-59 q18~ n.s. 9.6e-40 6.9e-69 rain~ n.s. n.s. n.s. Only the variables with significant p-values and visual agreement using the class-wise Pareto Density Estimation are presented. Groundwater depth on the hillslope (GW25~) and water temperature at the upper gauge (Wt18~) are thus not presented. ==== Refs Fowler D. et al. The global nitrogen cycle in the twenty-first century . Phil. Trans. R. Soc. B 368 , 20130164 , doi: 10.1098/rstb.2013.0164 (2013 ).23713126 Vitousek P. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3246610.1038/srep32466ArticleBroadband terahertz metamaterial absorber based on sectional asymmetric structures Gong Cheng 1Zhan Mingzhou 2Yang Jing 1Wang Zhigang 2Liu Haitao 1Zhao Yuejin 3Liu Weiwei a11 Institute of Modern Optics, Nankai University, Key Laboratory of Optical Information Science and Technology, Ministry of Education, Tianjin 300071, China2 School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China3 School of Optoelectronics, Beijing Institute of Technology, Beijing, 100081, Chinaa liuweiwei@nankai.edu.cn30 08 2016 2016 6 3246605 05 2016 09 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/We suggest and demonstrate the concept and design of sectional asymmetric structures which can manipulate the metamaterial absorber’s working bandwidth with maintaining the other inherent advantages. As an example, a broadband terahertz perfect absorber is designed to confirm its effectiveness. The absorber’s each cell integrates four sectional asymmetric rings, and the entire structure composed of Au and Si3N4 is only 1.9 μm thick. The simulation results show the bandwidth with absorptivity being larger than 90% is extended by about 2.8 times comparing with the conventional square ring absorber. The composable small cell, ultra-thin, and broadband absorption with polarization and incident angle insensitivity will make the absorber suitable for the applications of focal plane array terahertz imaging. ==== Body In 2011, Tao et al. from Boston University proposed a metamaterial absorbing enhanced optical-readout bimaterial cantilever pixels for Microwave and Terahertz (THz) wave imaging1. Since then, the bimaterial cantilever focal plane array (FPA) imaging sensor integrated with metamaterial absorber has gained increased attention owing to its many distinctive properties2345. In 2012, Alves et al. reported a micro-electro-mechanical systems (MEMS) bimaterial THz sensor operating at 3.8 THz. Its pixels integrated metamaterial absorber and the measurement showed that the fabricated absorber has nearly 90% absorption at 3.8 THz23. In 2013 and 2014, they improved their design and the absorption achieved near 100% at 3.8 THz and the responsivity is around 1.2 deg/μW45. In 2015, Ma et al. demonstrated an infrared bimaterial cantilever focal plane array integrated with metamaterial absorber to enhance the infrared imaging performance6. The metamaterial absorbers provide unprecedented ability to absorb energy of electromagnetic waves. The absorbed energy heats bimaterial cantilever to deform its optical-readout structure. To increase the sensitivity and reduce the response time of the cantilever sensor, relatively thin absorber which is compatible with MEMS-based bimaterial fabrication process is required3. To improve the imaging resolution, the sensor’s unit cell should be small enough4. To enhancing dynamic range of the deformable cantilever sensor, the broadband absorption with polarization insensitivity and incident angle insensitivity is important. However, it is a great challenge to simultaneously meet all the aforementioned properties (ultra-thin, small cell, and broadband), especially in the THz frequency range. Since Padilla et al demonstrated the metamaterial absorber in 200878, many groups began to study high performance broadband THz metamaterial absorbers9101112131415161718192021222324. In general, there are several methods are widely used for extending the bandwidth. The first is combing multiple metamaterial structures (or cells) with approximate resonance frequencies into a large cell91011. The second is nesting multiple metamaterial structures (or cells) into a new cell121314. The third is stacking multiple structures into a new multilayer cell151617181920. The fourth is based on doped silicon grating21222324. However, the first method will make the absorber’s unit cell too large. The second, third and fourth methods are constrained by the structures’ spatial arrangement, fabrication process, or thickness. To overcome the limitations of prior works, we suggest the concept of sectional asymmetric metamaterial structures which can manipulate specific device’s working bandwidth with maintaining the inherent advantages of the device. In the following a broadband THz absorber based on the structures will be demonstrate to confirm this idea. The absorber integrates four sectional resonators into a small cell with inheriting the complete resonator’s advantages of polarization insensitivity and incident angle insensitivity, while the bandwidth with absorptivity being larger than 90% is extended to about 2.8 times. Its entire structure which is compatible with MEMS-based fabrication is only 1.9 μm thick. The small cell, ultra-thin, and broadband absorption will make the absorber suitable for the applications of optical-readout bimaterial cantilever focal plane array imaging sensor45, or some electrical-readout imaging sensors such as microbolometer sensor252627 and pyroelectric sensor28. Principle and Design The basic idea of sectional asymmetric structures can be explained in such a simple way that multiple sectional structures in one cell result in coupling of multiple resonant frequencies. It will extend the bandwidth effectively by combing the frequency responses. As an example, Fig. 1 describes the design process of a sectional asymmetric cell. First of all, choosing one complete metamaterial structure as basic structure as is shown in Fig. 1(a). And then, dividing the symmetrical structure into sections and varying the characteristic size of each section as shown in Fig. 1(b,c). Finally, compose these asymmetric sections into a new unit cell and the cell is called sectional asymmetric cell which is shown in Fig. 1(d). Next, we proposed a broadband THz absorber based on the above example to verify its effectiveness. The basic structure is a simple square ring resonator which has advantages of polarization insensitivity and incident incidence angle insensitivity12. Figure 2(a) describes one cell of the absorber. Figure 2(c) shows a 3 × 3 cells’ array. The cell includes four quarter sectional square rings: Ring 1, Ring 2, Ring 3, and Ring 4, and these rings form an asymmetric ring structure. The outer side length of four complete square rings are P1 = 19.4 μm, P2 = 19 μm, P3 = 18.4 μm, and P4 = 18 μm, respectively. The gaps a, b, c, and d between the sectional rings are 2.2 μm and the width of the sectional ring is w = 3.8 μm. The period of one metamaterial cell is 22 μm. The absorber is made of Au and Si3N4 which are compatible with MEMS-based fabrication. It comprises three layers: the top layer is an array of sectional asymmetric Au resonators (0.1 μm thick); the middle layer is Si3N4 dielectric film (t = 1.7 μm thick); the bottom layer is Au ground (0.1 μm thick). The thermal, mechanical, and optical properties of Au and Si3N4 make the absorber suitable for applications of bimaterial cantilever focal plane array optical readout imaging29. The physical concepts and explanation of the bandwidth broadening are as follows: 1) To realize perfect absorption the impedance of the absorber should be matched to that of free space, for example: μ = ε then Z = (μ/ε) 1/2 = 1, which ε stands for the normalized electric permittivity, μ is the normalized magnetic permeability, and Z represents the normalized free space impedance. The sectional square ring (Au bracket) is an example of electric ring resonator (ERR) and couples strongly to uniform electric fields, but negligibly to a magnetic field. By adding a ground plane, the magnetic component of the incident electromagnetic wave induces a current in the sections of the ERR that are parallel to the direction of the E-filed. The electric and magnetic response can then be tuned independently. The ERR determines the electric response while the dielectric type and thickness between the ERR and the ground plane determines the magnetic response. 2) In this design, the resonant frequency of the absorption peak is mainly determined by the outer side length P of basic square rings. Therefore, we integrate four sectional square rings with different size (P1–P4) to support multiple resonant modes closely positioned together in the absorption spectrum. By tuning the thickness of the dielectric film, the sectional asymmetric structure can be impedance-matched to free space at each resonant frequency and absorption broadening is achieved. To provide a further interpretation, the Transmission line model of the sectional asymmetric metamaterial cell is described in Fig. 2(b). R stands for electromagnetic loss of the Si3N4 dielectric film. The four sectional square rings are equivalent to four parallel RLC circuit. R1, R2, R3, R4 represent ohm resistance of the four Au sectional rings. L1, L2, L3, L4 stand for equivalent inductance and C1, C2, C3, C4 are equivalent capacitance of the four sectional rings, respectively. According to the RLC circuit model, the resistance will not affect the resonance frequency, so we omitted it for simplicity. The inductance and capacitance can approximately describe the resonance of sectional asymmetric structures. The inductance of each sectional square ring can approximately be given by Li ~ (t/w) · Pi, where t is thickness of the Si3N4 dielectric film, w is the width of the sectional ring, Pi is the outer side length of the basic square ring. The capacitance can be expressed by Ci ~ (Pi · w)/t. Then the resonance frequency of the specific sectional ring is given by3031: Here i represent the sectional ring resonators. The Equation 1 demonstrates that the resonance frequency f is an approximate linear function of 1/Pi. Therefore, four sectional square rings will correspond to four resonance frequencies. The bandwidth of the absorber will be broadened by optimizing and adjusting the four outer side lengths P1, P2, P3, and P4. Results and Discussions The proposed absorber can be regarded as an effective media and characterized by a complex electric permittivity ε and complex magnetic permeability μ. The resonance structures couple strongly to the electric or magnetic fields and match the impedance Z = (μ/ε)1/2 to free space to minimize the reflectance. The absorber’s reflectance and transmission can be acquired by simulating the complex frequency dependent S parameters, S11 and S217. Then, the absorptivity A is calculated by where R = |S11|2 and T = |S21|2 are the reflectance and transmission, respectively. In our design the transmission T is zero because of the Au ground. Therefore, the absorptivity can be given by A = 1−R. We modeled the sectional asymmetric structures and simulated the electromagnetic characteristics by the commercial 3D electromagnetic simulator CST Studio Suite 2012. The thickness of its Si3N4 dielectric film is 1.7 μm and the dielectric constant is 8. The material of the sectional ring is Au with an electric conductivity 4.6 × 107 s/m and the thickness of the ring is 0.1 μm. The unit cell boundary condition with Floquet-port was used to simulate the absorption spectra, because the Floquet mode can be applied to any periodical array whether mirrored or rotated. The absorptivity curve of sectional asymmetric absorber is shown in Fig. 3(a) and there are four absorption peaks A1 = 99.2%, A2 = 96.4%, A3 = 99.3%, and A4 = 81.3% corresponding to four resonance frequencies 4.7 THz, 4.82 THz, 4.96 THz, and 5.13 THz, respectively. The bandwidth with absorptivity being larger than 90% is about 364 GHz. Figure 3(b) is the resonance current distributions in one cell at different absorption peaks. It shows that the sectional square ring1 primarily contributes to absorption peak A1, the ring2 contributes to absorption peak A2, the contributions of ring3 and ring4 corresponding to absorption peak A3 and A4, respectively. Moreover, we provide the absorption spectrum in the situation of only having isolated Au bracket (quarter sectional ring) in Fig. 3(a). The four absorption spectra are all narrowband and the absorption peaks are located at 4.706 THz, 4.784 THz, 5.014 THz, and 5.222 THz respectively. It’s worth mentioning that the maximum absorptivity of the isolated Au bracket absorber is only about 90% and lower than the counterpart (about 99%) of their combination. The results demonstrate that the sectional asymmetric structure can realize better impedance-matched to free space by the coupling of four isolated Au brackets effectively. Furthermore, as a comparison we modeled an absorber based on a complete square ring structure. The period of its unit cell is 22 μm and the outer side length of the square ring is P4 = 18 μm. The layer and materials are the same as the proposed sectional asymmetric broadband absorber. Figure 3(c) shows its absorptivity curve. The bandwidth with absorptivity being larger than 90% is only about 126 GHz. The bandwidth of sectional asymmetric structure absorber is about 364/126 = 2.8 times than that of complete square ring structure absorber. In application of focal plane array THz imaging, the sensor integrated absorber should be insensitive to the incidence angles, especially for the optical-readout cantilever sensor which will deflect angles owing to the bimaterial thermal effect, and the absorber should be polarization insensitive to maximize the absorption. To evaluate these characteristics, we simulated the absorption spectra of sectional asymmetric broadband absorber in different polarization angles and incidence angles by the CST2012. Figure 4(a) shows the absorptivity curves at various polarization angles for the normal incident radiation. Figure 4(b) depicts the calculated average curve of the absorptivities according to the various polarization angles. The polarization angle φ is defined as the angle between electric field E and positive x axis and depicted as the inset in Fig. 4(b). The equation for calculating average absorption curve of Fig. 4(b) is given by where Aaverage stands for the average absorptivity at the different polarization angles, Aφ = 0°, Aφ = 10°, …,Aφ = 160°, Aφ = 170° represents the absorptivity at polarization angles φ = 0°, φ = 10°, …,φ = 160°, φ = 170°, respectively. The major metrics to define polarization-insensitive are 1) the absorptivity; 2) the resonance frequency. The absorbers which are sensitive to polarization will have severer absorptivity decline and resonance frequency shift7 in different polarization directions. For the polarization-insensitive absorbers, although they cannot realize uniform absorption exactly at different polarizations and most of polarization-insensitive absorbers will show differences between neighboring polarizations, but the polarization-insensitive absorbers can keep relative high absorption and the resonance frequency will not be offset too much in different polarization directions. As is shown in Fig. 4, although the absorptivity has fluctuation when φ sweeps from 0° to 170°, the simulation results show that the proposed structure provides relative high absorptivity (The range of values is about 60~99%) and keeps broadband absorptions (resonance frequency almost no shift) at different polarization angles. Furthermore, the calculated average absorption according to the polarization angles (φ = 0°, φ = 10°, …. φ = 160°, φ = 170°) also shows broadband high absorption in the same frequency range. Figure 5(a) describes how the absorptivity changes for different incidence angles which increase with a step of 10 degrees from 0° to 40° for the TE (Transverse Electric) radiation. Figure 5(b) shows how the absorptivity changes for the TM (Transverse Magnetic) radiation. The incidence angle θ is defined as the angle between wave vector k and the surface normal of the absorber and is depicted as the insets. According to the Fig. 5, the absorptivity decreases a little when φ sweeps from 0° to 40° for the TE wave. Meanwhile, the absorptivity increases and has frequency shift when φ sweeps from 0° to 40° for the TM wave. Although the absorptivity has fluctuation, the simulation results demonstrate that the absorber keeps the characteristic of broadband absorption at various oblique incident angles. Conclusion The paper proposed the concept of sectional asymmetric structures. They can manipulate specific device’s working bandwidth with maintaining the properties of the basic structure. To verify its effectiveness a broadband THz absorber was designed and evaluated numerically. Each cell of the absorber integrates four sectional square rings with approximate resonance frequencies. The entire structure composed of Au and Si3N4 is only 1.9 μm thick. The simulation results show its bandwidth with absorptivity being larger than 90% is extended to about 2.8 times comparing with the classic square ring absorber. We believe the sectional asymmetric structures have two distinctive advantages: 1) manipulating specific device’s working bandwidth while maintaining the inherent advantages of the complete structure; 2) not increasing size of the structure and thickness of the device. Therefore, it will be suitable for the focal plane array THz imaging sensors such as optical-readout bimaterial cantilever sensors or some electrical-readout sensors (microbolometer sensors and pyroelectric sensors). Methods Design of the sectional asymmetric metamaterial structures There are four steps to design a normal sectional asymmetric structure (or cell). The first step is choosing one complete resonance structure as basic structure. The second step is dividing the symmetrical structure into sections. The third step is varying the characteristic size of each section. The fourth step is composing these asymmetric sections into a new structure (cell). Then, we called it sectional asymmetric metamaterial structure. It should be mentioned that the selected basic structure in the first step should be multiple symmetric structures, such as square ring, hexagonal ring, circular ring, or elliptical ring and so on. We take another simple example to demonstrate the design method. This example is also a metamaterial absorber made of Au and Si3N4, but its basic structure is circular ring. The absorber comprises three layers: the top layer is an array of sectional asymmetric Au resonators (0.1 μm thick); the middle layer is Si3N4 dielectric film (1.8 μm thick); the bottom layer is Au ground (0.1 μm thick). Figure 6(a) shows one cell based on a complete circular ring. After the aforementioned four steps, the Fig. 6(d) describes the final sectional asymmetric unit cell which integrates four circle sections with four resonance frequencies. The outer radiuses of four circle rings are 9.6 μm, 9.4 μm, 9.2 μm, and 9 μm, respectively. The gaps between the sectional rings are 2.1 μm and the width of the sectional circle ring is 3 μm. The period of one metamaterial cell is the same as the proposed sectional asymmetric square ring absorber (22 μm). Figure 1(e) depicts the absorptivity curve of the metamaterial absorber simulated by CST 2012. The absorber’s bandwidth with absorptivity being larger than 90% is about 390 GHz, but its entire thickness is only 2 μm. In addition it’s worth mentioning that we can broaden the absorption spectra using more sectional rings, or narrow the absorption spectra using fewer sectional rings. Numerical simulation We modeled the cell structures and simulated their electromagnetic characteristics by the commercial 3D electromagnetic simulator CST Studio Suite 2012. We use auto meshing technology and frequency-domain solver to acquire S-parameter. The unit cell boundary condition with Floquet-port was used to simulate the absorption spectra, because the Floquet mode can be applied to any periodical array whether mirrored or rotated. The resonance current distributions were obtained based on the Field Monitor technology of the CST at certain frequencies. The thickness of Si3N4 dielectric film is 1.7 μm and its dielectric constant is 8. The material of the sectional ring is Au with an electric conductivity 4.6 × 107 s/m and the thickness of the ring is 0.1 μm. Additional Information How to cite this article: Gong, C. et al. Broadband terahertz metamaterial absorber based on sectional asymmetric structures. Sci. Rep. 6, 32466; doi: 10.1038/srep32466 (2016). This work is financially supported by National Natural Science Foundation of China (61505087, 11574160), National Basic Research Program of China (2014CB339802) and Tianjin Research Program of Application Foundation and Advanced Technology (15JCZDJC31700). Author Contributions W.L. planned and supported the works. C.G. designed the metamaterial structures. C.G. and M.Z. performed the numerical simulation. Z.W., J.Y. and W.L. analyzed the data. W.L., H.L. and Y.Z. supervised the project. All authors participated in the discussion of the results and the writing of the manuscript. Figure 1 Design example of a sectional asymmetric metamaterial unit cell. (a) The basic structure: complete square ring in one cell and its outer side length is P1. Then, dividing the symmetrical structure into sections and varying the characteristic size of each section: (b) two asymmetric sectional square rings and (c) three asymmetric sectional square rings. Finally, compose these asymmetric sections into a new unit cell: (d) the final sectional asymmetric square ring cell. Figure 2 Proposed broadband THz sectional asymmetric metamaterial absorber. (a) Top structure in one cell of the absorber. (b) Transmission line model of the cell. (c) Diagrammatic sketch of a 3 × 3 cells array. Figure 3 Simulation results. (a) Absorptivity curve of the sectional asymmetric metamaterial absorber; for comparison the absorption spectra of isolated Au brackets (quarter sectional ring) absorber are also provided. (b) Resonance current distributions in one cell at different absorption peaks. (c) Absorptivity curve of the compared metamaterial absorber based on complete square ring. Figure 4 Simulation and calculation results. (a) Absorptivity curves at various polarization angles φ for the normal incident radiation. The polarization angle φ is defined as the angle between electric field E and positive x axis and depicted as the inset. (b) The calculated average curve of these absorptivity curves. Figure 5 Simulation results. (a) Absorptivity curves at various oblique incident angle θ for the TE radiation. (b) Absorptivity curves at various oblique incident angle θ for the TM radiation. The incidence angle θ is defined as the angle between wave vector k and the surface normal of the absorber and is depicted as the insets. Figure 6 Design example of the sectional asymmetric metamaterial structure. (a) The basic structure: complete circle ring in one cell. (b) Then, dividing the symmetrical structure into sections and varying the characteristic size of each section: (b) two asymmetric sectional circle rings and (c) three asymmetric sectional circle rings. (d) The final sectional asymmetric circle ring cell. (e) Absorptivity curve of the designed metamaterial absorber simulated by CST 2012. ==== Refs Tao H. , Kadlec E. A. , Strikwerda A. C. , Fan K. , Padilla W. J. , Averitt R. D. , Shaner E. A. & Zhang X. . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3228110.1038/srep32281ArticlePlasmid-mediated quinolone resistance determinants in quinolone-resistant Escherichia coli isolated from patients with bacteremia in a university hospital in Taiwan, 2001–2015 Kao Cheng-Yen 1Wu Hsiu-Mei 1Lin Wei-Hung 23Tseng Chin-Chung 3Yan Jing-Jou 4Wang Ming-Cheng 35Teng Ching-Hao 6Wu Jiunn-Jong a171 Department of Medical Laboratory Science and Biotechnology, College of Medicine, National Cheng Kung University, Tainan, Taiwan2 Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan3 Division of Nephrology, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan4 Department of Pathology, National Cheng Kung University Hospital, National Cheng Kung University, Tainan, Taiwan5 Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan6 Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan7 Department of Biotechnology and Laboratory Science in Medicine, School of Biomedical Science and Engineering, National Yang Ming University, Taipei, Taiwana jjwu1019@ym.edu.tw30 08 2016 2016 6 3228128 04 2016 04 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The aim of this study was to characterize fluoroquinolone (FQ)-resistant Escherichia coli isolates from bacteremia in Taiwan in 2001–2015. During the study period, 248 (21.2%) of 1171 isolates were identified as levofloxacin-resistant. The results of phylogenetic group analysis showed that 38.7% of the FQ-resistant isolates belonged to phylogenetic group B2, 23.4% to group B1, 22.6% to groupA, 14.9% to group D, and 0.4% belonged to group F. FQ-resistant isolates were highly susceptible to cefepime (91.5%), imipenem (96.0%), meropenem (98.8%), amikacin (98.0%), and fosfomycin (99.6%), as determined by the agar dilution method. β-lactamases, including blaTEM (66.1%), blaCMY-2 (16.5%), blaCTX-M (5.2%), blaDHA-1 (1.6%), and blaSHV-12 (1.6%), were found in FQ-resistant isolates. The results of PCR and direct sequencing showed that 37 isolates (14.9%) harbored plasmid-mediated quinolone resistance (PMQR) genes. qnrB2, qnrB4, qnrS1, coexistence of qnrB4 and qnrS1, oqxAB, and aac(6′)-Ib-cr were found in 1, 4, 4, 1, 15, and 14 isolates, respectively. PMQR genes were successfully transfered for 11 (29.7%) of the 37 PMQR-harboring isolates by conjugation to E. coli C600. These findings indicate that qnr genes remained rare in E. coli but demonstrate the potential spread of oqxAB and aac(6′)-Ib-c in Taiwan. ==== Body Fluoroquinolones (FQs) are potent and broad-spectrum agents extensively used to treat a wide range of Gram-positive/negative bacterial infections by inhibiting the activity of both DNA gyrases (GyrA and GyrB) and the topoisomerase IV enzymes (ParC and ParE)1. Unfortunately, despite prescribing guidelines that now recommend reserving FQ use, over the last decade, worldwide spread of FQ-resistant organisms has reduced their therapeutic effectiveness and emerged as an important threat to global health2. Organisms resistant to FQs can occur via several mechanisms, including intrinsic mutations under selection pressure or harboring transferable plasmid-mediated quinolone resistance (PMQR) determinants2. The most common mechanism of high-level FQ resistance is due to mutation in one or more of the genes that encode the targets of FQs. Kishii et al. showed the mutations that alter the expression and function of outer membrane protein, OmpF, can also lead to FQ resistance in Escherichia coli3. In addition, resistance can be conferred by upregulation of chromosomal multidrug efflux pumps (for example, AcrAB-TolC) (by mutations in regulatory proteins), increasing the capability of actively removing FQs and other drugs from the bacterial cell4. Although FQ resistance can arise by a range of mechanisms, the greatest concern is placed on these bacteria harboring transferable PMQR genes; for example qnr alleles, oqxAB, qepA, and aac(6′)Ib-cr5678. The binding of the Qnr protein to the topoisomerase physically prevents the intercalation of the FQs with the target enzyme and thus causes drug resistance5. A variant of an aminoglycoside acetyl transferase, aac(6′)-lb-cr, is able to confer decreased susceptibility to FQs by acetylating the amino nitrogen on the piperazinyl substituent present in these antimicrobial agents6. Moreover, two plasmid borne efflux systems, oqxAB and qepA, which encode transporters that can export FQs and other drugs, have become increasingly prevalent among Enterobacteriaceae over the past decade78. Although most E. coli are harmless, some pathogenic E. coli isolates can cause diverse gastrointestinal or urinary tract diseases, and even bacteremia, and thus cause millions of death every year. The characterization of FQ-resistant E. coli was reported worldwide; however, isolates in most studies were enrolled over a relatively short duration. As a result, the longitudinal evolution and epidemiologic trends FQ-resistant E. coli isolates are possibly hidden. The aim of this study was to investigate the molecular epidemiology of FQ-resistant E. coli isolated from patients with bloodstream infections in Taiwan, 2001–2015. Results Long-term surveillance and antimicrobial susceptibility of FQ-resistant E. coli During the study period, 2001–2015, we randomly selected 1,171 E. coli isolates from patients with bacteremia, of which 248 (21.2%) were identified as levofloxacin-resistant by using the disk diffusion method (Table 1). The trend in the prevalence of FQ-resistant invasive isolates remained stable during the 15-year surveillance (19.2–24.3%) (Table 1). The phylogenetic analysis revealed five groups (A, B1, B2, D, and F) in 248 FQ-resistant isolates. Ninty-six (38.7%) of the FQ-resistant isolates belonged to phylogenetic group B2. Phylogenetic group B1 was the second most common, representing in 23.4% of the isolates, followed by group A (22.6%), group D (14.9%), and group F (0.4%) (Table 1). The dramatically increasing ratio of phylogenetic group B2 among FQ-resistant isolates was revealed during the study period (Table 1). The susceptibilities of the 248 FQ-resistant isolates to 15 antimicrobial agents are shown in Table 2. All isolates were resistant to levofloxacin and ciprofloxacin, as determined by the agar dilution method. However, the entire collection was highly susceptible to cefepime (91.5%), imipenem (96.0%), meropenem (98.8%), amikacin (98.0%), and fosfomycin (99.6%) (Table 2). One isolate showed resistance to tigecycline, and all isolates were susceptible to colistin. Moreover, a total of 89 (35.9%) and 223 (89.9%) isolates were defined to be ESBL-producers and multidrug resistant (MDR) strains, respectively. The trends of resistance of FQ-resistant invasive isolates to 11 selected antimicrobial agents were generally stable during this 15-year surveillance (Fig. 1). The prevalence of antimicrobial resistance to tetracycline decreased from 86.7% to 55.6% during this period (Fig. 1). Characterization of antimicrobial resistance genes The numbers of β-lactamase- and PMQR-producers among the 248 FQ-resistant isolates are shown in Table 1. The results showed that the dominant β-lactamase was blaTEM (66.5%), followed by blaCMY (19.0%), blaCTX-M (4.8%), blaDHA (1.6%), and blaSHV (1.6%) in FQ-resistant E. coli isolates (Table 1). Sequence analysis revealed that 6 blaCTX-M-14, 3 blaCTX-M-174, 2 blaCTX-M-15, 1 blaCTX-M-13, and 1 blaCTX-M-55 genes were identified among 12 isolates producing blaCTX-M type extended spectrum β-lactamases (ESBLs) (isolate 1902 harbored blaCTX-M-14 and blaCTX-M-15). Only the blaSHV-12 ESBL was found in 4 blaSHV-porducers. In addition, all blaCMY and blaDHA genes were identified as blaCMY-2 and blaDHA-1, respectively. The prevalence of PMQR genes, including qnr alleles, aac(6′)-Ib-cr, qepA, and oqxAB were determined by PCR and direct sequencing, and the results showed that 37 FQ-resistant isolates (14.9%) harbored at least one PMQR gene (Table 1). qnrB2, qnrB4, qnrS1, and the coexistence of qnrB4 and qnrS1 were found in 1, 4, 4, and 1 isolates, respectively (Table 1). oqxAB and aac(6′)-Ib-cr genes were identified in 15 (isolate 1315 harbored only oqxA but not oqxB) and 14 isolates (2 isolates also harbored qnrB4), respectively (Table 1). qnr alleles, including qnrA, qnrC, qnrD, qnrVC, and qepA, were not found in any of the detected isolates. This survey also showed a trend of increase in the prevalence of aac(6′)-Ib-cr and oqxAB among FQ-resistant isolates between 2004–2006 and 2010–2012 (Table 1). Among 10 qnr-producers, blaSHV-12, blaDHA-1 blaCMY-2 were found in 3, 4, and 2 isolates, respectively. However, no blaSHV-12 or blaDHA-1 were detected in oqxAB- or aac(6′)-Ib-cr-producers. In contrast, blaCMY-2 was found in 7 oqxAB-producers (7/15, 46.7%) and 6 aac(6′)-Ib-cr-producers (6/14, 42.9%), respectively. Characterization of QRDR mutations in PMQR-harboring isolates Thirty-seven PMQR-harboring E. coli isolates were distributed into each of the four main phylogroups: A, 12 isolates (32.4%); B1, 15 isolates (40.5%); B2, 6 isolates (16.2%); and D, 4 isolates (10.9%) (Table 3). Chromosomal QRDR mutations were determined by PCR and direct sequencing, and the results showed that only 1 (isolate 1019) and 2 (isolate 1706 and 1763) isolates contained wild-type GyrA and ParC, respectively (Table 3). The most common point mutations in PMQR-harboring isolates were GyrA S83L/D87N (31 isolates, 83.8%) and S83L (4 isolates, 10.8%), and those in ParC were S80I (23 isolates, 62.2%) and S80I/E84V (6 isolates, 16.2%) (Table 3). PMQR gene transfer and plasmid analysis E. coli isolates harboring PMQR genes were further analyzed by conjugation tests to determine whether there was horizontal plasmid spread in Taiwan. Transfer of PMQR genes by conjugation to recipient cells of E. coli C600 was successful for 11 (29.7%) of the 37 selected isolates (2, 4, 1, 2, and 2 parental isolates harbored qnrB, qnrS, qnrB/qnrS, oqxAB, and aac(6′)-Ib-cr/qnrB, respectively) (Table 4). Plasmid numbers and sizes present in parental isolates and transconjugants were verified according to the method of Kado and Liu9, and the results showed that 14 transconjugants (except 1962-3) contained only a single plasmid with a size over 50 kb (Table 4). The antimicrobial resistance genes in transconjugants were further verified by PCR, and the results showed that the aac(6′)-Ib-cr and qnrB4 genes were located on the same plasmid in 1377-3. Two and three transconjugants harboring different plasmid profiles were selected from parental isolates 1426 and 1962, respectively (Table 4). No co-transference of qnrB4 and qnrS1 were found in 30 randomly selected transconjugants from isolate 1426. In contrast, transference of aac(6′)-Ib-cr, qnrB, and aac(6′)-Ib-cr/qnrB from isolate 1962 was found in 6 (20%), 4 (13.3%), and 20 (66.7%) of transconjugants. Co-transference of blaDHA-1 and qnrB to recipient cells was found in 3 of 5 qnrB-producers (isolates 1377, 1426, and 1962) (Table 4). No blaCMY-2 was detected in oqxAB- or aac(6′)-Ib-cr-harboring transconjugants. Transconjugant 1649-2 showed resistance to ampicillin and cefoxitin with an un-identified β-lactamase gene. In addition, transconjugants 1377-3, 1706-2, and 1962-2 showed increased MICs to tetracycline. The results indicated the co-transference of the tetracycline resistance gene with PMQR determinants. Moreover, 6 of 11 transconjugants showed high resistance to trimethroprim (MIC > 256 μg/mL) (Table 4). PCR-based replicon typing results revealed that IncN, IncFII, and IncHII were identified in 4, 4, and 2 PMQR-plasmids of transconjugants harboring only a single plasmid. However, 3 plasmids (613-3, 1377-3 and 1426-4) were nontypable by PCR-based replicon typing (Table 4). Discussion In this study, we present the characteristics of 248 FQ-resistant bacteremia isolates of E. coli from Taiwan, 2001–2015. Among them, 37 isolates harbored at least one PMQR gene. oqxAB and aac(6′)-Ib-cr genes were most prevalent among PMQR-producers. In addition, horizontal transmission of PMQR genes is often accompanied by transmission of genes conferring resistance to other antimicrobial agents. Antimicrobial resistance in Gram-negative bacteria is on the rise worldwide, particularly in E. coli, which constitutes a majority of invasive Gram-negative isolates. Wong et al. showed that ciprofloxacin resistance in E. coli isolated from bacteremia in Canada peaked in 2006 at 40% and subsequently stabilized at 29% in 2011, corresponding to decreasing ciprofloxacin usage after 200710. In this study, we showed the prevalence of FQ-resistant invasive E. coli isolates is lower compared with Canada (Table 1). In addition, the prevalence of FQ resistance in bacteremia-causing E. coli was lower than urinary-tract-related E. coli in Taiwan (21.2% vs. 32%)11. Moreover, the entire collection was highly susceptible to cefepime, imipenem, meropenem, amikacin, and fosfomycin (Table 2). Fosfomycin is found active against Enterobacteriaceae, particularly E. coli, regardless of source (urinary tract infections or bacteremia), ciprofloxacin resistance, and ESBL production121314. In addition, fosfomycin is recommended as one of the first-line agents for treatment of urinary tract infections (UTIs) in the latest guidelines endorsed by the Infectious Diseases Society of America and the European Society for Clinical Microbiology and Infectious Diseases15. As a result, the clinical usefulness of fosfomycin, as a first-line treatment agents of bacteremia E. coli infections, should be evaluated further, especially in regions where ciprofloxacin resistance rates are high. The phylogenetic group B2 was the most common pathogenic E. coli in many countries, and group A and group B1 were usually isolated as commensals1617. Massot et al. showed a parallel and linked increase in the frequency of the B2 group strains (from 9.4% in 1980 to 22.7% in 2000 and 34.0% in 2010) and of virulence factors18. Here, we showed 38.7% of the FQ-resistant bacteremia E. coli isolates belonged to phylogenetic group B2, followed by group B1 (23.4%), group A (22.6%), group D (14.9%), and group F (0.4%) (Table 1). Moreover, based on the 15-year epidemiologic analysis, we further showed that the increasing trend of group B2 among bacteremia E. coli isolates (Table 1). Phylogenetic group B2 dominates the bacteremia E. coli isolates during the period 2007–2015, but group B1 was most prevalent among bacteremia E. coli isolates during the period 2001–2006 (Table 1). As a result, the longitudinal collection of clinical isolates provides the opportunity to characterize the dynamics of the epidemiologic trend and evolution in infectious pathogens over long periods. Zhao et al. showed that qnr, aac(6′)-Ib-cr, qepA, and oqxAB were found in 2.7%, 24.5%, 11.9% and 6.3% of ciprofloxacin-resistant E. coli isolates in China, respectively19. Yang et al. showed that PMQR genes were detected in 59 of 80 (73.8%) ciprofloxacin-nonsusceptible bacteremia E coli isolates from Korea20. In this study, we revealed the prevalence of PMQR genes among FQ-resistant E. coli in Taiwan (14.9%) was relatively lower than in China (37.3%)19 or in Korea (73.8%)20. In addition, the dominant PMQR genes among FQ-resistant E. coli in Taiwan is oqxAB (40.5%), followed by aac(6′)-Ib-cr (37.8%), and qnr alleles (27.0%). No qepA-producer was found in this study. Although PMQR genes provide a low level of FQ resistance, they have been reported to favor the selection of additional chromosome-encoded resistance mechanisms21. Moreover, all of the PMQR-positive isolates had QRDR mutations (Table 3). These results suggest that along with high-level resistance mediated by QRDR mutations, selection pressure from FQs was absent, and in this case PMQR genes may be lost21. It is possible that evolution by natural selection may explain the higher level of FQ resistance and the relatively lower prevalence of PMQR genes in FQ-resistant invasive E. coli from Taiwan. As a result, continual epidemiologic surveillance of PMQR genes is necessary to evaluate whether there are specific plasmids disseminated in Taiwan. Previous studies showed the most common point mutations in ciprofloxacin-resistant E. coli isolates from China were GyrA S83L/D87N (263 isolates, 87.1%) and S83L (21 isolates, 7.0%), and those in ParC were S80I (233 isolates, 77.2%) and S80I-E84V (35 isolates, 11.6%)19. Our results regarding the distribution of QRDR mutations among FQ-resistant isolates were consisted with previous studies (Table 3). Isolate 1019 showed low-level FQ resistance presented S129A/S134G/A141V/L151M substitutions in ParC in the absence of GyrA substitutions raised the possibility that these mutations were not associated with FQ resistance. However, the direct evidence to demonstrate the association of specific QRDR mutations with FQs susceptibility is still limited and thus worth investigating. A striking association between blaDHA-1 and qnrB4 was reported in Korea and Taiwan2223, and this tight association was also observed in our study (Table 4). The co-transference of the blaDHA-1 and qnrB4 genes was identified by conjugation assay (3/4, 75%) (Table 4). In contrast, although 7 oqxAB- (7/15) and 6 aac(6′)-Ib-cr-producers (6/14) also carried blaCMY-2, the results of the conjugation assay showed that no blaCMY-2 was located on oqxAB- or aac(6′)-Ib-cr-containing plasmids (Table 4). To our knowledge, this is the first description of the high co-occurrence of blaCMY-2 in oqxAB or aac(6′)-Ib-cr-producing E. coli. Highly transferable PMQR genes were observed in this study (11/37, 29.7%) (Table 4). Additional phenotypically expressed resistances were co-transferred with PMQR genes by 12 plasmids (92.3%, except 613-3), resulting in diverse resistance patterns (Table 4). Overall, the most frequently co-transferred resistances were to ampicillin (69.2%), trimethoprim (42.6%), ceftazidime (38.5%), cefotaxime (30.8%), cefoxitin (30.8%), kanamycin (30.8%), and tetracycline (23.1%) (MICs > 4-fold change) (Table 4). These results indicated the high co-existence of antimicrobial resistance genes on the PMQR-plasmids. In summary, plasmid profiling of E. coli isolates exhibiting the co-existence of both PMQR genes and other antimicrobial resistance genes on a single plasmid shows how they contribute to the rapid spread and increase in bacterial resistance, which is important to public health. The plasmid backgrounds of the PMQR genes were variable, ruling out the hypothesis for the spread of specific plasmids in Taiwan, however, continual epidemiologic surveillance and monitoring antimicrobial prescriptions and consumption would decrease the prevalence of FQ-resistant organisms and PMQR spread. Methods Sampling and isolation of E. coli Bacteremia E. coli isolates were recovered in National Cheng Kung University hospital, 2001 to 2015. The Ethics Committee approved that no formal ethical approval was needed to use these clinically obtained materials, because the isolates were remnants from patient samples, and the data were analyzed anonymously. A total of 1,171 non-duplicate clinical isolates were randomly selected and stored at −80 °C in Luria-Bertani (LB) broth containing 20% glycerol (v/v) until used. E. coli was identified in the clinical laboratory by colony morphology, Gram stain, biochemical tests, and the Vitek system (bioMérieux, Marcy l′Etoile, France) according to the manufacturer’s recommendations. Susceptibility to levofloxacin for E. coli isolates was determined by the disk diffusion method (5 μg/disc, BD BBL™ Sensi-Disc™, Sparks, MD, USA) on Mueller-Hinton (MH) agar (Bio-Rad, Marne la Coquette, France) based on the CLSI guidelines24. A total of 248 levofloxacin-nonsusceptible bacteremia E. coli isolates were identified for further analysis. Antimicrobial susceptibility testing Antimicrobial susceptibilities to ampicillin, ampicillin-sulbactam, gentamicin, colistin, and tigecycline (BD BBL™ Sensi-Disc™) were determined by the disk diffusion method on Mueller-Hinton agar24. MICs of selected antimicrobial agents (from Sigma-Aldrich: amikacin, cefepime, cefotaxime, ceftazidime, ciprofloxacin, fosfomycin, kanamycin, levofloxacin; from USP Standards: cefoxitin, imipenem, meropenem) were determined by the agar dilution method in accordance with CLSI guidelines24. E. coli ATCC 25922 and Pseudomonas aeruginosa ATCC 27853 were used as quality control strains. The interpretation of resistance to these antimicrobial agents was determined according to the recommendations of the CLSI25. Tigecycline and colistin susceptibilities were interpretated according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST)26 and previous study27, respectively. MDR E. coli was defined as isolates that were resistant to at least 3 classes of the tested antimicrobial agents28. Characterization of antimicrobial resistance genes All 248 FQ-resistant E. coli isolates were further screened for selected β-lactamases (blaTEM, blaSHV, blaCTX-M, blaDHA, and blaCMY) and PMQR genes (qnr alleles, oxqAB, qepA, and aac(6′)Ib-cr) by PCR amplification with specific primers (Supplmentary Table S1). DNA sequencing was further carried out on β-lactamases (except blaTEM) and PMQR genes, and the DNA sequences and deduced amino acid sequences were compared with genes in the GenBank database (http://www.ncbi.nlm.nih.gov/genbank/) to confirm the subtypes of antimicrobial resistance genes. Screening for mutations in quinolone resistance-determining regions GyrA and ParC QRDRs of 37 isolates harboring PMQR genes were examined by amplifying and sequencing gyrA (490 bp) and parC (470 bp) genes using primers (Supplmentary Table S1) described by Zhao et al.19. Amplimers were sequenced and amino acid mutations were determined using the control strain E. coli K-12 (NZ_AKBV01000001.1) as a reference. Determination of the phylogenetic origin of E. coli isolates Phylogenetic grouping of E. coli isolates was performed using a previously published method29. Primers used are described in Supplmentary Table S1. The PCR-amplified products were separated by electrophoresis on 1.8% agarose gels, stained with ethidium bromide, and assigned to one of the seven phylogenetic groups A, B1, B2, C, D, E and F. Conjugation experiments and plasmid analysis The liquid mating-out assay was carried out to transfer PMQR genes from 37 FQ-resistant E. coli isolates to rifampicin-resistant E. coli C600 as described previously30. Transconjugants were selected on LB plates containing 256 μg/mL rifampicin (Sigma) and 0.06 μg/mL ciprofloxacin. The plasmids were extracted as described previously9, followed by electrophoresis in a 0.6% agarose gel at 50 V for 3 h and compared by co-electrophoresis with plasmids of known sizes from Salmonella OU7526 and a GeneRularTM DNA ladder (Fermentas, Burlington, ON, Canada) to predict the plasmid sizes30. Plasmids were typed by PCR-based replicon typing according to the previous study31. Additional Information How to cite this article: Kao, C.-Y. et al. Plasmid-mediated quinolone resistance determinants in quinolone-resistant Escherichia coli isolated from patients with bacteremia in a university hospital in Taiwan, 2001–2015. Sci. Rep. 6, 32281; doi: 10.1038/srep32281 (2016). Supplementary Material Supplementary Information We thank Robert Jonas for helpful comments on this manuscript. This study was supported by grant MOST 104-2320-B-006-018-MY3 from the Ministry of Science and Technology, R.O.C. and by grant NCKUH-10301002 from the National Cheng Kung University Hospital, Tainan, Taiwan. Author Contributions C.-Y.K. designed the study. C.-Y.K., H.-M.W., W.-H.L., C.-C.T., M.-C.W. and C.-H.T. were responsible for E. coli isolation, antimicrobial susceptibility test, genotyping of the antimicrobial resistance genes and drafted the manuscript. C.-Y.K., J.-J.Y. and J.-J.W. contributed ideas and edited the manuscript. All authors read, commented on, and approved the final manuscript. Figure 1 Trends of antimicrobial resistance among 248 FQ-resistant E. coli, 2001–2015. AMP, ampicillin; AN, amikacin; CAZ, ceftazidime; CTX, cefotaxime; FEP, cefepime; FOS, fosfomycin; FOX, cefoxitin; GM, gentamicin; KN, kanamycin; SAM, ampicillin-sulbactam; TET, tetracycline. Table 1 Distribution of phylogenetic group, PMQR genes, and β-lactamase genes in 248 FQ-resistant bacteremia E. coli isolates. Characteristic No. (%) of isolates 2001–2003 45 (19.4) 2004–2006 49 (20.4) 2007–2009 41 (19.2) 2009–2012 59 (24.3) 2013–2015 54 (22.2) Total 248 (21.2) Phylogenetic group, No. (%)  A 10 (22.2) 14 (28.6) 11 (26.8) 14 (23.7) 7 (13.0) 56 (22.6)  B1 16 (35.6) 14 (28.6) 10 (24.4) 8 (13.6) 10 (18.5) 58 (23.4)  B2 7 (15.5) 7 (14.2) 18 (44.0) 29 (49.1) 35 (64.8) 96 (38.7)  D 12 (26.7) 14 (28.6) 1 (2.4) 8 (13.6) 2 (3.7) 37 (14.9)  F 0 0 1 (2.4) 0 0 1 (0.4) PMQR genes, No. (%)a  qnrB — 1 (qnrB2) 1 (qnrB4) — 1 (qnrB4) — 3  qnrS 1 (qnrS1) — — 1 (qnrS1) 2 (qnrS1) 4  qnrB + qnrS — — — 1 (qnrB4, qnrS1)   1  oqxAB 2 6 2b 4 1 15  aac(6′)-Ib-cr — 4 2 5 1 12  qnrB + aac(6′)-Ib-cr — — 1 (qnrB4) — 1 (qnrB4) 2 β-lactamase genes, No. (%)  blaTEM 28 21 21 27 28 125  blaCTX-M 0 0 0 0 7 7  blaCMY 0 4 1 8 1 14  blaTEM/blaCTX-M 1 1 0 0 1 3  blaTEM/blaDHA 0 0 1 0 0 1  blaTEM/blaCMY 1 7 9 6 9 32  blaTEM/blaSHV 0 1 0 1 0 2  BlaCTX/blaCMY 0 0 0 0 1 1  blaSHV/blaDHA 0 0 0 1 0 1  blaTEM/blaSHV/blaDHA 0 1 0 0 0 1  blaTEM/blaCTX-M/blaDHA 0 0 0 0 1 1 aqnr alleles (qnrA, qnrC, qnrD, qnrVC) and qepA were not found in any of the detected isolates. bIsolate 1315 harbored only oqxA but not oqxB. Table 2 In vitro activity of 15 antimicrobial agents against 248 FQ-resistant bacteremia E. coli isolates. Antibiotica MIC (μg/mL) % Susceptibility Range MIC50 MIC90 S I R Ampicillinb — — — 6.0 1.2 92.8 Ampicillin-sulbactamb — — — 42.0 17.0 41.0 Ceftazidime 0.06–>256 1 256 63.7 1.6 34.7 Cefepime <0.03–>256 0.12 4 91.5 3.2 5.3 Cefotaxime <0.03–>256 0.25 64 59.3 1.6 39.1 Cefoxitin 0.12–>256 8 256 54.0 1.6 44.4 Imipenem 0.12–>256 0.25 0.5 96.0 2.8 1.2 Meropenem <0.03–>128 <0.03 0.06 98.8 0 1.2 Amikacin 1–>256 4 8 98.0 0.4 1.6 Gentamicinb — — — 54.0 3.6 42.4 Kanamycin 2–>256 16 >256 68.1 5.6 26.3 Tetracycline 1–>256 128 256 26.2 0.4 73.4 Fosfomycin 0.25–>256 1 2 99.6 0 0.4 Ciprofloxacin 0.12–>256 32 128 0 1.6 98.4 Levofloxacin 4–128 16 64 0 3.6 96.4 MIC50/90, minimum inhibitory concentration for 50% and 90% of the isolates, respectively; S, susceptible; I, intermediate resistant; R, resistant. aOne isolate was resistant to tigecycline, and all isolates were susceptible to colistin. bAntimicrobial susceptibilities of ampicillin, ampicillin-sulbactam, and gentamicin were determined by the disk diffusion method. Table 3 Phylogenic group, MICs, PMQR genes and QRDR mutations of 37 E. coli isolates harboring PMQR genes. Isolate Year Phylogenic group MIC (μg/mL) PMQR genes QRDR mutationsa CIP LVX GyrA ParC 534 2001 B1 64 32 oqxAB S83L, D87N S80I 613 2002 B1 4 8 qnrS1 S83L A81P 680 2002 A 128 64 oqxAB S83L, D87N S80I, A108V 905 2005 B1 64 64 oqxAB S83L, D87N S80I 906 2005 B1 64 32 oqxAB S83L, D87N S80I 946 2005 A 256 64 oqxAB S83L, D87N S80I 966 2005 B1 128 32 oqxAB S83L, D87N S80I 970 2005 B1 64 32 oqxAB S83L, D87N S80I 977 2005 A 16 8 oqxAB S83L, D87N S80I 1019 2006 A 1 4 qnrB2 —b S129A, S134G, A141V, L151M 1029 2006 A 128 64 aac(6′)-Ib-cr S83L, D87N S80I, E84G 1045 2006 D 128 16 aac(6′)-Ib-cr S83L, D87N S80I 1050 2006 A 16 32 qnrB4 S83Y G78C, S129A, S134G A141V, L151M 1077 2006 D 128 8 aac(6′)-Ib-cr S83L, D87N S80I 1078 2006 D 256 16 aac(6′)-Ib-cr S83L, D87N S80I 1206 2007 B1 128 64 oqxAB S83L, D87N S80I 1262 2008 B2 128 16 aac(6′)-Ib-cr S83L, D87N S80I, E84V 1270 2008 B2 128 16 aac(6′)-Ib-cr S83L, D87N S80I, E84V 1315 2009 B1 8 8 oqxA S83L, D87N S80I 1377 2009 B1 128 64 qnrB4, aac(6′)-Ib-cr S83L, D87N S80I 1426 2010 B2 256 128 qnrB4, qnrS1 S83L, D87N S80I, E84V 1465 2010 A 128 32 oqxAB S83L, D87N S80I 1480 2010 B1 64 32 oqxAB S83L, D87N S80I 1504 2011 A 128 32 aac(6′)-Ib-cr S83L, D87N S80I 1510 2011 A 128 32 aac(6′)-Ib-cr S83L, D87N S80I 1516 2011 B1 16 16 qnrS1 S83L S80I 1540 2011 B2 256 16 aac(6′)-Ib-cr S83L, D87N S80I, E84V 1558 2011 B1 32 16 oqxAB S83L, D87N S80I 1604 2012 B1 128 64 oqxAB S83L, D87N S80I 1619 2012 B2 64 16 aac(6′)-Ib-cr S83L, D87N S80I, E84V 1649 2012 D 128 64 qnrB4 S83L, D87N S80I 1705 2012 A >256 64 aac(6′)-Ib-cr S83L, D87N A108T 1706 2013 B1 16 8 qnrS1 S83L —b 1763 2013 A 32 64 qnrS1 S83L —b 1878 2014 B1 16 16 oqxAB S83L, D87N S80I 1902 2015 B2 256 32 aac(6′)-Ib-cr S83L, D87N S80I, E84V 1962 2015 A 128 32 qnrB4, aac(6′)-Ib-cr S83L, D87N S80I Abbreviations: CIP, ciprofloxacin; LVX, levofloxacin. aQRDRs of E. coli K-12 (NZ_AKBV01000001.1) as a wild-type reference. bIsolates with no mutations in the GyrA or ParC. Table 4 MICs, antimicrobial resistance genes and plasmid profiles of E. coli isolates used in conjugation experiments. Group and isolate MIC (μg/mL) of antimicrobial agent Presence or absence of PMQR genes Plasmid characterization AMP CAZ CTX FOX TET KN FOS CIP LVX TMP qnrB qnrS aac(6′)- Ib-cr oqxAB β-lactamase No, Size (~Kb)a Replicon(s) Clinical isolates (donors)  534 >256 0.5 0.06 4 2 4 0.5 32 32 1 − − − + blaTEM 2, 50/80 IncFIB, IncFII, IncN  613 8 0.25 0.06 4 128 8 1 4 8 0.25 − +(S1) − − − 3, 60/80/>90 IncFIB, IncFII  906 >256 256 32 256 128 8 1 8 8 >256 − − − + blaTEM, blaCMY-2 4, 7/70/80/90 IncFIB, IncI1, IncFII  1019 >256 256 16 256 8 >256 32 1 2 >256 +(B2) − − − blaTEM, blaSHV-12 1, >90 IncHI2  1377 >256 64 8 256 128 >256 1 16 8 >256 +(B4) − + − blaTEM, blaDHA-1 10, 5/6/7/8/10/50/55/80/90/>90 IncFIB, IncI1, IncFIA  1426 >256 >256 32 >256 4 >256 1 256 256 >256 +(B4) +(S1) − − blaSHV-12, blaDHA-1 6, 7/15/23/50/90/>90 IncHI2, IncN  1516 >256 64 16 64 2 8 0.5 16 16 >256 − +(S1) − − blaCMY-2 7, 5/7/8/9/23/50/90 IncI1, IncFIC, IncFII, IncN  1649 >256 64 8 256 2 >256 1 64 64 >256 +(B4) − − - − 4, 7/23/80/>90 IncFII  1706 >256 0.5 0.06 2 64 8 4 2 8 0.25 − +(S1) − − blaTEM 5, 5/6/8/80/>90 IncFII,  1763 >256 128 8 128 >256 >256 1 32 64 >256 − +(S1) − − blaTEM, blaCMY-2 6, 8/10/55/70/90/>90 IncI1, IncFII,  1962 >256 64 >256 256 128 16 1 128 32 >256 +(B4) − + − blaTEM, blaDHA-1 blaCTX-M-14 8, 5/6/8/9/50/80/90/>90 IncHI2, IncFIB, IncFII, IncFIA, IncN Recipient  C600 4 0.25 0.06 2 2 8 2 <0.03 0.06 0.25 − − − −   − − Transconjugants  534-3 >256 0.25 0.06 2 2 8 2 0.5 0.5 0.5 − − − + blaTEM 1, 50 IncN  613-3 8 0.25 0.06 2 4 4 2 0.5 0.5 0.25 − +(S1) − − − 1, 60 UT  906-4 >256 0.25 0.06 4 2 8 2 0.12 0.25 0.25 − − − + blaTEM 1, 70 IncFII  1019-4 >256 16 1 4 2 >256 2 0.25 0.5 >256 +(B2) − − − blaTEM, blaSHV-12 1, >90 IncHI2  1377-3 256 1 0.12 8 128 >256 1 0.5 0.5 0.25 +(B4) − + − blaTEM, blaDHA-1 1, >90 UT  1426-4 64 4 0.25 32 2 4 2 0.25 0.5 0.25 +(B4) − − − blaDHA-1 1, 90 UT  1426-9 4 0.5 0.06 4 2 4 2 1 1 >256 − +(S1) − − − 1, 50 IncN  1516-3 4 0.25 0.06 2 2 8 2 0.5 1 >256 − +(S1) − − − 1, 50 IncN  1649-2 64 2 0.25 16 1 16 2 0.5 0.5 >256 +(B4) − − − − 1, 80 IncFII  1706-2 >256 0.25 0.06 2 32 4 1 0.5 1 0.25 − +(S1) − − blaTEM 1, 80 IncFII  1763-5 >256 0.25 0.03 4 1 >256 2 1 1 >256 − +(S1) − − blaTEM 1, 90 IncFII,  1962-1 64 2 0.25 32 1 4 2 0.25 0.5 0.25 +(B4) − − − blaDHA-1 1, 90 IncHI2  1962-2 4 0.25 0.06 4 64 32 2 0.25 0.25 >256 − − + − − 1, 50 IncN  1962-3 64 2 0.25 16 64 32 4 0.5 0.5 >256 +(B4) − + − blaDHA-1 2, 50/90 IncHI2, IncN Abbreviations: AMP, ampicillin; CAZ, ceftazidime; CTX, cefotaxime; FOX, cefoxitin; TET, tetracycline; KN, kanamycin; FOS, fosfomycin; CIP, ciprofloxacin; LVX, levofloxacin; TMP, trimethoprim. aNumber and size of plasmids were predicted by the Kato & Liu method with modification9. ==== Refs Drlica K. , Hiasa H. , Kerns R. , Malik M. , Mustaev A. & Zhao X. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3100310.1038/srep31003ArticleHyperuricemia in acute gastroenteritis is caused by decreased urate excretion via ABCG2 Matsuo Hirotaka a1*Tsunoda Tomoyuki 2*Ooyama Keiko 3*Sakiyama Masayuki 14*Sogo Tsuyoshi 2Takada Tappei 5Nakashima Akio 6Nakayama Akiyoshi 1Kawaguchi Makoto 17Higashino Toshihide 1Wakai Kenji 8Ooyama Hiroshi 3Hokari Ryota 9Suzuki Hiroshi 5Ichida Kimiyoshi 610Inui Ayano 2Fujimori Shin 11Shinomiya Nariyoshi 11 Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Tokorozawa, Saitama 359-8513, Japan2 Department of Pediatric Hepatology and Gastroenterology, Saiseikai Yokohamashi Tobu Hospital, Yokohama, Kanagawa 230-0012, Japan3 Ryougoku East Gate Clinic, Sumida-ku, Tokyo 130-0026, Japan4 Department of Dermatology, National Defense Medical College, Tokorozawa, Saitama 359-8513, Japan5 Department of Pharmacy, The University of Tokyo Hospital, Bunkyo-ku, Tokyo 113-8655, Japan6 Division of Kidney and Hypertension, Department of Internal Medicine, Jikei University School of Medicine, Minato-ku, Tokyo 105-8471, Japan7 Department of Urology, National Defense Medical College, Tokorozawa, Saitama 359-8513, Japan8 Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Aichi 461-8673, Japan9 Department of Internal Medicine, National Defense Medical College, Tokorozawa, Saitama 359-8513, Japan10 Department of Pathophysiology, Tokyo University of Pharmacy and Life Sciences, Hachioji, Tokyo 192-0392, Japan11 Department of Internal Medicine, Teikyo University School of Medicine, Itabashi-ku, Tokyo 173-8605, Japana hmatsuo@ndmc.ac.jp* These authors contributed equally to this work. 30 08 2016 2016 6 3100305 04 2016 11 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/To clarify the physiological and pathophysiological roles of intestinal urate excretion via ABCG2 in humans, we genotyped ABCG2 dysfunctional common variants, Q126X (rs72552713) and Q141K (rs2231142), in end-stage renal disease (hemodialysis) and acute gastroenteritis patients, respectively. ABCG2 dysfunction markedly increased serum uric acid (SUA) levels in 106 hemodialysis patients (P = 1.1 × 10−4), which demonstrated the physiological role of ABCG2 for intestinal urate excretion because their urate excretion almost depends on intestinal excretion via ABCG2. Also, ABCG2 dysfunction significantly elevated SUA in 67 acute gastroenteritis patients (P = 6.3 × 10−3) regardless of the degree of dehydration, which demonstrated the pathophysiological role of ABCG2 in acute gastroenteritis. These findings for the first time show ABCG2-mediated intestinal urate excretion in humans, and indicates the physiological and pathophysiological importance of intestinal epithelium as an excretion pathway besides an absorption pathway. Furthermore, increased SUA could be a useful marker not only for dehydration but also epithelial impairment of intestine. ==== Body Hyperuricemia is a common disease which induces gout, and can lead to renal disorder, hypertension, cardiovascular or cerebrovascular diseases1. ATP-binding cassette transporter, subfamily G, member 2 (ABCG2/BCRP) is a high-capacity urate transporter2 and expresses in both intestine3 and kidney4. We and others previously demonstrated that ABCG2 dysfunction by its common variants causes gout256 and hyperuricemia27 by decreasing urate excretion. However, the evaluation of intestinal urate excretion in humans is very difficult due to urate degradation by intestinal bacterial flora. Thus, our previous study8 has revealed the importance of ABCG2 for intestinal urate excretion using Abcg2-knockout mice, but not in humans. In this study, to clarify the physiological role of intestinal urate excretion via ABCG2 in humans, we performed genotyping of ABCG2 dysfunctional variants in end-stage renal disease (hemodialysis) patients whose serum uric acid (SUA) levels are extremely elevated910 and urate excretion almost depends on intestinal excretion via ABCG2 because of their almost complete absence of renal urate excretion. Furthermore, to investigate the pathophysiological role of intestinal urate excretion via ABCG2 in intestinal diseases, we also performed genotyping of ABCG2 dysfunctional variants in acute gastroenteritis patients whose ABCG2 function of intestinal urate excretion should be seriously impaired due to damage to the intestinal epithelium. Results Genotyping of ABCG2 Genotyping results of the two ABCG2 dysfunctional variants, Q126X (rs72552713) and Q141K (rs2231142), for 106 hemodialysis patients, 106 sex- and body mass index (BMI)-matched health examination participants and 67 acute gastroenteritis patients, were shown in Table 1. The call rates for both variants were 100%, and they were in Hardy-Weinberg equilibrium (P > 0.05). Haplotype frequency of Q126X and Q141K was estimated as shown in Supplementary Table 1. This result indicates that there is no simultaneous presence of the minor allele of Q126X (“T” allele) and Q141K (“A” allele) in one haplotype, which is consistent with our previous study2. Therefore, we presumed the diplotypes of all samples as shown in Table 1. In this study, all of the participants were divided into three groups (full function, 3/4 function and ≤1/2 function) based on estimated ABCG2 function for the following analyses. Analysis of hemodialysis patients The estimated ABCG2 function of 106 hemodialysis patients and the mean SUA for each group were shown in Table 2. The less activity the ABCG2 function showed the higher the SUA (7.1 mg/dl for full function, 7.9 mg/dl for 3/4 function and 8.4 mg/dl for ≤1/2 function), and multiple regression analysis revealed that ABCG2 dysfunction significantly elevated SUA (P = 1.1 × 10−4). On the other hand, in 106 sex- and BMI-matched health examination participants, ABCG2 dysfunction tended to elevate SUA (5.3 mg/dl for full function, 5.0 mg/dl for 3/4 function and 6.0 mg/dl for ≤1/2 function), although not significantly (P = 0.36, Table 2). Analysis of acute gastroenteritis patients The SUA levels of 67 patients were measured during an acute period of gastroenteritis. Additionally, the SUA levels of 55 patients were measured during the recovery period from gastroenteritis. The mean SUA levels of the acute and recovery period (Table 2) were 8.8 mg/dl and 4.7 mg/dl, respectively, and the paired t-test showed a significant difference between them (P = 2.3 × 10−12). The number of patients, who were divided into three groups by estimated ABCG2 function, and the mean SUA levels at the acute and recovery period of gastroenteritis were shown in Table 2. In the acute period, ABCG2 dysfunction significantly elevated SUA (7.5 mg/dl for full function, 9.6 mg/dl for 3/4 function and 10.6 mg/dl for ≤1/2 function, P = 6.3 × 10−3), and the degree of dehydration also affected SUA (P = 1.6 × 10−3, Supplementary Table 2). However, ABCG2 dysfunction was not associated with the degree of dehydration in the acute period (P = 0.50, Table 3) and the significant association between ABCG2 dysfunction and SUA remained after the adjustment for the degree of dehydration (P = 7.8 × 10−3), indicating that the association between ABCG2 dysfunction and SUA was not due to dehydration. Regarding the recovery period, there was a trend for SUA to increase by ABCG2 dysfunction (4.2 mg/dl for full function, 4.9 mg/dl for 3/4 function and 5.4 mg/dl for ≤1/2 function, Table 2), but it was not significant (P = 0.10). Discussion ABCG2, which mediates urate excretion, expresses in both intestine3 and kidney4. About two-thirds of urate is excreted from kidney and about one-third from intestine1112. This is consistent with our previous study using Abcg2-knockout mice8. However, ABCG2-mediated intestinal urate excretion has not been directly shown by human study. In end-stage renal disease (hemodialysis) patients whose SUA levels are extremely elevated910, renal urate excretion is nearly completely absent, and almost all urate excretion must depend on intestinal excretion via ABCG2. Thus, it was supposed that the degree of intestinal ABCG2 dysfunction strongly affects the severity of hyperuricemia in hemodialysis patients (Fig. 1), as was shown by multiple regression analysis in the present study (Table 2). This finding is the first evidence for a physiological role of ABCG2 on intestinal urate excretion in humans. Besides the physiological role for intestinal urate excretion via ABCG2 in humans, we for the first time demonstrated that hyperuricemia in acute gastroenteritis patients is caused by decreased urate excretion in addition to dehydration which is generally considered to be a major cause of hyperuricemia in acute gastroenteritis patients13. Pathogens which cause acute gastroenteritis, such as rotaviruses, primarily infect the villus epithelium of the small intestine14151617. These viruses induce the destruction of infected intestinal epithelial cells, but they also mediate the down-regulation of the expression of absorptive enzymes, transporters and cytokines, which instigate malabsorption of D-xylose, lipid or lactose141718. In acute gastroenteritis patients, intestinal inflammation would also seriously impair the function of intestinal urate excretion of ABCG2, which could be one of the reasons why SUA is markedly increased in acute gastroenteritis patients. Therefore, it is clearly possible that the degree of renal ABCG2 dysfunction affects the severity of hyperuricemia in gastroenteritis patients (Fig. 1), as was first shown by linear regression analysis in acute period gastroenteritis patients in the present study (Table 2). The evaluation of intestinal urate excretion in humans is very difficult because urate excreted into the intestinal lumen is rapidly metabolized by bacterial flora. Thus, our previous study8 could reveal the importance of ABCG2 for intestinal urate excretion not using human, but rather Abcg2-knockout mice treated with oxonate, an uricase inhibitor. In addition, another study has also reported the decreased intestinal excretion and increased plasma concentration of uric acid in Abcg2-knockout mice19. Taking into account the results from both hemodialysis and acute gastroenteritis patients in the present study, we for the first time demonstrated that ABCG2 mediates intestinal urate excretion in humans, which suggests the physiological importance of intestinal epithelium as an excretion pathway besides an absorption pathway. In addition, if an end-stage renal disease patient develops acute gastroenteritis, both renal and intestinal urate excretion via ABCG2 will extremely decrease, and thereby greatly elevate SUA. In light of these findings, although further studies would be necessary because of the limited sample size in this study, we proposed a physiological model of urate excretion via ABCG2 in humans, and a pathophysiological model of hyperuricemia in intestinal and renal diseases (Fig. 1). Physiologically, ABCG2 mediates urate excretion in both intestine and kidney in humans. Pathophysiologically, in end-stage renal disease patients, the degree of intestinal ABCG2 dysfunction strongly affects the severity of hyperuricemia because urate excretion almost all depends on intestinal excretion via ABCG2. Contrarily, in acute gastroenteritis patients, the function of intestinal urate excretion via ABCG2 is severely impaired. Therefore, the degree of renal ABCG2 dysfunction clearly affects the severity of hyperuricemia. By this proposed model, physicians will recognize that increased SUA levels could be a useful marker not only for dehydration but also for intestinal impairment which induces urate export failure in intestines. Physicians could also consider “the urate excretion failure due to intestinal impairment” as one of the common causes of hyperuricemia which is often complicated in patients with acute gastroenteritis. In summary, we revealed that two common dysfunctional variants (Q126X and Q141K) of ABCG2 have a significant negative effect on both intestinal and renal urate excretion in humans, and that intestinal and renal ABCG2 dysfunction markedly increases SUA in end-stage renal disease and acute gastroenteritis. These findings for the first time demonstrated the physiological and pathophysiological roles of ABCG2 on intestinal urate excretion in humans. Methods Participants This study was approved by the institutional ethical committee of the National Defense Medical College, and all procedures were performed in accordance with the Declaration of Helsinki with written informed consent from each subject. When the participant was a minor, written informed consent was obtained from each parent or guardian of that participant. Degree of dehydration in acute gastroenteritis patients was evaluated by physicians (T. Tsunoda and T.S.) according to the criteria recommended by the Center for Disease Control (CDC)20, and classified as “minimal or no dehydration”, “mild to moderate dehydration”, and “severe dehydration”. In order to clarify the physiological role of intestinal urate excretion via ABCG2, 106 maintenance hemodialysis patients not taking medications for hyperuricemia were assigned from among the outpatients at Ryougoku East Gate Clinic (Tokyo, Japan). Their SUA levels were measured three times just before each maintenance hemodialysis, and the average was used for analyses. In addition, 106 sex- and BMI-matched subjects were selected from health examination participants in the Shizuoka area in the Japan Multi-Institutional Collaborative Cohort Study (J-MICC Study)2122. Sixty-seven pediatric patients with acute gastroenteritis were also recruited at the Department of Pediatric Hepatology and Gastroenterology in Saiseikai Yokohamashi Tobu Hospital (Yokohama, Japan). Their SUA levels were measured twice at the acute and recovery period of gastroenteritis. The details of participants in this study are shown in Supplementary Table 3. Genetic analysis and estimation of ABCG2 function Genomic DNA was extracted from whole peripheral blood cells23. Genotyping of ABCG2 dysfunctional variants, Q126X (rs72552713) and Q141K (rs2231142), was performed using the TaqMan method (Life Technologies Corporation, Carlsbad, CA, USA) with a LightCycler 480 (Roche Diagnostics, Mannheim, Germany) as previously described24. Custom TaqMan assay probes were designed as follows: for Q126X, VIC-CCACTAATACTTACTTGTACCAC and FAM-CCACTAATACTTACTTATACCAC; for Q141K, VIC-CTGCTGAGAACTGTAAGTT and FAM-CTGCTGAGAACTTTAAGTT. To confirm their genotypes, DNA sequencing analysis was performed with the following primers: for Q126X, forward 5′-TGTACAATGAAAAGAGAAAGGTGAG-3′ and reverse 5′-CTGCCTTTTCACATAAGTGTC-3′; for Q141K, forward 5′-ATGGAGTTAACTGTCATTTGC-3′ and reverse 5′-CACGTTCATATTATGTAACAAGCC-3′. Direct sequencing was performed with a 3130xl Genetic Analyzer (Life Technologies Corporation)2324. We previously reported that Q126X is a nonfunctional variant, Q141K is a half-functional variant for urate excretion compared to the wild-type, and that there was no simultaneous presence of the minor alleles of Q126X and Q141K in one haplotype2, which is confirmed in the participants of the present study (Supplementary Table 1). Thus, three haplotypes were defined as *1 (126Q and 141Q), *2 (126Q and 141K) and *3 (126X and 141Q) as previously reported25, and all patients could be divided into the following ABCG2 functional groups: full function (*1/*1), 3/4 function (mild dysfunction, *1/*2), 1/2 function (moderate dysfunction, *1/*3 or *2/*2), and ≤1/4 function (severe dysfunction, *2/*3 or *3/*3)25 as shown in Table 1. Statistical analysis For all calculations in the statistical analysis, the software R (version 3.1.1) (http://www.r-project.org/) was used26. Comparison of SUA between the acute and recovery period of gastroenteritis was performed with a paired t-test using a two-tailed P value. Linear regression analysis was performed to test the hypothesis that there was no relation between ABCG2 dysfunction and SUA in the analysis of acute gastroenteritis patients. Multiple regression analysis including ABCG2 function and age in the model was used for the analysis of hemodialysis patients and sex- and BMI-matched health examination participants, because age could not be completely matched in the selection from health examination participants. The association between ABCG2 and dehydration was examined using the Cochran-Armitage trend test. Haplotype estimation was performed with the EM algorithm27 using the package haplo.stats of the software R. We set the significance threshold as α = 0.05. Additional Information How to cite this article: Matsuo, H. et al. Hyperuricemia in acute gastroenteritis is caused by decreased urate excretion via ABCG2. Sci. Rep. 6, 31003; doi: 10.1038/srep31003 (2016). Supplementary Material Supplementary Information The authors are deeply grateful to all of the individuals who participated in this study. We are also indebted to K. Gotanda, Y. Morimoto, M. Miyazawa, S. Shimizu, T. Chiba, Y. Kawamura, T. Nakamura, H. Nakashima and Y. Sakurai of the National Defense Medical College for their genetic analysis and valuable discussions, and to A. Tokumasu of the Ryougoku East Gate Clinic, and M. Naito and N. Hamajima of the Nagoya University Graduate School of Medicine, for sample collection. This work was supported by grants from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan including the MEXT KAKENHI (Grant numbers 221S0001, 221S0002, 25293145, 26461244, and 15K15227), the Ministry of Health, Labour and Welfare of Japan, the Ministry of Defense of Japan, the Gout Research Foundation of Japan and the Kawano Masanori Memorial Foundation for Promotion of Pediatrics. Yes, there is potential competing interest: H.M., T. Takada, K.I. and N.S. have a patent pending based on the work reported in this paper. Other authors have declared that no competing interests exist. Author Contributions H.M., T. Tsunoda, K.O. and M.S. conceived and designed this study. H.M., T. Tsunoda, K.O., M.S., T.S., K.W., H.O., A.I. and S.F. collected samples and analyzed clinical data. H.M., M.S., A. Nakayama, M.K. and T.H. performed genetic analysis. H.M. and M.S. performed statistical analyses. A. Nakashima, T. Takada, R.H., H.S., K.I., A.I., S.F. and N.S. provided intellectual input and assisted with the preparation of the manuscript. H.M., T. Tsunoda, K.O. and M.S. wrote the manuscript. Figure 1 Pathophysiological model of ABCG2-mediated urate excretion in end-stage renal disease and acute gastroenteritis patients. SUA, serum uric acid. ABCG2 physiologically mediates urate excretion in both intestine and kidney. In end-stage renal disease (renal failure) patients, renal urate excretion would be nearly eliminated with urate excretion depending almost entirely on intestinal excretion. Thus, the degree of intestinal ABCG2 dysfunction strongly affects the severity of hyperuricemia in renal diseases such as end-stage renal disease. On the other hand, in acute gastroenteritis patients, intestinal inflammation seriously impairs the intestinal urate excretion via ABCG2. Therefore, the degree of renal ABCG2 dysfunction markedly affects the severity of hyperuricemia in intestinal diseases such as acute gastroenteritis patients. Table 1 Genotyping results for each estimated ABCG2 function of participants. Estimated ABCG2 function Rs72552713 (Q126X) Rs2231142 (Q141K) Diplotype* Number of participants Hemodialysis Health examination† Acute gastroenteritis Full function C/C C/C *1/*1 51 50 29 3/4 function C/C C/A *1/*2 46 41 30 1/2 function C/C A/A *2/*2 4 8 7   C/T C/C *1/*3 3 5 1 ≤1/4 function C/T A/C *2/*3 2 2 0   T/T C/C *3/*3 0 0 0 Total       106 106 67 **1, *2 and *3 represent haplotypes “C-C” (126Q and 141Q), “C-A” (126Q and 141K) and “T-C” (126X and 141Q) of two dysfunctional variants, Q126X (rs72552713) and Q141K (rs2231142), respectively. †106 health examination participants were matched for sex- and body-mass index to 106 hemodialysis patients and selected from J-MICC Study. Table 2 Estimated ABCG2 function and SUA of hemodialysis patients and acute gastroenteritis patients. Estimated ABCG2 function (Diplotype of Q126X and Q141K)* Hemodialysis Acute gastroenteritis Case Control† Acute period Recovery period N SUA (mg/dl) β (SEM)‡ P value§ N SUA (mg/dl) β (SEM)‡ P value§ N SUA (mg/dl) β (SEM)‡ P value|| N SUA (mg/dl) β (SEM)‡ P value|| Full function (*1/*1) 51 7.1 ± 0.1   50 5.3 ± 0.2   29 7.5 ± 0.5   24 4.2 ± 0.3   3/4 function (*1/*2) 46 7.9 ± 0.1   41 5.0 ± 0.2   30 9.6 ± 0.7   24 4.9 ± 0.4   ≤1/2 function (*1/*3, *2/*2, *2/*3 or *3/*3) 9 8.4 ± 0.7   15 6.0 ± 0.3   8 10.6 ± 1.4   7 5.4 ± 0.6   Total 106 7.5 ± 0.1 0.63 (0.16) P = 1.1 × 10−4 106 5.3 ± 0.1 0.17 (0.18) P = 0.36 67 8.8 ± 0.4 1.73 (0.61) P = 6.3 × 10−3 55 4.7 ± 0.2 0.60 (0.36) P = 0.10 N, number; SUA, serum uric acid. Plus-minus values are means ± SEM. **1, *2 and *3 represent haplotypes of two dysfunctional variants (Q126X and Q141K) as previously reported. Detailed information on ABCG2 haplotypes is also shown in Table 1. †106 controls were matched for sex- and body-mass index to 106 hemodialysis patients and selected from health examination participants in J-MICC Study. ‡β means regression coefficient. §P values were obtained by multiple regression analysis including ABCG2 function and age in the model. ||P values were obtained by linear regression analysis. Table 3 Dehydration in acute gastroenteritis patients for each ABCG2 function. Estimated ABCG2 function (Diplotype of Q126X and Q141K)* Number P value‡ Acute gastroenteritis Dehydration† − + Full function (*1/*1) 29 23 6   3/4 function (*1/*2) 30 20 10   ≤1/2 function (*1/*3, *2/*2, *2/*3 or *3/*3) 8 6 2   Total 67 49 18 0.50 **1, *2 and *3 represent haplotypes of two dysfunctional variants (Q126X and Q141K). 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3217310.1038/srep32173ArticleRole of IL-17 Pathways in Immune Privilege: A RNA Deep Sequencing Analysis of the Mice Testis Exposure to Fluoride Huo Meijun 1Han Haijun 1Sun Zilong 1Lu Zhaojing 1Yao Xinglei 1Wang Shaolin a2Wang Jundong b11 Shanxi Key Lab of Environ-Veterinary Science, College of Animal Science and Technology, Shanxi Agricultural University, Taigu, Shanxi, 030801, People’s Republic of China2 Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agriculture University, Beijing, 100193, People’s Republic of Chinaa shaolinwang@outlook.comb wangjd53@outlook.com30 08 2016 2016 6 3217311 05 2016 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/We sequenced RNA transcripts from the testicles of healthy male mice, divided into a control group with distilled water and two experimental groups with 50 and 100 mg/l NaF in drinking water for 56 days. Bowtie/Tophat were used to align 50-bp paired-end reads into transcripts, Cufflinks to measure the relative abundance of each transcript and IPA to analyze RNA-Sequencing data. In the 100 mg/l NaF-treated group, four pathways related to IL-17, TGF-β and other cellular growth factor pathways were overexpressed. The mRNA expression of IL-17RA, IL-17RC, MAP2K1, MAP2K2, MAP2K3 and MAPKAPK2, monitored by qRT-PCR, increased remarkably in the 100 mg/L NaF group and coincided with the result of RNA-Sequencing. Fluoride exposure could disrupt spermatogenesis and testicles in male mice by influencing many signaling pathways and genes, which work on the immune signal transduction and cellular metabolism. The high expression of the IL-17 signal pathway was a response to the invasion of the testicular immune system due to extracellular fluoride. The PI3-kinase/AKT, MAPKs and the cytokines in TGF-β family were contributed to control the IL-17 pathway activation and maintain the immune privilege and spermatogenesis. All the findings provided new ideas for further molecular researches of fluorosis on the reproduction and immune response mechanism. ==== Body Epidemiological investigations showed male infertility, low birth rates and abnormalities in sperm morphology, oligospermia and azoospermia occurring in areas with a high fluoride content1234567. Even in 2008 and 2009, Bruce Spittle, Managing Editor of the Journal Fluoride, published two articles in two consecutive years and emphatically stated the adverse effects of fluoride on male reproductive function78. Further studies in animals indicated a negative impact of fluoride ingestion on testicular histology, the structure of hypothalamus-pituitary-testicular and sperm quality9, including: sperm malformation7101112, sperm density, motility and activity81314, spermchemotaxis15, sperm hyperactivation, capacitation, acrosome reaction and fertilizing ability16. But how does fluoride affect male reproductive function with regard to the mechanism? It has been widely reported in the male reproductive systems that spermatogenesis was formed in testes and regulated by the hormone testosterone, cytokines and gene and protein expressions1718. Meanwhile, our previous studies and many hazard identification studies also revealed that high doses of fluoride in animals affect potentially sensitive reproductive-tract targets and pathways, such as the reduction of antioxidant defenses, the enhancement of oxidative stress, and changes in the testicular cell cycle19202122. Overall, a number of studies have indicated fluoride exposure disrupts testicular development, but most of them focused on pathological observation and a limited number of genes so that up to now the specific molecular mechanisms of fluoride-induced spermatogenesis dysfunction were not clear. Due to the complexity of molecular mechanisms, high throughput methods are quite necessary and playing more and more important roles in the research of toxicology. Moreover, the matured transcriptome sequencing (RNA-Seq) platforms have been successfully applied to the detection of gene fusions in cancer23, the analysis of vaccinia virus and host cell transcriptomes24 and the quantitative calculation of the abundance of expressed genes among the tissue transcriptome sequence data25. Thus, the deep RNA-Seq was applied to focus on genes and biological pathways affected by fluoride using and experimental validation to uncover the molecular basis of reproduction and sperm metabolism disorder. Delineating the overall gene expression profile in the testicles of experimental fluorosis mice will help to deeply identify the mechanisms involved in reproductive toxicity and other pathological disorders associated with fluoride. Methods Animals Sixty adult male Kunming mice (aged 8 weeks, 25–26 g b.w.) were purchased from the Experimental Animal Center of Shanxi Medical University (Taiyuan, China), housed in standard plastic cages, maintained in a temperature-controlled environment (22–25 °C) with a 12 h light/dark cycle and fed a standard mouse diet and water ad libitum. After one-week acclimation, these mice were divided randomly into three groups of 20 each: a control group, which drank distilled water, and other two treatment groups, which received 50 and 100 mg/l NaF in their drinking water. The doses were chosen on the basis of the previous studies and considered the toxicities of fluoride in the male reproductive system262728. To make sure of more than four spermatogenic cycles in mice (approximately 40 days)13, animals were treated with fluoride for 56 days. It’s important to note that in our previous research no significant differences were observed in body weight and major organ coefficient (testis/body weight) compared with the control group after 56 days fluoride exposure915. Based on that, we can probably rule out the influence of body weight change on the testicular in itself. Meanwhile, the formal study has found the decreased sperm and disorganized spermatogenic cells with the morphological observations of testis, more severely in high F group. And in Sertoli cells, we observed the density of cytoplasm decreased, heterochromatin gathered and mitochondria appeared with numerous vacuoles. All of these provided the support for sequence analysis. Statement: All experimental procedures were conducted and performed as the policies for animal care and use encompass regulations approved by the Institutional Animal Care and Use Committee of Shanxi Agricultural University, including Animal Welfare Act, Guide for the Care and Use of Laboratory Animals and Guide for the Care and Use of Agricultural Animals in Research and Teaching. RNA Sample Preparation All mice were killed by cervical dislocation on the 56th day, testicles were immediately isolated, frozen in liquid nitrogen and stored at −80 °C for RNA extraction and gene expression research. Total RNA was extracted from five tissue samples in each group using TRIzol (Invitrogen, Carlsbad, CA, USA) according to the protocol provided by the manufacturer. The quality and purity of total RNA were monitored by Nanodrop ND-2000 spectrophotometer (Nanodrop Technologies Inc., DE, USA) and electrophoresing on a 0.8% agarose gel (Sigma, St. Louis, MO), respectively. RNA Deep Sequencing Based on the recently published papers, RNA deep sequencing was conducted as follows2930. Briefly, the sequencing library of each RNA sample was prepared with the TruSeq RNA Sample Preparation Kit according to the manufacturer’s instructions (Illumina, San Diego, CA). The enriched libraries were diluted with elution buffer to a final concentration of 10 nM. Each sample (ca. 7 pM concentration) was subjected to 50 cycles of sequencing from both ends by the Illumina HiseqTM 2000 sequencing technology. Before doing any further analysis, FastQC (http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/) was applied to perform quality control checks on raw sequence data coming from high throughput sequencing pipelines. Following deep sequencing analysis of 50-bp length paired-end reads, Bowtie and Tophat were used to align the reads into transcripts based on the Mouse Reference Genome (ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/m_musculus_ncbi37_c.ebwt.zip). To measure the relative abundance of each transcript, the resulting aligned reads were analyzed with Cufflinks suite (http://cufflinks.cbcb.umd.edu). Expression of each transcript was quantified as the number of reads mapping to a gene divided by the gene length in kilobases and the total number of mapped reads in millions, and designated as fragments per kilobase of exon per million fragments mapped (FPKM). Gene Annotation and Expression Profiling Analysis The Ensembl Transcript ID was used as the primary identifier for all analyses. When multiple splice variants existed, all of them were selected. In generating the FPKM distributions of intergenic regions, regions with a distance of at least 10 kb from any RefSeqor Ensembl gene were selected. The annotation information corresponding to each Ensembl Transcript ID was retrieved from the Ensembl database via BioMart (http://www.biomart.org/biomart/martview). For each fluoride concentration of interest, all the transcripts were pulled from the file generated by Cufflinks. The measurements with RPKM values close to zero (approximately 5% of the total) were discarded. The RPKM values were logarithmically transformed to base 2, and the measurements of each transcript within an experimental group were subjected to outlier detection2930. Enriched Biochemical Pathways in the Fluorosis Testicle Ingenuity Pathway Analysis (IPA, Ingenuity System Inc, USA, http://www.ingenuity.com/) were used to alter the significant genes, identify global canonical pathways and dynamically generate biological networks in the testicle of experimental fluorosis mice3132. The core component of IPA is the Ingenuity Pathways Knowledge Base (IPKB), which contains the biological function, interaction, and related information of a curated gene set and more than 330 biochemical pathways31. Using the whole gene set of IPKB as the background, the genes with their symbols and the corresponding GenBank accession numbers were uploaded into the IPA with a view to revealing the enriched biochemical pathways2930. All the pathways with one or more genes overlapping the candidate genes were extracted. In IPA, each of the canonical pathway was assigned a P value via Fisher’s exact test, which denoted the probability of overlap between the pathway and input genes33. Reported significance was defined as P < 0.05 with a fold change (FC) larger than 1.5. Quantitative Real Time RT-PCR Quantitative real-time RT-PCR (qRT-PCR), the traditional quantification method on gene expression, was adopted to further confirm the findings from the RNA-seq analysis. On the basis of the results, we optionally detected several significant genes involved in the IL-17 signaling pathway with the same RNA samples used for RNA-seq analysis, considering they are the only pathways showing differences in the testicle of all the fluorosis groups. These genes and their primers used in the qRT-PCR array were listed in Supplementary Table S1. Primers were designed using Primer Express v. 3.0 software (Applied Biosystem Inc., CA, USA). The qRT-PCR analysis was conducted in a total volume of 10 μl containing 5 μl 2 × SYBR Premix Ex TaqTM (Takara Bio Inc., China), combined with sense and antisense primers (0.4 μl, final concentration 250 nM), and 1 μl diluted cDNA in a 384-well plate using the Applied Biosystems QuantStudioTM 7 Flex Real-Time PCR System (Thermo Fisher Scientific, USA). The conditions for real-time PCR were as follows: after initial denaturation at 95 °C for 15 s, 55 PCR cycles were started with thermo cycling conditions at 95 °C for 5 s, 61 °C for 15 s, and 72 °C for 6 s, and then a melting curve analysis was performed to verify the specificity of the PCR product. Every sample was analyzed in triplicate. System software and the 2−ΔΔCt method were applied to quantitative calculation. Data Analysis for qRT-PCR All data were conducted by GraphPad Prism 5 software (GraphPad Software Inc., San Diego, USA). Statistical analysis was performed by one-way ANOVA and followed by a Tukey’s test. All values in the experiment were expressed as mean ± SEM (standard error of the mean) and values of P < 0.05 were expressed statistically significant (n = 5 per group). Result Overview of Sequencing Data from RNA-seq Analysis Sequencing and mapping quality were analyzed using FASTQC. Total sequences among samples ranged from 30 to 37 million reads, with an average of approximately 31 million raw reads per sample. About 23–32 × 106 reads (82–84% of the total raw reads) were uniquely aligned to mouse genome sequence among samples, with an average of 24 × 106 reads per sample. Identification of Genes and Pathways Altered in Testicle Analysis of the data indicated that there were 120 and 298 differentially expressed genes in the 50 mg/l and 100 mg/l NaF-treated groups, respectively. To further understand these changes at the pathway level, an IPA analysis was conducted and showed 99 and 246 genes mapped with corresponding GenBank, meanwhile, 19 and 33 signaling pathways to be significantly altered in the two treated groups separately (Fig. 1). In the overview, a huge variety of the pathways with the different biological functions were identified by IPA in each treatment group. Study found that in the 50 mg/l NaF-treated group there was a significant influence on the communication signals between cells and cell biological mechanisms, related to the cellular growth, proliferation & development. However, it was noteworthy that 14 signaling pathways mainly focused on the immune responses in the 100 mg/l NaF-treated group, and among them the interleukin-17 (IL-17), IL-17A and other two signaling transduction pathways presented the close association with the regulation of the IL-17 family and IL-17 receptors, which laid the foundation for validating the predicted genes. There were 7 signaling pathways altered in both the NaF-treated groups as listed in Fig. 2. These signals were highly related with oxidative stress, cell development and cell apoptosis. Axonal Guidance Signaling and EphrinB Signaling pathway were associated with neurotransmission and altered in both the treatments. In addition, for further information about the relationships between the differentially expressed genes and toxicology, 36 signaling pathways interacted in toxicity and were identified by IPA in the 100 mg/l NaF-treated group. Among them, four pathways were significantly altered, as listed in Fig. 3. Also four of them were highly relevant to cell differentiation and apoptosis as well as oxidative metabolism, including the transforming growth factor beta (TGF-β) signaling pathway, glutathione depletion reactions and NRF2-mediated oxidative stress response, especially the TGF-β signaling pathway involved in many cellular processes and commonly inducing the production of cytokines. Description of Important and Representative Genes in Testicle In the perspective of gene functions, based on gene function annotation by IPA, 367 differentially expressed genes (DEGs) were screened both in the 50 mg/l and 100 mg/l NaF-treated groups when compared with the control group. All the genes were grouped into various functional categories, and the relationship among genes and functions, diseases were presented accurately. In Fig. 4, the percentage of genes that worked on the reproductive system development and function reached up to 12.26%. About 10.90% and 7.08% were related to cell signaling and cellular growth and proliferation, respectively. More than 7.08% genes worked on skeletal and muscular disorders. Almost 56.38% genes were participating in the process of cell metabolism. It was found that the same gene may plays a different role in multiple metabolic processes. In the perspective of pathways, shown in the Fig. 5, it has already suggested a correlation among the high-expression pathways identified by IPA software. These figures told us that many common genes were working on the regulation by the different signal pathways. Therefore, the interaction of multiple genes were concerned. Just as shown in the Table 1, in the testicle of mice treated with different fluoride concentrations, there were nine important and representative genes that appeared in more than four pathways, even MAP2K2 were directly involved in the regulation of almost 20 significant pathways. All of MAP2K2, PIK3R1, MAP2K3, MAPKAPK2 and IL17RC participated in the IL-17 intracellular metabolic processes (Fig. 6). Expression Analysis by qRT-PCR Based on the RNA-seq analysis of the pathways, nine genes, including IL17A, IL17RA, IL17RC, MAP2K3, MAP2K6, PIK3R1, MAPKAPK2, MAP2K1 and MAP2K2, representing the IL-17 signaling pathway described above were selected for confirmation as well as to monitor their expression with qRT-PCR, and the data was statistically analyzed as follows (Fig. 7). Compared with control group, in the 100 mg/l NaF-treated group the mRNA expression level of IL17RA, IL17RC, MAP2K1, MAP2K2, MAP2K3 and MAPKAPK2 increased remarkably. The gene expression of MAP2K6 and PIK3R1 reduced gradually. There was not significant changes in the gene expression of 50 mg/l NaF-treated group. Besides that, the linear regression analysis of the fold change of the gene expression ratios between RNA-seq and qRT-PCR showed significantly positive correlation (Supplementary Fig. S1), confirming our transcriptome analysis. Discussion Although fluoride is safe and even healthy at low concentrations, sustained consumption of large amounts of soluble fluoride salts is dangerous. It was well known that toxic levels of fluoride exposure over a long period of time can adversely cause skeletal and tooth fluorosis induced by oxidative stress of osteoblasts and osteoclasts343536. It also can lead to some adverse effects on a number of physiological functions, for example, thyroid dysfunction37, nephrotoxicity3538, cardiometabolic risk3940, neurodevelopmental disorder in juvenile stage384142 and even male reproductive endocrine disruption78. However, the mechanisms of reproduction injury induced by taking in excess fluoride were still inconclusive. Attempting to address the root cause, this experiment was the first time using the transcriptome sequencing in the testicle of experimental fluorosis mice to explore the relative gene expression levels in mouse testis and interpret the effect of fluoride poisoning in the male reproductive system. Different from earlier studies, our study considered the damages of fluoride on the male reproductive system holistically, including a variety of pathways and genes, rather than just a single factor. Generally, the testis and the capacity of sperm were of the important indices for evaluating the reproductive system. The testis comprises mostly seminiferous tubules and interstitial cells, localized between seminiferous tubules, to produce and secrete testosterone43. The epithelium of the tubule consists of a type of sustentacular cells known as Sertoli cells, which differentiate through meiosis into sperm cells. During spermatogenesis, the main function of Sertoli cells is to nourish the developing sperm cells and also act as phagocytes, consuming the residual cytoplasm and secreting the inhibin, activins and androgen binding protein44. While our previous studies reported that the pathologic and morphological changes of chronic fluorosis in testicles and sperm were observed. The cavitation of seminiferous tubules, cellular atrophy and other structural damages can result in the reduction of androgen binding protein synthesis and the inadequate amounts of testosterone, which, in turn, can cause spermatogenesis to be blocked and spermatid developed abnormally with different morphology. Song Ke qin et al.45 also found the distention and vesiculization of smooth endoplasmic reticulum and the deposition of large lipid droplets appearing in the Sertoli cells under the ultrastructural observations of rat testes. So what happened in these cells? Mendoza-Schulz A. et al.46 said that fluoride had significantly effect on hormone secretion and protein synthesis in the endocrine cells. They found the changes in phosphorylation status of both cytoskeletal and cytosolic protein fractions, as well as in actin cytoskeletal arrangements were observed. Similarly, in our research of the 50 mg/l NaF-treated group, actin nucleation and actin cytoskeleton signal pathways were stimulated with the significant expression of growth factors. In response to these microenvironmental and functional alterations, immune cells often represent dramatically change their functional activities to reprogram their cellular metabolism and release the metabolic stresses47. A lymphocyte, such as T cells, transforms from a relatively inert cell to a cell engaging in robust growth and proliferation, often producing large amounts of effector molecules, including cytokines47. Yet despite all that, there is emerging evidence that metabolic enzymes and regulators can also have a direct role in controlling immune cell functions47. For instance, in CD4 T cells, GAPDH has been described to bind to IL2 mRNA and inhibit translation. Accordingly, the testicular immunological efficiency was enhanced along with the increase of doses of fluoride. Although the testis is an immune privileged organ and the most important spaces of spermatogenesis and steroidgenesis, toxic agents and inflammation may overwhelm immune suppressor mechanisms inducing autoimmune reactions against spermatic antigens which result in aspermatogenesis and infertility18. The cytokine interleukin-17, ukin-17 (IL-17 or IL-17A) and the pathology associated with aberrant IL-17 signaling played an important role in maintaining the testicular immune including cell immunity, mucosal immunity and cytokines, especially in experimental autoimmune orchitis (EAO)184849. Jacobo P. et al.49 reported that in EAO testis developed by active immunization with spermatic antigens, testis-infiltrating cells revealed an increased number of macrophages, dendritic cells and T cell subsets including Th17 cells so that TNF-α, IL-17 and other immune cells secreted pro-inflammatory cytokines, which disrupted the normal testicular immune suppressor microenvironment. And they said IL-17 cells in EAO testis have a mature immunogenic status and are able to induce immune responses to testicular antigens. In many cases, an excess of IL-17 is associated with abnormal inflammation, implicated in rheumatoid arthritis, asthma, psoriatic arthritis, ankylosing spondylitis, systemic lupus erythematosus and autoimmune encephalomyelopathy, which, not surprisingly, have become a major therapeutic target for these diseases. It have been recently found Th17 cells are a subset of T helper cells and play important functions in host defense and the pathogenesis of various human autoimmune and inflammatory diseases505152. Th 17 cells could produce IL-17A, who would mediate many of the downstream pathologic functions in the cells. IL-17A utilizes IL-17RA and IL-17RC as its receptors that are mainly expressed on tissue epithelial cells and fibroblasts. While IL-17A is important for host defense against many extracellular pathogens, they can also cause excessive tissue damage and exacerbate proinflammatory responses during autoimmunity52. Therefore, as for our study, the IL-17 signal pathway and its proinflammatory cytokines were expressed in higher levels in high fluoride-exposed testis (100 mg/l NaF). It was the response to the invasion of the immune system by extracellular fluoride and involve in the maintenance of testicular immune privilege and spermatogenesis53. And the activation of toll-like receptors IL-17RA and IL-17RC suggested that these cells played important roles in protecting the seminiferous epithelium from invading fluoride. During this study we also found the transforming growth factor beta (TGF-β) signaling pathway has the most important research value in the toxicology field. TGF-β signaling pathway is involved in many cellular processes in both the adult organism and the developing embryo including cell growth, cell differentiation, apoptosis, cellular homeostasis and other cellular functions545556. TGF-βs belong to a family of the immunosuppressive and anti-inflammatory TGF superfamily and widely distributed in embryonic and adult tissues18. Most TGF-βs are present in the testis as the latent inactive precursor form and are expressed constitutively at high levels being produced mainly by Sertoli cells, Leydig cells, and peritubular, but in post pubertal testis, cytokines of the TGF-β family are also expressed by early spermatids and spermatocytes. Once activated at its site of action by local proteases, TGF-βs would contribute to the immunological privileged site of the testis through their strong immunosuppressive ability1852. Thus, what we think is that the gene activation of TGF-β family have help to sustain the immune exemption of testicle in fluorosis. In addition, based on the expression of MKK3/6, MKK1/2 and PI3K in RNA-seq and the intracellular metabolic processes of IL-17 signaling pathway, we could infer that the IL-17 family members took part in the activation of the Mitogen-activated protein (MAP) kinase pathway and PI3 Kinase-AKT pathway, which are involved in the regulation of a variety of growth and differentiation pathways through several phosphorylation cascades5257. The MAP signaling cascade is activated by a number of receptors: the extracellular mitogen binds to the membrane receptor, then this allows Ras (a GTPase) to swap its GDP for a GTP, and activate MAP3K, which activates MAP2K, which activates MAPK, finally MAPK can activate a transcription factor5859. MAPK-ERK1/2 played an important role in the regulation of cell growth and cell cycle progression. PI3-kinase and its downstream kinase AKT are potent inhibitors of apoptosis in many cell types. AKT is phosphorylated upon IL-17stimulation and also adds to the possible involvement of PI3-kinase in the propagation of signal through the IL-17R52. Together, these results indicated that PI3-kinase/AKT and MAPKs serves as the upstream arbitrator of the IL-17 pathway activation and had contributed to the increased binding of the inflammatory transcription factor in IL-17 pathways. Anyway, all the found helped us to better understand the molecular basis of reproduction and sperm metabolism disorder and deeply identify the mechanisms involved in reproductive toxicity and other pathological disorders associated with fluoride. At first, the aim we were pursuing was to find really reliable molecules and genes associated with reproduction by RNA direct sequencing of testis. However, what we got was quite surprising: a plenty of other metabolic pathways and classic genes of the systemic and comprehensive responses were dig out. Peeping a spot to see overall picture: local delicate change was packed with the complex issues of the whole organism. But for the further verification and exploration, researches on the cellular level and the significant expression of proteins during the spermatogenesis should be carried out. Conclusions The high expression of genes in the IL-17 signal pathway was the response to the invasion of the testicular immune system by extracellular fluoride. The cytokines of the TGF-β family performed key roles in the maintenance of immune privilege and spermatogenesis. Meanwhile, PI3-kinase/AKT and MAPKs acted as the upstream arbitrator of the IL-17 pathway activation and have contributed to the increased binding of the inflammatory transcription factor in IL-17 pathways. All the findings, including the metabolic pathways and classic genes, could provide new ideas and clues for further researches of the molecular mechanism of fluorosis on the field of reproduction and development, immune response, oxidative stress, cell regulation mechanism and so on. Additional Information How to cite this article: Huo, M. et al. Role of IL-17 Pathways in Immune Privilege: A RNA Deep Sequencing Analysis of the Mice Testis Exposure to Fluoride. Sci. Rep. 6, 32173; doi: 10.1038/srep32173 (2016). Supplementary Material Supplementary Information Supported by National Natural Science Foundation of China (Grant Nos 31172376 and 31372497, 31540061). Thank University of Virginia for offering a powerful bioinformatics platform for our study. Thank Dr. Wang Jundong and Dr. Li Mingding for providing a visiting scholar opportunity to Meijun Huo. Author Contributions J.W., S.W. and Z.S. designed the study and contributed funding. H.H. and Z.L. collected samples and processed samples. S.W., M.H. and X.Y. completed RNA sequencing and statistical analyses. M.H. and S.W. contributed to writing the manuscript. All authors discussed the results and commented on the manuscript. Figure 1 Enriched biochemical pathways altered in the testicle in the 50 mg/l and 100 mg/l NaF-treated groups compared to the control groups. Figure 2 The common significant pathways between the 50 mg/l and 100 mg/l NaF-treated groups. Figure 3 The significant pathways related to toxicology altered in the 100 mg/l NaF-treated group. Figure 4 The percentage of different functional genes in all the 367 DEGs screened in the 50 mg/l and 100 mg/l NaF-treated groups. It not only presented the relationship among genes and functions, diseases, but also describes the important role of genes on the development the reproductive system, nervous system, skeletal and muscular disorders, cell signaling and other metabolic processes. Figure 5 Detected interactions of enriched pathways in the testicle in the 50 mg/l and 100 mg/l NaF-treated groups. All significant pathways identified by IPA software were highly interrelated. The number represented the count of the common genes between two pathways. Figure 6 The map of the intracellular metabolic processes for IL-17 signaling pathway. The genes marked with red color indicated their value of genetic expression were significantly changed in the 100 mg/l NaF group. MAP2K3/MAP2K6marked by MKK3/6, MAP2K1/MAP2K2 marked by MKK1/2, and PIK3R1 marked by PI3K. Figure 7 Results of the nine mRNA expression related to the IL-17 signaling pathway in testis of mice in each treatment group. Compared with the control group, *P < 0.05, **P < 0.01, ***P < 0.001, n = 5. Table 1 Important and representative genes altered in the fluorosis testicle based on the significant pathways of 100 mg/l NaF-treated group. # Symbol Matched Pathway Entrez Gene Name Ensembl Fold Change p-value Location Type(s) 1 MAP2K2(20) Role of IL-17A in Arthritis mitogen-activated protein kinase kinase 2 ENSMUST00000105331 2.038 4.49E-02 Cytoplasm kinase IL-17 Signaling Axonal Guidance Signaling Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis TGF-β Signaling ErbB4 Signaling CD40 Signaling Nicotinate and Nicotinamide Metabolism Glioblastoma Multiforme Signaling CXCR4 Signaling Role of NANOG in Mammalian Embryonic Stem Cell Pluripotency Cardiac Hypertrophy Signaling NRF2-mediated Oxidative Stress Response ErbB Signaling Ovarian Cancer Signaling Fc Epsilon RI Signaling Inositol Phosphate Metabolism Antiproliferative Role of Somatostatin Receptor 3 IL-17A Signaling Renin-Angiotensin Signaling 2 PIK3R1(16) Role of IL-17A in Arthritis phosphoinositide-3-kinase, regulatory subunit 6 ENSMUST00000060441 2.935 5.84E-03 Cytoplasm kinase IL-17 Signaling Axonal Guidance Signaling Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis ErbB4 Signaling CD40 Signaling Glioblastoma Multiforme Signaling CXCR4 Signaling Role of NANOG in Mammalian Embryonic Stem Cell Pluripotency NRF2-mediated Oxidative Stress Response ErbB Signaling Fc Epsilon RI Signaling Inositol Phosphate Metabolism Antiproliferative Role of Somatostatin Receptor 4 IL-17A Signaling Renin-Angiotensin Signaling 3 MAP2K3(11) Role of IL-17A in Arthritis mitogen-activated protein kinase kinase 3 ENSMUST00000019076 1.658 4.12E-02 Cytoplasm kinase IL-17 Signaling Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis TGF-β Signaling CD40 Signaling Nicotinate and Nicotinamide Metabolism Role of PKR in Interferon Induction and Antiviral Response NRF2-mediated Oxidative Stress Response ErbB Signaling Fc Epsilon RI Signaling Inositol Phosphate Metabolism 4 WNT6(5) Axonal Guidance Signaling wingless-type MMTV integration site family, member 6 ENSMUST00000006716 2.945 4.93E-04 Extracellular Space other Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis Glioblastoma Multiforme Signaling Role of NANOG in Mammalian Embryonic Stem Cell Pluripotency Human Embryonic Stem Cell Pluripotency 5 WNT9A(4) Axonal Guidance Signaling — ENSMUST00000108783 2.205 3.52E-02 Other other Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis Glioblastoma Multiforme Signaling Role of NANOG in Mammalian Embryonic Stem Cell Pluripotency 6 WNT10A(4) Axonal Guidance Signaling wingless-type MMTV integration site family, member 10A ENSMUST00000006718 1.973 2.21E-02 Extracellular Space other Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis Glioblastoma Multiforme Signaling Role of NANOG in Mammalian Embryonic Stem Cell Pluripotency 7 GNA11(4) Axonal Guidance Signaling guanine nucleotide binding protein (G protein), alpha 11 (Gq class) ENSMUST00000043604 2.433 9.84E-03 Plasma Membrane enzyme Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis CXCR4 Signaling Inositol Phosphate Metabolism 8 MAPKAPK2 (4) Role of IL-17A in Arthritis mitogen-activated protein kinase-activated protein kinase 2 ENSMUST00000016672 1.991 7.62E-03 Nucleus kinase IL-17 Signaling Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis CD40 Signaling 9 IL17RC(4) Role of IL-17A in Arthritis interleukin 17 receptor C ENSMUST00000113062 3.053 1.21E-03 Plasma Membrane transmembrane receptor IL-17 Signaling Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis IL-17A Signaling ==== Refs Elbetieha A. , Darmani H. & Al-hiyasat A. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3153110.1038/srep31531ArticleMapping rare, deleterious mutations in Factor H: Association with early onset, drusen burden, and lower antigenic levels in familial AMD Wagner Erin K. 12Raychaudhuri Soumya 34567Villalonga Mercedes B. 1Java Anuja 8Triebwasser Michael P. 9Daly Mark J. 3410Atkinson John P. 9Seddon Johanna M. a12111 Ophthalmic Epidemiology and Genetics Service, New England Eye Center, Tufts Medical Center, Boston, MA 02111, USA2 Department of Ophthalmology, Tufts University School of Medicine, Boston, MA 02111, USA3 Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA4 Partners HealthCare Center for Personalized Genetic Medicine, Boston, MA 02115, USA5 Division of Genetics, Brigham and Women’s Hospital, Boston, MA 02115, USA6 Division of Rheumatology, Immunology, and Allergy, Brigham and Women’s Hospital, Boston, MA 02115, USA7 Faculty of Medical and Human Sciences, University of Manchester, Manchester M13 9PL, UK8 Washington University School of Medicine, Department of Medicine, Division of Nephrology, Saint Louis, MO 63110, USA9 Washington University School of Medicine, Department of Medicine, Division of Rheumatology, Saint Louis, MO 63110, USA10 Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA11 Sackler School of Graduate Biomedical Sciences, Tufts University, Boston, MA 02111, USAa jseddon@tuftsmedicalcenter.org30 08 2016 2016 6 3153108 01 2016 21 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The genetic architecture of age-related macular degeneration (AMD) involves numerous genetic variants, both common and rare, in the coding region of complement factor H (CFH). While these variants explain high disease burden in some families, they fail to explain the pathology in all. We selected families whose AMD was unexplained by known variants and performed whole exome sequencing to probe for other rare, highly penetrant variants. We identified four rare loss-of-function variants in CFH associated with AMD. Missense variant CFH 1:196646753 (C192F) segregated perfectly within a family characterized by advanced AMD and drusen temporal to the macula. Two families, each comprising a pair of affected siblings with extensive extramacular drusen, carried essential splice site variant CFH 1:196648924 (IVS6+1G>A) or missense variant rs139360826 (R175P). In a fourth family, missense variant rs121913058 (R127H) was associated with AMD. Most carriers had early onset bilateral advanced AMD and extramacular drusen. Carriers tended to have low serum Factor H levels, especially carriers of the splice variant. One missense variant (R127H) has been previously shown not to be secreted. The two other missense variants were produced recombinantly: compared to wild type, one (R175P) had no functional activity and the other (C192F) had decreased secretion. ==== Body Age-related macular degeneration (AMD), an irreversible degenerative disease, is the leading cause of blindness in adults over the age of 60. The disease affects the central region of the retina, resulting in progressive visual impairment and reduced quality of life. AMD is highly heritable and twin studies have shown that between 46% and 71% of phenotypic variance is explained by genetic factors12. Several environmental and genetic components contribute to its multifactorial etiology2. Early genome-wide scans for evidence of linkage in AMD families revealed several signals including one mapping to the long (q) arm of chromosome 1345. Investigation of the genetic architecture of AMD subsequently evolved over the next 15 years on population, family, and individual levels. Genome-wide association studies (GWAS) and meta-GWAS efforts identified numerous genetic variants in over 20 different genes showing an association with AMD risk, including a common variant in the coding region of complement factor H (CFH) (RefSeq NM_000186)678910111213. While these known variants may explain high burden of disease in some AMD families, they do not explain the patterns of disease observed in several other families with multiple affected individuals. Recent studies have identified several rare, functional, penetrant variants in genes involved in the alternative pathway (AP) of complement activation that are associated with high risk of AMD and earlier age of disease onset. The first rare variant identified to be associated with AMD, CFH R1210C, was found to be highly penetrant with an odds ratio of about 20 (P = 7.0 × 10−6)14. Other rare variants in the CFH gene, including R53C, D90G, and P503A, were later found to segregate within AMD families densely affected with the disease1516. A recent targeted sequencing study of independent cases and controls showed an enrichment of rare CFH variants in AMD patients17. Rare variants in CFI, C3, and C9 have also been identified by targeted sequencing of the exons of these genes in a sample of over 7,600 AMD cases and unaffected controls18. Results from this and other recent studies showed a burden of CFI rare variants in AMD cases1819, an association between AMD and the rare K155Q variant in C3182021, and an association between AMD and the rare P167S variant in C918. Considering the increased risk of AMD associated with rare variants discovered to date, we selected densely affected families with a lower than expected genetic load for known AMD-associated SNPs using an established method22. We conducted whole exome sequencing to investigate the coding sequences of genes and to determine whether rare and highly penetrant variants could explain the prevalence of AMD in these families. We sought to examine the functional and phenotypic consequences of identified rare variants in order to understand their role in the onset and development of AMD. Results Herein we report four independent families each harboring a unique rare, loss-of-function (LOF) variant in CFH associated with AMD. These variants were identified using the xBrowse software to filter variants by the following stringent criteria: (1) had a minor allele frequency (MAF) of <0.1% in the 1000 Genomes Project and Exome Aggregation Consortium (ExAC) databases, (2) belonged to a potentially damaging functional annotation class, (3) was predicted in silico to have a functional impact on protein function, and (4) followed the inheritance pattern of the disease within the family. Fig. 1A shows a multigenerational pedigree with both AMD-affected and unaffected members from which we sequenced eight subjects from two generations. Affected and unaffected family members were classified according to the Clinical Age-Related Maculopathy Staging (CARMS) system (see Methods)23. Affected family members showed early age at onset of AMD with a mean age at first diagnosis of 58 and a range between 46 and 67 years of age. The unaffected members (Pedigree A; IV:3 and IV:7) were 67 and 65 years old at their most recent follow-up exams, respectively, and were confirmed by ocular examination to be unaffected. After applying our described variant filtering criteria to Pedigree A (Table 1), only one rare non-synonymous variant segregated with the autosomal dominant pattern of inheritance suggested for AMD in this family. The variant, CFH 1:196646753 is a missense mutation that results in the substitution of a phenylalanine for the cysteine at position 192 of the protein (CFH C192F). The risk allele for this variant has a frequency of 0 in the 1000 Genomes Project and ExAC databases. PolyPhen-2, SIFT, MutationTaster2, and FATHMM all predict this mutation to be deleterious to the protein structure. We selected this family based on low genetic risk scores for members affected with AMD and we verified that no other CFH variants segregated with AMD within the family. Though all family members carried the more common, lower impact AMD risk alleles at CFH rs1061170 (Y402H) and CFH rs1410996, neither variant segregated with AMD in this family; in fact, all but two of the sequenced members, including both unaffected family members, were homozygous for the risk allele at CFH rs1410996. Thus, these known common variants did not segregate with the disease and could not explain the high level of penetrance of disease observed in this family as effectively as the rare C192F variant. Factor H (FH) bearing this variant was recombinantly produced on two separate transfections and found to be secreted in the first transfection at 36% and in the second at 57% of the amount compared to wild type (Supplementary Fig. S1). Pedigree B (Fig. 1B) shows a pair of siblings affected with geographic atrophy. Filtering common variants and variants with low function impact on the protein left 114 variants shared by both siblings. Of those, a rare essential splice site variant in CFH emerged as a putative candidate mutation to explain the prevalence of AMD in this family. This mutation, CFH 1:196648924, is a substitution of an adenine for a guanine at the first base pair of the sixth intron of CFH and is located in a splice donor site (CFH IVS6 + 1G > A). It is predicted to be “disease causing” by MutationTaster2 and to cause an “alteration of the wild type donor site, most probably affecting splicing” by Human Splicing Finder. The risk allele for this variant has a frequency of 0 in the 1000 Genomes Project and ExAC databases. Both affected members were heterozygous for the risk allele at CFH Y402H and CFH rs1410996, although these variants are unlikely to explain the severity of disease seen in this family. The splice site variant observed in this family is located at the 5′ end of the sixth intron. Retention of this intron results in the addition of 30 amino acids to the protein before a stop codon is encountered, leaving a truncated protein 20% the size of the wild type protein with only the first four CCP domains. The truncation caused by this mutation in an essential splice site likely explains the low serum FH levels measured in the two members of this family as described below. Pedigree C (Fig. 1C) shows a pair of siblings with advanced AMD. After filtering of common variants and variants with low potential for impacting protein function, 108 variants remained for analysis. Of these, 97 were missense variants and 4 were variants in essential splice sites. A single missense variant in CFH was identified as a probable candidate for the causative mutation in this family. The variant, rs139360826 (CFH R175P), is a substitution of a guanine for a cytosine resulting in a change of the 175th amino acid from an arginine to a proline. It is predicted to be “possibly damaging” by PolyPhen2 and “damaging” by SIFT, while MutationTaster2 and FATHMM predict the variant to be neutral. This variant has a minor allele frequency of 0 in the 1000 Genomes Project and ExAC databases. Both members of this family were heterozygous for the risk allele at CFH Y402H and CFH rs1410996, although these variants are unlikely to explain the severity of disease seen in this family. Factor H bearing this rare variant was produced recombinantly and it had no cofactor activity for C3b (Supplementary Fig. S2). Pedigree D (Fig. 1D) shows a family with two generations affected with advanced AMD. We found 34 rare, high impact variants segregating with AMD in individual II:2 and his son (III:1). Of these variants, a rare missense variant in CFH was identified as the candidate variant explaining AMD on the paternal side of the family. This variant, rs121913058 (CFH R127H), is a substitution of a guanine to adenine that results in the change from an arginine to histidine at the 127th amino acid. This variant is predicted to be deleterious to the protein structure according to all four in silico prediction software programs. In accord with these predictions, this variant has been extensively evaluated and shown not to be secreted24. It has a frequency of 3.0 × 10−5 (an allele count of 2/66,622) in the European samples from the ExAC database and a frequency of 0 in the 1000 Genomes Project. Both subject II:1 and her unaffected daughter, subject III:2, were heterozygous for the risk allele at CFH Y402H and CFH rs1410996, thus these variants did not segregate with AMD on the maternal side of this family. Subject II:2 is heterozygous for the risk allele at CFH rs1410996 but homozygous for the non-risk allele at CFH Y402H. The affected son, subject III:1, is heterozygous for the risk allele at CFH Y402H and homozygous for the risk allele at CFH rs1410996. Considering the pattern of risk allele inheritance of the two common variants in CFH, there is little evidence they are responsible for the AMD seen in the affected family members. We assessed the genotypes of all family members for known AMD and other retinal disease-associated variants to ensure that the disease seen in affected subjects could not be explained by other known high impact risk alleles. None of the family members carried the rare AMD risk alleles at CFH R53C, CFH D90G, CFH P503A, or CFH R1210C14151618 nor did they carry risk alleles for macular diseases in the BEST1, ABCA4, or other retinal degeneration-associated genes25. We measured serum FH levels in each family in order to assess the effects of the four CFH variants on secretion of the FH protein. Members of all four pedigrees who carried rare, high impact CFH variants had lower serum antigenic FH levels compared to family members who did not carry the variants. Their levels were still within the normal clinical laboratory range (160–412 μg/ml), with the exception of one member of Pedigree B (Pedigree B; II:1 = 147 μg/ml) (Fig. 2 and Supplementary Table S1). We selected serum samples from our biorepository to determine if these relatively low but normal levels are characteristic of individuals who are heterozygous for rare LOF CFH variants. We first selected serum from unrelated individuals who were heterozygous for at least one rare LOF CFH variant (n = 3), and additionally selected serum from a set of unaffected control individuals (CARMS grade 1 in the worse eye) who were confirmed not to carry any of the known rare variants in CFH (n = 45). The mean serum FH level in the unaffected controls was significantly different from mean serum FH level in the unrelated carriers (P = 0.01). Rare variant carriers in Pedigrees A, B, and C also had serum FH levels that were significantly different from unaffected controls (P = 1.0 × 10−3, 4.3 × 10−2, and 4.58 × 10−8, respectively). There was no significant difference in mean serum FH level between rare variant carriers from Pedigree D and unaffected controls (P = 0.26), but there were only two carriers in this family and for one, the serum FH level was lower than the controls. We further confirmed that serum FH levels of rare variant carriers from all four families did not differ from the serum FH levels for unrelated LOF variant heterozygotes (P values: 0.29 to 0.84) (Fig. 2). We used our AMD genotype-phenotype database to explore the clinical history and phenotypic appearance of carriers and non-carriers of each rare variant. In addition to these variants being associated with more advanced AMD within these families, carriers also had earlier age of onset of advanced disease (mean age = 59.2) compared to individuals with advanced AMD without rare CFH variants (mean age at diagnosis in our AMD database = 69.6, n = 1,627)26. We also explored disease symmetry, and among affected individuals carrying a rare CFH variant in these families, 75% (n = 9 of 12 carriers) exhibited a symmetric fundus phenotype. Segregation with extramacular drusen was seen in both eyes of all affected family members in Pedigrees A-C (Table 2 and Fig. 3). All members of Pedigree A carrying the CFH C192F variant showed several large macular and extramacular drusen in the region temporal to the macula. Members of Pedigree B carrying the CFH IVS6 + 1G>A variant had extensive extramacular drusen in four of the seven possible peripheral fundus locations. Both members of Pedigree C carrying CFH R175P had extensive extramacular drusen in all seven peripheral fundus locations. We investigated the presence of one or more locations of extramacular drusen versus none by comparing the subjects in these three families who had extramacular drusen to 230 unrelated individuals with advanced disease and complete extramacular drusen information in our database who did not carry the CFH C192F, CFH IVS6+1G>A, or CFH R175P variants based on sequencing. Overall, 57% of the unrelated individuals without these variants had extramacular drusen, whereas 100% of individuals within the three families who carried these variants exhibited drusen outside the macular area (P = 6.1 × 10−3). Extramacular drusen burden did not appear to segregate with the presence of the rare variant CFH R127H seen in Pedigree D (Table 2). Subject II:2 of Pedigree D, a carrier of the risk allele, had no drusen in any of the seven peripheral fundus locations based on available imaging, while his son, also a carrier of the risk allele, had extensive extramacular drusen in all seven locations. Discussion Using next-generation whole exome sequencing and a step-wise filtering methodology, we identified highly penetrant CFH variants that were strongly associated with advanced AMD in four independent families with a low burden of risk based on previously reported AMD genetic variants22. The identified variants were associated with a higher frequency of drusen, earlier age of disease onset, and phenotypic symmetry compared with non-carriers. Regarding the four mutant proteins, expression profiles and functional analyses provided an explanation for low serum FH levels and/or deficient cofactor activity. The FH protein consists entirely of 20 homologous repeating units (“like beads on a string”) of from 56 to 66 amino acids each. They are variably known as a complement control protein (CCP), short consensus repeats (SCR), or Sushi domains. Most are encoded by a single exon. Each CCP harbors four cysteine residues that participate in two disulphide bridges with one at each end of the repeat. Repeats with a missense mutation involving one of the four cysteine residues commonly lead to a misfolded domain, and the protein is poorly secreted or has a short half-life leading to haploinsufficiency. The variant C192F (Pedigree A) is of the aforementioned category. We prepared this variant recombinantly in the laboratory and found that the protein was secreted at ~45% the amount compared to wild type. We also prepared the variant R175P (Pedigree C) recombinantly and found that it had no functional activity. Most splice site variants, like IVS6 + 1G>A in Pedigree B, lead to haploinsufficiency as the protein is not synthesized. This explains the low antigenic levels observed in this family. The fourth variant, R127H (Pedigree D), has been reported in the literature and shown not to be secreted. We believe carriers in these families have only one allele substantially contributing to the blood level of FH. The protein from the other allele is either not synthesized/secreted or secreted but having moderately reduced function. Thus, at sites of injury and/or degeneration, complement homeostasis is altered such that overactivation of the AP occurs and thereby generates excessive and potentially damaging anaphylatoxins (C3a and C5a) and membrane attack complexes (C5b-C9) in the retina. Variants in CFH associated with AMD, including two common variants rs1061170 and rs1410996, were initially identified using case-control study designs81327. These two common variants explain 17% of AMD liability, but not everyone affected with AMD carries these variants14. Rare variants in CFH as well as other genes in the complement pathway have since been identified, and carry a higher risk of disease1415161718. The CFH R53C variant, located in CCP1, decreases the ability of FH to perform decay accelerating activity15; the CFH D90G variant, located in CCP2, was found to decrease cofactor-mediated inactivation15; and the CFH R1210C variant, located in CCP20, shows defective binding of FH to C3d, C3b, heparin/glycosaminoglycans, and endothelial cells (Table 3)1430. Another rare variant was found to segregate with AMD in an Amish family, but no functional work was done to determine the effect of the mutation on FH protein. It is located in a CCP whose function is currently unknown16. Other variants in CFH were associated with basal laminar drusen34 but no functional work was done to assess the effect of these variants. In a separate targeted sequencing study of unrelated cases and controls, we found 65 rare variants in CFH17. The four variants found to segregate with AMD in this family-based study were identified independent of that study and with a different next generation whole exome methodology. These four variants were discovered to be a subset of the variants found with targeted sequencing of cases and controls. Thus, the rare variants were confirmed using two different platforms. The association in these families, the phenotypic appearance of the carriers, and the functional impact of the variants underscore their importance. Previous studies report a distinctive drusen appearance as well as an earlier age of AMD onset in carriers of rare variants in CFH; our results are consistent with these findings1525. Carriers of the four rare CFH variants we report here showed an earlier age of disease onset when compared to other cases in our AMD registry. Extramacular drusen, seen in 11 of 12 carriers of variants in this study, is not a clinical phenotype consistently seen in AMD, but it has been reported as associated with other mutations in CFH25. Of note, 9 of the 12 carriers of a rare CFH variant in these families had similar phenotypic appearances in both eyes, a characteristic trait of monogenic ocular diseases and macular dystrophies. These mutations and their associated phenotypic characteristics may be helpful in identifying individuals with macular degeneration in a clinical population who are more likely to be carriers of these rare variants. Access to a large family-based resource with clinical phenotype data and family history information gave us the ability to identify variants that are rare in the general population but enriched in certain families. We chose to utilize whole exome sequencing for a subset of our vast database in order to examine coding regions across the genome. This approach also allowed us to confidently exclude other candidate variants if they did not meet our strict filtering criteria implemented through the xBrowse software. Serum protein antigenic and functional analyses reflected the structural impact of these rare LOF mutations. These data strengthen our conclusion that these mutations are responsible for the AMD phenotype characterized in these families. Identification of these rare variants augments our understanding of the biology of FH which could potentiate the development and optimization of novel treatments aimed at slowing the progression of AMD and decreasing visual loss. These mutations often result in haploinsufficient protein levels, and selected patients may respond to treatments that involve FH supplementation. Earlier and more frequent monitoring for the initial signs of AMD in young members of families carrying these variants could lead to better management and education regarding behavioral risk factors and ultimately a reduction in the ocular morbidity associated with the disease. Risk prediction models of AMD progression have shown that, in addition to eight common AMD risk variants, the rare variants CFH R1210C and C3 K155Q are also independently associated with progression of the disease to advanced stages36. Incorporation of additional rare or low frequency variants may aid in the development of a more precise model to better predict a patient’s risk of developing advanced stages of AMD. Furthermore, growing evidence of the impact of rare variants may raise awareness in the clinic setting for high risk of disease in the families affected. Investigating the associated functional and phenotypic consequences of rare variants will further our understanding of their role and that of CFH in the pathophysiology of AMD, and may lead to innovative therapeutic techniques. Materials and Methods Study population All study participants were previously enrolled in ongoing genetic and epidemiologic studies of AMD. Approval for this research was obtained from the institutional review board at Tufts Medical Center. Signed informed consent was obtained from all participants, and all procedures were carried out in accordance with approved protocols. Diagnosis and phenotyping All affected and unaffected individuals in the study were evaluated by board-certified ophthalmologists. Individuals either (1) were clinically evaluated with visual acuity measurements, dilated slit lamp biomicroscopy, and stereoscopic color fundus photography or (2) had ophthalmologic medical records and images reviewed by retina specialists. Affected individuals had clinical evidence of AMD classified as drusenoid retinal pigment epithelial detachment, geographic atrophy (advanced dry AMD), or neovascular AMD (wet AMD) according to CARMS grades 3B, 4, and 5, respectively23. We defined unaffected individuals as those who had no signs of early, intermediate, or advanced macular degeneration in either eye and were categorized as CARMS grade 1 in both eyes. We reviewed ocular records, fundus photographs, and other ocular images including autofluorescence and ocular coherence tomography to determine the grade. We evaluated the presence of drusen in the macular area (defined as a circular area of 3 mm or 2 disc diameters in radius, centered at the fovea) from color fundus images which were obtained in up to seven standard fields based on the modified Airlie House classification38. With standard field 2 centered on the macula, the presence of drusen in the macular area was assessed in this field as previously described25. We also reviewed fundus images to evaluate the presence of drusen in seven extramacular regions of the retina including temporal to the macula, nasal to the optic disc (defined as a semicircular area of 3 mm or 2 disc diameters in radius, nasal to the optic disc), along the temporal vascular arcade, and the superotemporal, inferotemporal, superonasal, and inferonasal fundus quadrants (defined as the retina beyond the retinal vascular arcades extending to or beyond the equator). We evaluated each region for the presence of drusen as previously described25. Family selection We selected families whose burden of AMD could not be explained by any of the known AMD-associated common or rare variants22. We selected individuals based on the following criteria: (1) families had multiple members affected with macular degeneration; (2) multiple affected individuals with a low genetic risk score and relatively younger age of onset of AMD (less than 75); and (3) those affected did not carry risk alleles at CFH R1210C, CFH R53G, CFH D90G, CFH P503A, and C3 K155Q. The genetic risk score is defined as the sum of the log odds ratio for each risk allele from 26 loci associated with AMD (equation (1)): where xi is 0, 1, or 2 copies of the risk alleles and is the log of the odds ratio of the risk allele estimated using multivariate logistic regression on genetic data collected on a cohort of over 4,800 independent AMD cases and validated controls. A low genetic risk score is defined as any score that is lower than the risk score represented by the maximized sum of sensitivity and specificity (threshold score = 0.874) (Supplementary Fig. S3). Exome sequencing Genomic DNA was extracted from blood using the standard protocol for purification of DNA from up to 10 ml of whole blood samples using the Qiagen Autopure LS automated Nucleic Acid Purification Instrument. Exome sequencing was performed at the Perkin Elmer Center for Genome Innovation at University of Connecticut. Genomic DNA was prepared and exomic sequence was targeted following the SureSelectXT Target Enrichment System for Illumina Paired-End Sequencing Library 6.1 protocol from Agilent. Following exome library preparation, the samples were sequenced using the Illumina HiSeq2000 Sequencing System. The sequenced samples had an average of 96.6% of the exome covered at ≥10X. After quality control and variant calling, 598,065 high quality variants were identified. Read mapping, variant detection, and annotation Following deconvolution of barcodes from each lane, individual reads were aligned to the human reference genome (hg19) using the Burrows Wheeler Aligner resulting in BAM files39. Variant calling was performed using the best practices recommendations of the tools in the Genome Analysis Toolkit (GATK) version 3.1 suite (http://www.broadinstitute.org/gatk/guide/best-practices)4041. Genomic variant call format (gVCF) files containing variant calls for all loci were created separately for each sample using the HaplotypeCaller tool. The gVCFs were combined and raw genotypes were called for the sample set as a whole using the GenotypeGVCFs tool. The resulting raw genotype calls in the VCF file were filtered for low quality genotypes using the Variant Quality Score Recalibration tool. Functional effects for the variants were annotated using the Ensembl Variant Effect Predictor42. Data analysis For densely affected families with a low burden of known AMD-associated variants, we hypothesized that some of these families might be explained by variants that are highly penetrant and follow an autosomal dominant mode of inheritance. In order to test this hypothesis, we designed the following filtering strategy to identify rare and potentially pathogenic exomic variants that segregate with AMD in families. To screen for rare variants that segregate with AMD in the families, the xBrowse (https://xbrowse.broadinstitute.org) tool was used to filter variants in a step-wise manner. We prioritized variants that (1) were rare (MAF <0.1% in the 1000 Genomes Project and the ExAC databases), (2) belonged to a potentially damaging functional annotation class (i.e., nonsense, missense, splice site, frameshift), (3) were predicted to have a functional impact on protein function (i.e., in silico prediction of damaging or deleterious by PolyPhen-243, SIFT44, MutationTaster245, FATHMM46, and Human Splicing Finder47 depending on the type of mutation), and (4) matched the inheritance pattern of AMD within the family (e.g., if neither parent manifested the disease [based on an ocular examination], but offspring had the macular disease, then the pattern of inheritance was determined likely to be recessive rather than dominant). Comparisons of mean serum FH levels in carriers and non-carriers were performed using an independent samples t-test. The association of extramacular drusen and variant status was determined using Fisher’s exact test; related non-carriers from Pedigrees A and D were excluded from this analysis. Factor H serum level quantification Fasting blood samples were collected for all members of each family. The blood was centrifuged and serum was separated within 60 minutes of collection. The samples were frozen and stored in liquid nitrogen until testing was performed. FH serum antigenic levels were analyzed at the National Jewish Center for Immunology and Respiratory Medicine, Diagnostic Immunology and Complement Laboratory by radial immunodiffusion with anti-human antibodies (Abs) specific for FH as previously described48. Recombinant synthesis and functional analysis of Factor H variants Protein expression Point mutations were introduced in the wild type FH cDNA in the pSV vector using site-directed mutagenesis (QuikChange; Agilent Technologies) to prepare the variants R175P and C192F, and the resulting constructs were transiently transfected in 293T cells as previously described4950. Three days after transfection, supernatants were concentrated. Quantitation and characterization of FH were performed by sandwich enzyme-linked immunosorbent assay and Western blotting. Quantitation of FH secreted into the supernatant Briefly, the capture anti-FH antibody, A254 (Quidel, USA), was coated at 1 mg/ml overnight at 4 °C and then blocked overnight at 4 °C. Dilutions of concentrated wild-type and variant FH samples and purified human FH (Complement Technologies, Inc., USA) were incubated for 1 h and then washed with PBS containing 0.05% Tween 20. Next, goat anti-human FH Ab (Quidel, USA) was applied for 1 h at 37 °C. After washing, HRP-coupled donkey anti-goat immunoglobin G (IgG, Jackson Immunoresearch, USA) was added and incubated for 1 h at 37 °C. After washing, TMB substrate (Pierce, Rockford, IL) was added and absorbance at 630 nm was assessed in an ELISA reader. Cofactor assays FH preparations (200 ng; wild type, R175P or C192F) were incubated for 30 min at 37 °C with C3b (10 ng) and Factor I (20 ng) in 15 μl of buffer (10 mM Tris, pH 7.4, 150 mM NaCl). To stop the reaction, 7 μl of 3X reducing Laemmli sample buffer was added. Samples were boiled at 95 °C for 5 min, electrophoresed on 10% Tris-glycine polyacrylaminde gels, transferred to nitrocellulose, and blocked overnight with 5% nonfat dry milk in phosphate-buffered saline. Blots were probed with a 1:5,000 dilution of goat anti-human C3 (Complement Technologies) followed by horseradish peroxidase-conjugated rabbit anti-goat IgG and developed with SuperSignal substrate (Thermo Scientific). Additional Information How to cite this article: Wagner, E. K. et al. Mapping rare, deleterious mutations in Factor H: Association with early onset, drusen burden, and lower antigenic levels in familial AMD. Sci. Rep. 6, 31531; doi: 10.1038/srep31531 (2016). Supplementary Material Supplementary Information This research was supported in part by NIH grants R01-EY11309 (J.M.S.), 1R01AR063759-01A1 (S.R.), 5U01GM092691-04 (S.R.), 1U01HG007690-01 (S.R.), F30HL103072 (M.T.), R01-AI041592 (J.P.A.), U54 HL112303 (J.P.A.); the Doris Duke Clinical Scientist Development Award (S.R.); the Rheumatic Disease Core Center supported by NIH-Arthritis and Musculoskeletal and Skin Diseases P30 AR48335 (J.P.A.), Massachusetts Lions Eye Research Fund, Inc. (J.M.S.); Research to Prevent Blindness Challenge Grant to the New England Eye Center, Department of Ophthalmology, Tufts University School of Medicine; and the Macular Degeneration Research Fund of the Ophthalmic Epidemiology and Genetics Service, New England Eye Center, Tufts Medical Center, Tufts University School of Medicine. M.T. is a F30 Ruth L. Kirschstein National Research Service Award recipient (National Heart, Lung and Blood Institute). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Author Contributions J.M.S. recruited and ascertained the families, and interpreted clinical data and ocular images. J.M.S., S.R., M.J.D. and J.P.A. conceived, designed, and guided the analyses. E.K.W., J.M.S., S.R. and M.J.D. analyzed and interpreted the data. J.M.S., M.B.V. and E.K.W. drafted the manuscript. M.B.V. assisted with acquisition and organization of pedigree and phenotypic data. J.P.A. and A.J. interpreted the antigenic data and conducted functional analyses. All authors reviewed and revised the manuscript. Figure 1 Pedigree diagrams for families carrying rare, loss-of-function CFH variants. (A) Pedigree A (CFH C192F), (B) Pedigree B (CFH IVS6 + 1G > A), (C) Pedigree C (CFH R175P), (D) Pedigree D (CFH R127H); ⚪ = female; ◽ = male; * = sequenced; ∅ = deceased; ⦁ and ◾ = affected with advanced AMD; “N” = confirmed unaffected; empty ⚪ and ◽  = unknown affection status; rare variant genotype listed below each sequenced subject. Figure 2 Serum factor H levels according to carrier state of rare CFH variants. ⚪ = subjects carrying rare CFH variant; ▴ = subjects not carrying rare CFH variant. controls = CARMS grade 1 and no known rare variants in CFH; unrelated carriers of loss-of-function mutations = nonsense, splice-site, and loss of a conserved cysteine; normal clinical laboratory range = 160–412 μg/ml. Figure 3 Fundus photographs from family members carrying rare CFH variants showing numerous large drusen and extramacular drusen. Fundus color photographs of subjects in the four pedigrees: IV:5 from Pedigree A showing several large macular and extramacular drusen with retinal pigment epithelial irregularities in her left eye (OS) at age 71 (a) and extramacular drusen and macular pigment disruption following intravitreal anti-vascular endothelial growth factor injections OS after 8 years of follow-up (b). II:1 from Pedigree B showing numerous large macular and extramacular drusen with transition in her right eye (OD) from drusenoid retinal pigment epithelial detachments at age 64 (c) to geographic atrophy at age 76 (d). Subject II:2 from Pedigree C showing several drusen throughout the posterior pole OD (e) and OS (f) at age 55, with neovascular disease OS. Subject III:1 from Pedigree D showing numerous drusen OD at age 56 (g) and OS at age 54 (h); patient previously received laser treatment OD for neovascular macular degeneration. Some subjects progressed after date of images; last known phenotypes are shown in Table 2. Table 1 Step-wise filtering of variants according to frequency in population databases, segregation pattern, functional annotation, and predicted deleteriousness.   Pedigree A Pedigree B Pedigree C Pedigree D Affected:Unaffected ratio per family 6:2 2:0 2:0 3:1 MAF <0.1% in databases 2605 1841 1646 1845 Shared among affected but not unaffected 11 867 847 124 High and moderate impact SNPs 5 114 108 34 Missense and nonsense variants:  Total 5 95 97 32  Probably damaging (Polyphen-2) 1 24 20 12  Deleterious (SIFT) 3 49 45* 15  Disease Causing (MutationTaster2) 3 65 54 23  Damaging (FATHMM) 1 17 18 7  Deleterious according to all four prediction softwares 1* 7 5 3*  Deleterious according to at least 3/4 prediction softwares 1 24 20 9 Essential Splice Site Variants:  Total 0 3 4 1  Disease Causing (MutationTaster2) NA 2 0 1  Affects Splicing (Human Splicing Finder) NA 1 2 1  Deleterious according to both prediction softwares NA 1* 0 1 *Indicates the damaging predictions for the CFH rare variant in the respective family. Table 2 Genotype-phenotype characteristics of families carrying rare CFH variants. ID AMD Disease Status Genotype CARMS Grade OD CARMS Grade OS Drusen Location Pedigree A (CFH C192F)  III:2 Affected G/T 4 4 Macula, temporal to the macula  IV:1 Affected G/T 3B 3B Macula, temporal to the macula, nasal to the optic disc, along the vascular arcade  IV:2 Affected G/T 5B 3A Macula, temporal to the macula  IV:3 Unaffected G/G 1 1 None  IV:4 Affected G/T 3B 3B Macula, temporal to the macula  IV:5 Affected G/T 3A 5B Macula, temporal to the macula, along the temporal vascular arcade, superotemporal, inferotemporal, superonasal  IV:6 Affected G/T 5B 5B Macula, temporal to the macula  IV:7 Unaffected G/G 1 1 None Pedigree B (CFH IVS6+1G>A)  II:1 Affected G/A 4 4 Macula, temporal to the macula, nasal to the optic disc, along the temporal vascular arcade, superotemporal, superonasal, inferonasal  II:2 Affected G/A 4 4 Macula, temporal to the macula, nasal to the optic disc, along the temporal vascular arcade, superotemporal Pedigree C (CFH R175P)  II:1 Affected G/C 5B 3A Macula, temporal to the macula, nasal to the optic disc, along the temporal vascular arcade, superotemporal, inferotemporal, superonasal, inferonasal  II:2 Affected G/C 5B 5B Macula, temporal to the macula, nasal to the optic disc, along the temporal vascular arcade, superotemporal, inferotemporal, superonasal, inferonasal Pedigree D (CFH R127H)  II:1 Affected G/G 5B 5B Macula, temporal to the macula, nasal to the optic disc, along the temporal vascular arcade, superotemporal, inferotemporal, superonasal  II:2 Affected G/A 4 4 None  III:1 Affected G/A 5B 5B Macula, temporal to the macula, nasal to the optic disc, along the temporal vascular arcade, superotemporal, inferotemporal, superonasal, inferonasal  III:2 Unaffected G/G 1 1 None AMD: Age-related macular degeneration; CARMS: Clinical Age-Related Maculopathy Staging23; OD: right eye; OS: left eye. Table 3 Rare variants in CFH reported to be associated with age-related macular degeneration in families. hg19 Position SNP ID Amino Acid Consequence CCP Function 1:196642206 NA R53C 1 Normal FH levels; Decreases the ability of FH to perform decay accelerating activity16 1:196643011 NA D90G 2 Normal serum FH levels; Decreases cofactor-mediated inactivation16 1:196645148 rs121913058 R127H 2 Low serum FH levels; Haploinsufficiency of serum FH 1:196646702 rs139360826 R175P 3 Low serum FH levels; Haploinsufficiency of serum FH 1:196646753 NA C192F 3 Low serum FH levels; Haploinsufficiency of serum FH 1:196648924 NA NA (Splice variant) 4 Low serum FH levels; Truncation of protein; Low levels of FH secreted from cell and haploinsufficiency of serum FH 1:196683035 rs570523689 P503A 8 May affect C3b binding affinity17 1:196716375 rs121913059 R1210C 20 Defective binding to C3d, C3b, heparin/glycosaminoglycans, and endothelial cells26272829 ==== Refs Sobrin L. & Seddon J. M. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3199510.1038/srep31995ArticleUPF1 regulates myeloid cell functions and S100A9 expression by the hnRNP E2/miRNA-328 balance Saul Meike J. 12Stein Stefan 3Grez Manuel 3Jakobsson Per-Johan 4Steinhilber Dieter a2Suess Beatrix b11 Department of Biology, Technical University Darmstadt, Schnittspahnstr. 10, 64287 Darmstadt, Germany2 Institute of Pharmaceutical Chemistry/ZAFES, Goethe University Frankfurt, Max-von-Laue-Str. 9, 60438 Frankfurt/M., Germany3 Georg-Speyer-Haus, Paul-Ehrlich-Str. 42-44, 60596 Frankfurt/M., Germany4 Department of Medicine, Rheumatology unit, Karolinska Institute, 17176 Stockholm, Swedena steinhilber@em.uni-frankfurt.deb bsuess@bio.tu-darmstadt.de30 08 2016 2016 6 3199512 05 2016 01 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/UPF1 is a key player in nonsense mediated mRNA decay (NMD) but also involved in posttranscriptional gene regulation. In this study we found that UPF1 regulates the expression of genes with functions in inflammation and myeloid cell differentiation via hnRNP E2. The majority of the UPF1-regulated genes identified in monocytic cells contain a binding site for hnRNP E2 within 5′ UTR located introns with hnRNP E2 acting here as splicing regulator. We found that miRNA-328 which is significantly induced during monocytic cell differentiation acts independently from its gene silencing function as RNA decoy for hnRNP E2. One representative gene controlled by the hnRNP E2/miRNA-328 balance is S100A9 which plays an important role in cell differentiation and oxidative stress response of monocytes. Induction of miRNA-328 expression during cell differentiation antagonizes the blockade by hnRNP E2 which results in the upregulation of CD11b expression and ROS production in monocytic cells. Taken together, our data indicate that upregulation of miR-328 is responsible for the induction of hnRNP E2 target genes during myeloid cell differentiation. ==== Body Monocytes and macrophages play a central role in the innate immune system, responsible for the recognition and clearance of pathogens and dead cells. They are essential for the initiation and resolution of inflammation by phagocytosis, release of pro- and antiinflammatory cytokines, reactive oxygen species (ROS) and by regulation of the acquired immune system12. In response to specific stimuli, monocytes start to differentiate into macrophages. Subsequently, certain surface markers like CD14 are induced determining the differentiation state of monocytes1. Regulation of myeloid cell differentiation on the level of transcription has been studied extensively, however the impact of post-transcriptional regulation on this process is still less known. The Up Frame Shift Protein 1 (UPF1) has originally been discovered as central component of the NMD pathway. However, in the last years it became obvious that UPF1 is not only important for the elimination of aberrant mRNAs harboring premature termination codons but is also involved in the regulation of gene expression controlling mRNA processing steps such as splicing, mRNA transport, translation or mRNA turnover34567. A recent mass spectrometry-based proteomics study performed in our lab revealed that knockdown of UPF1 leads to multiple changes of the proteome in undifferentiated Mono Mac 6 (MM6) cells. Interestingly, the majority of the proteins downregulated by UPF1 knockdown returned to control levels during cell differentiation by TGFβ and calcitriol8. Pathway analysis demonstrated that c-Myc and granzyme A/B-mediated signaling pathways are highly associated with UPF1. Both pathways are correlated with myeloid cell differentiation and inflammatory responses910 which suggests an important regulatory function of UPF1 during myeloid cell maturation. A detailed analysis of the genes downregulated by UPF1 knockdown led to the identification of a binding site for heterogeneous nuclear ribonucleoprotein (hnRNP) E2 in their 5′ UTR. HnRNPs are multifunctional RNA binding proteins involved in the processing pre-mRNA into mature mRNA, but are also important determinants of mRNA export, localization, transport and stability11. HnRNP E2, also known as αCP2 or polyC binding protein 2 (PCBP2) belongs to the class of minor hnRNP proteins12. While it is widely believed that hnRNPs (such as hnRNPE2) are involved in splicing1314 some of them also mediate translational repression15. HnRNPs are ubiquitously expressed in all tissue types to varying levels. HnRNPs are predominantly nuclear at steady state; however, some of them are able to rapidly shuttle between the nucleus and the cytoplasm. Along with this, the multiple functionalities of hnRNP E2 as splicing regulator and translational repressor can be explained. C/EBPα mRNA, a master regulator of myeloid cell differentiation, is a prominent example of translational inhibition by hnRNP E2. hnRNP E2 inhibits differentiation via binding to a C-rich motif in the 5′UTR of C/EBPα. Interestingly, the microRNA miR-328 can interact with hnRNP E2 independent from any known factors of the miRNA gene silencing machinery simply by acting as decoy of hnRNP E2 thus relieving translational inhibition of C/EBPα myeloid differentiation16. Here we present data which indicate that the balance between hnRNP E2 and miR-328 controls the expression of many more genes involved in myeloid cell differentiation. We could show that UPF1 downregulates hnRNP E2 expression providing a link between UPF1 and hnRNP E2. Furthermore, we found that miR-328 is induced during myeloid cell differentiation and consequently, the balance between hnRNP E2 and miR-328 is altered leading to inhibition of hnRNP E2 and the concomitant upregulation of the expression of genes linked to myeloid cell maturation and function. A representative example of these proteins is the calcium binding protein S100A9 which was analyzed in detail. Taken together, our data demonstrate that cell functions such as ROS production and CD11b-mediated adhesion and migration is regulated by the hnRNP E2/miR-328 balance. Results mRNA expression analysis of downregulated proteins by UPF1 knockdown In a mass spectrometry based proteomics study we identified a set of genes which are controlled by UPF18. A subset of these proteins was downregulated in response to UPF1 knockdown in the microsomal fraction of undifferentiated cells and readjusted to control levels during differentiation (Fig. 1A and Table S1). Quantitative RT-PCR analysis of these genes revealed no significant changes in their mRNA expression (Fig. 1B), indicating that UPF1 influences gene expression on the posttranscriptional level. Identification of a C-rich motif within the 5′UTR of downregulated proteins by UPF1 knockdown Close inspection of the gene structure of the candidates which are downregulated by UPF1 knockdown revealed that 75% of the genes contain an intron within their 5′UTR. This percentage is significantly higher than the average of all human genes with a 35% likelihood of introns at this position (Fig. 2A)17. This unusual high occurrence of 5′UTR introns suggested a search for potential regulatory sequences in this set of introns. We used the motif-based sequence analysis tool “MEME”18 and identified a C-rich consensus motif (CUCCCCC, Fig. 2B,C). In some introns the motif is present twice albeit its location is not conserved. This C-rich motif has already been described as a binding site for hnRNP E2 within the 5′UTR of C/EBPα15. UPF1 knockdown upregulates hnRNP E2 expression in undifferentiated and differentiated MM6 cells The presence of the C-rich elements prompted us to investigate whether UPF1 mediates some of its cell type-dependent effects via hnRNP E2. We analysed the effect of UPF1 knockdown on hnRNP E2 expression in undifferentiated and differentiated MM6 cells by Western blot. Knockdown of UPF1 increases hnRNP E2 protein expression in undifferentiated and in 4 days differentiated MM6 cells (Fig. 3A). The data suggest that hnRNP E2 expression is downregulated by UPF1 in undifferentiated as well as in differentiated MM6 cells. Effect of UPF1 knockdown on S100A9 protein expression A high percentage of the identified UPF1-regulated genes such as S100A9, CDC42, HMGB2 and members of 14-3-3 protein family are related to cell differentiation and inflammation19202122232425. In order to investigate the mechanism behind the UPF1 effects we selected S100A9, an important regulator for myeloid cell functions, for further analysis26. It is strongly upregulated during cell differentiation and regulates the inflammatory and migratory potential of myeloid cells. It functions as a damage-associated molecular pattern molecule which is actively secreted or released from necrotic cells in response to tissue injury or stress. Therefore, S100A9 is a significant functional representative for the identified differentiation related genes. We validated the results of proteomics analysis where we saw a downregulation of S100A9 expression in undifferentiated but not in differentiated cells after UPF1 knockdown by Western blot. UPF1 knockdown caused a significant 50% reduction of S100A9 expression in undifferentiated but not in differentiated MM6 cells (Fig. 3B). These data confirm the results of the proteomics study showing that the effects of the UPF1 knockdown on S100A9 expression are dependent on the differentiation status of the MM6 cells. Reporter gene analysis of the S100A9 5′UTR The next step was to determine whether S100A9 is regulated by hnRNP E2 via the C-rich element in the 5′-UTR intron. Therefore, we performed reporter gene assays with a reporter plasmid in which the 5′-UTR of S100A9 was cloned in front of a luciferase gene. In addition, we constructed a control plasmid in which the intron was deleted (S100A9Δint) and a plasmid with a mutated C-rich element (S100A9mut). Luciferase activity was analyzed in HeLa cells without and with UPF1 and hnRNP E2 knockdown, respectively. The siRNA-mediated knockdown of UPF1 or hnRNP E2 was verified by qRT-PCR and Western blot analysis. On mRNA level, the UPF1 and hnRNP E2 expression was reduced by 80% after 24h (Fig. S1A/B). On protein level, we observed a 50% to 70% reduction for UPF1 and hnRNP E2 expression (Fig. S1C/D). The reporter gene assays revealed that the presence of the intron in the 5′UTR of S100A9 significantly increases luciferase reporter gene activity (Fig. S2). Luciferase activity of the S100A9 5′UTR construct was significantly reduced by UPF1 knockdown whereas hnRNP E2 knockdown alone had no influence on luciferase activity but abolished the UPF1 knockdown effect in the double knockdown experiment (Fig. 4A). Thus, hnRNP E2 inhibits reporter gene activity when UPF1 expression is low and the concomitant downregulation of hnRNPE2 restores reporter gene activity suggesting that hnRNP E2 functions as an inhibitor. In contrast to the S100A9 5′UTR construct, no influence of UPF1 or hnRNP E2 knockdown was observed when the intron was absent (S100A9Δint, Fig. 4B). Then, we mutated the C-rich motif of the S100A9 5′UTR construct (CTTCCCC to CTTGAGC). Similar to the S100A9Δint construct, the S100A9 mutant was unaffected by UPF1 or hnRNP E2 knockdown (Fig. 4C). These data suggest that UPF1 regulates S100A9 expression via the C-rich sequence and hnRNP E2. UPF1 downregulates hnRNP E2 expression (Fig. 3A) and reduces its inhibition of S100A9 expression via the C-rich sequence in the 5′UTR intron. The mutation of the C-rich sequence within the intron suggests that hnRNP E2 may act as splicing regulator as previously shown for CD4513. An RT-PCR with specific primers targeting the 5′UTR region of S100A9 clearly shows the two splicing isoforms (Fig. 4D). We then performed qRT-PCR to quantify the splicing pattern of S100A9 5′UTR in MM6 cells with UPF1 knockdown. As shown in Fig. 4E, knockdown of UPF1 increases differentiation-dependently the 5′UTR splicing. The expression of the 5′UTR intron was not affected by UPF1 knockdown in undifferentiated and differentiated MM6 cells, respectively (Fig. 4F). These data indicate that hnRNP E2 act as intronic splicing silencer of S100A9 in a differentiation-dependent manner. MiRNA-328 inhibits hnRNP E2-mediated suppression of S100A9 expression in differentiated MM6 cells The upregulation of hnRNP E2 in response to UPF1 knockdown is in line with the downregulation of S100A9 expression in undifferentiated MM6 cells. However, it cannot explain the observed upregulation of S100A9 expression and 5′UTR splicing in UPF1 knockdown cells during cell differentiation (Figs 1A, 3C and 4E) since there is no difference in hnRNP E2 protein expression in undifferentiated and differentiated MM6 cells (Fig. 3A). Recently, it was reported that miRNA-328 interacts with hnRNP E2 through a C-rich sequence thereby acting as a decoy16. Thus, we hypothesized that miRNA-328 might antagonize the hnRNP E2/S100A9 interaction by competing for binding to hnRNP E2. First, we analyzed miRNA-328 expression in MM6 cells during differentiation with TGFβ and calcitriol for 4 days by qRT-PCR (Fig. 3C). Cell differentiation leads to a strong upregulation of miRNA-328 expression in a time-dependent manner. As control we used a randomly chosen miRNA, miRNA-128, whose expression was not affected by TGFβ and calcitriol. No significant changes in miRNA-328 expression were observed in MM6 cells upon UPF1 knockdown (Fig. S3) which demonstrates that miRNA-328 expression is not regulated by UPF1. The strong differentiation-dependent upregulation of the miRNA328 suggests that it might inhibit repression by hnRNP E2 of the UPF1 regulated proteins through acting as a decoy as reported for C/EBPα16. We knocked down miRNA-328 to analyze inhibition of hnRNP E2 activity by miRNA-328. A specific siRNA against the stem loop region of pre-miRNA-328 was used resulting in a significant reduction of miRNA-328 expression to nearly 40% in differentiated MM6 cells (Fig. S4). In order to investigate whether miRNA-328 is responsible for the prevention of S100A9 downregulation by UPF1 knockdown in differentiated cells, the effect of miRNA-328 knockdown on the expression of the hnRNP E2 target gene S100A9 was then analyzed in undifferentiated as well as differentiated ∆UPF1 cells. Knockdown of miRNA-328 leads to a significant reduction of S100A9 expression in undifferentiated as well as in differentiated ∆UPF1 MM6 cells (Fig. 3D). The data suggest that upregulation of miR-328 expression during cell differentiation acts as hnRNP E2 decoy to prevent inhibition of hnRNP E2 target genes in differentiated cells. This is supported by the fact that upregulation of hnRNP E2 expression by UPF1 knockdown does not inhibit S100A9 expression in differentiated cells in the presence of miRNA-328 but when miRNA-328 is knocked down. Finally, it can be concluded that induction of miRNA-328 expression during cell differentiation is responsible for the inhibition of hnRNP E2-mediated repression of certain genes in differentiated cells. Influence of miRNA-328 on reactive oxygen species production and on the differentiation pattern of MM6 cells Our data presented here suggest that UPF1 regulates the expression of genes containing a C-rich sequence in their 5′UTR via the balance between hnRNP E2 and the miRNA-328. Since a disproportionate high number of genes associated with myeloid cell functions are under the control of UPF1 (Fig. 1) we hypothesized that the hnRNP E2/miRNA-328 balance could be involved in the regulation of genes required for myeloid cell functions. Therefore, we investigated whether miR-328 knockdown has any influence on leukocyte functions such as the production of reactive oxygen species (ROS) or cell differentiation. ROS production in undifferentiated and differentiated MM6 cells was analyzed using a dihydrorhodamine oxidation assay. The increase in intracellular ROS production during differentiation by TGFβ and calcitriol was significantly reduced by miRNA-328 knockdown (Fig. 5A,B). The influence of miRNA-328 knockdown on cell differentiation was assessed by the determination of various monocytic surface markers, i.e. CD33, CD11b, CD14 and CD15 using FACS analysis (Fig. 5C). CD14 is a typical marker for mature peripheral blood monoytes. As expected, CD14 is upregulated in MM6 cells during differentiation27. It is slightly increased in undifferentiated and differentiated MM6 cells in response to miRNA-328 knockdown. CD33 is a monocytic surface marker, which can be found in immature myeloid cells27. No alteration of CD33 expression was observed in response to miRNA-328 knockdown. Furthermore, MM6 cells are also positive for CD15 expression, a monocyte counter-receptor for endothelial selectins28. The expression of CD15 was decreased during differentiation with TGFβ and calcitriol, but was not influenced by miRNA-328 knockdown. Finally, we measured CD11b expression which represents a marker for mature myeloid cells29. The analysis revealed a strong upregulation of the CD11b marker during MM6 cell differentiation which was significantly reduced by miRNA-328 knockdown (Fig. 5C). These data support a regulatory role of miRNA-328 during myeloid cell maturation. Discussion Recently, the NMD factor UPF1 was identified as a critical regulator of gene expression in MM6 cells in a mass spectrometry based proteomics study8. Interestingly, expression of several proteins which were downregulated by UPF1 knockdown was readjusted to control levels during differentiation by TGFβ and calcitriol. Since there were no concomitant chances in the mRNA levels (Fig. 1B) it became obvious that UPF1 regulates the expression of these genes on posttranscriptional level, a function that might be independent from its role during NMD830 or it might be a consequence of secondary effects by NMD inhibition. Many of the identified UPF1-regulated proteins possess an intron in the 5′-UTR containing a C-rich element as a common motif. The C-rich element is the binding motif for the RNA binding protein hnRNP E2. We found that hnRNP E2 expression is slightly decreased by UPF1 which provides the functional link between both proteins. Our reporter gene assay with the S100A9 5′UTR confirmed that the C-rich element in intron 1 mediates the UPF1 effects via hnRNP E2. However, this mechanism could not explain the upregulation of S100A9 expression during cell differentiation since the hnRNP E2 levels in the controls as well as in the UPF1 knockdown cells which express elevated hnRNP E2 levels remain unchanged during differentiation, respectively. We found that miRNA-328 expression is strongly upregulated during MM6 cell differentiation (Fig. 3B) and by knockdown of miRNA-328 we could show that this miRNA acts as antagonist of hnRNP E2 thus preventing repression of its target genes in differentiated MM6 cells (Fig. 3D). The constant expression of hnRNP E2 and the cell differentiation-dependent increase in miRNA-328 expression suggest that the miRNA-328/hnRNP E2 balance is the critical determinant for hnRNP E2 activity and that upregulation of miRNA-328 expression during cell differentiation is responsible for the upregulation of hnRNP E2 target gene expression in differentiated cells (Fig. 6). Moreover, we identified a disproportionate high ratio of potential hnRNP E2 target genes with functions related to inflammation and myeloid cell differentiation. For example the expression of Rho GTPase Cdc42 is associated with monocytic differentiation31 and it is essential for regulation between myelopoiesis and erythropoiesis23. Furthermore, two members of the 14-3-3 protein family 14-3-3G and 14-3-3T were identified as novel hnRNP E2/miR-328 targets. Members of this protein family inhibit TLR mediated cytokine induction25 and control monocytic migration and differentiation3233. Additionally, we identified S100A9 as novel hnRNP E2 target gene, an important pro-inflammatory mediator in acute and chronic inflammation34. We chose the S100A9 for mechanistic investigations as it is prominently expressed in myeloid cells. Furthermore, S100A9 is an important protein for leukocyte functions which is mainly expressed in monocytes, early differentiated macrophages and neutrophils26. It forms a heterodimer with S100A8 and binds to RAGE and to TLR4, promoting inflammatory response in leukocytes353637. Moreover, S100A9 interacts with the NADPH oxidase complex to increase ROS production in myeloid cells which in turn contributes to inflammation and differentiation of monocytes3839. We hypothesized that miRNA-328, by antagonizing hnRNP E2 function, controls myeloid cell differentiation and ROS production by upregulating of gene expression relevant for myeloid cell differentiation such as S100A9. Therefore, it was particularly interesting to evaluate the influence of miRNA-328 on the differentiation pattern and the cellular ROS production during myeloid cell maturation. Indeed, we observed a significant reduction of CD11b expression in differentiated MM6 cells in response to miRNA-328 knockdown (Fig. 5C). CD11b plays an important role in the myeloid cell migration from the blood stream to the site of inflammation404142 assuming that miRNA-328 directly modulates adhesive and migrating activities of monocytes. Furthermore, miRNA-328 knockdown causes a significant reduction of ROS production in differentiated MM6 cells (Fig. 5A,B), that might be at least in part related to the decreased S100A9 expression which is an important regulator of NADPH oxidase43. Furthermore, it is known that CD11b plays a critical role in the regulation of oxidative stress in monocytes44. Taken together, our results demonstrate that the NMD factor UPF1 regulates genes with functions in myeloid cell differentiation via the balance between hnRNP E2 and miRNA-328. During monocyte maturation miRNA-328 is upregulated and antagonizes hnRNP E2 which then leads to increased ROS production as well as monocyte adhesion and migration. Materials and Methods Cell culture MM6 cells were obtained from DSMZ (DSMZ no. ACC124) and grown in RPMI-1640 medium supplemented with 10% (v/v) fetal calf serum (FCS, Biochrom AG), 100 μg/ml streptomycin (PAA), 100 U/ml penicillin (PAA), 1× non essential amino acids (Sigma Aldrich), 10 μg/ml insulin, 1 mM oxaloacetate (AppliChem) and 1 mM sodium pyruvate (PAA). Cell culture was carried out in a humidified atmosphere of 5% CO2 at 37 °C. MM6 cells were differentiated with 1 ng/ml TGFβ and 50 nM calcitriol at 37 °C, 6% CO2. The following stably transfected MM6 cells were used: MM6 control (MISSION shRNA plasmid CHCOO2, Sigma Aldrich) and MM6 ΔUPF1 (MISSION shRNA plasmid (NM_002911.2-2451s1c1, Sigma Aldrich)45. HeLa cells were obtained from DSMZ (DSMZ no: ACC57). These cells were grown in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% (v/v) fetal calf serum, 100 μg/ml streptomycin, 100 U/ml penicillin. Cell culture was carried out in a humidified atmosphere of 5% CO2 at 37 °C. Plasmid constructs S100A9 5′UTR reporter gene constructs were prepared using restriction enzymes and PCR methods. The complete 5′UTR of the S100A9 gene was PCR amplified using gDNA from MM6 cells as a template, the primers S100A9-Fwd (5′-AGTCGAGCTAG CAAACACTCTGTGTGGCTCCTCG-3′), S100A9-unspliced-Rev (5′- CTAGTACTCGAGC GTCTTGCACTCTGTCTGTGTAAT-3′) and Phusion polymerase (NEB). For amplification of spliced 5′UTR (S100A9Δint) the primers S100A9-Fwd and S100A9-spliced-Rev (5′-CTAGT ACTCGAGCGTCTTGCACTCTGTCAAAGC-3′) were used. The PCR fragments and the plasmid pGL4.10 (Promega) were digested by NheI and XhoI (NEB). The digested inserts were ligated in front of synthetic firefly luciferase (luc2) of pGL4.10 vector using T4 DNA ligase (NEB); the pGL4.10 plasmid was pretreated with antarctic phosphatase (NEB). Mutation of the C-rich sequence was generated by site directed mutagenesis PCR of the construct S100A9 leading to the plasmid S100A9mut using the primers (GTAAGTGAGCTGCCAGCTTGAGCAGGCAGAAGCCTGCCTG) and (CAGGCAGGCTTC TGCCTGCTCAAGCTGGCAGCTCACTTAC), respectively, and Pfu polymerase (Fermentas). All plasmid sequences were confirmed by DNA sequencing. Transfection 24 h prior to transfection, HeLa cells were seeded at a density of 4 × 104 cells per well. 800 ng/well of S100A9-unspliced or S100A9-spliced luciferase reporter gene plasmid and 200 ng/well of pSV40-Rluc as internal standard were transfected using Lipofectamine2000® (Invitrogen) according to manufacturer′s instructions. For co-transfection with siRNAs, 200 ng/well of reporter gene construct, 200 ng/well of pSV40-Rluc and 20 pmol/well siRNA were used for transfection with Lipofectamine2000. After 24 h, reporter gene activity was determined with the Dual-Glo™ Stop and Glow Luciferase Assay system following the manufacturer’s protocol (Promega) and measured with a Tecan infinite® M200 reader. Renilla luciferase activity was used to normalize the luciferase activity to the transfection efficacy. RNA extraction and real-time quantitative RT-PCR Total RNA was extracted with RNeasy Mini kit (Qiagen) according to manufacturer’s instructions. Residual DNA was removed by on-column DNAse digestion using RNase-Free DNase Set (Qiagen). 1 μg RNA was used for cDNA synthesis using High Capacity RNA-to-cDNA Kit (Applied Biosystems). Real-time quantitative PCR (qRT-PCR) was performed in Applied Biosystems StepOne PlusTM Real-Time PCR System (Applied Biosystem) using Power SYBR Green PCR Master Mix (Applied Biosystems). Fold inductions were calculated using 2(−ΔΔCt)-values. Primer sequences are given in Table 1. RT-PCR 0.5 μl cDNA was used for RT-PCR using 0.02 U/μl Q5® High-Fidelity DNA Polymerase (NEB) according to the manufacturer’s instructions with 4% DMSO addition. The primers S100A9 RT-PCR-F (CACTCTGTGTGGCTCCTCG) and S100A9 RT-PCR-R (CGTCTTGC-ACTCTGTCTG) were used for the amplification of S100A9 5′UTR. RNA interference UPF1 and hnRNP E2 were transiently depleted using siRNA oligonucleotides. 24 h prior to transfection, HeLa cells were seeded at a density of 4 × 104 cells per well. 20 pmol/well siRNA oligonucleotides were transfected using Lipofectamin2000® (Invitrogen) according to manufacturer′s instructions. For UPF1 knockdown, MISSION® siRNA SASI_Hs01_00101018 (Sigma Aldrich) and for hnRNP E2 knockdown, MISSION® siRNA SASI_Hs01_00319507 (Sigma Aldrich) were used. As control, a siRNA against GFP was designed (5′-UCUCUCACAACGGGCAUUU-3′). Cells were harvested 24 h after transfection. The efficiency of UPF1 or hnRNP E2 knockdown was assessed by qRT-PCR and Western blot. MicroRNA quantification using stem loop real-time RT-PCR 100 ng freshly isolated RNA were transcribed into cDNA using miRNA specific stem-loop primer. qRT-PCR using Universal Probe library probe #21 (Roche Diagnostics), TaqMan Universal PCR Master Mix 2 x (Applied Biosystem) and a miRNA specific primer was performed on in Applied Biosystems StepOne PlusTM Real-Time PCR System (Applied Biosystem). Specific primers were designed for the specific amplification of miRNA-328, miRNA-128 and the loading control U48. Stem loop primer miRNA-328: GTTGGCTCTGGTGCAGGGTCCGAGGTATTCGCAC CAGAGCCAACACGGAA, stem loop primer miRNA-128: GTTGGCTCTGGTGCAGGGTCCGAGGTATTCGCACCAGAGCCAACCTGTTC, stem loop primer snoRNA-U48: GTTGGC TCTGGTGCAGGGTCCGAGGTATTCGCACCAGAGCCAACGGTCAG, forward primer miRNA-328: GCTGGCCCTCTCTGCCC, forward primer miRNA-128: CCGGTCACAGTGAA CCGGT, forward primer snoRNA-U48: GAGTGATGATGACCCCAGGTAA, universal primer: GTGCAGGGTCCGAGGT. Stem loop reverse transcription and real time RT-PCR were preformed as described previously46. Fold inductions were calculated using 2(−ΔΔCt)-values. miRNA-328 knockdown in MM6 cells Using siDesign Center (GE Dharmacon) a specific siRNA was designed against the loop region of pre-miRNA-328 to downregulate miRNA-328 expression. 2 pmol/μl of the 3′-cholesterol-tagged ON TARGET siRNA-pre-miR-328 (GGGAGAAAGUGCAUACAGC-3′-Chl) or control siRNA (5′-UCUCUCACAACGGGCAUUU-3′-Chl) was directly added to MM6 cell culture medium. Both siRNAs were synthesized by GE Dharmacon. The efficiency of miR-328 knockdown was assessed by stem loop real time RT-PCR in 4 days differentiated MM6 cells. Western blot analysis The efficiency of UPF1 and hnRNP E2 knockdown in HeLa cells was assessed by Western blot analysis. Cells were lysed in T-PER™ tissue protein extraction reagent (Life technologies) for 30 min at 4 °C. The protein content was determined by Bradford assay (BioRad Laboratories). Western blot analysis of the cell lysates and microsomal fraction was performed as previously described8. The following antibodies were used to stain the blots: hnRNP E2 (ab77323, Abcam), UPF1 (antiserum was generously supplied by Jens Lykke-Andersen, University of California, San Diego), S100A9 (ab92507, Abcam) and β-actin (sc-1616, Santa Cruz Biotechnology). Dihydrorhodamine 123 assay About of 5 × 105 MM6 cells were resuspended in 2.5 ml of Hanks Balanced Salt Solution with Ca2+/Mg2+ (HBSS, Invitrogen), 0.5% bovine serum albumin (PAA), 1000 U catalase (Sigma), 7.5 mM glucose (Roth) and incubated for 5 min at 37 °C. Then, dihydrorhodamine 123 (DHR, Sigma) was added to a final concentration of 0.29 μM, incubated for further 15 min at 37 °C, kept on ice for 30 min and finally analyzed using FACS Canto II (Becton Dickinson). FACS analysis of surface marker About 1 × 105 MM6 cells were incubated for 30 min at room temperature with antibodies for CD11b (CD11b-PECy7, eBioscience), CD14 (CD14-APC, eBioscience), CD15 (CD15-eFluor 450, eBioscience), CD33 (CD33-PE P67.6, eBioscience), FVD eFluor® (eBioscience) or with the proper control IgGs. The optimal concentration for each antibody was adjusted according to manufacturer’s instructions. To block unspecific binding of antibodies, human Fc Block (Miltenyi) was added to the cell suspension. After washing with PBS, FACS analysis was performed using FACS Canto II (Becton Dickinson). Statistics Results are given as mean + SEM of at least three independent experiments. Statistical analysis was carried out by Student’s paired or unpaired t-test (two-tailed), one way ANOVA or respectively for the time course experiment two way ANOVA, Bonferroni post test was used. Differences were considered as significant for p < 0.05 (indicated as *p < 0.05, **p < 0.01 and ***p < 0.001) using GraphPad Prism 5.0. Additional Information How to cite this article: Saul, M. J. et al. UPF1 regulates myeloid cell functions and S100A9 expression by the hnRNP E2/miRNA-328 balance. Sci. Rep. 6, 31995; doi: 10.1038/srep31995 (2016). Supplementary Material Supplementary Information We are grateful to Andreas Malsy and Angelika Tintschl-Körbitzer for technical assistance and to Jens Lykke-Andersen for generously providing us with the antiserum for UPF1. This project was supported with funding from the Else Kröner-Fresenius Stiftung (2013_A265 and Else Kröner-Fresenius Graduiertenkolleg), the Deutsche Forschungsgemeinschaft (SFB902 and ECCPS) and LOEWE Center for Cell and Gene Therapy, Frankfurt. Author Contributions M.J.S. and S.S. performed the experiments, M.J.S., M.G., P.-J.J., D.S. and B.S. designed the experiments and M.J.S., D.S. and B.S. wrote the manuscript. Figure 1 (A) Effect of UPF1 knockdown on UPF1 target protein expression in undifferentiated and differentiated MM6 cells. Cell differentiation was performed with TGFβ and calcitriol8. (B) Effect of UPF1 knockdown on mRNA expression of the indicated UPF1 target genes in 1 day differentiated and undifferentiated MM6 cells. The relative changes to control (set as 1) are given as the mean of three independent experiments. Figure 2 (A) Occurrence of 5′UTR introns in genes detected in the proteomics study compared to the composition of the entire human genome. (B) Conserved hnRNP E2 binding motif within the 5′UTR intron of genes coding for downregulated proteins by UPF1 knockdown (www.meme.sdsc.edu). The overall height of each stack indicates the sequence conservation at the respective position (measured in bits). (C) Localization of the C-rich sequence within the 5′UTR introns. The C-rich sequence is shown as red box, the intron as black line (not drawn to scale). Figure 3 (A) Western blot analysis of hnRNP E2 protein expression in the microsomal fraction of MM6 and ∆UPF1 MM6 cells incubated with and without TGFβ (1 ng/ml) and calcitriol (50 nM) for 4 days. β-Actin served as loading control. (B) Western blot analysis of S100A9 protein expression of MM6 and ∆UPF1 MM6 cells and (D) MM6 cells and ∆miR-328 ∆UPF1 MM6 cells. The cells were incubated with and without TGFβ (1 ng/ml) and calcitriol (50 nM) for 4 days. β-Actin was used as loading control. The relative changes to control samples (set as 1) are given as mean + SEM of minimum three independent experiments; t-test, p* < 0.05; **p < 0.01. Blots are shown from one representative experiment. (C) Regulation of miRNA-328 and miRNA-128 expression during MM6 cell differentiation by calcitriol (50 nM) and TGFβ (1 ng/ml). After the indicated time points, RNA was extracted and miRNA expression was determined by qRT-PCR. The relative changes to day 0 are given as the mean + SEM of three independent experiments; two way ANOVA, Bonferroni post test, *p < 0.05, **p < 0.01. Figure 4 Luciferase reporter gene assays with S100A9 (A), S100A9Δint (B) and S100A9 mut (C) reporter plasmids. HeLa cells with knockdown of UPF1 and hnRNP E2 alone or in combination as indicated were transiently transfected. After 24 h, reporter gene activity was determined and normalized for transfection efficiency using the Dual-GloTM luciferase assay system. The relative changes in reporter gene activity are given as the mean + SEM of minimum three independent experiments; t-test, **p < 0.01, ***p < 0.001. (D) RT-PCR analysis of S100A9 5′UTR splicing in undifferentiated MM6 cells. PCR products obtained with specific primers flanking the S100A9 5′UTR intron were separated on a 3% agarose gel. (E) Effect of UPF1 knockdown on splicing of the S100A9 5′UTR intron in MM6 cells. ∆UPF1 or control MM6 cells were grown in standard medium or differentiated with TGFβ (1 ng/ml) and calcitriol (50 nM) for 1 day. Then, cells were harvested and total RNA was extracted and analyzed by qRT-PCR with primers spanning the 5′UTR intron (S100A9-5′UTR-F/R) and (F) with primers detecting specifically 5′UTR intron (S100A9-intron1-F/R). β-actin served as control. The relative changes to undifferentiated MM6 cells are given as the mean + SEM of at least three independent experiments; t-test, **p < 0.01. Figure 5 (A) Effect of cell differentiation and ∆miR-328 on the ROS production of MM6 cells. ROS production was determined with the dihydrorhodamine oxidation assay. The relative changes in ROS production to differentiated MM6 cells (set as 1) are given as mean + SEM of three independent experiments. (B) FACS histogram is shown from one representative experiment. (C) FACS analysis of CD33, CD11b, CD14 and CD15 expression in MM6 cells in response to cell differentiation and ∆miR-328. The relative changes are given as mean + SEM of three independent experiments, one way ANOVA test, Bonferroni post test, p* < 0.05, **p < 0.0, ***p < 0.001. Figure 6 Regulation of gene expression during myeloid cell differentiation by the balance between hnRNP E2 and miRNA-328. Expression of hnRNP E2 target genes is induced by the upregulation of miR-328 expression during cell differentiation. Table 1 Primer sequences used for qRT-PCR. Primer Sequence Actin-F CGGGACCTGACTGACTACCTC Actin-R CTTCTCCTTAATGTCACGCACG CDC42-F TGCACTTACACAGAAAGGCC CDC42-R CTTCTTCGGTTCTGGAGGCT 1433T-F CGGTGCTGGAATTGTTGGAT 1433T-R TTCAGCAAGGTACCGGAAGT HMGB2-F CTAAAAGGCCACCATCTGCC HMGB2-R GATAGGCCAGGGTGTTCACT TCP4-F TCAAGCTCTTCTGGCAGTGA TCP4-R GCTCTCGAAGTCTCACCTGT S100A9-5′UTR-F CACTCTGTGTGGCTCCTCG S100A9-5′UTR-R GTTCCAGCTGCGACATTTTG S100A9-intron1-F AGCTGCCAGCTTCCCCAGG S100A9-intron1-R GCTGTCAAGCTTCTTTGACAC S100A9-cds-F GTGCGAAAAGATCTGCAAAATTT(*) S100A9-cds-R GGTCCTCCATGATGTGTTCTATGA (*) THOC4-F AGGCCTGCACAGAGCGTAA THOC4-R TCCAGCGCCACGGTTT RPS14-F TCGGGCGGATTGAGGAT RPS14-R TTCCTGCGAGTGCTGTCAGA 1433G-F GGAGCGCTACGACGACATG 1433G-R AGTGGCTCATTCAGCTCTGTCA FAAA-F GAGCCAGGCGGCTACCAT FAAA-R TGCAGCATCGTCCAGTACATG hnRNP E2-F GAACTCACCATTCCAAACGATTT hnRNP E2-R TTGATTTTGGCGCCTTGAC UPF1-F CCTTCCCATCCAACATCTTC UPF1-R AACATCGGTTTATCGGGTTG (*) Primer sequence adopted from47. ==== Refs Huber R. et al. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3191910.1038/srep31919ArticleResponse of aboveground biomass and diversity to nitrogen addition – a five-year experiment in semi-arid grassland of Inner Mongolia, China He Kejian 12Qi Yu 3Huang Yongmei 1Chen Huiying 1Sheng Zhilu 1Xu Xia 1Duan Lei 41 State Key Laboratory of Earth Surface and Resource Ecology, College of Resources Science and Technology, Beijing Normal University, Beijing 100875, P.R. China2 College of Resource and Environment, Yunnan Institute of Geography, Yunnan University, Kunming 650091, P.R. China3 Inner Mongolia Research Academy of Environmental Sciences, Hohhot 010011, P.R. China4 State Key Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P.R. Chinaa ymhuang@bnu.edu.cn30 08 2016 2016 6 3191920 04 2016 28 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Understanding the response of the plant community to increasing nitrogen (N) deposition is helpful for improving pasture management in semi-arid areas. We implemented a 5-year N addition experiment in a Stipa krylovii steppe of Inner Mongolia, northern China. The aboveground biomass (AGB) and species richness were measured annually. Along with the N addition levels, the species richness declined significantly, and the species composition changed noticeably. However, the total AGB did not exhibit a noticeable increase. We found that compensatory effects of the AGB occurred not only between the grasses and the forbs but also among Gramineae species. The plant responses to N addition, from the community to species level, lessened in dry years compared to wet or normal years. The N addition intensified the reduction of community productivity in dry years. Our study indicated that the compensatory effects of the AGB among the species sustained the stability of grassland productivity. However, biodiversity loss resulting from increasing N deposition might lead the semi-arid grassland ecosystem to be unsustainable, especially in dry years. ==== Body Nitrogen (N) is the primary limiting nutrient for plant growth in many terrestrial ecosystems1. Therefore, N fertilization has been widely used to improve soil N availability and promote plant productivity in N-limited ecosystems2. Because of increasing anthropogenic emissions, atmospheric N deposition has substantially increased on a global scale and is a large N source for many terrestrial ecosystems234. In semi-arid areas of northern China, the current rate of total N deposition is likely to be greater than 1.5 g N m−2 yr−1 5. In addition, a higher N deposition rate could occur in the future6. Increasing the N input would strongly affect the plant community and would further affect ecosystem functions, such as global carbon cycles78910. N enrichment usually increases community productivity by stimulating plant growth111213. However, increased N input would reduce the niche dimension, lead to long-term biodiversity loss14, and further decrease ecosystem functions15. Individual species and functional groups of the plant community respond to N enrichment differently as a result of the inherent differences of N-use efficiency and strategies1116, causing cascading effects on competitive exclusion, species composition change and biodiversity loss4817. Thus, a better understanding of how the productivity, biodiversity, species and community structure respond to N enrichment is essential for managing and protecting ecosystems. Studies on N deposition and its effects on natural vegetation primarily concern temperate humid regions of the northern hemisphere4. In arid and semi-arid ecosystems, plant diversity and primary production are limited by both water and N1218. These grasslands are sensitive to N enrichment because the availability of N is chronically low in these regions1219. In these ecosystems, even small amounts of N fertilization may have important repercussions for their biodiversity and ecosystem functions20. Previous studies have suggested that plant responses to N addition are greater in mesic than in dry ecosystems11, and that the N thresholds for calcareous grasslands are higher than those for acid grasslands21. However, how semi-arid ecosystems respond to N enrichment remains unknown. Drought is an extreme climatic event that occurs frequently in semi-arid zones. The frequency and severity of droughts are expected to increase in these zones22. Drought reduces plant cover and productivity23 and changes the composition of species by restraining dominant species or reducing the emergence of annual plants24. With the resumption of rainfall after a drought, both vegetation cover and productivity recover2324. N addition would accelerate the productivity of aboveground tissues, resulting in increased evaporative demands, higher drought susceptibility and weakened competitive species performance25. Furthermore, N addition can enhance grassland recovery after a drought in arid environments24. However, the effect of N addition on semi-arid grassland with fluctuating precipitation has not been well demonstrated. To understand how plant communities respond to increasing N deposition in a semi-arid ecosystem, we conducted a 5-year field experiment with six levels of N addition to simulate N deposition in a Stipa krylovii steppe of Inner Mongolia. The aims of this study are to investigate the response of aboveground biomass and species richness to N addition, and the interannual differences of these responses. Methods Study area The experimental site is located at Taibus Banner in Inner Mongolia, China (115°29′10″E/42°06′44″N). The altitude is 1450 m. It is a typical semi-arid agro-pastoral ecotone between the North China Plain and the Inner Mongolia Plateau. The climate is continental and has a mean annual temperature of 1.6 °C, annual precipitation of 400 mm, and annual pan evaporation of 1900 mm. The growing season usually starts in late April and ends in late September. The temperature and precipitation were in a normal range during the years of experiment (2010–2015), except for a drought in 2011. In 2011, the precipitation during the growing season was much less than that in the other years (Table 1). The soil is a light chestnut soil (pH = 7.5). The organic carbon content and total nitrogen content are 17.44 g kg−1 and 1.80 g kg−1, respectively26. The annual natural N deposition is approximately 3.43 g N m−2 yr−1 27. The experimental grassland is Stipa krylovii steppe, which is a typical grassland of the Eurasian steppe. Dominant species are Stipa krylovii and Artemisia frigida. The permanent experimental area (>100 ha) has been fenced with barbed wire since 1998 to exclude grazing. Experimental design The N addition experiment pre-treatment was conducted on the fenced area in May 2010. The experimental site was divided into 18 plots of 3 × 6 m with additional 1-m buffer zone between the plots. The plot corners were marked with polyvinyl chloride (PVC) stakes that were approximately 1 m tall. The N addition experiment was implemented starting in 2011 with six treatments: 0 (N0), 2 (N2), 5 (N5), 10 (N10), 25 (N25), and 50 g N m−2 yr−1 (N50). The six treatments were randomly assigned to the 18 plots (three replicate plots per treatment). The NaNO3 solution was sprayed two times per year in early June and early July, with half of the annual amount applied each time. All plots received the same additional amount of water, which was approximately 0.5% of the annual rainfall. The N addition from well water was <0.005 g N m−2 yr−1. Sampling and measurements Sampling and measurements were carried out in early September of each year, beginning in 2010. The aboveground plant material was harvested in three 0.5 m × 0.5 m quadrats for each plot. After harvest, we sorted all living plants to the following species: Stipa krylovii, Artemisia frigida, Convolvulus ammannii, Cleistogenes squarrosa, Leymus chinensis, and remaining species. All species were divided into two functional groups: grasses and forbs. The remaining species were almost all forbs; thus, they were classified as forbs. Samples were oven dried at 65 °C for 48 hours to constant weight. All biomass variables were converted to units of g m−2. Species richness was surveyed as the number of species in each plot. Statistical analyses The aboveground biomass (AGB) and species richness of each plot in 2010 prior to treatment were used as a baseline against which all treatments comparisons were made. The response ratios (R)28 of the AGB and species richness were calculated to quantify the impacts of N application by comparing the variables of the after-treatment (2011–2015) to that of the pre-treatment (2010). The response ratio was calculated as where VA is the value of the variable in each plot with the N application and VP is the pre-treatment value of the same variable in the same plot. To exclude the effects caused by other factors, we revised the response ratios by the correction factor (cf)29. The cf was calculated as where is the mean pre-treatment value of the variable in the control plot (N0) and is the mean after-treatment value of the same variable in the control plot. To perform statistical analyses, we calculated the relative effects of N addition (E) by transforming the revised response ratios to the natural log, which was calculated as where R is the response ratios and cf is the correction factor. Then, we calculated the relative effects of each N treatment on the total AGB, species richness, the AGB of functional groups and the common species in each N treatment year. The relative effects would be zero, positive or negative if no change, increased or decreased effects occurred with the N addition, respectively. The relative effects of N addition on these variables were tested in a repeated-measure analysis of variance (ANOVA). The year was treated as a repeated effect. N treatments entered the model as class variables, and they were defined as continuous variables. The Student-Newman-Keuls (SNK) post-hoc test was performed to evaluate the differences in the relative effects at different N treatments and among experimental years for each variable. Least-squares regression line was applied in describing the relationship between the relative effects and nitrogen loads. All analyses were carried out using the statistical software SPSS21.0 (IBM Company, Armonk, NY, USA). Results Basic community characteristics in pre-treatment year The total AGB of the treatments ranged from 90.28 to 132.66 g m−2 in 2010, before the experiment was implemented (Table 2). Perennial grasses and forbs accounted for 34% and 65% of the total AGB, respectively, whereas the annuals accounted for less than 1%. Thirty-three species presented in the experimental site. The species richness of the treatments ranged from 5.80 to 6.73. The common species were Stipa krylovii, Artemisia frigida, Convolvulus ammannii, Cleistogenes squarrosa and Leymus chinensis. These common species accounted for almost 75% of the total AGB of the community (Fig. 1). There were no significant differences in the total AGB, the AGB of the functional groups, the AGB of common species and the species richness among the treatments in 2010 (Table 2). Response of species composition to nitrogen addition The species composition changed noticeably after three years of N addition. In 2014 and 2015, along with N addition levels, the proportion of grasses increased whereas that of forbs decreased; the proportion of Leymus chinensis increased whereas that of Stipa krylovii and Artemisia frigida decreased. In particular, Leymus chinensis became one of the most dominant species in the high N treatments (Fig. 1). Effects of nitrogen addition on the total AGB and species richness The total AGB did not have a noticeable increase in the N addition experiment, as indicated by the almost neutral overall relative effects (Fig. 2a). The repeated measures ANOVA analysis also showed that the N addition had no significant effects on the total AGB (F = 1.811, p = 0.185, Table 3). However, the year had a significant effect on the total AGB (F = 19.994, p < 0.05, Table 3). N addition had an obvious negative effect on the total AGB in 2011. However, the relative effects on the total AGB were positive in other experimental years (Fig. 2a). There was an obvious decrease in species richness with N addition in our experiment, as indicated by the negative relative effects on species richness both in the whole experimental period and in individual years (Fig. 2b). Furthermore, the N addition and the year had significant effects on the species richness (F = 6.040, p = 0.005; F = 6.235, p = 0.007; respectively, Table 3). The species richness decreased with increasing N addition and experimental time (Fig. 2b). Effects of nitrogen addition on the AGB of the functional groups The grasses and the forbs had opposite responses to N addition. The relative effects of N addition on the AGB of grasses were negative in the lower N treatments (N 2, N5 and N10) and positive in the higher N treatments (N 25 and N 50) overall (Fig. 3a). In contrast, the relative effects on the AGB of forbs were positive in the lower N treatments and negative in the higher N treatment overall (Fig. 3b). The results of the repeated measures ANOVA showed that the N addition had no significant effects on the AGB of grasses (F = 1.757, p = 0.196, Table 3). However, the year had a significant effect on the biomass of grasses (F = 4.009, p = 0.015, Table 3). The AGB of grasses increased significantly with N addition over the experimental time (Fig. 3a). The N addition, the year, and the interaction of N×Year had significant effects on the AGB of forbs (F = 3.278, p = 0.043; F = 5.808, p = 0.002; F = 3.609, p = 0.001; respectively, Table 3). The relative effects on the AGB of forbs increased with increasing N application and experimental time (Fig. 3b). More notably, the AGB of forbs decreased obviously in 2011, as indicated by a large negative effect. However, it had recovered to pre-treatment levels in 2012, as indicated by a positive effect (Fig. 3b). Effects of nitrogen addition on the AGB of common species Species showed different overall responses to N addition in the experiment. The relative effect on AGB of Leymus chinensis was positive and increased more in the higher N treatments (Fig. 4c). It was positive in the lower N treatments (N2, N5, and N10) and negative in the higher N treatments (N25 and N50) for Stipa krylovii and Artemisia frigid (Fig. 4a,d). It was negative and declined more in the higher N treatments for Cleistogenes squarrosa and the remaining species (Fig. 4b,f). It was negative and unchanged among the six N treatments for Convolvulus ammannii (Fig. 4e). More notably, there was a clear compensatory effect of biomass among Gramineae species. Along with the N addition levels, the biomass of Stipa krylovii and Cleistogenes squarrosa decreased whereas that of Leymus chinensis increased (Fig. 4a–c). Species responses to N addition were lessened in 2011 compared to the other experimental years. In the year 2011, the response differences were minimal among the six N treatments for all species, as indicated by a slope of almost zero. However, the N addition enhanced the response of species in the other years because the response differences increased with increasing N application and experimental time (Fig. 4a–f). Discussion Response of the total AGB to N addition from community to species The total AGB of the grassland did not change significantly in the N addition experiment. N addition generally have a positive effect on grassland productivity1130. This could be because the N addition lessens the N limitation by increasing soil N availability and thus stimulates plant growth31. However, many experiments have found that few or no productivity changes occurred with N addition in the Inner Mongolian steppe32 and for some other grasslands2433. The lack of grassland AGB response to N addition in our experiment might be largely attributed to the three factors that follow. First, primary production was co-limited by available water and N in semi-arid ecosystems121834. Hence, water availability mediated the response of productivity to N addition35. The slope of the total AGB along with N addition was more gentle in the dry year (annual rainfall was approximately 260.10 mm in 2011) in our experiment (Fig. 2a). Though the increasing N additions enhanced the soil N availability, the limited precipitation might have restrained the productivity response to N addition in our experiment. Second, our experiment was launched in an area with a high natural N deposition of approximately 3.43 g N m−2 yr−1 27. Previous studies have suggested that high background N deposition might weaken the effects of N addition36. Furthermore, there was a lower N saturation threshold of less than 10 g N m−2 yr−1 in a similar grassland of the Inner Mongolian steppe32. Therefore, the amount of the added N might have easily reached or exceeded the N saturation threshold in our experiment, which might have reduced the sensitivity of the vegetation to N additions37. Finally, there were opposite responses with respect to AGB between the grasses and the forbs (Fig. 3), which might have buffered the responses of community AGB to N addition and increased community stability38. There was a compensatory effect of N addition on AGB between the grasses and the forbs in this experiment. The results are consistent with previous experiments that were conducted in the Inner Mongolian steppe; the biomass of grasses increased with N addition, whereas that of forbs decreased3239. In addition, we found that there was a clear compensatory effect of biomass among Gramineae species, i.e., Stipa krylovii, Cleistogenes squarrosa and Leymus chinensis. After three years of the experiment (2014 and 2015), Leymus chinensis became one of the most dominant species in high N plots (Fig. 1). It indicated that Leymus chinensis was better able to take advantage of the increased N, thus resulting in an increased dominance of competition40. Additionally, the competitive advantages of the species that are consistently dominant in a low N environment were dwindling with increasing N addition41. This could be explained by the difference in their fine root morphology, the favorable effects of nitrogen and the subsequent growth responses resulting from their different nitrogen and water use efficiencies394243. Species showed differential responses to N addition, which led to a reordering of species composition in this study. Similar results have been obtained from research in grassland ecosystems844. This may be a consequence of interspecific competition caused by interspecific differences in resource-use strategies and in N re-sorption proficiency30. Response of species richness to N addition There was a noticeable decrease in species richness with N addition in our experiment. It has been verified in the Inner Mongolian steppe9113139 and other regions of the world4546, that N addition causes an obvious reduction in species richness. Our results indicate that species had differential growth responses to N enrichment (Fig. 4). This might be a result of their inherent difference in N-use efficiency and strategies1116. The differential growth responses thus cause cascading effects on competitive exclusion817. However, our results support the hypothesis of asymmetric competition, specifically, that the initial densities and establishment timing of competing species have large effects on the dynamics of plant competition because they lead to asymmetries in plant size and resource capture47. The grasses increased whereas the forbs decreased with N addition (Fig. 3) and N addition suppressed litter decomposition, especially grasses litter decomposition in our experiment (Supplementary Fig. S1). Accordingly, litter biomass increased with N addition in our experiment (Supplementary Fig. S2). The increase in grasses might result in increased litter accumulation and decreased light intensities at the ground surface in the community, thereby suppressing seed germination, inhibiting seedling establishment and increasing the mortality of small plants39. Moreover, the eutrophication caused by N addition simplifies habitats by decreasing their niche dimensionality, which would lead to loss of biodiversity14. Interannual differences in response to N addition Our findings suggested that plant responses to N addition were lessened in the dry year (2011) than in wet or normal years. The results are consistent with previous studies, which suggested that the response of plants to N was dependent on the amount of rainfall, with a more noticeable response as a result of high amounts of precipitation1213. It indicates that nitrogen and water availability is tightly linked through biogeochemical feedbacks18. In addition, N addition had an obvious negative effect on the total AGB in the dry year (Fig. 2a). A previous study suggested that N addition resulted in decreased soil moisture34 and that it exacerbated the decrease of water availability in soil as a result of drought conditions. Then, the decrease of water availability might increase NH4+ concentration and accelerate acid producing soil processes4849. Finally, increased soil acidification suppresses plant growth and yield50. Accordingly, our results indicate that N addition exacerbates the impacts of moisture stress on the ecosystems in this arid area and that increasing N deposition might intensify productivity reductions that are caused by drought conditions. Our findings suggested that the total AGB and species richness had a tendency to recover with N addition after drought conditions (2012). The results agree with previous research that drought conditions depress seed germination and plant growth and that increased N input can enhance grassland recovery after a drought24. Moreover, our findings indicate that the recovery may be a result of an increase of the forbs (Fig. 3b). This could be explained by the increased probabilities of a new species entering a community as a result of increased resource availability and altered disturbance regimes51. Conclusions The differential responses of species and the compensatory effects of AGB between grasses and forbs or among Gramineae species might sustain the stability of grassland productivity in the context of increased N addition. However, biodiversity loss resulting from increasing N deposition might lead the semi-arid grassland ecosystem to be more unsustainable, especially in dry years. Long-term studies are needed to further test these findings and uncover their possible mechanisms. Additional Information How to cite this article: He, K. et al. Response of aboveground biomass and diversity to nitrogen addition – a five-year experiment in semi-arid grassland of Inner Mongolia, China. Sci. Rep. 6, 31919; doi: 10.1038/srep31919 (2016). Supplementary Material Supplementary Information We are grateful for the financial support of the National Natural Science Foundation of China (41371069) and the Teacher training program of Yunnan University (XT412003). We would like to thank the anonymous reviewers for their excellent suggestions. Author Contributions Y.H. designed the experiment. Y.Q., K.H., H.C. and Z.S. conducted the experiment. X.X. and L.D. assisted the data collection. K.H. wrote the main manuscript text and prepared the figures. Y.H. and L.D. revised the first drafts. All authors reviewed the manuscript. Figure 1 Figure 2 Relative effects of N addition on the total AGB (a) and species richness (b). Horizontal lines indicate neutral effects. Fitted lines are based on the least-squares regression (Supplementary Table S1). Figure 3 Relative effects of N addition on the AGB of grasses (a) and forbs (b). Horizontal lines indicate neutral effects. Fitted lines are based on the least-squares regression (Supplementary Table S1). Figure 4 Relative effects of N addition on the AGB of the common species. Horizontal lines indicate neutral effects. Fitted lines are based on the least-squares regression (Supplementary Table S1). Table 1 Climate characteristics during the experiment (2010–2015). Year Growing season (April to September) Annual precipitation (mm) Average monthly temperature (°C) Average monthly precipitation (mm) 2010 13.30 ± 1.30 a 67.05 ± 7.67 a 492.60 2011 13.15 ± 1.02 a 36.38 ± 3.43 b 260.10 2012 13.47 ± 0.81 a 68.20 ± 8.97 a 487.90 2014 14.00 ± 0.74 a 54.50 ± 3.21 a 371.90 2015 13.22 ± 0.81 a 60.53 ± 5.25 a 440.10 Different letters represent significant interannual differences for average monthly temperature or precipitation at p < 0.05, tested by one-way ANOVA (n = 6); mean ± standard error is shown. Table 2 Mean ± standard error of the total aboveground biomass (AGB), species richness, the AGB of functional groups and common species before the N addition experiment (2010) assigned to the six treatments.   N0 N2 N5 N10 N25 N50 F p The total AGB 126.25 ± 17.59 109.48 ± 14.74 132.66 ± 10.03 90.28 ± 11.77 128.21 ± 6.67 104.25 ± 8.49 1.826 0.175 Species richness 6.73 ± 0.59 6.40 ± 0.50 6.13 ± 0.18 5.67 ± 0.37 6.27 ± 0.18 5.80 ± 0.46 0.909 0.507 Functional groups Grasses group 35.59 ± 3.74 39.06 ± 6.61 46.12 ± 4.66 46.28 ± 5.31 40.96 ± 9.13 28.23 ± 11.5 0.873 0.527 Forbs group 90.66 ± 15.6 70.42 ± 19.13 86.54 ± 11.98 44.01 ± 9.34 87.25 ± 11.61 76.02 ± 10.5 1.668 0.217 Common species Artemisia frigida 62.67 ± 13.95 61.48 ± 18.91 32.56 ± 2.44 12.78 ± 4.06 51.85 ± 13.01 48.31 ± 14.9 2.279 0.112 Stipa krylovii 24.58 ± 7.78 26.99 ± 10.54 32.31 ± 10.21 27.1 ± 1.26 28.03 ± 5.41 22.59 ± 8.56 0.172 0.968 Leymus chinensis 2.49 ± 1.18 2.58 ± 1.93 4.31 ± 1.56 6.78 ± 3.99 4.02 ± 0.46 0.49 ± 0.37 1.138 0.392 Convolvulus ammannii 3.62±0.84 3.42 ± 1.11 11.61 ± 7.06 9.15 ± 3.95 4.17 ± 1.55 13.23 ± 9.93 0.678 0.648 Cleistogenes squarrosa 8.52 ± 6.67 9.50 ± 2.43 9.50 ± 4.29 12.40 ± 0.86 8.91 ± 3.27 5.15 ± 3.52 0.352 0.872 Remaining species 25.06 ± 5.81 17.52 ± 5.18 29.25 ± 3.48 24.59 ± 11.61 27.8 ± 9.75 21.14 ± 4.37 0.348 0.874 Differences between N treatments are indicated with p-values (one-way ANOVA, Num df = 5). Note: The units of the biomass are g m−2. Table 3 Repeated measures ANOVA for the relative effects of the total aboveground biomass (AGB), species richness, the AGB of functional groups and common species to N addition from 2011 to 2015.   Nitrogen (Num df = 5) Year (Num df = 3) Nitrogen × Year (Num df = 15) Effect F p F p F p The total AGB 1.811 0.185 19.994 0.000* 1.350 0.225 Species richness 6.040 0.005* 6.253 0.007* 1.246 0.314 Functional groups Grasses group 1.757 0.196 4.009 0.015* 1.320 0.241 Forbs group 3.278 0.043* 5.808 0.002* 3.609 0.001* Common species Artemisia frigida 24.804 0.000* 15.001 0.000* 10.476 0.000* Stipa krylovii 0.935 0.493 2.519 0.110 1.704 0.151 Leymus chinensis 2.208 0.121 7.573 0.005* 3.721 0.008* Convolvulus ammannii 0.489 0.778 3.480 0.026* 1.738 0.087 Cleistogenes squarrosa 3.244 0.044* 9.081 0.000* 3.183 0.002* Remaining species 0.750 0.602 4.310 0.011* 0.755 0.714 Note: *p < 0.05 indicates significant differences from repeated measures ANOVA. ==== Refs Vitousek P. M. & Howarth R. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3190010.1038/srep31900ArticleDBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies Ye Chengxi a12Hill Christopher M. 1Wu Shigang 3Ruan Jue 3Ma Zhanshan (Sam) b21 Department of Computer Science, Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742, USA2 Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223 China3 Agricultural Genome Institute, Chinese Academy of Agricultural Sciences, No.7 Pengfei Road, Dapeng New District, Shenzhen, Guangdong 518120, Chinaa cxy@umd.edub samma@uidaho.edu30 08 2016 2016 6 3190017 11 2015 20 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The highly anticipated transition from next generation sequencing (NGS) to third generation sequencing (3GS) has been difficult primarily due to high error rates and excessive sequencing cost. The high error rates make the assembly of long erroneous reads of large genomes challenging because existing software solutions are often overwhelmed by error correction tasks. Here we report a hybrid assembly approach that simultaneously utilizes NGS and 3GS data to address both issues. We gain advantages from three general and basic design principles: (i) Compact representation of the long reads leads to efficient alignments. (ii) Base-level errors can be skipped; structural errors need to be detected and corrected. (iii) Structurally correct 3GS reads are assembled and polished. In our implementation, preassembled NGS contigs are used to derive the compact representation of the long reads, motivating an algorithmic conversion from a de Bruijn graph to an overlap graph, the two major assembly paradigms. Moreover, since NGS and 3GS data can compensate for each other, our hybrid assembly approach reduces both of their sequencing requirements. Experiments show that our software is able to assemble mammalian-sized genomes orders of magnitude more quickly than existing methods without consuming a lot of memory, while saving about half of the sequencing cost. ==== Body The Human Genome Project (HGP), which is perhaps the largest biomedical research project humans have ever undertaken, is responsible for greatly accelerating the advancement of DNA sequencing technologies1. Three generations of DNA sequencing technologies have been developed in the last three decades, and we are at the crossroads of the second and third generations of the sequencing technologies. Third generation sequencing (3GS) technology promises to significantly improve assembly quality and expand its applications in biomedical research and biotechnology development. However, lack of efficient and effective genome assembly algorithms has arguably been the biggest roadblock to the widespread adoption of 3GS technologies. 3GS long reads (averaging up to 5–20 kb per run at this time) usually have high error rates: ~15% with PacBio sequencing2, and as high as ~40% with Oxford Nanopore sequencing3. These high error rates make the assembly of 3GS sequences seem disproportionally complex and expensive compared to the assembly of NGS sequences. As a comparison, the whole genome assembly of a human genome using 3GS data was first reported to have taken half a million CPU hours4 compared to ~24 hours with Illumina NGS sequencing data5. Consequently, in practice, many applications of 3GS technology have been limited to re-sequencing bacteria and other small genomes6. While software for 3GS assembly has made important improvements27891011121314151617, especially for high coverage data, the software is still quite slow and not ideally suited for modest coverage data. Another major issue is that the sequencing cost of 3GS technology, while decreasing with time, is still at least an order of magnitude more expensive than the popular Illumina NGS sequencing at the time of this work. While the evolution of genome assembly software solutions has been influenced by multiple factors, the most significant one has been the length of the sequences18. Although increasing sequence lengths may simplify the assembly graph6, the sequence length also has a critical impact on the computational complexities of genome assembly. Computational biologists have historically formulated the genome assembly problem as a graph traversal problem181920, i.e., searching for a most likely genome sequence from the overlap graph of the sequence reads in the case of the first generation sequencing technology. The string graph and the best overlap graph are specific forms of the Overlap-Layout-Consensus (OLC) paradigm that are more efficient by simplifying the global overlap graph192122. The read-based algorithms, aiming to chain the sequencing reads in the most effective way, are computationally expensive because pair-wise alignment of the sequences is required to construct the overlap graph. This issue was tolerable for the relatively low amount of sequences produced from the low-throughput first generation sequencing technologies, but quickly became overwhelming with the enormous amount of short reads produced by high-throughput NGS data. The strategy of chopping the sequencing reads into shorter and overlapping k-grams (so-termed k-mers) and building links between the k-mers, was developed in the de Bruijn graph (DBG) framework to simplify NGS assembly. Assembly results are extracted from the linear (unbranched) regions of the k-mer graph in this approach20. The overlap graph model or the OLC-based software packages, such as Celera Assembler1, AMOS23 and ARACHNE24, originally used for assembling the first generation sequence data, were also adopted for the NGS assembly before DBG-based approaches became the de facto standard. Newer 3GS technologies, including single-molecule, real-time sequencing (SMRT) and Oxford Nanopore sequencing, produce much longer reads than NGS. The longer reads from 3GS technology make the OLC approaches, which were originally used in the first generation genome assembly, feasible again. Nevertheless, the high error rates of current 3GS technologies render the existing OLC-based assemblers developed for relatively accurate sequences unusable. Similarly, the error-prone long reads make the DBG full of branches and therefore unsuitable for 3GS assembly. Faced with these challenges, the developers of 3GS technology have resorted to using error correction techniques279101317 to create high quality long reads and reusing the algorithms originally developed for the first generation sequence assembly. However, error correction for these long reads require extensive computational resources, even for small microbial genomes. Moreover, the high sequencing depth (usually 50x–100x) required by existing 3GS genome assemblers increases sequencing cost significantly, especially for large genomes. These issues have put 3GS technology at a severe disadvantage when competing against widely used NGS technology. In this article, we introduce algorithmic techniques that effectively resolve many of these issues. But first, we present a brief account of the existing genome assembly software technologies to put our contribution in proper context. Researchers began with scaffolding approaches such as AHA16, PBJelly15 and SSPACE-LongRead11 to patch the gaps between high quality assembly regions, i.e., first build a scaffold by aligning reads to the contigs and then use reads that span multiple contigs as links to build a scaffold graph. In ALLPATHS-LG14 and Cerulean12, long reads are used to find the best path in the de Bruijn graph that bridges the gaps between large contigs. Although these software packages have indeed achieved important advances for 3GS genome assembly, resolving intricate ambiguities is inherently difficult and can lead to structural errors. Furthermore, the underlying graph search algorithms usually have exponential complexity with respect to the search depth and thus, scales poorly; highly repeating regions (such as long repeats of simple sequences) will lead to large search depths and are not resolvable. In addition, the more powerful read overlap graph structure (of the long reads) was not fully explored in all these approaches. Often these algorithms rely on heuristics such as contig lengths and require iterations1214. To circumvent these important issues associated with the hybrid approach, a Hierarchical Genome-Assembly Process (HGAP)13 was developed using a non-hybrid strategy to assemble PacBio SMRT sequencing data, which does not use the NGS short reads. HGAP contains a consensus algorithm that creates long and highly accurate overlapping sequences by correcting errors on the longest reads using shorter reads from the same library. This correction approach was proposed earlier in the hybrid setting and is widely used in assembly pipelines291017. Nonetheless, this non-hybrid, hierarchical assembly approach requires relatively high sequencing coverage (50x–100x) and substantial error correction time to obtain satisfactory results. It is noteworthy that most of the algorithms we reviewed here were originally designed for bacterial-sized genomes. Though recent advancements in aligning erroneous long reads625 have also shortened the computational time of 3GS assembly, running these programs on large genomes, especially mammalian-sized genomes, usually imposes a large computational burden (sometimes up to 105 or 106 CPU hours) more suited to large computational clusters and well beyond the capability of a typical workstation. In this study, we design algorithms to enable efficient assembly of large mammalian-sized genomes. We observe that per-base error correction of each long erroneous reads and their pair-wise alignment takes a significantly large portion of time in existing pipelines, but neither of these is necessary at an initial assembly stage. If all sequencing reads are structurally correct (non-chimeic), one can produce a structurally correct draft genome and improve the base-level accuracy in the final stage, as was originally done in the OLC approach. Taking advantage of this observation, we develop a base-level correction-free assembly pipeline by directly analyzing and exploiting overlap information in the long reads. Unlike previous approaches, we use the NGS assembly to lower the computational burden of aligning 3GS sequences rather than just polishing 3GS data. This allows us to take advantage of the cheap and easily accessible NGS reads, while avoiding the issues associated with existing hybrid approaches mentioned previously. Meanwhile, since NGS and 3GS are independent of each other, the sequencing gaps in one type of data may be covered by the data from the other. The utilization of NGS data also lowers the required sequencing depth of 3GS, and the net result is reduced sequencing cost. Hence, we get the best of both worlds of hybrid and non-hybrid assembly approaches. Specifically, we map the DBG contigs from NGS data to the 3GS long reads to create anchors for the long reads. Each long read is (lossily) compressed into a list of NGS contig identifiers. Because the compressed reads are often orders of magnitude shorter than the original reads, finding candidate overlaps between them becomes a simple bookkeeping problem and the approximate alignments and overlaps can be calculated cheaply with the help of the contig indentifiers. An overlap graph is constructed by chaining the best overlapped-reads in the compressed domain. The linear unbranched regions of the overlap graph are extracted and uncompressed to construct the draft assembly. Finally, we polish the draft assembly at the base-level with a consensus module to finish the assembly. Overall, compared with the existing approaches, our algorithm offers an efficient algorithmic solution for assembling large genomes with 3GS data in terms of computational resources (time and memory) and required sequencing coverage while also being robust to sequencing errors. Furthermore, our pipeline utilizes the reads overlap information directly and provides an efficient solution to the traditional read threading problem, which is valuable both theoretically and practically even for the NGS assembly2026. Methods and Implementations Our algorithm starts with linear unambiguous regions of a de Bruijn graph (DBG), and ends up with linear unambiguous regions in an overlap graph (used in the Overlap-Layout-Consensus framework). Due to this property, we dub our software DBG2OLC. The whole algorithm consists of the following five procedures, and we implement them as a pipeline in DBG2OLC. Each piece of the pipeline can be carried out efficiently.Construct a de Bruijn graph (DBG) and output contigs from highly accurate NGS short reads. Map the contigs to each long read to anchor the long reads. The long reads are compressed into a list of contig identifiers to reduce the cost of processing the long reads (Fig. 1A). Use multiple sequence alignment to clean the compressed reads, and remove reads with structural errors (or so-called chimeras) (Fig. 2). Construct a best overlap graph using the cleaned compressed long reads (Fig. 1B). Uncompress and chain together the long reads (Fig. 1C), and resort to a consensus algorithm to convert them into DNA sequences (Fig. 1D). Details for procedure (2–5) are explained below. The explanation of procedure (1) can be found in our previous SparseAssembler for NGS technology5 and is omitted here. Availability The source code and a compiled version of DBG2OLC is available in the following site: https://github.com/yechengxi/DBG2OLC. Reads Compression We use a simple k-mer index technique to index each DBG contig and map the pre-assembled NGS contigs back to the raw sequencing reads as anchors. The k-mers that appear in multiple contigs are excluded in our analysis to avoid ambiguity. Empirically for PacBio reads, we found that using k = 17 were adequate for all our experiments. For each 3GS long read, we report the matching contig identifiers as an ordered list. A contig identifier is reported if the number of uniquely matching k-mers in that contig is above a threshold, which is adaptively determined based on the contig length. We set this threshold in the range of (0.001~0.02)*Contig_Length. This easily tuneable threshold parameter allows the user to find a balance between sensitivity and specificity. With low coverage datasets, this parameter is set lower to achieve better sensitivity; otherwise it is set to higher to enforce better accuracy. In all our experiments, the contigs are generated with our previous SparseAssembler5. After this procedure, each read is converted into an ordered list of contig identifiers. An example of such a list is {Contig_a, Contig_b}, where Contig_a and Contig_b are identifiers of two different contigs. We also record the orientations of these contigs in the mapping. This compact representation is a lossy compression of the original long reads. We term the converted reads as compressed reads in this work. A compressed read is considered to be equivalent to its reverse complement, and the same compressed reads are then collapsed. Since a de Bruijn graph can efficiently partition the genome into chunks of bases as contigs, this lossy compression leads to orders of magnitude reduction in data size. Moreover, the compact representation can span through small regions with low or even no NGS coverage; these important gap regions in NGS assembly can be covered by 3GS data. Likewise, small 3GS sequencing gaps may be covered by NGS contigs. These sequencing gaps will be bridged in the final stage. Similarity detection between these compressed reads becomes a simpler bookkeeping problem with the identifiers and can be done quickly with low memory. To demonstrate the effectiveness of this strategy, we ran it over five datasets including genomes of different sizes and different sequencing technologies (Table 1, resources can be found in the Supplementary Materials). The compression usually leads to three factors of reduction in read length with 3GS. Ultra-fast Pair-wise Alignments Most existing algorithms rely on sensitive algorithms2728 to align reads to other reads or assemblies. In our approach, since the compressed reads are usually much shorter than the original reads, alignments of these compressed reads can be calculated far more efficiently. We adopt a simple bookkeeping strategy and use the contig identifiers to build an inverted-index. Each identifier points to a set of compressed reads that contain this identifier. This inverted-index helps us to quickly select the potentially overlapping reads based on shared contig identifiers. Alignments are calculated only with these candidate compressed reads. The alignment score is calculated using the Smith-Waterman algorithm29; the contig identifiers that can be matched are positively scored while the mismatched contig identifiers are penalized. Scores for match/mismatch are calculated based on the involved contig lengths or the number of matching k-mers in the previous step. With the compressed reads, our algorithm can finish pair-wise alignments in a small amount of time. As discussed previously, state-of-the-art assembly pipelines usually resort to costly base-level error correction algorithms to correct each individual read2781013, which they then feed into an existing assembler. However, an important finding of this work is that per-base accuracy may not be a major roadblock for assembly contiguity. Rather, the chimeras or structural sequencing errors are the major “hot spots” worth putting major effort into. Without cleaning these chimeras, the overlap relations include many falsely generated reads and will lead to a tangled overlap graph. To resolve this issue, we compute multiple sequence alignments (MSA) by aligning each compressed read with all other candidate compressed reads. With MSA we can detect the chimeric reads and the spurious contig identifiers in each read (Fig. 2). Both of these errors are cleaned up. The major side effect of this correction is a slightly increased requirement of the 3GS data coverage so that each compressed read can be confirmed by at least another one. The remaining minor errors (mostly false negatives) in the cleaned compressed reads will be tolerated by the alignment algorithm. In our experiments, we noticed that this algorithm is accurate enough to find high quality overlaps and can be used for constructing draft genomes as assembly backbones. Read Overlap Graph Compared with most hybrid approaches that used long reads to link together the short read contigs, our approach takes the unorthodox way–we use the short read contigs to help link together the long reads. We construct a best overlap graph21 using the above-described alignment algorithm with the compressed reads. In the best overlap graph, each node represents a compressed read. For each node, the best overlapped nodes (one before and the other after) are found based on the overlap score, and the links between these nodes are recorded. The overlap graph is calculated in two rounds (Fig. 1B). In round 1, all the contained nodes (with respect to other nodes) are filtered off. For example, {Contig_a, Contig_b} is removed if {Contig_a, Contig_b, Contig_c} is present. With this strategy, alignments with repeating and contained nodes are avoided. In round 2, all suffix-prefix overlaps among the remaining nodes are detected with the alignment algorithm. Nodes are chained one to another in both directions and in the best overlapped fashion. Graph simplification is applied to remove tiny tips and merge bubbles in the best overlap graph. Truly unresolvable repeats result in branches in the graph21 and will be kept as the assembly breakpoints. Note that constructing the overlap graph with the compressed reads offers us several major benefits. (1) Long read information is sufficiently utilized. (2) The costly long read alignments are accelerated with the easily available NGS contigs. (3) The expensive graph search algorithms (with exponential complexity to the search depth) often used for graph resolving in many existing genome assembly programs are no long needed in our software. Consensus It is noteworthy that only in this final stage that the compressed reads are converted back to the raw nucleotide reads for polishing purpose. Linear unbranched regions of the best overlap graph encode the unambiguously assembled sequences. Uncompressed long reads that lie in these regions are laid out in the best-overlapped fashion and patched one after another (Fig. 1C). NGS contigs are included when there is a gap in the 3GS data. Reads that are related to each backbone are collected based on the contig identifiers. A consensus module is finally called to align these reads to each backbone and calculate the polished assembly (Fig. 1D). To polish the 3GS assembly backbone, we use an efficient consensus module Sparc30. Sparc builds an efficient sparse k-mer graph structure5 using a collection of sequences from the same genomic region. The heaviest path approximates the most likely genome sequence (consensus) and is found in a sparsity-induced reweighted graph. Results We conducted a comprehensive comparison on a small yeast genome (12 Mbp) dataset to provide a scope of the performance of each software program we compared in this study. Since most other programs do not scale linearly with the data scale and require thousands of hours per-run on genomes larger than 100 Mbp, the readers are encouraged to read through their original publications for the performance results of those programs. As a side note, the advent of 3GS long reads has raised the bar to a higher level compared with previous sequencing techniques: existing reference genomes usually contain a large number of structural errors and/or variations that can surpass the number of assembly errors using the long reads. In most cases we select assemblies by other assemblers with more coverage (~100x) as references. If high quality reference genome is available, thorough evaluations of our algorithm show that DBG2OLC can provide high quality results with fewer structural errors and comparable per-base accuracy. This has been recently demonstrated in the case study of D. melanogaster genome by Chakraborty et al.31 who compared our pre-released software with other premier programs for 3GS data. In this paper, we demonstrate results on some other well-studied species and use existing high coverage assemblies as quality checks. On medium to large genomes, DBG2OLC can produce comparably good results with one to two orders of magnitude less time and memory usages than most existing pipelines. A draft assembly (without polishing) of a 3 Gbp H. sapiens can be finished in 3 CPU days with our pipeline, utilizing 30 × 3GS and 50x NGS data. This computational time is roughly comparable to many existing NGS assemblers. The time consumption of each step running different genomes can be found in Table 2. We compared our algorithm results with Celera Assembler (CA, version 8.3rc2), PacBioToCA (in CA8.3rc2)2, ECTools9, MHAP (in CA8.3rc2)7, HGAP (in SMRT Analysis v2.3.0)13 and Falcon assembler (v0.3.0), which are well recognized as the best-performed genome assemblers for 3GS technologies. Data from PacBio SMRT RS-II (the currently leading platform of 3GS technology) was used to perform the comparative experiments (50x Illumina MiSeq reads were additionally used for PacBioToCA and DBG2OLC, the two hybrid methods). The experiments are run on a server with eight Intel Xeon E7-8857 v2 CPUs (each has 12 cores) and 2 TB memory. For all DBG2OLC experiments in this paper we used SparseAssembler (Ye et al.5) to preassemble 50x Illumina short reads into contigs and then to compress the 3GS reads. Similarly, Celera Assembler was used to assemble the same short reads into contigs for ECTools. Unassembled short reads were fed into PacBioToCA according to its specification. At the time of this work, 50x Illumina reads cost less, and also can be obtained more easily, than 1 × 3GS reads. Celera Assembler could be run with uncorrected reads on small datasets, so we run it as a baseline. It is noteworthy that in our current implementation, most of the computation time (~90%) is spent on the consensus step, in which BLASR28 is called to align all raw reads to the assembly backbone. Since the alignments are multi-threaded, the wall time can be reduced depending on the available threads. The consensus step is relatively independent in genome assembly and is open to any future improvements and accelerations. The overall computational time of the whole pipeline scales near linearly to the data size, which is a highly valuable property to large-scale genome assembly problems. Using 10x–20x coverage of PacBio sequence data, we obtained assembly N50s that are significantly (>10x) better than Illumina data alone (Table 1). The datasets, commands, and parameters can be found in the Supplementary Materials. We used QUAST 3.032 in its default setting to evaluate the assembly results; these are reported as the NGA50, per-base identity rates and misassembly errors. In analyzing 3GS assembly results, the NGA50 is a measure of the average length of high quality region before reaching a poor quality region in the assembly. The identity rates were calculated by summarizing the single base mismatches and insertion/deletion mismatches. Relocations, inversions, and translocations are regarded as misassembly errors32. The alignment dot plots can be found in the Supplementary Materials. The nearly perfect diagonal dot plots indicate that DBG2OLC can produce structurally correct assemblies from as low as 10x long read data. For the yeast dataset we picked an assembly from 454 data (NCBI Accession No.: GCA_000292815.1) and another assembly generated using MHAP with high coverage data as references. DBG2OLC takes advantage of different sequencing types and obtains the most contiguous results using 10x–40x data with comparable levels of accuracy (Table 3). Some non-hybrid assemblers are not able to fully assemble the yeast genome with 10x–20x PacBio data. It is also worth mentioning a caveat in many current hybrid error correction approaches. These pipelines use NGS contigs to correct the 3GS reads, which seem to have improved the accuracy of each individual 3GS read. However, the errors in NGS contigs may have corrupted the originally correct 3GS reads and lead to consensus errors in the final assembly. For example, we notice the identity rates of the ECTools assembly are higher when aligned to the 454 reference, contrary to all other pipelines. With high enough coverage (and significantly increased sequencing cost), the 3GS self-correction based assembly methods produce better assembly results. Since our pipeline has a major advantage in low coverage data and efficiency, it is expected to scale well to large genomes where low coverage data and computational time becomes major concerns. We tested DBG2OLC on other medium to large genomes from PacBio sequencers (Table 4). On the A. thaliana genome (120 Mbp), the computations with DBG2OLC finish in one hour, with an additional hour spent constructing the initial NGS contigs. The consensus module takes another 10–20 CPU hours to get the final assembly. The peak memory usage is 6 GB. In comparison, existing pipelines can take over one thousand CPU hours with problems of this scale. On a large 54x human (H. sapiens) dataset, DBG2OLC is able to produce an assembly with high contiguity starting from 10x PacBio data (NG50 433 kbp) and DBG contigs generated from 50x Illumina reads (Table S1 in Supplementary Materials). To produce a better assembly, the longest 30x of the reads in this dataset (mean length 14.5 kbp) are selected (Table S2 in Supplementary Materials). DBG2OLC occupies 70 GB memory to store the 17-mer index, and takes 37 CPU hours to compress and align the 30x longest PacBio reads. The pair-wise alignment takes only 3 hours and takes less than 6 hours on the full 54x dataset. The final consensus takes roughly 2000 CPU hours. In an initial report by PacBio scientists, the overlapping process took 405,000 CPU hours4. Our final assembly quality (N50 = 6 Mbp) is comparable to the state-of-the-art results obtained using orders of magnitude more resources. When evaluating this assembly, QUAST 3.0 can take weeks to finish the full evaluation even on our best workstation. We therefore only align our assembly to the longest 500 Mbp assembly generated by the Pacific Biosciences, and report the NGA50 and identity rate in this portion. DBG2OLC was also tested on an Oxford Nanopore MinION sequencing dataset (Table 4). According to initial studies, this type of data has higher (up to ~40%) error rates3 compared to PacBio SMRT sequencing. However, we find DBG2OLC still successfully assembled the E. coli into one single contig. The polished assembly has an error rate of 0.23%. The dot plot of the alignment of the assembly to the reference can be found in Fig. 13 of the Supplementary Materials. Compared with the state-of-the-art assemblers for 3GS technologies, our proposed method produces assemblies with high contiguity using lower sequencing coverage and memory, and is orders of magnitude faster on large genomes. Its combination of different data types leads to both computation and cost efficiency. These advantages are gained from three general and basic design principles: (i) Compact representation of the long reads leads to efficient alignments. (ii) Base-level errors can be skipped, but structural errors need to be detected and cleaned. (iii) Structurally correct 3GS reads are assembled and polished. DBG2OLC is a specific and simple realization of these principles. Interestingly, this implementation builds a nice connection between the two major assembly frameworks, and even though DBG2OLC is majorly developed for 3GS data, this strategy of compression and converting a de Bruijn graph to an overlap graph is general and can be used for popular NGS data. A preliminary showcase on a purely NGS dataset can be found in the Supplementary Materials. The strategy of compressing long reads and performing the most computationally expensive tasks in the compressed domain strikes a balance between the DBG and OLC frameworks. Summary and Discussion In summary, we have built and validated a new de novo assembly pipeline that significantly reduces the computational and sequencing requirements of 3GS assembly. We demonstrate that the erroneous long reads can be directly assembled and can lead to significantly improved assembly without base-level error correction. This strategy, first publicly demonstrated in our pre-released pipeline in 2014, has paved the road for several subsequent development attempts on efficient utilization of 3GS data and promises even more efficient 3GS assemblers. Another major finding in developing DBG2OLC is that 3GS technologies generate chimeric reads, and the problem seems to be severer with the PacBio platform. These structural errors lead to tangles in the assembly graph and greatly hamper the assembly contiguity. The most straightforward way to clean up the chimeric reads resorts to multiple sequence alignment, as implemented in DBG2OLC, which leads to a slightly increased coverage requirement. This limitation will serve as the starting point for future development. We conjecture that near perfect assemblies can be reached with even lower coverage if the chimeras/structural errors can be removed. Additional Information How to cite this article: Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016). Supplementary Material Supplementary Information We appreciate Prof. Mihai Pop, Prof. James Yorke, Dr. Aleksey Zimin and their groups at the University of Maryland for supports and helpful discussions. We thank Dr. Sergey Koren and Daniel Liang for helping us to improve our manuscript. This research received funding from the following sources: National Science Foundation of China (Grants No. 61175071, 71473243), the Exceptional Scientists Program and Top Oversea Scholars Program of Yunnan Province, and Yunling Industrial Innovation Grant. Author Contributions C.Y. and Z.M. conceived and designed the study; C.Y. and C.M.H. wrote and tested the software; C.Y. and Z.M. wrote the paper; C.M.H. and J.R. participated in performance evaluation and discussion; S.W. helped in running test cases. Figure 1 (A) Map de Bruijn graph contigs to the long reads. The long reads are in red, the de Bruijn graph contigs are in other colors. Each long read is converted into an ordered list of contigs, termed compressed reads. (B) Calculate overlaps between the compressed reads. The alignment is calculated using the anchors. Contained reads are removed and the reads are chained together in the best-overlap fashion. (C) Layout: construct the assembly backbone from the best overlaps. (D) Consensus: align all related reads to the backbone and calculate the most likely sequence as the consensus output. Figure 2 Reads correction by multiple sequence alignment. The left portion shows removing a false positive anchoring contig (brown) that appears only once in the multiple alignment. The right portion shows detection of a chimeric read by aligning it to multiple reads. A breakpoint is detected as all the reads can be aligned with the left portion of the target read are not consistent with all the reads that can be aligned with the right portion of the target read. Table 1 The demonstration of the compression ratio on various datasets. Datasets Sequencing Technology Average Raw Read Length NGS Contig N50 (DBG k-mer size) Average Compressed Read Length Compression Ratio S. cer w303 PacBio 4,734 31,233 (k = 51) 7 1:676 A. thaliana ler-0 PacBio 5,614 2,264 (k = 51) 8 1:702 H. sapiens PacBio 14,519 3,115 (k = 51) 11 1:1320 E.coli K12 Oxford Nanopore 6,597 3,303 (k = 21) 4 1:1649 E.coli K12 Illumina Miseq 150 3,303 (k = 21) 2 1:75 Table 2 Computation time of each procedure. Species Long Read Source Short Read Assembly (CPU hr) Compression (CPU hr) Graph Construction (CPU hr) Consensus (CPU hr) S. cer w303 20x PacBio 0.1 0.03 0.005 2 A. thaliana ler-0 40x PacBio 1 0.6 0.2 18 H. sapians 30x PacBio 25 37 3 1600 E. coli K12 30x Nanopore 0.1 0.02 0.002 2 Table 3 Assembly performance comparison on the S. cerevisiae genome (genome size: 12 M bp). Cov Assembler Time (h) NG50 Contigs NGA50 (454) Identity (454) Misass-emblies (454) NGA50 (PacBio) Identity (PacBio) Misass-emblies (PacBio) Longest Sum 10x MHAP* — — — — — — — — — — —   HGAP* 36.3 — 554 — 99.68% 105 — 99.77% 6 36,942 1,512,911   CA* 15.1 85,728 289 68,030 97.49% 134 81,451 97.46% 13 448,177 12,285,888   PacBioToCA 173.5 19,694 898 19,378 99.88% 112 18,689 99.90% 6 221,736 10,741,663   ECTools 24.5 120,126 169 98,965 99.76% 324 109,640 99.73% 29 525,820 11,785,741   Falcon* 1.3 — 675 — 99.23% 116 — 99.28% 4 36,616 4,137,485   DBG2OLC 1.7 475,890 67 168,612 99.70% 408 355,269 99.81% 46 1,174,277 11,899,604 20x MHAP* 17.1 241,394 87 155,221 99.70% 508 241,260 99.75% 22 490,764 12,123,145   HGAP* 31.1 8,578 1,210 6,908 99.85% 307 7,619 99.90% 20 86,998 8,624,090   CA* 42.4 371,115 165 201,649 98.83% 284 329,930 98.82% 21 680,599 13,052,212   PacBioToCA 400.9 66,974 395 65,171 99.87% 157 65,171 99.91% 7 628,280 11,487,222   ECTools 34.2 176,663 172 109,931 99.77% 565 150,351 99.74% 46 624,112 12,887,799   Falcon* 3.5 110,083 180 93,385 99.38% 345 110,438 99.42% 15 281,041 10,583,868   DBG2OLC 2.6 597,541 47 172,455 99.71% 440 576,287 99.88% 37 1,085,773 12,476,994 40x MHAP* 36.6 614,363 65 243,012 99.91% 598 589,044 99.94% 24 1,090,578 12,356,826   HGAP* 36.2 211,631 93 198,387 99.94% 528 348,754 99.99% 30 796,762 12,387,287   CA* 115.2 365,912 114 160,867 99.66% 358 377,360 99.60% 11 769,189 15,171,228   PacBioToCA 621.7 96,817 371 96,476 99.87% 178 94,480 99.91% 6 742,046 11,700,172   ECTools 55.8 255,956 271 166,945 99.79% 891 214,377 99.76% 64 714,196 14,481,947   Falcon* 11.2 614,509 58 247,745 99.72% 336 555,886 99.74% 10 1,069,920 12,116,235   DBG2OLC 4.2 672,955 28 238,683 99.87% 431 544,679 99.90% 36 1,086,380 12,149,997 80x MHAP* 13.5 751,122 43 248,079 99.91% 526 745,563 99.95% 10 1,537,433 12,350,704   HGAP* 46.5 818,775 33 248,655 99.95% 534 678,552 99.99% 23 1,545,906 12,621,393   CA* 236.0 430,552 75 201,397 99.80% 319 397,774 99.74% 12 984,295 16,571,250   PacBioToCA 274.3 64,967 364 63,651 99.88% 45 62,268 99.91% 10 233,799 11,651,218   ECTools 100.9 247,871 382 154,348 99.79% 1,470 164,839 99.76% 101 881,635 15,925,328   Falcon* 34.7 810,136 99 247,480 99.81% 437 810,134 99.82% 24 1,537,463 12,681,860   DBG2OLC 8.1 678,365 29 204065 99.92% 426 574,476 99.95% 35 1,089,897 12,209,592 *Assemblers that use only 3GS data. Table 4 DBG2OLC assembly performance comparison on various genomes. Genome Size Coverage NG50 Contigs NGA50 Identity Misassemblies Longest Sum A. thaliana 120 Mbp 10x PacBio 405,464 881 258,924 99.77% 704 1,549,329 119 Mb     20x PacBio 2,431,755 306 926,138 99.90% 117 6,015,430 120 Mb     40x PacBio 3,601,597 243 1,605,981 99.93% 131 15,473,059 129 Mb H. sapiens 3.0 Gbp 10x PacBio 432,739 16,689 347,104 99.56% — 3,507,306 2.97 G     20x PacBio 1,886,756 9,757 1,416,766 99.82% — 14,597,500 3.13 Gb     30x longest PacBio 6,085,133 13,095 4,124,714 99.85% — 23,825,526 3.21 Gb E. coli 4.6 Mbp 30x Nanopore 4,680,635 1 1,850,974 99.77% 1 4,680,635 4.7 Mb ==== Refs Venter J. C. et al. The sequence of the human genome . Science 291 , 1304 –1351 , doi: 10.1126/science.1058040 (2001 ).11181995 Koren S. et al. Hybrid error correction and de novo assembly of single-molecule sequencing reads . Nature biotechnology 30 , 693 –700 , doi: 10.1038/nbt.2280 (2012 ). Laver T. et al. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3217210.1038/srep32172ArticleLong noncoding RNA linc00598 regulates CCND2 transcription and modulates the G1 checkpoint Jeong Oh-Seok 1Chae Yun-Cheol 1Jung Hyeonsoo 1Park Soon Cheol 1Cho Sung-Jin 2Kook Hyun 3Seo SangBeom a11 Department of Life Science, College of Natural Sciences, Chung-Ang University, Seoul 156–756, Republic of Korea2 Department of Biology, College of Natural Sciences, Chungbuk National University, Cheongju, Chungbuk 361-763, Republic of Korea3 Medical Research Center for Gene Regulation and Department of Pharmacology, Chonnam National University, Gwangju 501–746, Republic of Koreaa sangbs@cau.ac.kr30 08 2016 2016 6 3217228 04 2016 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Data derived from genomic and transcriptomic analyses have revealed that long noncoding RNAs (lncRNAs) have important roles in the transcriptional regulation of various genes. Recent studies have identified the mechanism underlying this function. To date, a variety of noncoding transcripts have been reported to function in conjunction with epigenetic regulator proteins. In this study, we investigated the function of linc00598, which is transcribed by a genomic sequence on chromosome 13, downstream of FoxO1 and upstream of COG6. Microarray analysis showed that linc00598 regulates the transcription of specific target genes, including those for cell cycle regulators. We discovered that linc00598 regulates CCND2 transcription through modulation of the transcriptional regulatory effect of FoxO1 on the CCND2 promoter. Moreover, we observed that knockdown of linc00598 induced G0/G1 cell cycle arrest and inhibited proliferation. These data indicate that linc00598 plays an important role in cell cycle regulation and proliferation through its ability to regulate the transcription of CCND2. ==== Body Long noncoding RNAs (lncRNAs) are noncoding transcripts longer than ~200 bp, which are expressed in a more cell type-specific fashion than protein-coding genes1. Transcriptomic analyses have shown that lncRNAs are dominantly transcribed in the eukaryotic genome. During the last years, they have drawn considerable attention owing to their participation in various cellular processes, such as cell cycle regulation, and their role in human diseases234. An example of an extensively studied lncRNA is lncRNA-p21, which can suppress the transcription of genes involved in apoptosis and cell cycle through physical association with hnRNP-K, and can also inhibit the translation of β-catenin and Jun B mRNA56. Other lncRNAs, such as HURC and PANDA, also play a role in cell cycle and apoptosis through regulating the expression of cell cycle-related proteins78. However, the functional roles of lncRNAs remain obscure. Even though lncRNAs have been revealed to function as transcriptional and posttranscriptional regulators of protein-coding genes, the mechanisms that underlie these epigenetic roles are not yet fully understood. Many well-known lncRNAs have been reported to regulate transcription of neighboring genes on the same chromosome91011. However, lncRNAs can also act as transcriptional trans-regulatory elements, without affecting the transcriptional regulation of their neighboring genes81213. Some nuclear lncRNAs have been shown to regulate gene expression by guiding specific proteins to target gene loci, or by acting as scaffolds for the recruitment of epigenetic modifying enzymes and the formation of chromatin remodeling complexes121415. Motivated by these studies, we hypothesized that certain lncRNAs can regulate the expression of cell cycle-related genes by interacting with specific transcription factors through yet unidentified mechanisms. The FoxO subfamily of transcription factors consists of functionally related proteins, including the mammalian FoxO1 (FKHR), FoxO3a (FKHRL1), FoxO4 (AFX), and FoxO61617. It has been reported that these transcription factors are involved in regulating a variety of biological processes, including metabolism, cell cycle, cell death, DNA repair, and oxidative stress response, via modulating a variety of target genes17181920. Recent studies have shown that FoxO family members can promote cell cycle arrest at the G1/S boundary both by upregulating cell cycle inhibitors, such as p21 and p27, and by downregulating positive cell cycle regulators, such as CCND1 and CCND2212223. In this study, we investigated the function of linc00598, also known as TTL (Twelve-thirteen Translocation Leukemia gene), which is located on chromosome 13, 74 kb downstream of FoxO1, by microarray expression analysis of linc00598 stable-knockdown cell lines. Analysis revealed that linc00598 knockdown affects the expression of 156 genes, 119 of which are downregulated. One of the downregulated genes was CCND2, which functions as a cell cycle regulator and is negatively regulated by FoxO1, whereas linc00598 was found to be able to interact with FoxO1. Furthermore, knockdown of linc00598 caused cell cycle arrest at the G0/G1 boundary, significantly reducing cell proliferation. Our results reveal a novel mechanism of transcriptional regulation of CCND2 by lncRNA linc00598 and FoxO1. Results Characteristics of long noncoding RNA linc00598 A previous study suggested that local changes in gene expression can be regulated by cis-acting lncRNAs, transcribed from sequences located in the same genomic region24. In our search for lncRNAs acting as cis-transcriptional regulators of FoxO1, we used the UCSC Genome Browser25 to examine the region close to the FoxO1 genomic locus. We detected a long intergenic noncoding RNA, annotated as linc00598, located between FoxO1 and COG6 (Fig. 1a). To identify the coding potential of each variant of linc00598, we applied the coding potential assessment tool (CPAT) software26. All linc00598 variants were found to produce noncoding transcripts similar to other lncRNAs, such as MALAT-1 and Xist (Fig. 1b). We performed qRT-PCR to determine the expression levels of linc00598 in nine human cell lines. The colorectal cancer cell line HCT116, which displayed the lowest expression levels among the nine, was used as the calibrator, i.e., all other cell lines were compared to it to calculate the relative expression values that are depicted in Fig. 1c. The cell line with the highest levels of expression was HepG2. HEK293t cells also showed very high expression levels of linc00598 and were chosen for further study. To determine the isoforms of linc00598 expressed in the HEK293t cell line, we performed northern blot using random probes specific to the 5′ region of the target transcripts. The results showed that TTL-B2, the longest isoform of linc00598, is the dominant, endogenously expressed isoform in HEK293t cells (Fig. 1d and Supplementary Fig. S1a,b). A recent study supported that several nuclear localized lncRNAs play a role in transcription regulation24. To determine the localization of linc00598, we performed nuclear/cytoplasmic RNA fractionation in HEK293t cells (Fig. 1e). We observed that linc00598 was mainly located in the nuclear compartment, similarly to Xist, a well-known nuclear lncRNA27. In order to confirm this result, we performed RNA fluorescence in situ hybridization (RNA-FISH) using an antisense linc00598 RNA probe. As seen in Fig. 1f, linc00598 in the HEK293t cells is exclusively retained in the nucleus. We conclude that linc00598 is expressed in human cells and is localized in the nucleus. linc00598 can regulate the transcription of genes related with cell cycle regulation To determine the function of linc00598 as a transcriptional regulator, we designed shRNAs targeting linc00598 and produced stable linc00598 knockdown HEK293t cells (Supplementary Fig. S2a). We performed microarray analysis using control shRNA and two shlinc00598 stable HEK293t cell lines (two replicates for each cell line) in order to identify linc00598 target genes. As our aim was to filter out genes that did not display significant changes in expression, we chose only those genes whose expression values in the knockdown cells were higher or lower by a factor of at least 1.4 than that in the control cells. A total of 156 genes satisfied these criteria, of which 119 were downregulated and 37 upregulated (Fig. 2a). The fact that the vast majority (76%) of the differentially expressed genes were downregulated indicates that linc00598 is mostly involved in target gene activation in HEK293t cells. However, the expression levels of FoxO1 and COG6, which are located proximally to the linc00598 genomic locus, did not exhibit changes in the linc00598 knockdown cells. These results were confirmed by qRT-PCR (Supplementary Fig. S2b). Next, we performed functional annotation of the results by mapping these lists into the Gene Ontology (GO)28 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways29 databases, by utilizing the DAVID (Database for Annotation, Visualization and Integrated Discovery) software3031. Results showed that a significant number of linc00598-regulated genes are involved in major biological processes, such as the regulation of cell cycle and regulation of cyclin-dependent protein kinase activity, as well as the modulation of responses to organic substances, drugs, and endogenous stimuli (Fig. 2b). To confirm the changes in expression that were determined through the microarray analysis, we performed qRT-PCR for five linc00598-regulated genes, including those that exerted biological functions related to the cell cycle, in samples from two independent shlinc00598 stable HEK293t cell lines. All five genes displayed changes in expression consistent with the microarray data (Fig. 2c). The changes were further validated using ectopic transfection of the linc00598 transcripts TTL-B2 and TTL-T in HEK293t cells (Fig. 2d and Supplementary Fig. S2c, respectively). To identify the part of the RNA sequence responsible for transcriptional regulation, we produced two different linc00598 DNA constructs, containing either the 5′ (663 bp) or the 3′ region (3309 bp) of TTL-B2. Notably, overexpression of either DNA constructs did not influence the expression of the linc00598 target genes (Fig. 2e), indicating that both parts of the RNA sequence are necessary for target gene regulation. Therefore, one of the linc00598 isoforms, TTL-B2, appears to function as a transcriptional regulator of various target genes, in HEK293t cells. linc00598 regulates transcription of CCND2 through modulating accessibility of FoxO1 to the CCND2 promoter Among the differentially expressed genes identified, CCND2 displayed the highest fold change (~2.17). Therefore, we tried to determine the mechanism of transcriptional regulation of CCND2 by linc00598. It has been shown that CCND2 is negatively regulated by FoxO123, whereas our array data indicate that linc00598 functions as a transcriptional activator for a variety of genes including CCND2. To test whether the protein levels of CCND2 are also regulated by FoxO1 and linc00598, we compared CCND2 levels in control shRNA, shFoxO1, and shlinc00598 cells. As expected, expression of CCND2 was negatively regulated by FoxO1 and positively regulated by linc00598 (Supplementary Fig. S3a,b). We next analyzed the interaction between linc00598 and transcriptional regulators related to CCND2 expression by using RPIseq, a sequence-based predictive method with an accuracy ranging from 57–99% when faced with independent datasets of RNA-protein interactions32. We found that various transcriptional regulators, including FoxO1, p300, CBP, SMYD2, JMJD1C, and LSD1, had scores higher than 0.5, which indicates high interaction probabilities between TTL-B2 and each of these proteins (Fig. 3a), and also suggests that these proteins have a high probability of participating in the linc00598 transcriptional regulatory mechanism. To test whether linc00598 indeed interacts with the aforementioned proteins, we performed RNA immunoprecipitation (RIP) assays using the indicated antibodies, followed by qRT-PCR. As seen in Fig. 3b, the results revealed that linc00598 was associated with the FoxO1 protein, which, as mentioned above, is a negative transcriptional regulator of CCND2. Accumulation evidence indicates that lncRNAs can change the transcriptional activity of specific target genes via interaction with proteins; for example, the ncRNA Ctbp1 has been shown to increase the transcriptional activity of androgen receptors in prostate cancer cells33. To further investigate the mechanism of transcriptional regulation of CCND2 by linc00598 and FoxO1, we performed chromatin immunoprecipitation (ChIP) using anti-FoxO1 antibody in linc00598 stable-knockdown cell lines, followed by qPCR assays. We observed that FoxO1 occupancy on the CCND2 promoter increased when linc00598 was knocked down, suggesting that linc00598 is required for inhibition of FoxO1 accessibility to the promoter of CCND2 (Fig. 3c). Alternatively, the reduced presence of FoxO1 on the CCND2 promoter could be a result of a reduction in total FoxO1 levels. To examine this possibility, we checked the expression of FoxO1 in shlinc00598 stable cells. The results showed that FoxO1 expression was not changed by depletion or overexpression of linc00598 (Supplementary Fig. S3c). Moreover, as it has been reported that the transcriptional activity of FoxO1 is regulated by its localization34, we performed nuclear/cytoplasmic fractionation to determine whether the overexpression of linc00598 changes the localization of FoxO1. As seen in Supplementary Fig. S3d, no such changes were observed. To provide further evidence that the regulation of CCND2 expression by linc00598 is dependent on the modulation of the accessibility of FoxO1 to CCND2 promoter, a reporter assay was performed using control and shlinc00598 stable HEK293t cells that were transfected with either wild type CCND2 promoter, or a mutant form in which the FoxO1 consensus binding sequences had been altered. Consistent with our qRT-PCR and microarray data, CCND2 promoter activity was decreased in the shlinc00598 stable cell line. Furthermore, CCND2 promoter activity was rescued when we performed the luciferase assay using the shlinc00598 stable cell line that was transfected with the mutant promoter construct, suggesting that linc00598 regulates CCND2 by modulating FoxO1 binding on its promoter (Fig. 3d). To further demonstrate that linc00598 regulates the transcription of CCND2 by modulating the accessibility of FoxO1 to the promoter of CCND2, we performed qRT-PCR assays using control and shFoxO1 stable HEK293t cells transfected with TTL-B2. As expected, overexpression of TTL-B2 in the control cells caused upregulation of CCND2 expression. On the contrary, there was no significant change in CCND2 expression in the shFoxO1 stable cell line (Fig. 3e), which is consistent with the results shown in Fig. 3d, which also suggest the existence of a FoxO1-mediated mechanism through which linc00598 regulates CCND2. Taken together, these findings strongly suggest that linc00598 regulates expression of CCND2 through reducing the binding affinity of FoxO1 to the CCND2 promoter. Knockdown of linc00598 induces cell cycle arrest and inhibits cell proliferation We investigated the physiological consequences of linc00598 knockdown in HEK293t cells. Since linc00598 can regulate CCND2, which is a positive cell cycle regulator, we performed MTT assays to measure proliferation of control and shlinc00598 stable HEK293t cell lines. As shown in Fig. 4a, cell proliferation was reduced when linc00598 was knocked down. Consistent results were obtained from cell counting assays, in which depletion of linc00598 led to a decreased number of cells (Fig. 4b). Since linc00598 regulates expression of CCND2, we next examined whether linc00598 knockdown affected the cell cycle in HEK293t cells. To this end, we performed propidium iodide (PI) staining followed by FACS analysis. As expected, the two linc00598 knockdown cell lines exhibited an increase in G1 phase (about 8% and 13%, respectively) and a slight decrease in both S and G2-M phase (Fig. 4c). To determine whether the cell cycle arrest in the two shlinc00598 stable cell lines was caused by the depletion of CCND2, we performed another FACS analysis using the shlinc00598#2 stable cell line transfected with a CCND2 overexpression vector. Overexpression of CCND2 rescued the G1 arrest (G1 is reduced from 45.98% to 39.95%), suggesting that the cell cycle arrest caused by depletion of linc00598 is caused by a decrease of CCND2 levels (Fig. 4d). These results are consistent with a previous study according to which, CCND2 contributes to the G1-S cell cycle transition35. It has been reported that the CCND2/CDK4/p27 complex is required for nuclear translocation of CCND236. Since the expression levels of CDK4 and p27 were not influenced in shlinc00598 stable HEK293t cell lines (Supplementary Fig. S4a,b), we examined the localization of CCND2 and CDK4 by performing nuclear/cytoplasmic fractionation. The amounts of CCND2 in both nucleus and cytosol were reduced in the two shlinc00598 stable HEK293t cell lines, whereas the mainly cytosolic localization of CDK4 was not affected by shlinc00598 knockdown (Supplementary Fig. S4c). These results suggest that linc00598 knockdown has no effect on the expression and localization of other complex components. Taken together, our results clearly indicate that linc00598 affects cell proliferation through modulation of the G0-G1 checkpoint, via transcriptional regulation of CCND2. Discussion Recent studies have revealed that various lncRNAs are transcribed in large amounts in the eukaryotic genome and these noncoding transcripts are involved in the regulation of gene expression and various biological processes including the cell cycle34. An example is NcRNACCND1, also called pncRNA (promoter-associated non-coding RNA), that is transcribed from the 5′ regulatory region of CCND1 and negatively regulates CCND1 by recruiting the RNA binding protein, TLS (translocated in liposarcoma)3738. Gadd7 is another lncRNA involved in cell cycle control, specifically regulating Cdk6 expression in a post-translational manner. Gadd7 is transcriptionally induced by DNA damage caused by UV radiation and directly binds to TDP-43 (TAR DNA binding protein). This binding inhibits the interaction between TDP-43 and Cdk6 mRNA, resulting in the degradation of Cdk6 mRNA39. linc00598, also known as the TTL, is located at the locus 13q14.11, downstream of the FoxO1 genomic locus. It has three isoforms, TTL-T, TTL-B1, and TTL-B2. Notably, northern blot analysis showed that TTL-B2 is the dominant expressed isoform in HEK293t cells. Results of RNA-FISH and qRT-PCR from fractionated RNA revealed a nuclear localization of linc00598 and suggested that linc00598 may probably serve as a cis- or trans-transcriptional regulator24. It has been reported that CCAT1-L (colorectal cancer specific lncRNA) localizes to its site of transcription and functions as a cis-transcriptional regulator of MYC, promoting long-range chromatin looping and interacting with the transcriptional regulator protein, CTCF15. Another example is Paupar, which interacts with chromatin at over 2,800 sites located on multiple chromosomes, and regulates target gene expression in cis and in trans. Our array data demonstrate that linc00598 can regulate the expression of various target genes including cell cycle regulator CCND2, suggesting that the expression of linc00598 could have an effect on cell cycle and proliferation. In order to determine the mechanism through which CCND2 is regulated by linc00598, RIP and ChIP assays were performed. Results showed that linc00598 can interact with FoxO1 and depletion of linc00598 influence in accessibility of FoxO1 to the CCND2 promoter. Furthermore, unlike the wild type, mutation of FoxO1 binding sites of the CCND2 promoter rescued promoter’s activity in the shlinc00598 stable cell line. Consistently, ectopic expression of linc00598 has no significant effect on the expression of CCND2 in FoxO1-knockdown cells. These results indicate that linc00598 modulates the accessibility of FoxO1 to the CCND2 promoter. Finally, we demonstrated that linc00598 can regulate cell cycle and cell proliferation by regulating the expression of CCND2, as linc00598 knockdown reduces cell proliferation by downregulating CCND2. Furthermore, a heatmap was generated from the hierarchical clustering of data from a systematic qRT-PCR analysis of a selected group of genes, including FoxO target genes (I), linc00598 target genes (II), and Negative genes (III), in control shRNA, shlinc00598, siFoxO1, and shlinc00598/siFoxO1 cell lines. The heatmap revealed additional putative target genes under the control of the linc00598-FoxO1 regulatory mechanism, in ways similar to CCND2 (Supplementary Fig. S5). Candidate target genes could be upregulated by linc00598, such as CTGF and DDIT4, or downregulated by linc00598, such as FASLG. These results indicate that part of the putative target genes of FoxO1 are regulated by linc00598, and suggest that the relationship between FoxO1 and linc00598 needs to be examined further. In this study, we provide for the first time information on the mechanism of transcriptional regulation of CCND2 by linc00598. Specifically, we demonstrate that linc00598 regulates the expression of CCND2 through inhibiting the recruitment of FoxO1 to the CCND2 promoter (Fig. 4e). The effects of this lncRNA on cell cycle regulation and cell proliferation indicate that linc00598 has the potential to promote transformation in human cells. The exact mechanism through which linc00598 affects the ability of FoxO1 to bind on the CCND2 promoter is yet to be elucidated. Moreover, further studies are needed to determine the physiological significance of linc00598. Taken together, the results of our study strongly indicate that linc00598 regulates CCND2 in trans through modulation of the accessibility of FoxO1 to theCCND2 promoter. Methods Plasmid Constructs To construct mammalian expression vectors, we employed modified pcDNA6-HA-myc-his plasmids (Invitrogen) to create expression vectors for TTL-T, TTL-B2 (whole), the 5′ fragment (663 bp) of TTL-B2, and the 3′ fragment (3309 bp) of TTL-B2. The pOTB7-CCND2 (hMU010514) expression vector was obtained from the Korean Unigene Information (KUGI) collection. The CCND2 coding sequence was subcloned into the mammalian expression vector p3XFLAG-CMV10 (Sigma). The CCND2 promoter region (−463 to 0) was amplified from human genomic DNA and inserted into the KpnI/HindIII sites of the pGL3-basic vector (Promega). The three FoxO1 binding elements (TATTT) of the cloned promoter were replaced with mutated elements (TGCCT or CGCCG) by site-directed mutagenesis. Short hairpin RNAs (shRNAs) against human linc00598 and FoxO1 were designed using the siRNA sequence designer software (Clontech). The double-stranded oligonucleotides used for shRNA plasmid construction were produced using primers from the 5′ to the 3′ end (Supplementary Table S1). The oligonucleotide for FoxO1 siRNA was introduced into the pBabe-dual vector using primers from the 5′ to the 3′ end (Supplementary Table S1). These oligonucleotides were inserted into the AgeI/EcoRI site of the pLKO.1 TRC vector. Antibodies Antibodies against β-actin (sc-47778), CBP (sc-369), CDK4 (sc-260), FKHR (sc-374427), H3 (sc-8654), JMJD1C (sc-83420), LSD1 (sc-271720), p300 (sc-585), SMYD2 (sc-130879; Santa Cruz Biotechnology), Normal Mouse IgG (12-371; Millipore), β-tubulin (T4026; Sigma), and CCND2 (#3741; Cell Signaling) were employed. Cell Culture HeLa and HEK293t cells were grown in Dulbecco’s modified Eagle’s medium (DMEM), whereas H1299, HCT116, HepG2, HL60, K562, MCF7, and THP1 cells were grown in RPMI-1640 containing 10% heat inactivated fetal bovine serum and 0.05% penicillin-streptomycin, at 37 °C in a 5% CO2 atmosphere. HEK293t cells were seeded in a 60 mm plate at a density of 4.0 × 105 cells per well and transfected with the indicated constructs using polyethylenimine (Sigma). After 48 h of incubation, cells were harvested and used for each of the experiments. Reverse Transcription and Real-time PCR Total RNA was isolated from HEK293t cells, using RNAiso Plus (TaKaRa). The synthesized cDNA was quantified and then used for analysis of mRNA expression. The PCR primers used are presented in Supplementary Table S1. Dissociation curves were created after each PCR run to ensure the amplification of a single product of the appropriate length. The mean threshold cycle (Ct) and standard error values were calculated from individual Ct values obtained from triplicate reactions. The normalized mean Ct values (ΔCt) were calculated by subtracting the mean Ct of β-actin. ΔΔCT was calculated as the difference between the control ΔCt and the values obtained for each sample. The n-fold change in gene expression, relative to an untreated control, was calculated as 2−ΔΔCT. Chromatin immunoprecipitation analysis ChIP analysis was performed as described previously40. Briefly, control and shlinc00598 stable HEK293t cells were harvested and cross-linked with the addition of 1% formaldehyde in the medium for 10 min at 37 °C, followed by the addition of 125 mM glycine for 5 min at room temperature. The cells were then lysed in SDS lysis buffer, and the samples were sonicated and immunoprecipitated using the indicated antibodies. The immunoprecipitates were eluted and reverse cross-linked. The DNA fragments were then purified and PCR-amplified for quantification using the respective primer pairs (Supplementary Table S1). Dissociation curves were generated at the end of each PCR run to confirm the amplification of a single product of the expected length. The mean threshold cycle (Ct) and standard error values were calculated from individual Ct values, obtained from duplicate reactions. The normalized mean Ct values (ΔCt) were calculated by subtracting the mean Ct of the input from that of the anti-CCND2 immunoprecipitated sample. MTT Assay Control and shlinc00598 stable HEK293t cells were seeded in 48-well plates (8 × 104 cells per well). After 24, 48, and 72 h, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) was added to the cells at a final concentration of 0.5 mg/mL; after the addition, cells were further incubated for 4 h at 37 °C. The medium was then removed by aspiration, and DMSO was added (200 μl/well). OD values were determined on an ELISA reader (Biochrom) at a wavelength of 570 nm. The value of a blank sample, containing DMSO alone, was measured and subtracted from all values to correct for background in measurements. FACS Analysis To assess the cell-cycle profile, control and shlinc00598 stable HEK293t cells were prepared. Control and shlinc00598 stable HEK293t cells transfected with the indicated plasmids were also seeded and harvested 48 h later. Cells were trypsinized, rinsed and fixed in ice-cold 70% ethanol for 30 min. Immediately before flow cytometric analysis, the cells were treated with RNase A (100 μg/mL) and stained with propidium iodide (PI, Sigma) for 30 min, then subjected to fluorescence-activated cell sorting (FACS) analysis using a BD Accuri C6 cytometer (BD Biosciences). Data were analyzed using BD Accuri C6 software (BD Biosciences). RNA Immunoprecipitation Analysis We followed a modified version of the RIP protocol41. HEK293t cells were washed and then lysed with polysome lysis buffer (100 mM KCl, 5 mM MgCl2, 10 mM Hepes pH 7.0, 0.5% NP-40, 1 mM DDT, and 100 units/mL RNase out (Invitrogen), supplemented with a protease inhibitor cocktail. Cell extracts were then incubated with the indicated antibodies at 4 °C overnight. The next day, protein A/G-agarose beads (GenDEPOT) were added, and the samples were incubated at 4 °C for 4 h. Beads were then collected, washed five times with NT2 buffer, containing 50 mM Tris-HCl (pH 7.4), 150 mM NaCl, 1 mM MgCl2, and 0.05% NP-40). RNAiso Plus was added to the beads to extract protein-interacting RNA, which was then treated with RNase-free DNase I (TaKaRa) and measured by qRT-PCR assays. Microarray Analysis For linc00598 target gene profiling, we used the Illumina HumanHT-12 v4 Expression BeadChip (Illumina), which includes a bead pool of more than 47,231 unique bead types corresponding to 28,688 RefSeq annotated transcripts. Total RNA (0.55 μg) isolated from control and shlinc00598 stable HEK293t lines was reverse transcribed and amplified according to the protocols described in the Illumina TotalPrep RNA amplification kit manual (Ambion). In vitro transcription was then carried out to generate cRNA (0.75 μg), which was hybridized onto each array (two replicates for each condition) and then labeled with Amersham fluorolink streptavidin-Cy3 (GE Healthcare Bio-Sciences). The array was then scanned using the Illumina Bead Array Reader Confocal Scanner. Array data export processing and analysis were performed using Illumina GenomeStudio v2011.1 (Gene Expression Module v1.9.0). This data set was submitted to the Gene Expression Omnibus under submission number GSE80514. Array probes were transformed by logarithm and normalized by quantile method. Gene enrichment and functional annotation analysis for the significant probe list were performed using the DAVID software (http://david.abcc.ncifcrf.gov/home.jsp). Analysis of nuclear and cytoplasmic linc00598 abundance Nuclear and cytoplasmic RNA were isolated from untransfected cells for analysis of endogenous linc00598 expression and localization. Cells growing in 100 mm dishes were rinsed twice with ice-cold 1 × PBS, harvested in 1 mL ice-cold 1 × PBS by scraping, and centrifuged at 1,000 rpm for 10 min. Cell pellets were resuspended by gentle pipetting in 200 μL lysis buffer A containing 10 mM Tris (pH 8.0), 140 mM NaCl, 1.5 mM MgCl2, and 0.5% NP-40, then incubated on ice for 5 min, and centrifuged at 1,000 × g for 3 min at 4 °C. The supernatant (cytoplasmic fraction), was added to 1 mL RNAiso Plus for RNA isolation and purification. Nuclear pellets underwent two additional rinses with lysis buffer A and a final washing step with lysis buffer A containing 1% Tween-20 and 0.5% deoxycholic acid. Purified nuclear pellets were then resuspended in 1 mL RNAiso Plus. Both RNA samples were treated with RNase-free DNase I, converted to cDNA, and quantified by qRT-PCR assays. RNA fluorescence in situ hybridization HEK293t cells on PLL-coated cover glass were fixed in 1 × PBS with 4% paraformaldehyde for 15 min, then treated with 0.2 N HCl for 10 min, followed by incubation with 20 μg/mL proteinase K (Biofact) for 5 min at 37 °C. After undergoing acetylation in a solution containing 0.1 M triethanolamine (pH 8.0) and 0.1% acetic anhydride, the cells were then rinsed three times with 1 × PBS. Post fixation was performed using 4% paraformaldehyde for 20 min and rinsed three times with PBT (1 × PBS plus 0.1% Tween20). Prehybridization was carried out at 64 °C overnight in hybridization buffer (50% deionized formamide, 5 × SSC, 1 × Denhardt’s solution, 0.1% CHAPS, 100 μg/mL heparin, 0.1% Tween 20, and 100 μg/mL tRNA). The prehybridization buffer was replaced with fresh hybridization buffer containing 2 ng/mL of the linc00598 probe and incubated at 64 °C overnight. After washing, samples were incubated at room temperature for 2 h in PBT containing 1% blocking reagent (Roche), then incubated at 4 °C for another 16 h with 1:2,000 Anti-DIG/POD antibody (Roche). After incubation, the color reaction was carried out using a tyramide kit (Tyramide Signal Amplification (TSA) Plus Cyanine 3/Fluorescein System, Perkin Elmer Lifer Sciences) at a 1/50 dilution, and leaving the samples in the dark for 10 min. After washing, samples were stained with 4′,6-diamidino-2-phenylindole (DAPI, Sigma) to visualize cell nuclei. Stained samples were rinsed in PBT overnight, then mounted in Fluoromount-G (SouthernBiotech) and examined by confocal laser scanning microscopy in a LSM700 microscope (Carl Zeiss Microscopy). Northern blot analysis Total RNA samples prepared as described above were denatured at 65 °C for 10 min in a double volume of formamide-formaldehyde loading buffer, and then separated by electrophoresis in a 1.0% GTG agarose gel containing 1.85% formaldehyde. The gel was transferred to Hybond-XL nylon membranes (GE Healthcare) using 20 × standard saline citrate. The random hexamer probes used for linc00598 detection were synthesized using a Random Primed DNA Labeling Kit (Roche), whereas the PCR products containing the 5′ region of target transcripts were used as a template. The sequences of the primers of the PCR reaction, linc00598-probe-F and linc00598-probe-R, are shown in Supplementary Table S1. Luciferase assay Luciferase assays were conducted using a CCND2 promoter reporter system, containing either wild type or a mutant form of the promoter. Control and shlinc00598 stable HEK293t cells were transfected with the indicated DNA constructs, using PEI. Cells were harvested after 48 h and assayed for luciferase activity, using a luciferase assay system (Promega). Each value is the mean of five replicates from a single assay. All experiments were performed at least three times. Statistical analysis The results are expressed as means ± S.D of three or more independent experiments. Differences between groups were evaluated via Student’s t-tests, performed with Microsoft Office Excel. A P < 0.05 was considered statistically significant. The heatmap analysis was performed using the MeV v4.9 genomic analysis software (open source). Additional Information How to cite this article: Jeong, O.-S. et al. Long noncoding RNA linc00598 regulates CCND2 transcription and modulates the G1 checkpoint. Sci. Rep. 6, 32172; doi: 10.1038/srep32172 (2016). Supplementary Material Supplementary Information We would like to thank Daeyoung Kim and Jaesung Choi of the Chung-Ang University for their technical supports. This work was supported by the Ministry of Education, Science and Technology (NRF-2013R1A2A2A01068788 and NRF-2016R1A4A1008035) the Basic Science Research program through the National Research Foundation of Korea (NRF), Republic of Korea. This research was also supported by the Chung-Ang University Research Scholarship Grants in 2016. Author Contributions O.-S.J. designed the experiments and analyzed the results. O.-S.J., Y.-C.C., H.J. and S.-J.C. performed experiments. S.B.S. and O.-S.J. wrote the manuscript. S.C.P. and H.K. supervised the design of the experiments. Figure 1 Expression of linc00598, a nuclear localized RNA, in human cells. (a) linc00598, which is transcribed by a sequence located between the FoxO1 genomic locus and the COG6 genomic locus, has three isoforms, TTL-T, TTL-B1, and TTL-B2. (b) Bioinformatic analysis of the coding potential of the three linc00598 transcript variants. Results were obtained using the CPAT software. (c) The expression of linc00598 was quantified by qRT-PCR in various human cell lines and normalized to β-actin. The HCT116 cell line was used as a calibrator, and its expression levels were arbitrarily set to “1.” (d) In order to determine the endogenous expression of linc00598 isoforms, total RNA from HEK293t cells was analyzed by northern blot using random probes specific to the 5′ region of target transcripts. (e) Total RNA from HEK293t cells was separated into cytoplasmic and nuclear fractions and used to evaluate the expression levels of linc00598 by qRT-PCR. Xist and β-actin RNA were quantified and used as references to calculate relative levels of each transcript and as controls to evaluate subcellular fractionation. The ratios of cytoplasmic to total, and nuclear to total RNA levels are shown. The results are expressed as mean ± S.D. (n = 3). (f) RNA-FISH was performed to detect linc00598 (red) expression in HEK293t cells with Dig-labeled probes specific to the 5′ region of target transcripts. Images shown were acquired by laser scanning microscopy. Nuclei are colored blue due to DAPI. The white scale bar in all images represents 10 μm. Figure 2 linc00598 functions to regulate genes involved in cell cycle regulation. (a) Identification of linc00598 target genes by hierarchical clustering; changes in the expression of a large number of genes in linc00598 knockdown stable HEK293t cells are displayed. Upregulated and downregulated (by a factor of at least 1.4) gene clusters are represented by red and green, respectively. (b) Biological and molecular functional classification of linc00598 target genes, using the annotation tool DAVID. **P < 0.01 and ***P < 0.001. (c–e) The mRNA levels of indicated genes in linc00598 knockdown stable HEK293t cells and HEK293t cells transfected with indicated DNA constructs were analyzed by qRT-PCR and normalized to β-actin. The results are shown as means ± S.D. (n = 3). *P < 0.05 and **P < 0.01. Figure 3 linc00598 regulates the transcriptional activity of FoxO1 to the CCND2 promoter. (a) Scores of the interaction probability between TTL-B2 and various proteins as predicted by RPIseq. (b) linc00598 interacts with FoxO1 in HEK293t cells. Total cell extracts from HEK293t cells were prepared and immunoprecipitated using indicated antibodies. Associated RNAs were purified and linc00598 levels were measured using qRT-PCR. Results are expressed as fold enrichment relative to an isotype IgG control antibody. Values are means ± S.D. (n = 6). *P < 0.05. (c) ChIP analyses of the CCND2 promoter region and a distal region in linc00598 knockdown stable HEK293t cells were conducted using anti-IgG and anti-FoxO1 antibodies, and examined via qRT-PCR. The results are shown as mean ± S.D. (n = 3). (d) Control and shlinc00598#2 stable HEK293t cell lines were transfected with vectors containing the wild-type (pGL3-CCND2-WT) or the mutant (pGL3-CCND2-MT) CCND2 promoter. Following transfection, cell extracts were assayed for luciferase activity. Luciferase activity was normalized to that of β-galactosidase. The results are expressed as means ± S.D. (n = 3). *P < 0.05 and ***P < 0.001. (e) FoxO1 knockdown stable HEK293t cells were transiently transfected with pcDNA-TTL-B2, analyzed by qRT-PCR and normalized to β-actin. The results are expressed as means ± S.D. (n = 3). *P < 0.05, **P < 0.01 and ***P < 0.001. Figure 4 linc00598 regulates cell proliferation via modulating cell cycle. (a) Cell proliferation was assessed through MTT assay in which linc00598 knockdown stable HEK293t cells were used. Results are expressed as means ± S.D. (n = 3). *P < 0.05, **P < 0.01, and ***P < 0.001. (b) Cell counting assays were performed using linc00598 knockdown stable HEK293t cells. The results are shown as means ± S.D. (n = 3). **P < 0.01 and ***P < 0.001. (c) Cell cycle phases of control and shlinc00598 stable HEK293t cell lines were analyzed by PI staining. Cells were fixed, stained with PI for 30 min, and analyzed by FACS. (d) Control and shlinc00598#2 stable cell lines were transfected with the indicated plasmids. Cell cycle phases of each cell line were assessed by PI staining. Cells were fixed, stained with PI for 30 min, and analyzed by FACS. (e) A model for regulation of CCND2 transcription by linc00598 through modulating accessibility of FoxO1 to the CCND2 promoter. ==== Refs Cabili M. N. et al. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3218410.1038/srep32184Article3D-engineering of Cellularized Conduits for Peripheral Nerve Regeneration Hu Yu 12*Wu Yao 2*Gou Zhiyuan 1*Tao Jie 1Zhang Jiumeng 1Liu Qianqi 1Kang Tianyi 1Jiang Shu 2Huang Siqing 2He Jiankang 3Chen Shaochen 4Du Yanan 5Gou Maling a11 State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan province, China2 Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan province, China3 State key laboratory for manufacturing systems engineering, Xi’an Jiaotong University, Xi’an, 710049,China4 Department of NanoEngineering, University of California, San Diego, La Jolla, California 92093, USA5 Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084. Chinaa goumaling@scu.edu.cn* These authors contributed equally to this work. 30 08 2016 2016 6 3218426 04 2016 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Tissue engineered conduits have great promise for bridging peripheral nerve defects by providing physical guiding and biological cues. A flexible method for integrating support cells into a conduit with desired architectures is wanted. Here, a 3D-printing technology is adopted to prepare a bio-conduit with designer structures for peripheral nerve regeneration. This bio-conduit is consisted of a cryopolymerized gelatin methacryloyl (cryoGelMA) gel cellularized with adipose-derived stem cells (ASCs). By modeling using 3D-printed “lock and key” moulds, the cryoGelMA gel is structured into conduits with different geometries, such as the designed multichannel or bifurcating and the personalized structures. The cryoGelMA conduit is degradable and could be completely degraded in 2-4 months in vivo. The cryoGelMA scaffold supports the attachment, proliferation and survival of the seeded ASCs, and up-regulates the expression of their neurotrophic factors mRNA in vitro. After implanted in a rat model, the bio-conduit is capable of supporting the re-innervation across a 10 mm sciatic nerve gap, with results close to that of the autografts in terms of functional and histological assessments. The study describes an indirect 3D-printing technology for fabricating cellularized designer conduits for peripheral nerve regeneration, and could lead to the development of future nerve bio-conduits for clinical use. ==== Body Peripheral nerve injury most commonly arises from trauma, and less frequently, secondary tumor resection or congenital defects1. Approximately 2–5% of trauma patients experience a peripheral nerve injury and about 100,000 peripheral nerve surgeries are performed each year in the North America2. In cases of nerve defects shorter than 5 mm, a direct tension-free neurorrhaphy is the preferred nerve repair procedure3. For larger gaps, the current “gold standard” is autologous nerve graft. However, nerve autograft presents a number of disadvantages, including the requirement of a second surgery, donor site morbidity, limited graft availability, size and geometrical mismatch, and the possibility of painful neuroma formation4. These limitations have motivated the investigation and development of alternative therapeutic strategies to autograft. Thus far, many nerve repair strategies, such as nerve guidance scaffolds, physiochemical and biological cues, have been applied to guide and promote nerve regeneration145. Nerve guidance conduits (NGCs) have been widely used for bridging nerve defects through supporting and directing the sprouting axons, allowing the diffusion/influx of oxygen and nutrients, and preventing the infiltration of inflammatory cells and myofibroblasts6. Biomaterials from natural and synthetic polymers have been proposed to construct NGCs for peripheral nerve regeneration6. Gelatin, which is essentially denatured collagen, has been commonly used in food, cosmetic industries as well as medicine, such as hemostatic agent and blood volume expander789. Gelatin scaffolds have also been used extensively for tissue engineering1011. For peripheral nerve regeneration, several studies have demonstrated that gelatin conduits are of less cytotoxicity and higher biodegradability, and can promote improved nerve regeneration8912. Gelatin methacryloyl (GelMA) is generated from the modification of gelatin with pendant methacryloyl substitution groups, which confers gelatin the properties of photocrosslinking and radical polymerization10. GelMA has suitable biological properties and tunable physical characteristics, and thus has been widely used for biomedical applications, such as engineering of bone, cartilage, and vascular tissues1013. The gelatin derivative is an inherently cell-adhesive material comprised of modified natural extracellular matrix (ECM) components that can provide functional cues to the resident cells within the scaffolds and thus can aid in nerve regeneration1415. Moreover, cell delivery can be facilitated by priming the support cells in vitro before transplanted into the injury site, which reduces the rate of cell loss and leakage to surrounding tissues1115. Peripheral nerve injury may involve one or more nerves with different lengths and injury degrees (ranging from neurapraxia to neurotmesis)216. In addition, the injured nervesmay be varied in geometries17. The inherent variance in patient anatomies and injury profiles have motivated the development of personalized treatment for peripheral nerve injury18. However, challenges remain for conventional manufacturing methodologies to fabricate nerve conduits with complex or custom geometries, because the conduits are mainly manufactured around cylindrical substrates. The acquired nerve conduits with simpler architectures may not be sufficient to promote structural and functional nerve regeneration141819. Recent advances in materials and manufacturing enable the fabrication of complex or patient-specific devices20. Three-dimensional (3D) printing, an additive manufacturing technology, is a powerful tool for fabricating 3D constructs with intricate geometries under computer-aided design/computer aided manufacture (CAD/CAM) system control21. The technique currently has been applied to manufacture customized medical devices, such as amputee prosthetics, airway splints, and scaffolds for tissue engineering22. However, the current 3D-printed devices are often made from synthetic materials that lack of biological functionality for cell delivery23. The aim of this study was to establish a novel manufacturing method for the fabrication of nerve conduits with designer geometries for peripheral nerve regeneration, using cell-adhesive gelatin cryogels that prepared by cryopolymerization of GelMA (cryoGelMA). CryoGelMA NGCs with complex or custom architectures (multichannel, bifurcating and anatomically accurate) could be manufactured using a commercially available inexpensive desktop 3D printer. Then the degradability and biocompatibility of the cryoGelMA NGCs were evaluated. The introduction of support cells, an important biological cue, into nerve conduits holds great promise for nerve repair by providing a beneficial local microenvironment for the regenerating axons2425. Adipose-derived stem cells (ASCs) have attracted considerable attention for nerve tissue engineering, because they are multipotent, and can be easily obtained via minimally invasive techniques and be rapidly expanded in vitro2627. Thus the cryoGelMA NGCs were loaded with ASCs to repair a 10 mm nerve defects in rats, and the ability of promoting nerve regeneration was assessed by walking track analysis, electrophysiological assessment, and histological examination. Our strategy to construct a nerve guidance bio-conduit with designer geometries for peripheral nerve regeneration is outlined in Fig. 1. Results Fabrication of cryoGelMA NGCs Moulds with a “lock and key” structure were fabricated by a 3D printing technique, as shown in Fig. 1. Assisted by the 3D-printed moulds, cryoGelMA NGCs with intricate architectures could be obtained. A multichannel NGC that mimics nerve fascicles and a bifurcating NGC that mimics nerve plexus were successfully constructed (Fig. 2A,B). The appearance of NGCs is white and practically in accordance with the original CAD models. To create a patient-specific NGC that was anatomically accurate, we integrated the indirect 3D printing technique with magnetic resonance (MR) neurography and successfully fabricated a personalized NGC with architectures matching the sciatic nerve of a patient (Fig. 2C). The 3D-printed moulds for molding geometrically complex and patient-specific NGCs are shown in 1A–C. A cryoGelMA NGC based on the general anatomical features of a rat sciatic nerve was fabricated to test its degradability, biocompatibility, and efficacy in promoting nerve regeneration. A rat sciatic nerve was transected from a Sprague-Dawley (SD) rat weighted 220–250 g to provide a tissue template. A NGC with inner diameter of 1.5 mm, outer diameter of 4.0 mm, and length of 15 mm was fabricated (Fig. 3A). The 3D-printed moulds for molding the NGC are available in Figure S1D. SEM revealed that the NGC had highly porous microstructure that was essential for cell attachment, proliferation, and survival (Fig. 3B). The wall thickness of the fabricated conduits matched with the original CAD model, but the inner diameter was approximately 0.1 mm smaller than the CAD model. Degradability of cryoGelMA NGCs Non-biodegradable conduits are associated with several disadvantages, such as chronic inflammation and a secondary surgery for conduits removal9. Thus, biodegradable materials are advocated for the preparation of NGCs. Firstly, we tested whether the cryoGelMA NGCs could be enzymatically degraded in vitro. As shown in Fig. 3C, the NGCs could be degraded completely in the presence of 1 mg/ml collagenase type II within 20 h. Then the NGCs were implanted subcutaneously on the dorsal site of rats to evaluate the degradability in vivo (Fig. 3D). The NGCs degraded throughout the implantation period, and remained structurally stable for 2 weeks after implantation. The NGCs were collapsed at 4th week, and did not completely degrade in 2 months. The infiltration of fibroblasts and inflammation cells were evaluated by H&E staining (Fig. 3E). Rare fibroblasts and inflammatory cells could be seen in the NGCs within 2 weeks, suggesting the NGCs prevented the fibrous tissue ingrowth effectively and provoked mild acute inflammatory responses. At 4th and 8th weeks, the NGCs elicited a foreign body reaction, and fibrous tissue with dispersing neocapillaries could be observed in the NGCs. In vitro cell compatibility of cryoGelMA NGCs The suitability of the cryoGelMA NGCs as a substrate for cell attachment and growth was further investigated. Rat ASCs were found distributed throughout the NGCs with rare dead cells as revealed by the live/dead staining (Fig. 4A). The ASCs attached to the surface of NGCs and maintained their fibroblast-like morphology after 2 days of culture (Fig. 4B,D). The deposition of ECMs by the ASCs was more apparent on the NGCs than that on the tissue culture polystyrene (TCP) (Fig. 4C,D). AlamarBlue assay was carried out to evaluate the cell viability, and a lower proliferation rate was observed on the NGCs (Fig. 4E). The gene expression of neurotrophic factors of the ASCs cultured on the NGCs and TCP was further tested. As shown in Fig. 4F, the expression of BDNF and GDNF was significantly up-regulated after cultured on the NGCs (p < 0.05). In vivo nerve regeneration The rat sciatic nerve transection model has been commonly used for the evaluation of tissue engineered NGCs in promoting peripheral nerve regeneration in vivo28. The cryoGelMA NGCs were implanted into the injured sciatic nerve to evaluate the nerve regeneration behaviors through the prepared four groups (sham surgery, autograft, NGCs, NGCs + ASCs). All rats were in good health condition throughout the experiment. To assess the functional recovery of the sciatic nerve, walking track analysis was performed on all operated animals at 2nd, 4th, 8th and 16th weeks post-surgery (Fig. 5). Sham surgery did not affect the SFI value significantly. The autograft group showed a significantly higher SFI value than the NGCs group at 8th and 16th weeks (p < 0.05), but there was no significant difference between the autograft group and the NGCs + ASCs group. Though repair with NGCs had a lower SFI value than that of NGCs+ASCs, no significant difference was observed. Electrophysiological analysis was performed at 4th, 8th, and 16th weeks postoperatively (Fig. 6). CMAP has been commonly used to determine the numbers of regenerated motor nerve fibers29. The action potentials were observed in all groups at 4th week and still intensive at 8th and 16th weeks after surgery, indicating a gradual enhancement of functional recovery for the injured nerves3031. In consistence with the SFI findings, the CMAP in the NGCs + ASCs group was close to the autograft group, and there was no significant difference between the NGCs + ASCs and the NGCs group. NCV is an objective index that offers important insight for evaluating the conduction of action potentials in peripheral nerve31. The NCV value of the NGCs group was significantly lower than that of the autograft and NGCs + ASCs groups at 4th and 8th weeks after implantation (p < 0.05), but no statistically significant difference was observed at 16 weeks among the three groups. Latency of CMAP onset was decreased over time for the autograft, NGCs, and NGCs + ASCs groups, but no significant difference was observed among the three groups. Macroscopically, the cryoGelMA NGCs were all degraded completely, and the proximal and distal stumps were successfully reconnected by the regenerated nerve at 16th week after surgery (Fig. 7). H&E staining showed the general regenerated nerve fibers morphology in the distal segment at 16th week after implantation (Fig. 8A). The axon diameter and myelin sheath thickness of the distal segments of regenerated nerves were then evaluated by toluidine blue staining and transmission electron microscope (TEM) (Fig. 8B–E). The sham surgery group has the largest axon diameter and thickest myelin sheath. The axon diameter and myelin sheath thickness of the NGCs + ASCs group were significant longer than that of the NGCs group (p < 0.05). Although myelin sheath in the NGCs + ASCs group was thinner than that of the autograft group (p < 0.05), there was no significant difference in the axon diameter. After sciatic nerve transection, the gastrocnemius muscles demonstrated degradations of muscle fibers and became fragments, and then regained nerve re-innervation32. H&E staining was performed to evaluate the recovery of nerve function in all groups (Fig. 9A–D). Compared to normal muscle morphology in the sham surgery group, gastrocnemius muscles were degenerated in the autograft and NGCs + ASCs groups, and prominently in the NGCs group. The muscle fiber diameter in the sham surgery, autograft, NGCs, and NGCs + ASCs groups was 43.0 ± 8.3 μm, 37.8 ± 8.6 μm, 33.9 ± 4.5 μm, and 36.0 ± 5.5 μm, respectively (Fig. 9E). The relative gastrocnemius muscle weight increase was similar to the increase in muscle fiber diameter in the four groups (Fig. 9F). The muscle fiber diameter and weight observed in the NGCs + ASCs group significantly increased when compared with that of the NGCs group. Discussion In this work, we demonstrated a flexible method for the fabrication of cryoGelMA NGCs with desired geometries by a low cost desktop 3D printer. At present, the desktop 3D printer is being widely used in education, manufacturing, and industry for its low cost and versatility in fabrication33. With the help of the desktop 3D printer, rationally designed “lock and key” moulds were printed to fabricate NGCs with complex or personalized geometries for peripheral nerve regeneration. Using the “lock and key” moulds, the prepared NGCs could be acquired without dissolving the negative moulds by organic solvent, thus reducing the manufacturing time and avoiding organic solvent influences the internal structural characteristics of the conduits, such as pore size3435. Conventionally, the NGCs are simple cylindrical structures, and it’s difficult and time-consuming to fabricate NGCs with complex architectures181936. The fabrication of NGCs with advanced structures, such as multichannel, has been reported in previous studies using a wire mesh method36373839. However, the conventional method is infeasible to fabricate NGCs with versatile structure parameters, such as the internal diameter or wall thickness, that might affect the efficacy of nerve regeneration5640. Take advantages of the indirect 3D printing technique, we can reliably fabricate NGCs with advanced structures and control the structure parameters. Our technique has advantages in terms of simplicity, flexibility and low cost in fabricating designer NGCs with complex or personalized geometries for peripheral nerve regeneration, which may lead to the development of future NGCs for clinical use. Recently, microstereolithography was used for patterning NGCs with intricate geometries, and a 3D printing methodology was also applied to construct anatomical nerve regeneration pathways based on 3D scanning of a rat bifurcating nerve141819. However, to our knowledge, the fabrication of a NGC based on patient-specific anatomy has never been explored. MR neurography has been increasingly used in recent years to evaluate abnormalities such as nerve injury, entrapment, and neoplasm4142. The complex 3D anatomy of peripheral nerve is resolvable with multiplanar reconstruction, which provides prudently information of the length of injured nerve and the geometries of the proximal and distal discontinuous nerve stumps2. In this work, we performed an attempt to integrated 3D printing methodology with MR neurography to engineer a NGC based on the anatomic geometries of a patient without any aggressive manipulations, which allows the customization of a NGC that precisely match a particular nerve defects of a patient18. Both in vitro and in vivo degradation studies show that the cryoGelMA NGCs were degradable. The NGCs have a proper degradation rate (completely degraded at 2–4 months), which is similar to several FDA approved NGCs, such as Neurotube® and AxoGuardTM Nerve Connector6. We found that ASCs cultured on the NGCs gave rise to more ECMs accumulation than that on the TCP. Furthermore, the expression of several neurotrophic factors mRNAs, such as BDNF, was unregulated after seeding the ASCs on the NGCs. The enhancement of cell-cell and cell-matrix interactions on the NGCs provides a more physiologically relevant environment to the ASCs, and thus enhances their functions43. Those results suggested that the introduction of ASCs into cryoGelMA NGCs may provide a favorable repair-conducive environment for nerve regeneration26. In vivo experiments also confirmed a benefit of applying the ASCs in promoting nerve regeneration after transplanted into the injured site. Several previous studies have demonstrated the utilization of ASCs improved axonal regeneration in vivo, and this effect has been attributed mainly to the environmental support provided by the ASCs during nerve regeneration44454647. Walking track assessment and electrophysiological analysis are widely accepted techniques for the functional evaluation of sciatic nerve repair in rats2432. We found that the cryoGelMA NGCs cellularized with ASCs showed similar results to the autograft group in function recovery and axonal regeneration as evidenced by no statistical difference in SFI, electrophysiological results, and nerve and muscle fiber diameters between the two groups. Although we did not observe significant beneficial effects on gait and electrophysiological analysis in ASCs-seeded NGCs compared to bare conduits, the significantly increased axonal regeneration and nerve re-innervation of gastrocnemius muscle suggested the application of ASCs promoted nerve regeneration in histomorphological parameters. The discrepancy between the outcomes concerning motion analysis and tissue structures is in line with several previous study3245. A higher dose of ASCs may show improved functional recovery as a relatively low dose of ASCs (1 × 106) was used in our study4648. Conclusion We described an indirect 3D-printing technology for fabricating cellularized designer cryoGelMA NGCs for peripheral nerve regeneration. By molding with 3D-printed “lock and key” moulds, NGCs with desired geometry, such as multichannel, bifurcating and the personalized structures, could be obtained by a low cost desktop 3D printer. The ASCs-cellularized NGCs were comparable with that of the autografts in repairing a peripheral nerve defect, showing potential clinical application in peripheral nerve regeneration. Materials and Methods Synthesis of GelMA GelMA was synthesized following the procedures described elsewhere13. Briefly, gelatin type A (300 bloom from porcine skin, Sigma) at 10% (w/v) was dissolved into stirred Dulbecco’s phosphate buffered saline (DPBS) at 60 °C. Methacrylation of gelatin was achieved by adding 20% (v/v) of methacrylic anhydride (Sigma) at a rate of 0.5 mL/min and reacting at 50 °C for 1 h. Following a 5× dilution with warm DPBS (40 °C), the mixture was dialyzed against distilled water at 40 °C for 2 weeks. The sample was then lyophilized and stored at −20 °C until further use. CryoGelMA NGCs fabrication CryoGelMA NGCs with desired structures, such as multichannel and bifurcating, were prepared by molding based on “lock and key” moulds that were designed via SolidWork version 2012 (SolidWorks Corp., Waltham, Massachusetts, USA) and manufactured by a commercially available desktop ink-jet printer (TD-IIA, TD ARTIST, Chengdu, China). To fabricate a cryoGelMA NGC based on anatomic geometry of a patient, the shape of sciatic nerve was isolated from the MR neurography by a commercially available software (Mimics, Materialise). Based on the image data, “lock and key” moulds were designed and converted into an STL file followed by 3D printing49. To further investigate the degradability, biocompatibility, and efficacy of nerve regeneration of the cryoGelMA NGCs, a 10 mm right sciatic nerve was acquired from the mid-thigh level of SD rats (220–250 g). The diameters of proximal and distal stumps of the injured nerve were measured for designing moulds. GelMA prepolymer solution was formed by dissolving 5% (w/v) GelMA in dH2O and maintained at 60 °C to dissolve adequately. After incubated on ice for 5 min, 0.5% (w/v) ammonium persulfate (APS; Sigma) and 0.1% (w/v) tetramethylethylenediamine (TEMED; Sigma) were added to the prepolymer solution. The solution was then pipetted into the 3D-printed moulds cavity and underwent cryopolymerization for 24 h in a −20 °C refrigerator. The resulting cryogels were hydrated and harvested, and washed by deionized water extensively. After immersed in 75% ethyl alcohol for one hour, the gels were washed and collected into cell culture dish, lyophilized overnight (Boyikang), and stored in −20 °C prior to use. SEM The morphology of the cryoGelMA NGCs were observed by using scanning electron microscopy (SEM, Hitachi S4800) operated at 5.0 kV. For this observation, the lyophilized conduits were mounted on aluminum stubs and gold-coated for 90 s before SEM imaging. Degradability CryoGelMA NGCs were incubated with 1 mg/ml collagenase type II (Sigma) in DPBS and were placed on an orbital shaker at 100 rpm and 37 °C. At predefined time points (t = 4, 8, 12, 16, and 20 hours), the conduits were harvested. The degradation of the NGCs was calculated as a ratio of loss of dried weight to the primary weight. For in vivo degradation study, the conduits were implanted subcutaneously on the back of SD rats. At predefined time points (1, 2, 4 and 8 weeks) after implantation, the implants were photographed and harvested together with surrounding tissue for histological evaluation. We confirm that all experiments were performed in accordance with the guidelines and regulations of Sichuan University Committee on Animal Research and Ethics and were approved by the Institutional Animal Care and Use Committee of West China Hospital of Sichuan University. Cell adhesion and proliferation Rat ASCs were isolated from subcutaneous adipose tissue of inguinal region of SD rats. ASCs were then maintained in Dulbeccos’ modified Eagles’ medium (DMEM, Invitrogen) with low glucose, containing 10% (v/v) fetal bovine serum (FBS, Invitrogen), 100 U/ml penicillin, 100 μg/ml streptomycin. Cells were trypsinized upon 80% confluency and each conduit was seeded with 1 × 105 cells. 2 days after seeding, Live/Dead assay (Invitrogen) was performed for visualization of cell viability using a Zeiss confocal microscope (Zeiss). Moreover, F-actin was stained using rhodamine phalloidin (Cytoskeleton) and cell nucleus was stained using DAPI (Invitrogen), and images were taken on the confocal microscope. The morphology of ASCs on the cryoGelMA NGCs was visualized using SEM. After fixed with 3% glutaraldhyde for 2 h, specimens were rinsed with PBS and dehydrated with graded concentrations (30, 50, 70, 90, 100% v/v) of ethanol. Then the samples were coated with gold and observed with SEM. Cell proliferation was determined by AlamarBlue assay (Invitrogen). Briefly, 5 × 104 cells in 50 μl were seeded on each conduit and incubated for 1.5 h to allow for cell attachment. Then 1 ml fresh medium was added and the composites were cultured in 24-well plates for 24, 48 and 72 h. Meanwhile, ASCs of same density were seeded on the TCP as the control. After each time point of cell seeding, the culture medium was removed and 1 ml of 10% (v/v) Alamar blue in culture solution was added. After 3 h of incubation, aliquots were pipette into a 96-well plate and the absorbance at 570 nm and 595 nm was measured. Cell numbers were determined by a standard curve. RT-PCR Total RNA was extracted using the Trizol® reagent (Invitrogen) form ASCs cultured on conduits and TCP for 2 days. RNA strand was reverse transcribed into cDNA and amplified using PrimeScript II 1st Strand cDNA Synthesis Kit (TaKaRa). Polymerase chain reactions (PCRs) were performed using primers for glyceraldehyde 3-phosphate dehydrogenase (GAPDH), nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), and glial cell-derived neurotrophic factor (GDNF) as previously described50. PCRs were carried out with SYBR Premix Ex Taq (TaKaRa). The resulting amplification was monitored with the CFX96 Real-Time System (Bio-Rad). The expression levels were normalized against the reference gene GAPDH, and the relative gene expression was analyzed. The primer sequences for each gene used in this study are shown in Table S1. Animal and surgical procedure SD rats weighing 220–250 g were used and randomly divided into four experimental groups: sham surgery group (n = 6), autograft group (n = 12), NGCs group (n = 12) and NGCs + ASCs group (n = 12). 1 × 106 ASCs at early passages (P3–P6) were seeded on each conduit and cultured for 3 h at 37 °C to allow cells fully attached to the cryoGelMA scaffolds. After anesthetized by intraperitoneal chloral hydrate, the hair on the right femur was removed. Under aseptic conditions, the right sciatic nerve was exposed, and a 10 mm segment of the sciatic nerve was removed at the mid-thigh level. The NGCs were interposed between the proximal and distal nerve stumps. The nerve stumps were inserted into the NGCs to a depth of 2.5 mm, and fixed with 8-0 absorbable vicryl sutures. For autograft, the 10 mm transected nerve was re-implanted under microscope. Following the implantation, the muscle incision was closed using 5-0 vicryl sutures and the skin was closed with 2-0 silk sutures. Postoperatively, animals were free access to food and water, and housed in a controlled room with 12 h light cycles. Walking track analysis The motor functional recovery was evaluated by walking track analysis at 2, 4, 8 and 16 weeks post-operatively. Pre-operatively, all rats were underwent conditioning training in a 50 cm × 8 cm wooden track. After the hind feet dipped in black ink, rats were allowed to walk down the track. Five measurable footprints were collected for each rat. Sciatic Function Index (SFI) was calculated by the formula proposed by Bain et al.51 as follows: The print length (PL) is the distance from the heel to the third toe, the toe spread (TS) is the distance from the first to the fifth toe, and the intermediary toe spread (IT) is the distance from the second to the fourth toe. EPL, ETS, and EIT represent recordings from the operated foot, as well as NPL, NTS and NIT from the non-operated foot. A value of −100 implies total impairment. Electrophysiological analysis Electrophysiological tests were performed using a previous developed method at 4, 8 and 16 weeks after implantation30. An electromyograph machine (Nuocheng, Shanghai, China) was used to measure all the experimental animals. After the sciatic nerve was exposed under anesthetization, a stimulating electrode was placed at the proximal side of regenerated nerve, and a recording electrode was inserted into the gastrocnemius muscle. The reference electrodes were positioned between the stimulating electrode and the recording electrode. The ground electrode was placed in the tail. For quantitative analysis, the peak amplitude of compound muscle action potential (CMAP), nerve conduction velocity (NCV), and latency of CMAP onset values were calculated respectively. Histological assessment The distal nerve segments were harvested immediately after electrophysiological examination at 16 weeks after implantation. The paraformaldehyde-fixed nerves were dehydrated, embedded in olefin, cut into 5 μm-thick slices, and stained with hematoxylin/eosin (H&E). The other samples were embedded in Epon 812 epoxy resin and stained with toluidine blue after cut into semi-thin sections (0.5 μm). The images of histological sections were captured and analyzed using a digital image analysis system (Nikon E600 Microscope with a Nikon Digital Camera DXM 1200, Nikon Corporation, Japan). To observe the ultrastructure of myelin sheath, ultrathin sections (50 nm) were viewed and photographed with a Hitachi H7650 TEM (Tokyo, Japan). The diameters of myelinated axons and thickness of myelin sheath were quantified from TEM images using the Image J software. For each specimen, a total of 50–60 random axons were analyzed. The gastrocnemius of both limbs was harvested from the bone attachments at 16 weeks after surgery. The moist weights of the gastrocnemius muscle were weighed on an analytic scale, and the ratio of wet weight on the experimental to contralateral sides in each group was calculated to evaluate the target muscle reinnervation. Then the middle portion of the muscle was dissected and placed in 4% paraformaldehyde for H&E staining. The diameters of muscle fibers were calculated from 5 random fields using the Image J software. Statistical analysis Values are expressed as means ± standard deviation. Significant differences among groups were analyzed by single-factor analysis of variance (ANOVA) followed by Bonferroni’s post-hoc test using SPSS 16.00 software. Statistically significant differences between medians were determined with a Mann-Whitney U test. A value of p < 0.05 was considered statistically significant. Additional Information How to cite this article: Hu, Y. et al. 3D-engineering of Cellularized Conduits for Peripheral Nerve Regeneration. Sci. Rep. 6, 32184; doi: 10.1038/srep32184 (2016). Supplementary Material Supplementary Information This work is supported by the National Natural Science Funds of China (81422025, 81572990), and supported by National High Technology Research and Development Program (“863” Program) of China (2015AA020303, 2014AA020509). Sichuan province science and technology support plan (2015SZ0049). Author Contributions M.G., Y.H., S.J., S.H. and Y.D. designed the experiment. Y.H. and Y.W. fabricated the scaffolds/conduits, conducted the in vitro and in vivo studies, and drafted the manuscript; Z.G. designed and 3D printed the moulds; J.T. and J.Z. characterized the materials; Q.L. and T.K. were involved in some of the staining experiments and results analysis; and M.G., S.C., S.J., S.H. and J.H. supervised this project. All authors contributed to discussion and analysis of the data. Figure 1 Schematic presentation of the 3D-engineered bio-conduit for peripheral nerve regeneration. Moulds with a “lock and key” structure were fabricated by an indirect 3D printing technique. Then a cryoGelMA NGC was fabricated and seeded with ASCs to bridge a 10 mm sciatic nerve defect. Figure 2 Computer models and photographs of cryoGelMA NGCs with complex geometries, such as multichannel (A) and bifurcating (B). A patient’s sciatic nerve was reconstructed based on MR neurography, and then a personalized NGC was fabricated (C). Figure 3 Fabrication, characterization and degradation of cryoGelMA NGCs used for nerve repair in rat sciatic nerve transection model. (A) The diameters of the transected sciatic nerve were measured for NGCs design and fabrication. (B) SEM micrographs of the NGCs. (C) Degradation of the NGCs in presence of collagenase type II (1 mg/ml) solution in vitro (n = 3). (D) Photographs of the biodegradable NGCs subcutaneously on the dorsal site of rats at 1, 2, 4, and 8 weeks after implantation (scale bars = 5 mm). (E) Representative H&E staining of tissue sections of the NGCs at various time point (1, 2, 4, and 8 weeks) after implantation (scale bars = 200 μm). Figure 4 The attachment, proliferation, survival, and secretion of neurotrophic factors of ASCs on cryoGelMA NGCs in vitro. (A) Live/dead analysis of ASCs on the NGCs after 2 days of cell seeding (Scale bars = 200 μm, scale bars in upper left inset = 25 μm). (B) Staining of F-actin by rhodamine phalloidin. The ASCs spreaded on the surface of NGCs after 2 days of culture (Scale bars = 200 μm, scale bars in upper left inset = 25 μm). SEM micrographs of ASCs cultured on the TCP (C) and NGCs (D). (E) Analysis of the proliferation of ASCs on the TCP and NGCs after 1, 2, and 3 days of culture (n = 3). (F) Gene expression of major neurotrophic factors (NGF, BDNF, and GDNF) of ASCs on the TCP and NGCs at 2 days post-seeding. *p < 0.05 for comparison with the TCP. Figure 5 The SFI values of rats at 2, 4, 8 and 16 weeks after treatments (n = 4). *p < 0.05 for comparison with the autograft group. Figure 6 Electrophysiological assessments of the regenerated nerves in different treatment groups at 4, 8, and 16 weeks postoperatively. (A) Representative CMAP recordings at the injured side in each group at 16 weeks after implantation. The peak amplitude of CMAP (B), NCV value (C), and latency of CMAP onset (D) were recorded at different intervals after surgery. ∗p < 0.05 for comparison with autograft group, and #p < 0.05 for comparison with NGCs group. Figure 7 Intraoperative photographs of the cryoGelMA NGCs for nerve regeneration in a rat sciatic nerve transection model. (A,B) The rat sciatic nerve was transected to create a 10 mm gap and bridged with the 3D-printed NGCs. The general observations of the regenerated sciatic nerve in the sham surgery (C), autograft (D), NGCs (E), and NGCs + ASCs (F), groups at 16 weeks after surgery. Figure 8 Histological assessment of the regenerated sciatic nerves in the distal segment at 16 weeks after surgery. (A) H&E staining shown the overview of nerve morphology in each group (Scale bars = 200 μm). Myelination of regenerated nerves revealed by toluidine blue staining (B, scale bars = 25 μm) and TEM (C, scale bars = 5 μm). Statistical analysis of the diameters of myelinated nerves (D) and thickness of myelin sheath (E) for each group (n = 4). ∗p < 0.05 for comparison with autograft group, and #p < 0.05 for comparison with NGCs group. Figure 9 The gastrocnemius muscles atrophy and re-innervation. (A–D) H&E staining of gastrocnemius muscles cross-section in the sham surgery (A), autograft (B), NGCs (C), and NGCs + ASCs (D), groups at 16 weeks after implantation (Scale bars = 100 μm). (E) The mean diameters of muscle fibers and (F) the wet weight of the operated side to the non-operated side in different groups (n = 4). ∗p < 0.05 for comparison with autograft group, and #p < 0.05 for comparison with NGCs group. ==== Refs Faroni A. , Mobasseri S. A. , Kingham P. J. & Reid A. J. Peripheral nerve regeneration: experimental strategies and future perspectives . Adv Drug Deliv Rev 82–83 , 160 –167 (2015 ). Chhabra A. , Ahlawat S. , Belzberg A. & Andreseik G. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3217110.1038/srep32171ArticleEffect of silver on the phase transition and wettability of titanium oxide films Mosquera Adolfo A. 1Albella Jose M. 1Navarro Violeta 2Bhattacharyya Debabrata 3Endrino Jose L. a31 Instituto de Ciencia de Materiales de Madrid, Consejo Superior de Investigaciones Científicas, E-28049 Madrid, Spain2 Interface Physics Group, Kamerlingh Onnes Laboratory, Leiden University, The Netherlands3 Department, School of Aerospace, Transport and Manufacturing (SATM), Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL, UKa j.l.endrino@cranfield.ac.uk30 08 2016 2016 6 3217121 04 2016 29 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The effect of silver on the phase transition and microstructure of titanium oxide films grown by pulsed cathodic arc had been investigated by XRD, SEM and Raman spectroscopy. Following successive thermal annealing up to 1000 °C, microstructural analysis of annealed Ag-TiO2 films reveals that the incorporation of Ag nanoparticles strongly affects the transition temperature from the initial metastable amorphous phase to anatase and stable rutile phase. An increase of silver content into TiO2 matrix inhibits the amorphous to anatase phase transition, raising its temperature boundary and, simultaneously reduces the transition temperature to promote rutile structure at lower value of 600 °C. The results are interpreted in terms of the steric effects produced by agglomeration of Ag atoms into larger clusters following annealing which hinders diffusion of Ti and O ions for anatase formation and constrains the volume available for the anatase lattice, thus disrupting its structure to form rutile phase. The effect of silver on the optical and wetting properties of TiO2 was evaluated to demonstrate its improved photocatalytic performance. ==== Body Titanium dioxide is a polymorphous compound with a broad range of applications in catalysis and photocatalysis, gas sensors, energy storage, self-cleaning devices, optical and corrosion protective coatings1. These applications are dependent on the crystallographic structure, morphology and physical properties of the different phases of titania. As a bulk material, it can exhibit anatase, rutile and brookite forms while TiO2 thin films only show amorphous, anatase or rutile structures. Brookite thin films can only be achieved by chemical deposition techniques23 at high deposition or annealing temperatures4. Different chemical routes have been used to synthesize bulk titania. Sol-gel5, hydrothermal techniques6, spray pyrolysis and chemical vapour deposition allow to synthesize anatase powders at low temperatures78, while rutile phase can be obtained after annealing treatments at temperatures around 900 °C9. In TiO2 powders, the transition temperature is determined by grain size, deposition techniques and process conditions such as thermal annealing10. In some applications, for instance optical coatings, the fabrication of rutile at lower temperatures is of paramount importance, since rutile is thermodynamically the most stable phase of titania, giving the highest refractive index and hardness1112. Nowadays, there are many reports on the structural and morphological properties of the anatase-rutile (A-R) transformation upon annealing treatments, showing either pure or mixed rutile phase at temperatures above 800 °C131415. To promote the A-R transition at lower temperatures for bulk titania, many dopants have been proposed, thus expanding its range of applications. For instance, V-doped TiO2 powders show the promotion of rutile phase at 700 °C, with an improvement of their ferromagnetic characteristics16. Besides, Ni- and Ru-doped TiO2 systems also show rutile phase at 700 °C having larger grain size17. In addition, other dopant promoters such as Co, Cr, Cu, Na, Ni, Sn, Al and Zn have been studied in the past12. In these earlier studies, silver (Ag) has been theoretically predicted as a cation promoter for the A-R transition in bulk titania, although no systematic work has been reported. Recently, the thin film properties of TiO2 have been thoroughly investigated, because it can be used for photocatalytic applications, as hydrophobic coating for optical glass and antireflection coating in solar cells. In addition, Ag-doped TiO2 films are well known for their antibacterial properties18. However, the influence of silver on the phase transition and other physical properties of the films is not well documented, and only a few studies have been reported on the evolution of the phases of TiO2 films grown by chemical methods such as sol-gel containing low Ag concentrations192021. These works show either a mixture of TiO2 phases or no evidence of the rutile phase after thermal annealing at temperatures up to 700 °C21222324. In contrast, while physical deposition techniques are used such as sputtering25, pulsed laser26 and cathodic arc27, the influence of silver on the transition temperature from anatase to rutile of TiO2 films has not been fully investigated2328. It is evident that the tailoring of crystalline phases of TiO2 matrix would optimise their device performance by enhancing the catalytic properties, refractive index profile and bio-activity of the selected phase of interest29303132. It is also desirable to achieve denser rutile films at temperatures compatible with non-high temperature resistant substrates, having superior mechanical, optical and charge transport properties3334. In a recent work, we have evaluated the effect of incorporating silver into TiO2 films using X-Ray Absorption Near Structure (XANES)35. The results had demonstrated, for the first time to the best of our knowledge, the dominant effect of silver on the phase transition from amorphous state to anatase and rutile. The main purpose of this work is to investigate the underlying physical mechanisms of the anatase to rutile phase transformation phenomenon further and determine the effect of incorporating Ag nanopaticles into TiO2 thin films systematically. The phase property and surface morphology of TiO2 films have been studied by tailoring the addition of Ag content into TiO2 matrix followed by successive thermal treatments up to 1000 °C to identify the boundary of amorphous to anatase transition, and similarly the possibility of inducing anatase to rutile transition at lower annealing temperature. In addition, the wetting properties and optical spectral response of TiO2 thin films have been assessed to study the influence of Ag incorporation onto their photocatalytic performance and optical transmittance. Results Raman Analysis It is well-known that Raman spectroscopy is a powerful tool to detect the vibrational modes of chemical bonds and can identify the distinct crystalline state of materials accurately. In this work, we have employed this technique to investigate the effect of silver on the microstructural properties of TiO2 films after thermal annealing. The Raman spectra, as shown in Fig. 1, indicate that the as-deposited samples are non-crystalline in nature, since no characteristic bands of TiO2 are detected. The strong band located at 520 cm−1 corresponds to the LO-phonon line of the silicon substrate as well as to the associated noise as expected. The evolution of spectra from pure TiO2 films following annealing, Fig. 1a, reveals three bands located at 144, 395 and 638 cm−1 at 200 °C that are characteristic Eg (Low-Frequency, LF), B1g, and Eg (High-Frequency, HF) phonon modes of anatase3637 respectively. With an increase of the annealing temperature above 200 °C, the anatase vibrational modes became more intense until a new prominent band develops at 1000 °C, representing characteristic of vibration modes of rutile phase38. At this high temperature other rutile bands, 442 and 608 cm−1 which are associated with the Eg and A1g phonon modes were also observed along with an additional band arising from two phonon scattering vibrations located at 235 cm−1. As for the Ag-TiO2 nanocomposite films, the vibrational modes corresponding to the anatase start to form at 400 °C for the samples with lowest Ag content (0.08Ag-TiO2), whereas weaker B1g, and Eg (HF) modes of anatase tend to develop at 600 °C (Fig. 1a). Even with an increase of temperature up to 800 °C, these bands still remain weak in intensity. In addition, the Eg rutile vibration starts to appear at this higher temperature, which is fully developed at 1000 °C, accompanied by the evolution of the other two intense vibrational rutile modes. For the 0.16Ag-TiO2 samples, Fig. 1a, the vibrational anatase modes are detected at and above 600 °C, with a new band centred at 198 cm−1 corresponding to the Eg vibration phonon mode, while the other fundamental vibrational modes of anatase are very weak. The band located at 245 cm−1, which is related to the double phonon scattering as stated above, indicates the anharmonicity of the emerging rutile phase36. Further annealing at 800 °C produces a shift of this band to 235 cm−1 along with other two vibrational rutile modes, the Eg and A1g centred at 442 and 608 cm−1 respectively with no sign of anatase bands. At 1000 °C, only the vibrational modes associated to the rutile phase were observed. The distinct features were observed from the 0.28Ag-TiO2 and 0.40Ag-TiO2 films unlike low Ag content samples. As shown in Fig. 1b, the broad and intense Eg (HF), Eg (198 cm−1) anatase modes as well as a weak rutile double phonon band (at 245 cm−1) were detected at 600 °C simultaneously, which were otherwise absent at lower annealing temperatures. In addition, the annealed 0.40Ag-TiO2 sample at 600 °C had also shown a new band at 320 cm−1, featuring the two-phonon scattering band of the anatase phase. Further annealing at 800 °C produces an enhancement of the vibrational rutile modes, characterized by narrow and intense bands, especially the Eg and A1g phonon modes that became sharper when the annealing temperature reached to 1000 °C. It is noteworthy that in all of the Ag-TiO2 samples the broad and complex bands, located at wavenumbers higher than 650 cm−1, are originated from the silicon substrate. Preliminary analysis of Raman spectra have established that the pure as-deposited TiO2 films grown by pulsed cathodic arc are primarily amorphous. Following thermal treatments, the anatase phase is developed at 200 °C for these films, while for Ag containing samples with the lowest atomic ratio (0.08) the anatase transition is shifted to 400 °C, and finally showing weak bands of rutile at 800 °C. In samples with Ag ratio of 0.16, anatase phase fully develops at annealing temperature of 600 °C. With increasing temperature above 600 °C, the weak rutile bands start to form that are further developed becoming more intense at 800 °C. In contrast, the spectra corresponding to samples with higher Ag ratios (0.28 and 0.40) exhibit that the samples are amorphous up to 600 °C with little sign of anatase. Above 600 °C anatase phase is predominant, however a favourable thermally induced grown condition promotes rutile phase to form and develop simultaneously unlike low Ag-content sample. At higher temperatures above 800 °C, the rutile phase seems to be the dominant one as only rutile bands are present. Crystallographic phase and Microstructure Figure 2 shows grazing angle X-ray diffraction spectra of pure TiO2 and Ag-TiO2 films in as-deposited form and after annealing at temperatures up to 1000 °C. For pure TiO2 sample, the absence of XRD peaks confirms that the structure of the films is amorphous at room temperature (25 °C) showing only broad background, whereas above 200 °C the XRD patterns reveal four distinct peaks at 25.3, 48.1, 55.0 and 62.7° respectively, originated from anatase phase (JCPD-211272 data card, used as reference). Rutile peaks at 27.4, 54.3, 56.6 and 69.1° were only observed when the annealing temperature was increased up to 1000 °C based on rutile data card reference identification (JCPD-211276). The peak located at 56.2° is attributed to the silicon substrate. In contrast, the XRD spectra of the Ag containing TiO2 films with low atomic ratio (0.08 and0.16) show that they are still amorphous at 200 °C, thereby validating Raman scan (Fig. 2a) discussed in earlier section. Only peaks related to anatase phase were observed in these samples when annealing temperature reached at 400 °C, while a mixture of rutile and anatase phases were observed at 800 °C. XRD analysis had established that the final crystal structure of the Ag-TiO2 films became rutile following thermal annealing at higher temperature at and above 1000 °C. This results are in agreement with previous results, which show the phase evolution of the Ag-TiO2 films with annealing treatments35. For these low Ag-content annealed samples, no peak related to silver was observed. This can be interpreted by the fact that silver nanoparticles are finely dispersed in the film microstructure and their concentration is likely below the detection limit of the diffractometer as also reported by others23. In Fig. 2b, the XRD patterns of samples with higher Ag concentrations (0.28 and 0.40 atomic ratio) reveal the formation of anatase phase only at and above 600 °C unlike the low Ag-content samples shown in Fig. 2a that produces anatase phase at 400 °C. Further thermal treatments have shown a promotion of rutile at 800 °C but with no evidence of anatase phase. At 1000 °C, only the rutile phase was observed. It was also noted from XRD analysis that high temperature annealing of the high Ag content TiO2 film at 1000 °C gives rise to an additional peak at 38.1°, corresponding to the (111) plane of crystalline silver (reference JCPD-40783)39. The identification of the (111) silver by XRD in samples with high Ag ratio (>0.16) reveals that Ag atoms diffuse into the amorphous TiO2 matrix and agglomerate in forming larger clusters following heat treatment subsequently. The crystallite size of silver in the 0.28 and 0.40 Ag-TiO2 samples have been found to increase with the Ag atomic ratio and annealing temperature. The grain size of Ag was calculated from the width (FWHM) of the XRD peaks according to Scherrer equation as given in Table 1 40. In fact, this type of agglomeration of Ag and Au atoms as metallic nanoparticles in dielectric materials owing to heat treatment is well documented in the literature23. The initial nuclei are supposed to grow by Ostwald-type ripening in a broad range of sizes as the annealing temperature increases41. As shown in Fig. 3, HRTEM analysis exhibits the presence of Ag clusters in 0.28 Ag-TiO2 films following annealing at 200 °C that are of 4.5 nm size on average. In addition, TEM image also reveals the (111) crystallographic planes similar to XRD analysis, having the characteristic separation distance of 0.23 nm. The formation of the Ag clusters and their agglomeration with temperature have been further identified by FESEM study of the cross sectional scan of the films. Figure 4 shows the images of silver nanoparticles embedded in Ag-TiO2 films annealed at different temperatures. In the as-deposited samples, the surface morphology of the film is columnar in nature with a homogeneous texture. As shown in Fig. 4b, silver nanoparticles are distributed within the coating microstructure at 200 °C, and it is agglomerated in spherical-shaped particles with a mean grain size of around 40 nm. SEM and XRD analysis had further revealed that the clustering of Ag nanoparticles increases in size from 45 to 70 nm following an increase in annealing temperature from 400 to 800 °C respectively. As observed in Fig. 4c–e, these clusters tend to diffuse and migrate towards the film surface, in agreement with the results by other authors4243. XRD results had confirmed the interpretation of the Raman spectra on the nature of shift of the phase transition. The transition temperature from amorphous to anatase shifts progressively up to 400 °C for low Ag content samples compared to the as-deposited TiO2 film, whereas such transition occurs at higher temperature at 600 °C for higher Ag concentration. It was further observed that the appearance of the rutile phase is promoted at lower temperatures 800 °C and even at 600 °C for higher Ag contents in Ag-TiO2 samples that would be of potential interest for thin film device applications. Furthermore, HRTEM and FESEM analysis indicate that Ag nanoparticles migrate through the TiO2 microstructure under the influence of thermal treatments, forming agglomerates that increase their grain size with annealing temperature. Silver Oxidation by XPS Analysis The gradual transformation of silver to the metallic state with increasing annealing temperature had been observed by XPS analysis. Figure 5 shows the XPS spectra of the Ag 3d core level of 0.28Ag-TiO2 films before and after annealing at 300 and 400 °C. The Ag 3d5/2 and Ag 3d3/2 peaks have been detected giving binding energies of 369.0 and 375.0 eV respectively (Fig. 5a). After deconvolution, the spectra have shown a small shoulder peak located at 368.0 eV along with a doublet located at 374.0 eV. The high energy value of the Ag 3d peaks could be ascribed to the presence of spatial charge associated to the ion bombardment, as well as to the particle size44. Additionally, adventitious carbon on the film surface45 could also contribute to this effect, whereas the small doublet is attributed to Ag0 4647. To avoid the effect of carbon, the annealed samples were etched for 60 minutes for XPS characterisation. XPS analysis of the samples annealed at 300 °C (Fig. 5b) shows that the Ag 3d5/2 and Ag 3d3/2 core levels are located at 368.3 and 374.3 eV respectively. The position of these peaks coincides with the previous doublet, a characteristic of metallic silver4849, which is in good agreement with the XRD results. As shown in Fig. 5c, annealing at higher temperatures allows the metallic state of silver to become stable implying that there is no significant shift of the Ag core level peaks in this case. Surface morphology by AFM Analysis Figure 6a shows the surface morphology of pure TiO2 and 0.16Ag-TiO2 films without annealing. A surface with average rms roughness of 0.2 nm (Ra = 0.2 ± 0.1 nm) was observed in the pure TiO2 sample. The grainy structure and the absence of atomically smooth terraces indicates that the as-deposited samples are amorphous/polycristalline in nature50. The 0.16Ag-TiO2 sample shows densely populated grain structures, giving a higher rms roughness value as Ra = 0.7 ± 0.1 nm (Fig. 6b). Following annealing at 800 °C, a change in surface morphology was clearly noticed from AFM scan of these samples. In contrast to the as-deposited pure TiO2, the annealed sample, Fig. 7a, shows flat terraces similar to those observed in rutile TiO2 (110) crystalmetals with the characteristic monoatomic step height of 0.3 ± 0.1 nm, indicating the crystallinity acquired during annelaing51. However, for the 0.16Ag-TiO2 sample, Fig. 7b, the atomic terraces are not observed which is expected due to silver diffusion and segregation onto the film surface, as confirmed by SEM analysis (Fig. 4e). In addition, a change in the average roughness value was obtained after annealing at 800 °C: the pure TiO2 films show Ra = 5.1 ± 0.2 nm, whereas in the 0.16Ag-TiO2 sample it was increased giving Ra = 7.2 ± 0.2 nm. Comparing the Ra values obtained from Ag-content samples after annealing at 800 °C, the films roughness increases slightly in good agreement with the previous results that has established this increase in Ra values related to phase transformations of the film microstructure with thermal annealing1352. Wetting Property The photocatalytic performance of the Ag-TiO2 films had been assessed by investigating wetting properties of the annealed samples at different temperatures. The effect of UV irradiation time on contact angle of the films is illustrated in Fig. 8a,b for two samples with different Ag contents of 0.08 and 0.28 respectively. In the as-deposited films, the value of the wetting angle before UV irradiation was measured as 81°, which indicates partially hydrophobic state of the film surface. As can be observed from Fig. 8a, the contact angle of UV-irradiated films with lower silver content (0.08) decreases monotonously in all samples irrespective of post-processing thermal treatment. This signifies the tendency of the films to become highly hydrophilic following irradiation. It is noteworthy that the contact angle decreases sharply for the samples, subjected to annealing at lower temperature range between 200–400 °C. This is, in fact, the boundary between amorphous to anatase transformation at which the film surface reaches quickly, by about 30 min, at superhydrophilic state producing contact angle ~5°, whereas the annealed samples between 600–1000 °C require longer irradiation time of about 60 min to reach the superhydrophilic state. Finally, at 1000 °C when the crystalline phase is fully transformed to rutile, the time required to achieve superhydrophilicity increases further about 80 minutes giving rise to contact angle of 19°. In contrast, the wetting angle of 0.28Ag-TiO2 sample shows significant difference compared to 0.08Ag-content films as shown in Fig. 8b. In higher Ag-content samples, the contact angle takes longer time up to 140 min to reach lower value in achieving hydrophilic state under similar processing conditions. In particular, the annealed samples at 600 °C and above gave a low value of contact angle, however tend to retain its hydrophilicity value,, of about 50°, substantially after prolong period of UV exposure. It is evident that the presence of Ag in TiO2 matrix would influence the wetting properties of the annealed film surface during crystallization process and change in microstructure induced by phase transition as reported by others5354. The results had established that the Ag-TiO2 structure with high silver content, when subjected to high temperature annealing to reach full phase transformation to rutile, maintain the lower and constant value of hydrophobicity, being insensitive to UV illumination. Optical properties The Ag-content samples deposited on glass substrates and annealed at 300 °C and 450 °C respectively were chosen for the spectral characterisation in the UV-visible-NIR bands. The transition temperature of the glass substrate is 557 °C that imposes limitation on choice of higher annealing temperatures. This paper is, therefore, focussed on qualitative study of the photocatalytic performance of TiO2 film at lower temperature range below 500 °C which prevents structural relaxation in glass to retain its mechanical property. As expected, the optical study of the TiO2 sample will only provide the effect of amorphous to anatase phase transformation at 300–450 °C. In fact, TiO2 at its anatase phase has soft crystal direction along the [001] orientation, e.g., normal to the device layer plane that allows easier band gap tuning unlike rutile phase. While the rigorous analysis of the optical properties of annealed Ag-content TiO2 film is beyond the scope of this paper, it will be still interesting to investigate qualitatively the degree of improvement of its photocatalytic behaviour from variation of the energy band gap (Eg) owing to complex phase kinetics of Ag-content TiO2 matrix at anatase phase. The energy band gap (Eg) of the material was estimated from the transmission spectrum and optical absorption coefficients obtained from the well-known formulas given by equations (1,2) using graphical methods55. where, α is the absorption coefficient that depends on valence and conduction band configuration of the material, and varies with photon energy, hν. Eg is the material band gap and η0 is the refractive index. Here, λ is wavelength, h is Planks constant and c is velocity of light in free space. n is a constant typically considered as 1/2 for allowed band transitions and 2 for forbidden transitions. In this study, the Ag-TiO2 samples annealed at 300–450 °C gave rise to anatase phase which shows an indirect band gap transition as expected. The value of constant, n is usually taken as 1/2 for allowed transition. However, for indirect and allowed transition as observed in anatase TiO2 film, n is considered here as 2 by taking into account of multi-phonon scattering using same approximate equation (1) as validated by others54. Figure 9a–c illustrate the transmittance characteristics of the as-deposited TiO2 and Ag-TiO2 samples before and post annealing at 300 °C and 450 °C respectively. Figure 9a shows high transmittance of around 80–90% in the visible range of 350–500 nm obtained from the as-deposited TiO2 sample prior to annealing that starts to decrease gradually above 550 nm giving an average value of 70% in NIR band. The rapid decay of the transmittance curve for all samples towards UV band represents the intrinsic absorption band edge of the material with cut-off wavelength at λ = 390 nm. Following annealing as depicted in Fig. 9b,c, the samples exhibit similar trend with a slight shift of the transmission peak but with a reduction of transmittance values, in particular for the samples having higher Ag-content, e.g. 0.28Ag and 0.40Ag, along with a shift of the absorption band edge towards shorter wavelength. The spectral response of the higher Ag-content samples also shows an additional strong absorption band that starts to form at longer wavelength, for example the 0.28-Ag-TiO2 sample producing an absorption peak at 500 nm following annealing at 300 °C. This effect is prominent at annealing temperature of 450 °C for all higher Ag-content samples that give rise to a strong absorption peak with larger shift towards longer wavelength and of reduced transmission. The maximum redshift was measured from the 0.40-Ag-TiO2 sample with absorption peak at 547 nm. A similar nature of shift of the transmittance peak and of the absorption edge were observed for all samples depending on Ag-contents that can be attributed to thermally induced diffusion and agglomeration of Ag nanoparticles acting as scattering centres. The increased absorption and redshift towards NIR band obtained from the high Ag-content TiO2 structure can be explained due to the combined effects of onset of the phase transition and formation of larger Ag clusters along with surface plasmon resonance originated from Ag agglomeration and its migration towards film surface56. Figure 10 shows the variation of bandgap (Eg) with annealing temperature for different Ag-content TiO2 samples. As expected, the band gap is increased in all samples following thermal annealing due to the shift of intrinsic absorption band edge towards short wavelength. It is noteworthy that an incorporation of Ag nanoparticles in TiO2 matrix causes a decrease in bandgap with and without thermal treatment compared to pure TiO2 structure, e.g., Eg from 3.1 eV in TiO2 to 2.8 eV in 0.40Ag-TiO2 sample at the as-deposited condition. This can be explained by charge transfer of type-d electron of Ag to the conduction band of TiO2, resulting in narrowing of bandgap as reported by others57. In effect, Ag nanoparticles act as recombination centre for electron trapping by introducing new electronic states within bandgap of TiO2. Thus the preliminary results have established the possibility of improvement of photocatalytic efficiency by reducing the band gap in anatase Ag-content TiO2 film at lower annealing temperature. Discussion The amorphous structure resulting from the deposition of compounds with highly directional bonds, such as in TiO2 thin films, has been attributed to the relatively high energy needed by the bonded atoms to rotate around a particular bond to satisfy crystal symmetry58. The energy required to re-arrange the Ti-O bonds in forming a crystalline structure, can be induced by soft thermal annealing. In this process, these bonds suffer a continuous reorganization during the transition, with the breaking and re-forming, to crystallize in anatase and eventually in the more stable rutile phase. Previous studies have shown that a relatively soft heat treatment (200–400 °C) to pure TiO2 films is enough to activate the transition from the amorphous to anatase phase135960. The crystallization temperature depends on the host material, synthesis method, grain size and the deposition conditions, whereas the transition had been identified by XRD and SEM techniques131460616263. According to some authors, metal cations added to the anatase phase, with valence band lower tan +3, or larger radii than Ti4+ ions occupy substitutional positions in the TiO2 matrix. The ultimate effect is an increase in oxygen vacancies in the TiO2 lattice to compensate the charge neutrality, thus promoting antase-to-rutile transformation in doped samples1264. However, such concept does not take into account of the diffusion and agglomeration processes of silver nanoparticles during the annealing treatment, as observed in this and other studies196566. In this work adapting cathodic arc technique, the anatase structure of films was obtained at 200 °C for pure TiO2, but the presence of Ag atoms increases the crystallization temperature, as detected by XRD and Raman spectroscopy. Thus, the amorphous-to-anatase transition temperature was found to be systematically delayed until it reached to 400 °C for the atomic ratio of 0.08, and to 600 °C for higher Ag concentrations. Frequently, silver is obtained in the oxide state when deposited by PVD and CVD techniques in reactive oxygen atmospheres2467, and for this reason the increase in the transition temperature from amorphous to anatase could be ascribed to the additional energy required to dissociate Ag-O bonds initially formed in the deposited films. Additionally, the lower chemical affinity of silver towards oxygen, as compared to titanium, also favours the reduction of silver to the metallic state during annealing, as it has been revealed by XPS and XRD analysis. Moreover, FESEM image analysis indicates that Ag atoms diffuse at higher annealing temperature and eventually nucleate forming large aggregates with lower surface energy, as observed by other authors68. The nucleation of silver aggregates is by itself another factor that may strongly affect the anatase transition due to their much larger size, e.g., mean grain size of several nm in annealed films at 200 °C when compared to the ionic radii of Ti and O atoms as 0.13 and 0.074 nm respectively. Therefore, it is reasonable to assume that the presence of Ag aggregates would slow down the re-arrangement of Ti-O bonds in the amorphous films to crystallize into the anatase structure. It is also found that an increase in Ag concentration tends to hinder the crystallization to higher temperatures, as indicated by XRD spectra of the 0.28 and 0.40 Ag samples, in which anatase phase forms only at 600 °C. On the other hand, the A-R phase transformation initiates between 700–1000 °C in pure TiO2 powders and films131726697071, while full rutile phase is usually detected at around 1000 °C. In this work, rutile phase is also clearly distinguished from anatase at 1000 °C by its characteristic vibrational bands. In case of TiO2 films with low Ag content (Ag below 2 at.%), some authors have observed the rutile phase at 750 °C24. In other studies, with lower Ag/Ti content (0.06) obtained by sol-gel, the A-R transition is found at temperatures close to 800 °C72. However, the samples produced in this study show an earlier onset of the transition to rutile which is initiated at lower temperature of 600 °C for the Ag atomic ratio of 0.08, with the rutile proportion in the film becoming higher as the Ag concentration increases. The thermally induced agglomeration of silver atoms may explain the promotion of rutile phase at lower temperature, since the A-R transition implies a contraction of the c-axis, with a reduction of the unit cell volume of around 8%12. The agglomeration of Ag and formation of lager clusters within TiO2 matrix will eventually constrain the volume available for the anatase lattice, thus disrupting the anatase phase to form a more stable and denser rutile microstructure. In addition, the presence of silver aggregates with different sizes noticeably affects the wetting properties and optical transmittance as discussed above. It is well known that the photocatalytic response in TiO2 is determined, among other factors, by photo-generation of electron-hole (e–h) pairs and their subsequent energy separation efficiency. According to the model proposed by Meng68, small size Ag clusters act as electron traps for photogenerated e–h carriers in the TiO2 film through a Schottky barrier effect, thus increasing the concentration of holes and, consequently, their surface energy. The ultimate effect is the absorption enhancement of –OH and O2− species leading to hydrophilicity of the film surface as depicted in Fig. 8. On the contrary, large size Ag nanoparticles that can be found in samples with higher Ag-content and/or annealed at T > 600 °C act as electronic recombination centres. In effect, this would reduce the separation efficiency of the e-h pairs and, therefore, the hydrophilic response of the films (Fig. 8b). In addition, other morphological properties such as grain size, surface roughness, texture, and even the amorphous→anatase→rutile transition would also contribute to the wetting properties of the film surface. In particular, the surface energy of anatase has been found to be lower than rutile12. This may explain the lower irradiation time (20 min) needed to reach the superhydrophilic state in the samples with low Ag content, when subjected to annealing at 400 °C that promotes anatase phase in accordance with the results obtained by other authors7374, though the films present faster response to UV irradiation. Similarly, larger size of Ag agglomerates and their diffusion towards film surface following annealing at 450 °C can be considered as the major physical mechanisms resulting in an additional absorption peak and its redshift towards NIR in high Ag content samples as observed from the transmittance spectra in Fig. 9. Finally, a qualitative description of the phase transition in Ag-TiO2 films is depicted schematically in Fig. 11 that demonstrates the nature of transformation of crystalline states within the Ag-TiO2 matrix including their interdependence on Ag atomic ratios and thermal annealing temperature, as evaluated in this interesting study. The faded zones comprise of a mixture of phases that could be found extending over a wide temperature range. It should be noted that the crystallization temperature of the different TiO2 phases presented in this study was taken as an estimated value since the thermal annealing was conducted for 1h each in step of 200 °C, and was increased up to 1000 °C as final step. The qualitative diagram clearly indicates an early onset of stable rutile phase at around 600 °C for higher concentration Ag-content TiO2 samples compared to lower Ag-content ones. This effect is envisaged to have an impact on achieving stable rutile phase in TiO2 films at lower processing temperature for photocatalytic and thin film device applications. Conclusions The influence of silver on phase transformation of TiO2 films had been thoroughly investigated by depositing Ag-TiO2 thin film structure on silicon substrate employing reactive pulsed cathodic arc technique and followed by thermal annealing up to 1000 °C for 1 hour. The surface morphology and crystal orientation of the Ag-TiO2 films had been evaluated using SEM, Raman and XRD analysis with an emphasis on the wetting properties and optical transmittance. In samples with high Ag:(Ti + Ag) atomic ratio of 0.28, Raman analysis shows characteristic bands of anatase at 600 °C, co-existing with small rutile peaks which eventually develop into well defined, with no overlapping, bands of rutile at 800 °C. XRD analysis has revealed the formation of (111) plane of crystalline silver in high Ag-content sample (>0.16) indicating favourable conditions for diffusion of Ag nanoparticles into amorphous TiO2 structure following thermal annealing and finally, their agglomeration in forming larger clusters that has an impact on their wetting property and optical absorption. TEM analysis has identified the Ag clusters of about 4.5 nm in size estimated from 0.28 Ag-content sample at 200 °C and its (111) plane with characteristic separation of 0.23 nm. With higher annealing temperature at 800 °C, the size of Ag clusters increases up to 70 nm as observed from SEM image analysis. The experimental results have demonstrated the dominant role of Ag concentration and its grain size in tailoring thermally induced phase transition of TiO2 films. The amorphous to anatase transition is found to be delayed until 600 °C in low Ag-content TiO2 films compared to 200 °C in the pure TiO2 films, whereas the rutile phase is, in fact, promoted at lower temperature with onset at 600 °C for higher Ag-content TiO2 films. This has established clearly the possibility of low temperature fabrication of TiO2 thin film structure to achieve stable rutile phase by incorporating Ag with precise control of its atomic concentration that would simultaneously (a) inhibit amorphous to anatase transition and (b) promote anatase to rutile transition at lower temperature range of 600 °C. These contrasting effects have been tentatively explained by the steric constraints imposed by diffusion and agglomeration of silver atoms in forming larger clusters following thermal annealing. In the first case, by hindering the diffusion process of the smaller titanium and oxygen ions to form anatase, whereas, in the second case, by a progressive reduction of the available space to maintain relatively high volume of the anatase unit cell, these two thermally induced processes would ultimately disrupt its anatase structure leading to formation of more stable and denser rutile phase. In addition, the study of the wetting property reveals that the presence of silver clusters in the TiO2 films renders their partial hydrophobic character to a superhydrophilic state, with a rapid response to the UV light, for low Ag content samples in its anatase phase, subjected to annealing at 200–400 °C. The transmittance characteristics of Ag-TiO2 coatings have exhibited the formation of additional absorption peak and its redshift towards near infrared in high Ag-content samples owing to large size of Ag agglomerates and surface plasmon resonance effect. The narrowing of band gap is observed in anatase Ag-content TiO2 films at lower annealing temperature showing promise in tailoring photocatalytic efficiency. The synergy of formation of rutile phase in TiO2 films at lower annealing temperature, its improved wetting properties and increased optical absorption at near infrared band by incorporation of silver nanoparticles into TiO2 matrix is envisaged to enhance the functionality of Ag-TiO2 thin films having potential for photocatalytic, antimicrobial, optical coatings and thin film IR sensor applications. Methods Silver containing TiO2 films (Ag-TiO2 samples) with different silver concentration have been deposited by pulsed cathodic arc on [100] silicon substrates using pure (99.99%) titanium and silver cathodes. The setup of pulsed cathodic arc system was described elsewhere7576. The cathodic arc technique allows the control of the composition by adjusting the pulse ratio on the Ag and Ti cathodes. The arc discharge was made in a reactive atmosphere, with an oxygen flow of 60 sccm and working pressure of 1 × 10−2 mbar. In order to obtain homogeneous films, the substrates were located at 12 cm from the cathodes and rotated with a frequency of 8 Hz by an MDRIVE 23 PLUS motor. The different samples, with varying Ag:Ti + Ag atomic ratio concentrations which were chosen as 0.08, 0.16, 0.28 and 0.40 respectively in trial run, were produced by changing the pulse ratio on the Ti and Ag cathodes as 38:2, 8:2, 4:2 and 2:2 respectively. The film thickness was around 100 nm in all samples, as measured with a DEKTAK 150 STYLUS profilometer. The film microstructure was analysed by scanning electron microscopy (FESEM NANOSEM 230), equipped with X-ray energy dispersion spectroscopy which was employed to estimate the Ag:(Ti + Ag) atomic ratio concentration. Following deposition, the samples were annealed in ambient atmosphere at 200, 400, 600, 800 and 1000 °C in step for 1 hour each, respectively. Raman spectra were recorded before and after thermal annealing using an ENWAVE EZraman-N spectrometer provided with a LEICA DM 300 microscope. The spectra were generated using a diode laser at 532 nm and power of 350mW. In addition, XRD analysis had been performed for all the samples, before and after annealing, by X-ray diffractometry (D8 BRUKER ADVANCED with CuKα radiation) in the 2θ range, from 20° to 80° with 0.5° incident grazing angle. XPS measurements were performed in an ultrahigh vacuum, with a base pressure of 1 × 10−10 mbar, PHOIBOS 100 ESCA/Auger spectrometer with a MgKα anode (1253.6 eV). For data analysis, the spectra were subjected to the Shirley background subtraction formalism. In order to analyze the Ag 3d core levels in the as-deposited samples, the binding energy scale was calibrated with respect to the C 1s core level peak at 285.0 eV. For the annealed samples, the spectra were collected before and after a sequence of etching treatments of about 60 minutes by Ar+ bombardment. The etching rate of the sample was 0.12 nm per minute. The morphological studies of selected Ag-TiO2 samples before and after annealing at 800 °C were conducted using atomic force microscopy (AFM, Multimode Veeco) in the tapping mode77. AFM image analysis was performed with Gwyddion program applying a plane background subtraction filter. The cross section images of the thin film samples were also investigated by high resolution scanning electron microscopy (HRSEM), NANOSEM 230 FEI. Furthermore, high resolution TEM (HRTEM) images were evaluated for samples annealed at 200 °C, using a FEI TECNAI T30 microscope. The ultra-thin foils of around 25 nm were prepared by Focus Ion Beam (FIB) HELIOS 600 dual system for TEM analysis. Finally, in order to investigate the effect of silver on the wetting properties of the films, contact angle measurements were carried out by illuminating the film surface with UV radiation (Xe lamp of 125 W) for a time period ranging from 0 up to140 min. After UV irradiation, distilled water droplets (1 μl) were produced on the samples to wet the sample surface, and the contact angle was collected with a CCD CAM 100 (KSV Instruments). The optical transmission property of TiO2 films was studied by depositing the thin film on borosilicate crown glass substrates and the spectral characteristics of the samples were evaluated using a SOLIDSPEC 3700 UV-visible-NIR spectrometer to calculate the transmittance and the energy band gap respectively. Additional Information How to cite this article: Mosquera, A. A. et al. Effect of silver on the phase transition and wettability of titanium oxide films. Sci. Rep. 6, 32171; doi: 10.1038/srep32171 (2016). This work was supported by the State Secretary of Research, Development and Innovation of Spain through the FUNCOAT project, within the program CONSOLIDER INGENIO 2010 (ref. CSD2008-00023). Author Contributions A.A.M., J.M.A., V.N., D.B. and J.L.E. wrote the article and analysed the experimental data. The experimental work has been performed by A.A.M. and V.N. All the authors participated equally in the discussion, and the article was reviewed by A.A.M., J.M.A., V.N., D.B. and J.L.E. Figure 1 Raman spectra of the Ag-TiO2 films as a function of annealing temperature with silver concentration as: (a) 0.08–0.16Ag and (b) 0.28–0.40Ag. The pure TiO2 Raman spectrum is inserted in both graphs as reference. Anatase and Rutile bands are labelled as A and R respectively. Figure 2 XRD patterns of pure TiO2 and Ag containing TiO2 thin films with silver concentration as: (a) 0.08–016Ag and (b) 0.28–0.40Ag annealed at different temperatures. The pure TiO2 XRD pattern is inserted in both graphs as reference. Anatase, Rutile and silver phases are labelled as A, R and S respectively. Figure 3 HRTEM image of silver nanoparticles in the 0.28Ag-TiO2 film annealed at 200 °C and of 1 hour duration, shows the (111) crystallographic planes. Figure 4 SEM images of the morphology of the 0.16Ag-TiO2 samples: (a) As-deposited and (b–e) Annealed at 200, 400, 600 and 800 °C respectively. The arrows indicate silver particles. Figure 5 XPS Analysis of Ag-3d core level spectra of the 0.28 Ag-TiO2 films (a) As-deposited, and (b,c) Annealed at 300 °C and 400 °C respectively for 1 hour. The annealed samples have been analysed after 60 min etching. Figure 6 Topographic AFM images and height profile of the amorphous as-deposited films: (a) Pure TiO2 and (b) 0.16Ag-TiO2. Figure 7 Topographic AFM images of the annealed films at 800 °C: (a) Pure TiO2, with height profile of the atomic terraces and (b) 0.16Ag-TiO2. Figure 8 Evolution of the wetting angle on Ag-TiO2 films under UV illumination: (a) 0.08Ag-TiO2 and (b) 0.28Ag-TiO2. Figure 9 Optical transmittance spectra of TiO2-Ag thin film coatings deposited on glass: (a) As-deposited samples without annealing, (b) Annealed at 300 °C and (c) Annealed at 450 °C respectively for 1 hour. Figure 10 Variation of the energy bandgap (eV) versus annealing temperature for different concentration of silver content in TiO2 thin film structure. Figure 11 Phase diagram of the Ag-TiO2 films with different silver content expressed in atomic percent Ag:(Ti + Ag). The phase diagram was obtained based on both Raman and XRD data. Table 1 Silver (Ag) grain size (nm) in the TiO2 samples annealed at different temperatures. Samples Temperature (°C) 200 400 600 800 1000 0.28Ag-TiO2 41.4 47.7 48.1 67.5 93.4 0.40Ag-TiO2 45.9 55.0 63.8 42.8 66.9 ==== Refs Diebold U. The surface science of titanium dioxide . Surface Science Reports 48 , 53 –229 (2003 ). Kuznetsova I. N. , Blaskov V. , Stambolova I. , Znaidi L. & Kanaev A. TiO2 pure phase brookite with preferred orientation, synthesized as a spin-coated film . Materials Letters 59 , 3820 –3823 (2005 ). Di Paola A. , Addamo M. , Bellardita M. , Cazzanelli E. & Palmisano L. Preparation of photocatalytic brookite thin films . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3245010.1038/srep32450ArticleRising Mediterranean Sea Surface Temperatures Amplify Extreme Summer Precipitation in Central Europe Volosciuk Claudia a1Maraun Douglas 12Semenov Vladimir A. 134Tilinina Natalia 5Gulev Sergey K. 56Latif Mojib 171 GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany2 Wegener Center for Climate and Global Change, University of Graz, Austria3 A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russia4 Institute of Geography, Russian Academy of Sciences, Moscow, Russia5 P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia6 Lomonosov Moscow State University, Moscow, Russia7 Cluster of Excellence “The Future Ocean”, Christian-Albrechts-Universität zu Kiel, Kiel, Germanya cvolosciuk@geomar.de30 08 2016 2016 6 3245014 02 2016 05 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The beginning of the 21st century was marked by a number of severe summer floods in Central Europe associated with extreme precipitation (e.g., Elbe 2002, Oder 2010 and Danube 2013). Extratropical storms, known as Vb-cyclones, cause summer extreme precipitation events over Central Europe and can thus lead to such floodings. Vb-cyclones develop over the Mediterranean Sea, which itself strongly warmed during recent decades. Here we investigate the influence of increased Mediterranean Sea surface temperature (SST) on extreme precipitation events in Central Europe. To this end, we carry out atmosphere model simulations forced by average Mediterranean SSTs during 1970–1999 and 2000–2012. Extreme precipitation events occurring on average every 20 summers in the warmer-SST-simulation (2000–2012) amplify along the Vb-cyclone track compared to those in the colder-SST-simulation (1970–1999), on average by 17% in Central Europe. The largest increase is located southeast of maximum precipitation for both simulated heavy events and historical Vb-events. The responsible physical mechanism is increased evaporation from and enhanced atmospheric moisture content over the Mediterranean Sea. The excess in precipitable water is transported from the Mediterranean Sea to Central Europe causing stronger precipitation extremes over that region. Our findings suggest that Mediterranean Sea surface warming amplifies Central European precipitation extremes. ==== Body Observational records show no clear trend in the intensity of summertime heavy rainfall in Central Europe1234. Yet, climate models generally project an increase of Central European summer precipitation extremes, even though mean precipitation is projected to decrease56789. These projected thermodynamic changes are a regional expression of global changes in the hydrological cycle that are primarily caused by increasing saturation vapour pressure of the warming atmosphere1011. Flood producing summer precipitation extremes in Central Europe are often associated with Vb-cyclones121314, southerly west-east cyclone tracks and cut-off lows15. Vb-cyclones are typically generated over the Gulf of Genoa, travel northeastward around the Alps and can transport large amounts of moisture towards Central Europe. Persistent cut-off lows over the northern central Mediterranean can cause precipitation extremes in Central Europe similar to those produced by Vb-cyclones. Thus, the Mediterranean Sea serves as a major moisture source for Central European heavy-precipitation events and associated flooding1617. The Mediterranean is itself a hotspot of global warming18. Its surface has continuously warmed since the mid–1970s, especially during summer (June, July, August; JJA). In fact, the beginning of the 21st century (2000–2012) featured the highest SSTs in the Mediterranean Sea during the instrumental record19 (Fig. 1a). Moreover, the increase from the 1970–1999 to the 2000–2012 period in Mediterranean SSTs (annual mean: 0.62 °C, JJA mean: 0.86 °C) is considerably stronger compared to that of the global oceans (annual mean: 0.15 °C, JJA mean: 0.19 °C). These trends are projected (by the coupled model intercomparison project phase 5; CMIP5-ensemble) to continue throughout the 21st century, with summertime SSTs reaching a warming of more than 2 °C by the end of the 21st century (2071–2098) compared to 1980–200520. Higher Mediterranean SSTs will in turn lead to enhanced evaporation and atmospheric moisture transport21, with potential impacts on Central European precipitation. For instance, high Mediterranean SSTs contributed to the extreme precipitation that led to the Elbe-flooding in 200216. Yet, the impact of sea surface warming on such heavy precipitation events cannot be studied in detail based on observations alone due to the relatively short period of recent high SSTs and given the rareness of extreme events. Summer precipitation extremes in Central Europe may be amplified due to changes in convective storm dynamics (induced by, e.g., changes in vertical atmospheric profiles) or changes in cyclone-related precipitation. For instance, there are two major factors that may contribute to the intensification of cyclone-related summer precipitation extremes in Central Europe: changes in cyclone occurrence or pathway (dynamic changes) and changes in the amount of moisture carried by individual cyclones (thermodynamic changes). Yet, confidence in the thermodynamic aspects of climate change is generally higher than in dynamic changes22. The Mediterranean storm track in summer has intensified during recent decades23. Climate models do not simulate significant trends in the number of summer cyclones in the Mediterranean region however24. Considering Vb-cyclones, no trends have been observed to date in their occurrence25, and climate model projections even suggest a slight decrease of Vb-cyclone occurrence1426. Nevertheless, the amount of precipitation associated with Vb-cyclones is projected to increase1426, raising the question of where the additional precipitable water originates. Methods In this study, by conducting sensitivity experiments with the atmosphere general circulation model (AGCM) ECHAM527, we aim to disentangle the impacts of Mediterranean Sea warming on Central European precipitation extremes from other effects in the background climate. To this end, we carry out experiments that are identical except for SST and sea ice concentration (SIC). The control experiment is forced globally with monthly climatological fields of 1970–1999 SST and SIC. In the warm Mediterranean experiment (Medwarm), we employ the warmer 2000–2012 SST climatology only in the Mediterranean and Black Seas (see Fig. 1b for the difference in JJA SST forcing climatology). In the global warm experiment (Globwarm), the AGCM is forced globally with monthly climatological fields of 2000–2012 SST and SIC. For each experiment we computed a 40-member ensemble of one year. The model is integrated at a relatively high horizontal resolution for a global atmosphere model of T159 (equivalent to approximately 0.75° × 0.75° lat/lon) and with 31 vertical levels. Forcing conditions for all three experiments were taken from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST)19. Radiative and greenhouse gas forcings are fixed to present-day levels. We analyse summer precipitation extremes and the associated atmospheric mechanisms in the three model experiments. We define heavy-precipitation events as days where daily precipitation exceeds the 95th percentile of all summer (JJA) days (wet and dry). To have the same sample size for all simulations we individually choose the 95th percentile of all summer days as threshold in each experiment, i.e., in all experiments the 5% of all summer days with the heaviest precipitation are analysed. Differences between the 40-year-long experiments are compared for (i) climatological seasonal summer means over all summer days (wet and dry), and (ii) mean heavy-precipitation events as represented by the mean threshold excess (i.e. the mean of the 5% heaviest precipitation events within 40 summers). We considered the mean threshold excess for comparison, as extreme values do not follow a normal distribution - neither block maxima nor threshold exceedances. Given the large number of excesses, the Central Limit Theorem applies, and we can thus assume a normal sampling distribution for the arithmetic mean28. This assumption implies that the sample means can be tested for differences employing a t-test28. We apply a two-sided independent samples t-test with the chosen significance levels being 90% for heavy-precipitation events and 95% for climatological summer means. We model daily precipitation extremes based on heavy-precipitation events (i.e., threshold excesses of the 95th daily precipitation percentile) with the generalised Pareto (GP) family of distributions29. The GP–parameters are estimated by the maximum likelihood method. Summer extreme events are defined by the 20-season return level of daily precipitation (RL20S) in JJA. For example, the RL20S for JJA is exceeded in any JJA season with the probability 1/20, i.e., on average every 20th JJA season. For cyclone identification and tracking we use the numerical algorithm of the P.P. Shirshov institute3031. The algorithm is applied to 6-hourly sea level pressure (SLP) fields from the model runs. The post-processing includes filtering out cyclones with lifetimes shorter than 1 day and reaching minimum SLP over the elevated areas (>1500 m). For mapping cyclone numbers and frequencies, 6-hourly trajectories are interpolated linearly onto 10-minute time steps in order to avoid systematic and random biases30. Composites of relevant variables are built on days of area-aggregated heavy-precipitation events over the study region located at 15–22°E, 46–51°N (red box in Fig. 2). To identify the synoptic pattern for flood-causing precipitation extremes in Central Europe we do not limit the analysis to single circulation types (e.g., Vb-cyclones). Instead, we apply an event-based approach associating cyclones with extreme precipitation, similar to Pfahl and Wernli, 201232. We analyse composites of cyclone tracks passing through the study region (i.e., the cyclone centre is at least one 6-hourly time step over the study region during a heavy-precipitation event). While there is a risk that our approach might miss some cyclones causing heavy-precipitation (e.g., cyclones propagating near the study region) this methodology ensures that we exclusively consider cyclones that definitely affect precipitation in the study region. Results In both the control and the Medwarm experiments, climatological summer mean precipitation over Central Europe (5–27°E, 42–56°N) is 2 mm/day. The Central European mean climatological summer cyclone track density is 27 cyclones per summer in both experiments (see corresponding patterns in Supplementary Figs S1–S2). The climatological summer patterns for both precipitation (compared to the E-OBS gridded observational dataset33) and cyclone track densities (compared to ERA-Interim reanalysis2334) are well represented by our model (see Supplementary Information for a detailed evaluation). The Central European average of 20-summer return levels (RL20S) is 53 mm/day in the control, 55 mm/day in the Medwarm and 57 mm/day in the Globwarm experiment (see corresponding patterns in Fig. 2). The locations of precipitation maxima that led to recent floods (e.g., eastern Austria, eastern Germany, southern Poland, Slovakia; see Supplementary Fig. S3) show high RL20S in all three experiments (Fig. 2), which gives us confidence in simulated extremes related to such synoptic situations. In comparison with the control experiment, summer RL20S are amplified in Central Europe along the Vb-cyclone track in both sensitivity experiments (Medwarm and Globwarm; Fig. 3), indicating stronger precipitation extremes even though simulated changes in summer-mean precipitation are much lower (<1 mm/day, Supplementary Fig. S1). The highest increase in extreme precipitation (Medwarm: 61.0%, Globwarm: 62.5%) is simulated in the Carpathian Basin; the largest decrease (Medwarm: −37.2%, Globwarm: −42.1%) in northeastern Germany. Note that the highest increase is not co-located with the region of maximum precipitation on heavy events (for precipitation composites on heavy-precipitation events see Supplementary Fig. S3). The intensification of RL20S along the Vb-cyclone track can be attributed to the warmer Mediterranean Sea as it appears not only in the Globwarm, but also in the Medwarm experiment. Hence, we focus in the following on comparisons between the Medwarm and the control experiments. We analyse the summer season in detail as a strong intensification of precipitation extremes with a warming Mediterranean is found. In spring and autumn, however, extremes are decreasing over most of Central Europe and in regions where extremes are amplified the response is weaker than in the summer season (Supplementary Fig. S4). To disentangle synoptic-scale events leading to severe flooding from small scale convective events with local impacts we aggregated precipitation over the study region (red box in Figs 2 and 3a). The summer RL20S averaged over this area amounts to 18.7 mm/day in the control and to 22.0 mm/day in the Medwarm experiment. To infer mechanisms for this increase by 17.4% we further analyse composites of relevant variables during heavy-precipitation days. A considerable portion of heavy-precipitation events in both the control and the Medwarm experiments is associated with the passage of cyclones that originate over the Mediterranean Sea (e.g., Vb-cyclones). This is clearly indicated by track densities of cyclones that passed through the study region on event days (Fig. 4). In both experiments ~70% of the analysed heavy-precipitation events are associated with a cyclone whereof ~50% are Vb-cyclones (identified according to Supplementary Fig. S5). No significant differences in cyclone track densities and SLP composites (Supplementary Fig. S6) are found between the two experiments. Hence, neither changes in cyclone pathways or intensities nor changes in the dominant synoptic pattern can explain the simulated strengthening of extreme precipitation (note however, that we found evidence for slightly reduced cyclone dynamics in the Medwarm experiment compared to the control experiment, Supplementary Fig. S7). Precipitable water (Fig. 5a, time lag: Supplementary Fig. S8) and moisture convergence (Fig. 5b, time lag: Supplementary Fig. S9) in the control experiment are anomalously high over Central Europe during heavy-precipitation events and on the day prior to such events. The western Mediterranean Sea is identified as a major moisture source region for heavy-precipitation in the study area by anomalous moisture divergence, moisture transport (Fig. 5b, time lag: Supplementary Fig. S9) and evaporation (Fig. 5c, time lag: Supplementary Fig. S10) on the day of and prior to the event. Differences between heavy-precipitation-event composites of variables related to the hydrometeorological cycle in the Medwarm and the control experiments (Fig. 5d–f) suggest that higher Mediterranean SSTs, by further moistening the atmosphere, amplify extreme precipitation. In particular, climatological mean higher precipitable water content in the Medwarm experiment over the Mediterranean Sea (by 5.5% on average, Supplementary Fig. S8) is further increased on heavy-precipitation days (Fig. 5d) and the preceding day (Supplementary Fig. S8). It further extends into Central Europe where the precipitable water content is then amplified by 3–5%. This slightly exceeds the Clausius-Clapeyron rate of 7% increased saturation vapour pressure per degree of warming35 (see Supplementary Fig. S11). However, the higher precipitable water content is not yet sufficient to explain the intensification of heavy-precipitation events (threshold excesses) by 12.2%. Moisture convergence and transport (Fig. 5e) indicate that the extra moisture is transported from the Mediterranean Sea into Central Europe in the Medwarm experiment. Averaged over the study region moisture convergence is amplified by 16.2% which explains the precipitation intensification beyond the higher atmospheric moisture content (note that changes related to dynamics which may additionally contribute to amplified moisture convergence are beyond the scope of this study however). The western Mediterranean Sea is identified as the major moisture source region; this is also true for the additional moisture in Medwarm which is supported by the change in evaporation (Fig. 5f, time lag: Supplementary Fig. S10). The latter is amplified over the whole western Mediterranean basin synchronised with the heavy-precipitation events (western Mediterranean average: 19.9%), and also on the two preceding days, thereby strongly exceeding the climatological summer mean increase (Supplementary Fig. S10). The similarity of evaporation over land between the experiments suggests that moisture recycling is not relevant for the intensified extreme precipitation. Discussion Our results show that the higher Mediterranean SSTs during recent decades amplify the magnitude of extreme precipitation events associated with cyclones that originate over the Mediterranean Sea (including those of Vb-type). The largest increase is located southeast of the precipitation maximum for both simulated heavy events and historical Vb-events. For intensified extreme precipitation changes in transients passing to Central Europe, moisture recycling or the dominant synoptic pattern are not required. The heavier precipitation events are likely related to thermodynamic changes: the stronger diabatic heating source along with increased water vapor content, intensifies moisture transport from the western Mediterranean Sea to Central Europe during heavy-precipitation events. These findings are in line with previous studies on thermodynamic changes2136. During heavy-precipitation events the Central European region is supplied with moisture from the Mediterranean Sea which leads to precipitation increases beyond amplified saturation vapour pressure (Clausius-Clapeyron rate). Our atmosphere-only experiments do not represent atmosphere-ocean feedbacks. We rather investigate the atmospheric response to assumed externally forced long-term SST changes. Our results are subject to the chosen atmospheric general circulation model realistically simulating the underlying processes. Yet, the major effect of increasing SSTs was thermodynamic, for which confidence is generally high compared to dynamical changes22. Dynamical changes were - in our model - less important for the strong precipitation response. Our study is by construction not affected by long-term internal climate variability: such macroscopic initial conditions uncertainty37 is caused by ocean circulation - we prescribed SSTs as climatological averages. Internal atmospheric variability is crucial to sample the distribution of extreme events. The atmosphere has essentially forgotten its initial state after a few months, such that in each year of our 40-year simulations - note that the SSTs are identical for each year - we sample from an identical climate distribution as in a 40-member ensemble of 1-year simulations. For each experiment we therefore have 184 excesses of the 95th percentile, sampled from an essentially stationary distribution. This sample is sufficient for a reasonable estimate of 20-season return levels38. We found a highly significant amplification of area-averaged heavy-precipitation events (excesses of the 95th percentile of all days in the respective experiment) with a warmer Mediterranean by 12.2%. With unchanged variance in both samples an increase by only 5.3% would be sufficient for a significant response at the 95% significance level, which gives us confidence in the simulated intensification of precipitation. Amplified Mediterranean SSTs are both forced anthropogenically20 and related to internal decadal-scale variability (e.g., Atlantic Multidecadal Oscillation)39. Increased subsidence in the descending branch of the Hadley circulation, associated with anticyclonic conditions over Central Europe may also contribute to warm anomalies in the Mediterranean Sea, and suppress cyclonic activity40. Yet, climate change scenarios show only slight reductions in Central European summer cyclone track densities24 and Vb-cyclones14, suggesting that such cyclones will most likely still be relevant in a future climate. Our atmosphere model sensitivity experiment suggests that the projected intensification of precipitation related to Vb-cyclones1426 can be attributed to the rise in Mediterranean SSTs which is itself projected to continue throughout the 21st century20. Additional Information How to cite this article: Volosciuk, C. et al. Rising Mediterranean Sea Surface Temperatures Amplify Extreme Summer Precipitation in Central Europe. Sci. Rep. 6, 32450; doi: 10.1038/srep32450 (2016). Supplementary Material Supplementary Information The authors acknowledge help with data analysis from R. Pilch. Data analysis was carried out with R, using the ismev, fields, ncdf and aspace packages. Simulations were run at the North-German Supercomputing Alliance (HLRN). This study was funded by the EUREX project of the Helmholtz Association (HRJRG-308). N. Tilinina and S.K. Gulev benefited from the support of the Russian Science Foundation (grant 14-50-00095). V.A. Semenov was also supported by Russian Foundation for Basic Research (14-05-00518) and Russian Science Foundation (grant 14-17-00700). Author Contributions C.V. and D.M. had the idea for the analysis, V.A.S. and M.L. designed the model sensitivity experiment. V.A.S. performed the simulations. C.V. performed the analysis, with support from D.M., V.A.S., N.T. and S.K.G. All authors discussed the results and commented on the manuscript. Figure 1 Observed Mediterranean summer SSTs. (a) Time series of JJA mean (°C). Area average over 5°W–42°E and 30°N–48°N from HadISST19, OISST41 and ERA-Interim34; (b) Significant difference (based on a two-sided independent samples t-test at the 95% significance level) in JJA mean SST patterns (°C) between the periods 2000–2012 (forcing climatology of warm Mediterranean (Medwarm) experiment) and 1970–1999 (forcing climatology of control experiment) from HadISST19. Map created with R version 3.2.3 (www.r-project.org). Figure 2 20-summer return levels in model experiments. (a) control, (b) Medwarm, and (c) Globwarm. Red box denotes study region for area average and further analyses (15–22°E, 46–51°N). Maps created with R version 3.2.3 (www.r-project.org). Figure 3 Increase in 20-summer return levels. (a) Medwarm, and (b) Globwarm experiment compared to control experiment. Red box denotes study region for area average and further analyses (15–22°E, 46–51°N). Increase of mean threshold excess (beyond 95th percentile of all summer days in the respective experiment) of box average (control: 12.3 mm/day, Medwarm: 13.8 mm/day) is 12.2% and highly significant (p-value < 0.0005). Maps created with R version 3.2.3 (www.r-project.org). Figure 4 Heavy precipitation causing cyclones. Track density of cyclones that pass through the study region (15–22°E, 46–51°N; red box in Fig. 2) on days where daily precipitation aggregated over that area exceeds the 95th percentile of all summer days in the respective experiment. Counts of cyclone centres that pass within 500 km of a grid point. Unit: Cyclones per summer (JJA). (a) Track density in control; (b) Track density in Medwarm. Maps created with R version 3.2.3 (www.r-project.org). Figure 5 Variables related to the hydrometeorological cycle during heavy-precipitation events. Heavy-precipitation events are days where daily precipitation aggregated over the study region (15–22°E, 46–51°N; red box in Fig. 2) exceeds the 95th percentile of all summer days in the respective experiment. (a–c) Composite anomalies in control experiment (relative to climatology) and (d–f) significant differences (based on a two-sided independent samples t-test at the 90% significance level) between composites in Medwarm and control: (a,d) Column integrated precipitable water (kg m−2); (b,e) vertically integrated moisture convergence (10−5 kg m−2 s−1) and vertically integrated moisture transport as vectors (every fifth vector is plotted), vector length is (b) 50 kg m−1 s−1 per degree lon/lat and (e) 10 kg m−1 s−1 per degree lon/lat; (c,f) evaporation (mm d−1). Maps created with R version 3.2.3 (www.r-project.org). ==== Refs Moberg A. & Jones P. D. Trends in indices for extremes in daily temperature and precipitation in Central and Western Europe, 1901-99 . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3183410.1038/srep31834ArticleEmergence of metapopulations and echo chambers in mobile agents Starnini Michele a1Frasca Mattia b2Baronchelli Andrea c31 Departament de Física Fonamental, Universitat de Barcelona, Martí i Franquès 1, 08028 Barcelona, Spain2 Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, Viale A. Doria 6, 95125 Catania, Italy3 Department of Mathematics, City University London, London EC1V 0HB, UKa michele.starnini@ub.edub mattia.frasca@dieei.unict.itc Andrea.Baronchelli.1@city.ac.uk30 08 2016 2016 6 3183419 04 2016 27 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Multi-agent models often describe populations segregated either in the physical space, i.e. subdivided in metapopulations, or in the ecology of opinions, i.e. partitioned in echo chambers. Here we show how both kinds of segregation can emerge from the interplay between homophily and social influence in a simple model of mobile agents endowed with a continuous opinion variable. In the model, physical proximity determines a progressive convergence of opinions but differing opinions result in agents moving away from each others. This feedback between mobility and social dynamics determines the onset of a stable dynamical metapopulation scenario where physically separated groups of like-minded individuals interact with each other through the exchange of agents. The further introduction of confirmation bias in social interactions, defined as the tendency of an individual to favor opinions that match his own, leads to the emergence of echo chambers where different opinions coexist also within the same group. We believe that the model may be of interest to researchers investigating the origin of segregation in the offline and online world. ==== Body Metapopulation models were first introduced in ecology and are nowadays widely used for the study of a large variety of phenomena, ranging from epidemic spreading to general social phenomena1234. They describe agents, possibly of different species, that diffuse stochastically on the vertices of a network and interact among them upon contact on the same vertex, whose occupancy is not limited (hence the term ‘bosonic’ often used to describe these models5). Recently, attention has been devoted to understand how different features of the metapopulation network, fixed during the dynamics of the process, affect the behavior of the system56. However, less attention has been devoted to describe how metapopulation structures emerge in absence of obvious environmental factors. How does a population end up into many segregated subgroups? The pioneering work of Schelling showed that no strong incentives are needed at a microscopic level for segregation to occur. Specifically, it showed that individual weak preferences to be surrounded by similar others are sufficient for the emergence of spatially segregated subpopulations, and no strong desire to avoid different others is needed78. Further studies confirmed this picture, showing that even a population of individuals who actively seek diversity can result into segregation91011. All of these models describe individuals that occupy the nodes of a lattice or network and are endowed with a visible trait that rules their interactions (e.g., skin color). They address the question of how different microscopic interaction rules impact the spatial distribution of these individuals. Crucially, the visible trait is modeled as a fixed and immutable characteristic of the individuals. In this paper, we relax the assumption of a fixed trait of the individuals and focus on the interplay between spatial mobility and opinion dynamics. We consider mobile agents characterized by a continuous variable, or “opinion”, that evolves in time depending on the microscopic interactions between individuals. The model we propose incorporatesMobility: Individuals move in a two dimensional space; Homophily: Individuals have a tendency to interact more with others who share their opinion; Social Influence: Interactions between individuals tend to increase their similarity. (Here we consider an operative definition of ‘social influence’, see e.g., refs 12 and 13). These three elements have been considered by a number of models, but the interplay between them has received less attention. For example, the question of why homophily and social influence do not necessarily yield social uniformity motivated the well-known Axelrod model of dissemination of culture1214, and models based on mobile interacting agents have been used to study such phenomena as epidemic spreading15, social cooperation16 and consensus17. Here, we consider the mobility scheme introduced in refs 18 and 19, which reproduces empirical data on human face-to-face interactions in social gatherings. However, while ref. 18 considers individuals characterized by a quenched “attractiveness” ruling the duration of their interactions, here the role of attractiveness is played by the status or opinion of individuals with respect to the other agents, that is, by a dynamic variable. Individuals tend to become more similar to the agents surrounding them and have a higher probability of moving away from dissimilar peers. We show that for certain values of the parameters the dynamics of the model yields the emergence of a metapopulation structure, i.e. physically segregated groups of individuals sharing similar opinions, that yet interact with each other through the exchange of agents. Finally, we address more in detail the relation between the segregation in the physical and opinion spaces. We specify further the role of homophily by introducing a confirmation bias of the agents, i.e. a tendency to acquire or evaluate new information in a way that confirms one’s current opinion and avoids contradiction with prior beliefs202122. Following a consolidated line of modelling in the context of continuous-variable models232425, we model confirmation bias as a bounded confidence between agents. This assumption reflects the idea that individuals will not interact with others whose opinion is too dissimilar from their own, and corresponds to a step-function description of the confirmation bias. The introduction of bounded confidence leads to the emergence of ‘echo chambers’ of agents that co-exist within the same group but do not influence each other, thus breaking the coupling between spatial segregation and polarization in the space of opinions. Model Definition The model is defined as follows. N individuals, initially randomly distributed in a square box of linear size L (corresponding to a density ρ = N/L2), perform a random walk of fixed step length v ⋅ δt and interact with the agents they find within a certain distance d. For the rest of the paper, without loss of generality, we fix δt = 1. The position of agent i at time t is indicated as (xi(t), yi(t)). Each individual i is characterized by a dynamical state variable si(t) ∈ [0, 1] representing his opinion, whose initial value si(0) is randomly extracted from a uniform and bounded distribution F(s) within the interval s ∈ [0, 1]. The si variable is defined in an opinion space with periodic boundary conditions, so that the difference between two states si and sj is always taken by modulo 1. Upon interaction, individuals modify their status seeking a local consensus with their neighbors. At each time t the status of each agent i, si(t), is updated as where is the set of neighbors of agent i, i.e., , and K is the coupling constant regulating the strength of the social influence they experience. However, individuals may also change autonomously their status. At each time step t, each individual has a very small probability R to reset his status si(t) to a new value, randomly extracted from the distribution F(s). The reset rate R introduces noise in the model and accounts for external factors or exogenous sources of information that can influence the opinion of the individuals. Homophily is modeled through the probability that an individual will continue the interaction with his neighbors or not. If an individual shares a similar opinion with his neighbors he will probably remain with them, otherwise he will walk away. Thus, the walking probability pi(t) of the agent i at time t is proportional to the difference between his status si(t) and the status of his most similar neighbor, where, as in Eq. (1), the difference between the states is taken modulo 1 to model an opinion space with periodic boundary conditions. Thus, each agent performs a step of length v in a random direction with probability pi(t) or maintains his position with probability 1 − pi(t). Isolated agents have a walking probability pi(t) = 1. Thus, heterogeneous groups are more fragile as individuals will tend to abandon them. Conversely, groups whose individuals experience a strong consensus will tend to persist in time with stable status and position. Results The model dynamics is fully characterized by four parameters: the collision rate pc, given by the product between the density ρ and the interaction area πd2, that is pc = πd2ρ, the velocity of agents v, the coupling constant K, and the reset rate R. The results presented here are obtained by numerical simulations of the model, see Methods. Group formation The microscopic rules described above introduce a positive feedback between mobility and opinion dynamics: Individuals can reach a local consensus based on proximity in the physical space, Eq. (1), and the achievement of a local consensus favors the persistence of that proximity, Eq. (2). As a consequence, in general the system reaches a quasi-stationary regime characterized by the presence of metastable groups of individuals. However, two events can alter the equilibrium of a group and change its composition and/or spatial properties, namely the arrival of a new individual and the spontaneous change of opinion by an agent. In the first case, either the newcomer’s opinion is close to the group’s local consensus and he will settle within the group with high probability, or he will leave, potentially having weakened the group by causing part of its members to shift their opinions - a scenario that may undermine or destroy the existing group. The second case is equivalent to the first, with the newly re-set agent that may remain in the group or leave it. This dynamic interplay between the processes of group formation and group fragmentation introduces a rich phenomenology which can be understood in light of two quantities: the average fraction of moving agents, 〈Nm〉, and the average size of the groups, 〈S〉, defined as where Nm(t) is the number of isolated and moving agents at time t, Ni(t) is the number of individuals forming group i at time t (see Methods), and is the set of groups at time t. Figure 1(A) shows the average fraction of moving agents 〈Nm〉 and the average groups size 〈S〉 as a function of the collision rate pc. For very small collision rates pc ≪ 1 the system is formed only by isolated agents and small groups, for very large collision rates pc ≫ 1 the network formed by the agents percolates, and a single group spans a finite fraction of the system, while for a large range of intermediate values of the collision rate a regime with several groups of different sizes and few isolated agents moving from one group to another emerges. This regime reveals the onset of a metapopulation structure which we further characterize in the next Section. The average number of moving agents 〈Nm〉 is inversely proportional to the collision rate, (inset, dashed line). This observation is in agreement with the hypothesis that the average number of collisions is constant and it does not depend on the collision rate pc, being regulated only by the probability that an individual leaves spontaneously a group as determined by K and R, so that 〈Nm〉 is simply proportional to the expected collision time . The velocity of agents, v, appears to have a small effect on the number of moving agents 〈Nm〉 but it is positively correlated with the average group size 〈S〉, large v values leading to significantly larger groups (Fig. 1B). Indeed, large values of v favor the mixing of the system, triggering a sort of rich-get-richer dynamics for the groups where the probability for a new individual to join a group is simply proportional to its size. On the contrary, small values of v promote the stability of existent groups, as the probability for a walking individual to re-join the group he just left is high. The average fraction of moving agents 〈Nm〉 and the average groups size 〈S〉 show strong dependence on the strength of social influence K (Fig. 1C). The larger the value of K, the smaller the number of interactions required before a moving agent reaches a local consensus within some group, so the number of moving individuals 〈Nm〉 decreases with K (with a functional form compatible with power law, 〈Nm(K)〉 ~ Kα, with α = −0.71, see inset). Note that, even for very small values of K, unstable groups of 4–5 individuals are formed, and the number of moving individuals 〈Nm〉 is stable with respect to K. The average size 〈S〉 slowly increases as K increases, reaches a maximum for , and then it decreases for larger values of the coupling constant K. With large K, indeed, the model dynamics produces more pairs, since individuals tend to get stuck with their first encounter. A similar behavior is observed for the average size of the groups 〈S〉 as a function of the reset rate R. In this case the peak of 〈S〉 is smoother, with a large range of values of R for which the size is maximum, (Fig. 1D). In fact, low values of R favor the formation of small but very stable groups, while high values of R produce smaller and very unstable groups. A confirm of this behavior can be found by observing the number of moving agents 〈Nm〉 as a function of R, shown in the inset. For small values of R there are few or no moving agents, and the system is almost frozen in a state with small groups of 7–8 individuals, while as R increases, the number of moving agents increases as well, with 〈Nm(R)〉 ~ Rα, with α = 0.71. We have also carried out extensive numerical simulations to address the dependence of the model with the number of individuals N, concluding that the model behavior is independent of the system size, if the density ρ is kept constant. As an example, in Fig. 1 (panels C and D) the curves are plotted for two values of the system size N = 200 and N = 400, showing that both the group size 〈S〉 and the fraction of moving agents 〈Nm〉 scale with N. Onset of metapopulation structures The metapopulation regime is characterized by groups of individuals heterogeneously distributed in the physical and opinion spaces. At any time, some individuals leave and join groups, moving freely in the physical space. This regime emerges when the collision rate pc is large enough to allow groups formation and the interchange of individuals between groups, but smaller than the percolation threshold. The size of the groups, as well as the number of individuals moving between groups, are regulated by the strength of the social influence of the individuals, modeled by the coupling constant K, and the external influence represented by the reset rate R (see Fig. 1C,D). The metapopulation regime is illustrated in Fig. 2, showing a snapshot of the model behavior for three different values of pc, modified by varying the density of agents (see also Movies S1 and S2). Agents not moving in a time window of 1,500 timesteps, i.e., forming stable groups over that observation time, are represented as filled circles. The value of agent status is color coded, illustrating how groups are formed by individuals sharing similar opinions. We note that as pc increases, the number of groups reduces and their size increases. At the same time, the difference in the opinions between the groups reduces, indicating that the system is approaching the regime where a unique group of individuals sharing the same opinion is formed. Panel B also shows the trajectories of two agents selected among those who have changed position at least once in the time observation window. They are representative of two distinct cases. One of them initially belonged to a group located in the right, bottom part of the physical space, then left the group and joined another one approximatively located in the center of the figure (trajectory depicted as a continuous line). The second individual left the group located in the center of the plane but eventually joined it again to remain within it for the rest of the observation (dashed line). In literature, metapopulation structures are characterized by the connectivity matrix representing metapopulations as nodes of a graph, and defining which groups may exchange agents. In our system, the connectivity is the result of the dynamical self-organization of the system. Despite the fact that every link is possible, only some of them, depending on the system parameters, are statistically relevant. In particular, the typical scenario observed for low values of v/L is that agents leaving a group travel for a short distance before reaching the new group. The probability that this group is one of the closest (in a geographical sense) is high, yielding a group connectivity that can be modeled as a random geometric graph. On the other extreme, for high values of v/L, agents are allowed to reach potentially any other group starting from their own, thus we expect a connectivity pattern with an all-to-all coupling between the populations. The characteristic timescale over which a metapopulation does not change its state depends on the reset rate R and on the coupling constant K. A large reset rate R implies a shorter lifetime for a group, while a large coupling strength K increases the resilience of a group to perturbations such as the spontaneous change of opinion by a member or the arrival of a new individual. Also the collision probability pc impacts the stability of groups: for small values of pc few individuals will collide with formed groups, intermediate values of pc will produce more collisions and less stability, and for very large values of pc the system percolates into one or few big groups which tend to keep their composition unchanged in time. This behavior is illustrated in Fig. 3(A), showing the number of stable groups in a given time window of length τ, indicated as 〈Nsg〉 (see Methods), for selected values of the parameters ruling the model. As expected, 〈Nsg〉 grows with pc until it reaches a maximum and then decreases as the system percolates into one or few groups. Therefore, the metapopulation regimes emerges for collision rates pc between the extreme scenarios of very small groups and system percolation. Figure 3(A) also shows how the average number of stable groups is affected by the coupling strength K and the reset rate R. Increasing K has an effect qualitatively similar to that obtained by a decrease of R (compare the curve for K = 0.05, R = 10−4 with that for K = 0.01, R = 10−5) as, in both cases, the formation of groups with few individuals is favored and a large number of stable groups appears even at low values of pc. Therefore, the strength of the social influence K and that of the external opinion sources R act as opposite forces on the group stability. Our analysis also focused on the role of initial conditions. Does a single stable group segregate into several different subgroups under the dynamics driven by a nonzero reset rate R? Or rather do particularly homogeneous initial conditions guarantee asymptotic stability? To address this question we consider two different kinds of extreme initial conditions: (i) all the agents have the same position in the space, xi = yi = L/2, ∀i, and (ii) all the agents have the same position in the space and the same status value, xi = yi = L/2, si(0) = 0.5, ∀i. Interestingly, the feedback between the dynamics in the physical space and the space of social consensus is enough to partition the population into different groups, well separated in both physical and opinion space, under both initial conditions, reaching a dynamical equilibrium indistinguishable from the one achieved with random initial conditions. Figure 3(B) shows the evolution in time of the average number of moving individuals, 〈Nm(t)〉, and the average groups size, 〈S(t)〉, for random initial conditions, compared to initial conditions i) and ii). While initially the evolution of these quantities is different, in the large time limit, , both 〈Nm(t)〉 and 〈s(t)〉 converge to the values that do not depend on the initial conditions. The model is therefore robust to changes in the initial conditions of the population. Emergence of echo chambers In the previous Sections, homophily was implemented through the probability of motion pi(t) defined so as to favor repeated interactions between agents sharing similar opinions. In this Section, we enrich the picture and consider confirmation bias, i.e., the tendency to prefer and select information in a way that confirms one’s beliefs or hypotheses, while giving less consideration to alternative possibilities20. We operationalize the confirmation bias through a parameter of bounded confidence, according to which individuals are influenced only by peers whose opinion is not too different from their own232425. Thus, within this framework, homophily enters also in the definition of the interaction rule between individuals (1), as social influence between agents i and j now depends on the difference of opinions: Here, the parameter C ∈ [0, 1] tunes the strength of the confirmation bias. For C = 0 we recover Eq. (1) (note that, giving periodic boundary conditions, the status difference cannot be greater that 0.5), while increasing values of C represent a stronger bias, the larger C the more an individual is biased toward similar opinions, so that fewer individuals are able to influence him. In the limit C → 1 social influence vanishes since no agent is able to influence any other one. Figure 4(A) shows the average group size, 〈S〉, and the number of stable groups, 〈Nsg〉, as a function of C, showing that a stronger confirmation bias yields a larger number of stable groups, yet their size 〈S〉 decrease with C. This behavior is common across different values of the parameters, such as the collision rate pc or the strength of the social influence K. For C → 1, the number of stable groups drops sharply, due to disappearance of the social influence effect. More importantly, Fig. 4(B) (see also Movie S3) shows that confirmation bias leads to the presence of groups where agents with heterogeneous opinions coexist, i.e. echo chambers of agents that ignore each other although being in spatial proximity and belonging to the same (spatially defined) group. Finally, we address more in detail the close relation between the physical and opinion spaces in order to uncover the impact of the confirmation bias. In the original formulation of the model, the physical metapopulation structure is mirrored in the space of consensus as different groups in general experience a consensus on different opinions (see Fig. 2). The introduction of confirmation bias changes this scenario, allowing the presence of groups with individuals sharing different opinions (see Fig. 4(B)). This fact can be quantified by measuring the correlation between the Euclidean distance between two individuals i and j, dij, and the difference between their status values, |si − sj|mod1, shown in Fig. 5. Without confirmation bias (for C = 0), for any choice of the other parameters the difference |si − sj|mod1 is small and constant for dij ≤ 1, i.e. within the radius of interaction. Then |si − sj|mod1 grows with the distance and reaches a second plateau for large distances , indicating that only individuals within the same group share the same opinion. The choice of the parameters impacts the level of consensus: larger values of the reset rate R or smaller values of the strength coupling K yield less consensus among the agents, and viceversa. The presence of confirmation bias lowers the degree of consensus within groups, leading to larger values of the difference |si − sj|mod1 for small distances dij. This is due to the fact that two or more echo chambers are formed within the same group, formed by agents with different opinions unable to influence each others. Increasing values of C make the difference |si − sj|mod1 more insensitive with respect to the distance dij, and in the limit C → 1 the opinion difference is independent of the physical distance. Conclusions This paper studied the interplay between mobility, homophily and social influence in the context of a simple model of opinion dynamics. The combination of these ingredients leads to the emergence of a metastable metapopulation structure in which groups of like-minded individuals spontaneously segregate in space, while single individuals constantly leave or join them. The emergence of the metapopulation regime crucially depends on the density of the agents, but it is not influenced by the initial conditions. The metapopulation structure is controlled, in terms of group sizes and stability, by the strength of the social influence, K, and the reset rate, R, at which the individuals spontaneously change their opinion. The feedback loop between mobility and social influence yields a strong assortativity between physical and opinion space: the closer two individuals are in space, the closer will be their opinions. This scenario is transformed by the introduction of confirmation bias. The fact that individuals can be influenced only by peers sharing similar opinions leads to the emergence of echo chambers where polarized opinions coexist within the same group. The contributions of the model are threefold. First, it shows that spatial segregation can result from a dynamics involving agents seeking consensus on a non-quenched variable. Second, it provides a framework in which the metapopulation structure, often assumed in the modelling of social systems, emerges from the microscopic rules of the model itself. Third, it shows that confirmation bias yields the possibility that different opinions coexist within the same metapopulation. We believe that our work opens interesting possibilities of future research. For example, it would be interesting to investigate the features leading to the observed fractal patterns of human space occupancy in archeological records2627 or present-day distribution of cities2829. The study of the emergent network properties, such as the distribution of tie strength and its evolution in time, would be interesting with respect to the impact of such time-varying topology on spreading dynamics. At the same time, the emergence of metapopulation structures in which like-minded individuals are relatively isolated from the rest of the subpopulation is interesting also in light of the recently documented emergence of online echo chambers, in which misinformation spreads and persists303132. Methods Dynamical equations of the model The dynamical equations governing the evolution of the model are fully specified by the rules for the agent position and status updates, given by Eq. 2 and Eq. 5, respectively. At each time step, the agent position is updated as: where ξi(t) is a random variable taken from an uniform distribution in [0, 2π]. The agent status is updated as: with s′ ∈ F(s) and Kij is given by with C = 0 in the absence of confirmation bias and 0 < C ≤ 1 in the more general case. Numerical simulations The results presented in the paper are for numerical simulation of the model with N = 200 agents, L = 50, K = 5 ⋅ 10−3, R = 2 ⋅ 10−5, v = 2, d = 1, averaged over 102 runs, unless otherwise specified. To avoid spurious effects due to a transient state, we start to observe the system after a time T0 = 103, which turns out to be sufficient to reach the steady state under different conditions, and run simulation up to Tend = T0 + T, with T = 105 time steps. Computation of the number of groups The number of groups Ni(t) is calculated as follows. At each time instant, we build the adjacency matrix {Aij(t)} with Aij(t) = 1 if i and j are neighbors, i.e. at a distance , and Aij(t) = 0, otherwise. Ni(t) is given by the number of components of {Aij(t)}. The number Nsg(t) of groups that are stable in a given time window of length τ counts the components of a different adjacency matrix computed as follows. From {Aij(t)}, for t > T0 + τ we construct the matrix , which now indicates if two agents have been neighbors in the whole time window [t − τ + 1, t], that is, if Aij(h) = 1 for h = t − τ + 1, …, t, and , otherwise. We then calculate Nsg(t) as the number of components of and average over time to obtain 〈Nsg〉. Additional Information How to cite this article: Starnini, M. et al. Emergence of metapopulations and echo chambers in mobile agents. Sci. Rep. 6, 31834; doi: 10.1038/srep31834 (2016). Supplementary Material Supplementary Information Supplementary Movie S1 Supplementary Movie S2 Supplementary Movie S3 M.S. acknowledges financial support from the James S. McDonnell Foundation. M.F. acknowledges the partial support from the FIR 2015-2016 project of the University of Catania. Author Contributions M.S., M.F. and A.B. conceived the research, M.S. and M.F. performed the simulations, M.S., M.F. and A.B. analyzed the data and wrote the manuscript. Figure 1 Behavior of the model as a function of the parameters. Average size of the groups formed 〈S〉 (main panels) and average fraction of moving agents 〈Nm〉 (insets). (A) 〈S〉 vs. the collision rate pc = πd2ρ. Inset: 〈Nm〉 vs. pc. The functional form is plotted in dashed line. (B) 〈S〉 vs. the velocity v. Inset: 〈Nm〉 vs. v. (C) 〈S〉 vs. the coupling constant K. The average size of the groups 〈S〉 shows a maximum for . Inset: 〈Nm〉 vs. K. The functional form 〈Nm〉 ~ Kα, with α = −0.70, is plotted in dashed line. (D) 〈S〉 vs. the reset rate R. The average size of the groups 〈S〉 shows a maximum for . Inset: 〈Nm〉 vs. R. The functional form 〈Nm〉 ~ Rα, with α = 0.85, is plotted in dashed line. Panels (C,D) show two different sizes of the model, N = 200 (red squares) and N = 400 (black circles). Figure 2 Sketch of the metapopulation structure emerging in the model. Parameters are set to N = 200, R = 10−4, K = 0.01, v = 2, and different values of the collision rate: (A) pc = 0.1 (for a full video, see Movie S1), (B) pc = 1, (C) pc = 5 (for a full video, see Movie S2). A time window of 1500 steps is considered. Agents not moving in this time window (i.e., forming stable groups) are represented as filled circles whose color codes for the status value. In addition, for panel B, the trajectories of two agents moving in the time window considered are also drawn. One of them (continuous line) moves from one group into another, while the other (dashed line) comes back to his own starting group. Figure 3 Stability of groups and effect of initial conditions. (A) Number of stable groups 〈Nsg〉, calculated in a time window of length τ = 50, as a function of the collision rate pc, for different values of K and R. (B) Average groups size 〈S(t)〉 (main) and average number of moving individuals 〈Nm(t)〉 (inset) as a a function of time t, for different initial conditions: random values of position and status, same position and random status, same position and status. Figure 4 Effects of confirmation bias. (A) Average group size 〈S〉 (main), and number of stable groups 〈Nsg〉 (inset), as a function of the parameter C tuning the strength of the bias, for different values of the social influence strength K and collision probability pc = πd2ρ. tuned by varying the box size L. (B) Sketch of the metapopulation structure obtained for C = 0.6 (for a full video, see Movie S3). The other parameters are fixed as in Fig. 2(b). Note the presence of groups formed by agents with very different opinions. Figure 5 Relation between physical and opinion spaces. Average correlation between the Euclidean distance between two individuals i and j, dij, and the difference between their opinions, |si − sj|mod1. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3218510.1038/srep32185ArticleGraphene Dendrimer-stabilized silver nanoparticles for detection of methimazole using Surface-enhanced Raman scattering with computational assignment Saleh Tawfik A. a1Al-Shalalfeh Mutasem M. 1Al-Saadi Abdulaziz A. 11 Department of Chemistry; King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabiaa tawfik@kfupm.edu.sa or tawfikas@hotmail.com30 08 2016 2016 6 3218516 05 2016 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Graphene functionalized with polyamidoamine dendrimer, decorated with silver nanoparticles (G-D-Ag), was synthesized and evaluated as a substrate with surface-enhanced Raman scattering (SERS) for methimazole (MTZ) detection. Sodium borohydride was used as a reducing agent to cultivate silver nanoparticles on the dendrimer. The obtained G-D-Ag was characterized by using UV-vis spectroscopy, scanning electron microscope (SEM), high-resolution transmission electron microscope (TEM), Fourier-transformed infrared (FT-IR) and Raman spectroscopy. The SEM image indicated the successful formation of the G-D-Ag. The behavior of MTZ on the G-D-Ag as a reliable and robust substrate was investigated by SERS, which indicated mostly a chemical interaction between G-D-Ag and MTZ. The bands of the MTZ normal spectra at 1538, 1463, 1342, 1278, 1156, 1092, 1016, 600, 525 and 410 cm−1 were enhanced due to the SERS effect. Correlations between the logarithmical scale of MTZ concentrations and SERS signal intensities were established, and a low detection limit of 1.43 × 10−12 M was successfully obtained. The density functional theory (DFT) approach was utilized to provide reliable assignment of the key Raman bands. ==== Body Raman spectroscopy is based on the behavior of the inelastically scattered photons upon interaction with targeted molecules, and it has been recently becoming an attractive tool for various applications. The most challenging problem with Raman techniques is the nature of the weak scattering, which hinders its effective utilization, especially for low-detection limit targets. The surface-enhanced Raman scattering (SERS) approach, however, could provide a promising strategy to solve this problem. Moreover, given the noticeable advances in instrument technology, Raman spectroscopy has begun to compete with well-established traditional analytical techniques in terms of sensitivity and ease of use1. In SERS, the targeted molecules are adsorbed from an aqueous solution onto nanoparticles that allow a charge transfer between analyte molecules and the particle surface, leading to an enhancement of the Raman signal2. Among the various commonly used types of materials to produce enhanced scattered Raman light are high-purity film-based substrates, which include metals settled on planar surfaces such as glass, quartz, and silicon wafers; or on nanoparticle-embedded surfaces such as silica beads and polystyrene34. SERS films can also be tuned somewhat to appropriate localized surface plasmon resonances by altering various parameters such as film thickness and deposition rate, with most thicknesses of metal being between 5–60 nm5. SERS substrates of colloidal silver or gold nanoparticles can consistently yield a large signal enhancement, explained by electromagnetic and/or chemical enhancement6. Recently, SERS has been reported as a promising technique for quantitative and qualitative identifications of various targets7. It demonstrated the potential to impact the areas of analytical chemistry, biochemistry, forensics, environmental analysis, and trace analysis. The SERS approach exhibits a number of advantages for use in low-detection limit drug analysis when compared to other analytical techniques. Due to its ultra-sensitivity, SERS was used to detect trace organic and inorganic analytes in different media. For example, some organophosphorus compounds, such as methylparathiol and dimethoate, that exist in pesticides were identified at the nanogram level8. Because water molecules scatter weakly in Raman experiments, it has made the SERS approach an attractive choice to conduct useful characterization of samples91011. However, one of the most challenging tasks in developing an effective analytical SERS-based method is the fabrication of the right metal colloid substrate, such as silver, that can exhibit a hotspot within the nanoparticles and subsequently achieve extremely high enhancement12. Since it is required to have more nanoparticles to hook the targeted molecules, the use of a support to load the silver nanoparticles may control the agglomeration that diminishes the enhancement in SERS. Dendrimers, which represent a new class of polymeric nanoscale compounds, are promising candidates for SERS applications due to their homogeneous nature and unique tree-like structure. They have been found to be useful in the health industry, and in pharmaceutical and materials applications13. In addition, dendrimers are considered as one of the most appropriate encapsulating agents for the stabilization of metal nanoparticles (NPs), due to their large size and the presence of a unique three-dimensional architecture of the dendrons that prevents leaching of the NPs during the course of the reaction14. The polyamidoamine dendrimers are considered the favored choice for pharmaceutical applications, due to their regular structure, large size, and chemical versatility15. Screening the literature reveals that several analytical procedures have been reported for the determination of a methimazole-based drug (also known as 1-methyl-2-mercapto-imidazole and tapazole), which is considered as an antihormone drug widely used to treat hyperthyroidism. These methods include molecularly imprinted biomimetic sensing16, fluorescence17, thin layer chromatography18, coulometry19, conductometry20, and high-performance liquid chromatography with ultraviolet detection21. To the best of our knowledge, no SERS attempts with the use of graphene dendrimeric-based substrates has been reported to detect low-concentration samples of methimazole (MTZ). In this work we adopted graphene as a support, modified with a dendrimer, to allow controlled silver nanoparticles to be linked to its branches. The prepared graphene linked with dendrimer-stabilized silver nanoparticles (G-D-Ag) was then evaluated as a potential SERS substrate for MTZ detection. Experimental Procedure Chemicals and Materials Methimazole (MTZ) “1-Methyl-2-imidazolethiol “(analytical standard, ≥99% purity), CAS number 60560, was purchased from Sigma-Aldrich. Silver nitrate (AgNO3, 99.8%), product number 30087, was purchased from BDH-Chemicals Ltd Poole England. Sodium borohydride (NaBH4), product number 63390, was purchased from Allied Signal. Ethylenediamine (≥99.5%), product number 03550, methyl acrylate (99%), CAS number 76778, thionyl chloride (SOCl2, ≥99%), product number 230464, and potassium bromide (KBr, ≥99%), product number 221864, were purchased from Sigma-Aldrich. Solutions were prepared with ultrapure water obtained from a water purification system (Ultra Clear™ Lab Water Systems, Siemens Water Technologies USA). Synthesis of graphene dendrimer silver composite Figure 1 shows the preparation steps of dendrimer functionalization with silver. About 0.2 g of the prepared graphene nanosheets was dispersed in 20 ml of SOCl2 by sonication in an ultrasound bath for 30 min and stirred for 12 h at 60 °C; the mixture was then filtered. The obtained material was dried overnight at room temperature. Next, 10 ml of ethylenediamine was added to the solid product, the reaction mixture was sonicated for 3 h at 60 °C, and stirred for another 12 h at room temperature. The solid product was collected by centrifugation at 10000 rpm/min for 10 min and dried overnight at room temperature. The last solid product was suspended in 10 ml methanol and was added dropwise to 25 ml of 1:4 methyl acrylate - methanol solution under stirring. The reaction mixture was treated in an ultrasonic bath at 60 °C for 2 hours and stirred for another 12 h at room temperature. The solid product was collected by centrifugation at 10000 rpm/min for 10 min and dried overnight at room temperature. Afterward, the obtained material was immersed in 10 ml methanol, and then a 1:1 mixture of 10 ml of ethylenediamine – methanol was added at a rate 1 drop/sec to the solution. The solution was placed in an ultrasonic bath at 50 °C for 5 h and stirred for another 10 h at room temperature. The solid product was collected by centrifugation and dried overnight at room temperature. The steps were repeated for methyl acrylate and ethylenediamine until reaching the third-generation. The third-generation polyamidoamine dendrimer on the graphene (G-D) presented a typical morphology when compared to the others obtained using higher dendrimer concentrations. The solid of this material was dispersed in 20 ml de-ionized water by sonication in an ultrasound bath for 10 min. Then, 10 ml of 0.2 M AgNO3 was added dropwise with the previously dispersed solid and the mixture was stirred for 1 hour. Then, 10 ml of a freshly prepared solution of NaBH4 was added to the solution and the solution was kept under stirring for another 5 h. Finally, the mixture was filtered, and the obtained material was washed with deionized water several times. The greenish yellow isolated solid was dried overnight at room temperature. The stabilization mechanism of the silver nanoparticles (AgNPs) on the graphene nanosheets through the dendrimers is shown in Fig. 2. The abbreviation used for graphene modified with a third-generation polyamidoamine dendrimer is G-D, while for graphene-dendrimer-silver nanoparticles it is G-G-Ag. Material Characterization Scanning Electron Microscope, JSM-6610LV, JEOL at 20 kV acceleration voltage equipped with energy-dispersive X-ray spectroscope, Mapping and transmission electron microscope (TEM, FEI Tecnai TF20) were employed to investigate the morphological and microstructural attributes of the synthesized material. The UV-Visible spectra of the graphene and G-D-Ag were recorded on a genesis 10S UV-Vis spectrophotometer (Thermo Scientific), using standard quartz cuvette at room temperature between 250–650 nm. The samples were prepared by dilution the stock solution 4x with distilled water. FT-IR spectra of samples were recorded using a Perkin-Elmer IR spectrophotometer using potassium bromide (KBr) pellets, the pellet was designed by blending the sample and KBr with a ratio of 1:100. The FT-IR measurement was scanned at a range from 400 to 4000 cm−1. The He-Ne laser source operating at 0.5 W was utilized for sample excitation. Surface-Enhanced Raman Scattering (SERS) spectroscopy The SERS spectra of samples were obtained by using a Raman spectroscopy system- a Lab Ram HR Evolution Raman spectrometer- equipped with an internal He-Ne 17 mW laser at a 633 nm excitation wavelength. SERS samples were prepared in a small cuvette by using a 4:1 volume ratio of aqueous MTZ solution to G-D-Ag. A 50x objective was used for focusing the laser beam to the solution. The data acquisition time was 20 sec with one accumulation for collection with each SERS spectra. A cuvette with dimensions of 1 cm radius and 2 cm height was used as a sample cell for the Raman spectra. The SERS spectra were obtained in the range from 400–2000 cm−1. Theoretical Calculations Density functional theory (DFT) calculations were employed to optimize the structure of MTZ and calculate its vibrational frequencies at the ground level. The Gaussian 09 program was used to carry out the DFT-B3LYP/6-311 ++ G(d,p) level of calculation22. Atomic displacements associated with each vibrational mode were carefully inspected using Gauss–View software23 and corresponding potential energy distributions (PEDs) were computed with Vida software24 in order to provide reliable assignments of the normal Raman, as well as SERS spectra, of MTZ. The minimum-energy structure of MTZ with atom numbering adopted is shown in Fig. 3. The vibrational frequencies were compared to the solid state Raman spectra (Table 1). Results and Discussion Structural analysis of G-D and G-D-Ag The ultraviolet-visible spectra of G-D and G-D-Ag are shown in Fig. 4. The maximum absorption band at 300 nm is attributed to the n-π* electronic transitions of the dendrimer. Moreover, the maximum absorption peak of G-D-Ag is at 400 nm, due to the plasmon resonance of G-D-Ag, indicating the formation AgNPs on the surface of the dendrimer. FT-IR was employed to confirm the chemical structure of G-D and G-D-Ag. Figure 5 shows the FT-IR spectra of G-D and G-D-Ag. The FT-IR spectrum of G-D shows a weak broadband at ~3418 cm−1, corresponding to the vibration of NH2. The very low-intensity peaks at 2923 cm−1 and at 2854 cm−1 are assigned to the symmetric and antisymmetric stretching vibrations of CH2, respectively. The bands at 1654 and 1324 cm−1 are assigned to C=C and C=O, respectively. The FT-IR spectrum of G-D-Ag differs from that of G-D, as evidenced by the weakening of the NH2 band in the range 3350 to 3450 cm−1. It suggests that the AgNPs are stabilized in the G-D network through this functional group25. The disappearance of the peak, attributed to C-O at 1324 cm−1 in the G-D-Ag spectrum, is probably due to the reduction of the oxygenated functional groups through the heat treatment process15. SEM, EDX and mapping imagings were used as techniques complementary to TEM to investigate the appearance of the synthesized materials, as seen in Fig. 6. The SEM images (Fig. 6a), shows the morphology of the prepared G-D, and the inset TEM image illustrates the formation of multi- dots of dendrimers on the graphene nanosheets. These dots are used as bases, or cores, for attracting and catching the silver ions. The presence of reactive amine groups on the surface of dendrimer-modified graphene was profited to allow the multipoint attachment of the AgNPs through the formation of linkages, (as shown in the mechanism-Fig. 2) which were further transformed to stable secondary amino linkages by reductive treatment with NaBH4. This allows for the controlled growth of AgNPs, as shown in the TEM image (Fig. 6g) and the SEM image, with TEM inset (Fig. 6b), which provide evidence that the Ag nanoparticles are well dispersed as a consequence of the stabilization of the growing silver by the different amide groups of the dendrimer. The nanoparticles could be stabilized by interaction with the primary amino groups remaining at the outer surface of the dendrimer. The mapping images, Fig. 6e,f, indicate that the stabilized AgNPs were mostly uniform dispersed. Further characterization was confirmed by EDX spectra (Fig. 6c,d), which confirms the presence of the silver, with strong interaction with the dendrimer, even after washing the sample several times, followed by drying. Therefore, the graphene was successfully used as an indirect support for the silver nanoparticles. The silver nanoparticles were decorated on the dendrimer branches rather than being directly attached to the graphene. This material provides the best SERS enhancement for MTZ compared with the AgNPs loaded graphene, because the dendrimer allows better distribution of AgNPs on the nanosheets, as shown in the TEM image. Therefore, the role of the graphene was as a support; however, the silver nanoparticles were located on the dendrimer branches (linkers) rather directly attached on the graphene. This way the silver nanoparticles were better distributed and decorated on the graphene sheets surface as shown in the TEM image. Raman Analysis of G-D and G-D-Ag The Raman spectra of the G-D and G-D-Ag are shown in Fig. 7. The Raman spectra of all samples displayed two prominent bands. While the D band around 1350 cm−1 is associated with disordered sp3 carbon atoms, the G band around 1590 cm−1 corresponds to ordered sp2–hybridized carbon atoms26. Further, the intensity ratio of D and G bands (ID/IG) increases. The ID/IG is used to assess the sp2/sp3 carbon ratio, which represents the degree of disorder and the average size of the sp2 carbon atoms domains. The ratio for G-D-Ag, 1.56, was larger than that for G-D, 1.22, suggesting that more graphitic domains are formed and the sp2 cluster number is increased after introducing the silver via the reduction process. This reflects the functionalization of the AgNPs on the dendrimer-modified graphene27. This can be explained by the removal of some oxygen-containing functional groups during the reduction process, leading to the formation of high-level fragmentation along the reactive sites of graphene dendrimer28. Surface-Enhanced Raman Scattering (SERS) spectra of MTZ with G-D-Ag The collected Raman spectrum for solid MTZ, compared with a 1 × 10−5 M concentration MTZ-(G-D-Ag) SERS spectrum, is depicted in Fig. 8. In order to understand the nature of the interaction between the bounding of the MTZ molecules and the surface of the AgNPs, it is useful to propose proper band assignments for the normal Raman and SERS spectra. For reliable assignments, we conducted DFT assessments of the vibrational frequencies of the single MTZ molecule and compared them with the corresponding ones resulting from the interaction between the silver and MTZ. All these data are listed in Table 1. The DFT method based on the hybrid B3LYP functional and split-valence 6–311 ++ G(d,p) basis set showed good agreement with the experimental results. The band observed at 1342 cm−1 and at 1345 cm−1 in the solid and solution Raman spectra, respectively, shifted to 1359 cm−1 in the SERS spectrum. This band shows the highest enhancement factor. The DFT calculation attributes this band mostly to the N2-C4 stretching (with some contribution from the ring and C6-N3-H bending) and successfully predicts its slight shift to the lower frequency side. Moreover, the modes observed at 1538 and 1463 cm−1 have shifted to 1522 and 1452 cm−1, respectively, in the SERS spectrum with significant enhancement. PED analysis shows that these bands are associated with S-C and C-N stretching modes (Table 1). The bands at 1278, 1156, 1092, 1016, and 600 cm−1 in the normal Raman spectrum are shifted to 1320, 1141, 1090, 1037, and 619 cm−1, respectively in the SERS spectrum. These bands show higher intensities in the SERS spectrum. The Raman bands recorded at 525 and 410 cm−1 are attributed to SCN bending and were observed at 498 and 427 cm−1, respectively, in the SERS spectrum. The red shift of the former, and the blue shift of the latter SCN bending modes have been reproduced successfully by the DFT approach, which makes it convenient to assign them accordingly. This suggests that in the SERS experiments silver particles interact with the MTZ molecules through both sulfur and nitrogen positions at a comparable level. SERS Enhancement Factors of MTZ The SERS enhancement factors (EFs) for the vibrations of MTZ (1 × 10−3 M) on G-D-Ag to the corresponding band obtained from 1.0 M saturated solution were calculated using the following equation. where δ and C are the Raman mode intensity and sample concentrations, respectively. The EFs for the SERS peaks of MTZ on G-D-Ag are given in Table 2. The EFs are not the same for the different MTZ modes; the maximum enhancement was observed at 1342 cm−1. SERS Spectra of MTZ at Different Concentrations The SERS spectra of MTZ aqueous solution with G-D-Ag as a substrate at different concentrations are given in Fig. 9a. The intensities of the SERS spectra increase with an increase in the concentration of MTZ. This suggests that the SERS intensities are proportional to the molecular quantity of MTZ. The highest enhanced band, at 1359 cm−1 in the SERS spectra, was selected for creating a qualitative analysis of MTZ. A plot of the SERS response versus the logarithmical scale of 10−6 M to 10−11 M of MTZ at 1359 cm−1 was obtained, (Fig. 9b), showing a good coefficient of determination (R2) of 0.9976. Within the dynamic range, the lowest concentration measured in the SERS analysis of the MTZ solution was 10−11 M. To evaluate the analytical performance of the proposed method, parameters such as linearity, repeatability, limits of detection and dynamic range were investigated under optimum experimental conditions. The results of the linear equations, dynamic range, and R2 for the obtained calibration curves of MTZ with G-D-Ag substrate are summarized in Table 3. Good linear relations between the enhanced SERS bands’ intensities in counts per second (cps) and the logarithmical scale of MTZ concentrations were noted with a wide dynamic linear range or linear working range (LWR) for MTZ with the substrate. The precision of the proposed method was checked by replicate analysis of the working standard of MTZ drug at six concentration levels. The relative standard deviation (RSD) for all concentration levels was <2.2%, which indicates both the precision and repeatability of the proposed method. The reproducibility of the method using the same batch of the prepared material was obtained in five days, with a corresponding relative average standard deviation of less than 4%. The results obtained by the reported method in this study were compared with some methods reported in the literature in terms of calibration range, detection limits, and determination coefficients (R2). The comparison with other methods for the determination of MTZ is summarized in Table 4. In comparison to other methods for determination of the MTZ, the proposed method has attracted more interest due to its sensitivity, good dynamic range, and simplicity Application of the proposed method for the determination of MTZ in real samples Determination of MTZ in tablet samples was examined to demonstrate the ability of the SERS method for the determination of MTZ in real samples. The proposed method was applied for the determination of MTZ in the commercial pharmaceutical dosage forms, tablet samples. In order to access the matrix effect, the relative recoveries of the method were calculated. The obtained results, shown in Table 5, indicate the accuracy of the method, as well as the low interference limits caused by the frequently encountered excipients and the degradation products. Thus, the SERS method retained its efficiency for the determination of MTZ in real samples. Conclusion We have reported the synthesis of graphene functionalized with polyamidoamine dendrimer decorated with silver nanoparticles (G-D-Ag), characterized by using various techniques including SEM, TEM, FTIR and UV. The SERS method was exploited to record the vibrational frequencies of MTZ adsorbed on G-D-Ag. The optimized conformation and vibrational assignments of MTZ were carried out using a DFT calculation with a B3LYP/6-311 ++ G (d, p) basis set. The vibration assignments and the wavenumber of vibration frequency bands in the theoretical spectra were in agreement with those of the experimental spectra. Most of the bands related to N and S atom were apparently enhanced and slightly shifted. These results confirm that MTZ molecules were adsorbed on the G-D-Ag, probably through the lone pair on the N and S atoms. The correlation between the logarithmical scale of MTZ concentration and the SERS signal was linear within a dynamic range of 10−6–10−11 and R2 of 0.9976, and with good detection limits down to 1.43 × 10−12. Additional Information How to cite this article: Saleh, T. A. et al. Graphene Dendrimer-stabilized silver nanoparticles for detection of methimazole using Surface-enhanced Raman scattering with computational assignment. Sci. Rep. 6, 32185; doi: 10.1038/srep32185 (2016). The authors would like to acknowledge the support provided by King Abdulaziz City for Science and Technology (KACST) through project No. A.T.34-8. The authors would like also to acknowledge the support by King Fahd University of Petroleum and Minerals (KFUPM). Author Contributions T.A.S. and A.A.A.-S. created the ideas of the project and conducted the establishment of the system. T.A.S., M.M.A.-S. and A.A.A.-S. contributed to the experimental work; synthesis and characterization, results optimization and calculations, and developed the manuscript and review the final article. Figure 1 Illustration explaining the synthesis steps of the graphene- polyamidoamine dendrimer-silver G-D-Ag. Figure 2 Mechanism of the stabilization of the AgNPs on the graphene through the dendrimer for the preparation of graphene- polyamidoamine dendrimer-silver (G-D-Ag). Figure 3 The optimized structure of MTZ. Figure 4 UV-Vis absorption spectra of (a) the G-D and (b) the G-D-Ag. Figure 5 FT-IR spectra of (a) G-D and (b) G-D-Ag. Figure 6 (a) Typical SEM image (inset: TEM image) of G-D; (b) SEM image (inset: TEM image) of G-D-Ag; (c) EDX spectra of G-D; (d) EDX spectra of G-D-Ag; (e) Mapping image of G-D; (f) Mapping image of G-D-Ag; (g) TEM image of G-D-Ag. Figure 7 Raman spectra of (a) G-D and (b) G-D-Ag. Figure 8 Raman spectrum of (a) pure solid MTZ and (b) SERS spectrum of 1 × 10−5 M MTZ with G-D-Ag as a substrate, Laser ʎ = 633 nm, acquisition time; 20 sec, and objective; 50x.; with the assignments of Raman bands. Figure 9 (a) SERS spectra of MTZ with different concentration using G-D-Ag, (b) calibration curve of the band at 1359 cm−1. Laser ʎ = 633 nm, acquisition time; 20 sec, and objective; 50x. Table 1 Infrared, Raman, SERS and calculated DFT vibrational frequencies (cm−1) of MTZ. Observed Calculated Assignments with Corresponding potential energy distributions (PEDs) (%) IR Raman (Solid) Raman (Solution) SERS MTZ MTZ-Ag 3159 w 3161 w 3166 m   3162 3166 97% ν (C7-H) 3104 w 3105 w 3106 vw   3142 3147 98% ν (C6-H) 3012 w       3022 3021 96% ν (C5-H11)         2999 2995 100% ν (C5-H12) 2949 vw 2950 m 2960 m 2945 m 2936 2932 96% ν (C5-H13) 1578 vs 1579 s 1580 m 1567 w 1588 1581 63% ν (C6 = C7), 10% δ (N3-H) bend   1538 vw   1522 vs 1509 1496 24% ν (N2-C4), 15% ν (C-C), 38% δ (H11-C-H12) bend         1473 1467 23% ν (S-C4), 14% ν (C4-N) bend, 10% δ (N3-H) bend,   1479 vw 1480 vs   1466 1457 72% δ CHMe scissoring 1462 s 1463 vs 1460 vw 1452 s 1459 1452 23% ν (S-C4), 14% ν (N3-C4), 12% δ (C-H) bend, 1403 m 1410 m 1410 vw 1408 w 1415 1411 14% ν (N2-C4), 14% ν (N3-C6), 13% ν (S-C4), 30%δ (C -H) bend 1339 vs 1342 s 1345 s 1359 vs 1315 1328 32% ν (N2-C4), 11% δ ring bend, 19% δ C6-N3-H bend 1274 s 1278 m 1281 m 1320 s 1285 1309 15% ν (N2-C5), 19% δ N3-H (C6-H) bend, 14% δ ring breathing 1248 m 1252 vs 1255 vw 1277 vw 1212 1237 51% ν (N3-C4), 18% δ N3-H (C6-H) bend, 13% δ (C7-H) bend 1152 vs 1156 vw 1153 m 1141 m 1159 1150 16% ν (N3-C6), 16% ν (S-C4), 15% δ (H11-C-H12) rock, 1086 vw 1092 m 1088 vw 1090 m 1089 1091 46% ν (N3-C6), 14%δ (N3-H) bend, 21% δ (C7-H) bend 1014 s 1016 m 1017 vw 1037 m 1013 1022 15% ring CH bend, 13% δ CHMe bend, 41% δ ring bend 913 m 915 vs 916 s 937 w 913 923 12% ν (N2-C4), 12% δ N3-H (C6-H) bend, 62% δ ring bend 818 w 810 vw   830 vw 806 818 89% γ (H-C6-C7-H) twist 673 vs 679 vw 684 vs 687 w 685 699 25% δ (C7-N2-C5) bend, 15% δ (C4-N2-C5) bend   643 vw   670 vw 650 667 47% ring CH bend, 39% γ (N3-C4-N2) 599 vw 600 vw 602 vw 619 m 603 623 78% γ CN ring bend. 527 vs 525 m 522 w 498 s 534 520 53% δ (S-C4-N3) bend, 25% δ (S-C4-N2),   493 vw     503 569 84% γ (N3- C6-C7) 411 s 410 s 410 m 427 m 411 421 71% δ (S-C4-N2)   264 m 260 m 279 w 238 251 85% γ (C4-S) wag   208 vw 209 vw   207 220 76% γ ring Values are in cm−1; ν, stretch; γ, bend; δ, symmetric. vs. very strong; s, strong; m, medium; w, weak; vw, very weak. Table 2 SERS enhancement factor of MTZ on G-D-Ag substarte. SERS spectra (cm−1) Enhancement Factor (EF) 1522 8.3 × 104 1452 1.1 × 104 1359 1.5 × 105 1320 2.5 × 104 1141 1.0 × 104 1090 2.3 × 104 1037 3.8 × 104 619 1.4 × 104 498 2.0 × 104 427 2.4 × 104 Table 3 Regression equation between Raman intensities and concentrations of MTZ and their coefficient of determination (R2). Raman Peaks Regression Equation R2 Dynamic linear range (M) LOD*(M) 1359 cm−1 y = 292.43x + 3409.8 0.9976 10−6–10−11 1.43 × 10−12 1320 cm−1 y = 144.97x + 1651.9 0.9921 10−6–10−11 2.67 × 10−12 498 cm−1 y = 124.14x + 1479 0.9744 10−6–10−11 3.71 × 10−12 427 cm−1 y = 63.771x + 739.39 0.9651 10−6–10−11 0.91 × 10−11 *LOD: limit of detection. Table 4 Comparison of dynamic linear range, detection limits between and coefficient of determination (R2) this method and other methods for the determination of MTZ. Method Dynamic linear range (M) Limit of detection (M) R2 Ref. SERS 10−6–10−11 See Table 3 See Table 3 Present work SERS 5.0 × 10−8–5.5 × 10−7 7.4 × 10−5 0.998 29 SERS 1.8 × 10−9–1.3 × 10−6 8.8 × 10−10 0.9992 30 Flow-Injection 1.75 × 10−5–8.75 × 10−4 8.75 × 10−6 0.999 31 Capillary Electrophoresis 1.0 × 10−7–2.0 × 10−4 5.0 × 10−8 0.9995 32 DPV 1.0 × 10−7–2.0 × 10−5 2.0 × 10−8 0.998 33 HPLC 0.2 × 10−6–2.0 × 10−6 0.18 × 10−6 0.9975 34 SWV 6.0 × 10−6–240 × 10−6 1.98 × 10−6 0.9996 35 Table 5 Determination of MTZ in pharmaceutical tablet samples (n = 3); Recovered concentrations obtained for MTZ using a SERS method with G-D-Ag and calibration curve at 1359 cm−1 (n = 3). Sample Expected Found Recovery % Confidence interval Bias (%) Tablet 1 5 mg/g 4.93 mg/g 98.6 0.31 × 10−6 M −1.4 Tablet 2 5 mg/g 4.88 mg/g 97.6 0.31 × 10−6 M −2.4 Spiked 1 2.5 × 10−6 M 2.61 × 10−6 M 104.4 0.48 × 10−6 M +4.4 Spiked 2 5.0 × 10−6 M 5.13 × 10−6 M 102.6 0.72 × 10−6 M +2.6 ==== Refs Fleischmann M. , Hendra P. J. & McQuilla A. J. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3233010.1038/srep32330ArticleA Na+ Superionic Conductor for Room-Temperature Sodium Batteries Song Shufeng 12Duong Hai M. 1Korsunsky Alexander M. 3Hu Ning 2Lu Li a11 Materials Science Group, Department of Mechanical Engineering, National University of Singapore, 117575 Singapore2 College of Aerospace Engineering, Chongqing University, Chongqing 400044, P.R. China3 Multi-Beam Laboratory for Engineering Microscopy (MBLEM), Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, United Kingdoma luli@nus.edu.sg30 08 2016 2016 6 3233022 02 2016 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Rechargeable lithium ion batteries have ruled the consumer electronics market for the past 20 years and have great significance in the growing number of electric vehicles and stationary energy storage applications. However, in addition to concerns about electrochemical performance, the limited availability of lithium is gradually becoming an important issue for further continued use and development of lithium ion batteries. Therefore, a significant shift in attention has been taking place towards new types of rechargeable batteries such as sodium-based systems that have low cost. Another important aspect of sodium battery is its potential compatibility with the all-solid-state design where solid electrolyte is used to replace liquid one, leading to simple battery design, long life span, and excellent safety. The key to the success of all-solid-state battery design is the challenge of finding solid electrolytes possessing acceptable high ionic conductivities at room temperature. Herein, we report a novel sodium superionic conductor with NASICON structure, Na3.1Zr1.95Mg0.05Si2PO12 that shows high room-temperature ionic conductivity of 3.5 × 10−3 S cm−1. We also report successful fabrication of a room-temperature solid-state Na-S cell using this conductor. ==== Body Since their introduction in 1991, rechargeable lithium-ion batteries have proliferated throughout consumer electronics. They continue doing so apace, alongside increasing use in stationary energy storage applications. In considering future rechargeable batteries, the increasing lithium consumption and the likely future costs must be taken into account. Sodium (Na) has redox potential of Eo = −2.71 V vs. standard hydrogen electrode, which is close to that of Li. Na-based batteries have recently began making a comeback as an alternative for large-scale energy storage123. In the development of oxide-based batteries, a principal long-standing challenge is associated with the ionic conductivities of solid electrolytes, poor mixed ionic-electronic conductivities in the electrodes, and inferior interfacial contact between electrolytes and electrodes4. This explains the reason why, despite increasing interest in solid-state electrolytes, little progress in solid-state batteries has been reported, with only few publications on oxide-based solid-state sodium batteries567. In the present work, the fabrication of a room temperature solid-state Na-S battery using an oxide electrolyte is demonstrated that represents the first step towards the creation of a solid-state room-temperature Na-S battery. The development of sodium batteries began with 1960s, when a sodium beta-Al2O3 (NaAl11O17) solid electrolyte was first reported8, which inspired intense interest in the solid-state electrochemistry of Na-conducting solid electrolytes. However, the high operation temperature (300 to 350 °C) required for this system has raised a series of concerns over battery design and manufacture, safety issues as well as maintenance costs. For example, the extremely corrosive polysulphide melts, and the degradation of sodium beta-Al2O3 at the high operation temperature, can potentially result in battery failure, leading to fire hazard, and in some cases causing explosion910. Decreasing the battery working temperature would enhance battery safety, improve durability, and reduce cost11. It is particularly desirable for a solid-state Na-based battery to operate at ambient temperature. Unfortunately, to date no superior solid-state electrolytes have been reported for room-temperature Na-based battery operation, in particular for the Na-S system. A promising sulphide glass-ceramic electrolyte with a conductivity of 10−4 S cm−1 at room temperature, has recently been reported by Tatsumisago’s group12. However, a practically useful value of 10−3 S cm−1 is required to enable realistic battery design13. Four decades ago, pioneering work by Hong and Goodenough on NASICON (sodium super ion conductor) structure, Na1+xZr2SixP3−xO12 (0 ≤ x ≤ 3), demonstrated that good room-temperature conductivities (~10−4 S cm−1) could be achieved, owing to the presence of a 3D cation transportation channel1415. Surprisingly, this remarkable opening for further research in the field appears to have been ignored so far. Previously, we studied Li-ion electrolytes with garnet structure16. The alkaline earth cations have long been viewed as confined to being located exclusively at the dodecahedral 8-coordination sites (La sites) in the garnet structure owing to their large ionic radii1718. However, we found that alkaline earth metals can be made to occupy the octahedral 6-coordination sites (Zr sites) through a structural transformation by a facile mechanochemical method, leading to enhanced room-temperature conductivity19. We also note a report of conductivity enhancement in NASICON electrolytes to which metal oxides (for example, Y2O3, TiO2, SnO2, V2O5, Nb2O5, Ta2O5, MgO, ZnO) have been added, although the room-temperature conductivities were not studied in these systems20. Mindful of previous research reports, we describe here the development and characterization of NASICON electrolytes doped with alkaline earth ions at octahedral 6-coordination Zr sites through mechanochemical synthesis. Specifically, the prepared electrolyte with a composition of Na3.1Zr1.95Mg0.05Si2PO12 presents a high room-temperature conductivity at the level of 10−3 S cm−1. Results Materials synthesis Na3.1Zr1.95M0.05Si2PO12 (M = Mg, Ca, Sr, Ba) were synthesized by doping with alkaline earth ions at octahedral 6-coordination Zr sites. The procedure employed in this work consists of two sequential steps. Firstly, solid solutions of alkaline earth metal oxides (MO) and ZrO2 were synthesized by high energy ball milling at 875 rpm for 2 h (SPEX SamplePrep 8000 M Mixer). Then NASICON Na3.1Zr1.95M0.05Si2PO12 structures were synthesized through solid-state reaction of Na2CO3, Zr1.95M0.05O3.95, SiO2, and NH4H2PO4 at 1260 °C. X-ray diffraction patterns (Fig. 1a) show that the matrix of Zr1.95M0.05O3.95 is ZrO2, rather than MO. This provides a clear piece of evidence that mechanochemical synthesis leads to the formation of a solid solution of MO in ZrO2. Sintered Na3.1Zr1.95M0.05Si2PO12 gives rise to XRD patterns (Fig. 1b) that exhibit monoclinic C2/c NASICON phase structure with very low impurity level of ZrO2, ~3–5wt.% from Rietveld refinement of powder XRD data (Tables S1–S4). Materials characterization Conductivities of sintered pellets of Na3.1Zr1.95Mg0.05Si2PO12 are evaluated by electrochemical impedance spectroscopy (EIS). Typical EIS plots as shown in Fig. 2a obtained using ion-blocking Au electrodes exhibit two semicircles and one tail in the high- and low-frequency range, suggesting that the investigated material is inherently ionically conductive and is bulk-boundary resistance separated. The EIS results resolve well the grain and grain-boundary resistances at room temperature in the frequency range of 12 MHz and 0.2 MHz. In Fig. 2a, one depressed semicircle in the higher frequency range (12–8 MHz) represents the bulk contribution, Rb, which not start from “0” due to a contact resistance, Rs (~120 Ω), whereas, another semicircle in the lower frequency range (8–0.2 MHz) represents the grain-boundary contribution, Rgb21. The total conductivity of the Na3.1Zr1.95Mg0.05Si2PO12 pellet (thickness of 2.7 mm and diameter of 4.5 mm) at room temperature is calculated to be ~3.5 × 10−3 S cm−1. An interesting observation is that the grain-boundary resistance is much lower than that of grain at room temperature. This demonstrates by far the best conductivity realized in a solid-state Na-ion electrolyte. Figure 2b shows the result of dc polarization measurement of sintered Na3.1Zr1.95Mg0.05Si2PO12 pellet with Au as blocking electrodes. The electronic conductivity ~1.3 × 10−8 S cm−1 at room temperature is detected by dc polarization technique. The sodium-ion transference number is close to one (tNa+ = (σtotal − σe)/σtotal = 0.99999). The conductivities of Na3.1Zr1.95M0.05Si2PO12 (M = Ca, Sr, Ba) are lower than that of Na3.1Zr1.95Mg0.05Si2PO12 (Fig. 2c). The Na+-ion mobility and conductivity depend mainly on the crystal structure. The addition of alkaline earth ions modifies the crystal structure of NASICON phase because of their large ionic radii. Besides, the addition of alkaline earth metals promotes sintering, and induces well-crystallized grains and dense microstructure (Fig. 2d) helpful for ion conduction. Besides the high ionic conductivity, an essential requirement for solid electrolytes is a large electrochemical stability window. The electrochemical stability of the present material against metallic sodium is examined by cyclic voltammetry using a Au/Na3.1Zr1.95Mg0.05Si2PO12/Na cell with a scan range of −0.2 to 9 V and a scan rate of 1 mV s−1 (Fig. 3a). It is noted that Han et al.22 indicated that the wide electrochemical stability of lithium solid electrolytes is overestimated by the large lithium deposition/dissolution peaks via conventional experimental method with Li/electrolyte/inert metal semi-blocking electrode, and new experimental method is developed to evaluate the electrochemical stability of lithium solid electrolytes which uses Li/electrolyte/electrolyte-carbon/inert metal cell. In the present work, therefore Na/Na3.1Zr1.95Mg0.05Si2PO12/Na3.1Zr1.95Mg0.05Si2PO12-carbon/Au cell is also assembled to further evaluate the electrochemical stability window of Na3.1Zr1.95Mg0.05Si2PO12, with a scan range of 0 to 9 V (to avoid Na deposition/dissolution peaks) and a scan rate of 0.1 mV s−1. As shown in Fig. 3b, the oxidation of Na3.1Zr1.95Mg0.05Si2PO12 starts at about 4.5 V, but the current is very low with the maximum current of about 0.2 μA at scan voltage of 9 V, indicating that only a little bit of Na3.1Zr1.95Mg0.05Si2PO12 is oxidized. Therefore, the Na3.1Zr1.95Mg0.05Si2PO12 electrolyte possesses a practically useful electrochemical window of 0–4.5 V vs Na/Na+, which is sufficient to most of sodium cathodes. The diffusion coefficient at room temperature can be calculated by Eq. 1 using the relation between the scan rate and peak current obtained from the slop of ip/A vs. v1/2 plot2324. where D is the cation diffusion coefficient in cm2 s−1, ip represents peak current in Amperes, C corresponds to the initial Na concentration in mol cm−3, n is the number of electrons per reaction species, A represents the electrode area in cm2, v represents the sweep rate in V s−1. Figure 3c shows the ip/A vs. v1/2 plot and it gives rise to the value of diffusion coefficient D of 5.24 × 10−8 cm2 s−1. The ionic conductivity is calculated via the Stokes-Einstein relationship25, where C, q, R, and T are the Na concentration (0.019 mol cm−3), carrier charge, gas constant, and absolute temperature, respectively. The ionic conductivity is calculated to be 3.7 × 10−3 S cm−1, which is consistent with the conductivity value obtained from ac impedance method (3.5 × 10−3 S cm−1). The Na/Na3.1Zr1.95Mg0.05Si2PO12/Na symmetric cells are galvanostatically cycled (Fig. 4). A minimal and stable polarization potential of 2.7 mV is obtained with current density of 44 μA cm−2. The direct-current conductivity of the present material is found to be 3.3 × 10−3 S cm−1 that is approximately consistent with the ac conductivity of 3.5 × 10−3 S cm−1 found by EIS, and the conductivity of 3.7 × 10−3 S cm−1 determined by cyclic voltammetry. Good agreement between different conductivity measurement methods (EIS, cyclic voltammetry, galvanostatic cycling), confirms the conclusion that the present material indeed possesses extremely high ionic conductivity in excess of 10−3 S cm−1 at room temperature. Figure 5 shows the temperature-dependent total ionic conductivity of Na3.1Zr1.95Mg0.05Si2PO12 electrolyte together with those of other promising Na-ion electrolytes. The Na3.1Zr1.95Mg0.05Si2PO12 electrolyte is characterized by the conductivity of ~3.5 × 10−3 S cm−1 at room temperature and activation energy of ~0.25 eV. For example, the organic liquid electrolyte propylene carbonate–ethylene carbonate-dimethyl carbonate (45:45:10 wt.%) containing 1M NaTFSI (ref. 26) has conductivity around 10−2 S cm−1. Polymer electrolyte, such as PEO-NaClO4-TiO2 (ether-oxygen-to-sodium ratio was 20:1, addition of 5% TiO2) (ref. 27) has room-temperature conductivity of 10−5 S cm−1. Doped sodium hydride electrolyte, such as Na2B10H10 has conductivity of 10−2 S cm−1 only above 110 °C, whilst its conductivity drops to only ~5 × 10−7 S cm−1 at room temperature28. Exceptionally, NaCB9H10 is reported to have the highest conductivity of ~0.03 S/cm at room temperature29. The chalcogenide glass-ceramic electrolyte, such as Na2Ga0.2Ge1.8Se4.95 has conductivity barely exceeding 10−5 S cm−1 at room temperature30. The crystalline Na3PS4 glass ceramic has conductivity of 2.62 × 10−4 S cm−1 at room temperature12, which is the best reported for a sodium sulphide conductor. The classical β-alumina electrolyte and NASICON-type crystal produced by Ceramatec possesses room-temperature conductivity of ~10−3 S cm−1, but extremely high sintering temperatures of 1800 °C are needed for fabrication3132. The present Na3.1Zr1.95Mg0.05Si2PO12 is characterized by practically useful conductivity of above 10−3 S cm−1. Application to all-solid-state sodium-sulphur batteries Discovery of the new solid electrolyte with high conductivity helps to overcome the poor mixed ionic and electronic conductivities. To reduce interfacial impedance and segregation of Na+ ions along the interface, inorganic-organic hybrid cathode can be considered. To achieve this, the immobilized ionic liquid-based Na-ion polymer electrolyte is firstly synthesized by a mechanochemical reaction. Then, the sulphur-carbon composite is synthesized through mechanochemical milling sulphur and carbon at the weight ratio of 1:1. The sulphur-carbon composite is mechanochemically milled with polymer electrolyte at the weight ratio of 1:1. Solid-state sodium batteries are assembled in a coin cell consisting of a sulphur-carbon-polymer hybrid cathode, a Na3.1Zr1.95Mg0.05Si2PO12 electrolyte and a sodium anode. Figure 6 shows galvanostatic testing results of the Na-S battery (Na/Na3.1Zr1.95Mg0.05Si2PO12/S) operated with a cut-off voltage range of 0.8–3.6 V at the current of 8.92 μA (i.e., ~0.01C rate) at ambient temperature. The initial discharge capacity is about 527 mAh g−1. This capacity is higher than those of high-temperature Na-S cells using beta-alumina as electrolyte and ambient-temperature Na-S cells with traditional sulphur-carbon composite using organic liquid electrolyte9113334. The present cell experiences a sharp decrease in capacity during the initial 10 galvanostatic cycles, with the discharge capacity fading from 527 to 160 mAh g−1 during ten cycles. Severe capacity decrease is likely to be associated with the generation of reversible sodium polysulphides that resist oxidation during subsequent charging. This phenomenon is known to be a general problem in other sulphur-based batteries (i.e., high-temperature Na-S batteries and Li-S batteries)2. Specific directed effort is required to address this fading mechanism and to enhance the cell performance. To evaluate the advantage of solid-state configuration to the liquid one, one cell is assembled with metallic sodium as anode, S-C composite as cathode, 1 M NaClO4/EC+PC (1:1 in weight) as liquid electrolyte, and glass microfiber as separator, whereas another cell using the present Na3.1Zr1.95Mg0.05Si2PO12 pellet (~1.0 mm) as electrolyte and separator is assembled. Figure 7 shows the electrochemical performance of the two types of Na-S batteries with a cut-off voltage range of 0.8–3.6 V at 1C and 5C rate. As shown in Fig. 7a,b, for the cells using liquid electrolyte and solid electrolyte respectively at 1C rate, there are no obvious discharge plateaus, but two charge plateaus at about 2.0 V and 2.4 V, which indicates a stepped oxidation reaction during charging process. The voltage profiles of solid-state cell coincide from 2nd to 5th cycle, indicating stable electrochemistry. Figure 7c reveals the highest initial capacity is ~180 mAh g−1, and the discharge capacity decays to ~64 mAh g−1 at 1C rate after 100 cycles with a capacity retention of only 36% of the cell using liquid electrolyte. For the solid-state one, the highest initial capacity is slight lower than that of liquid one, ~170 mAh g−1, but it delivers capacity of 150 mAh g−1 over 100 cycling with a capacity retention of 88%, indicating better cycling stability compared with the conventional Na-S batteries using liquid electrolyte. The Coulombic efficiency is maintained at ~100% except the first cycle for both cells. As shown in Fig. 7d, at 5C rate, the cell using liquid electrolyte delivers better initial capacity of ~84 mAh g−1, and fades mildly to ~54 mAh g−1 after 100 cycles. For the solid-state cell, the initial capacity is ~21 mAh g−1, and increase mildly to ~56 mAh g−1 after 60 cycles and ~60 mAh g−1 after 100 cycles, that is similar with the liquid one. Therefore, it is demonstrated that the Na-S cells using solid-state electrolyte can achieve better cycling stability than the liquid counterpart, because the solid-state electrolyte can efficiently depress the dissolution and shuttle of sodium polysufides in electrolyte. Discussion Structural features play a key role in delivering fast ionic conduction. The crystal structure of the present material is examined via Rietveld refinement of powder XRD data (Fig. S1 and Tables S1–S4). The structure includes ZrO6 octahedra corner-sharing with P/SiO4 tetrahedra, with the alkaline earth ions located at Zr sites. One ZrO6 octahedron is combined with six P/SiO4 tetrahedra, forming a monoclinic framework with a three-dimensional Na+ ions channels (Fig. 8a). The Na+ ions occupy three types of sites, which are coordinated by O2− ions as 6-fold Na(1) site, 8-fold Na(2) site and 5-fold Na(3) site, respectively35. Each Na(2) site connects two Na(1) sites, while each Na(1) site connects two Na(3) sites. There are no pathways among Na(2), Na(3) or Na(2) and Na(3) sites, owing to the long distances and/or polyhedra obstacles. We consider the possible efficient conduction pathway along the three-dimensional channels by selecting the shortest Na-Na hopping distances, that correspond to the lowest transport barrier36. For the Mg-doped system, the closest Na(1)-Na(2), Na(1)-Na(3), and Na(2)-Na(3) distances are 3.487 Å, 2.305 Å and 3.915 Å, respectively, which are more than twice the Na+ ionic radius (~1.02 Å). The Na(1)-Na(3) distance is the even shorter ~2.08 Å for Ca/Sr/Ba-doped systems, corresponding to approximately twice the Na+ ionic radius. This approch implies that the adjacent Na(1) and Na(3) sites may not be occupied simultaneously. The Na+ ions move toward the Na(1) vacancy, whilst, simultaneously the Na+ ions at the Na(3) sites migrate away, and vice versa. This suggests that the possible conduction pathway in monoclinic framework is the Na(2)-Na(1)-Na(3) pathway. It can be surmised that the observed increase in the ionic conductivity associated with the ionic radii of octahedrally coordinated cations, the large ionic radii increase the lattice parameters and cell volume, thus facilitating the Na+ ion mobility37. In the present materials, the unit cell parameters and cell volume increase with the substitution of alkaline earth ions for Zr, but little variation is observed for different alkaline earth ions (Fig. 8c). In fact, the lattice parameters and ionic radii do not follow a monotonic relationship, reaching a maximum near Na content of 3–3.2 per formula unit14. To jump from one site to next one, Na+ ions must pass through a bottleneck as defined by Hong14. In the monoclinic NASICON framework, the bottleneck is a pseudo-hexagonal ring consisting of alternating three ZrO6 octahedra and three P/SiO4 tetrahedra (Fig. 8b). The bottleneck size is the principal factor controlling the activation energy and ionic conductivity. West et al.38 suggested a triangle T1 defined by the three O2− ions to characterize the bottleneck size. We analyze the bottleneck in the pathway between the Na(2) and Na(1) sites using the area of triangle T1 (Fig. 8b). It can be seen that the area of triangle T1 increases with the substitution of alkaline earth ions for Zr, and decreases with the ionic radii of alkaline earth ions (Fig. 8c), indicating that the much larger alkaline earth ions narrow the bottleneck, thus decreasing the ionic conductivity. The Zr-Mg system has the largest area of triangle T1 (~6.522 Å2) that is significantly larger than that of the pure Zr system (~5.223 Å2), explaining the maximum ionic conductivity observed for the Zr-Mg system. In summary, here we demonstrate that the Na3.1Zr1.95Mg0.05Si2PO12 with NASICON phase has superior room-temperature ionic conductivity of 3.5 × 10−3 S cm−1. We report ground-breaking progress in manufacturing a solid-state room temperature Na-S battery using Na3.1Zr1.95Mg0.05Si2PO12 solid electrolyte. Initial adequate cell performance is demonstrated, and further improvement can be sought by developing hybrid positive electrodes and by achieving good electrode-electrolyte contact. Moreover, we demonstrate that the present solid-state electrolyte can efficiently depress the dissolution and shuttle of sodium polysufides which leads to better cycling stability than the liquid counterpart. The present work will help to identify new strategies for developing organic-inorganic hybrid positive electrodes and chemically stable oxide-based electrolytes for the next generation of safe and inexpensive high-performance solid state sodium batteries. Methods Preparation of Na3.1Zr1.95M0.05Si2PO12 (M = Mg, Ca, Sr, Ba) electrolytes The Na3.1Zr1.95M0.05Si2PO12 (M = Mg, Ca, Sr, Ba) were synthesized through solid-state reaction combined with mechanochemical synthesis. Firstly, The Zr1.95M0.05O3.95 solid solutions were prepared through mechanochemical reaction in a high energy ball mill for 2 h (SPEX SamplePrep 8000 M Mixer). The mixture of ZrO2 (Inframat Advanced Materials, ≥99.9%) and MO was milled by alternating 30 min of milling with 30 min in standby mode to avoid excessive heating. The solid electrolytes with the formula Na3.1Zr1.95M0.05Si2PO12 (M = Mg, Ca, Sr, Ba) were synthesized through solid-state reaction by mixing stoichiometric amounts of Na2CO3 (Sigma-Aldrich, ≥99.5%), SiO2 (Sigma-Aldrich, ≥99%), NH4H2PO4 (Sigma-Aldrich, ≥98%), and Zr1.95M0.05O3.95, and ball-milling with zirconium oxide balls for 2 h. The precursors were decomposed at 900 °C for 12 h in alumina crucibles, with repeated ball-milling for 2 h. The calcined powders were then cold pressed and sintered at 1260 °C for 16 h covered with the raw powders to avoid sodium loss. Characterization of solid electrolytes The crystal structure was analyzed by Rietveld refinement of powder XRD data (Shimadzu XRD-6000 Cu-Kα), using GSAS software. The microstructure was examined on polished surfaces of the sintered pellet using SEM (S-4300 Shimadzu). The ionic conductivities were fixed by impedance spectroscopy measurements that were performed with a Solartron 1260+1287 System, applying AC potential of 10 mV from 32 MHz to 1 Hz in Ar atmosphere. Ion-blocking electrodes were formed by Au sputtering on both surfaces of the pellet. Measurement of DC conductivity was performed using sodium-electrolyte symmetric cell with constant current density of 44 μA cm−2 at room temperature inside an Ar-filled glove box. Sodium plates (~0.22 mm thickness) were attached to both faces of the pellet (2.0 mm thickness, 9.0 mm diameter), to serve as non-blocking electrodes. DC polarization was performed to evaluate the electronic conductivity and sodium-ion transference number. A Na3.1Zr1.95Mg0.05Si2PO12 pellet (3.5 mm thickness, 9.1 mm diameter) was sputtered by Au on both surfaces and a constant voltage of 1 V was applied. Cyclic voltammetry measurements were performed using two methods. The first method was using Au/Na3.1Zr1.95Mg0.05Si2PO12 pellet/Na semi-blocking cell to perform a linear sweep from −0.2 V to 9 V vs Na+/Na with varied scan rate of 1 mV s−1. The second method was using Na/Na3.1Zr1.95Mg0.05Si2PO12/Na3.1Zr1.95Mg0.05Si2PO12-carbon/Au cell to perform a linear sweep from 0 to 9 V vs Na+/Na with scan rate of 0.1 mV s−1 according to ref. 22. To make the Na/Na3.1Zr1.95Mg0.05Si2PO12/Na3.1Zr1.95Mg0.05Si2PO12-carbon/Au cell, the Na3.1Zr1.95Mg0.05Si2PO12-carbon electrode was prepared by mixing Na3.1Zr1.95Mg0.05Si2PO12 powder, carbon black, polyvinylidene fluoride with a weight ratio of 36:54:10, and n-methylpyrrolidinone to an electrode slurry. The slurry was then casted onto the polished Na3.1Zr1.95Mg0.05Si2PO12 pellet (~1.0 mm thickness and ~9 mm diameter) and dried at 120 °C overnight, then sputtered Au, after which, metallic sodium was attached on the other side of the pellet. The Na/Na3.1Zr1.95Mg0.05Si2PO12/Na3.1Zr1.95Mg0.05Si2PO12-carbon/Au cell was assembled using CR2025 coin cell and was performed cyclic voltammetry measurements on Solartron electrochemistry workstation. Characterization of solid-state Na-S batteries A solid-state sodium battery was prepared with sulphur-carbon-polymer electrolyte hybrid material as cathode, Na3.1Zr1.95Mg0.05Si2PO12 ceramic pellet as electrolyte, sodium metal as anode. Firstly, the sulphur-carbon composite was prepared by mechanochemical milling with the sulphur to carbon weight ratio of 1:1 at 875 rpm for 5 h. The polymer electrolyte consisted of poly(ethylene oxide) (Sigma-Aldrich, 100 0000 g mol−1), NaClO4 (Sigma-Aldrich, ≥98%), SiO2 (Sigma-Aldrich, 5–15 nm particle size), 1-Ethyl-3-methylimidazolium bis(fluorosulfonyl)imide (Solvionic, H2O ≤ 20 ppm) was prepared by mechanochemical milling at 875 rpm for 1 h in a weight ratio of 0.53:0.074:0.06:1.33 in acetone. Following, the sulphur-carbon composite was added to the polymer electrolyte in a weight ratio of 1:1 and with mechanochemical milling at 875 rpm for 30 min. The slurry was then coated uniformly onto Na3.1Zr1.95Mg0.05Si2PO12 ceramic pellet (~1.2 mm thickness) and dried under vacuum at 50 °C overnight. Sodium foil was attached on the other surface of the Na3.1Zr1.95Mg0.05Si2PO12 ceramic pellet in Ar-filled glove box. Cell assembly was carried out in CR2025 coin cells. The charge-discharge measurements were conducted at a constant current of 8.92 μA (i.e., ~0.01C rate) with a cut-off voltage of 0.8–3.6 V on a MACCOR battery cycler at room temperature. To evaluate the capability of present solid-state electrolyte compared with conventional liquid electrolyte, two different configuration of Na-S cells were constructed. The first type of Na-S cells used 1 M NaClO4 in ethylene carbonate (EC)/propylene carbonate (PC) (1:1 in weight) as electrolyte and Whatman GF/A fiber as separator, and the second type of Na-S cells used the present Na3.1Zr1.95Mg0.05Si2PO12 ceramic pellet (~1.0 mm thickness) as electrolyte and separator. The sulphur-carbon composite (1:1 in weight) was mixed with Super P conductive carbon (TIMCAL Ltd.) and polyvinylidene fuoride (PVDF, Sigma) at a weight ratio of 8:1:1 in N-methylpyrrolildone (NMP, Sigma) solvent to form uniform slurries and then was coated on Al foils to prepare the cathode. The cells were assmbled in Ar-filled glove box with metallic sodium as anode. To assemble cells using solid-state electrolyte, sodium was attached on a side of polished pellet and a very little drop of liquid electrolyte was used as a buffer between solid-state electrolyte and cathode. The charge-discharge measurements were conducted at a constant current of 1C and 5C rate with a cut-off voltage of 0.8–3.6 V. Additional Information How to cite this article: Song, S. et al. A Na+ Superionic Conductor for Room-Temperature Sodium Batteries. Sci. Rep. 6, 32330; doi: 10.1038/srep32330 (2016). Supplementary Material Supplementary Information This research is supported by National University of Singapore, and the National Research Foundation, Prime Minister’s Office, Singapore under its Competitive Research Programme (CRP Award No. NRF-CRP 8-2011-04). This research is supported by Chongqing University, and the Fundamental Research Funds for the Central Universities (No. 0241005202014, No. 0903005203403). Author Contributions S.S., H.M.D., A.M.K., N.H. and L.L. conceived the ideas. S.S. performed the synthesis and characterization of materials and batteries. S.S. and L.L. analysed the data and wrote the paper. All authors discussed and commented on the paper. Figure 1 XRD patterns of (a) solid solutions of ZrO2 and MO (M = Mg, Ca, Sr, Ba) after high energy ball milling for 2 h. (b) Na3.1Zr1.95M0.05Si2PO12 (M = Mg, Ca, Sr, Ba) sintered at 1260 °C for 16 h. Figure 2 Characterization of Na3.1Zr1.95M0.05Si2PO12 (M = Mg, Ca, Sr, Ba) electrolytes. (a) Impedance plot of Na3.1Zr1.95Mg0.05Si2PO12 measured in Ar at room temperature. The inset is described from 12 MHz to 1 Hz. (b) Time dependence of dc current for Na3.1Zr1.95Mg0.05Si2PO12 pellet with applying a constant voltage of 1 V on the blocking electrodes. (c) Comparison of room-temperature conductivities of Na3.1Zr1.95M0.05Si2PO12. (d) SEM cross-section image of Na3.1Zr1.95Mg0.05Si2PO12. Figure 3 Cyclic voltammetry of Na3.1Zr1.95Mg0.05Si2PO12: (a) cyclic voltammetry of Au/Na3.1Zr1.95Mg0.05Si2PO12 pellet/Na cell from −0.2 to 9 V at scan rate of 1 mV s−1, (b) cyclic voltammetry of Au/Na3.1Zr1.95Mg0.05Si2PO12 pellet/Na3.1Zr1.95Mg0.05Si2PO12-carbon/Na cell from 0 to 9 V at scan rate of 0.1 mV s−1, and (c) Plot of peak current density vs. scan rate from the cyclic voltammetry. The inset is cyclic voltammetry curves at scan rate of 0.01 mV s−1 and 0.1 mV s−1. Figure 4 Galvanostatic cycling of symmetrical cells with sodium electrodes and Na3.1Zr1.95Mg0.05Si2PO12 electrolyte at the current density of 44 μA cm−2. Figure 5 Temperature-dependent ionic conductivity of Na3.1Zr1.95Mg0.05Si2PO12 compared with other reported Na-ion conductors. ■: Na3.1Zr1.95Mg0.05Si2PO12 values. The solid line represents linearly fitted data. Figure 6 Charge-discharge profiles of a solid-state sodium battery (Na/Na3.1Zr1.95Mg0.05Si2PO12/S) at ambient temperature. The batteries were examined at a constant current of 8.92 μA (i.e., ~0.01C rate) with a cut-off voltage of 0.8–3.6 V. Figure 7 Electrochemical performance of two types of Na-S batteries using liquid electrolyte and solid-state electrolyte: (a) voltage profiles of cells using liquid electrolyte at 1C rate, (b) voltage profiles of cells using solid electrolyte at 1C rate, and (c) cycling performance of the two types of cells at (c) 1C rate and (d) 5C rate. Figure 8 Refined crystal structure of Na3.1Zr1.95Mg0.05Si2PO12. (a) Polyhedral drawing of the unit cell of Na3.1Zr1.95Mg0.05Si2PO12. Na(1) ions: black spheres, Na(2) ions: yellow spheres, Na(3) ions: purple spheres. (b) A bottleneck of Na3.1Zr1.95Mg0.05Si2PO12 consisting of alternating three ZrO6 octahedra and three P/SiO4 tetrahedra. The triangle T1 is outlined. The Na(1), Na(2) and Na(3) ions are located below and above the bottleneck. (c) Lattice parameter, volume of unit cell and area of T1 of the Na3Zr2Si2PO121436 and Na3.1Zr1.95M0.05Si2PO12 (M = Mg, Ca, Sr, Ba). ==== Refs Hartmann P. . A rechargeable room-temperature sodium superoxide (NaO2) battery . Nat. Mater. 12 , 228 –232 (2013 ).23202372 Kundu D. , Talaie E. , Duffort V. & Nazar L. F. The emerging chemistry of sodium ion batteries for electrochemical energy storage . Angew. Chem. Int. Ed. 54 , 3431 –3448 (2015 ). Yabuuchi N. , Kubota K. , Dahbi M. & Komaba S. Research development on sodium-Ion batteries . Chem. Rev. 114 , 11636 –11682 (2014 ).25390643 Baek S. W. , Lee J. M. , Kim T. Y. , Song M. S. & Park Y. Garnet related lithium ion conductor processed by spark plasma sintering for all solid state batteries . J. Power Sources 249 , 197 –206 (2014 ). Wei T. , Gong Y. H. , Zhao X. & Huang K. An all-ceramic solid-state rechargeable Na+-battery operated at intermediate temperatures . 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3133410.1038/srep31334ArticleIn Situ and Ex Situ TEM Study of Lithiation Behaviours of Porous Silicon Nanostructures Shen Chenfei 1*Ge Mingyuan 12*Luo Langli 3Fang Xin 1Liu Yihang 4Zhang Anyi 1Rong Jiepeng 1Wang Chongmin 3Zhou Chongwu a141 Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089, United States2 National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, New York 11973, United States3 Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States4 Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089, United Statesa chongwuz@usc.edu* These authors contributed equally to this work. 30 08 2016 2016 6 3133404 02 2016 05 04 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/In this work, we study the lithiation behaviours of both porous silicon (Si) nanoparticles and porous Si nanowires by in situ and ex situ transmission electron microscopy (TEM) and compare them with solid Si nanoparticles and nanowires. The in situ TEM observation reveals that the critical fracture diameter of porous Si particles reaches up to 1.52 μm, which is much larger than the previously reported 150 nm for crystalline Si nanoparticles and 870 nm for amorphous Si nanoparticles. After full lithiation, solid Si nanoparticles and nanowires transform to crystalline Li15Si4 phase while porous Si nanoparticles and nanowires transform to amorphous LixSi phase, which is due to the effect of domain size on the stability of Li15Si4 as revealed by the first-principle molecular dynamic simulation. Ex situ TEM characterization is conducted to further investigate the structural evolution of porous and solid Si nanoparticles during the cycling process, which confirms that the porous Si nanoparticles exhibit better capability to suppress pore evolution than solid Si nanoparticles. The investigation of structural evolution and phase transition of porous Si nanoparticles and nanowires during the lithiation process reveal that they are more desirable as lithium-ion battery anode materials than solid Si nanoparticles and nanowires. ==== Body With ever-growing demands for high-performance power sources, especially in portable electronics and electrical vehicles (EV), tremendous research interests have been stimulated toward developing the next generation of lithium-ion batteries (LIBs) with high capacity, long cycle life, and low cost12. Compared with carbonaceous anodes (372 mAh/g for LiC6) used in commercial LIBs, silicon (Si) has a large theoretical gravimetric capacity of ~4200 mAh/g and volumetric capacity of ~8500 mAh/cm3, and therefore has been considered as one of the most promising anode materials for the next-generation LIBs34. However, Si experiences a dramatic volume change (>300%) during the lithium alloying/dealloying processes, and for crystalline Si (c-Si) this large volume expansion is accompanied with dramatic anisotropic expansion567. This change not only causes severe pulverization of the material but also induces electrical disconnection of the active material from the current collector, resulting in performance degradation of the battery if Si is used as the anode. To minimize the extent of volume change, tremendous efforts have been made on the synthesis of novel nanostructured Si materials, such as nanowires89, nanotubes101112, hollow spheres, and core-shell structures1314. Recently, three-dimensional porous structured Si has attracted significant attention. The pre-formed nanopores in the Si can provide a large space to accommodate the volume expansion, and therefore help to maintain the structure integrity when lithium alloys with Si. Moreover, this three-dimensional porous structure provides large surface area of the material to be accessible to the electrolyte and thus a short diffusion length for lithium ions to transport from electrolyte to Si, which facilitates the lithium alloying/dealloying processes at high current rates151617181920. To understand the lithiation/delithiation process of Si, it is of importance to directly observe the structural and chemical evolution during the process and thus correlate with the battery properties. Over the past few years, tremendous progress has been made toward developing methodologies for in situ observation of structural and chemical evolution of electrodes used for LIBs. Among them, in situ transmission electron microscopy (TEM) has been particularly informative and has revealed important features of the lithiation/delithiation process of Si nanoparticles and nanowires on phase transition, structural evolution, and lithiation kinetics672122232425262728. Specifically, both c-Si nanoparticles and nanowires are reported to transform to amorphous LixSi (a-LixSi) via electrochemical-driven solid-state amorphization. With further lithiation, a-LixSi transforms to crystalline Li15Si4 (c-Li15Si4)7212226. The fracture behaviour of c-Si nanoparticles during the first lithiation is reported to be particle-size-dependent. The critical fracture diameter is 150 nm, below which cracks do not form, and above which surface cracking and particle fracture takes place upon lithiation7. In comparison, the critical fracture diameter of amorphous Si (a-Si) particles is reported to be up to 870 nm. In addition, the lithiation reaction velocity of a-Si is approximately constant and does not slow as in c-Si, which suggests different stress evolution during lithiation and implies that a-Si may be a more desirable active material than c-Si27. These studies have led to fundamental understanding of the lithiation/delithiation process of Si nanoparticles and nanowires; however, these studies cannot provide direct explanation of better electrochemical performance achieved by newly reported nanostructured Si than solid Si nanoparticles and nanowires. Moreover, most studies only focus on the first several lithiation/delithiation cycles of Si, but do not look into post-cycling analysis of the structural evolution of Si. In this work, we study the phase transition and structural evolution of both porous Si nanoparticles and porous Si nanowires by in situ and ex situ TEM. The in situ TEM observation of lithiation process of porous Si nanoparticles reveals that the lithiation proceeds in an end-to-end manner, which is different from the surface-to-center manner for solid Si nanoparticles under the same experimental condition. In addition, much larger critical fracture diameter is achieved in porous Si particle than previously reported for c-Si and a-Si particles. Another interesting feature in the lithiation process of porous Si nanoparticles and nanowires is that a-LixSi does not transform to c-Li15Si4 even after full lithiation, which is distinct from that of solid Si nanoparticles and nanowires. The distinct lithiation behaviours of porous Si nanoparticles and nanowires are attributed to their interconnected three-dimensional porous structure, which is built up by numerous small domains. First-principle molecular dynamic simulation was conducted to investigate the effect of domain size on the phase stability of c-Li15Si4, which confirms the effect of nanostructure on phase transition. Moreover, structural evolution of porous and solid Si nanoparticles under successive lithiation/delithation cycles are compared through ex situ TEM, which confirms that porous Si is a more desirable anode material for LIBs than solid Si. Results In this work, the porous Si nanoparticles and nanowires were prepared according to our previous reports1518. To prepare porous Si nanoparticles, metallurgical Si was used as the starting material. After milling to submicron particles, the Si was etched in Fe(NO3)3/HF etchant to obtain porous structure. To prepare porous Si nanowires, a boron-doped Si wafer was used as the starting material and AgNO3/HF was used as the etchant to obtain the porous structure. To prepare Si nanowires without pores, a pure Si wafer without doping was used as the starting material. After etching by AgNO3/HF, Si nanowires without pores were obtained. For comparison, both Si nanoparticles with and without pores, and Si nanowires with and without pores are characterized by in situ TEM. The in situ TEM nanobattery setup is schematically shown in Fig. 1a. Figure 1b–g and Supplementary Movie 1 show the lithiation process of a ball-milled Si particle with largest diameter of ~950 nm and smallest diameter of ~630 nm. The ball-milled Si was prepared by ball-milling metallurgical Si and then being washed with HF and deionized water (DI-H2O) to remove the surface oxide layer (Supplementary Fig. 1a,b). After the Li2O/Li electrode contacted the ball-milled Si, a potential of −2 V was applied to the Cu electrode with respect to Li2O/Li electrode to initiate the lithiation process. As shown in Fig. 1c, a bump (indicated by the red arrow) comes out from the particle after lithiation for only 28 s, which is due to anisotropic expansion of Si particles. Further lithiation results in the change of contrast of the particle as shown in Fig. 1d. The gray LixSi shell and dark Si core indicates that lithium ions flow from surface to center of the particle in the radial direction. As the particle size is well above the reported critical fracture diameter of c-Si (150 nm), cracks (indicated by the blue arrows) start to form in the particle after lithiation for only 120 s (Fig. 1d). After 468 s of lithiation, the particle fractures into several pieces (Fig. 1g). The selected area electron diffraction (SAED) pattern in Fig. 1h exhibits rings made up of discrete spots, indicating nanosized polycrystalline nature of the ball-milled Si particle before lithiation. The ball-milled Si particle is made up of nanosized single crystalline Si particles, which results in the anisotropic expansion of the ball-milled Si particle during lithiation process. After full lithiation, the particle transforms to polycrystalline Li15Si4 as indicated by Fig. 1i. The Li2O phase in Fig. 1i is from the Li2O/Li electrode in contact with the particle. Figure 2 shows the lithiation behaviour of a typical porous Si particle. As illustrated in Fig. 2a and Supplementary Fig. 1c,d, numerous pores distribute uniformly throughout the whole porous Si particle after electroless etching of the ball-milled Si. To investigate the fracture behaviour of porous Si particle during the lithiation process, we chose a large particle with diameter up to 1.52 μm for in situ TEM observation. Figure 2b–f demonstrate the TEM images of the porous Si particle during the lithiation process. From the TEM images and Supplementary Movie 2, the volume expansion of the particle initiates in the lower right corner and then proceeds to the top left corner of the particle. This indicates that the lithium ions flow in an end-to-end manner, which is distinct from the surface-to-center lithiation manner observed in both crystalline and amorphous Si particles727. To clarify the lithium propagation manner of porous Si particle, the lithiation behaviour of another porous Si particle was characterized by in situ TEM with higher magnification as shown in Supplementary Fig. 2a–d and Supplementary Movie 3. The lithiation front is marked by the red dotted line in Supplementary Fig. 2b–d, which propagates from lithium source to the other end of the particle. This observation is consistent with Fig. 2 and confirms the end-to-end lithiation manner of porous Si particle. After lithiation for 1121 s, the volume expansion of the particle almost ended (Fig. 2e). To ensure full lithiation of the particle, the −2 V potential was applied to the Cu electrode for another ~200 s and no obvious volume expansion of the particle was observed during this period. After lithiation for 1335 s, no crack was observed in the particle and the diameter of the particle increased to 2.05 μm, corresponding to a volume expansion of 145% (Fig. 2f). The volume expansion is far less than the theoretical 300% for solid Si particles after full lithiation. This is attributed to the porous structure of the particle, which provides large space to accommodate the volume expansion by possible inward expansion during the lithiation process. The SAED patterns of the particle were obtained before lithiation and after full lithiation as shown in Fig. 2g,h, respectively. Before lithiation, the porous Si particle is polycrystalline as shown in Fig. 2g. After full lithiation (Fig. 2h), the SAED pattern indicates that a-LixSi (marked by the blue arc) and c-Li15Si4 (indicated by the green arrow) coexist629. The rings from Li2O/Li electrode are marked by the yellow arcs. This observation contrasts the SAED pattern of the fully lithiated ball-milled Si, which exhibits only c-Li15Si4 phase as shown in Fig. 1i. We note that the porous Si and ball-milled Si particles are prepared from the same starting material. Taking into account that the most distinguishable difference between the porous Si and the ball-milled Si is their microstructures, we believe that the porous structure helps to prevent the formation of c-Li15Si4 phase during the first lithiation process, and we will discuss it in detail later. A brief summary of the lithiation behaviours of solid and porous Si particles reveal that lithiation proceeds in a surface-to-center manner for solid Si particles while in an end-to-end manner for porous Si particles. Figure 3 schematically illustrates the different lithiation manners of solid and porous Si particles. As lithium diffuses faster in the surface of Si than that in the bulk, a-LixSi shell will form in ball-milled Si particle once lithiation occurs (Fig. 3b). As the a-LixSi shell thickens, cracks will form on the surface of the particle (Fig. 3c), which lead to final pulverization of the ball-milled Si particle as shown in Fig. 3d. The situation is different in porous Si particle, which is made up of numerous small domains (Fig. 3e) and possesses complex surface topological feature. The large and complex surface of porous Si lags the propagation of lithium in the whole particle. As a result, lithium tends to proceed from the lithium source and propagate through the whole particle in an end-to-end manner, even though lithium may proceed in a surface-to-center manner in each domain as shown in Fig. 3f,g. Because each domain in porous Si is in several nanometers, which is much smaller than the critical fracture diameter of solid Si, no crack will form during lithiation process (Fig. 3h). In addition, the porous structure provides large space to accommodate the volume expansion by possible inward expansion of each domain, leading to smaller volume change of the porous Si particle than solid Si particle. To further characterize the structural evolution of ball-milled Si and porous Si, ex situ TEM images and corresponding SAED patterns of the two samples were obtained before cycling and after being charge-discharged for 1 cycle, 10 cycles, and 50 cycles in Li-Si cells in the voltage window of 0.01–2 V (vs. Li/Li+) at a current density of 400 mA/g as shown in Fig. 4a–h. According to previous reports, the cutoff voltage range plays an important role to induce pore evolution in Si. Specifically, a large voltage window of 0.05-1 V would lead to porous structure of Si while Si cycled in a small voltage window of 0.17-0.6 V retains its original structure well after cycling30. In this work, we cycled the Li-Si cells in large voltage window of 0.01–2 V (vs. Li/Li+) so that we can study the capability of porous Si and ball-milled Si to suppress pore evolution during the cycling process. Before cycling, both ball-milled Si and porous Si are polycrystalline as indicated by the inset SAED patterns in Fig. 4a,e, respectively. After being charge-discharged for different cycles, both ball-milled Si and porous Si transform to amorphous structure as indicated by the inset SAED patterns in Fig. 4b–d,f–h. To quantitatively investigate the pore evolution processes of the two samples, pore size distributions were obtained based on statistical analysis of TEM images. Before cycling, the surface of ball-milled Si is smooth as shown in Fig. 4a. For porous Si particles, the pores are clearly resolved by the contrast in the image in Fig. 4e, and the mean diameter is 9.9 ± 0.1 nm based on the pore size distribution diagram in Fig. 4i. After being charge-discharged for only 1 cycle, nanopores are observed to form on the periphery of the ball-milled Si as indicated by the dark/light contrast in Fig. 4b, which is due to inelastic deformation of Li/Si during the lithiation/delithiation process30. On the contrary, the porous Si particle retains its original porous structure well as shown in Fig. 4f. This is confirmed by the pore size distribution diagram of two samples in Fig. 4j. The mean diameter of newly-formed pores in the ball-milled Si is 3.8 ± 0.1 nm. While for porous Si, the mean diameter of pores is 10.9 ± 0.1 nm, which is close to its original value before cycling. After cycling for 10 cycles, the surface of the ball-milled Si particles gets much rougher (Fig. 4c), while the pore size increase of porous Si is still not significant (Fig. 4g). As shown in Fig. 4k, the mean diameter of the pores in the ball-milled Si increases drastically to 20.1 ± 0.1 nm, corresponding to a 429% increase compared with that after 1 cycle. Similar to Ostwald ripening in which particles agglomerate to reduce surface energy, this increase of pore size with cycling is equivalent to agglomeration of pores so that the surface energy of the particle can be reduced31. In contrast to the significant pore size increase in ball-milled Si, the mean diameter of pores in porous Si is only 12.8 ± 0.1 nm after 10 charge-discharge cycles, corresponding to only 29% increase compared with that before cycling. After cycling for 50 cycles, pores in both ball-milled Si and porous Si increase in size as shown in Fig. 4d,h. According to Fig. 4l, the mean diameter of pores for ball-milled Si is 41.8 ± 0.1 nm. However, the mean diameter of pores for porous Si is 36.0 ± 0.1 nm, which is still smaller than that of ball-milled Si. As the pore evolution is due to inelastic deformation of Li/Si during lithiation/delithiation process, for solid Si nanoparticles, the inelastic deformation is severe due to its large volume change during lithiation/delithiation process. For porous Si nanoparticles, however, the domains of the particle are observed to expand into the void space in the particle based on the observation in Supplementary Fig. 2a–d that the contrast of the particle from the porous structure becomes obscure and uniform during the lithiation process. This lithiation behaviour of porous Si particle results in smaller volume change of the particle and stress relaxation in each domain. The stress relaxation prevents the stress in porous Si nanostructures from exceeding the elastic limit of Si, and thus suppresses the pore evolution in porous Si nanostructures. The formation and size increase of pores in ball-milled Si particles would cause significant volume expansion of particles as they transform from solid particles to totally porous structure. However, with pre-formed pores, the volume change of porous Si particles before and after cycling is much less significant than that of ball-milled Si particles. This difference in particle volume change during cycling results in the different cycling performance of the two electrodes. Figure 4m shows the cycling performances of ball-milled Si and porous Si electrodes tested in the voltage window of 0.01–2 V (vs. Li/Li+) at a current density of 400 mA/g. As shown in the figure, the capacity of ball-milled Si decays rapidly in the initial 10 cycles and then decreases in constant rate. This corresponds to the TEM observation that pore formation in ball-milled Si particles takes place in early cycles, which causes the particles to lose electrical contact from the current collector and thus leads to loss of active materials for capacity contribution. The volume change of porous Si during cycling is much less than that of ball-milled Si; however, the relatively large surface area of porous Si as compared to ball-milled Si would lead to more severe solid electrolyte interface (SEI) formation on porous Si particles, which would also cause capacity decay in the initial cycles. For this reason, it is essential to apply coating on porous Si particles (e.g. carbon coating) to mitigate the SEI formation and thus to further improve the cyclability of porous Si electrodes171819. In order to further demonstrate whether the microstructure or the starting material of porous Si would affect its lithiation behaviour, we prepared solid Si nanowires and porous Si nanowires according to our previous report using Si wafers as the starting material15. Figure 5 and Supplementary Movie 4 show the lithiation behaviour of a typical solid Si nanowire with diameter of ~120 nm and length of ~600 nm. The Si nanowire before lithiation is shown in Fig. 5a and Supplementary Fig. 3a,b. After lithiation for 103 s (Fig. 5d), the gray shell and dark core of the nanowire reveal that the lithiation of Si nanowire occurs through the formation of a-LixSi shell and Si core structure, which is due to the faster lithium diffusion rate on the nanowire surface than that in the center. After lithiation for 150 s, the volume expansion of the nanowire almost ended (Fig. 5e). To ensure full lithiation of the nanowire, the −2 V potential was applied to the Cu electrode for another ~130 s and no obvious volume expansion of the nanowire was observed during this period. After lithiation for 285 s, no crack was observed in the nanowire (Fig. 5f). This is in agreement with a previous report, which demonstrates that the critical diameter for pulverization of Si nanowire is in the regime of 220–260 nm32. The SAED pattern of the Si nanowire before lithiation (Fig. 5g) reveals its polycrystalline nature. After lithiation for 285 s, the SAED pattern of the nanowire (Fig. 5h) indicates that it has transformed to the c-Li15Si4 phase, which is similar to the result of the ball-milled Si particle in Fig. 1i. The lithiation behaviour of a porous Si nanowire bundle consisting of several porous Si nanowires was also examined by in situ TEM as demonstrated in Fig. 6 and Supplementary Movie 5. As shown in Fig. 6a and Supplementary Fig. 3c,d, the nanowires obtain highly porous structure with pore diameter and wall thickness of ~8 nm before lithiation. The single nanowire beside the nanowire bundle in Fig. 6a acts as the lithium diffusion path during the lithiation process. Figure 6b–g demonstrate the lithiation process of the porous Si nanowire bundle, from which we can find that the contrast of the nanowires from the porous structure becomes obscure and uniform during the process. This indicates that the a-LixSi expands into the void space in the nanowires, which helps to minimize the volume expansion of the nanowires. The lithiation front is marked by the red dotted line in Fig. 6b–e, which also indicates the end-to-end lithiation manner similar to that of porous Si particle. This observation demonstrates that the explanation of porous Si particle lithiation manner in Fig. 3 also applies to porous Si nanowires. After lithiation for 823 s, lithium was observed to diffuse out of the nanowire bundle as indicated by the red arrow in Fig. 6f, indicating that the lithiation process was complete. To ensure full lithiation, the −2 V potential was applied to the Cu electrode for another ~140 s and no obvious volume expansion of the nanowire bundle was observed during this period. After lithiation for 964 s, no crack was observed in the nanowire bundle (Fig. 6g). Figure 6h shows the SAED pattern of the nanowire bundle before lithiation, which reveals its polycrystalline nature. After lithiation for 964 s, the SAED pattern of the porous Si nanowire bundle (Fig. 6i) demonstrates that it has transformed to a-LixSi (marked by the blue arc). This observation contrasts the SAED pattern of the fully lithiated solid Si nanowire, which exhibits only c-Li15Si4 phase as shown in Fig. 5h. A brief summary of the lithiation behaviours of porous Si and solid Si nanostructures reveal that after full lithiation, solid Si nanostructures transform to c-Li15Si4 while porous Si nanostructures transform to a-LixSi. The porous Si nanostructures are made up of small Si domains as shown in Supplementary Figs 1d and 3d, while the domain of solid Si nanoparticle or solid Si nanowire is the whole nanoparticle or whole nanowire due to their solid structures. We believe that the different sizes of the domains of porous Si and solid Si lead to their different phase transition behaviours. To further illustrate the effect of domain size on the resultant phase after lithiation, first-principle molecular dynamic simulation was performed to study the structure stability of nanosized c-Li15Si4 particle. The simulated nanoparticle was constructed by 2 × 2 × 2 Li15Si4 crystalline supercells, which is composed of 128 Si atoms and 480 Li atoms, and corresponds to the size of 2 nm in three dimensions. Periodic boundary condition is applied in the simulation, and the empty space between Li15Si4 particles is set larger than 1 nm to exclude the mutual interaction of atoms from neighbouring particles. First-principle calculations were performed using the VASP code density functional theory (DFT) calculations in generalized gradient approximation (GGA) with the Perdew-Burke-Ernzerhof (PBE) function used to calculate the force among atoms3334. Molecular dynamic simulation was carried out at 300 K with a time step of 1 fs interval. Figure 7a–e show the structural evolution of Li15Si4 nanoparticle from the initial crystal to a disordered structure after 400 fs simulation. The yellow atoms are Si, and blue atoms are Li. At the early stage of the simulation (e.g. 100 fs), it is clear to see that the surface atoms are the first to deviate from their original positions due to the lack of symmetric force potential at the particle surface (Fig. 7b). In the following simulation, cascaded breakdown of the periodic force potential leads to the structure disordering from outer surface to the inner part of particle. After 400 fs simulation, the particle turns to an amorphous structure (Fig. 7e). To semi-quantify the structure amorphization, the radial distribution function (RDF) of Si-Si pairs was calculated and shown in Fig. 7f. At the initial stage (0–100 fs), the sharp peaks in RDF illustrate the well-defined crystal structure. However, after 400 fs simulation, peaks at large Si-Si distance are largely smoothed, indicating the disappearance of ordered atomic arrangement. The small peak showing up at 2.5 Å corresponds to the distance of Si-Si in the amorphous Si structure, which further demonstrates the destroying of crystalline Li15Si4 structure. Due to the constrained computation resource for first-principle molecular dynamic simulation of large-size particles, we adopted classical molecular dynamic simulation to characterize the structure stability of c-Li15Si4 particles with the same initial crystal structure as 2 nm particle (Fig. 7a) while with larger diameter of 6 nm, 8 nm, 10 nm, and 12 nm. After 400 fs simulation, the atomic structures and morphologies of the Li15Si4 particles are illustrated in Supplementary Fig. 4. The yellow atoms are Si, and blue atoms are Li. Periodic boundary condition was used with particle-to-particle distance larger than 5 nm to eliminate the mutual interaction. Simulation were conducted by using the LAMMPS software code35, and a second nearest neighbour (2NN) modified embedded atom method (MEAM) potential was used to account for the atomic interaction in Li-Si system36. Based on the comparison of enlarged images in Supplementary Fig. 4a–d, it is found that in 6 nm Li15Si4 particle (Supplementary Fig. 4a), the surface of the particle is in amorphous structure and the core atoms have lost their initial crystalline arrangement. In 8 nm particle, however, the crystallinity of the core increases compared with that of 6 nm particle even though the surface atoms in the 8 nm particle still rearrange in amorphous structure (Supplementary Fig. 4b). Similar trend is observed in 10 nm particle (Supplementary Fig. 4c) and when particle size increases to 12 nm, the crystallinity of the core is the highest and the crystalline volume is the largest among four particles even though the surface of 12 nm particle still tends to be amorphous (Supplementary Fig. 4d). Generally speaking, the trend is that as the particle size increases, the crystallinity in the core of the particles and the crystalline volume in the particles also increase. However, due to lack of symmetric force potential in the surface, the surface atoms in the particles always tend to deviate from their original positions and thus rearrange in amorphous structure. This simulation result further supports our conclusion that the small domains in porous Si nanostructures help to suppress c-Li15Si4 formation during the first lithiation process. Besides, this explains why some diffraction spots of c-Li15Si4 show up in Fig. 2h, which may be due to the formation of c-Li15Si4 in the cores of some large-size domains in the porous Si particle after full lithiation. For porous Si nanowire, however, only a-LixSi forms after full lithiation (Fig. 6i), which is possibly due to the smaller size of domains in porous Si nanowires than that in porous Si nanoparticles as we compare the domains marked in Supplementary Figs 1d and 3d. The formation of c-Li15Si4 during the first lithiation process is reported to be detrimental to the cycle life of Si-based LIBs and a cutoff voltage higher than 0.05 V is usually selected to suppress the formation of c-Li15Si4 at low potential37. Here, we report that in addition to the low cutoff voltage, the nanoporous structure can also suppress the formation of c-Li15Si4 during first lithiation process due to the effect of domain size, which helps to achieve the excellent cycling performances of porous Si nanostructures. Conclusion In conclusion, we have applied in situ and ex situ TEM to study the structural evolution and phase transition of porous Si nanoparticles and nanowires and have compared their behaviours with solid Si nanoparticles and nanowires. The critical fracture diameter of porous Si particles reaches up to 1.52 μm, which reveals its better capacity to accommodate volume expansion during the lithiation process. In addition, the porous Si nanoparticles and nanowires transform to the a-LixSi phase after full lithiation in contrast to the c-Li15Si4 phase for solid Si nanoparticles and nanowires, which is due to small Si domains in porous Si nanoparticles and nanowires as revealed by the first-principle molecular dynamic simulation. Finally, ex situ TEM observation of porous Si nanoparticles and solid Si nanoparticles reveal that porous Si nanoparticles obtain better capability to suppress pore evolution than solid Si nanoparticles during the cycling process. The better capabilities of porous Si nanostructures to accommodate volume expansion, to suppress c-Li15Si4 formation during the first lithiation process, and to suppress pore evolution during cycling make them more desirable lithium-ion battery anode materials than solid Si nanostructures. Methods Materials preparation Synthesis of porous Si particles: Porous Si particles were synthesized according to our previous report18. Specifically, metallurgical Si particles were ground to fine powder using ball-milling operated at grinding speed of 1200 rpm for 5 hours. After that, the Si particles were soaked in a ferric etchant containing 0.03 M Fe(NO3)3 and 5 M HF under continuous stirring for 2 hours. The precipitates containing porous Si particles were then collected and washed with ethanol and DI-H2O. After drying at 90 °C in air for 6 hours, the particles were collected for further use. Synthesis of ball-milled Si particles: Metallurgical Si particles were ground to fine powder using ball-milling operated at grinding speed of 1200 rpm for 5 hours. The Si powder was then washed with HF and DI-H2O successively to remove surface oxide layer. After drying at 90 °C in air for 6 hours, the particles were collected for further use. Synthesis of porous Si nanowires: Porous Si nanowires were synthesized according to our previous report15. Specifically, boron-doped Si wafers (resistivity <5 mΩ·cm) were immersed in an etchant solution containing 0.02 M AgNO3 and 5 M HF for 3 h. After being washed with DI-H2O, concentrated HNO3, and DI-H2O again, sequentially, porous Si nanowires were collected by scratching the wafers using a blade. Synthesis of solid Si nanowires: Si wafers without doping were immersed in an etchant solution containing 0.02 M AgNO3 and 5 M HF for 3 h. After being washed with DI-H2O, concentrated HNO3, and DI-H2O again, sequentially, solid Si nanowires were collected by scratching the wafers using a blade. Preparation of Si-based electrodes: The active material can be either porous Si nanoparticles or ball-milled Si nanoparticles. To prepare electrodes, active Si material was first mixed with carbon black and alginic acid sodium salt with mass ratio of 7:2:1 in water to form uniform slurry. The slurry was coated on copper foil and then dried at 90 °C in air for 6 hours. Electrochemical measurements For battery measurements, CR2032 coin cells were assembled using lithium foil as counter/reference electrode and Celgard 2400 as separator. The prepared Si-based electrodes were used as working electrodes. The electrolyte was 1 M LiPF6 in dimethyl carbonate (DMC)/fluoroethylene carbonate (FEC), 1:1 by volume. The galvanostatic charge-discharge test was carried out in the voltage window of 0.01–2 V (vs. Li/Li+) at a current density of 400 mA/g. In situ TEM characterization The experimental setup is schematically illustrated in Fig. 1a. The in situ TEM characterization was conducted using a nanobattery configuration with Si (ball-milled Si nanoparticles, porous Si nanoparticles, solid Si nanowires, or porous Si nanowires) as the working electrodes, Li as the reference electrode, and Li2O as the solid electrolyte. All the in situ electrochemical tests were conducted in a Titan 80–300 scanning transmission electron microscope (STEM) operated at 300 kV with a Nanofactory TEM scanning tunneling microscopy (STM) holder. To assemble the nanobattery, a Cu rod and a W rod were firstly cut to produce clean and fresh cross section. Si was randomly attached to Cu rod as the working electrode by directly touching Si powder with the Cu rod. After that, the holder was transferred to Ar-filled glovebox, in which the W rod was used to scratch the Li metal surface to fetch some fresh Li. A conformal coating layer of Li on one end of the W rod served as the reference electrode and lithium source. The W rod was then mounted onto the holder by a screw for reliable mechanical and electrical connection. The entire assembly was then transferred to the microscope column within a sealed plastic bag. The lithium metal was only exposed to air during the insertion of the TEM holder into the microscope column, which is typically about 2 s. During this short period of air exposure, the surface of the lithium metal was oxidized to Li2O, which acts as the solid electrolyte for the function of the nanobattery. To initiate lithiation process, a bias of −2 V was applied on the Si electrode against the Li electrode to promote Li ion transport through the Li2O layer. Ex situ TEM characterization To characterize the structural evolution of ball-milled Si nanoparticles and porous Si nanoparticles after different charge-discharge cycles, the Li-Si cells were cycled in the voltage window of 0.01–2 V (vs. Li/Li+) at a current density of 400 mA/g, and were then disassembled at delithiated state after different cycles inside Ar-filled glovebox. The active materials from the electrodes were then washed with acetonitrile and 0.5 M H2SO4 to remove the residual electrolyte and lithium salts. After that, the active materials were washed with DI-H2O and ethanol, and finally dried at 90 °C in air for 6 hours before ex situ TEM characterization. Transmission electron microscope (JEOL, JEM-2100F) was used for ex situ TEM characterization in the paper. The pore size distributions were obtained based on statistical analysis of TEM images. For each sample, 200 pores were selected from TEM images and the largest diameter of each pore was measured for statistical analysis. Additional Information How to cite this article: Shen, C. et al. In Situ and Ex Situ TEM Study of Lithiation Behaviours of Porous Silicon Nanostructures. Sci. Rep. 6, 31334; doi: 10.1038/srep31334 (2016). Supplementary Material Supplementary Information Supplementary Movie 1 Supplementary Movie 2 Supplementary Movie 3 Supplementary Movie 4 Supplementary Movie 5 A portion of the TEM images used in this article were generated at the Center for Electron Microscopy and Microanalysis, University of Southern California. M.G. finished the research reported in this paper at University of Southern California, and contributed to discussions after he joined Brookhaven National Laboratory. M.G. acknowledged the support of Brookhaven National Laboratory, which was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-SC0012704. C.W. was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, Subcontract No. 6951379 under the Batteries for Advanced Battery Materials Research (BMR). The in situ TEM work was conducted in the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL), a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at PNNL. Author Contributions C.S. and M.G. contributed equally to the work. C.S. and M.G. conceived the idea and carried out the synthetic experiments. L.L. and C.W. carried out the in situ TEM characterization. C.S. carried out the ex situ TEM characterization and electrochemical test. M.G. carried out the simulation. C.S., M.G. and C.Z. wrote the manuscript. L.L., X.F., Y.L., A.Z., J.R. and C.W. edited the manuscript. C.Z. supervised the project. Figure 1 In situ TEM observation of the lithiation process of a ball-milled Si particle. The test was carried out using a nanobattery configuration with a ball-milled Si particle attached to a Cu rod as the working electrode, Li as the reference electrode, and Li2O as the solid electrolyte. (a) Schematic of the in situ TEM nanobattery. (b) TEM image of the ball-milled Si particle before lithiation. (c–g) Time series of the lithiation of the ball-milled Si particle, which illustrates the crack nucleation and fracture of the particle. After the Li2O/Li electrode contacted the ball-milled Si, a potential of −2 V was applied to the Cu electrode with respect to Li electrode to initiate the lithiation process. (h,i) Selected area electron diffraction (SAED) patterns of the ball-milled Si particle before (h) and after lithiation (i). Figure 2 In situ TEM observation of the lithiation process of a porous Si particle. (a) TEM image of the porous Si particle with diameter up to 1.52 μm before lithiation. (b–f) Time series of the lithiation of the porous Si particle, which illustrates the volume expansion of the particle without crack formation. (g,h) SAED patterns of the porous Si particle before (g) and after lithiation (h). Figure 3 Schematic diagram illustrating the lithiation manners of ball-milled Si and porous Si nanoparticles. (a–d) Schematic diagram showing the surface-to-center lithiation manner of ball-milled Si particle. (e–h) Schematic diagram showing the end-to-end lithiation manner of porous Si particle. Figure 4 Ex situ TEM characterization of ball-milled Si and porous Si after different charge-discharge cycles and comparison of their cycling performances. The Si electrodes were cycled in Li-Si cells in the voltage window of 0.01–2 V (vs. Li/Li+) at a current density of 400 mA/g and then disassembled at the delithiated state before TEM observation. (a–d) TEM images of ball-milled Si before cycling (a), after cycling for 1 cycle (b), 10 cycles (c), and 50 cycles (d). (e–h) TEM images of porous Si before cycling (e), after cycling for 1 cycle (f), 10 cycles (g), and 50 cycles (h). The insets in (a–h) are the corresponding SAED patterns. (i–l) Pore size distributions of porous Si before cycling (i) and the comparison of ball-milled Si and porous Si after cycling for 1 cycle (j), 10 cycles (k), and 50 cycles (l). (m) Cycling performances of Li-Si cells using ball-milled Si and porous Si as working electrode, respectively. The galvanostatic charge-discharge test was carried out in the voltage window of 0.01–2 V (vs. Li/Li+) at a current density of 400 mA/g. Figure 5 In situ TEM observation of the lithiation process of a typical Si nanowire. (a) TEM image of the Si nanowire before lithiation. (b–f) Time series of the lithiation of the Si nanowire. (g,h) SAED patterns of the Si nanowire before (g) and after lithiation (h). Figure 6 In situ TEM observation of the lithiation process of a porous Si nanowire bundle. (a) TEM image of the porous Si nanowire bundle before lithiation. (b–g) Time series of the lithiation of the porous Si nanowire bundle. The single nanowire beside the bundle provides lithium diffusion path. (h,i) SAED patterns of the Si nanowire bundle before (h) and after lithiation (i). Figure 7 First-principle molecular dynamic simulation to study the structure stability of a nanosized c-Li15Si4 particle. (a) The modeled structure of c-Li15Si4. (b–e) Atomic structure and morphology of the Li15Si4 particle at different simulation stages. (f) Si-Si radial pair distribution function at different stages of the simulated process. The appearance and increasing intensity of the peak at 2.5 Å indicate the intermixing of Si and Li to form an amorphous phase. ==== Refs Tarascon J. M. & Armand M. Issues and challenges facing rechargeable lithium batteries . Nature 414 , 359 –367 (2001 ).11713543 Goodenough J. B. & Kim Y. Challenges for Rechargeable Li Batteries . Chem. Mater. 22 , 587 –603 (2010 ). Boukamp B. A. , Lesh G. C. & Huggins R. A. All-Solid Lithium Electrodes with Mixed-Conductor Matrix . J. Electrochem. Soc. 128 , 725 –729 (1981 ). Larcher D. et al. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3257910.1038/srep32579ArticleEpigenetic regulation of OAS2 shows disease-specific DNA methylation profiles at individual CpG sites Gu Xiaolian a1Boldrup Linda 1Coates Philip J. 2Fahraeus Robin 123Nylander Elisabet 4Loizou Christos 5Olofsson Katarina 5Norberg-Spaak Lena 5Gärskog Ola 5Nylander Karin 11 Department of Medical Biosciences/Pathology, Umeå University, Umeå, Sweden2 RECAMO, Masaryk Memorial Cancer Institute, Brno, Czech Republic3 Institut de Génétique Moléculaire, Université Paris 7, Hôpital St. Louis, Paris, France4 Department of Public Health and Clinical Medicine/Dermatology and Venereology, Umeå University, Umeå, Sweden5 Department of Clinical Sciences/ENT, Umeå University, Umeå, Swedena xiaolian.gu@umu.se30 08 2016 2016 6 3257904 04 2016 10 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Epigenetic modifications are essential regulators of biological processes. Decreased DNA methylation of OAS2 (2′-5′-Oligoadenylate Synthetase 2), encoding an antiviral protein, has been seen in psoriasis. To provide further insight into the epigenetic regulation of OAS2, we performed pyrosequencing to detect OAS2 DNA methylation status at 11 promoter and first exon located CpG sites in psoriasis (n = 12) and two common subtypes of squamous cell carcinoma (SCC) of the head and neck: tongue (n = 12) and tonsillar (n = 11). Compared to corresponding controls, a general hypomethylation was seen in psoriasis. In tongue and tonsillar SCC, hypomethylation was found at only two CpG sites, the same two sites that were least demethylated in psoriasis. Despite differences in the specific residues targeted for methylation/demethylation, OAS2 expression was upregulated in all conditions and correlations between methylation and expression were seen in psoriasis and tongue SCC. Distinctive methylation status at four successively located CpG sites within a genomic area of 63 bp reveals a delicately integrated epigenetic program and indicates that detailed analysis of individual CpGs provides additional information into the mechanisms of epigenetic regulation in specific disease states. Methylation analyses as clinical biomarkers need to be tailored according to disease-specific sites. ==== Body DNA methylation of the fifth position of cytosine is an important regulatory mechanism of genome function. Methylation is subject to dynamic changes and essential for the regulation of gene expression, cellular differentiation and is commonly altered in human disease123. Genome-wide array- and sequencing-based techniques are increasingly applied to investigate DNA methylation, providing a broader view of global methylation patterns, giving a better understanding of the functional elements controlling gene expression and identifying numerous disease-associated differentially methylated CpG sites456. The exact mode of epigenetic modifications for particular genes and their role in disease, however, is yet to be completely understood. Overexpression of OAS2 (2′-5′-oligoadenylate synthetase 2) has been reported in patients with inflammatory, autoimmune and malignant diseases, whereas its role in these conditions remains poorly understood78. The OAS2 protein is a well-known innate immune activated antiviral enzyme catalyzing synthesis of 2′-5′-oligoadenylate for RNase L activation and inhibition of viral propagation9. More recent studies show that it also participates in other biological processes. In pancreatic β cells, OAS2 could be induced and activated by in vitro transcribed cellular RNAs, leading to cell proliferation inhibition and apoptosis10. In acute monocytic leukemia cells THP-1, NOD2 (Nucleotide-binding and oligomerization domain-2, an immune receptor to intracellular bacterial lipopolysaccharides) was found to interact with OAS2 enhancing RNase-L function, indicating a connection between OAS2 and other innate immune signaling pathways11. Extracellular OAS2 has also been reported as a negative regulator of T-cell function in oral cancer, promoting tumour progression by modulating anti-tumour immune response8. Interestingly, in psoriasis, a chronic inflammatory skin disease, overexpression of OAS2 was found to be associated with differential DNA methylation121314. Squamous cell carcinoma of the head and neck (SCCHN), the sixth most common malignant tumour worldwide, constitutes an anatomically heterogeneous group of neoplasms arising within the head and neck area15. Several risk factors have been well characterized, such as tobacco smoking and alcohol consumption, and oncogenic viruses have also been suggested as a cause for the development of a subset of SCCHN1617. Infection with high-risk human papillomavirus (HPV, double-stranded DNA viruses infecting epithelial cells), is most commonly found in tonsillar SCC (66.4%) and least in tongue (25.7%) and pharyngeal (15.3%) SCC18. Recent investigations on the incidence of HPV infection in SCCHN in northern Sweden identified HPV positivity in 91% of tonsillar SCC19, whereas no evidence of HPV infection was observed in SCC of the mobile tongue20. Although overexpression of OAS2 has been reported in SCCHN8, the status of OAS2 in these distinct subtypes of SCCHN is not well known. Pyrosequencing is a sequencing-by-synthesis method that quantitatively measures DNA methylation based on the detection of pyrophosphate released upon nucleotide incorporation21. As a cost-effective and efficient method to quantify DNA methylation it is widely used to validate high-throughput methylation array data, providing a clearer picture of methylation status for defined DNA regions4. Therefore in this study, we performed pyrosequencing to detect DNA methylation of OAS2 in psoriasis, SCC of the mobile tongue and SCC of the tonsil. Unexpectedly, we found that distinct epigenetic features were notable at 4 successively located CpG sites within a genomic area of 63 bp in these different pathological conditions. Exploring mechanisms of epigenetic changes in OAS2 will be useful for illustrating the role of OAS2 in human diseases. In a broader context, our data provide novel insight into the sophisticated epigenetic machinery and reinforce that methylation analyses as clinical biomarkers will need to be tailored according to disease-specific sites. Materials and Methods Patients and samples This is a retrospective study of 58 patients plus control samples. Twelve patients were diagnosed with moderate-severe psoriasis, 12 with SCC of the mobile tongue and 34 with SCC of the tonsil. For all patients with SCC of the mobile tongue and 11 patients with SCC of the tonsil collected for this study, biopsies were taken from tumour and adjacent tumour-free tissue prior to treatment (clinical data are shown in Supplementary Table S1). DNA samples from 23 tonsillar samples have been used in another study19. The status of HPV infection and p16 expression (a proposed surrogate marker for high risk HPV infection22) in these tonsillar tumor samples had been determined (17/23 were HPV-positive and 21/23 showed p16 expression)19. The quick score system was applied to evaluate levels of p16 expression. The quick score produces values ranging from 0 to 18 by multiplying the percentage of p16 positive cells (scored as 0–6) with intensity (scored as 1–3)23. Quick scores ranging from 0 to 12 were seen in these samples. For the psoriasis group, 12 patients diagnosed with moderate-severe psoriasis and matched healthy individuals were the same as included in a previous study24. Clinical data on patients with ready-to-use DNA samples are shown in Supplementary Table S2. This study was approved by the Regional Ethics Review Board, Umeå, Sweden (Dnr 08-108 M and Dnr 08-003 M) and performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from all subjects. DNA/RNA isolation Biopsies were fresh-frozen in liquid nitrogen and stored at −80 °C until DNA extraction. AllPrep DNA/RNA/miRNA Universal Kit (Qiagen, Hilden, Germany) was used to simultaneously isolate DNA and RNA from tumour (T) and tumour-free (TF) samples from patients with tongue and tonsillar SCC. Briefly, the fresh frozen biopsies (less than 20 mg) were homogenized in 600 μl Buffer RLT PLT Plus using the Precellys Tissue homogenizer (Bertin Technologies, Artigus Pres Boreaux, France). Tissue lysates were processed according to the Qiagen protocol and eluted twice in a total of 60 ul RNase-free water for RNA isolation and twice in a total of 150 Buffer EB for DNA isolation. The final yields range from 4.86 to 77.04 μg for RNA and 3.45 to 71.69 μg for DNA. Quantity and purity of DNA/RNA was measured using a NanoDrop ND-1000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). DNA quality was confirmed by gel electrophoresis and RNA quality by Agilent RNA 6000 Nano kit (Agilent 2100 Bioanalyzer, Agilent Technologies, Santa Clara, CA, USA). Another 23 DNA samples of tonsillar SCC had been extracted from paraffin embedded diagnostic biopsies (percentage of tumour cells range from 25 to 95%) using the QIAamp DNA FFPE Tissue Kit or QIAamp Mini Kit (Qiagen, Valencia, CA, USA)19. Following the manufacturer’s instructions, eight sections with a thickness of 10 μm were cut from each paraffin-embedded tumour block for DNA preparation. Purified DNA was eluted in 50 μl of Buffer ATE (supplied with the QIAamp DNA FFPE Tissue Kit) or Buffer AE (supplied with the QIAamp Mini Kit). The final DNA yields range from 4 to 50.60 μg. DNA from psoriatic epidermis and healthy controls was isolated using the PureLink® Genomic DNA Kits (Life Technologies, Carlsbad, CA, USA)24. Bisulfite treatment and pyrosequencing Based on our previously published methylation 450 K array data on psoriasis (accession number: GSE63315)24, 13 probes for OAS2 were found. Among these CpG sites, three were differentially methylated in psoriasis compared to matched controls (|delta-beta| > 0.1 and adjusted P-value < 0.01) (Supplementary Table S3). Of these, two were located 391 and 213 bp upstream of the transcription start site (TSS) respectively and one in the first exon. In order to validate the array data and evaluate its representativity of the surrounding area, four commercially available PyroMark CpG assays from Qiagen were used to determine methylation levels in two areas in which these three CpG sites were located (Supplementary Fig. S1). Information of the four PyroMark CpG assays detecting a total of 11 CpG sites is summarized in Supplementary Table S4. A schematic diagram of CpG sites spanning −500 bp upstream of TSS to the first exon (+317 bp) is shown in Fig. 1a. Five hundred ng of genomic DNA was used for bisulfite conversion using EpiTect Fast DNA Bisulfite kit (Qiagen). Bisulfite converted DNA samples were cleaned up hereafter and finally eluted in 20 μl Buffer EB. According to the PyoMark PCR protocol, 1 μl bisulfite converted DNA were amplified in 25 μl PCR reactions and 10 μl PCR product was used for pyrosequencing. Pyrosequencing was performed using the PyroMark Q24 advanced machine and following the instructions for PyroMark Q24 Advanced CpG Reagents from Qiagen. Degree of methylation was expressed as methylated cytosines divided by total cytosines (the sum of methylated and unmethylated cytosines), ranging from 0 to 100%, corresponding to array beta value 0 to 1. Real time RT-PCR Real-time RT-PCR was performed to detect OAS2 mRNA levels in tumour and adjacent tumour-free controls. Complementary DNA (cDNA) was synthesized from 500 ng of total RNA with oligo (dT) primer, according to the instructions for the RevertAid H minus first strand cDNA synthesis kit (Fermentas, Thermo Scientific, Wilmington, DE, USA). Real time RT-PCR was performed using an IQ5 multicolor real-time PCR detection system with IQ SYBR Green Supermix (Bio-Rad Laboratories, Hercules, CA, USA). Primers for OAS2 were ordered from Bio-rad (Bio-Rad, assay ID qHsaCED0037726). NormFinder software was used to analyze a set of reference gene candidates based on our own whole-genome expression data, and a total of four genes were confirmed to be good reference genes in our study, including LAD1 (Forward: CCTCCCACCCGTCACACT, Reverse: CTGCTGTAGGTTCGCTGTGT), RPS12 (Forward: TGCTGCTGGAGGTGTAATGG, Reverse: GCACACAAAGATGGGCTTGG), GAPDH and USB). Primers for GAPDH and USB were ordered from Primerdesign Ltd (Southhampton, United Kingdom) and the sequences of primers were not provided. For real time RT-PCR data normalization, the geometric mean of these reference genes were calculated. The cycling conditions were set as follows: enzyme activation at 95 °C for 3 min, 40 cycles of denaturation at 95 °C for 15 sec and annealing/extension at 60 °C for 60 sec. For OAS2 mRNA levels in psoriasis, we used our previous published gene expression array data of the same material25. DNA Methylation data from Epigenome Roadmap The Roadmap Epigenomics Project has produced 127 reference epigenomes spanning diverse cell and tissue types, providing the largest collection so far of human epigenomes representative of all major lineages in the human body26. A total of 37 reference methylomes by whole genome bisulphite sequencing (WGBS) were available, representing multiple brain, heart, muscle, gastrointestinal tract, adipose, skin and reproductive samples, as well as immune lineages, ES (embryonic stem) cells and iPS (induced pluripotent stem) cells, and differentiated lineages derived from ES cells26. OAS2 DNA methylation data in the promoter region (1000 bp upstream of TSS and the first exon, a sequence of 1317 bp) was extracted using UCSC Table Browser27. A total of 25 CpG dinucleotides were found in the defined promoter region using the February 2009 (CrCh37/hg19) build of the human genome. Cell culture and stimuli Human adult epidermal keratinocytes (HEKa, Life technologies, Carlsbad, USA) were maintained in medium 154 with human keratinocyte growth supplement (HKGS) (Life technologies) and cultured at 37 °C with 5% CO2. The day before stimulation, cells between passage 3 to 6 were plated in 6-well plates at 2 × 105 cells/well in 2 ml of complete growth medium. At the time of stimulation, cells were treated with 1 μg/ml double-stranded RNA (dsRNA) analog poly(I:C) (Polyinosinic acid: Polycytidylic acid) or 1 μg/ml double-stranded DNA (dsDNA) analog poly(dA:dT) (poly(deoxyadenylic-deoxythymidylic) acid sodium salt) (Invivogen, San Diego, CA, USA). Experiments were performed in duplicate and repeated in two independent experiments. Cells were collected 24 hours after stimulation and RNA/DNA co-isolated using ZR-Duet™ DNA/RNA MiniPrep from Zymo Research, according to the manufacturer’s manual (Irvine, CA, USA). Statistics To identify differentially methylated CpG sites, DNA methylation levels in diseased tissue were compared with controls, either skin from healthy volunteers for the psoriasis samples or self-paired tumour-free samples for cancer patients. Non-parametric two-tailed tests were used and the significance level was set at 5%. Wilcoxon signed-rank test for two related samples was performed to compare differences between tumour and adjacent tumour-free samples. Mann-Whitney U test for two independent samples was performed to compare differences between psoriatic epidermis and epidermis from healthy individuals. Significantly differentially methylated sites (P < 0.05) with more than 10% decrease in absolute methylation were defined as hypomethylated. Spearman correlation coefficient (rho) was calculated to evaluate the strength of correlation. All statistical tests were conducted in IBM SPSS Statistics 21. Results Pyrosequencing confirmed hypomethylation of OAS2 in psoriasis Methylation status of 11 OAS2 CpG sites in psoriasis and control skin samples were successfully quantified using pyrosequencing. As both 450K array24 and pyrosequencing data were available for CpG1, 2, 6 and 9, we first evaluated the correlation between data determined by pyrosequencing and methylation array. Spearman correlation analysis indicated good correlation between the two platforms, with the strongest correlation seen for CpG1 (rho = 0.963, P = 0.000) (Supplementary Table S5). Individual methylation levels at the 11 CpG sites are presented in Fig. 1b showing a high degree of inter-individual and inter-locus variation. In general, high methylation levels were seen at CpG1 to 4 and low levels at CpG5 to 11. When comparing psoriasis to control skin, an overall demethylation was observed and a total of 8 CpG sites were identified as hypomethylated (mean methylation difference >10%, P < 0.01). The most hypomethylated site being CpG1, with a mean methylation difference of 31% between psoriatic epidermis and controls (P = 0.000). Only two OAS2 CpG sites were hypomethylated in SCCHN Methylation status of the same 11 CpG sites was investigated in SCCHN. In Fig. 1c (mobile tongue SCC) and 1D (tonsillar SCC) we can see that, similar to psoriatic epidermis, methylation levels at these 11 CpG sites exhibited inter-individual and inter-locus variations. The highest methylation levels in both tumour and tumour-free tissue were seen at CpG2 and 3, whereas methylation levels at CpG5 to 11 were less than 10%. When comparing tongue tumour with tumour-free tissue pairwise, significant methylation differences were seen only at CpG2 (P = 0.002) and CpG3 (P = 0.002). Similarly, significant decreases in DNA methylation were seen in tonsillar SCC compared to tumor-free tissues at CpG2 (P = 0.023) and CpG3 (P = 0.023). Notably, methylation levels at these two CpG sites were the least changed in psoriasis versus control skin. Furthermore, the degree of hypomethylation in mobile tongue SCC was higher than that in tonsillar SCC. HPV infection and DNA methylation of OAS2 DNA methylation levels of OAS2 in another 23 tonsillar cancer samples were also studied. HPV status and p16 expression (based on quickscore ranging from 0 to 18) in these samples have been investigated previously19. In this sample group, 17 tumour samples were HPV-positive, and all of these HPV-positive tumours were p16-positive (quickscore ≥ 6). Among the six HPV-negative tumours, both negative and positive staining for p16 were seen (quickscore from 0 to 12). When comparing HPV-positive with HPV-negative tumours, no difference in OAS2 DNA methylation was found based on HPV status (Supplementary Fig. S2). Similarly, no correlation between p16 staining and DNA methylation of OAS2 was identified. Correlation between DNA methylation and gene expression In order to evaluate whether OAS2 DNA methylation could be involved in regulating gene expression, correlation between DNA methylation and gene expression was investigated using our previous gene expression profiling data for psoriasis (accession number GSE53431). OAS2 expression in SCCHN was studied using real time RT-PCR. Expression data are from the same subjects as the methylation data. In Fig. 2, we can see that similar to overexpression of OAS2 in psoriasis (P = 0.000, mean fold change = 8.1), OAS2 was significantly overexpressed in tongue SCC compared to tumour-free tissues (P = 0.003, mean fold change = 11.8). Overexpression of OAS2 was also seen in tonsillar SCC (P = 0.013, mean fold change = 2.4) but levels were much lower than in psoriasis and tongue SCC. Methylation levels at each CpG site were then correlated to gene expression data (Supplementary Table S6). In psoriatic epidermis, OAS2 mRNA was significantly correlated with methylation levels of all 11 CpG sites, with the strongest correlation seen between CpG1 methylation and gene expression (Spearman correlation coefficient rho = −0.845, P = 0.000) (Fig. 3a). In tongue SCC, methylation levels at CpG2 and CpG3 were significantly correlated with mRNA levels (Spearman correlation coefficient rho = −0.738 (CpG2) and −0.769 (CpG3), P = 0.000) (Fig. 3b), whereas in tonsillar SCC OAS2 hypomethylation at CpG2 and 3 was not correlated with gene overexpression (Fig. 3c). Methylation levels at CpG 2 and 3 demonstrate least variation across different tissues As DNA methylation could be tissue-specific2628, we sought to investigate whether the difference in methylation between psoriasis and SCCHN arises merely from tissue-dependent methylation modifications. OAS2 methylation levels in the proximal promoter region were obtained from 37 reference methylomes. Methylation status across different tissues/cells for each CpG site is shown in Supplementary Fig. S3 and level of variability for each site measured by calculating the coefficient of variation (CV, Supplementary Table S7). A high degree of tissue- and/or developmental-specific variations in DNA methylation was seen for the majority of CpG sites (Supplementary Fig. S3A). Focusing on methylation status of 18 adult tissues/cells (Supplementary Fig. S3B), high methylation variations were also seen, indicating tissue-specific methylation status for most CpG sites. We then inspected methylation status for the two CpG sites (CpG2 and 3) that were hypomethylated in SCC but not in psoriasis. Interestingly, methylation levels at these two CpG sites were more consistent across different tissue/cells compared to nearby CpG sites. Our pyrosequencing data also showed that methylation levels at these two CpG sites were similar between healthy epidermis and tumour-free head and neck tissues, whereas at the two most nearby CpG sites (CpG1 and CpG4), tissue-specific methylation levels were seen. Innate immune response was not accompanied by altered methylation of OAS2 As OAS2 is involved in the innate immune response to viral infection we performed cell line experiments to study gene expression and DNA methylation in response to innate immune triggers. The methylation status for OAS2 in primary HEKa cells corresponded closely to normal epidermal cells and OAS2 mRNA was increased upon poly(dA:dT) or poly(I:C) stimulation, whereas DNA methylation levels were not affected (Supplementary Fig. S4). Discussion We previously profiled DNA methylation in psoriatic epidermis using the Illumina 450K BeadChip platform and found hypomethylation of OAS2 in psoriasis compared to healthy controls. Though covering key features of the human genome, only 2% of the human genome CpG sites were targeted and hybridization probes spanning 50 bases in the 450K platform limits the identification of heterogeneous methylation and informative single CpG sites429. Therefore, further characterization of methylation changes at single-base resolution and with broader CpG coverage is required to elucidate details of epigenetic modifications. In this study, by using the quantitative pyrosequencing method, we have clarified OAS2 methylation status in two genomic regions where the three array identified hypomethylated CpG dinucleotides are located. Our data demonstrated that methylation changes did not occur in a coordinated manner, and notably, distinct methylation levels were seen at 4 successively located CpG sites within a genomic area of 63 bp. One common DNA methylation analysis task is to identify Differentially Methylated Regions (DMRs) between two groups as it is widely accepted that DNA methylation alterations at multiple adjacent CpG sites is of biological relevance30. On the other hand, several studies have identified single CpG dinucleotides important for gene expression and disease development, and demethylation pressure at specific CpGs has been suggested3132. Therefore, the importance of epigenetic modifications in diverse biological processes should be carefully evaluated based on methylation results with single-base resolution. Similar to the strong inverse correlation between OAS2 DNA methylation and gene expression in psoriasis reported by Roberson et al.14, we also found out that gene expressions in psoriatic epidermis and tongue SCC were highly correlated with DNA methylation. Interestingly, we demonstrated that distinct CpG sites were targeted for methylation modification in different diseases. The relationship between genetic variation, DNA methylation and gene regulation is complex and can be of different nature depending on tissue and genomic region33. As different types of tissues are investigated in this study, it is not unexpected that methylation changes at different CpG sites are required for gene regulation in different tissues. Interestingly, when focusing on the 63 bp region where CpG1 to 4 are located, differentially methylated CpG sites in psoriasis and SCCHN were mutually exclusive. CpG1 and 4 were hypomethylated in psoriatic lesions compared with controls, whereas CpG2 and 3 were hypomethylated in SCCHN when compared with adjacent tumour-free tissue. By comparing the methylation status at different CpG sites across different normal tissues/cells using the Roadmap reference data, high degree of tissue-dependent variation in OAS2 DNA methylation was clearly seen. Noteworthy, methylation levels at CpG 2 and 3 are least variegated across normal tissue/cells, but turn out to be the only two CpG sites that are demethylated in tongue and tonsillar SCC. Therefore, methylation levels at these two CpG sites seems to be specifically modified only in some diseases. As reverse correlations between DNA methylation and gene expression were seen in psoriatic epidermis and tongue SCC, and transcription factors could be important drivers of methylation changes534, it seems likely that under distinct pathological conditions, different transcriptional factors targeting different genomic elements are recruited for activating OAS2 expression. The general hypomethylation of OAS2 seen in psoriasis might functionally be related to OAS2 mRNA up-regulation, whereas in SCC of the mobile tongue, local decreased methylation at only two CpG sites (CpG2 and 3) seems sufficient to affect regulation of OAS2 expression. Though it is far from understood how a specific CpG dinucleotide is marked for modification, distinct epigenetic modes underlying common overexpression of OAS2 in benign hyper-proliferative and malignant conditions indicate that understanding of epigenetics could offer useful information for understanding the pathogenesis of different diseases. When treating primary HEKa cells with dsRNA or dsDNA analogues, we found potent OAS2 mRNA induction whereas DNA methylation levels remained unchanged (Fig. S4). Thus, it seems that epigenetic mechanisms are not required for transcriptional activation of OAS2 in keratinocytes in short-term antiviral response. By comparing HPV-positive with HPV-negative tonsillar SCC, no difference in methylation level was found. Though a direct connection between HPV infection and OAS2 expression has not yet been established, we speculate that in psoriasis and SCCHN, the classical antivirus pathway was not responsible for overexpression of OAS2. Besides the well-known antiviral function of the OAS family, OAS proteins are implicated in other cellular events such as gene induction, regulation of apoptosis, cell growth and differentiation735. Very recently, it was shown that extracellular OAS2 could lead to immune dysfunction in oral SCC8, suggesting a cancer-promoting role for OAS2. As OAS2 expression levels differ between the subtypes of SCCHN, it remains to be elucidated whether this is a common function of OAS2 in SCCHN. In summary, we used a high resolution quantitative method for analysis of OAS2 DNA methylation in psoriasis and SCCHN. Four successive CpG sites located in a 63 bp promoter area of OAS2 were differentially methylated in a site- and disease- specific manner. Our results provide further insight into how epigenetic programming integrates delicately with genomic elements. Unraveling the epigenetic mechanisms involved in regulation of OAS2 could aid our understanding of the role of OAS2 in different cellular contexts. More generally, DNA methylation analysis has promise for diagnosis, prognosis and prediction of therapeutic response in cancer and other diseases3637. Our data indicate disease- and/or tissue-specific epigenetic regulation of individual genes, such that accurate analysis of methylation requires detailed mapping of individual CpG sites to identify the changes that characterize different disease states. In turn, identifying specific sites and how they are targeted for methylation-mediated regulation may improve our understanding of the underlying biology of normal and diseased tissues. From a clinical viewpoint, analysis of methylation at single CpG sites represents a simple assay and can provide predictive biomarkers31, but these assays may need to be tailored to different CpG sites in different disease states. Additional Information How to cite this article: Gu, X. et al. Epigenetic regulation of OAS2 shows disease-specific DNA methylation profiles at individual CpG sites. Sci. Rep. 6, 32579; doi: 10.1038/srep32579 (2016). Supplementary Material Supplementary Information This study was supported by grants from Hudfonden, Lion’s Cancer Research Foundation, Umeå University, The Swedish Cancer Society contract number 15 0637, Umeå University and project MEYS-NPSI-LO1413 from the Ministry of Education, Youth and Sports and GACR P206/12/G151 (PC) in the Czech Republic. Author Contributions X.G. designed and performed experiments, analyzed data and wrote the manuscript. L.B. performed experiments. P.J.C. wrote the manuscript. R.F. designed experiments. E.N., C.L., K.O., L.N.S. and O.G. provided medical materials. K.N. supervisor the project and wrote the manuscript. All authors commented on the manuscript. Figure 1 Hypomethylation of OAS2 in psoriasis and SCCHN. (a) Schematic diagram of CpG sites spans −500 bp upstream of transcription start site (TSS) to the first exon (+317 bp). CpG sites are indicated by vertical ticks. The CpG sites covered by PyroMark CpG assays are numbered in order from 1 to 11 (pyrosequencing ID). Array identified hypomethylated CpG sites in psoriasis are highlighted by thick vertical ticks. (b–d) Methylation status of 11 CpG sites in psoriasis, tongue SCC and tonsillar SCC determined by pyrosequencing analysis. Individual methylation data are shown as dot plots and the horizontal lines indicate means. Mean methylation difference (MMD) between disease and controls is shown under each CpG sites. Mann-Whitney U test was performed for comparing psoriasis with controls and Wilcoxon signed ranks test for comparing tumour with adjacent tumour-free samples (***P < 0.001, **P < 0.01, *P < 0.5). Figure 2 OAS2 was significantly upregulated in psoriasis and SCCHN. Levels of OAS2 mRNA in psoriasis were determined previously using Illumina HumanHT-12 v4 Expression BeadChip. Significant up-regulation of OAS2 was seen in psoriasis compared to matched controls (***P < 0.001). Levels of OAS2 mRNA in SCCHN and adjacent tumour-free tissues were determined using real time RT-PCR, and found to be significantly upregulated in tongue SCC (**P < 0.01) and tonsillar SCC (*P < 0.05). LAD1, RPS12, GAPDH and USB were used as internal controls for real time RT-PCR analysis. Figure 3 Correlation between OAS2 DNA methylation and gene expression. Spearman correlation test was performed to study the correlation between DNA methylation and gene expression. In psoriasis, DNA methylation at each CpG site was negatively correlated with gene expression. The strongest correlation was seen between CpG1 methylation and gene expression (rho = −0.845, P = 0.000). In tongue SCC, DNA methylation at CpG2 and 3 was negatively correlated with gene expression. The higher correlation between CpG3 methylation and gene expression is shown (rho = −0.769, P = 0.000). No correlation between OAS2 DNA methylation and gene expression was found in tonsillar SCC (rho = −0.307, P = 0.164). ==== Refs Ziller M. J. et al. Charting a dynamic DNA methylation landscape of the human genome . Nature 500 , 477 –481 (2013 ).23925113 Smith Z. D. & Meissner A. DNA methylation: roles in mammalian development . Nat. Rev. Genet. 14 , 204 –220 (2013 ).23400093 Jones P. A. Functions of DNA methylation: islands, start sites, gene bodies and beyond . Nat. Rev. Genet. 13 , 484 –492 (2012 ).22641018 Plongthongkum N. , Diep D. H. & Zhang K. Advances in the profiling of DNA modifications: cytosine methylation and beyond . Nat. Rev. Genet. 15 , 647 –661 (2014 ).25159599 Schubeler D. Function and information content of DNA methylation . Nature 517 , 321 –326 (2015 ).25592537 Bock C. Analysing and interpreting DNA methylation data . Nat. Rev. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3245510.1038/srep32455ArticleOpen System Tribology and Influence of Weather Condition Lyu Yezhe a1Bergseth Ellen 1Olofsson Ulf 11 Department of Machine Design, (KTH) Royal Institute of Technology, SE-100 44 Stockholm, Swedena yezhe@kth.se30 08 2016 2016 6 3245517 05 2016 09 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The tribology of an open system at temperatures ranging between 3 °C and −35 °C, with and without snow, was investigated using a pin-on-disc tribometer mounted in a temperature-controlled environmental chamber. The relationship between the microstructure and ductility of the materials and the tribology at the contacting surfaces was investigated. The study shows that during continuous sliding, pressure causes snow particles to melt into a liquid-like layer, encouraging the generation of oxide flakes on the contact path. The friction coefficient and wear rate are dramatically reduced through an oxidative friction and wear mechanism. In the absence of snow, the tribological process is controlled by the low temperature brittleness of steel in the temperature range from 3 °C to −15 °C. At these temperatures, cracks are prone to form and extend on the worn surfaces, resulting in the spalling of bulk scraps, which are crushed into debris that increases the friction coefficient and wear rate due to strong abrasion. When the temperature falls to −25 °C, an ice layer condenses on the metal surfaces and relaxes the tribological process in the same way as the added snow particles, which significantly decreases the friction and wear. ==== Body Tribology is important in systems that contain interacting surfaces in relative motion, such as bearings, gears, and brakes. The interacting surfaces may have very different characteristics as regards roughness, hardness, plasticity, brittleness and diverse contaminants, all of which significantly influence the tribological process1. While some of these factors are determined during the manufacturing process, others vary with the operating environment. This environment may be closed or open. Closed systems (such as the seals, valves and gears in a gearbox) are theoretically isolated from the natural environment, and so are not affected by weather conditions. Open systems on the other hand, are greatly affected by weather conditions such as precipitation, temperature and humidity – feet, for example, may slip when it is raining, and tires may spin on a snowy road. Temperature influences the tribological process by affecting the properties of the interacting surfaces. Polymers, for example, are harder at low temperatures than at room temperature2, and body-centred cubic steel experiences a ductile-to-brittle transition with decreasing temperature3. All these changes in properties affect the tribological process at the molecular scale when the interacting surfaces move relative to one another4. Therefore, even the simplest tribological process may exhibit great complexity, such as local deformation and corrosive processes56789. Tribology at the wheel-rail contact plays a key role in railway performance. Friction controls the tracking and braking, while wear affects reliability and endurance. Researchers have investigated the effect of temperature, humidity and natural contaminants (e.g. sand, water, and leaves) on tribology at the wheel-rail contact1011121314. However, more research is needed on wheel-rail tribology in winter when the temperature is below zero and snow particles are present. The reason for the lack of research in this area is the difficulty of achieving stable control of sub-zero temperatures. Although several apparatuses have been set up to obtain a cryogenic environment covering an extensive temperature range (−268 °C to 20 °C)151617, all of them ignore the influence of natural air and contaminants as they all achieve the low temperature by dint of a vacuum or liquid cryogen atmosphere. An open system such as a wheel-rail system usually operates in a habitable environment. Most countries at high latitudes experience problems with wheel-rail contact in winter18192021. One possible reason is the ductile-brittle transition that wheel and rail steels experience as the temperature drops. The impact energy of a typical grade rail steel (UIC60 900A) was tested and the results are shown in Fig. 1. The ductile-brittle transition can be seen as the temperature decreases from 20 °C to −35 °C. As the rail becomes more brittle, the risk of crack generation increases, which may accelerate wear damage and cause traffic to be halted. Another possible reason is that snow dragged into the wheel-rail contact acts as a lubricant, resulting in loss of adhesion. Thus these two factors need to be investigated systematically. For the current project, a sizable quasi-sealed and temperature-controlled environmental chamber was built to simulate cold weather in the real world. The sliding contact was simulated using a pin-on-disc tester. Much effort was devoted to investigating the tribological performance between the simulated wheel-rail contact at different temperatures with and without snow. The combination of contact pressure and sliding speed represented a common rail head-wheel tread contact condition. The range of temperatures tested covered the typical temperature range in high latitude countries. The microstructure of the metal and worn features were analysed by scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). Wear was examined using a Talysurf roughness tester. On the basis of the experimental results, deductions were made about the influence of varying environmental temperatures on the tribological performance at the wheel-rail contact. A possible pattern of behaviour of the snow particles at the wheel-rail contact is also proposed. Results Tribological performance of the pins Figure 2a,b show the mean value with error bars corresponding to the standard deviations of the friction coefficient and wear rate on the pins as a function of temperature. The results shown in black and blue were obtained in the current study (temperature ranges from −35 °C to 3 °C), and the results in red were obtained in a previous study (3 °C to 20 °C)13. It can be seen that the friction coefficient and wear rate remain quite stable in the temperature range from 3 °C to 20 °C. However, in the range from −35 °C to 3 °C, the friction coefficient and wear rate show strong temperature dependence. For the current study, the friction and wear rate overall showed a decrease when snow particles were added into the contact at all test temperatures and both contact pressures. This decline was notable at −5 °C and −15 °C, where the friction coefficient decreased more than 0.1 when snow was added while the wear rate decreased one order of magnitude. The wear rate after snow was added decreased to a very low level, similar to that without snow (lower than 5 × 10−5 mm3·Nm−1) despite the change in temperature. The lowest friction coefficient and wear rate in the tests with snow added were observed at −35 °C for both contact pressures. When snow was not added, friction and wear (solid lines in Fig. 2a,b) underwent a transition as a function of temperature. Initially the friction and wear increased as the temperature fell from 3 °C to −15 °C, and then sharply decreased with a further decrease in temperature from −15 °C to −35 °C. In the tests without snow, the friction coefficients obtained at 900 MPa at all test temperatures (black solid line in Fig. 2a) are consistently higher than those at 1500 MPa (blue solid line in Fig. 2a) at corresponding temperatures. The same phenomenon can be seen in the tests with snow added. The wear rates in tests at 900 MPa, on the other hand, are lower than those at 1500 MPa with and without snow. Measurement of wear tracks on the discs The wear loss on the disc was too small to measure using an analytical balance. The width and depth of wear tracks were therefore used to evaluate the wear performance of the discs. Figure 2c–j present the wear track profiles on the discs tested under different conditions. These profiles were obtained with the help of a stylus instrument. It should be noticed that all the scales on the y-axis are centred and cover the range of −10 to 10 μm. On the x-axis the range is from −2 to 2 mm. Without snow, the widest and deepest wear tracks, representing the most severe wear condition on the disc, were obtained in the tests at −15 °C for both contact pressures. The narrowest wear track in the tests without snow occurred at −35 °C. Further, the widths and depths of the wear track on the disc tested with snow were much lower than those obtained without snow. All these findings are in accordance with the observation of the pins (Fig. 2a,b), demonstrating the concomitant wear conditions on the wheels and rails22. Discussion Railway vehicles operate in a variety of climates, including sub-zero temperatures. This research revealed that friction and wear are much more sensitive to temperature between −35 °C and 3 °C than between 3 °C and 20 °C (Fig. 2). Lubrication effect of snow particles As similar tribological conditions exist on the pins and the discs observed in Fig. 2, the friction and wear mechanisms were analysed based on observation of the pins. Figure 3 presents the SEM micrographs of typical worn surfaces on the pins tested with snow. A large area of continuous blackish phase can be observed at the contact path in the tests at all temperatures and both contact pressures (Fig. 3a,c,e). Area EDS analysis was conducted to identify the chemical composition of the blackish phase, and the results are shown in Fig. 3b,d,f. The EDS results show that the blackish phase is mainly composed of Fe and O with an atomic ratio between iron and oxygen of around 2:3. The blackish phase is therefore deduced to be hematite (Fe2O3), which is prone to generate in an air-rich, damp environment23. Lari et al. demonstrated the formation of large platelets of oxide layers under wet conditions24. As the pins and discs used in the experiment were carefully cleaned before tests commenced, the hematite is thought to self-generate during the tribological process. Normally, worn features containing large amounts of self-generated oxides in flake form indicate mild wear. This conclusion is based on Quinn’s research, which showed the relationship between wear regimes and the formation of oxides25. Lyu et al. verified this by achieving a reduced level of wear after oxide flakes self-produced in a simulated wheel-rail contact using a pin-on-disc tribometer13. Oxide flakes can self-generate in a rolling-sliding contact as easily as in a pure sliding contact, decreasing the wear between the contacting steels26. Friction, like wear, strongly depends on the oxides at the contacting surfaces. The lubrication effect of the oxide layers can be attributed to their physical properties. Hematite (800 to 1000 HV27) is much harder than the base steel (pearlitic steel 500 to 700 HV28) and allows only limited elastic/plastic deformation. These characteristics enable hematite to hinder the adhesion between two contacting steel surfaces, and thus abrasion is also reduced. The formation of hematite flakes is likely to be the main reason why the friction coefficient and wear rate were greatly reduced after snow particles were added into the contact. Zhu et al. reported a lower friction level because of the formation of oxide flakes with a pin-on-disc tribometer mounted in damp environment14. Although on the macro scale the surfaces of the pin and the disc seem to be as smooth as at manufacture, countless asperities are visible on a micro scale (Fig. 4). Most of the asperities on two shearing surfaces are not homogenous but keep coming in and out of contact. Although the nominal contact pressures between the pin and disc are 900 MPa/1500 MPa, the actual instantaneous pressure on some specific asperities can be much higher. The snow particles added in to the contact must sooner or later encounter these asperities. According to the pressure melting theory of ice/snow (Fig. 4), snow particles melt into a very thin liquid-like layer (Fig. 4c) and adhere to the contacting surfaces under such high pressure29. It is feasible to apply this theory to the current test since several researchers have demonstrated in both computational and experimental studies that ice/snow particles exhibit surface melting under high pressure3031323334. When snow is added to the pin and disc contact, the contact is thus thought to contain both air and water. Such an environment is the seedbed for the generation of oxides at the contacting surfaces, consistent with the existence of hematite flakes (Fig. 3). This oxidation reduced the friction and wear after snow particles were added in to the contact. There is no other comparable published information about the influence of snow on the tribology at the wheel-rail contact. As the snow particles are believed to melt into a water layer due to pressure melting, studies on the effect of water will be discussed. Several laboratory experiments have shown a decrease in the friction coefficient and wear rate with the addition of water to the wheel-rail contact. In these studies, large-scale oxide layers were observed on the worn surfaces353637. A real-world measurement with a hand-pushed tribometer also observed a 0.1 decline in the friction coefficient after water was added to the rail head38. The only research into the effect of snow particles on tribology was carried out with a cast-iron block brake and steel wheel as contacting materials39. The friction coefficient decreased about 0.2 after snow particles were applied to the contact. All the above research results are consistent with the findings of the current research, which directly and indirectly verifies the lubrication effect of snow particles at the wheel-rail contact. Tribological mechanism at −5 °C and −15 °C without snow Both the rail and wheel materials used in the current research are pearlitic steels. The typical microstructure of pearlitic steel consists of ferrite and pearlite. Figure 5a shows the morphology of UIC60 900A pearlitic rail steel (pin materials) taken with SEM. The massive grey phase is ferrite and the white lamellar phase is pearlite. There is always a distinguishable phase boundary between the ferrite and pearlite (Fig. 5b). Normally, the ferrite-pearlite phase boundary is enriched by inclusions (such as MnS and oxides) that generate during solidification4041. The inclusions give rise to weakness at the phase boundary, which is prone to generate cracks and corrosion pits. There is also a difference in the thermal expansion coefficient between the pearlite and ferrite42. Therefore, cracks tend to generate between the ferrite-pearlite phase boundaries at low temperatures due to the low temperature brittleness. Figure 5c shows a typical crack along a pearlite-ferrite phase boundary on the worn surface of a pin tested at −15 °C and 900 MPa without added snow. Similar cracks are common on the worn surfaces of pins tested at −5 °C and −15 °C without snow addition (Fig. 5c–f). Close to the cracks, countless pieces of wear debris can also be observed (bright areas in Fig. 5c–f). At temperatures of −5 °C and −15 °C without snow, all the worn surfaces are covered by debris and a large number of scratching features are present (Fig. 6a,b). Point EDS analyses were conducted to identify the composition of the wear debris, and the results are shown in Fig. 6c–f. The wear debris is almost pure iron (about 98 wt.% as shown in Fig. 6d–f). It can be concluded that the wear debris originated from the base metal and resulted in the scratching features shown in Fig. 6a,b during sliding. The most likely origin of the wear debris is the bulk scraps generated due to low temperature brittleness. In this process cracks were generated along the ferrite-pearlite phase boundary. With repeated shearing, these cracks gradually extended and resulted in the spalling of bulk scraps, which were subsequently involved in the sliding process as a third-body phase. The bulk scraps were also susceptible to low temperature brittleness and were easily crushed into tiny wear debris under continuous shearing between the pin and disc. Oxidation seldom occurred in the tests without snow at −5 °C and −15 °C, as shown by the fact that neither oxide flakes nor oxide pits were found on the worn surfaces (Fig. 6a,b). The tribological mechanism in tests without snow at −5 °C and −15 °C is likely to be abrasion/ploughing and differs significantly from the tests with snow. Abrasion/ploughing was widely found at the contact containing high hardness third-body debris. With graphene added into an alumina composite, higher wear rate and scratching features were found on the mating surfaces743. In previous tribological tests with steel44 and brass45 samples, friction and wear increased when hard asperities became embedded in the soft base surface, which increased the abrasion/ploughing effect. In wheel-rail contacts, typical third-body debris involves sands and oxide particles, both of which have been demonstrated to easily embed in wheel and rail steels. This increases the friction coefficient and wear rate through the abrasion/ploughing mechanism. In a laboratory-scale test with a twin-disc apparatus, the friction coefficient increased 0.2 when sand was added into the wheel-rail contact, and the wear rate increased more than 3 times11. Another laboratory experiment using a twin-disc setup showed similar results with the wheel-rail contact with sand addition showing a 0.2 increase in the friction coefficient compared with the contact without sand addition37. Oxide particles have also been shown to increase the friction coefficient and wear rate at the wheel-rail contact where abrasive features were found on the worn surfaces1013. Ice condensation at temperatures below −15 °C The friction coefficient and wear rate in tests without snow addition increase noticeably as the temperature drops from 3 °C to −15 °C. By contrast, when the temperature drops from −15 °C to −35 °C (Fig. 2) the friction coefficient and wear rate decrease sharply, a change that cannot be attributed to the ductile-brittle transition of steel. The worn surface of the pin tested at −35 °C and 1500 MPa without snow was tested using SEM to determine the tribological mechanism, and the results are shown in Fig. 7a. A large area of blackish phase can be observed at the contact path, an observation that is very similar to that for tests with snow (Fig. 3a,c,e). EDS analysis confirmed that the deposit is hematite (Fe2O3) as the atomic ratio between iron and oxygen is about 2:3 (Fig. 7b). The same oxide flakes were generated here as in the tests with snow, which explains the sharp decrease in the friction coefficient and wear rate when the temperature decreased from −15 °C to −35 °C (Fig. 2). It is suspected that some agent is generated during the tests which encourages the generation of oxide flakes, as hematite is prone to form in humid air. Figure 7c shows the disc surface after testing without snow addition at −35 °C. A large-scale ice layer has condensed on the disc surface. The microscopic morphology of the condensed ice layer measured in-situ with optical microscopy (OM) is shown in Fig. 7d. Compared with the natural snow particle observed in-situ (Fig. 7e), the condensed ice particles are smaller in size and have an irregular structure. Although the ice particles condensed on the disc surface discontinuously, they were thought to participate in the tribological process in the same way as the snow particles added intentionally. Their presence encourages the generation of oxide flakes in the contact path, which in turn reduces the friction coefficient and wear rate at the wheel-rail contact. To confirm the possibility of ice condensation on the disc surface, the saturation vapour pressure as a function of temperature in the range used in the experiment was calculated according to Wexler’s equation (1)46: where T is the temperature in Kelvin and c0 to c4 are fitting coefficients (c0 = −0.60436117 × 104, c1 = 0.1893292601 × 102, c2 = −0.28244925 × 10−1, c3 = 0.17250331 × 10−4, c4 = 0.2858487 × 10). Figure 7f plots this equation, the correlation between the saturation vapour pressure (Pa) and the temperature (°C). The corresponding saturation vapour pressure values at the temperatures tested are indicated by asterisks. It can be seen that the air becomes saturated more easily at lower temperatures (at −35 °C the saturation vapour pressure is one order of magnitude lower than that at 3 °C). Kuroda et al. discuss the kinetics of the ice condensation process, demonstrating that the ice condensation rate is a decreasing function of the saturation vapour pressure47. The above two scenarios jointly show the possibility of an ice condensation layer on the metal surfaces (Fig. 7c,d) when temperature decreased to −35 °C. This condensed ice layer would act in the same way as the snow particles added intentionally, and would significantly reduce the friction coefficient and wear rate at the wheel-rail contact. Conclusions The tribological performance at the wheel-rail contact in the open system (different temperatures from −35 °C to 3 °C, with and without added snow) was investigated using a pin-on-disc tribometer mounted in a temperature-controlled environmental chamber. It was found that the friction coefficient and wear rate are much more sensitive to temperatures in this range than at room temperatures. The snow particles added to the wheel-rail contact melt into a liquid-like layer during sliding because of pressure melting and encourage the formation of hematite (Fe2O3) flakes at the contact, dramatically reducing the friction and wear. Once there are snow particles in the contact, the wear rate becomes independent of temperature because oxidative wear governs the mild wear process. In the absence of snow, the tribological process is controlled by the low temperature brittleness in the temperature range from 3 °C to −15 °C. Cracks are prone to form on the worn surfaces, which extend gradually and result in the spalling of bulk scraps. The bulk scraps are subsequently crushed into tiny debris that sharply increase the friction coefficient and wear rate due to strong abrasion. When the temperature decreases to −25 °C, an ice layer condenses on the metal surfaces and has a similar effect on the tribological process to that of the added snow particles. The ice layer also causes hematite (Fe2O3) to form flakes that decreases the friction coefficient and wear rate. Materials and Methods Materials The materials used in the research were cut from R7 wheel and UIC60 900A rail steels, both of which are commonly used wheel and rail materials. The chemical composition (wt.%) for the R7 wheel is 0.7% C, 0.3% Si, 1.0% Mn, 0.04% P, 0.04% S. For the UIC60 900A rail the composition is 0.52% C, 0.4% Si, 0.8% Mn, 0.035% P, 0.035% S. Impact toughness measurement The impact toughness was measured according to a standard method for metallic materials, ISO 148-1 (International Standard for Metallic Materials-Charpy Pendulum Impact-Test Part 1: Test Method). Specimens for the impact toughness measurement were manufactured from UIC60 900A rail steels by wire cutting into a cuboid shape (10 × 10 × 55 mm3), containing a V-notch of 2 mm in depth with a 45° angle. A JBDS-300C digital low temperature Charpy pendulum impactor was applied at testing temperatures of 20 °C, 3 °C, −5 °C, −15 °C, −25 °C, −35 °C, respectively. Tests were repeated three times at each temperature level. Tribology testing technique The friction and wear tests were conducted using a pin-on-disc tribometer that contained a horizontally rotating disc and a dead-loaded pin (Fig. 8). A group of weights connecting the fulcrum through a beam provide the normal force at the contact between disc and pin. The rotation rate is controllable so that a pure sliding contact is achievable at various speeds between the pin and disc. The discs were manufactured from R7 wheel and pins from UIC60 900A rail steel. The pins featured a uniform tip radius of 5 mm and the discs (50 mm in radius) were flat. Accurate grinding was performed so that both the pin and disc surfaces had a centre-line-average roughness of 0.6 μm, which is common on railway wheels and rails48. Before testing commenced, all the samples were subjected to a standard cleaning procedure: 10 min ultrasonic cleaning in heptane and methanol, respectively, followed by oven-drying at 100 °C for 20 min. The sliding speed was fixed at 0.01 m s−1. Two contact pressures were chosen, 900 MPa and 1500 MPa (calculated using Hertzian contact theory49), This combination of sliding speed and contact pressures represents typical rail head-wheel tread contact conditions50. The tests were carried out in a quasi-sealed, temperature-controlled environmental chamber at temperatures of 3 °C, −5 °C, −15 °C, −25 °C, −35 °C. Half of the tests were conducted with the addition of natural fresh snow particles, collected as needed. The snow particles were added to the pin-disc contact every 5 min with a 17 ml spoon. Every test condition was repeated three times. Each test lasted 30 min (a sliding distance of 18 m). The friction force was measured by a HBM Z6 load cell throughout the tests. The friction coefficient was calculated by dividing the friction force by the normal force. An average for each test was calculated using the friction data from the last 10 min to exclude the running-in phase. Mean values and standard deviations were the final form of the friction results. These values were calculated from the averages of the three repeats within each test condition. The wear volume of the pin was calculated based on the equation for an ellipsoid segment after measuring the wear scar with a Nikon MM-60 measuring microscope. The specific wear rate was calculated using Archard’s equation (2)43: where K is the wear rate, V the wear volume, F the normal force and s the sliding distance. The wear rate results were also in the form of mean values and standard deviations for the three repeats within each test condition. Characterisation Features of the worn surface were observed using SEM (Hitachi S-3700N). Chemical compositions at specific areas were measured by EDS (Bruker XFlash 6–10). The microstructure of specimens was examined using SEM (JSM-7800F Field Emission Scanning Electron Microscope). The imaged surface was first ground with 400 grit, 800 grit and 1200 grit sandpaper and then polished and etched with 4% nital for 30 sec. The cross-sectional wear tracks on the disc samples were measured using a Talysurf PGI 800 (Taylor/Hobson Precision, UK) with a stylus tip radius of 2 μm. The examined distance was 4 mm and the gap between each sample point was 5 μm. The morphology of the collected snow particles and condensed ice layers on the disc surface were observed using an OM (Olympus BH2 System Microscope). Additional Information How to cite this article: Lyu, Y. et al. Open System Tribology and Influence of Weather Condition. Sci. Rep. 6, 32455; doi: 10.1038/srep32455 (2016). This research was performed under the auspices of the KTH Railway Group, with the financial support of Stockholm Country Council, Traffic Administration and Swedish Transport Administration. The authors acknowledge Dr. F. Sui and Mrs. W. Long from the Department of Materials Science and Engineering, Royal Institute of Technology for help with the SEM observations. Y.Z.L. is grateful for thescholarship from the China Scholarship Council (CSC). Author Contributions Y.L., E.B. and U.O. conceived the research idea. Y.L. performed the tribological tests and the characterisation. Y.L., E.B. and U.O. analysed and discussed the tribological performance obtained from the experimental results. All authors contributed to the writing of the manuscript. Figure 1 Impact energy of UIC60 900A rail steel as a function of temperature, showing a ductile-brittle transition with temperature decrease. Figure 2 Results (mean value and standard deviation) of the (a) friction coefficient and (b) wear rate on the pins as a function of temperature (the results from −35 °C to 3 °C in black and blue are from the current research project and the results from 3 °C to 20 °C in red are cited from a previous study13 for comparison). (c–j): Wear track profiles of discs tested at two loads and different temperatures with or without snow addition. Figure 3 SEM micrographs of the oxide flakes on the worn surfaces of pins tested with snow addition at: (a) 900 MPa/3 °C, (c) 900 MPa/−35 °C and (e) 1500 MPa/−15 °C. Area EDS analyses of the corresponding oxide flakes: (b) 900 MPa/3 °C, (d) 900 MPa/−35 °C and (f) 1500 MPa/−15 °C. Figure 4 Schematics showing the changing of snow particles into a water layer according to the pressure melting theory. Figure 5 SEM observation of (a) typical microstructure of UIC60 900A rail steel and (b) a phase boundary between pearlite and ferrite. Cracks on the worn surfaces of pins tested without added snow at (c) 900 MPa/−15 °C (the crack is likely to extend along the pearlite-ferrite phase boundary), (d) 900 MPa/−5 °C, (e) 1500 MPa/−15 °C and (f) 1500 MPa/−5 °C. Figure 6 Macroscopic morphology of the wear debris on the worn surfaces of the pins tested without snow addition at: (a) 900 MPa/−5 °C and (b) 1500 MPa/−15 °C. Microscopic morphology and EDS analyses of the wear debris: (c,d) 900 MPa/−5 °C and (e,f) 1500 MPa/−15 °C. Figure 7 An explanation of low friction coefficient and wear rate below −15 °C without snow addition. (a) Oxide flake on the worn surface of pin tested at 1500 MPa/−35 °C. (b) area EDS analysis of the oxide flake shown in (a). (c) Macroscopic and (d) microscopic morphology of the ice layer condensed on the disc at 1500 MPa/−35 °C. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3233210.1038/srep32332ArticleIn silico modelling of a cancer stem cell-targeting agent and its effects on tumour control during radiotherapy Marcu Loredana G. a12Marcu David 11 Faculty of Science, University of Oradea, Oradea 410087, Romania2 School of Physical Sciences, The University of Adelaide, SA 5005, Australiaa loredana@marcunet.com30 08 2016 2016 6 3233208 03 2016 03 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Head and neck cancers (HNC), like most solid tumours, contain a subpopulation of cancer stem cells (CSC) that are commonly responsible for treatment failure. Conventional therapies are unsuccessful in controlling CSCs, thus novel, targeting therapies are needed. A promising agent is ATRA (All-trans-retinoic acid) that was shown to induce CSC differentiation, cell cycle redistribution and CSCs radiosensitisation. To add to the limited data, this work simulated the effects of ATRA on a virtual HNC and evaluated tumour response to radiotherapy. A Monte Carlo technique was employed to grow a HNC consisting of all lineages of cancer cells. The biologically realistic input parameters led to a pre-treatment CSC population of 5.9%. The Linear Quadratic model was employed to simulate radiotherapy. ATRA-induced differentiation, cell arrest and apoptosis were modelled, based on literature data. While the effect of differentiation was marginal, the strongest influence on CSC subpopulation was displayed by ATRA’s cell arrest effect via an exponential behaviour of the dose-response curve. The apoptotic effect induced by ATRA shows linear correlation between the percentage of apoptotic cells and dose required to eradicate CSCs. In conclusion, ATRA is a potent CSC-targeting agent with viable impact on tumour control when combined with radiotherapy. ==== Body Cancer Stem Cells (CSC) and their Role within the Tumour Locally advanced head and neck carcinomas (HNC) are aggressive tumours due to several radiobiological factors such as: hypoxia, elevated levels of the endothelial growth factor receptor and accelerated repopulation during treatment. Beside these factors the response to irradiation is also dictated by tumour composition, mainly by the presence of stem-like cells that hold the ability to proliferate indefinitely. The current literature is filled with an ever-growing body of evidence towards the existence of cancer stem cells. These cells represent a subpopulation of tumour cells that proliferate indefinitely, are tumorigenic and also more quiescent than non-cancer stem cells1. Furthermore, these cells are considered to be accountable for treatment resistance and failure, as well as tumour recurrence. The ability to divide symmetrically is another powerful tool that cancer stem cells use for their survival. Symmetrical division of cancer stem cells is the process whereby in mitosis, both resulting cells are stem cells. Since cancer growth is sustained by this small subpopulation of cancer stem cells, their symmetrical division further increases the subpopulation and, consequently, resistance to treatment. Based on a study looking at the expression of CSC marker proteins in a head and neck squamous cell carcinoma xenograft mouse model, Geissler et al. have assumed that CSCs can be sub-classified into migratory and stationary cancer stem cells2. Consequently, stationary CSCs are quiescent in nature while migratory CSCs are active and invasive, thus being responsible for tumour growth and regrowth. The main properties of CSC are summarised below:Long-lived and have the ability to proliferate indefinitely (Moore et al.1) Can generate all heterogeneous lineages of the original tumour (Al Hajj et al.3) Can recreate themselves by symmetrical division Morrison et al.4 Are more resistant than non-stem cancer cells Moore et al.1 Preferentially reside in certain microenvironmental niches within the tumour (often prefer hypoxic environment) Peitzsch et al.5 Can be classified into migratory CSCs (i.e. active and invasive) and stationary CSCs (i.e. quiescent, non-invasive) Geissler et al.2 Experimental studies on the phenotypic heterogeneity of tumours have shown that cancers comprise of various cell subpopulations with heterogeneous molecularity, which confers them distinct biological behaviour2. Consequently, among these varied subpopulations there are cell groups with different features that are linked to invasiveness and metastases, radioresistance, resistance to chemotherapy, etc. Eventually, the extent of the more aggressive subpopulations will dictate the fate of the tumour. This fact is prompting the need for the quantification of the CSC subpopulation. Tumour cell line experiments have shown that the percentage of CSC varies severely among tumours of different histopathological type. While a low percentage of CSCs have been found in acute myeloid leukaemia (0.4%), colon cancers have been suggested to have a much higher subpopulation of CSCs (82.7%)6. In head and neck tumours, the first identification of CSC has been reported by Prince et al. who has isolated a cellular subgroup exhibiting stem-like properties7. To date, the number of quantitative reports in the literature on the percentage of CSC in head and neck cancer is very scarce. The existing literature illustrate that there are significant differences among the studied head and neck cell lines. Accordingly, in the experiments conducted by Tang et al. the CSC proportion in various head and neck cell lines ranged between 1.7% and 13.5%8. The experiment undertaken by Harper et al. on HNC cell lines has indicated that the proportion of CSC in CaLH3 cell line is 12.3%9. There are experimental studies that focused on the characterisation of CSC cells through stem cell markers. Given that the number of such studies is still scant and the results inconclusive, there is need for additional tools that could assist in explaining the impact of CSC subpopulations within head and neck cancers on treatment outcome10. It is therefore important to determine the pattern of CSC contribution to tumour proliferation during radiotherapy and its role in tumour recurrence by quantitative means. CSC and Resistance to Treatment Advanced and unresectable head and neck cancers are traditionally treated with chemo-radiotherapy. Conventional radiotherapy delivers a total dose of 70Gy in 2Gy fractions over 7 weeks, with limited tumour control. However, tumour hypoxia and repopulation hinder the efficacy of conventional radiotherapy. A more effective schedule is hyperfractionated radiotherapy11, whereby smaller doses are delivered twice a day (1.2Gy per fraction) over the same time period, thus totaling 84Gy. This type of fractionation overcomes to certain extent tumour repopulation in between fractions and stimulates reoxygenation. Cancer stem cells are an added challenge to head and neck radiotherapy as CSCs have been shown to be more resistant to radiation than differentiated or non-CSC1. This behaviour prompts for the development of CSC-targeted therapies that could sensitise the cells to the effect of radiotherapy. CSC-Targeting Therapies: All-Trans-Retinoic Acid (ATRA) Given that the differentiated state assures better response to radiotherapy, a plausible strategy to increase tumour control would be to stimulate CSC differentiation. One of the agents that was found to exhibit a powerful differentiating potential is all-trans-retinoic acid (ATRA)1213. ATRA is a member of the retinoid family and is an active metabolite of vitamin A. Retinoids present a potent effect on cell growth, differentiation and apoptosis and influence multiple signaling pathways that are involved in stem cell preservation14. Both in vitro and in vivo pre-clinical studies showed that ATRA has powerful effects on CSCs by inducing cell cycle arrest due to the complexity of DNA damage and also apoptosis1213. Furthermore, differentiation caused by ATRA was observed in the previously mentioned studies, which was associated with downregulation of the Wnt pathway, a central mechanism controlling malignant transformation. The overall effects of ATRA have led to a decrease in the surviving fraction when ATRA was combined with radiotherapy13 (Fig. 1). CSC-targeting agents, including ATRA, represent an innovative approach towards cancer management and they are currently being investigated in pre-clinical settings. The present work is therefore an added tool that allows the investigation of the potential effects of ATRA on head and neck cancer. The Aim and Justification of the Current Work The aim of this work is to integrate the properties of CSCs into a virtual hypoxic head and neck cancer grown via Monte Carlo techniques in order to quantify the behaviour of CSC during hyperfractionated radiotherapy. Another important goal was to evaluate tumour response as a function of the interplay between radiotherapy and ATRA. The current work focuses on head and neck squamous cell carcinomas, as they are one of the most radiobiologically challenging tumours. The reason to choose a stochastic approach to model tumour growth and response to treatment is to better fit the biological reality whereby the cellular phenotype, malignant growth, cellular damage, and cell kill due to either natural causes or irradiation, are all driven by probabilistic phenomena. Furthermore, within the model, each cell is followed throughout its life and treatment, knowing its age, phenotype, position in the cell cycle, number of generations and its oxygenation level. Due to the lack of quantitative data regarding the CSC division pattern within head and neck tumours, the goals of the current work are:To quantify the fraction of CSC during hyperfractionated radiotherapy and evaluate the influence of symmetrical division of CSCs on tumour response to treatment; To implement the properties of ATRA (i.e. differentiation, cell arrest, apoptosis) in the model and to evaluate the efficacy of each property on tumour response during radiotherapy; To analyse the effect of the CSC-targeting agent on the tumour as a whole. Results All the results shown below have been achieved by treating the virtual tumour with hyperfractionated radiotherapy. The first section shows the effect of high symmetrical division probabilities on tumour response to radiotherapy alone, while all other sections present the results of ATRA when combined with hyperfractionated radiotherapy. The influence of symmetrical division on CSC subpopulation and response to hyperfractionated radiotherapy To illustrate the impact of symmetrical division probability (SDP) on CSC subpopulation a scenario involving moderately hypoxic HNC with various SDPs for cancer stem cells has been modeled (Fig. 2). SDP has been varied from the initial 1.9% up to a percentage that resulted in uncontrolled tumour growth, which was found to be 30%. The aim was to determine the treatment time required for complete tumour eradication and to evaluate the quantitative link between the probability of symmetrical division and the percentage of CSCs in the tumour. Tumour eradication has not been achieved within the clinically allocated treatment time (7 weeks) for percentages of CSC SDP larger than (or equal to) 10%. For percentages as high as 30 and over, the tumour seems uncontrollable, at least with the current treatment technique. Comparing the plateau values in Fig. 2, it is observed that each 10% increase in the probability of symmetrical division leads to 10% increase in the percentage of CSC subpopulation (particularly for tumours with a SDP greater than 10%). The effects of ATRA on cancer stem cells Three main properties of ATRA have been modelled: differentiation (ATRA 1), cell cycle arrest (ATRA 2), and induction of apoptosis (ATRA 3). The differentiation mechanism manifests through the loss of symmetrical division of stem cells. Both the independent as well as the combined effect (ATRA1+2+3) of the above properties have been studied (Fig. 3). Since differentiation yields in reduction of SDP, the effect of this mechanism can be deducted from Fig. 2. For a tumour that exhibits SDP of 20%, if differentiation reduces this value to 10%, Fig. 2 shows that the ATRA-induced effect results in a dose de-escalation of 32%. Applying the same principle to the tumour with 30% SDP presented in Fig. 2, we observe that a drop of 10% due to ATRA differentiation would control a tumour that otherwise was uncontrollable. The head and neck tumour studied in the employed model displays a naturally low SDP of 1.9%, which negates the effect of ATRA-induced differentiation in this particular tumour. Therefore, as shown in Figs 3 and 4, there is no difference in CSC response when the SDP is varied from 1.9% to 0.1%. The surviving curves in Fig. 3 that represent the RT-only scenario and RT+ATRA1 show minimal difference (3 dose fractions). Figure 4 illustrates the effect of differentiation when combined with cell arrest with or without apoptosis. The differences in the total dose to control the CSC subpopulation among tumours with varied SDP are 1.1 Gy with cell arrest and 1.2 Gy with cell arrest and apoptosis. The effect of differentiation through reduction of SDP was marginal due to the already small pre-treatment SDP of 1.9%. This parameter would have a higher impact in tumours with large initial SDPs, similar to the hypothetical scenarios presented in Fig. 3. Due to this result all further simulations have been processed with 1.9% SDP as in the initial tumour growth model. However, it is to be noted that by simply arresting the cells in the G2 phase, ATRA inhibits proliferation thus inducing a significant improvement in CSC response to hyperfractionated radiotherapy. With cell arrest (ATRA1+2), there is a 12-fraction difference as compared to radiotherapy-alone for the same tumour response. This corresponds to a dose de-escalation of 14.4 Gy. Also, the effect of apoptosis decreases the total dose needed for CSC eradication with a further 10.8 Gy. The effect of ATRA on cell cycle distribution To investigate the dose-dependent response of CSC to ATRA, various scenarios involving different percentages of CSCs arrested in the G2 phase have been simulated (as described in Methods) for a fixed percentage of apoptotic death among the blocked cells. Extreme percentages (10% and 90%) have been modelled to evaluate the least optimal and the best-case scenarios. Figure 5 shows a supra-linear relationship between the fraction of cell cycle arrest and CSC subpopulation response to treatment, thus implying a very potent effect on the overall response. ATRA and induction of apoptosis Similarly to the effect of cell arrest, apoptosis was simulated within the (10–90%) range as described in Methods, for a fixed percentage of cells arrested in G2. The effect of apoptosis on CSC response seems to increase linearly with the percentage of apoptotic cells (Fig. 6), thus showing a less pronounced influence as opposed to the effect of cell arrest. Comparison of ATRA effects on CSCs The individual effects of ATRA on CSCs have been presented in one graph to illustrate their influence on tumour response. The current parameters for the modelled HNC allow little variation for SDP. Given the initial low percentage of 1.9%, any further reduction has a negligible effect on tumour control, suggested by the constant line in Fig. 7. To enable the representation of the three effects in one common graph, the initial SDP of 1.9% has been considered 100% of possible effect. The apoptotic effect induced by ATRA shows linear correlation between the percentage of apoptotic cells and dose required to eradicate CSCs. Unexpectedly, the strongest influence on CSC subpopulation control has been displayed by ATRA’s cell arrest effect, illustrated by an exponential behaviour of the dose-response curve (Fig. 7). Discussion The current work has analysed the radiobiological challenges raised by the CSC subpopulation in a virtual hypoxic head and neck cancer. The model has simulated the properties of cancer stem cells during radiotherapy and has shown that the percentage of CSCs increases considerably during treatment, due to their radioresistance. This result is in accordance with the literature findings13. The ability to divide symmetrically is a potent tool of CSCs, and yet to be quantified. Due to the lack of such data in the scientific literature, the model has considered various scenarios when the symmetrical division probability is increased during radiotherapy and has concluded that high percentages of symmetrical division of CSCs enable uncontrolled tumour proliferation. Quantification of symmetrical division probability shows the high impact of this parameter on tumour composition. Tumour eradication has not been achieved within the clinically allocated treatment time (7 weeks) for percentages of CSC SDP larger than (or equal to) 10%. Thus high percentages of SDP represent a challenge in radiotherapy, reason why CSC-targeting agents are currently trialed in pre-clinical studies. All-trans-retinoic acid has proven to be an effective agent with a potential to induce cell arrest and apoptosis. To add to the literature data, we have developed an in silico tool to study the three main features of ATRA: differentiation, cell cycle arrest, and induction of apoptosis. The effect of differentiation through reduction of SDP was minimal, which is due to the already small pre-treatment SDP of 1.9%. This parameter would have a higher impact in tumours with large SDPs, similar to the hypothetical scenarios presented in Fig. 2. Induction of cell arrest by ATRA is a potent targeting approach in HNC. The G2 phase of the cell cycle is known to have an increased radiosensitivity, therefore cells that are arrested in this phase in order to repair their ATRA-induced DNA damage, are also more exposed to cell kill during radiotherapy. Furthermore, given that HNC are rapidly growing tumours, meaning that the cycling population exhibits greater kinetics along the cell cycle, the two doses of radiation administered during hyperfractionated radiotherapy are an added benefit to efficient tumour kill. When employing various percentages of cell arrest, the model showed an exponential correlation between this parameter and the tumoricidal dose. Apoptotic cell death induced by ATRA was shown to be linear in relation to the total dose. For both cell cycle arrest and apoptosis, extreme values have been simulated in order to analyse the least optimal as well as the best-case scenarios. Given the low initial rate of symmetrical division, which denied ATRA the possibility to intervene as a differentiating agent, ATRA was proven to be a potent radiosensitising and CSC-targeting agent for head and neck cancer with viable impact on tumour control when combined with radiotherapy. This shows the critical importance of determining quantitative values for the pre-treatment CSC subpopulation and for the rate of symmetrical division. Each histopathological tumour type is likely to have its own value for the above-mentioned parameters and we expect the cell arrest and apoptotic effects to remain exponential and linear, respectively, with differentiation adding another strong influence on treatment outcome. Therefore, given the dose-dependent response of CSCs to ATRA, it is crucial to obtain both quantitative and qualitative knowledge on CSC dynamics in order to describe the resistant subpopulation and to design efficient and less toxic treatment regimens in head and neck oncology. Methods Simulation of head and neck tumour growth The first step of this work was the growth simulation of a head and neck cancer, having biologically realistic growth kinetic parameters. Consequently, the head and neck cancer grown within the model has some standard values, in good correlation with the literature averages as shown in Table 1. The tumour growth algorithm follows a Monte Carlo technique that takes probabilistic decisions based on input parameter values obtained from the literature (Table 1). The tumour growth module has been described previously1516. The tumour growth module generates a probabilistic value for the type of new cell to be created. The hierarchical cell lineage is comprised of (1) cancer stem cells (CSC), (2) differentiated cells (D) and (3) quiescent or resting cells (Q). Cancer stem cells have the ability to procreate indefinitely and can undergo symmetrical division by giving birth to two stem cells, while differentiated cells are only able to contribute to tumour growth for 3 generations after which they die. Quiescent cells reside in the G0 phase outside the cell cycle and represent about 85% of the total cell population, value that has been obtained through multiple iterations. With every cell generation, a new cell-cycle time is allocated to both the original as well as the newly created cell. These cell-cycle time values are generated according to an asymmetrical Gaussian distribution truncated at one standard deviation towards lower values and 2 standard deviations towards higher values. This approach is in agreement with the literature data whereby the average head and neck cell cycle time is 33 h, ranging from 20 h to 60 h17. The tumour has been grown until a clinically detectable size of 107 cells. The CSC subpopulation modelled here has biological and radiobiological characteristics according to the latest experimental findings. Consequently, CSCs in the current model exhibit: indefinite proliferation capacity1, CSC-specific division pattern (both symmetrical and asymmetrical division)3 and the ability to generate all heterogeneous lineages of the original tumour3. Furthermore, the radioresistance of CSCs was established according to the literature18 and adapted for HNC. Since hypoxia is an important factor that contributes to the overall tumour response to radiotherapy, the virtual head and neck cancer is considered to be moderately hypoxic, in order to represent the average patient group. Every 24 hours the model generates a set of statistical results based on its current state that are stored in a result file for later interpretation. All random generators employed by the model are using the Mersenne Twister algorithm (a pseudorandom number generator) in its 32 bit implementation, allowing for generation of good quality random numbers at sensible speed. Modelling radiotherapy with ATRA as CSC-targeting agent Proliferating cells cycle along the four phases of the cell cycle (M, G1, S, G2) whereas non-proliferating cells rest in the quiescent phase (G0). Each phase of the cycle has been correlated with a phase-specific surviving fraction derived from the literature19. Surviving fractions have been determined using the Linear Quadratic model starting from the premise that the average surviving fraction of HNC after 2Gy is 54%17. The effects of ATRA, as a CSC-targeting agent have been implemented into the model. The three effects that have been suggested by the literature to be of importance when targeting CSCs are: differentiation, cell cycle arrest and apoptosis1213. Differentiation has been simulated by reducing the symmetrical division probability from the initial 1.9% (see Table 1) to 0.1% in a step-like manner. Cell cycle arrest in the G2 phase has been modelled based on the work of Bertrand et al.13. They have shown that administration of ATRA prior to radiotherapy has increased the CSC population in the G2/M phase for up to 48 h, with a peak of 80% cells being arrested after 24 h following radiotherapy. Studies in mice have shown that the effect of ATRA on CSCs is dose-dependent12. In the model we have considered the effects of various doses of ATRA leading to different percentages of cells being arrested (from 10% to 90% cell arrest). Cells are blocked in the G2 phase in order to undergo radiation-caused DNA damage repair. However, part of the cells will not be able to repair their DNA breaks, reason why they will die via apoptosis. Regarding the percentage of cells that are eliminated through apoptosis, a sensitivity study has been conducted with values from 10 to 90%. To sum up, the three variables that have been modelled as the effect of ATRA on CSCs are as follows:Differentiation, by varying the symmetrical division probability (0.1–1.9%); Cell arrest, by varying the percentage of cells blocked in G2 (10–90%). Apoptosis, by varying the percentage of cells arrested in G2 that undergo apoptosis (10–90%). Additional Information How to cite this article: Marcu, L. G. and Marcu, D. In silico modelling of a cancer stem cell-targeting agent and its effects on tumour control during radiotherapy. Sci. Rep. 6, 32332; doi: 10.1038/srep32332 (2016). This work was supported by a grant of the Ministry of National Education, CNCS-UEFISCDI, Project no. PN-II-ID-PCE-2012-4-0067. Author Contributions L.G.M. and D.M. have equally contributed to this work. L.G.M. developed the study concept, processed the data and drafted the manuscript. D.M. wrote the code for simulation and provided critical revision of the manuscript. Both L.G.M. and D.M. have analysed and interpreted the data. Both authors approved the final version of the manuscript. Figure 1 ATRA and its potential properties as indicated by in vitro and in vivo studies. Figure 2 The impact of symmetrical division probability on CSC subpopulation in a moderately hypoxic HNC. Figure 3 Survival curves of the CSC subpopulations under hyperfractionated radiotherapy and various ATRA effects for 0.1% SDP. Figure 4 The effect of differentiation when combined with cell arrest without apoptosis (ATRA 1+2) and with apoptosis (ATRA 1+2+3). Figure 5 The effect of cell arrest induced by ATRA on the CSC subpopulation. Figure 6 The effect of apoptotic death caused by ATRA on the CSC subpopulation. Figure 7 Comparison of the ATRA effects on CSCs. Table 1 Tumour growth parameters. Tumour growth parameters Model values Input parameters  Length of S phase 11 h17  Mean cell cycle time (range) 33 h (20 – 60h)19  Duration (proportions) of cell cycle phases M:7%; G1:40%; S:30%; G2:23%17  Cell loss factor 85%19 Model-derived parameters  Volume doubling time 52 d20  Labelling index 4.7%21  Cell division rate (24h) 1.3%  Pre-treatment probability of CSC symmetrical division 1.9%  Pre-treatment percentage of CSCs 5.42% ==== Refs Moore N. & Lyle S. Quiescent, slow-cycling stem cell populations in cancer: a review of the evidence and discussion of significance . J. Oncol . 396076 (2011 ).20936110 Geißler C. et al. The challenge of tumor heterogeneity–different phenotypes of cancer stem cells in a head and neck squamous cell carcinoma xenograft mouse model . In Vivo 26 , 593 –598 (2012 ).22773573 Al Hajj M. , Wicha M. S. , Benito-Hernandez A. , Morrison S. J. & Clarke M. F. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3172010.1038/srep31720ArticleThe Association between Ideal Cardiovascular Health Metrics and Extracranial Carotid Artery Stenosis in a Northern Chinese Population: A Cross-Sectional Study Hao Zhiru 1*Zhang Yong 1*Li Yongming 1Zhao Jinbo 2Zhou Yong 3Qiu Jing 4Zhao Ruiping a1Hu Jiang b51 Department of Cardiology, Central Hospital of Baotou, Baotou, 014040 China2 Graduate school, Baotou Medical College, Baotou, 014040 China3 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050 China4 School of Public Health, Ningxia Medical University, Yinchuan, 750004 China5 Department of Surgery, Central Hospital of Baotou, Baotou, 014040 Chinaa ruipingzhao@163.comb hujiang1961@aliyun.com* These authors contributed equally to this work. 30 08 2016 2016 6 3172001 02 2016 26 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Past epidemiologic studies have indicated that the ideal cardiovascular health (CVH) metrics are associated with a lower risk of cardiovascular diseases (CVDs) and stroke. Carotid artery stenosis (CAS) causes approximately 10% of ischemic strokes. The association between ideal CVH and extracranial CAS has not yet been assessed. In the current study, extracranial CAS was assessed by carotid duplex ultrasonography. Logistic regression was used to analyze the association between ideal CVH metrics and extracranial CAS. A total of 3297 participants (52.2% women) aged 40 years and older were selected from the Jidong community in China. After adjusting for sex, age and other potential confounds, the odds ratios (95% confidence intervals) for extracranial CAS were 0.57 (0.39–0.84), 0.46 (0.26–0.80) and 0.29 (0.15–0.54), and for those quartiles, quartile 2 (9–10), quartile 3 (11) and quartile 4 (12–14), respectively, compared with quartile 1 (≤8). This negative correlation was particularly evident in women and the elderly (≥60 years). This cross-sectional study showed a negative correlation between the ideal CVH metrics and the prevalence of extracranial CAS in northern Chinese adults. ==== Body Carotid artery stenosis (CAS) causes approximately 10% of ischemic strokes1. Approximately 7% of first ischemic strokes were associated with extracranial CAS2. Data from the Global Burden of Disease Study 2010 (GBD2010) indicated that the leading cause of death in China is stroke3. Furthermore, previous studies have indicated that many patients with CAS have a greater risk of dying due to myocardial infarction (MI) than from stroke45. In the Framingham Heart Study, the prevalence of CAS in people aged 66 to 93 years was 7% in women and 9% in men6. CAS refers to an atherosclerotic narrowing specifically of the extracranial CAS, the internal CAS or the common CAS7. Genetic susceptibility may play a key role in the development of CAS, and there may be different pathophysiologies for the different CAS locations89. However, there are other possible factors in the development of CAS, including differences in the prevalence of risk factors or of particular life styles across different ethnic populations10. Due to the high prevalence of extracranial CAS, the study of risk factors and protective measures for extracranial CAS has particular public health significance in China. The American Heart Association (AHA) has defined ideal cardiovascular health (CVH) as including four ideal health behaviors (body mass index, physical activity, healthy diet, and smoking status) and three ideal health factors (total cholesterol, blood pressure and fasting blood glucose)11. Worldwide, cardiovascular diseases (CVDs) remain a major public health burden and are expected to increase over the next 10 years as the population ages1112. Several studies have suggested that the ideal CVH metrics were remarkably negatively associated with the total incidence of CVD and stroke11131415. In addition, a study based on 5440 Chinese adults found a clear gradated negative relationship between a higher number of ideal CVH metrics and a lower prevalence of asymptomatic intracranial carotid artery stenosis (ICAS)16. However, the association between the ideal CVH metrics in the AHA definition and extracranial CAS is still unclear. Therefore, a cross-sectional analysis was conducted to explore this association in a northern Chinese cohort that consisted of 3297 adult participants. Results From the initial sample of 4428 participants, 369 participants were excluded because of physical disabilities or because they did not provide informed consents and 762 participants were excluded because of incomplete data on their health factors, health behaviors or other variables. Finally, 3297 participants were included in the final analysis. Table 1 shows the basic characteristics of the participants stratified by sex. Women tended to be younger, lower educated and of average income. Participants with heavy alcohol consumption were almost always male (99% vs 1%). In addition, parameters such as BMI, SBP, DBP, FPG and TG were higher in men, while TC was lower in men, compared to the values of those parameters in women. Table 2 shows the association between each CVH metric and the prevalence of extracranial CAS. After adjusting for sex, age, alcohol use, average monthly income of each family member, education level and the other six cardiovascular health metrics, we found that the ideal smoking status, blood pressure, total cholesterol and fasting blood glucose metrics were significantly associated with a lower prevalence of extracranial CAS (OR = 0.55, 95% CI: 0.35–0.85, P = 0.007; OR = 0.46, 95% CI: 0.25–0.84, P = 0.012; OR = 0.45, 95% CI: 0.24–0.85, P = 0.014; OR = 0.55, 95% CI: 0.34–0.90, P = 0.017; respectively). In further stratified analyses, the negative associations of extracranial CAS with the ideal blood pressure and ideal total cholesterol were significant (P ≤ 0.05) in men but not in women, and the negative correlation of extracranial CAS with the ideal total cholesterol and ideal fasting blood glucose were only found in middle-aged groups (40–60 years of age). Similarly, the negative correlation with the ideal smoking status was particularly evident in women and the elderly (≥60 years). Table 3 shows the relationship between the total score of the ideal CVH metrics and the prevalence of extracranial CAS. After adjusting for sex, age, alcohol use, average monthly income of each family member, and education level, participants in the highest quartile of the ideal CVH metrics summary score had a lower prevalence of extracranial CAS compared to those in the lowest quartile of the summary score (OR = 0.29, 95% CI: 0.15–0.54, P < 0.001). The stratified analyses found that this significant negative correlation was still evident particularly in men (P < 0.001) and the elderly (≥60 years) (P < 0.001). Discussion The main strengths of the present study are as follows. 1) The preliminary analysis showed that the ideal smoking status, blood pressure, total cholesterol and fasting blood glucose metrics were significantly associated with a low prevalence of extracranial CAS in the total population compared to the poor group. 2) Our data indicated that individuals in the highest quartile of the total ideal CVH metrics had a 71% reduced risk of developing extracranial CAS compared to those in the lowest quartile, after adjusting for potential confounds (sex, age, alcohol use, average monthly income of each family member and education level). 3) A similar negative correlation was observed in subgroups of women and the elder (≥60 years). ECAS is a subclinical indicator for stroke and cerebrovascular diseases. The association between ECAS and CVD suggests that CVD may primarily contribute to ECAS and then lead to cerebrovascular diseases via subclinical cerebrovascular changes. To our knowledge, this study is novel in its exploration of the potential association between the ideal CVH and extracranial CAS in an adult Chinese population. Previous studies have investigated the combined association of extracranial CAS prevalence and different risk factors on atherosclerosis. The Framingham Heart Study, a multivariate logistic regression model, showed that age, cigarette smoking, systolic blood pressure, and cholesterol were independently related to carotid atherosclerosis617. Similar to previous studies17181920, we showed that the ideal metric of smoking status was inversely associated with extracranial CAS. In the Cardiovascular Health Study19, the severity of CAS was greater in current smokers than in former smokers, and the severity of CAS was significantly associated with pack-years of exposure to tobacco. Similarly, the Framingham Heart Study found that extracranial CAS was correlated with the quantity of cigarettes smoked over time, especially in women17, which is consistent with our findings. Although the association in our study did not reach statistical significance (P = 0.086) in men, there was a highly significant trend across the total participants (P = 0.007). There was an OR of 1.33 (95% CI: 0.37–4.77) for intermediate smoking compared to sparse smoking that could have been caused by the small sample size of smokers, which could have led to insufficient statistical power. According to our study, the ideal metrics of blood pressure, total cholesterol and fasting blood glucose had inverse relationships with extracranial CAS. Previous studies on risk factors for extracranial CAS also showed similar results17212223. The Framingham Heart Study indicated that there was a 2-fold increased risk of carotid stenosis for every 20 mmHg increase in SBP17. Sutton-Tyrrell et al. found that a SBP of ≥160 mmHg was the strongest independent predictor of extracranial CAS, especially in the elderly21. Our study confirmed this association, in men but not in women, a finding that can be explained by physique differences between the sexes. The MESA study24 showed that total cholesterol was strongly associated with a carotid plaque lipid core and the Framingham Heart Study17 found that the relative risk (RR) of CAS was >25%, and increased approximately 1.1 for every 10 mg/dL increase in total cholesterol, which are findings that are both consistent with our results, particularly among middle-aged adults (40–60 years of age) compared to the elderly. Cholesterol levels often decline in the elderly, which may be a cause of the lower association in our study. In addition, our finding of a negative association between the ideal FPG and extracranial CAS is supported by results from the IRAS (Insulin Resistance Atherosclerosis Study)25, suggesting that the progression of carotid atherosclerosis is accelerated in persons with type 2 diabetes and that this increased rate of atherosclerosis is partially explained by the atherogenic risk factor profile associated with diabetes. Similarly, the Cardiovascular Health Study23 also reported that diabetes was associated with carotid IMT and the severity of CAS. In the present study, significant negative correlations between the ideal CVH body mass index, physical activity or health diet metrics and extracranial CAS were not observed. The previous study also found that physical activity was not associated with carotid atherosclerosis26. Previous studies found inverse associations between improving diet and weight management and the development of carotid atherosclerosis272829, which was in contrast to our study. The present study indicated that there was no significant relationship between diet and CAS (OR 0.81, 95% CI: 0.46–1.43; in those with a poor diet score compared to those with an ideal diet score), which is contrary to a previous study (ref. 27) in regard to the OR value. This inconsistency may be explained by the following two reasons. First, the two studies used different definitions of ideal diets, and in particular, the different ranges led to different cut-offs for ideal, intermediate and poor diet scores. Second, the association between the ideal diet score and CAS may be smaller in a Chinese population than in other populations, and therefore, our study may not have enough statistical power to detect the association (OR 0.81, 95% CI: 0.46–1.43, P = 0.28). In our study, participants were Han-ethnic Chinese, who probably have different physiques and lifestyles than other ethnic populations. Our study indicated a significant negative correlation between the ideal CVH metrics and the prevalence of extracranial CAS. Extracranial CAS has several causes including atherosclerosis, fibromuscular dysplasia (FMD), cystic medial necrosis, arteritis, and dissection, with the most frequent cause being atherosclerosis29. Atherosclerosis is a systemic disease and patients with extracranial CAS typically have an escalated risk of other adverse cardiovascular events, including myocardial infarction (MI), peripheral arterial disease (PAD), and death303132. Risk factors associated with extracranial CAS, such as cigarette smoking, hypertension, diabetes and hypercholesterolemia, are the same as those for atherosclerosis located elsewhere, but differences exist in the relative contribution to the risk in the various vascular beds. Therefore, it makes sense that maintaining the ideal CVH metrics may be the most effective means to avoid extracranial CAS. This is the idea of primordial prevention11. There are potential limitations of our study. First, the Jidong community involves mainly regional populations, so the results may not be generalizable across the nation due to geographic variations, and different educational, economic and cultural backgrounds. Second, this study was a cross-sectional study that did not have the capacity to evaluate causal relationships between the ideal CVH metrics and extracranial CAS. Therefore, our study can only speculate that maintaining CVH may be beneficial in reducing the risk of atherosclerosis. Prospective studies are needed to further examine the causality links. Third, carotid duplex ultrasonography is a noninvasive vascular test that may underestimate the severity of stenosis (especially in cases of less than 50% stenosis)33. However, carotid duplex ultrasonography is widely used for initial evaluations and to estimate CAS, and experienced sonographers are able to provide accurate and relatively inexpensive assessment of CAS via this method34. Fourth, the cardiovascular behavior measures, such as physical activity, smoking, and dietary intake, were from self-reported questionnaires, so misclassification was possible, especially in regard to diet and physical activity. Finally, extracranial CAS involves complex mechanisms like different etiologies and pathogeneses, which our study did not identify. Therefore, different potential risk factors and preventive strategies for CAS need to be explored further. In conclusion, the ideal CVH metrics were significantly associated with the prevalence of extracranial CAS in northern Chinese adults, especially in women and the elderly (≥60 years). This negative correlation indicates that maintaining an ideal CVH may be of great value in preventing extracranial CAS. Prospective studies are needed to further investigate these questions. Method Study Design and Participants From July 2013 to August 2014, 9,078 participants (man 4,768, aged 18–82 years old) were enrolled in the study cohort and comprised employees (including those who were retired) and their family members from the Jidong Co. Ltd, a large Oilfield in Hebei Province, China. In our study, the inclusion criteria were: (1) aged 40 years or older; and (2) without stroke, transient ischemic attack, and myocardial infarction (MI). Among the 9078 potential participants, 4428 satisfied the above inclusion criteria. In addition, participants were excluded from this study according to following exclusion criteria: (1) incomplete data on health factors or behaviors, or not providing informed consent, and (2) physical disabilities. Ethics Statement The study was performed according to the guidelines of the Helsinki Declaration, with the approval of the Ethics Committee of the Jidong Oilfield Hospital. All participants agreed to study participation and provided informed consents. Assessment of Cardiovascular Health Metrics Information about smoking, physical activity, and dietary intake was collected via questionnaires. Dietary habits were assessed with a brief semi-quantitative food frequency questionnaire3536, which had definitions similar to the AHA definitions of dietary habits (see Table 4). The definition of an ideal diet score in this study was as reported in our previous publication37. According to the AHA definitions11, we further categorized smoking status, physical activity and dietary intake into three groups: “ideal”, “intermediate” or “poor”. Smoking was classified as ideal (never or quit smoking >12 months previously), intermediate (quit smoking ≤12 months ago), or poor (currently smoking); physical activity was classified as ideal (≥150 min/week of moderate intensity or ≥75 min/week of vigorous intensity), intermediate (1–149 min/week of moderate intensity or 1–74 min/week of vigorous intensity), or poor (none). Healthy diet behaviors were classified as ideal (4–5 components), intermediate (2–3 components) or poor (0–1 component). Body mass index (BMI) was calculated based on the weight (accurate to 0.1 kg) and height (accurate to 0.1 cm) measurements of the participants, as body weight (kg)/the square of height (m2). Participants’ blood pressure was measured twice by experienced research nurses following 5 minutes of rest in a seated position using a mercury sphygmomanometer with a cuff of the appropriate size. The averages of the two systolic blood pressure (SBP) and diastolic blood pressure (DBP) readings were used for the analysis. If the deviation of the two measurements was more than 5 mm Hg, an additional reading was taken and the average of the three readings was used. All blood pressure was measured using the right arm. Hypertension was defined as the presence of a history of hypertension, using antihypertensive medication, a SBP ≥ 140 mm Hg, or a DBP ≥ 90 mm Hg. According to the AHA definitions11, BMI was classified as ideal (<25 kg/m2), intermediate (25 to 29.9 kg/m2) or poor (≥30 kg/m2); blood pressure was classified as ideal (SBP < 120 mmHg and DBP < 80 mmHg and untreated), intermediate (120 mm Hg ≤ SBP ≤ 139 mmHg, 80 mmHg ≤ DBP ≤ 89 mmHg, or treated to SBP/DBP < 120/80 mmHg), or poor (SBP ≥ 140 mmHg, DBP ≥ 90 mmHg, or treated to SBP/DBP > 120/80 mmHg). Blood samples were collected from the antecubital vein by trained research nurses in the morning following overnight fasting and were transfused into vacuum tubes containing EDTA. The tubes were then centrifuged for 10 minutes at 3000 rotations per minute at 25 °C. After separation, plasma samples were used within 4 hours. All biochemical variables, including total cholesterol and fasting blood glucose, were measured using an autoanalyzer (Olympus, AU400, Japan) in the central laboratory of the Jidong Oilfield Hospital. According to the AHA definitions11, fasting blood glucose was classified as ideal (<100 mg/dL and untreated), intermediate (100 to 125 mg/dL or treated to <100 mg/dL), or poor (≥126 mg/dL or treated to ≥100 mg/dL); total cholesterol was classified as ideal (<200 mg/dL and untreated), intermediate (200 to 239 mg/dL or treated to <200 mg/dL), or poor (≥240 mg/dL or treated to ≥200 mg/dL). Assessment of Extracranial Carotid Artery Stenosis All participants (≥40 years) underwent carotid duplex ultrasonography in a supine position, with their head turned to the contralateral side. All carotid scans were performed by two independent sonographers with ultrasounds. The sonographers were blind to the baseline information of the participants. Carotid duplex ultrasound modalities combined 2-dimensional real-time imaging with Doppler flow analysis to evaluate the vessels of interest (typically the cervical portions of the common and internal carotid arteries) and to measure blood flow velocity. Extracranial CAS was defined by a peak systolic blood flow velocity ≥125 cm/s and a vertical artery peak systolic blood flow velocity of ≥170 cm/s in the common carotid artery or internal carotid artery. Extracranial CAS was graded according to the diagnostic criteria identified by the Society of Radiologists in the Ultrasound Consensus Conference in 2003. In our study, the degree of CAS was classified as normal (no stenosis) or stenosis (<50% stenosis, ≥50% stenosis or occlusion) involving at least one internal or common CAS. Assessment of Potential Covariates Biographical information (age, race, sex, education level, average monthly income of each family member, alcohol use and disease history) was collected via questionnaires at the baseline visit. Participants were divided into two groups according to age: 40–59 years and ≥60 years. Participants’ education level was categorized as “illiterate or primary”, “middle/high school” or “college graduate or above”. The average monthly income of each family member was reported to be “ ≤¥3,000”, “¥3,001–5,000” or “ ≥¥5,001”. Heavy alcohol consumption was defined as a daily intake of at least 100 ml of liquor (equivalent to 240 ml of wine or 720 ml of beer) for more than a year. The existence of a history of stroke or MI was defined as any self-reported previous physician’s diagnosis of stroke or MI. Statistical Analyses Statistical analyses were performed using SAS software, version 9.4 (SAS Institute, Cary, North Carolina, USA). Categorical variables were described using percentages and compared with Chi square tests. Continuous variables were described using means (standard deviation [SD]) and compared with ANOVAs. Logistic regression was used to estimate the prevalence of extracranial CAS across the subgroups of each ideal CVH metric by calculating the odds ratio (OR) and 95% confidence interval (CI). Adjustments were made for five variables (sex, age, alcohol use, average monthly income of each family member, and education level) that were identified as potential confounds of the risk factors for extracranial CAS141638. In addition, the composite score of the seven CVH metrics was quantified by adding the following numeric values assigned to each component based on category: 0 = poor, 1 = intermediate, and 2 = ideal39. The prevalence of extracranial CAS was analyzed using the total score of the CVH metrics inserted into the models as quartiles (with the lowest quartile as the reference), using logistic regression. All statistical tests were 2-sided, and significance levels were 0.05. Additional Information How to cite this article: Hao, Z. et al. The Association between Ideal Cardiovascular Health Metrics and Extracranial Carotid Artery Stenosis in a Northern Chinese Population: A Cross-Sectional Study. Sci. Rep. 6, 31720; doi: 10.1038/srep31720 (2016). This study was supported by research grants from the National 12th Five-Year Major Projects of China (grant number 2012BAI37B03) and Recovery Medical Science Foundation. Author Contributions Z.H., Y.Z., R.Z., J.H. and Y.Z. conceived and designed this study, Z.H., Y.Z., Y.L. and J.Q. directed data analysis, Z.H. and Y.Z. writing the paper. Z.H., Y.Z., Y.L. and J.Z. prepare the database and reviewed the paper. R.Z., J.H. and Y.Z. conducted the quality assurance, reviewed and edited the paper. All authors reviewed the manuscript. Table 1 Characteristics of Study Participants Stratified by Sex.   ALL (n = 3297) Man (n = 1576) Women (n = 1721) P-value Income, ¥/month n(%)       <0.001  ≤¥3000 1642(49.8) 714(43.5) 928(56.5)    ¥3001–5000 1451(44.0) 746(51.4) 705(48.6)    ≥¥5001 204(6.2) 116(56.9) 88(43.1)   Education level n(%)       <0.001  Illiteracy/primary 242(7.3) 85(35.1) 157(64.9)    Middle school 1852(56.2) 823(44.4) 1029(55.6)    College/University 1203(36.5) 668(55.5) 535(44.5)   Alcohol use n(%)       <0.001  Yes 103(3.1) 102(99.0) 1(1.0)    No 3194(96.9) 1474(46.1) 1720(53.9)    BMI(kg/m2) 24.9 ± 3.28 25.6 ± 2.98 24.3 ± 3.41 <0.001  SBP(mmHg) 131 ± 19.8 133 ± 18.81 129 ± 20.5 <0.001  DBP(mmHg) 83.7 ± 12.2 87.8 ± 12.7 79.9 ± 12.6 <0.001  FPG(mg/dl) 5.51 ± 1.37 5.67 ± 1.52 5.37 ± 1.20 <0.001  TC(mg/dl) 4.69 ± 0.89 4.62 ± 0.85 4.76 ± 0.92 <0.001  TG(mg/dl) 1.71 ± 1.42 1.92 ± 1.62 1.52 ± 1.06 <0.001 BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FPG, fasting blood pressure; TC, total cholesterol; TG, triglyceride. Table 2 Odds Ratio with 95% CI of Each Component of Cardiovascular Health Metric for Extracranial Carotid Artery Stenosis Stratified by Age and Sex. Metrics Total Sex Age(years) Man Women 40~59 ≥60 Smoking  Poor 1.00 1.00 1.00 1.00 1.00  Intermediate 1.33(0.37–4.77) 1.66(0.46–6.04) —* 0.99(0.12–7.99) 1.14(0.21–6.33)  Ideal 0.55(0.35–0.85) 0.67(0.42–1.06) 0.14(0.04–0.45) 0.82(0.45–1.46) 0.45(0.24–0.86)  P-value 0.007 0.086 0.001 0.492 0.016 BMI  Poor 1.00 1.00 1.00 1.00 1.00  Intermediate 0.91(0.48–1.72) 1.20(0.47–3.02) 0.88(0.35–2.25) 0.98(0.41–2.37) 0.90(0.35–2.36)  Ideal 1.03(0.54–1.98) 1.77(0.69–4.51) 0.58(0.21–1.56) 1.18(0.48–2.91) 1.17.(0.44–3.10)  P-value 0.926 0.235 0.278 0.721 0.751 Physical activity  Poor 1.00 1.00 1.00 1.00 1.00  Intermediate 0.59(0.23–1.55) 0.76(0.25–2.31) 0.27(0.03–2.18) — 1.77(0.58–5.36)  Ideal 1.01(0.69–1.47) 1.21(0.74–1.97) 0.70(0.35–1.30) 1.45(0.86–2.45) 0.77(0.44–1.35)  P-value 0.979 0.460 0.258 0.163 0.358 Diet  Poor 1.00 1.00 1.00 1.00 1.00  Intermediate 1.17(0.72–1.55) 1.21(0.68–2.13) 1.25(0.49–3.18) 1.91(0.58–2.06) 1.25(0.60–2.60)  Ideal 0.81(0.46–1.43) 0.80(0.40–1.62) 0.87(0.31–2.48) 0.73(0.34–1.57) 0.86(0.36–2.05)  P-value 0.459 0.542 0.797 0.472 0.734 Total cholesterol  Poor 1.00 1.00 1.00 1.00 1.00  Intermediate 0.71(0.36–1.37) 0.65(0.27–1.57) 0.69(0.23–2.08) 0.41(0.20–1.11) 1.49(0.48–4.65)  Ideal 0.45(0.24–0.85) 0.29(0.13–0.69) 0.74(0.27–2.07) 0.39(0.18–0.85) 0.72(0.24–2.21)  P-value 0.014 0.005 0.570 0.018 0.571 Blood pressure  Poor 1.00 1.00 1.00 1.00 1.00  Intermediate 0.64(0.44–0.93) 0.63(0.40–1.01) 0.60(0.31–1.19) 0.69(0.40–1.18) 0.61(0.35–1.04)  Ideal 0.46(0.25–0.84) 0.43(0.19–0.96) 0.51(0.19–1.37) 0.48(0.22–1.04) 0.34(0.12–0.97)  P-value 0.012 0.040 0.180 0.064 0.043 Fasting blood glucose  Poor 1.00 1.00 1.00 1.00 1.00  Intermediate 0.62(0.37–1.06) 0.51(0.26–1.04) 0.72(0.29–1.75) 0.41(0.19–0.87) 1.06(0.49–2.28)  Ideal 0.55(0.34–0.90) 0.70(0.38–1.27) 0.34(0.14–0.83) 0.39(0.20–0.76) 0.71(0.34–1.49)  P-value 0.017 0.243 0.023 0.005 0.361 CI: confidence interval. The following potential confounders were adjusted for each OR: sex, age, alcohol use, average monthly income of the family members, education level and the other six cardiovascular health metrics. *None of the women were former smokers but have quit smoking for ≤12 months. Table 3 Associations of Extracranial Carotid Artery Stenosis with Ideal Cardiovascular Health Metrics Stratified by Age and Sex. Metrics Prevalence of Extracranial CAS(%) Total Sex Age (years) Man Women 40~59 ≥60 Quartile 1 (≤8) 46.9 1.00 1.00 1.00 1.00 1.00 Quartile 2 (9–10) 33.3 0.57(0.39–0.84) 0.68(0.42–1.09) 0.39(0.19–0.77) 0.67(0.38–1.16) 0.55(0.32–0.94) Quartile 3 (11) 11.6 0.46(0.26–0.80) 0.40(0.18–0.89) 0.43(0.19–0.99) 0.71(0.35–1.45) 0.31(0.13–0.76) Quartile 4 (12–14) 8.2 0.29(0.15–0.54) 0.51(0.23–1.12) 0.11(0.04–0.34) 0.38(0.17–0.88) 0.21(0.07–0.60) P for trend   <0.001 0.012 <0.001 0.026 <0.001 The following potential confounders were adjusted for each OR: sex, age, alcohol use, average monthly income of the family members, education level. Table 4 Definition of Ideal Diet Score (>20 Years of Age) by the AHA and the Criteria Used in the Study. 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==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3230910.1038/srep32309ArticleCrystal Structure of Major Envelope Protein VP24 from White Spot Syndrome Virus Sun Lifang 1Su Yintao 1Zhao Yanhe 1Fu Zheng-qing 2Wu Yunkun a11 State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, China2 Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USAa ykwu@fjirsm.ac.cn30 08 2016 2016 6 3230918 04 2016 01 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/White spot syndrome virus (WSSV) is one of the major and most serious pathogen in the shrimp industry. As one of the most abundant envelope protein, VP24 acts as a core protein interacting with other structure proteins and plays an important role in virus assembly and infection. Here, we have presented the crystal structure of VP24 from WSSV. In the structure, VP24 consists of a nine-stranded β–barrel fold with mostly antiparallel β-strands, and the loops extending out the β–barrel at both N-terminus and C-terminus, which is distinct to those of the other two major envelope proteins VP28 and VP26. Structural comparison of VP24 with VP26 and VP28 reveals opposite electrostatic surface potential properties of them. These structural differences could provide insight into their differential functional mechanisms and roles for virus assembly and infection. Moreover, the structure reveals a trimeric assembly, suggesting a likely natural conformation of VP24 in viral envelope. Therefore, in addition to confirming the evolutionary relationship among the three abundant envelope proteins of WSSV, our structural studies also facilitate a better understanding of the molecular mechanism underlying special roles of VP24 in WSSV assembly and infection. ==== Body White spot syndrome virus (WSSV) is a rod-shaped enveloped virus with a large, double-stranded DNA genome1234, and belongs to the family Nimaviridae as the sole member of a novel genus Whispovirus56. The virus has a wide host range of most species of crustaceans7, and therefore becomes the major and most serious pathogen in cultured shrimp and has caused severe mortality and huge economic losses to the world’s shrimp farming industry8. So far, three geographic WSSV isolates have been sequenced, and in the complete genome sequence approximately 180 open reading frames are likely to encode functional proteins59, most of which share no homology to any known proteins or motifs10. Using proteomic method, more than 50 structural proteins are known, of which 22 are envelope proteins111213. The envelope proteins have absorbed a lot attention due to their critical roles in virus entry, virus assembly, host cell targeting as well as host defense triggering14. It has been indicated that VP28, VP26, VP24, and VP19 are the four most abundant envelope proteins of WSSV41115. Neither of which shares significant homology with known structural proteins from other viruses5. However, VP28, VP26 and VP24 share significant sequence similarities. Previous studies have showed that VP28 is crucial for virus entry involving in attaching and penetrating into host cells1617, while VP24 could not bind to host cell membrane though it could interact with VP28 to form a protein complex and participate in virus infection together1819. Moreover, studies have further shown VP24 could bind with many other structural proteins including VP28, VP26, VP19, VP33, VP38, VP51A, VP53A and wsv010 for its function in WSSV infection or morphogenesis1120212223. For the interaction, VP24 has been recognized as a core protein to associate with other structural protein partners and form an envelope protein complex, serving as a hub protein to function in cell recognition, cell attaching and guidance of virus entry2425. Recently, VP24 has been demonstrated to be a chitin-binding protein involved in WSSV infection26. However, the exact role and molecular mechanisms of VP24 in WSSV infection and assembly remain elusive. Identification the proteins involved is crucial to the understanding of the molecular events. The structural interpretation of them will provide valuable information for understanding their acting modes. Till now, only two three-dimensional structures of WSSV structural proteins, VP26 and VP28, were reported to occur as trimers in the viral envelope, further supposed VP26 and VP28 were located on the outer surface of the virus and were observed as a surface protrusion in the envelope by immunoelectron microscopy27. A structural elucidation of VP24 was hampered by the failed attempt to obtain soluble VP24 protein full-length or fragments. Here, we have successfully prepared soluble VP24 protein by adding a non-denaturing protein-solubilizing agent and finally determined the crystal structure of VP24. As one of the major envelope proteins, VP24 forms a trimer with each monomer adopting a typical nine-stranded β-barrel architectures with a conservative hydrophobic core similar to that of VP28 and VP26, but with a totally different N-terminal region and a distinct protruding C-terminus. The electrostatic surface potential calculation of VP24 further reveals almost opposite surface properties of both the front and bottom surfaces to those of VP28 and VP26, which could explain the mechanistic difference in host-cell membrane attachment for VP24 and VP28. In addition to confirming the evolutionary conservation among the three abundant envelope proteins of WSSV, VP24, VP26 and VP28, our structural studies also provide insight into a better understanding of the molecular mechanism underlying special roles of VP24 in WSSV infection and assembly. Results and Discussion Crystal structure of VP24 The transmembrane truncated VP24 (residues 28-208) was expressed and purified in E. coli BL21 (DE3) successfully. However, a lot of precipitation was appeared while the recombinant VP24 concentration reached above 0.8 mg/ml. Lucky, after screening, with the addition of non-denaturing protein-solubilizing agent NDSB-201, soluble VP24 could reach a concentration of 3.5 mg/ml and yield crystals. Using SAD phasing, the crystal structure was determined to a resolution of 2.4 Å with a final Rwork of 0.17 and Rfree of 0.19 (refinement statistics see Table 1). The final monomer model of VP24 contains residues 40-208. The overall structure comprises nine β strands and one α helix, of which the nine antiparallel β-strands adopt a β–barrel fold to form the core of the protein, in which strand 9 is hydrogen-bonded to strand 1, and the short α helix on the turn between β3 and β4 is hanged out the β–barrel fold (Fig. 1A). In the crystal structure, VP24 adopts a nine-stranded β–barrel fold with mostly antiparallel β-strands (Fig. 1A). It’s noted that β2 and β7 both have a kink in strands. Inside the β-barrel, it is a highly hydrophobic core. The inner surface lining of the core is mainly contributed by the hydrophobic side chains from five Ile, seven Leu, five Phe, five Val, two Tyr and one Met residues; the hydrophobicity of the core is quite conserved among VP24, VP28 and VP26 (Fig. 2). The N-terminal and C-terminal loops extend outside the β-barrel to opposite direction, both almost perpendicular to the axis of the β–barrel (Fig. 1). Oligomization of VP24 In the crystal, VP24 forms a trimer by crystallographic three-fold symmetry axis (Fig. 1). The trimer interface has a buried surface area of 1187.1 Å2, accounting for 12.6% of total monomer surface area (http://pdbe.org/pisa/). And the trimer interaction mainly contributed by β strands β1-β9-β6 and β7’. To further validate the trimeric formation, a chemical cross-linking assay indicated that glutaraldehyde cross-linked VP24 into trimers in a concentration-dependent manner, suggesting a trimer formation in solution (Fig. 3). Furthermore, the oligomerization state of recombinant VP24 was also investigated by gel filtration chromatography and comparison with VP26 and VP28. In the gel filtration analysis, VP24 preferred an oligomerization state rather than a monomer state (Fig. 4). Accordingly, in our judgement, the trimeric assembly observed in crystal structures similar to that of VP28 or VP26 should represent a natural conformation in the viral envelope, rather than the dimer formation as previously suggested24. However, the trimer interaction is weak, suggesting a possible monomer-trimer transition during WSSV biological process. This is consistent with the previous reports of viral structural proteins exhibiting multiple functions by adopting different oligomerization states2829. Structural comparison of VP24 with VP28 and VP26 With the sequence similarity shared by VP24 with VP28 and VP26, the VP24 structure can be well superimposed to that of VP28 (PDB: 2ED6) and VP26 (PDB: 2EDM) with a RMSD for backbone atom of 1.9 Å and 2.5 Å, respectively. In overall, the three envelope proteins share a conserved nine-stranded β–barrel fold (Fig. 5), which is different from the predominant eight-stranded β–barrel, a viral canonical jelly-roll fold, commonly observed in other viral proteins3031323334353637. This structural similarity suggests that the three WSSV envelope proteins could have evolved from a common ancestral origin via gene duplication38, such as the three β-jelly roll folds in picorna-like virus capsids that could evolved by triplication of a single domain and further independent evolution of the three domains3940. However, some distinct observes in their structures. Compared to VP28, VP24 lacks the two short 310 helix at the top of the β–barrel, and in contrast to VP26, it did not have a short pair β-sheet at the top of the β–barrel (Fig. 5). Furthermore, significantly different to those of VP26 and VP28, the N-terminus of VP24 forms a loop perpendicular to the barrel axis, which may pull the protein more closely attached to the viral envelope, compared to the protruding helix bundle parallel to the barrel axis of VP28 (Figs 2 and 5). As a linker connecting to transmembrane helix anchor, the N-terminus of VP24, VP26 and VP28 with distinct topology may implicate their differential roles for virus assembly. And the C-terminal of VP24 also extends out the barrel as a flexible long loop, which might grant the C-terminus more dynamics and facilitate VP24 to recruit other structural proteins. More interestingly, the electrostatic surface potential measurement of VP24 structure reveals an electronegative surface (Fig. 6A), owing to the presence of residues aspartate and glutamate residues at the top of β–barrel core (away from the viral envelope), and a highly electropositive surface at the bottom of the barrel core, distinct to those of VP28 and VP26 (Fig. 6BC). As shown in Fig. 6, in contrast to VP24, VP28 is electroneutrality and electronegative, respectively; while VP26 almost has the opposite electrostatic surface. This might suggest different preference of ligand recognition of them. Furthermore, VP24 is considered the core of the infectome, these distinct surface features should reasonably explain the mechanism underlying the different binding property of them with other viral proteins or host protein as previously described1823242526, and further provide insight into their different roles in WSSV assembly and infection. Interaction analyses of VP24 Previous studies have showed that VP24, VP28, and VP26 could interact with each other and form a complex11. To assess binding affinities of VP24 to VP28 and VP26 respectively, in vitro ITC assay indicated that the interaction could be too weak to be measured from the heat generated by reaction (Supplementary Figure). However, in the previous report, it has been shown that three C-terminal deleted mutants VP2426–172, VP2426–135, VP2426–98 and three N-terminal deleted mutants VP2462–208, VP2499–208, VP24136–208 could all interact with VP2841. It implies the N terminus and C terminus of VP24 both take part in the interaction with VP28. According to the trimer structure of VP24, the oligomer interfaces are composed mainly by strands β1-β9-β6 and β7’, which are included mostly in above-mentioned VP24 mutants. It is thus speculated that major envelope proteins VP24 and VP28 might interact with each other to form a heterotrimer as well as a self-interaction homotrimer because of the similar interfaces. Moreover, a recent report has shown that VP24 is a chitin-binding protein involved into WSSV infection through the chitin-binding domain of VP24 containing residues186-20026. In the VP24 structure, this chitin-binding domain including strand β9 located at the interface of the trimer. This further supports that VP24 could function as a monomer to present β9 at the surface for chitin binding during virus infection and undergo a monomer-trimer transition for different biological roles. In conclusion, we presented a high resolution structure of WSSV major envelope protein VP24 with a unique nine-stranded β–barrel fold with mostly antiparallel β-strands, shared by the two mentioned WSSV envelope proteins but distinct from the featured eight-stranded jelly roll of other viral proteins. The structure also reveals distinct topologies of both the N-terminal and C-terminal loop extending out the β–barrel. Further, the electrostatic surface potential calculation reveals an almost contrary electrostatic property for the front and bottom surfaces of VP24 compared to VP28 and VP26, which could provide mechanistic insight into the distinct function of them for virus infection. Based on our work combined with previously studies, it is suggested that VP24, VP26 and VP28 all favor trimers with a weak interaction when aggregated in the envelope and could adopt different oligomerization states to exhibit different functions. While VP26 may locate inside viral envelop, VP24 and VP28 may sit outside viral envelope with VP24 barrel attaching more closely to the envelope (Fig. 7). Through the extended dynamic C-terminus, VP24 may interact with more structural protein partners for WSSV assembly or infection. Furthermore, VP24 may bind to chitin of host cell via strand β9, anchoring WSSV to the host cell and facilitating the attachment of VP28 to the host cell and membrane fusion, and initiate virus infection. Hence, our structure will contribute to an in-depth investigation and understanding of the molecular mechanism of WSSV assembly and infection, and in turn provide valuable information on neutralizing antibody design and vaccine development against WSSV. Materials and Methods Cloning, expression, and purification The gene coding for the truncated constructs of VP24 was amplified from the WSSV genome and inserted into vector pET21b, by using restriction enzymes NdeI and XhoI, resulting in a C-terminal hexahistidine tag for purification. Sequence analysis showed that only one Met site was presented in truncated VP24 sequence. So some mutants (L69M, L88M, L121M, I133M, and L69M/L121M) were constructed to increase the ratio of Met. The mutants were generated by site-directed mutagenesis using the pET21b-VP24 vector as the template and confirmed by sequencing. All recombinant plasmids were transformed into Escherichia coli BL21 (DE3). Cells were grown to an OD600 of 0.8 at 37 °C, and VP24-His6 fusion protein expression was induced by 0.3 mM isopropyl-β-D-thiogalactoside (IPTG) overnight at 16 °C. Cells were centrifuged, resuspended in lysis buffer containing 25 mM Tris-HCl (pH 7.0), 300 mM NaCl, 5% glycerol and sonicated on ice. Cell debris was removed by centrifugation. Purification was achieved by Ni-NTA affinity chromatography (GE Healthcare), gel filtration (Superdex 200 HR 16/60; GE Healthcare). Mutants were measured by Circular dichrosim spectra to estimate the stability of their secondary structure. Seleno-methinonine (SeMet, Sigma-Aldrich) labeling of mutants (L69M and L69M/L121M) were produced by inhibiting endogenous methionine biosynthesis in M9 minimal medium supplemented with specific amino acids as well as SeMet and then purified in the similar protocol as the native protein4243. Purified protein fractions were collected and concentrated to a final concentration of 2.5 to 3.5 mg/ml plus with 0.5 M Non Detergent Sulfobetanines NDSB-201 (Sigma). Crystallization and data collection Crystals of VP24 and mutants (L69M, L69M/L121M) were obtained using the sitting drop method at 16 °C. The initial screens were carried out using Qiagen crystallization screen kits (the JCSG Core I-IV suites). The initial conditions were further optimized to obtain diffraction-quality crystals. The best crystals of VP24 were found with a reservoir solution of 0.1M Tris-HCl, pH 8.5, 2.75 M Ammonium acetate with drop volume ratio of two parts protein: one parts reservoir solution by using the hanging-drop vapor diffusion method. 10 mM ATP was as a critical additive in present of the drop. Prior to data collection, crystals were briefly soaked in a cryo-protectant solution consisting of 30% glycerol, picked up in a CryoLoop, and flash-cooled at liquid nitrogen. The X-ray diffraction data sets were collected for single anomalous diffraction (SAD) phasing using the beamline BL17U at Shanghai Synchrotron Radiation Facility (SSRF, shanghai, China) using a charge-coupled device (CCD) detector. Structure determination, and refinement Data sets were integrated and scaled using HKL2000 package. Further processing was carried out using programs from the CCP4 suite44. Phasing was achieved by SAD method by using L69M/L121M-Se data set. SHELXD was used to locate the positions of selenium sites45. After phase calculation, phase extension, and phase improvement by density modification, the initial model was built automatically by Phenix program AutoSol containing about 80% of the polypeptide (~amino acids) for VP24. Then native VP24 was determined by the molecular replacement, using the initial model as the search model and the native dataset to refine. Iterative cycles of manual rebuilding and maximum likelihood refinement were performed by Coot46 and Phenix47. All structure figures were prepared by using PyMOL program (DeLano Scientific LLC). Sequence alignment was generated with DaliLite server48. The atomic coordination and structure factors for VP24 have been deposited in the Protein Data Bank under the accession code of 5HLJ. The data collection and refinement statistics were listed in Table 1. Cross-linking assay For nonspecific cross-linking, purified protein in PBS buffer (around 0.6 mg/ml in 40 ul) was incubated with various concentrations of glutaraldehyde (0, 0.0001%, 0.001%, 0.01%) at room temperature for 4 h, respectively. The reaction was quenched by addition of 50 mM Tris-HCl, pH 8.0. The sample was mixed with equal volume of SDS loading buffer, separated on 15% SDS-PAGE gels and stained with Coomassie blue. Isothermal titration calorimetry (ITC) assays The dissociation constant (Kd) and stoichiometry of the interaction between VP24 and VP28 or VP26 were measured by ITC using an ITC200 calorimeter (GE Healthcare). Calorimetric titration of VP28 (0.3 mM in the syringe; 2 μl injections) or VP26 (0.2 mM in the syringe; 2 μl injections) to VP24 (0.012 mM or 0.03 mM in the cell, 200 μl) was performed at 25 °C in assay buffer containing 25 mM Tris-HCl, pH7.0, 200 mM NaCl, 5% glycerol or buffer containing 25 mM Tris-HCl, pH7.0, 100 mM NaCl. Time between injections was 150 s. ITC data were analyzed by integrating the heat effects after the data were normalized to the amount of injected protein. Data fitting was conducted to determine the dissociation constant and stoichiometry based on a single-site binding model using the Origin software package (MicroCal). Additional Information Accession codes: The crystal structure of VP24 has been submitted to the Protein Data Bank with the 397 accession code of 5HLJ. How to cite this article: Sun, L. et al. Crystal Structure of Major Envelope Protein VP24 from White Spot Syndrome Virus. Sci. Rep. 6, 32309; doi: 10.1038/srep32309 (2016). Supplementary Material Supplementary Information The authors thank staff at the beamline BL17U1 at Shanghai Synchrotron Radiation Facility (SSRF) for assistance with diffraction data collection and F. Yang for kindly providing valuable discussion and cDNA encoding WSSV proteins. This work was supported by the National Nature Science Foundation of China (31270790, 31302225), the Nature Science Foundation of Fujian Province (2016J0101), and National Thousand Talents Program of China. Author Contributions L.S. and Y.W. conceived and designed the experiments, L.S., Y.S. and Y.Z. performed the experiments, L.S., Z.F. and Y.W. analyzed the data, L.S. and Y.W. wrote and revised the manuscript. Manuscript is reviewed, discussed and approved by all the authors. Figure 1 Structure of VP24. (A) Cartoon diagram of the VP24 monomer. The secondary structural elements, N and C termini are labeled. (B) Cartoon diagram of the VP24 trimer (crystallographic symmetry-related molecules). (C) Top view of the VP24 trimer. Diagrams were prepared using the program PyMol. Figure 2 The structure and the sequence alignment of VP24 with VP28 (PDB: 2ED6) and VP26 (PDB: 2EDM). The secondary structure is assigned by DSSP information for helix (H), strand (E) and coil (L), respectively. Residues of hydrophobic side chains lining the inner surface of the β–barrel core are highlighted in yellow boxes. This figure was created by using DaliLite. Figure 3 Cross-linking assay of purified VP24. Increasing amounts of glutaraldehyde (0, 1, 10, 100, 1000 ppm) were incubated with the purified VP24. The samples were analyzed by 15% SDS-PAGE. M: protein marker. Figure 4 The oligomerization state of recombinant VP24 was analyzed in the gel filtration of Superdex 200 column (GE Healthcare) and compared to those of VP26 and VP28. Figure 5 The superposition of VP24 (slate) to VP28 (orange) (A) and VP26 (yellow) (B). Figure 6 Electrostatic surface potential of VP24 (A), VP28 (B), and VP26 (C). The right line was the structure of their 180 degree rotation view, respectively. The core of the β-barrel was highlighted by black circle. Figure 7 3D models of the location of VP24, VP28 and VP26. VP24 and VP28 anchor on the outside viral envelope membrane, while VP26 anchor on the inside viral envelop membrane. The proteins would have a reversible monomer to trimer transition. VP24 could bind to chitin via its β9 strand (colored by red) which may draw the distance between WSSV and host cell closer, and help VP28 to attach the host cell and the virus enter the cytoplasm. Table 1 Data collection and refinement statistics of VP24. Data collection VP24 L69M/L121M-Se Space group I 21 3 I 21 3 Cell dimensions  a, b, c (Å) 140, 140, 140 140, 140, 140  α, β, γ (°) 90, 90, 90 90, 90, 90  Resolution (Å) 2.40–50 (2.40–2.44) 2.8–44 (2.80–2.85)  Rmerge (%) 7.6 (94) 10 (77.6)  I/σI 51 (1.65) 32.6 (3.04)  CC1/2 (0.663) (0.729)  Completeness (%) 99.83 (100) 98.53 (100)  Redundancy 20.6 (20.4) 7.3 (7.5)  Wilson B-factor (Å2) 71.49 72.74 Refinement  Resolution (Å) 2.4–31.25    No. reflections 17728    Rwork/Rfree (%) 17.08/19.26    No. atoms 1382    Water 54   B factors  Protein 71.86    Water 74.85    R.m.s.d bonds (Å) 0.008    R.m.s.d angles (°) 1.125   Ramachandran plot  Favored (%) 96.41    Allowed (%) 3.59    Outliers (%) 0.00    Rotamer outliers (%) 0.00   Numbers in parentheses refer to the highest-resolution shell. ==== Refs van Hulten M. C. , Westenberg M. , Goodall S. D. & Vlak J. M. Identification of two major virion protein genes of white spot syndrome virus of shrimp . 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