dataesr/scientific-paragraphs-categorization huggingface dataset:
Further research will decipher mechanisms underlying functional differences between natural killer cells from patients and healthy individuals and evaluate the potential interest of immunostimulatory approaches in tyrosine kinase inhibitor discontinuation strategies. (ClinicalTrial. gov Identifier NCT00478985) Natural killer-cell counts are associated with molecular relapse-free survival after imatinib discontinuation in chronic myeloid leukemia: the IMMUNOSTIM study Delphine Rea, 1,2,3* Guylaine Henry,  4  Zena Khaznadar, 1,5 Gabriel Etienne,  3, 6  François Guilhot,  3, 7  Franck Nicolini,  3, 8  Joelle Guilhot,  3, 7  Philippe Rousselot,  3, 9  Françoise Huguet,  3, 10  Laurence Legros,  3, 11  Martine Gardembas,  3, 12  Viviane Dubruille,  3, 13  Agnès Guerci-Bresler,  3, 14  Aude Charbonnier,  3, 15  Frédéric Maloisel,  16  Jean-Christophe Ianotto,  17  Bruno Villemagne,  18  François-Xavier Mahon,  3, 6  Hélène Moins-Teisserenc,  1, 4, 5  Nicolas Dulphy 1,4,5* and Antoine Toubert  1, 4, 5.
Patients IMMUNOSTIM is a sub-study of the STIM trial approved by French health authorities (NCT00478985). 9 Written informed consent was given in agreement with the Declaration of Helsinki. Imatinib was stopped after ≥3 years of therapy and ≥2 years of undetectable BCR-ABL1 transcripts. Stringent monitoring by RT-qPCR was performed after imatinib discontinuation to detect a molecular relapse. 9 The assay sensitivity was ≥4. 5 log. Consecutively detectable peripheral blood BCR-ABL1 transcripts showing a ≥1 log increase or loss of a major molecular response [BCR-ABL1/ABL1 internationally standardized (IS) ratio ≤0. 1%] defined molecular relapse and triggered imatinib resumption. In IMMUNOSTIM, heparinized blood was collected at baseline, bimonthly for 6 months then every 6 months until 24 months unless imatinib was resumed.
Funding This work was supported by research grants from the  Association pour la Recherche sur le Cancer  (ZK, # DOC20100600956 ),  Association LMC France  (# R13102HH ),  Assistance Publique-Hôpitaux de Paris  ( Translational Research Grant  in Biology 2010 # RTB10002 ) and the  French Ministry of Health/Institut National du Cancer  ( Programme Hospitalier de Recherche 2006 ). D. Rea et al. 1376 haematologica | 2017; 102(8).
RNA quality and absence of the 16S and 23S rRNA species were checked on an Agilent Bioanalyzer with the Agilent RNA 6000 Pico kit (Agilent Technologies). RNA samples depleted in rRNA were sent to GATC Biotech for strand-specific library preparation and sequenced on an Illumina HiSeq 2000 with 100 bp single reads. Raw reads from each sample were trimmed using Trimmomatic  [31]  to remove the TruSeq3-SE adaptors using clip parameters 2 : 30 : 10, a sliding window of size 4 with a mean quality of 20, minimum quality of leading and trailing bases of 10, and a minimum final length of 70 nt for a read to be retained. The human genome (GRCh37) and the genome of L. salivarius UCC118 were combined to generate a database to which the RNA-seq reads could be aligned simultaneously. STAR  [32]  was used to align the trimmed reads to both genomes, allowing for a 0.
5 ratio of mismatches to mapped length, with the remainder of parameters set to default. HTSeq  [33]  was used to determine the number of reads aligning to each gene, using the intersection-nonempty setting. The read numbers of each gene were expressed in RPKM (reads per kilobases per million reads) scores  [34]. A custom Perl script was written to determine the number of reads that aligned to the lncRNA, the number of reads that aligned at each position along the megaplasmid pMP118 and to calculate the log 10 of the number of reads aligning at each position. These logged counts were used as input for the BLAST Ring Image Generator (BRIG)  [35] , used to generate Figs 1(b) and S2(a) (available with the online Supplementary Material). lncRNA sequence, comparative genomics, RNA structure and quantitative PCR (qPCR) primer design The lncRNA sequence was obtained by circular RACE experiments performed according to methods described elsewhere  [36].
The circular RACE was performed on UCC118, UCC119, AH43310 and AH43324 strains, with RNAs extracted at 10 and 24 h of culture. The lncRNA sequence was searched (BLASTN) against the NCBI non-redundant nucleotide database and against the 45 L. salivarius genomic sequences available in our laboratory. When a positive match for the lncRNA was obtained, the lncRNA genomic area was sequenced (Sanger sequencing method; GATC Biotech) in order to confirm the sequence. The corresponding PCRs were performed with the high-fidelity Phusion polymerase and using the primers LSL_1886_F and LSL_1883_R (Table  S1 ). RNA structure of the lncRNA was predicted with the lncRNA alignment in RNAalifold  [37] , part of the Vien-naRNA Web Services. The sequences of the genes of interest from all the L. salivarius strains were aligned with Muscle and primers were designed within the conserved areas using the Primer3Plus Web tool (Table  S1 ).
Microarray hybridization and analysis L. salivarius UCC118 wild-type and both mutant strains were grown in MRS, and RNA was extracted in duplicate, as described above, in exponential and stationary phases. Labelling of cDNA with Cy3 and Cy5 dyes was carried out using a chemical labelling kit (Kreatech), following the manufacturer's instructions. Microarray slides were hybridized for 16 h at 55 C and scanned using an Agilent Microarray Scanner system (G2505B) with Agilent scan control software (version 7. 0). Agilent feature extraction software (version 9. 1) was used to process the image file and the extracted data were further processed using an in-house microarray transform platform, as previously described  [2]. Genes were selected as being significantly changed in expression if their fold change in Cy3/Cy5 ratio was >3 and where the P value was <0.
4b ). lncRNA is expressed in all L. salivarius strains harbouring the sequence, but expression levels vary Comparative genomics revealed that the sequence corresponding to this newly described lncRNA was uniquely present in L. salivarius (i. e. absent in all other genomes in the nonredundant NCBI DNA database) and was present in 34 of the 45 L. salivarius genomes available. Twenty-seven of these strains were available as cultures in our laboratory collection, and among these, 10 harboured a lncRNA sequence identical to that of L. salivarius UCC118 (Table  1 ). The boundaries of the lncRNA were confirmed by a circular RACE approach on four strains (UCC118, UCC119, AH43310 and AH43324). The 27 lncRNA sequences were extracted from the genomes, and confirmed by Sanger sequencing, allowing a multiple alignment (Fig.
The 11 strains sharing 100 % sequence identity for the lncRNA had lower OD 600 values after 24 h than the other strains, except for strain CCUG45735. This was particularly true for the four strains UCC118, UCC119, AH43310 and AH43324, for which the OD 600 values did not exceed 6. 6 after 24 h. The 11 strains also showed lower growth rates. The mean generation time for the 27 L. salivarius strains was 53. 6±15. 9 min, which is characteristic of Lactobacillus growth. Total RNA was extracted for the 27 strains at exponential (5 h), stationary (10 h) and late stationary (24 h) phases. Only the RNA profiles of four strains, UCC118, UCC119, AH43310 and AH43324, showed the visible presence of the lncRNA (Fig. S5 ). For these four strains, the peak area for the lncRNA increased during growth showing accumulation (data not shown), as described above for L.
5. Expression levels of the lncRNA during the growth of L. salivarius in MRS. The expression levels of lncRNA were quantified in 27 L. salivarius strains by RT-qPCR after 5 h (exponential phase), 10 h (stationary phase) and 24 h (late stationary phase) of culture. The 11 strains sharing an identical nucleotide sequence to the L. salivarius UCC118 lncRNA are highlighted with +++ (see also Table  1 ). Data are means±SD of two independent replicates. of the lncRNA, and some specific traits such as lower OD 600 values and higher megaplasmid copy number (Fig. S8 ). -1 0 1 2 3 4 UCC118 UCC119 AH4231 AH4331 AH43310 AH43324 AH43348 CCUG45735 CCUG47825 CCUG47826 L21 NCIMB8818 JCM1046 NCIMB8817 DSM20492 CCUG47171 CCUG44481 O1M14315 CCUG43299 JCM1040 DSM20555 Gul1 Gul2 JCM1047 CCUG38008 LMG14476 The downstream LSL_1884 gene encoding the predicted HTH protein did not follow the same expression pattern as that of the lncRNA, and there were some differences in HTH expression levels in the L.
salivarius UCC118 mutant was observed (data not shown). Microarray analyses of cultures in both exponential and stationary phases were performed to try to identify the function of the lncRNA. The whole transcriptomes of these two mutants were compared with the wild-type L. salivarius UCC118. Expression of only a few genes were up-regulated in the mutants in exponential phase, including 10 genes of the fatty acid biosynthesis operon fab (encompassing 13 genes) and 3 genes from the megaplasmid-encoding hypothetical proteins, two of which (LSL_1831 and LSL_1832) might be a toxin/antitoxin system (Table  S4 ). The expression levels of LSL_0450 and the fabD gene, both from the fab operon, were quantified by RT-qPCR in the panel of 27 L. salivarius strains and no correlation to the lncRNA expression level was observed (Table  S3 ).
In addition, a preliminary metabolomic analysis (gas chromatography-mass spectrometry) did not detect differences in the fatty-acid profile of wild-type UCC118 and the two deletion mutants (data not shown). Expression of eighteen genes was down-regulated in the mutants compared to the wild-type. Twelve of the genes down-regulated in the mutants were harboured by the megaplasmid (Table  S4 ). The mostly significantly repressed expression levels in the mutants were for pflA and pflD in the exponential phase. Expression of these two genes, also members of the top 10 expressed genes in L. salivarius UCC118 (Fig. S2c ), was quantified in the 27 L. salivarius strains and again no correlation with the lncRNA expression level was observed (Table  S3 ). As the four strains with the highest expression level of the lncRNA presented higher megaplasmid copy number than chromosome copy number, the ratio between these two genomic elements was quantified for both mutants (Table  2 ).
Expression of the 11 gene operon from LSL_0449 to LSL_0459, dominated by fatty acid biosynthesis genes, was significantly and uniformly up-regulated in both deletion mutants. However, a preliminary metabolomic analysis (gas chromatography-mass spectrometry) did not detect any differences in the total cellular fatty-acid profile of wild-type UCC118 cultures and the two deletion mutants (data not shown). It is still unclear why the lncRNA is expressed in such high abundance but does not seem to play a major role in the strain growth or metabolism, at least according to the approaches we took, including two knockout constructions. A full proteomic and metabolomic analysis of wild-type and deletion mutants would be required to seek to identify phenotypes dependent on the lncRNA. The expression of several coding stretches on the megaplasmid was significantly reduced by lncRNA deletion, including two genes involved in formate metabolism (Table  S4 ).
The apolipoprotein E (APOE) gene has been consistently shown to modulate the risk of Alzheimer's disease (AD). Here, using an AD and normal aging dataset primarily consisting of three AD multi-center studies (n = 1,781), we compared the effect of APOE and amyloid-␤ (A␤) on baseline hippocampal volumes in AD patients, mild cognitive impairment (MCI) subjects, and healthy controls. A large sample of healthy adolescents (n = 1,387) was also used to compare hippocampal volumes between APOE groups. Subjects had undergone a magnetic resonance imaging (MRI) scan and APOE genotyping. Hippocampal volumes were processed using FreeSurfer. In the AD and normal aging dataset, hippocampal comparisons were performed in each APOE group and in 4 carriers with positron emission tomography (PET) A␤ who were dichotomized (A␤+/A␤-) using previous cut-offs.
The first dataset in our study, known as the AD and normal aging dataset (n = 1,781) consisted of imaging data from three large multi-center AD consortiums, (i) The Alzheimer's Disease Neuroimaging Initiative (ADNI), (ii) the AddNeuroMed study (ANM), and (iii) the Australian Imaging, Biomarkers and Lifestyles (AIBL) study, as well as a sample of non-demented individuals from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K) and a dementia study from King's College London, UK (BRC-AD). The sample of non-demented individuals from the SNAC-K study were considered separate from healthy controls as the recruitment criteria for these subjects was epidemiological in nature and we could not exclude the possibility of memory impairment in some subjects. In our second dataset, we used a large sample of healthy 14-yearold adolescents (n = 1,387) in order to determine the neurodevelopmental effect of APOE 4 genotype on hippocampal volume.
This is particularly important because adolescence is a time of substantial dynamic neurobiological and behavioral changes. These changes are often beneficial and can optimize the brain for adult maturation, but can also confer neural vulnerabilities for certain types of psychiatric or neurological illness. The aim of this study was to firstly evaluate the neuroanatomic effect of APOE genotype on the hippocampus in the AD and normal aging dataset. Previous studies have demonstrated a linear effect of APOE genotype on disease risk, with 2 carriers possessing a low risk of developing AD, and 4 carriers possessing the greatest risk  [17]. We aimed to test if this linear stepwise effect of APOE genotype also imparted a similar neuroanatomic effect on the hippocampus across the different stages of AD pathophysiology.
AD and Normal Aging Dataset (n = 1,781) Alzheimer's Disease Neuroimaging Initiative (n = 779) A detailed description of the study design can be found on the ADNI webpage (http://www. adniinfo. org). Data was obtained for subjects from the ADNI online database (http://adni. loni. usc. edu). Subjects were between 55 and 90 years of age. ADNI was approved by the institutional review board and ethics committees of participating institutions, and written informed consent was obtained from all participants or their next of kin. i. AD (n = 177): General inclusion/exclusion criteria: 1) MMSE scores between 20 and 26; 2) CDR of 0. 5 or 1. 0; 3) met NINCDS/ADRDA criteria for probable AD. ii. MCI (n = 383): General inclusion/exclusion criteria: 1) subjects had MMSE scores between 24 and 30 (inclusive); 2) memory complaint.
The AIBL study is a prospective longitudinal study of aging, integrating data from neuroimaging, biomarkers, lifestyle, clinical, and neuropsychological analysis. Detailed information about the study design has been described in previous publications  [20, 25]  BRC-AD is a neuroimaging study which was designed to establish imaging markers for the earlier detection and diagnosis of AD. Data was collected at the Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. A total of 89 subjects (AD: 33, CN:56) were obtained with APOE data for this study. Diagnostic inclusion and exclusion criteria for this study were exactly the same as for the ANM study.
Swedish National study on Aging and Care in Kungsholmen (SNAC-K) study (n = 382) Participants were recruited from a larger population-based epidemiological study, the SNAC-K. In this study, participants were randomly selected to take part from the island of Kungsholmen in central Stockholm to examine aging in late adulthood  [26]. During the first data collection, a subsample of non-institutionalized and non-disabled participants were randomly selected to undergo MRI. Participants with dementia diagnoses, schizophrenia diagnosis, bipolar disorder diagnosis, self-reported stroke, stroke observed on MRI, self-reported Parkinson's disease, or epilepsy, were excluded. The study design has been described in detail elsewhere  [22]. We used a sample of 459 individuals from SNAC-K, who underwent MRI imaging and APOE genotyping.
Neuroimaging-Genetics IMAGEN Study (n = 1,387) This is the first European multi-center study combining genetics with behavioral and neuropsychological measures, functional and structural neuroimaging, and genome-wide association analyses in 2,000 healthy 14-year-old adolescents. A description of the study design are provided in Schumann et al. [23]. We selected 1,387 healthy adolescents with available MRI data and ApoE status information. Genome-wide genotyping was performed using Illumina Quad 610 and 660 arrays (San Diego, CA, USA). Quality control of the genome-wide data was performed and samples with the following criteria were excluded: genotype call rate < 95%, and those with discordance between clinical and genotypic gender. Single nucleotide polymorphisms (SNP) quality control filters were used as described in the ENIGMA consortium imputation protocol (http://enigma.
Image acquisition High resolution 3D T1-weighted MRI were acquired for each subject and a comprehensive quality control procedure was applied to all MR images according to the AddNeuroMed study quality control framework  [24, 28]. ADNI: The protocol included a high resolution T1 weighted sagittal 3D MP-RAGE volume (voxel size 1. 1 × 1. 1 × 1. 2 mm³), and axial proton density with T2 weighted fast spin echo images. MRI scanner protocols from models of General Electric (GE) Healthcare, Philips Medical Systems, and Siemens Medical Solutions were supported. ANM: Data acquisition took place using six different 1. 5T MR systems (4 General Electric, 1 Siemens, and 1 Picker). At each site a quadrature birdcage coil was used for RF transmission and reception. Data acquisition was designed to be compatible with the ADNI.
Aβ PET methods Data on A␤ imaging with positron emission tomography (PET) was accessed for a total of 95 ADNI and 57 AIBL 4 carriers. A␤ imaging for these subjects was conducted using either 11 C-Pittsburgh Compound B (PiB), or 18 F-florbetapir. PET scans that were acquired as close as possible to the structural MRI scans in the ADNI and AIBL study were chosen. The PET imaging methodology of the ADNI and AIBL studies has been extensively described elsewhere  [29, 30]. For PiB PET, the measure of amyloid burden was calculated by averaging the ratio of cortical to cerebellar signal (SUVR) measurements from frontal, parietal, anterior cingulate, and parietal regions of interest  [29]. For 18 F-florbetapir, the SUVR was calculated for 6 pre-defined regions of interest (frontal, temporal, parietal, anterior cingulate, posterior cingulate, and precuneus).
Comparing the effect of APOE genotype on hippocampal volume in the AD, and normal aging dataset (n = 1,781) and the IMAGEN study of healthy 14-year-old adolescents (n = 1,387) In AD patients, 4 carriers had significantly smaller hippocampal volumes than non-carriers. A significant linear stepwise reduction in hippocampal volume was observed with 2 carriers possessing the largest volumes, 3 carriers possessing intermediate volumes and 4 carriers possessing the smallest volumes. This pattern was also observed in the MCI group (Table  3 ). The effect of the 4 allele on hippocampal volume was found to be moderately The effect of APOE genotype on hippocampal volumes in CN individuals was not significant (left region: p = 0. 052; right region: p = 0. 053) and the magnitude of this non-significant difference in both regions was small (Cohen's d = 0.
16; effect size r = 0. 08). This non-significant pattern was also observed in elderly individuals from the SNAC-K study, as well as in healthy adolescents from the IMA-GEN study (Table  3 ). Figure  1  displays hippocampal volumes by APOE genotype in the AD and normal aging dataset and IMAGEN study of adolescents. Hippocampal volumes of AD 4 carriers were found to be significantly smaller than MCI, CN, and non-demented 4 carriers. This pattern was also observed in MCI 4 carriers who had significantly smaller volumes than CN, and non-demented 4 carriers (Table  4 ). In carriers of the 2 allele, the MCI and CN groups possessed significantly larger hippocampal volumes than 2 carriers of the AD group (Table  5 ).
Additionally, when combining data across cohort studies, it is important to consider study design differences that may complicate the interpretation of our results. For instance, the use of different AD diagnostic criteria across the different cohort studies may contribute to a level of diagnostic variability between groups. Participants from the ADNI and AIBL study were also highly educated, had few comorbidities, and were of Caucasian background. As such, future prospective studies with more representative samples should be conducted to address how these comorbidities, namely the presence of vascular disease, could potentially influence the size of the hippocampus. We demonstrated that systematic bias was not present in our dataset when comparing hippocampal volumes between APOE groups within each cohort study separately (Supplementary Material).
An independent sample of healthy 14-year-old adolescents also provides an understanding into the role of APOE in adolescent brain neurodevelopment. In conclusion, our findings in the largest APOE neuroimaging dataset show that hippocampal volume loss is present in patients with AD and in subjects with an increased risk of developing AD, particularly subjects with memory impairment. However, healthy older individuals did not show APOE 4 dependent changes in the hippocampus, suggesting that the relationship between APOE 4 and A␤ may be mediated by the presence of neurodegeneration. The same pattern was also observed in healthy young adolescents who possessed no hippocampal differences between different APOE groups. Our study thus shows hippocampal volume loss is moderated by APOE 4 and A␤ in AD and the MCI stages of the AD pathological Authors' disclosures available online (http://j-alz.
ACKNOWLEDGMENTS Data used in preparation of this article were obtained from the  Alzheimer's Disease Neuroimaging Initiative (ADNI) database  (http://adni. loni. ucla. edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found on ADNI website (http://adni. loni. usc. edu/). Data used in the preparation of this article were obtained from the  Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing (AIBL)  funded by the  Commonwealth Scientific and Industrial Research Organisation (CSIRO) , which was made available at the ADNI database (http://www. loni. ucla. edu/ADNI). The AIBL researchers contributed data but did not participate in analysis or writing of this report.
AIBL researchers can be found on the AIBL website (http://aibl. csiro. au). Data used in the preparation of this study was obtained from the  AddNeuroMed  study which was supported by  InnoMed , ( Innovative Medicines in Europe ) an  Integrated  Project funded by the  European Union  of the  Sixth Framework program  priority  FP6-2004-LIFESCIHEALTH-5 ,  Life Sciences, Genomics and Biotechnology for Health, Health Research Council of Academy of Finland  (HS), The  Gamla Tjanarinnor Foundation ,  The Swedish Alzheimer's Association and Swedish Brain Power. Data used in the preparation of this study were obtained from the  Swedish National Study of Aging and Care in Kungsholmen  (SNAC-K) which was supported by  Stiftelsen för Gamla Tjänarinnor and Sigurd och Elsa Goljes Minne , the  Swedish Research Council , the  Swedish Council for Working Life and Social Research, Swedish Brain Power , an  Alexander von Humboldt Research Award , and a donation from the af  Jochnick Foundation.