dataesr/scientific-paragraphs-categorization huggingface dataset:
specificity of ngs-Based Kir allele Typing Due to the high degree of KIR polymorphisms and the fact that NGS technology generates a lot of sequencing reads, three different algorithms were evaluated to increase the reliability of KIR allele assignment as reported for NGS-based HLA typing  (50). KIR allele assignment was first done manually and then confirmed using both BiRD pipeline and Profiler software. Overall, resulting KIR allele assignments of the 30 reference IHW samples were feasible for all loci and for the majority of samples without remaining ambiguities (Table  1 ). We further evaluated the strength of our NGS-based method for KIR allele assignment. For all IHW reference samples tested (N = 30), the number of KIR alleles previously known in the IPD/KIR database and those obtained by our NGS-KIR based typing approach was compared for each KIR locus.
As an example, from the 30 IHW samples tested, only 5 KIR3DL3 alleles out of 60 expected alleles for this framework gene were previously known in the IPD/KIR database (Table  S1  in Supplementary Material), 54 KIR3DL3 alleles from 24 heterozygous and 6 homozygous samples (Table  1 ) were assigned by our NGS-based KIR allele typing approach (Figure  4 ). Our NGS-based KIR allele typing approach permits identification of additional framework KIR alleles, e. g. , KIR3DP1 (n = 43), KIR2DL4 (n = 48), and KIR3DL2 (n = 44) (Table  1 ; Figure  4 ). NGS-based KIR typing method also allows the identification of polymorphisms of well-functionally characterized KIR by increasing the number of assigned KIR alleles of the 30 IHW samples available in the IPD/KIR database (Table  S1  in Supplementary Material), e.
g. , KIR2DL1 (n = 30), KIR2DL2 (n = 10), KIR2DS1 (n = 11), KIR2DS2 (n = 12), KIR3DL1 (n = 35), and KIR3DS1 (n = 11) (Table  1 ; Figure  4 ). The number of activating KIR2DS1, KIR2DS2, and KIR3DS1 assigned alleles by NGS remained low because only IHW samples with the corresponding activating KIR gene were included in this analysis. Overall, a higher number of KIR alleles were identified from these 30 IHW samples by our shotgun NGS methodology compared to those previously characterized by other less sensitive methods, as referred to in the IPD/KIR database (N = 422 vs N = 233, respectively). The knowledge of KIR allele typing of IHW samples, recently updated thanks to an exome capture  (47) , permits to evaluate the concordance of our NGS-based KIR allele results (Table  1 ) with those of Norman et al.
KIR allele determinations using manual, BiRD algorithm, and different versions (the latest one Rev 2. 0. 188) of Profiler software were carefully reviewed. Only IHW samples sequenced on different runs and with the same KIR allelic results were reported (data not shown). These potential discrepancies (5%), possibly linked to the design and implementation of each algorithm, need to be further validated by another typing method such as SSP or sequencing. Overall, our NGS-based method and exome data showed a rate of concordance of 95% for all loci, established for all KIR genes on 22 IHW samples, suggesting a reliable method.
Our study evaluated the performance of different algorithms for KIR allele assignment. Reliability of the manual, BiRD pipeline, and Profiler software was tested since neither algorithm alone was able to provide 100% accuracy for all KIR loci. Our results showed that the Profiler software was reliable to assign KIR alleles through the full length of each KIR gene, excluding KIRDL5A variants. In this case, KIR2DL5A and KIR2DL5B sequences were too closed, and Profiler software failed to accurately analyze both sequences. Since all coding, non-coding, and regulatory regions were explored, one could expect that a lot of new KIR alleles will soon be described. Analysis with Profiler consists of two distinct parts. The first part is performed in three steps in a Linux environment: the first step corresponds to the merging of each R1 and R2 issued from the same cluster to each other, each time that a complementarity of at least 10 bases is found, with correction or base calling inconsistencies using a quality value for each nucleotide.
There are two interests in this step: longer sequences and lower sequences number were analyzed. The second step corresponds to the phasing of each sequence based on KIR databases using Blast algorithm. Third, the data file from Blast was used to merge all sequences together to construct each allele. In this step, calculation for depth of each position and the number of sequences used for each allele are determined. The second part is done on a Windows environment. A friendly interface presents graphics of all sequences for all studied loci. Assignment of all sequences is done using a database, highlighting all mismatches compared to reference and also differences between KIR alleles selected. Each allele is scored for quality control as per the European Federation for Immunogenetics guideline.
Until now, KIR genetic population studies have often been restricted to the identification of KIR gene content, or of A and/ or B KIR haplotypes  (51, 52). Determination of KIR alleles in healthy individuals of a given population may provide a better definition of KIR haplotypes  (52)  and KIR gene linkage disequilibrium (53) and will considerably increase the IPD/KIR database. The implementation of our suitable NGS. KIR method will enable analysis of all allelic polymorphism within KIR genes extending to all coding, non-coding, and regulatory regions. A link between KIR allelic polymorphism and the expression level and/or function of the corresponding KIR + NK cells is necessary for all KIR genes as previously established for the expression level of HLA-A and HLA-Cw molecules  (54) (55) (56).
Investigation of KIR allelic polymorphism may be of an immunological interest in the context of viral infections such as those related to CMV (62), HIV  (63) , HCV  (64) , and of human reproduction  (65). In the context of HSCT, inclusion of KIR allele typing in addition to HLA typing may provide a better evaluation of HSC donor's KIR + NK cell repertoire  (21, 59, 60, 66, 67). An identification of those with the best antileukemic potential will provide a potential tool to determine an early posttransplant hematopoietic chimerism when donor and recipient have identical KIR genotypes  (68)  as well as the impact of KIR + NK cell alloreactivity on HSCT outcome  (69) (70) (71) (72) (73). The functional relevance of typing both KIR and HLA genes at   (47). In this case, KIR allele typing for each locus and for all samples corresponds to the combined KIR allelic results obtained using manual pipelines, BiRD, and Profiler softwares.
aUThOr cOnTriBUTiOns BM performed KIR allele typing by next-generation sequencing, KIR allele assignment, interpretation of data, and wrote the manuscript. NL performed DNA extractions from EBV-B cell lines, KIR genotyping and KIR allele typing by next-generation sequencing and commented on the manuscript. MA upgraded Profiler software integrating a KIR module, analyzed data, and commented on the manuscript. UG developed a pipeline for KIR allele assignment, analyzed data, and commented on the manuscript. CW and GD performed DNA extractions from EBV-B cell lines and commented on the manuscript. EC supervised the development of a pipeline for KIR allele assignment, provided a bioinformatic help on KIR read mapping, and commented on the manuscript. AW provided advices on the library construction setting and commented on the manuscript.
acKnOWleDgMenTs The authors are most grateful to  Audrey Donnart ,  Dr. Audrey Bihouée , and  Dr. Richard Redon  of the  Genomics and Bioinformatics Core Facility of Nantes (GenoBiRD, Biogenouest, Nantes, France)  for their technical support. The authors would also like to thank  Dr. Anne Cesbron  ( HLA laboratory, EFS Nantes, France ) for the access of MiSeq platform,  Dr. Kenza Belhaj  ( EFS La Plaine Saint Denis, France ) for her contribution in KIR pipeline development by  GenoBIRD genomics platform, Britt House Europe (Hegenheim, France) , and  Dr. David Senitzer  ( Division of Hematology and Bone Marrow Transplantation, Duarte, CA, USA ) for help in the editing of the manuscript. This work was supported by  EFS Pays de la Loire  and by grants from  International Research Group  on unrelated Hematopoietic stem cell Transplantation (IRGHET 2015),  Etablissement Français du Sang  ( EFS 2016-09 ), and  Association Leucémie Espoir Atlantique Famille (LEAF).
Economic evaluation The economic evaluation of the CAPRI program will adopt a societal perspective, assessing intervention, medical and non-medical costs. All resources used by patients included in the study will be considered in the frame of a cost-effectiveness study. It is expected that in comparison with usual care, CAPRI intervention will result in cost-effective care with improvement in patients' adherence to oral anticancer therapy. Cost data will be collected monthly using retrospective selfquestionnaires for non-hospital costs. For hospital costs, medico-administrative data will be used. Table  3  presents the resources used to be included in the cost-effectiveness study, and their value units.
Process evaluation A parallel evaluation will be conducted to describe both the steps taken to implement the intervention, and the prevailing conditions, which may be important to helping/ supporting process implementation. This evaluation will be led as a longitudinal study through quarterly assessments of web portal use by enrolled patients and professionals, alongside evaluations of their satisfaction and needs. Analysis will also include the description of Nurse Navigator activities and specific skills. Data on access to, and use of, the web portal will be extracted from the web portal records. In addition, focus groups with Nurse Navigators will be organized throughout the study. Lastly, semi-structured interviews with patients, relatives and healthcare professionals engaged in the program will be conducted by the research team at the end of the trial.
Data analysis Appropriate descriptive statistics will allow presentation and comparison of sample characteristics at baseline, and at each evaluation time point. The primary analyses will utilize a between-group design (CAPRI versus control groups) at six time points (each month)). Significant change in treatment delivery will be measured on the RDI ratio, calculated with the Morisky score and/or the Medication Event Monitoring System (MEMs) results. If distribution is normal, a student t-test will be used to compare RDI means, as well as secondary outcomes designed as continuous variables. If not, a Mann-Whitney test will be used. Chi2 or Fisher's test will be used to compare secondary outcomes designed as binary variables. Baseline data will be examined to analyze probability of attrition bias.
hominis, while 5 (20. 8%) were identified as C. parvum. When only colon intraepithelial neoplasia/adenocarcinoma was considered, this proportion was maintained: the presence of 7 (78%) C. hominis and 2 (22%) C. parvum isolates was confirmed. The sequences obtained showed 100% identity with GenBank reference sequences. There were not differences in the risk for colon cancer when these species were considered independently. The presence of the parasites in tissues was confirmed by microscopic observation in 11 colonic neoplastic sections out of 15 (Fig  2 ). In order to exclude EBV, an oncogenic pathogen potentially responsible for colon cancer, biopsies from cancerous and control subjects were analyzed. Results showed a homogeneous distribution of the virus among groups of Cryptosporidium-infected and non-infected patients, as well as among subjects with and without colon cancer.
Patient selection and data collection This is a single-centre retrospective observational study evaluating the difference between two groups of patients treated for renal graft intolerance syndrome by either percutaneous graft embolization as first-line treatment (Group 1) or directly by surgical graft removal (Group 2). The period of inclusion was from January 2005 until December 2014. The data were collected from our renal transplant registry with prospective database collection and from patients' medical records, papers or electronics. We have included only those patients treated after the first transplant year. Patients lost for follow-up after the intervention (dialysed outside France) were excluded. We also excluded all patients with a graftrelated condition other than graft intolerance syndrome which might have contributed to the therapeutic decision, like those with a frank acute rejection (high grade fever with remarkable swelling of the graft and/or pain needing more than weak opioids), renal graft-related cancer, recurrent pyelonephritis or pyonephrosis of the renal graft, or in whom a future renal transplantation was planned after surgical removal of one of the two iliac fossa nonfunctioning renal grafts (Fig.
The phantom was placed in the head position on the patient scanning couch and three sets of planar data and three sets of SPECT acquisitions (with CT, if available) were acquired and saved for processing. After making the measurements, participants were asked to report the details of their equipment, acquisition parameters, processing methods, and results. For the second trial, a more prescriptive protocol was written, mostly dealing with harmonizing the acquisition parameters and the calibration methodology. Additional training was provided in the form of informal lectures given by the more experienced participants in the project. The B-series source in air was again used for calibration, but the actual activity of only that source, as measured by NIST, was given to each participant -all other source activities remained unknown.
Analysis methodology To facilitate consistent comparison of the results between the centres for each of the three exercises, all activity values reported by the participants are presented as ratios, R, of the mean of the participants' reported activities for each source at the prescribed reference time to the NIST calibrated activity for that source at the same reference time. Unless otherwise stated, the quoted uncertainties are standard (k = 1) uncertainties calculated from the quadratic addition of the relative combined standard uncertainty on the NIST activity for the specific source and the relative standard deviation of the three activity determinations for that source as reported by the participant. Data were analysed for each of the three exercises separately by grouping the R-values by source size, thereby giving four subsets of data in each exercise.
Trial 2 In addition to the data received from the laboratories participating in Trial 1, the data from Trial 2 included responses for both CTAC and planar from one participant that did not provide data in Trial 1. This gives a total of 9 institutes reporting results for planar and 5 institutes giving values for CTAC. It should also be noted that, as seen in Table  1 , one of the participants used a scanner for this trial that was different from the one used in Trial 1. It is therefore possible that there are additional components of uncertainty when comparing the results for that participant that are not present in the others. In the case of planar imaging, two results were identified by Grubb's tests to be outliers, with one value being too low (R = 0. 35) and the other being too high (R = 1.
Acknowledgments The authors would like to thank RadQual,  LLC  for providing the sources used in this study. Dr. Stig Palm  (formerly IAEA, presently  Gothenburg University)  is acknowledged for conceiving and initiating this project. This work was carried out as part of the  IAEA  Coordinated Research Project  E2. 10. 07  entitled " Development of Quantitative Nuclear Medicine Imaging for Patient Specific Dosimetry ".
2 ). Positioning of these different markers was automatically performed by the technique of marker tracking (Deftac ® software by Peprime lab, Poitiers, France). This was used to calculate flexion amplitudes for a gap of the ligament suture of 1 and 2 mm, taking as initial angle the seat angle and knotting of the frame, which is the flexion associated with initiation of the disunion of ligament suture. Flexion amplitude was called delta flexion angle (ΔF). Example: ΔF 2 mm = knee flexion angle for a distension of the suture of 2 mm-flexion angle and initial knotting of the frame (Fig. 3 ). The percentage of deformation of the frames (% def ) for a suture deviation of 1 and 2 mm were calculated too. Example: % def 2 mm = (distance between the two markers of the frame at flexion angle and initial knotting of the frame * 100)/distance between the two markers of the frame for distension of the suture of 2 mm.
Patients and serum samples Serum samples for ELISA analysis were collected from four centers (Taussig Cancer Institute, Cleveland, USA; AOU Careggi, University of Florence, Italy; Saint Louis Hospital, Paris, France; H. Lee Moffitt Cancer Center, Tampa, FL, USA). Peripheral blood mononuclear cells were collected from patients at Moffitt Cancer Center. All patients had provided consent to Institutional Review Board, or equivalent, approved protocols in hematology clinics at each center, and the Eastern Cooperative Oncology Group (ECOG) E2905 trial (www. clinicaltrial. gov NCT00843882). All routine clinical and biological data were available.
Patients From January 1st, 2010 to December 31st, 2015, we prospectively included all patients admitted with suspected BCNE to the 4 university hospitals in Marseille, France. Blood cultures were considered negative when no microorganism grew after 5 days of incubation. For each studied patient, a questionnaire was completed by the physician in charge. Requested information included age, sex, the involved cardiac valve and its type (native or prosthesis, and the type of preexisting valvular defect, if any), contact with cats or body lice, drug abuse, immunodeficiency (and its type), antibiotic uptake prior to blood cultures, clinical and echocardiographic data used in the Duke score,  [8]  clinical and biological data used in the Marseille score,  [9]  antibiotic treatment, and outcome (valvular surgery, recovery, and death).
Acknowledgments We are indebted to numerous general practitioners from France, from  Northern and Southern Germany and Switzerland , from Poland as well to many others for their help. We are indebted to  Prof. Antonius Schneider, Munich , for his support in the German cultural validation process. We thank  Sébastien de Villèle ,  Jean Yves Le Disez  and  Helen McCombie-Boudry  from the  Bureau de Traduction Universitaire Université de Bretagne Occidentale  and  Jean Sébastien Cadwallader  who provided the French translations for the linguistic validation procedure;  Alex Gillman  who provided medical writing services on behalf of the  Collège Brestois des Généralistes Enseignants.
5 A ˚and the high intensity 30 degree detector option IN11C for the high q data. For the low q data we used a wavelength of 8. 5 A ˚and the high resolution detector of IN11A. The correlation function S(q,t) as function of time, t was measured over a time range from 0. 005 to 28 ns and a momentum transfer range from 0. 10 to 0. 65 A ˚21. The first sample was about 3 mL of HbCO A solution, at a concentration of about 100 mg/mL in 50 mM sodium phosphate at pH 7. 1 in heavy water (D 2 O). Subtraction was done with the matching buffer for the sample. The second sample was about 3 mL of HbCO A solution, at a concentration of about 100 mg/mL in 50 mM sodium phosphate at pH 7. 1 in D 2 O and 3 mM IHP. Again, subtraction was done with the matching buffer for the sample. The samples were measured at a temperature of 288 K.
Patients and samples Ninety-nine surgically resected cholangiocarcinomas were included in the study. The median age of the patients was 62. 5 years (range 24 to 85) and the sex ratio (male/ female) was 2. 09. Risk factors of liver disease were identified in 23 patients: hepatitis B virus infection in 8 cases, alcohol in 6, non-alcoholic steatohepatitis in 6, hepatitis C virus infection in 1, primary sclerosing cholangitis in 2, and hemochromatosis in 2. Two patients had multiple risks factors. The main clinical characteristics of the 99 patients are summarized in Table  1. Follow-up data were available in a limited number of cases and could not be used for statistical analysis.
Some drivers experience Simulator Adaptation Syndrome (SAS), a condition in which nausea, disorientation, dizziness, headache, and difficulty focusing, are exhibited when driving in a simulator. To reduce this syndrome, we investigated the efficacy of tactile stimulation (TS) on mitigating Simulator Adaptation Syndrome (SAS) in a driving simulation. Fifteen drivers (eight women; mean age ¼ 24. 07 years) participated in this experiment. We compared the total scores of the Simulator Sickness Questionnaire (SSQ) across two stimulation conditions (TS condition and no stimulation condition as a baseline measure). The experimental outcomes revealed that TS seemed to decrease SAS due to attentional distraction from the symptoms and not because of an improvement in balance ability.
Introduction Simulator Adaptation Syndrome (SAS) is a condition that occurs due to a mismatch between sensory inputs regarding position and what is expected in driving simulators. This syndrome can range from mild discomfort to severe dry mouth, drowsiness, disorientation, vertigo, nausea, dizziness, and vomiting  (Ebenholtz, 1992; Cobb et al. , 1999). The aetiology of SAS is not completely understood (see  Mollenhauer, 2004 ; for an extensive review of SAS). As  Cox et al. (2011)  show, the causes of this syndrome can be assembled attending to individual factors (e. g. , age), characteristics of the driving simulator (e. g. , size of the display screen), and the individual's interaction with the simulator (e. g. , exposure time). To counterbalance this syndrome, some studies focus on mitigating SAS using drugs.
The use of drugs (for a review, see  Sherman, 2002)  is not an efficient countermeasure to mitigate SAS due to side effects that may affect training efficiency  (Murdin et al. , 2011). First, studies with scopolamine may cause sedation, dry mouth, blurring of vision, and light-headedness  (Crowley, 1987). Secondly, oral medication for SAS reduces gastric motility  (Wood et al. , 1987). Finally, it should be noted that medications do not reach their efficacy until several hours after administration. Considering these problems, alternative techniques have emerged to mitigate SAS using different sources of stimulation, like galvanic cutaneous stimulation (GCS), galvanic vestibular stimulation (GVS) and, more recently, auditory stimulation (AS). GCS restores normal balance in the context of vestibular sensory deprivation, as in fixedsimulators.
For example,  Reed-Jones et al. (2008), and G alvez-García (2015)  show that the application of GCS improves balance in subjects performing a simulator task. The improvement in balancing ability is correlated with the mitigation of SAS  (G alvez-García (2015) ). In addition, three studies show the positive impact of GCS on SAS  (Chu et al. , 2013; G alvez-García, 2015; G alvez-García et al. , 2015). GVS is a similar technique to GCS. This involves providing vestibular motion stimuli to reduce SAS. It is shown that GVS improves the body's balance (e. g. ,  Inglis et al. , 1995)  and, more importantly, reduces SAS  (Reed-Jones et al. , 2007). AS (more concretely, white noise) has been recently shown to be an efficient technique to mitigate SAS. G alvez-  García (2015)  shows that white noise improves balance in subjects performing a simulator task.