dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion The main objective of this study was to analyze the pattern of genetic diversity within and between wild and cultivated grapes from the Mediterranean basin and Central Asiaconsidered to be the center of domestication. We pooled information from six previous studies that examined both wild and cultivated accessions, and genotyped an additiopnal 403 wild accessions from the Caucases region and Croatia at 20 microsatellite loci. The microsatellite marker data from 1378 accessions was subjected to NJ clustering and Bayesian methods to elucidate groupings of wild grapevine populations and to infer gene flow and gene frequency changes that occurred during domestication.
Mutation Profile of OVPA8 Cell Line The frequency of TP53 mutations in HGSOC is estimated at 96%. The most frequently mutated hot-spots of TP53 are localized in exons 5-8  [13]. We analyzed OVPA8 and five other ovarian cancer lines by Sanger sequencing of these exons. We found homozygous mutation c. 733G>A (p. Gly245Ser) in OVPA8 cell line (Figure  8A ) which has been described as pathogenic in VarSome genomic variation databases and 'likely pathogenic' in ClinVar database  [14]. The results were additionally confirmed by NGS analysis (Figure  8B ). Using FISH analysis we also checked whether homozygous reading of this mutation in a Sanger sequencing plot could be related with a loss of a second copy of TP53. The results showed no numerical changes in chromosome 17 and TP53 itself in OVPA8 cells (Figure  8C ).
Domcke et al. , who analyzed the data from The Cancer Cell Line Encyclopedia (CCLE) and compared it with those from The Cancer Genome Atlas, proposed a ranking of cell lines by their suitability as HGSOC models. In this ranking SKOV3 and A2780 are both classified as "unlikely HGSOC"  [11]. The authors point out that these cells lack the major hallmarks of HGSOC, such as high copy number variation and mutations in TP53 and BRCA genes. Instead, they have mutations in "non-HGSOC" genes: ARID1A (mutation typical for clear cell and endometrioid ovarian cancers) and PI3K (frequently found in clear cell ovarian cancers). Additionally, Anglesio et al. , questioned the use of SKOV3 and A2780 as models of high-grade serous carcinoma  [15] , while Beaufort et al. have classified both of these lines as derived from "endometrioid or clear cell" ovarian cancers  [10].
Plating efficiency was estimated by comparing the ability of OVPA8 and the commercial ovarian cancer cell lines to form colonies. Cells were seeded at 1. 5-3. 0 × 10 3 cells/6-cm polystyrene plates and incubated until the formation of colonies (8-14 days, depending on the cell line). The culture medium was changed once a week. Colonies were fixed with methanol/formalin 1:1 (v/v), stained with 0. 5% crystal violet for 15 min at 37 • C, and documented using a G:Box Imaging System and GeneTools software (Syngene, Bangalore, India). For cell migration assay cells were harvested, resuspended in the serum-free medium, and seeded at a concentration of 7. 5 × 10 4 cells/well (300 µL/insert) on the upper surface of a 24-well transwell insert with a pore size of 8 µm (Falcon ® Corning, New York, NY, USA), pre-treated with fibronectin (10 µg/mL; Merck KGaA, Darmstadt, Germany).
The data was analyzed using Ion Reporter Software (Thermo Fisher Scientific) and ANNOVAR software was used to annotate genetic variants. Somatic gene loss events were detected using Ion Reporter's built-in algorithm for CNV analysis which performs a statistical comparison of the distribution of normalized amplicon coverage values across the entire set of BRCA1 and BRCA2 coding exons. The Ion AmplSeq™ Library Kit 2. 0 (Thermo Fisher Scientific) and the Ion AmpliSeq Cancer Hotspot Panel v2 (Thermo Fisher Scientific) was used to prepare the library for analysis of approximately 2800 COSMIC mutations in 50 cancer-related genes (ABL1, EGFR, GNAS, KRAS, PTPN11, AKT1, ERBB2, GNAQ, MET, RB1, ALK, ERBB4, HNF1A, MLH1, RET, APC, EZH2, HRAS, MPL, SMAD4, ATM, FBXW7, IDH1, NOTCH1, SMARCB1, BRAF, FGFR1, JAK2, NPM1, SMO, CDH1, FGFR2, JAK3, NRAS, SRC, CDKN2A, FGFR3, IDH2, PDGFRA, STK11, CSF1R, FLT3, KDR, PIK3CA, TP53, CTNNB1, GNA11, KIT, PTEN, VHL).
NGS was performed as described above, with the exception that 45 pM of library was taken for template preparation. TP53 mutations in exons 5-9 were analyzed in OVPA8 and five other cell lines by Sanger sequencing (Table  4 ), according to Krześniak et al. [43]. Fluorescence in situ hybridization (FISH) was performed to visualize chromosome 17 and TP53 locus. OVPA8 cells were fixed on microscope slides and stained using SpectrumGreen-labeled CEP17 and SpectrumOrange-labeled 17p13. 1 (TP53) probes (Vysis TP53/CEP17 FISH Probe Kit, Abbott, Lake Bluff, IL, USA). Both interphase and metaphase images were analyzed using an AxioImager. M2 (Zeiss) fluorescence microscope and AxioVision Microscope software (Zeiss).
Acknowledgments: We are very grateful to  Mirosław Markiewicz , head of the  Department of Hematology and Bone Marrow Transplantation, Andrzej Mielęcki Independent Public Hospital in Katowice (Poland) , for enabling us to perform cytogenetic analysis, and  Mariola Iliszko  from the  Department of Biology and Genetics, Medical University in Gda ńsk (Poland ) for her valuable support in karyotype analysis. We thank  Agata Chwieduk  for help in EBV detection, and  Krystyna Klyszcz  for their excellent technical assistance.
Background: An inhaled corticosteroid (ICS) or leukotriene receptor antagonist (LTRA) may prevent wheezing/asthma attacks in preschoolers with recurrent wheeze when added to shortacting β-agonist (SABA). Objective: The aim of this historical matched cohort study was to assess the effectiveness of these treatments for preventing wheezing/asthma attacks. Methods: Electronic medical records from the Optimum Patient Care Research Database were used to characterize a UK preschool population (1-5 years old) with two or more episodes of wheezing during 1 baseline year before first prescription (index date) of ICS or LTRA, or repeat prescription of SABA. Children initiating ICS or LTRA on the index date were matched 1:4 to those prescribed only SABA for age, sex, year of index prescription, mean baseline SABA dose, baseline attacks, baseline antibiotic prescriptions, and eczema diagnosis.
Data source and study approval At the time of this study, the Optimum Patient Care Research Database contained anonymized, longitudinal medical record data for 2. 5 million patients in the UK, where patients' electronic medical records, incorporating primary, secondary, and hospitalization care data, are centralized at their primary care practices. 26 The study was conducted in compliance with all applicable local and international regulations and to standards suggested for observational studies (details in the Supplementary materials). 27 The protocol, analyses, and dissemination of the results were approved by an independent steering committee of the Respiratory Effectiveness Group, 28 a not-for-profit research and advocacy organization dedicated to furthering real-life clinical research.
Children who experienced treatment failure before a first wheezing/asthma attack were censored at 7 days after the date of treatment failure, Outcome year 12 months after the index date for outcome evaluation SABA a ± SABA defined as addition of new therapy or ≥50% increase in dose of index date therapy. Treatment failure was included as a variable only in the Kaplan-Meier analyses (further information is provided in the Supplementary materials). Matching was completed using SAS version 9. 3 (SAS Institute, Cary, NC, USA). Outcome analyses were carried out using Stata version 14. 1 (StataCorp LLC, College Station, TX, USA).
Our findings suggest watchful waiting, obviously in conjunction with as-needed symptom management, may be the best approach for many children with preschool wheeze. Fitzpatrick et al  9  found that daily ICS was most likely to be efficacious for preschool children who had evidence of type 2 inflammation (aeroallergen sensitization and elevated blood eosinophil count). In a recent population-based study, 3 allergic rhinitis, eczema, and parental asthma were three readily assessed variables associated with asthma diagnosis by 4 years of age in children with ever-wheeze. Finally, outcomes in another recent study suggested that children with the 5/5 ALOX5 promoter genotype may be responsive to intermittent montelukast therapy (P-value for interaction =0. 08). 19 We were not able to assess these factors, as they were not evaluated in practice and/or recorded in the database for most children; however, an analysis including children with evidence of type 2 inflammation (aeroallergen sensitization and elevated blood eosinophil count or FeNO) is an important topic for further study in future observational studies using stratified analyses based on atopic status.
Nevertheless, a pragmatic trial of patients who persist on their index date therapy could further elucidate this point. In the LTRA vs ICS comparison, the fact that 69% of the children in the LTRA cohort were prescribed ICS in the outcome year while only 8% of the ICS cohort were prescribed LTRA during the outcome year suggests that those in the LTRA cohort had poorer control during the outcome year. Alternatively, this finding could be attributed to common prescribing pathways, whereby clinicians may be more likely to prescribe ICS to children whose symptoms do not respond to an LTRA than the converse (ie, prescribe LTRA to children whose symptoms do not respond to an ICS). Overall, many more children in the database were initiated on ICS (n=11,329) than LTRA (n=335). ] [40]  This study enabled us to record the occurrence of wheezing/asthma episodes over a 2-year time span, longer than most clinical trials.
In addition, the matched LTRA/SABA cohorts were slightly younger than the matched ICS/SABA cohorts (mean 2. 6 vs 3. 2 years), which could have influenced the findings in light of the time effects. Overall, our study population may represent children on the milder end of the spectrum, as the study design required excluding children prescribed ICS before the age of 1 and those prescribed ICS or LTRA during the baseline year. Another study limitation is that we were unable to ascertain whether children had persistent symptoms or were symptom-free between wheezing/asthma attacks. Moreover, the occurrence of adverse effects is not reliably recorded in medical records, hence not in the datasets, whereas a comparison of adverse occurrence associated with each treatment option would be useful information and constitutes an important area of further study.
In addition, we could not assess medication adherence, and our study design could not distinguish between daily or intermittent ICS administration nor whether new therapy during the outcome year constituted a switch or add-on to existing therapy. The analyses depended on the quality of data recorded in primary care records, and the ability to clinically characterize the children was restricted to data available in their medical records. For example, we used an ever-recorded diagnosis of eczema, present for 38%-41% of children in each cohort, as an indicator of atopy. Other limitations include those common to all observational studies, including the potential for selection bias and unmeasured confounding factors. Moreover, it is likely that not all secondary care and hospital attendance information was captured in the longitudinal, electronic medical records housed at each individual's primary care practice.
Acknowledgments The authors gratefully acknowledge  Ronan Ryan, PhD , and  Jaco Voorham, PhD  ( Observational and Pragmatic Research Institute Pte Ltd, Singapore ), for statistical expertise and assistance with the analyses. This work was supported by the  Respiratory Effectiveness Group  (http://effectivenessevaluation. org/). Access to data from the  Optimum Patient Care  Research Database (http://optimumpatientcare. org/ opcrd/) was provided as an in-kind donation from  Optimum Patient Care. Collaborators from the  Respiratory Effectiveness Group (REG) Small Airways Working Group and Child Health Working Group: Willem MC van Aalderen: Department of Pediatric Respiratory Medicine and Allergy, Emma Children's Hospital AMC, Amsterdam , the  Netherlands. Clare S Murray: Division of Infection , Immunity and  Respiratory Medicine , Manchester  Academic Health Science Centre, The University of Manchester ,  University Hospital of South Manchester, and Royal Manchester Children's Hospital, Manchester, UK.
TrkC-KF and Hey1 cooperate in inhibiting MDM2 transcription by direct binding to MDM2 promoter Because we (i) failed to detect any interaction between MDM2 protein and neither Hey1 nor TrkC-KF by proximity ligation assay (S5A Fig), (ii) observed that Hey1 DBD appears to be important for TrkC-KF/Hey1-mediated stabilization of p53 (Fig 4G ), and (iii) identified MDM2 in a chromatin immunoprecipitation sequence (ChIP-Seq) aimed at screening Hey1 binding sites in Hey1 overexpressing cells (Gene Expression Omnibus [GEO] accession number GSE60699  [27] ), we hypothesized that Hey1/TrkC-KF may transcriptionally regulate MDM2 expression. We first measured MDM2 expression by quantitative real-time PCR (RT-QPCR) in SHEP cells transfected with various expression plasmids. As described previously by Huang and colleagues, forced expression of Hey1 is able to deregulate MDM2 We described in a previous study the shuttling of TrkC-KF at the mitochondria by COBRA1, in which both partners activated BAX and induced MOMP, the subsequent release of cytochrome c, and apoptosome activation  [13].
Western blotting HEK293T, SHEP, and N2A cells were lysed in 50 mM HEPES pH 7. 6, 125 mM NaCl, 5 mM EDTA, and 0. 1% NP-40 in the presence of proteases inhibitors. For p53 western blots, SHEP cells were lysed in 50 mM Tris-HCl pH 7. 5, 100 mM NaCl, 10% glycerol, 0. 1% NP-40, and 0. 2 mM EDTA in the presence of proteases inhibitors. Western blots were quantified using the ImageJ64 software.
Proximity ligation assays (DuoLink) To assay protein interactions in cells by fluorescence, the DuoLink PLA kit was used (Sigma Aldrich). Briefly, cells were cultured on coverslips and then fixed in 4% PFA for 30 min and washed using PBS/7. 5% glycine for 5 min. Cells were then permeabilized in PBS/0. 2% Triton and incubated in a blocking solution for 30 min (PBS/2% BSA). After an overnight incubation with the primary antibodies, cells were incubated with Plus and Minus PLA probes. The probes were ligated and amplified using the Duolink In Situ Detection Reagents Orange (Sigma Aldrich). After several washes with the Duolink In Situ Wash Buffers for Fluorescence (Sigma Aldrich), nuclei were stained using DAPI, and coverslips were mounted in fluoromount. The analysis was made by fluorescence microscopy, and signal quantification was assessed using the ImageJ64 software to count the number of red fluorescence spots compared to total cell number (assessed using DAPI staining).
Luciferase assay To assay TrkC-KF transcriptional activity, SHEP cells were transiently transfected with the indicated constructs fused to Gal4 DBD, a plasmid containing the firefly luciferase gene under the UAS-Gal4 control, and a plasmid coding for the Renilla luciferase gene under the CMV promoter as a control. To assess Firefly and Renilla luciferase activities, Dual-Luciferase Reporter Assay System was used following manufacturer's instructions (Promega). Data represent Firefly value over Renilla value, indexed to control (Gal4).
Xenografts in ovo SHEP cells were transfected with jet prime and siRNA NT-3 (100 nM) and/or siRNA Hey1 or sip53 (50 nM) 24 h before inoculation. Five million cells were suspended in 25 μl complete medium and 25 μl matrigel (Corning 356231) and seeded on 10-d-old (E10) chick CAM. On day 15, tumors were resected and weighted. To monitor apoptosis on primary tumors, they were fixed on 4% PFA, cryoprotected by overnight treatment with 30% sucrose, and embedded in Cryomount (Histolab). TUNEL staining was performed on tumor cryostat sections (Roche Diagnostics), and nuclei were stained with DAPI. Three to eight sections were analyzed at ×20 magnification for at least 3 tumors for each condition. TUNEL and DAPI positive cells were counted by ImageJ64 software.
Transcriptomic data sets analysis The expression values analyzed here are publically available in GEO database (http://www. ncbi. nlm. nih. gov/geo/). T. Wolf cohort (GSE45480  [54] ) analysis was performed with Agilent-020382 Human Custom Microarray 44k (GPL16876); the following data set probes were used: NT-3 (NTF3) UKv4_A_23_P360797, TrkC (NTRK3) UKv4_A_23_P205900, UKv4_A_23_P88538, and Hey1 UKv4_A_32_P83845. In this study, for TrkC and Hey1 expression values, a mean of the values obtained with the various probes was calculated. Kaplan-Meier analysis was performed in R2: Genomics Analysis and Visualization Platform (http://r2. amc. nl). The p-value is calculated to determine the optimal cutoff and is finally corrected by Bonferoni as described in  [55]. A new grouping variable was made on the basis of NT-3, TrkC, and Hey1 as described in the main text.
(E) Human COBRA1 mRNA expression was assessed by RT-QPCR on SHEP cells transfected with siRNA control, siRNA NT-3, siRNA Hey1, or siRNA p53. Data represent mean ± SEM (n = 3) relative to GAPDH mRNA expression (housekeeping gene) and indexed to control. Ã p < 0. 05. Two-sided Mann-Whitney test compared to control. (F,H,J) Schematic representation of COBRA1 promoter (F), BAX promoter (H), and BAK promoter (J). Exons are indicated as gray boxes. The p53 binding site is indicated as a black box "P," with the corresponding sequence. The couples of primers a, b, and c used in the ChIP experiments described in figures (G), (I), and (K) are also indicated. (G,I,K) ChIP assays using chromatin isolated from SHEP cells, which were untransfected (white bars), transfected with control (gray bars), or TrkC-KF and Hey1 constructs (black bars).
Proteins were immunoprecipitated with an isotypic control antibody (white bars) or an anti-p53 antibody. DNA sequences from COBRA1 promoter (G), BAX promoter, (I) and BAK promoter (K) were amplified by RT-QPCR using couples of primers a (upstream control), b (p53 binding site), and c (downstream control) indicated on (F,H,J). Data represent mean values ± SEM (n = 3) indexed to isotypic IgG value. Underlying data can be found in S1 Data. BAK, B cell lymphoma 2 killer; BAX, B cell lymphoma 2-associated X; ChIP, chromatin immunoprecipitation; COBRA1, cofactor of breast.
Acknowledgments We thank  J. Bouzas-Rodriguez  for 2-hybrid constructs and  L. Giraud  for technical assistance. We thank  M. Gessler ,  J. A. Kessler ,  J. M. Shohet ,  F. Rother , and  R. Marschalek  for materials. We also would like to thank  J. C. Bourdon ,  V. Marcel ,  S. Cox ,  F. Maina ,  O. Meurette ,  C. Delloye-Bourgeois , and  V. Castellani  for helpful discussions and materials.
INCA (grant number 2012-116). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ANR  (grant number  DevDepR 08-BLAN-0279-01 ). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Ligue Received by MM. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ERC Advanced  grant (grant number  Deprec 294079 ). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. CNRS. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. INSERM. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Acknowledgements. The authors acknowledge the support of the  Austrian-French scientific exchange program  "Amadeus" (R. M. and A. H. ) and the support of the  Austrian Fonds zur Förderung der Wissenschaftlichen Forschung  (A. H. and D. U. ). They are also grateful to the  Hinode team  for allowing them to use their data. Hinode is a Japanese mission developed and launched by  ISAS/JAXA , collaborating with NAOJ as a domestic partner,  NASA  and  STFC (UK)  as international partners. Scientific operation of the Hinode mission is conducted by the Hinode science team organized at ISAS/JAXA. This team mainly consists of scientists from institutes in the partner countries. Support for the post-launch operation is provided by  JAXA  and  NAOJ (Japan) ,  STFC (U. K. ) ,  NASA (U. S. A. ) ,  ESA , and  NSC (Norway).
The landmark analyses excluded patients who died or progressed (contrast enhanced CT-based assessment of progressive disease, or started next anti-lymphoma treatment) before or at end of induction. GALLIUM is registered at ClinicalTrials. gov, number NCT01332968. Interpretation Our results suggest that PET is a better imaging modality than contrastenhanced CT for response assessment after first-line immunochemotherapy in patients with follicular lymphoma. PET assessment according to Lugano 2014 response criteria provides a platform for investigation of response-adapted therapeutic approaches. Additional supportive data are welcomed. Funding F. Hoffmann-La Roche.
A pooled analysis of these studies with longer follow-up was conducted; scans were centrally reviewed by three independent PET physicians. Post-treatment PET with a cutoff score of four or greater (defined as ¹ ⁸ F-FDG uptake in tumour higher than that in the liver) on the 5-point scale (also known as the Deauville criteria) The phase 3 GALLIUM study (NCT01332968) was designed to compare the efficacy and safety of induction therapy with obinutuzumab versus induction therapy with rituximab, combined with chemotherapy (bendamustine, CHOP [cyclophosphamide, doxorubicin, vincristine, and prednisone], or CVP [cyclophosphamide, vincristine, and prednisone]) in both groups and followed by maintenance with the same antibody alone, in responding patients with previously untreated, advanced, indolent non-Hodgkin lymphoma.
Statistical analysis The data reported in the primary GALLIUM study report were from a preplanned interim analysis, when the prespecified significance level for the primary endpoint had been crossed (cutoff Jan 31, 2016). 1  The results reported in this Article are from an updated analysis (cutoff Sept 10, 2016). As a secondary analysis of the GALLIUM trial, the analyses presented in this report are not powered. Demographic and baseline characteristics were summarised using descriptive statistics in the PET population (defined as all randomly assigned patients with available baseline and end-of-induction PET scans; the non-PET population included all other randomly assigned patients). Kaplan-Meier methodology was used to estimate landmark progression-free and overall survival distributions from end-of-induction therapy for each group.
Estimates of the differences between groups were determined using a stratified Cox proportional hazards analysis and expressed as HRs and 95% CIs. Estimated 2•5-year probabilities, including 95% CIs, were also used to describe progression-free and overall survival. Exploratory univariate and multivariable Cox analyses were undertaken to investigate factors that were prognostic for progression-free and overall survival. GALLIUM is registered at ClinicalTrials. gov, number NCT01332968.
Therefore, any variants detected in DNA samples from FFPE material should be confirmed by independent PCR and carefully verified using the recommended databases (described below) before interpreting and reporting them as mutations. Finally, when considering the type of nucleic acid to analyze, genomic DNA is highly recommended. Analyzing RNA may result in truncating or splice site variants being missed due to nonsense-mediated RNA decay  [29]. In addition, using whole-genome amplification for diagnostic purposes is discouraged as it may introduce a bias in allelic frequencies and could lead to allelic drop-out.