dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analysis Continuous variables are presented as mean ± SD and categorical as numbers and percentages. Continuous variables were compared with the use of 1-way ANOVA followed by Tukey multiple comparison test when P-value was <0. 05, or Kruskal--Wallis rank sum test followed by Dunn multiple comparisons test (for a P-value <0. 05), when normality or an equal variance test failed. Categorical variables were compared with the use of the Pearson Chi-square (sigma stat). Statistical analyses were performed using Graph Pad Prism software 6. 0 (www. graphpad. com). Receiver operating characteristic (ROC) curve analysis was performed using MedCalc 15. 8 software (www. medcalc. be).
Tumours were classified as HPVpositive if they were positive for HPV16 or HPV18. Statistical analysis. Differences in descriptive statistics by OPSCC subsite were estimated using the w 2 test and Fisher's exact test when cells were sparse. Unconditional logistic regression was used to calculate odds ratio (OR) adjusted with the confounders and matching factors: age, race, and gender. Subsite-specific adjusted ORs were calculated with unconditional multinomial logistic regression. To further explore the role of HPV, conditional logistic regression was used to calculate HPV/p16 status and subsite stratified ORs based on the matching factors, including age (defined in 7 categories), race (White/Black), and sex. All statistical analyses were implemented using SAS 9. 3 (SAS Institute, Cary, NC, USA).
Specifically, pathologists had access to all the pathology data that was available in the form of digitized slides (in. svs format) and were viewed using Aperio ImageScope 12•3 viewing software. This digital viewing application has all the imaging functionality normally available to pathologists in routine clinical practice and is used by the host institution to evaluate cases referred from outside institutions for opinions. For each patient, observers were required to select up to 5 differential diagnoses and provide a diagnostic likelihood (censored at 5% and summing to 100% in each case) from a drop-down menu of diffuse lung diseases (Appendix, Table  A1 ). The only stipulation was that diagnoses were considered in the context of the current ATS/ERS classification and terminology for the IIPs 4 • 2.
Patient population A total of 113 consecutive new referrals who required local MDTM characterisation were identified from the clinical database between March 1 st 2010 and August 31 st 2010. Of these, 43/113 (38•1%) were excluded on the basis that a) their initial workup HRCT scan had been performed at the referring institution (n=29), b) their lung function had been performed at the referring institution (n=4), or c) surgical lung biopsy had been performed by the referring institution (n=10), (Table  1  and Appendix.
7. 1. 0 or SeqScape 2. 5 (Applied Biosystems) were used. Substitutions were recorded relative to rCRS  45  and RSRS  46  (Supplementary Table  22 ). FASTmtDNA utility (www. mtdnacommunity. org) was used to convert sequences from rCRS-format to RSRS-format. Complete mtDNA sequences generated in this study are available at the NCBI (GenBank accession numbers KX358471-KX358508). Whole genome SNP data. Six BLT were genotyped on Illumina 730k platform and analyzed together with 1238 individuals from 83 Eurasian populations from previous studies (Supplementary Table  14 ). The dataset was preprocessed with PLINK v1. 07  47  to ensure that SNPs on the 22 autosomes with minor allele frequency > 1% and missing genotype rate < 3% are included and individuals with missing genotype data > 3% are omitted.
Relatives of the first and the second degree (one individual from a detected pair) were also removed  48. Because some analyses required that SNPs are in linkage equilibrium, the SNPs with r 2 > 0. 4 were pruned out in windows 200 SNPs with step 25 SNPs. Exact numbers of individuals, populations and SNPs used in each analysis are specified in Supplementary Table  14. Possible limitations of using six BLT samples in the genome-wide analyses are discussed in Supplementary Information Text (Material and Methods). The genome-wide genotypes of six BLTs are available at Gene Expression Omnibus (NCBI GEO accession number GSE82309) as well as in PLINK format in our website at www. ebc. ee/free_data. Whole genome SNP data analyses. Runs of homozygosity. Runs of homozygosity (RoH) in BLT were called using PLINK  47.
RoH were defined as regions with at least 50 consecutive SNPs in a window of 1500 kb with a gap less than 1000 kb between adjacent regions, with density of SNP coverage within the region no more than 1 SNP per 50 kb, and with no more than five missing calls and one heterozygote per window  49, 50. As total length of RoH segments varied substantially among individuals, we first took natural logarithm of these values for each individual and then calculated the mean for each population sample. We also calculated mean number of RoH segments for each population sample. F ST. Mean population pairwise F ST were calculated for BLT and a range of Eurasian populations (Supplementary Table  14 ) as in  51. PCA. PC analysis was performed using smartpca software implemented in EIGENSOFT package  15. Populations used in the analysis are listed in Supplementary Table  14.
Analysis of segments identical by descent (IBD). Refined IBD algorithm implemented in BEAGLE v4. 0  21, 22  was used to detect IBD segments shared by BLT and their host population (Belarusians) with a set of Eurasian populations. Sample sizes for all populations were balanced: ~ 5-6 individuals per each population (Supplementary Table  14 ). Refined IBD was run with the default settings except the ibdtrim parameter, which was reduced to 20 markers because of lower marker density in our dataset. IBD segments longer than 1 centiMorgan (cM) were analyzed. Two parameters that characterize IBD sharing were estimated. (i) An average number of IBD segments per pair of individuals for each BLT-[population] and Belarusians-[population] pair. (ii) An average total length of genome shared identical-by-descent per pair of individuals for the same BLT-[population] and Belarusians-[population] combinations.
95% CI for the average number of IBD segments were calculated as in  53  , while CIs for the average total length of genome shared identical-by-descent were calculated using the bootstrap percentile method with 10000 replicates. fineSTRUCTURE, GLOBETROTTER. SHAPEIT v2. r790 was used to phase autosomal SNP data  54. SNPs in phased haplotypes were subsequently imputed with IMPUTE2 software  55  using 1000 Genomes Project sequence data as a reference. Genetic maps were taken from the same 1000 Genomes download with physical positions in NCBI b37 coordinates. All SNPs in the data, which were absent in the reference panel, were excluded. The "chromosome painting" was performed using the ChromoPainter v2  18, 19. Prior to the main ChromoPainter analysis, we have analyzed a subset of the data with 10 EM iterations to calculate the recombination scaling constant (Ne) and mutation probabilities.
ALDER. ALDER Uniparental markers analyses. Y-STR phylogenetic networks were constructed using the Network software version 4. 6. 1. 2, applying the median-joining algorithm  57  (Fluxus Technology Ltd, http://fluxustechnology. com) and drawn using Network Publisher. Weighting of Y-STR loci for each haplogroup was done as described in  58. Datasets of Y-STR haplotypes for each haplogroup were compiled individually so that populations included maximally represent the phylogeographic pattern of a respective haplogroup. The final number of Y-STR loci used for network analyses for each haplogroup depended on the STR sets available in the literature (Supplementary Table  S4 ). For better visualization, minimal networks including only haplotypes no more than three or in some cases two mutation steps from BLT were built and shown in the figures alongside with the complete networks.
Acknowledgements We thank all volunteers, who took part in this study and made it possible, and especially  Rozalia Tufkreo  and  Abu-Bekir Shabanovich  for their assistance in sampling. We express our gratitude to  Yuldash Yusupov ,  Timur Ayupov ,  Zhaxylyk Sabitov  for ethnographic assistance. We thank  Jüri Parik ,  Tuuli Reisberg ,  Triinu Vetemäe  and  Merle Vetemäe  for assistance in DNA sequencing. Computational analyses were carried out at the  High Performance Computing Center, University of Tartu  and the  Core Computing Unit of the Estonian Biocentre. FA was supported by the subsidy allocated to the  Kazan Federal University  for the state assignment in the sphere of scientific activities, and with the work being performed according to the  Russian Government Program of Competitive Growth  of the  Kazan Federal University.
NMR spectroscopy Bruker Avance-300, Avance-400 and Avance-500 were used for solution NMR spectroscopic analysis. 1 H NMR DOSY measurements were performed at 500. 13 MHz with a 5 mm sequence using bipolar gradients. DOSY spectra were generated with the DOSY module of NMRNotebook™ software, through maximum entropy and inverse Laplace transform calculations. 1 H NMR DOSY measurements were performed at 500. 13 MHz with a 5 mm 1 H/X z-gradient BBI probe and by applying a PFGSTE pulse sequence using bipolar gradients. The solutions were analysed using a NMR microtube. The viscosity of CD 2 Cl 2 at 298 K was determined according ref. 5 (see the ESI †). Mass spectrometry was performed at the Service Commun d'Analyses, Université de Strasbourg (France). The electrospray analyses were performed on Micro-TOF (Bruker) apparatus equipped with an electrospray (ES) source.
Acknowledgements This work was done at  Université de Strasbourg  with public funds allocated by the  CNRS , the  French government  and by the  International Center for Frontier Research in Chemistry  (icFRC scholarship to G. K. ). We thank  Dr L. Barloy  for fruitful discussions. A. C. is grateful to the  HPC centre of the Université de Strasbourg  for computer resources. We thank  N. Kyritsakas  for X-ray structure resolution.
A, quantification and normalization of the SHAPE analysis obtained by the QuSHAPE software. The 302 nucleotides long sequence of VEGF-D 5 0 UTR has been split into three graphs representing the 5 0 (graph I, top), graph II (middle), and 3 0 (graph III, bottom) regions. B, autoradiograms of RNA enzymatic probing experiments followed by primer extension showing the localization of the enzymatic cleavages obtained with RNase V1 (V1), RNase T1 (T1), and RNase T2 (T2). (i) RNA, control RNA without enzymes; (ii) V1, T1 and T2: three different increasing concentrations of the three RNAses; (iii) RNA sequencing ladders were run in parallel (U,C,G,A lanes on each gel). C, putative secondary structure of the murine 5 0 UTR of VEGF-D mRNA. D, schematic representation of the BIACORE T200 analysis using surface plasmon resonance.
Acknowledgments We thank  J. J. Maoret  for his technical support and  Y. Barreira  from the platform  Anexplo Genotoul  ( Inserm US006, Toulouse, France ) for their outstanding technical assistance,  M. Khatib  from the imaging platform of I2MC for her scientific and technical support, and  A. Henras  ( LBME-CNRS UMR 5100, Toulouse, France ) for his scientific and technical support in ribosome profiling. We thank  Dr. P. Romby  ( IBMC-CNRS ) and  D. Arvanitis  for their scientific support.
Methods All patients on HD at our institution in January 2010 were screened for eligibility using the following exclusion criteria: dialysis vintage <6 months and previous surgical parathyroidectomy (PTX). Patients meeting our eligibility criteria were enrolled into the study and observed for a period of 60 months. The study was conducted in compliance with the Declaration of Helsinki, and all patients provided their signed consent to have their data entered in a database for analysis. The pre-dialysis, mid-week, serum PTH level was sampled every month. For analysis, patients were classified by the presence or absence of an event of significant decrease in serum PTH level over the first 36 months of the study. A significant decrease in serum PTH level was defined as a decrease of more than 50 % between two measurement periods within an interval of less than 3 months, with the mean of two successive PTH values used to calculate the change in PTH (Fig.
High PTH-related morbidity and mortality In a recent metaanalysis of HD patients, Natoli et al. reported that only a high serum PTH level was associated with mortality  [27]. Using the Fresenius US database, Block et al. reported an increased rate of mortality only among patients with a serum PTH level >600 pg/mL in an adjusted model, whereas in an unadjusted model, only low PTH levels were associated with a higher rate of mortality  [11]. The same findings were confirmed for patients with CKD not on dialysis by Kovesdy et al. [7]  and Nakai et al. in Japan  [28]. The mechanism of PTH toxicity is poorly understood. However, an elevated calcium x phosphorus (Ca x P) product associated with tertiary HPT and a high serum PTH level, associated with high serum FGF-23level, have been associated with a risk for progression of cardiovascular calcification  [5, 29].
Results and discussion RECQ helicase gene expression levels were analyzed in different types of hematological malignancies and in their normal counterparts using Oncomine Cancer Microarray database  [22]  as indicated in Table  1. Abnormal expression of at least one RECQ helicase was identified in all analyzed hematological malignancies (Table  1 ). RECQ1 was found to be significantly overexpressed in mantle cell lymphoma (P = 0. 0025)  [23] , in unspecified peripheral T-cell lymphoma (P = 0. 0038)  [24] , anaplastic large lymphoma (P = 0. 0024)  [24]  and angioimmunoblastic large cell lymphoma (P = 0. 001)  [24]  (Fig. 1a ). WRN is significantly overexpressed in primary effusion lymphoma compared to normal B cells (p = 0. 003)  [23]  (Fig. 1a ). RECQ4 expression was increased in Burkitt Lymphoma (P = 0.
001)  [23, 25] , in diffuse large B cell lymphoma (P = 0. 004)  [23]  and also in primary effusion lymphoma (P = 0. 005)  [23]  compared to normal counterpart (Fig. 1a ). RECQ5 is significantly overexpressed in acute myeloid leukemia (P = 0,001)  [26]  (Fig. 1a ). Comparing RECQ helicases expression between normal plasma cells (BMPC), premalignant cells from MGUS patients and multiple myeloma cells (MMC)  [27] , BLM and WRN were found to be significantly downregulated in MMC compared to normal BMPC (P = 0. 002 and P = Table  1  RECQ family member expression in hematological malignancies compared to that of their normal tissue counterparts using publicly available gene expression data, including the Oncomine Cancer Microarray and Genomicscape databases 0. 001 respectively) (Fig. 1b ). A decreased expression of BLM was also observed in MGUS compared to BMPC (P = 0.
01). RECQ1 and RECQ4 are overexpressed in MGUS (P = 0. 006 and P = 0. 002) and MMC (P < 0. 0001 and P = 0. 0009) compared to BMPC. Furthermore, a significant increased expression of RECQ1 in MMC compared to MGUS was identified (Fig. 1b ). Furthermore, using the human protein atlas database  [28] [29] [30] , the expression of RECQ1, RECQ4 and RECQ5 could be confirmed at protein level in myeloid and lymphoid cancer cell lines (Additional file 1: Figure  S1 ). We investigated whether RECQ helicases expression could be associated with tumor progression and prognosis in hematological malignancies (Table  2 ). In AML patients with abnormal karyotype (Verhaak cohort, N = 521 patients)  [31] , a high expression of BLM and RECQ4 is associated with a better overall survival (OS) (P = 0. 01 and P = 0.
RECQ5 increased expression was recently reported in JAK2V617F myeloproliferative neoplasms  [33]. RECQ5 depletion in JAK2V617Fmutant cells impairs replication after hydroxyurea treatment leading to a significant increased doublestranded breaks and apoptosis  [33]. RECQ5 represents a potent regulator of genome stability in myeloproliferative neoplasms in association with drug resistance a b Fig. 1  Increased RECQ helicase gene expression in hematological malignancies compared to normal counterparts using Oncomine database (a) and Genomicscape database (b). Data sets in a given panel were from the same study. GEP data are log transformed (Oncomine) or not (Genomicscape) and normalized as previously described  [64]  [33]. RECQ5 overexpression could also be involved in AML pathophysiology and chemoresistance.
Methods Databases: We used Oncomine Cancer Microarray database (http://www. oncomine. org) [22]  and Genomicscape (http://genomicscape. com/)  [63]  to study gene expression of RECQ family members in nine different human hematological malignancies and their normal tissue counterpart as indicated in Table  1. To compare the gene expression of a tumor type to its normal counterpart, we used gene expression data from a same study with the same methodology. All data were log transformed, median centered per array, and the standard deviation was normalized to one per array  [22]. Statistical comparisons were done with Mann-Whitney or Student t-test as previously published  [64]. Prognosis values of each member of RECQ family in hematological malignancies were determined by using Maxstat R package based on publicly available data (Gene Expression Omnibus (http://www.
Acknowledgements This work was supported by grants from  French INCA (Institut National du Cancer) Institute  ( 2012-109/087437 ),  Languedoc Roussillon CRLR  ( R14026FF ),  Fondation de France  ( 201400047510 ),  ITMO Cancer (MM&TT)  and  AXLR SATT EV  is supported by a grant from  Guillaume Espoir association (Saint-Genis-Laval, France).
Defining household and individual characteristics Data concerning sorghum seed acquisitions were gathered during the 2011-2012 cropping season. Fifteen of the village's 183 households were chosen to represent a three-level gradient of socioeconomic status (Table  1 ). Based on the local conceptions of wealth, household socioeconomic status was divided into three socioeconomic strata: poor, intermediate, and wealthy. Household inclusion in any one stratum was determined by four variables: estimated size of cattle herd, number of spouses, household members' average cropped sorghum area, and possession of an ox-plough or other animal-driven tools. All the active members of the surveyed households were interviewed, bringing the total number of informants to 70. The interviewing of an equivalent number of households in each socioeconomic stratum combined with the generally greater number of farmers in wealthy households led to an overrepresentation of farmers from the richest households in our sample compared to the entire population (Table  1 ).
Collection and characterization of seed circulation data Data concerning seed acquisition events were gathered through a standardized protocol that aimed to collect information on the type of acquired landrace and the nature of the relationship between provider and recipient. For each informant, the inventory of all landraces grown during the 2011-2012 cropping season was established. Subsequently, informants were asked to mention, for each landrace, its most recent external source (e. g. , other than own seed production) and the number of years since the event occurred. Informants were not asked to mention people to whom they had given seeds because we rapidly realized that they were much more forgetful and less accurate for these events. Market seed sources, for which an individual provider of seed was not identifiable, were distinguished from all other sources.
For each other seed acquisition event, the provider's geographical location was recorded, and the relationship between recipient and provider was documented. Three categories of seed source were established according to the residence of the seed provider: within household, within village, and outside village. Kinship relationships between provider and recipient were described with precision and cross-referenced with a genealogical data set (containing 2546 individuals) that we had gathered through our ethnographic fieldwork in the village. All of the recorded kin relationships were grouped into three categories: spouse (husband and wife relationships), paternal or maternal kin (all bloodrelated parents), and in-laws (any relationship established through one or several marriages, except spouse).
Thus, we conducted independence tests between variables concerning node and edge attributes. However, the results of independence tests should be interpreted with caution because, by definition, relational data observations are not completely independent. Pearson's chisquare tests were used preferentially. When the minimum expected value of any cell within a tested frequency distribution of events was < 5, Fisher's exact tests for count data were used. Analyses were carried out using the "stats" package (version 3. 0. 2), and network representations were performed using the "igraph" package (version 0. 6. 6; Csardi and Nepusz 2006), both using R (version 3. 1. 2; R Core Team 2014). Statistical significance was set at α = 0. 05. Our goals for SNA were twofold. First, we wished to understand the biases that may arise when considering households rather than individual farmers as the network nodes.
Acknowledgments: We gratefully acknowledge the  French Fondation pour la Recherche sur la Biodiversité  (FRB) that made possible NetSeed, an international collaboration of researchers studying farmer seed networks. Mathieu Thomas  was provided with six months of postdoctoral funding within this program. The  Centre de Synthèse et d'Analyse sur la Biodiversité (CESAB)  provided essential logistical support for regular workshops on the subject, which enabled us to develop and mature both the theoretical and methodological aspects of our research. Additional support of the ongoing research collaboration through the MIRES and MADRES networks was provided by the following agencies: the  Réseau National des Systèmes Complexes (RNSC) , the  Institut National de la Recherche Agronomique (INRA) , and the  Centre National de la Recherche Scientifique (CNRS).
A&A proofs: manuscript no. paper_fin dual band imaging (respectively centered at 1. 59 and 1. 67 µm,  Vigan et al. 2010)  with the IRDIS camera  (Dohlen et al. 2008 ), and at YJ (0. 95--1. 35 µm, spectral resolution R ≃ 54) with the Integral Field Spectrometer (IFS)  (Claudi et al. 2008). Note that these observations are unpolarized. In July, additional data were recorded in dual band imaging at K1K2 (centered at 2. 11 and 2. 25 µm) with IRDIS, and at YH (0. 95--1. 65 µm, R ≃ 33) with IFS. In all these observations, we used an apodized Lyot coronagraph including a 185 mas focal mask (SPHERE mask N_ALC_YJH_S) as well as a pupil mask. IRDIS provides a ≃ 12 ′′ ×12 ′′ field of view (FoV) (1100×1100 au, given the star's distance 92. 1 +6. 5 -5. 7 pc; van Leeuwen 2007), with a ≃ 12. 2 mas/pixel scale.
An IFS dataset consists of 21000 spectra spread over 5. 1×41 pixels on the detector. After extraction, the FoV is 1. 7 ′′ ×1. 7 ′′ and the spaxel size is 7. 4×7. 4 mas, i. e. 0. 68× 0. 68 au. The coronagraphic observations were performed keeping the pupil stabilized so as to perform Angular Differential Imaging (ADI) post-processing  (Marois et al. 2006). This allows the suppression of a large fraction of the residual starlight after the coronagraph. The FoV rotations for the different sets of data are provided in Table  1. Our observing sequence was as follows: 1/ Point Spread Function (PSF) imaging, with HD 106906AB offset from the mask, so as to record a PSF and a relative photometric calibration, 2/ Image of the star behind the mask, with four satellite footprints of the PSF that can be used for fine monitoring of the centering, 3/ Coronagraphic sequence, 4/ Image of the star behind the mask, with four satellite footprints again, 5/ PSF imaging, and 6/ Sky observations, with DITs corresponding to the DITs of the coronagraphic sequence.