dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements. This study was partly funded by the  French Ministry in charge of Ecology. We thank the  SAFIRE joint laboratory  and the  CHARMEX program  for providing us all campaign measurements used in this study. We thank the  EEA  for maintaining and providing the AirBase database of pollutant surface concentrations over Europe. We thank the principal investigators and their staff for establishing and maintaining the AERONET sites used in this study:  Didier Tanré for Banizoumbou ,  Cabo Verde  and Dakar;  Bernadette Chatenet  and  Jean-Louis Rajot  for Zinder and Cinzana;  Daniela Meloni  and  Alcide Di Sarra  for Lampedusa. We acknowledge the  Service d'Observation PHOTONS/AERONET  and the AERONET-ACTRIS TNA supporting the AERONET activity in Europe. Analyses and visualizations used in this study for the MODIS satellite AOD maps were produced with the Giovanni online data system, developed and maintained by the  NASA GES DISC.
2011 ). There are concerns on the sustainability of the development of this area given the limited water resource, the climate variability and the limited size of the pepper market. Several models have been developed at the scale of the uppermost quaternary aquifer of the Lake Chad, as part of the PhD works of  Leblanc (2002) ,  Gaultier (2004) ,  Zairi (2008)  who took into account the variable climatic forcing and in  Boronina and Ramillien (2008)  who focused their work on evapotranspiration and on the infiltration budget. Candela et al. (2013)  aimed to provide a user friendly model for the water planners of this area. One common conclusion of these models is that the Yobe River and the Lake Chad constitute presently the main recharge zones for the aquifer. However the poor coverage of their dataset, both in time and space and the resulting poor spatial resolution of the models produce large uncertainties in the water budget in the Yobe -Lake Chad area.
Since 2005, thanks to a series of research projects additional data have been gathered in this area regarding (i) the changes of livelihood of local population since the African Drought and the development of irrigated agriculture (ANR/Biodivalloc ANR/Plantadiv and EC2CO/Repas projects), (ii) the structure and hydraulic properties of the quaternary aquifer, from exploration geophysics, direct sampling and piezometric data (IRD/Lake Chad, EC2CO/Repas, and ANR/Ghyraf programs). The KY will therefore be considered as an example case for assessing the water budget of a combined river aquifer system in the Sahelian area. A conceptual model focused on the KY is proposed, and then a numerical model with a hundred meter spatial resolution is built near the city of Diffa. The first part of the present paper is devoted to the surface water changes in the Yobe River and the Lake Chad since the 1970s.
Surface water The Komadugu Yobe River (KY) originates in the wet highlands of the Jos Plateau in Nigeria. It flows through several wetlands before its entry in Niger and then is meandering over nearly 150 km in the Kadzell plain before reaching the Lake Chad (Fig. 1 ). The Kadzell plain itself is believed to have constituted the bed of the Megalake Chad that covered nearly 350 000 km 2 during the African Humid period nearly 6000 years ago  (Leblanc et al. 2006 ). The KY is a non-steady river at the decadal to millennial timescale; significant changes in its course since 1950 are reported by Martinsson (  2010 ) and a fossil valley of the KY can be seen 40 km northward of the present one. The present valley is 1 to 5 km wide and characterized by numerous abandoned meanders. The main source of data for the hydrology of the KY is the "Direction de l'Hydraulique" located in Diffa and the SIEREM database  (Boyer et al.
2006). There are several gauging stations along the course of the KY in Niger (Tam, Bagara, Geskerou, Bosso) but Bagara, situated 5 km upstream Diffa is by far the most complete. The annual rainfall on its watershed was computed from both rain gauges and satellite data, with a weight shifting from rain gauges data before 2000 toward satellite data later on, using the method assessed for the whole Lake Chad hydrologic basin by  Bastola and Delclaux (2011). Rainfall (Fig. 2a ) exhibits the same rupture as the one noted in the West African Sahelian record by Le  Barbé et al. (2002)  and  Mahé and Paturel (2009) ; the 1970s and especially the 1980s are marked by severe droughts. However, there is almost complete recovery of rainfall since the 2000s, as noted by  Lebel and Ali (2009)  for the whole Eastern Sahel.
Water level The region of Diffa lies in the Northern Sahel area and therefore suffers from a 9-month dry season during which people not living near the KY have to rely on groundwater. Water levels were therefore measured early and piezometric maps are available since the 1960s, mainly as BRGM (the French Geological Survey) unpublished reports, which are summarized in  Greigert (1979). Further discussions on the properties of the quaternary aquifer and on piezometric maps can be found in  UNESCO (1972) ,  IWACO (1985) ,  Leduc-PNUD (1991) ,  Carter and Alkali (1996) ,  Leduc et al. (1998) ,  Boronina and Ramillien (2005) ,  Candela et al. (2013)  and in the unpublished theses of  Leblanc (2002) ,  Gaultier (2004), and Zairi (2008). The map included in Fig. 1  is redrawn after  Zairi (2008)  and includes a large set of new data on the southern rim of the KY in Nigeria.
This standard deviation is nearly 0. 9 m close to the river and is less than 0. 3 m at distances larger than 2 km. However, due to the lack of continuity in the data record, these data cannot be used for quantitative modeling. Moreover, a 4 year long dataset including near monthly measurements and dating back from 1994 was found for the Assaga well in Gaultier's thesis  (Gaultier 2004 ). The Assaga well is located 15 km downstream Bagara and 170 m away from the river axis. The Bagara elementary school well, nearly 800 m away from the river (Fig. 3 ) constitutes the most continuous record with some data back from 1995 (Fig. 5c ). Measurements are interrupted in 1997 and resume after 2005 with an offset of more than one meter. This could result from a change in reference level, since the well is cased with concrete rings constituting a nearly 1 m high edge.
These results seem reasonable with respect to the decrease of discharge commonly observed for the KY between Tam and Bosso. However the lack of continuous datasets at these hydrological stations does not allow to confirm the infiltration balance of the KY from discharge data. It should therefore be considered that these estimates suffer from a 60% uncertainty resulting from the uncertainty on the river coefficients themselves (see Online Resource 2). The annual abstraction by irrigation can be roughly estimated by considering a total irrigated surface of 6 000 ha, with an annual water need of 600 mm identical to that of sweet pepper  (Dorrendos and Kassam 1979). This would require an annual uptake of 36×10 6 m 3 /yr, which is still negligible with respect to the total discharge of the KY. However, this constitutes a significant part of the water infiltrated from the KY.
Conclusion The Northern Sahel area generally lacks any active permanent hydrological network and groundwater constitutes there a key resource for development. Sensitivity of this resource to climate and to anthropic disturbances should be assessed to foster sustainable development. The KY area may serve as an example case due to its recent population growth and agricultural development in the immediate border of the river. It is shown here that even with scarce data the water budget of the river and the aquifer can be estimated from numerical modeling of groundwater flow. The model relies on groundwater monitoring, mainly on a 1 yr period, at various distances of the river. It is strengthened by exploration geophysics data, namely by TDEM and MRS. It requires in addition that an approximate piezometric map is available at a larger scale for providing boundary conditions.
Their connection with the aquifer can be questioned given the importance of these ponds for irrigation after the flow season. Moreover recharge of the aquifer could be optimized with small dams. To further generalize the method applied here to the KY valley, we suggest that integrated water resource management in the Sahelian area should consider the role of temporary rivers, and should involve data gathering and analysis on their immediate surroundings. Aknowledgements : The research presented in this paper has been funded by the Ghyraf ANR project, the REPAS CNRS/INSU EC2CO project and the IRD LAC TCHAD project. Nathalie Rouché is thanked for her help with the SIEREM database, François Delclaux for kindly providing the rainfall data, Gilbert Ferhat for his help with the leveling, Mathieu le Coz for sharing his experience on the permeability of the KY aquifer, and the whole IRD team in Niamey for logistic support.
Results obtained with a one-layer model First simulations were aimed at assessing the sensitivity of our observations to the different model parameters. This led us to choose to invert the following parameters: the permeability and porosity of the aquifer (K and φ), river coefficients at the bottom of the river for each hydrological year, and an offset corresponding to the leveling error between P1-3 and the riverbed. The best fitting model (Fig. OR2. 1) was obtained with the Fmincon optimization function of Matlab and the rms of the difference between modeled and observed water level values at P2, P3, and Bagara as objective function. We have also verified that our results were not dependent on the optimization method by checking also least squares and thermal annealing with similar results.
Genetic diversity analysis Allelic numbers (Na), average observed (Ho) and expected (He) heterozygosities were calculated using the GENETIX 4. 05 software  [10]. Data were analyzed for possible departures from Hardy-Weinberg equilibrium by estimating the significance of the multilocus inbreeding coefficient (Fis) with 1,000 random allelic permutations of the original datasets. The genetic structure among the investigated populations was also evaluated by calculating pairwise Fst values with 1,000 random permutations. The significance level of P value for Fis and Fst was defined as the probability of obtaining absolute values higher than or equal to the observed one under the null hypothesis. The genetic relationships between multilocus genotypes of the six reared strains and the wild populations of M.
Acknowledgements The PhD thesis of  Mrs Nugraha  is jointly supported by the  French Ministry of Foreign Affairs and IRD. We are very grateful to  Mr. Christophe Cochet  who bred the rainbowfish, collected their offspring and ensured their welfare. Data presented in this work were partly produced through the technical facilities of the  labex "Centre Méditerranéen de l'Environnement et de la Biodiversité ". This is publication IRD-DIVA-ISEM-2015-155.
PERMUTATION TESTS While SPM software is relying mostly on RFT and parametric computations, FSL 9 software favors permutation tests, which can be applied to voxel maximum t-or z-value and cluster extent statistics. Permutation tests are elegant because they only require the assumption of exchangeability. However, the nature of the inference also depends on this assumption. If nothing else is known, the only conclusion based on a "significant" permutation test is that exchangeability is violated-that is, two groups are different. However, one cannot infer what the nature of the 8 The "threshold-free cluster enhancement" statistics (TFCE,  Smith and Nichols, 2009) , implemented in FSL, somehow overcomes this problem, by proposing a single statistic. It however requires deciding on two parameters, instead on only one (cluster defining threshold).
ACKNOWLEDGMENTS Research funded by  Agence Nationale de Recherche   ANR-11-BSH2-010. Special thanks to  Michel Dojat  for the many discussions during the long and often frustrating writing on the review on synesthesia, during which the ideas presented in this paper progressively emerged. I thank  Alexis Roche  for his expert comments on MRI statistics, and  Charlotte A. Chun  for both helpful comments and corrections on the English writing. I also thank both reviewers for their careful reading and valuable suggestions.
The current controller of the patent is Arthrogen. Arthrogen licensed the patent from the AMC/UVA. JFW and FM hold patents related to AAV gene therapy technology, but these patents are not related to the work presented in the current manuscript. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials. FM, JFW and PTT consulted for companies for projects unrelated to the present work. PPT became an employee and stakeholder of GlaxoSmithKline (GSK) after completion of this study; GSK is not involved in this work.
In order to be able to compare cytokine levels between cell lines, the levels of responses are presented in arbitrary units (AU, percentages). The actual levels (pg/ml) of each FLS cell line used are presented in the supplementary material (S1 and S2 Datasets). To further assess hIFN-β bioactivity a quantitative gene reporter bioassay was used. Human type 1 IFN sensitive cells respond to the presence bio-active hIFN-β by producing luciferase. Human IFN-β bioactivity assessed through the quantitative gene reporter bioassay showed that supernatant of transduced activated RA FLS showed a clear positive effect on bioluminescence intensity of type 1 IFN sensitive cells (Fig  2B ). Since it is known that the bioactivity of human IFN-β is highly species-specific  [4] , we also investigated the effect on cytokines in FLS from different species.
Besides in the intra-articularly injected right joint, high copy numbers were observed in draining lymph nodes and lung tissue. Intermediate numbers of vector copies were detected in spleen, kidney and blood, low numbers in liver, blood and brain. Levels in heart and testis were very low or below the detection limit of the assay. Data shown are mean + SD, graphs are shown with logarithmic scale. The 100 vg copies detection limit is depicted with a gray dashed line. N = 6 per group. GFP, green fluorescent protein; IA, intra-articular; IV, intravenous; week 1 or 4, number of weeks after vector administration; AA, adjuvant arthritis model.
European countries. Intakes of 23 nutrients were estimated from country-specific validated dietary questionnaires using the harmonized EPIC Nutrient DataBase. Four nutrient patterns, explaining 67 % of the total variance of nutrient intakes, were previously identified from principal component analysis. Body weight was measured at recruitment and self-reported 5 years later. The relationship between nutrient patterns and annual weight change was examined separately for men and women using linear mixed models with random effect according to center controlling for confounders.
Study population The EPIC study is an ongoing prospective cohort study across 23 centers in 10 European countries: Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom. The cohort of 521,448 men and women recruited from 1992 to 2000 (age range 25-70 year) was enrolled from the general population with exceptions for France (national health insurance scheme members), Utrecht and Florence (breast cancer screening participants), Oxford (health conscious, mainly vegetarian, volunteers), and some centers from Italy and Spain (blood donors). The rationale for EPIC, study design, and methods has been described in detail elsewhere  [16, 17]. For the present study, we excluded pregnant women, participants with missing dietary or lifestyle information, missing data on weight and height or with implausible anthropometric values at baseline (n = 23,713); those likely to mis-report energy intake according to Goldberg  [18]  (n = 85,356 under-reporters and 22,513 over-reporters); and individuals with cancer at any site other than nonmelanoma skin cancer, diabetes, or cardiovascular disease at baseline (n = 30,054).
Nutrient patterns We used the same set of already-available nutrient patterns in the EPIC study as identified, validated, and interpreted previously  [15]. Briefly, main nutrient patterns were derived with PCA on the covariance matrix of individual intakes of all the 23 nutrients available in the EPIC Nutrient Database  [23]. Nutrient intake data, as estimated from dietary questionnaires, from all EPIC centers (i. e. , EPIC-wide analysis) and both sexes were combined. This approach captured a good proportion of the variance explained in each EPIC center and lead to very similar patterns in men and women when PCA was conducted by sex  [15]. Independence of scale of the variances and co-variances was achieved by taking the natural log of the input variables. Nutrient densities-calculated as nutrient intake (amount/ day) divided by alcohol-free energy (kcal/day)-were used as input variables in order to capture variability of nutrient intakes independently from variation in energy intake.
Assessment of other covariates Data on physical activity (inactive, moderately inactive, moderately active, and active), smoking (never, former, and current), and education (primary school, technical school, secondary school, and university degree) were collected at baseline through questionnaires  [17]. Information on smoking status was also collected during follow-up at the same time as anthropometric data collection. Thus, we could account for smoking status modification during follow-up (stable current smoker, stable former smoker, stable never smoker, quit smoking, started smoking). Participants with missing values for physical activity (8 %), education (5 %), and change in smoking status (12 %) were classified as a separate category.
At the food level, most pronounced differences between subjects with high adherence to PC1 as compared to PC4 were much higher intakes of fruits and vegetables combined with much lower intakes of milk, and red and processed meats (Online Resource 2). Some caution is warranted with the interpretation of our findings for the following reasons. First, only selfreported weight at follow-up was available in most centers. To mitigate this potential source of bias, we used a prediction equation to improve self-reported weight estimates  [21]. Furthermore, in the EPIC Norfolk study, a subcohort of EPIC, a high correlation between self-reported and measured weight data has been shown (r = 0. 97 in men and r = 0. 98 in women), which means that ranking of participants according to self-reported weight was good  [33].
The latter has been shown to partly account for BMI-related dietary under-reporting  [36]. Fourth, we were limited by the number of nutrients available in the harmonized nutrient database (i. e. , 23 compounds) to derive patterns. Therefore, we could not separate sugars into for example, fructose or galactose, or protein into animal and plant proteins. Finally, as with all observational studies, residual confounding by other dietary or lifestyle factors and selection bias cannot be ruled out completely and may have influenced our results. We performed mixed linear models with center as random effect on the intercept, and where indicated by likelihood ratio tests, also on the slope Adjustments were made for age, BMI at recruitment, physical activity, education, change in smoking status, energy intake, time in years between the two body weight assessments, time in years-squared, time in years with knots at percentiles 25 and 75, and BMI with knots at 25 and 30 kg/m 2 , and mutually for each PC score P trend was tested by using a contrast in the coefficients corresponding to the levels of categorical predictors PC1-4 principal components 1-4  There was evidence for a moderate-to-high heterogeneity across study centers in women, but not in men.
Reconstruction of the interaction network of TILs and T-cell immunomodulatory molecules reveals candidates for immunotherapy A number of immunoinhibitory and immunostimulatory molecules are currently under investigation for immunotherapy in various cancers  [27]. In an attempt to identify promising candidates for CRC immunotherapy, we reconstructed a network of TILs and immunomodulatory molecules for which agonists/antagonists are available. The interaction network between TILs and these druggable targets was then filtered for molecules which were significantly associated with good or bad prognosis in the TCGA data set. The highly interconnected subpopulations of TILs were Tfh, B cells, immature DCs, Tgd, Tregs, and CD8+ cells (Figure  4A ). The molecules significantly associated with survival included PD-1 and PD-L2.
Discussion We have developed an integrated strategy and for the first time characterized the immunophenotypes and the antigenome of human CRC. Our approach to deeply mine large datasets enabled us not only to disentangle tumor-immune cell interactions, but also to devise strategies for cancer immunotherapy in CRC. The dissection of the complex tumor microenvironment suggests several important biological conclusions. First, the results support the notion that the subpopulations of TILs mirror the underlying molecular phenotypes. Moreover, based on the enrichment of TIL subpopulations, specific characterization of all three studied molecular phenotypes (mutational status, microsatellite status, methylation status) or the combinations thereof is possible. Hence, a single assay (RNA sequencing) enables refined molecular taxonomy of the tumors.
Identification of immune-related genes In order to build a compendium of immune genes related to specific immune cell subpopulations, we collected expression profiles for different immune cell types from 36 studies from the Gene Expression Omnibus  [48]  and Array Express  [49]. The list of datasets is provided in Table  S1  in Additional file 2. Additionally, we included expression profiles from normal mucosa  [50]  and CRC cell lines  [13, 51]  as out-groups. A total of 813 Affymetrix HG-U133A microarrays were then normalized using the frozen robust multiarray analysis (fRMA)  [52]. Transcripts with significant differential expression across cell subtypes were identified using ANOVA (P < 0. 05). For the remaining genes, we ranked median mRNA expression levels within each immune cell type from highest to lowest.
Genomic and clinical data TCGA Data Portal was queried for clinical information (n = 610), somatic mutations (n = 522), germline mutations (n = 468), methylation data (n = 582), SNP arrays (n = 573), and RNA-seq expression profiles (n = 598) of colon and rectum adenocarcinoma patients (last update July 2014). Raw sequencing data and alignments were downloaded from the Cancer Genomics Hub (cgHub) repository (September 2013). Details on data generation are available in the original study  [10]. A total of 222,169 somatic mutations were screened for potential mutated epitopes in 522 patients. The mutations were collected from TCGA portal (n = 386 in the original publication) and additional experimentally validated somatic mutations (n = 136) were used. The latter were lifted over from the hg18 to hg19 genome version prior to merging.
To select for germline mutations, all protected mutations were downloaded from TCGA portal. There were hg19-mapped mutations for 385 tumors, 86 of which were excluded, because only the somatic mutations were analyzed. Additional mutations located on the hg18 genome (n = 169) were lifted over to hg19 prior to merging, summing up to 468 patients. The normalized gene expression results analyzed according to the RNASeqV2 protocol were obtained from TCGA portal. Clinical data and microarray expression profiles for validation were collated from 11 studies (Gene Expression Omnibus accession numbers GSE12945, GSE41258, GSE14333, GSE17538, GSE29623, GSE33113, GSE39582, GSE24549, GSE24550, GSE30378, GSE28722).