dataesr/scientific-paragraphs-categorization huggingface dataset:
Pan-European environmental sustainability indicator database To estimate the environmental impact of the diets, we developed the SHARP Indicators Database (SHARP-ID). This database contains GHGE and LU as indicators of the environmental impact and can be extended to other indicators. These two indicators relate to at least four of the planetary boundaries identified by  Rockstr€ om et al. (2009) , i. e. biodiversity loss, nitrogen cycle disruption, carbon cycle disruption, and land use change, as discussed by  Aiking (2014). Environmental impact was assessed using attributional LCA, an internationally accepted standardised methodology in accordance with ISO14040 and 14044:2006, with the aim to gain insight into the environmental impact of foods within the current food production practices  (Ekvall et al.
, 2016). To construct the database, we identified a total of 182 primary products relevant to the selected four European countries, using various publicly accessible data sources, e. g. : Agri-footprint (Europe)  (BlonkConsultants, 2015a (BlonkConsultants, , 2015b)) , Ecoinvent (Global, Swiss Confederation)  (Weidema et al. , 2013) , and primary production reports  (Marinussen et al. , 2012a; 2012b , 2012c , 2012d; Van Zeist et al. , 2012a; 2012b , 2012c , 2012d) , combined with European production, trade and transport data  (FAOstat, BACI World Trade Database, and GTAP). Starting from these 182 primary products, estimates were obtained for GHGE and LU for 944 FoodEx2 codes in the diet surveys covering 95% of the energy intake; for 134 FoodEx2 codes no estimate was obtained; these codes were herbs and spices, other ingredients, such as food additives, vitamin supplements, condiments, etc.
GHGE and LU of products derived from milk, such as cream, cheese and butter, were estimated by their mass fractions using the technical conversion factors of the FAO  (FAO, 1996) , and those of processed foods by their ingredient composition using recipes from the Dutch food composition table  (NEVO Stichting, 2016). GHGE and LU data were adjusted to reflect the foods as eaten to be comparable with the national dietary survey data by using appropriate conversion factors for edible portion, cooking losses and gains, and food losses and waste  (Bognar, 2002; Hoge Gezondheidsraad, 2005). For each FoodEx2-code, total GHGE per kg of food as eaten was calculated by multiplying the life cycle inventory data by appropriate conversions factors to reflect amount as consumed, i. e. conversion factors for production, edible portion, cooking losses and gains during preparation, and food losses and waste at production and consumption phase, and then adding impacts from packaging, transport and home preparation, and total LU per kg of food as eaten by multiplying the life cycle inventory data by appropriate conversions factors.
Demographics Data were collected on age (years), gender, educational level (low: primary or lower secondary degree; intermediate: higher secondary degree; and high: university or post-university degree), body weight (kg) and height (m) by means of questionnaires. Age was categorised in three categories (18e34 years, 35e49 years and 50e64 years), and overweight was defined as Body Mass Index (BMI) ! 25 kg/m 2 , calculated as body weight (kg) divided by height squared (m 2 ). In statistical analyses, subjects with missing data for educational level (n ¼ 134) and/or overweight status (n ¼ 56) were excluded, leaving 7806 adults for analysis.
To assess the strength of associations, fixed and, if applicable, random effects for the explanatory variables were represented by the regression coefficients with 95% confidence intervals (CI); all parameters were tested using Wald tests and a two-sided P-value below 0. 05 was considered as statistically significant. Model fit was examined by Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). All statistical analyses were performed using SAS version 9. 3 (SAS Institute Inc. ).
Conclusion In conclusion, observed variation in daily footprints of consumers' diets was mainly explained by the amount of energy consumed, which suggests that fighting obesity and reducing environmental footprints could go hand in hand. Once energy intake was accounted for, of our set of demographics, only country explained variation in footprints, which could not be unravelled into characteristics of the national food supply chains due to limitations of our standardised database of GHGE and LU values. Contributions of food groups to footprints however varied between countries, suggesting that the national food system is a likely determinant of dietary choices of consumers. Once country and reported energy intake were accounted for, total meat e especially ruminant meat e, explained most of the variation in environmental footprints, while variation by other animal-sourced foods, such as fish, dairy products and animal fats, were less prominent.
Acknowledgements This work was supported by the  European Union 's  H2020 Programme  under Grant Agreement number  633692  (SUSFANS: Metrics, models and foresight for European sustainable food and nutrition security); and  TiFN  under Project Agreement number  15SD01  ( SHARP-BASIC ). A. Kuijsten ,  G. Kaptijn  and  J. M. Geleijnse  received research funding from  TiFN  (grant  15SD01_SHARP ) and  A. Kuijsten  received funding from  Top sector Agri&Food & Alpro  (grant  AF-16507 ) for research on healthy and sustainable diets.
Population and data collection The French GP Sentinelles network (http://www. sentiweb. fr) is a real-time epidemiologic surveillance system inaugurated in 1984 based on about 1300 volunteer GPs (approximately 2% of all French GPs), located throughout metropolitan France  [18]. Differences between Sentinelles GPs and all French GPs have been reported elsewhere  [19]. During the study period, the mean turnover (the proportion of new reporting GPs) was 21% per year (range: 10 -36%). The catchment area was 1 GP per 55,115 persons. GPs reported weekly the number of male urethritis cases seen in consultation throughout the year. A case is defined by the presence of recent dysuria and/or purulent/mucoid urethral discharge in men. Cases reported between 2007 and 2017 were included in the study. For each case, descriptive data were collected:.
The major strength of our study is its use of the same clinical case definition for male urethritis over the study period, which allows for comparisons over time. Moreover, syndromic surveillance may not be affected by changes in testing policies and improvement in diagnostic tools. However, our clinical definition did not include data on inflammatory reaction in urethra (no biological confirmation needed). And this surveillance is blinded concerning asymptomatic NG or CT infections or other infections such as HIV or syphilis. For male urethritis cases included in the study, data collected on Mycoplasma genitalium do not allow to present analysis. This is a limitation according to the significant proportion of male urethritis cases caused by this pathogen. Other limitations are the absence of syndromic surveillance for women.
Patients and tissue samples Tumour samples were selected from the Montpellier Cancer Institute (ICM) biological resource centre. Pathological data including hormone-receptor status, HER2 status, histological type, grade and pTNM were recorded. Clinical data (e. g. , age, type of treatment, occurrence and type of relapse) were obtained by review of the medical files. The selected population included patients with non-metastatic TNBC who underwent mastectomy or breast-conservative surgery with negative margins, without previous history of cancer. In total, 51 patients with TNBC treated between 2004 and 2008 were included in this retrospective study. These patients did not receive neoadjuvant treatment, and were treated by postoperative radiotherapy or by radiotherapy with standard chemotherapy (anthracyclines and/or taxanes).
Statistical analysis Continuous variables were described as medians and range, and categorical variables as frequencies and percentages. A non-parametric test for trend was performed to test the TR-FRET expression increase across the three ordered groups of expression determined by IHC (weak/negative, moderate, and high for HER1 and HER3; 0, 1+, and 2+ for HER2). Relapse-free survival (RFS) was defined as the time from the date of surgery to the date of last contact or recurrence (local, regional, or distant), and estimated using the Kaplan Meier method. Univariate and multivariate analyses were performed using a Cox proportional hazard model. Hazard ratios (HR) were given with their 95% confidence interval (95% CI). All statistical analyses were performed with the STATA 13. 0 software (StatCorp, College Station, TX).
Following previous efforts to render the Conformational Space (CS) of flexible compounds by Generative Topographic Mapping (GTM), this polyvalent mapping technique is here adapted to the docking problem. Contact fingerprints (CF) characterize ligands from the perspective of the binding site by monitoring protein atoms that are "touched" by those of the ligand. A "Contact" (CF) map was built by GTM-driven dimensionality reduction of the CF vector space. Alternatively, a "Hybrid" (Hy) map used a composite descriptor of CFs concatenated with ligand fragment descriptors. These maps indirectly represent the active site and integrate the binding information of multiple ligands. The concept is illustrated by a docking study into the ATP-binding site of CDK2, using the S4MPLE program to generate thousands of poses for each ligand.
Therefore, these fragment counts were used as source of ligand-specific information in Hy vectors. Hy vectors of ligand poses consist of the above-mentioned CF vector defining the pose concatenated to the (geometry-independent) ISIDA fragment count defining the ligand. Therefore, unlike in CF space, two distinct ligands establishing contacts of similar nature with the same site anchor atoms will nevertheless map to distinct areas of Hy space, depending on their intrinsic structural dissimilarity. The specific fragmentation scheme yielding best results in this context was fine-tuned as described in Methods. Cyclin-dependent Kinase 2 (CDK2, e. g. , P24941 by Uniprot Accession ID) has been selected for this study, given the richness of co-crystallized diverse binders of the ATP site in the Protein Data Bank  [11] , as well as the richness of inhibitors with measured thermodynamic instability constants, reported in the ChEMBL database.
By highlighting in yellow all the ligands for which the most stable pose is native-like (RMSD < 2Å with respect to the PDB structure), it can be seen that difficulty to reproducibly descend to the bottom of the docking energy landscape (more than 10 simulations needed) is the hallmark of ligands in which this hard-to-reach absolute energy minimum eventually reveals itself as not native-like. There are two exceptions to this ad-hoc "rule": already mentioned 1Y91 and analogous 3NS9 (based on the same isopropyl-substituted heterocyclic scaffold). These two compounds have rugged, difficult-to-sample but well-behaved energy landscapes (energy minimum is the native-like pose). Figure  6. Simulation repeats required to reproducibly achieve best energy level, versus IRI index. On Y, the number of evolutionary simulations (limited to 20) performed by the S4MPLE docking script for each ligand in its attempt to reproduce at least five times a docking energy level within 1 kcal/mol from the known absolute optimum represents the facility to achieve convergence in terms of energy values.
Compound Curation All the PDB structures associated to the Uniprot code P24941 were downloaded from PDB and aligned in the PyMol interface (v. 1. 9. 0. 0, Open-Source). Using the 1CKP ligand as center, a sphere of residues within 12 Å was defined, external atoms being deleted. PDB structures with no ligand in the selected ATP site were discarded. The active site to be used in docking was taken from the 1CKP protein structure (hydrogens were added and ionizable side chains set to charged status, using the MOE [18] tool). As required for S4MPLE docking, a series of five site "hot spots" was specified-atoms used as references for the randomized initial placement of the ligand in the site, but with no special status in docking energy evaluation. These included the carbonyl and >NH of Leu83 participating in the "iconic" pair of hydrogen bonds characteristic for kinase ligand binding, but also the Cβ of Phe80 and the carbonyls of Glu81 and Phe160.
However, poses with RMSD values above 6. 0 Å were all assigned a maximum value of 6. 0-in order to allow the model to focus on the relevant RMSD range (discriminating between "badly docked" at 6>RMSD > 2 and "quasi-undocked" poses at RMSD > 6 is both irrelevant and very easy to achieve, as the latter have near-empty contact fingerprints). For each property, associated landscapes on the manifold constructed according to current GTM parameters were iteratively built on randomized 2/3 of the pose pool and challenged to predict the left-out 1/3 of poses. This three-fold cross-validation was repeated three times, returning associated cross-validated determination coefficients Q 2. Map fitness was estimated as the mean of these Q 2 values, minus one standard deviation. Hy map fitting followed the same procedure, with two important modifications: (1) Frame and selection data were taken from the merged "diverse" conformer pools of 42 randomly selected ligands.
The PDBligs. dat file in the Supplementary Material has these "training" ligands labeled "yes" in the third column of the file, by contrast to the 42 others left out for validation purposes (columns 1 and 2 report SMILES and source PDB entry, respectively). (  2 ) Descriptor space selection is now enabled in the evolutionary map builder, as one hundred different Hy descriptor spaces were considered. These are concatenations of CF descriptors with either of one hundred types of different ISIDA fragment descriptors. These 100 ISIDA fragmentation schemes are the default options used as pool of meaningful descriptor choices for solving various chemoinformatics problems in our group.
Selective Recognition of Actives (Virtual Screening) As the ultimate goal of docking calculations is the prioritization of active compounds out of a database of structures, and the use of contact fingerprints is known to significantly enhance success rates compared to the default ranking by docking scores, it is straightforward to ask whether CF-based maps may also be effective ligand/decoy discriminators. This problem was investigated on hand of the above-mentioned collection of 292 compounds including (roughly) 1/3 of potent binders, 1/3 of weak binders and 1/3 of DUD decoys. The challenge is to obtain Receiver Operating Characteristic (ROC) curves of maximal Area Under Curve (AUC) when ranking compounds by various calculated scores and expecting actives to be top-ranked. Practically, two scenarios were considered:.
Acknowledgments The salary of AS was sponsored from the  European Respiratory Society -Marie Sklodowska Curie actions COFUND RESPIRE 2 fellowships  ( MCF-7077-2014 ) and also from a grant supported by  Lungenliga Schweiz  ( 2017_14 ). The work was supported by an unrestricted grant from  Chiesi Pharmaceuticals , institutional funding from the  Academic Medical Centre, Amsterdam UMC, University of Amsterdam  ( IA601011 ).
8 cm in diameter, located 11. 5 cm above the active hole, was used as nicotine (or saline) delivery-associated discrete visual cue, and is named thereafter ''cue light'' or ''cue. '' It produced 5 Lux. As well, in given experimental groups and experiments, a blue light (blue LED, Sloan Precision Optoelectronics, Switzerland), 1. 8 cm in diameter, located on the opposite wall at 17 cm of the floor on the left side, was used as, and is named thereafter, ''Ambient light'' and abbreviated AL. It produced 15 Lux at a wavelength of 470 nm, which is known to not affect vision in Sprague-Dawley rats in a similar exposure pattern as in our experimental approach  (Tosini et al. , 2016). LED intensities were both measured in the middle of the cage with a Lux-meter (Moineau Instruments, France). Experimental contingencies were controlled and data were collected with a PC-windows-compatible SK_AA software (Imetronic, France).
FUNDING This work was supported by  La Fondation pour la Recherche Médicale  (FRM; grant  DPA20140629795  to VD-G), by l' Agence Nationale de la Recherche  ( ANR ; grant  ANR-10-EQX-008-1 ,  EquipEx OptoPath  to VD-G), by the  Aquitaine Region Council  (grant 2015- 1R30105 , fellowship to VG-R), by l 'Institut National de la Santé et de la Recherche Médicale (INSERM)  and the  University of Bordeaux.
Introduction The fluid and white matter suppression sequence (FLAWS) provides two T1-weighted coregistered datasets: a white matter (WM) suppressed contrast (FLAWS1) and a cerebrospinal fluid (CSF) suppressed contrast (FLAWS2). FLAWS has the potential to improve the contrast of the subcortical brain regions that are important for Deep Brain Stimulation surgery planning. However, to date FLAWS has not been optimized for 1. 5T. In this study, the FLAWS sequence was optimized for use at 1. 5T. In addition, the contrastenhancement properties of FLAWS image combinations were investigated using two voxel-wise FLAWS combined images: the division (FLAWS-div) and the high contrast (FLAWS-hc) image.
Introduction The acquisition of magnetic resonance (MR) images with different contrasts (T1, T2, diffusion, …) is today a standard procedure in both research and clinical practice. Typically, images are acquired in separate measurements and then pre-processing steps -such as co-registration-are needed to spatially normalize the data before analysis. In this context, magnetic resonance imaging (MRI) sequences that provide, in a single acquisition, co-registered datasets with different contrasts are of interest to reduce the amount of data processing and to minimize loss of information due to interpolation and other possible confounding effects. The fluid and white matter suppression (FLAWS) sequence  [1] , derived from the magnetizationprepared two rapid gradient-echoes (MP2RAGE) sequence  [2] , was introduced to provide two co-registered T1-weighted images of the brain with different contrasts in a single acquisition.
Automated MRI segmentation has become available for different types of SVD changes. Brain volume, WMH and infarcts have received the most attention, while fewer methods have been presented to quantify lacunes and EPVS. This study aimed to find an optimal combination of the major SVD brain changes by using automated MRI quantification tools. We examined volumetric data of WMH, lacunes, infarcts and EPVS as well as regional brain volume to identify the measures with the strongest associations with cognitive decline. A combined continuous measure was constructed to represent the global burden of SVD brain changes and its predictive value was validated against long-term cognitive and functional outcome.
Participants and design The data was drawn from the Leukoaraiosis and Disability (LADIS) Study, a longitudinal multicenter collaboration investigating the role of age-related WMH in functional disability. 11 In total, 639 subjects were enrolled at 11 European centers. At baseline, the subjects were 65-84 years old and were classified to have mild to severe WMH on MRI according to the modified Fazekas scale. 11 They were free of dementia and independent or only minimally impaired in instrumental activities of daily living (IADL) as evaluated with the Lawton IADL scale (score 0-1/8). 12 The sample represented a mixed population of subjects with either a risk of SVD (at least mild WMH on MRI) or early SVD (more advanced imaging findings, but still independent in daily life). At baseline, the subjects underwent brain MRI and clinical assessments including a standard neurological examination, functional status evaluation and a neuropsychological examination.
In follow-up, the clinical and neuropsychological assessments were repeated annually over 3 years. The number of subjects with clinical evaluation was 639 at baseline, 582 at the 1 st , 554 at the 2 nd and 523 at the 3 rd follow-up visit. The number of subjects with neuropsychological assessment was 638, 569, 496, and 468, respectively. A prolonged follow-up over 7 years was carried out by telephone interviews collecting data from the proxy/informant with the IADL scale focusing on activities in the past 3 months. Conversion from functional independence into disability was defined as an increase of IADL score from 0-1 to ≥2. Of the initial 639 subjects, 94 subjects had died during follow-up. In total, data of outcome in terms of functional disability or death was available for 633 (99%) subjects.
Consequently, the imaging data were not optimal but represented the normal clinical variability in the image quality. As the LADIS sample was recruited based on age-related WMH, the number of cases with cortical infarcts was relatively small (in total 73 infarcts) and the training set for the CNN algorithm remained restricted. Cortical infarcts, as a frequent concomitant finding of SVD, showed only a modest predictive value on cognitive impairment, which could be expected given the subcortical predominance of SVD pathology. The selection of MRI features for the global SVD measure was based on the significance of associations between volumes and multiple longitudinal cognitive and functional outcomes. As the relationship of individual volumes varied between different outcomes, the selected components were given equal weight in the combined score.
To address this, a recent longitudinal cohort study, based on administrative claims data from two large databases in Japan (the Japan Medical Data Center  [JMDC]  and Medical Data Vision [MDV] databases) reported differences in the prescription patterns of hyperlipidemia drug classes according to the stage of treatment  [18]. Previously untreated (UT) patients were most likely to be prescribed single-agent moderate statins as first-line therapy, while previously treated (PT) patients were most likely to be prescribed combination regimens. While adherence rates were generally high (≥80% in most patient subgroups), persistence rates were low, with more than half of UT patients discontinuing treatment during the 12-month observation period. Following on from this 'real-world' investigation, the JMDC and MDV databases were interrogated further in a sub-study to explore differences in the prescribing patterns of, persistence with, and adherence to LLT at a class level specifically among patients with additional risk factors, i.
Study This study was a retrospective, longitudinal, observational, cohort analysis of medical insurance claims data for patients in clinical practice in Japan who were prescribed a new medication for hyperlipidemia between January 1, 2014 and December 31, 2015. Results for the entire patient cohort have been reported previously  [18]. Anonymized patient-level data were extracted from the JMDC and MDV administrative claims databases (Supplementary Methods). In accordance with the Ethical Guidelines for Epidemiological Research published by the Japanese Ministry of Health, Labor, and Welfare, ethics approval and informed consent were not required. The study complied with the International Society for Pharmacoepidemiology Guidelines for Good Pharmacoepidemiology Practices. All authors had full access to all data, and take responsibility for its integrity and the data analysis.