dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions Thus, by combining the information from the Kendrick, van Krevelen and DBE diagrams constructed with the HRMS data of a corn silk hydro-alcoholic extract, 104 molecules were highlighted and described. These compounds consist of 55 flavonoids and 13 organic acids; 29 are lipids and 7 are nitrogenous compounds. The molecular network obtained with the HRMS/MS data revealed 79 ions which grouped into 5 molecular families. For 24 molecules, experimental MS/MS spectra matched with those of the GNPS library that proposes compound identification. After verifying the proposals with the mass spectra, cross-referencing information from the literature and using the cluster association, 24 other compounds were identified. Thirty-two phenolic compounds were identified with a structural hypothesis.
Acknowledgments: We thank the SALSA platform for spectrometric and chromatographic analyses (HRMS). Authors thank the projects  CHemBio  ( FEDER-FSE 2014-2020-EX003677 ),  Valbiocosm  ( FEDER-FSE 2014-2020-EX003202 ),  Techsab  ( FEDER-FSE 2014-2020-EX011313 ), QUALICHIM ( APR-IA-PF 2021-00149467 ), the  RTR Motivhealth  ( 2019-00131403 ) and the  Labex  programs  SYNORG  ( ANR-11-LABX-0029 ) and  IRON  ( ANR-11-LABX-0018-01 ) for their financial support of  ICOA ,  UMR 7311 ,  University of Orléans ,  CNRS. We thank  Cyril COLAS  of the SALSA platform of ICOA and  Béatrice Rhino  for the corn silk. We also thank  Elizabeth Rowley-Jolivet  for English language editing of the text.
Acknowledgements Financial support by the  MCIU of Spain  ( PID2020-113512GB-I00  and  TED2021-130285B-I00 ) is acknowledged. R. R. thanks  Xunta de Galicia  for postdoctoral fellowship. R. N. acknowledges the partial support from the  Israeli Ministry for Science and Technology. The  European Commission Research Executive Agency  (Grant Agreement number:  859752 -HEL4CHIROLED -H2020-MSCA-ITN-2019 ) is thanked for financial support. We acknowledge the  Ministère de l'Education Nationale, de la Recherche et de la Technologie , the  Centre National de la Recherche Scientifique (CNRS).
As with other FXR agonists, dose-related pruritus was frequently observed. Clinicaltrials. gov registration: NCT02855164 Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases worldwide 1,2. Nonalcoholic steatohepatitis (NASH), the progressive subtype of NAFLD, is characterized by the presence of steatosis, lobular inflammation and hepatocyte ballooning, with or without hepatic fibrosis  3, 4. In the United States, the estimated prevalence of NASH in patients with NAFLD is ~25% (ref. 2 ), while in the general population it is estimated at 1. 5-6. 45% (ref. 1  ). NASH is a risk factor for progression toward advanced fibrosis and cirrhosis with subsequent risks for hepatocellular carcinoma, portal hypertension, end-stage liver disease and death  [5] [6] [7] [8].
Study design and treatments FLIGHT-FXR (NCT02855164) was a phase 2, randomized, double-blind, placebo-controlled, dose-finding study with an adaptive design consisting of three sequential parts (Parts A, B and C). The study was conducted between August 2016 and April 2020 at 84 centers in 17 countries (Argentina, Australia, Austria, Belgium, Canada, France, Germany, India, Italy, Japan, Republic of Korea, the Netherlands, Singapore, Slovakia, Spain, Taiwan and the United States). Study design and number of patients per treatment group are shown in Extended Data Fig. 1  and Table  1. In Part A, 77 patients were randomized (1:1:1:1:1) to receive placebo or tropifexor (10, 30,  The study protocol and all amendments were reviewed by the Independent Ethics Committee or Institutional Review Board for each center.
Randomization in Part B was also stratified by Japanese or non-Japanese origin to ensure all treatment groups were represented in the subset of Japanese patients. In Part C, randomization was stratified by fibrosis stage 2 or 3, presence or absence of T2DM, and by Japanese or non-Japanese origin. https://doi. org/10. 1038/s41591-022-02200-8 In this double-blind study, patients, investigator staff, persons performing the assessments, the Novartis clinical trial team and contract research organization (CRO) associates involved with continued direct study site conduct (or delegates) remained blinded to individual treatment allocation from the time of randomization until database lock for each study part (week 16 for Parts A and B and week 52 for Part C). Randomization data were kept strictly confidential until the time of unblinding and were not accessible by anyone involved in the study except for the PK bioanalyst.
The identity of treatments was concealed using study drugs that were all identical in packaging, labeling, schedule of administration, appearance, taste and odor. Additional placebo capsules were given in active treatment groups when needed to maintain blinding. During the first interim analysis (week 8, Part A), the database was locked after ≥90% of patients completed their week 8 assessments. A Novartis pharmacometrician not involved in the clinical conduct of the study and a CRO performing the statistical analysis were unblinded to the week 8 results; this facilitated data review by the DMC. During the second (week 16, Part A) and third interim analyses (week 16, Parts A + B), Novartis and CRO associates involved in data analysis and reporting were unblinded to data. For the week 12 interim analysis of Part C data, Novartis and CRO associates involved in data management, analysis and reporting, and Novartis management, were unblinded, while Novartis and CRO associates (including field associates) involved with continued direct study site conduct, site personnel and patients remained blinded.
Liver MRI scans were acquired at screening and at week 12 in Parts A and B, and at baseline and weeks 12, 24 and 48 in Part C. Week 12 assessment was not done if the participant prematurely discontinued treatment before week 8. All MRI scans were performed locally (on GE, Philips and Siemens at 1. 5 T and 3 T; and Hitachi at 1. 5 T, whichever was available) and were evaluated by the central MRI laboratory (Bio-Telemetry Research, Rochester, NY, USA), blinded to the investigator, participant and sponsor until after the completion of study or study part and database lock. In Part C, liver biopsies were obtained for all patients at baseline and week 48. Biopsies were stained using hematoxylin and eosin and Masson trichrome stains. Biopsy sections were evaluated by the central histopathologist to confirm eligibility before randomization.
Statistical analysis All participants who received at least one dose of study drug and had at least one postbaseline safety assessment were included in the safety analysis set for the assessment of safety variables. The full analysis set was defined as all participants to whom study treatment had been assigned at randomization and was used for summarizing demographic and baseline characteristics and assessment of efficacy variables. The end-of-study analysis was conducted on all participant data collected up to the end-of-study visit or the premature treatment discontinuation visit. Analyses were performed using SAS or R programming language. The primary variables were assessed using descriptive statistics (incidence of AEs and SAEs, overall and by preferred term) and baseline-adjusted mean estimates and pairwise differences with a 95% CI from a repeated measures (in the case of multiple assessments) analysis of covariance (ANCOVA) model (ALT, AST and relative change in % HFF).
All LS means are reported by treatment arm and interpretation of the comparison does not include the 95% CI (of the difference) or P value. ANCOVA models included the baseline assessment and treatment as covariates. Repeated measures ANCOVA also included time (visit) and interaction terms of time with baseline assessment and treatment. Baseline assessment, geographical region and BMI group (stratification factor) were included as covariates. Missing data for ALT and AST were accounted for by using repeated measures ANCOVA (mixed-effects model repeated measures; MMRM), assuming data were missing at random. In the case of dose reduction or treatment discontinuation, any ALT or AST assessments were set to 'missing' for all primary efficacy analyses. Missing data for % HFF were imputed using the baseline value for the week 12 analysis.
Acknowledgements We thank  M. Cines ,  G. Muller  and  P. Kearney  for their contributions in study monitoring and study management. We thank  N. Harris  ( Novartis Pharmaceuticals UK Ltd, London, UK ),  M. Shah  and  A. Meka  ( Novartis Healthcare Pvt Ltd, Hyderabad, India ) for providing medical writing support/editorial support, which was funded by  Novartis Pharma AG, Basel, Switzerland  in accordance with Good Publication Practice (GPP3) guidelines (http://www. ismpp. org/gpp3). The study funder ( Novartis Pharma AG, Basel, Switzerland ) had a role in study design, data collection, data analysis, data interpretation, writing of the manuscript and decision to submit for publication. A. J. S. holds stock options in Exhalenz, Durect,  Genfit, Hemoshear, Indalo, Rivus ,  Sanyal Bio  and Tiziana; has received paid consulting advisor fees from  Albireo, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Conatus, Covance, Eli Lilly, Genentech, Genfit, Gilead, Hemoshear, HistoIndex, Inventiva, Janssen Pharmaceuticals, Mallinckrodt Pharmaceuticals, Madrigal ,  Merck ,  NGM Bio ,  NorthSea ,  Novartis ,  Novo Nordisk ,  Path AI ,  Pfizer ,  Poxel ,  Prosciento ,  Regeneron ,  Roche ,  Salix ,  Sanofi ,  Siemens ,  Takeda , Terns and 89Bio; is a nonpaid consultant for  Amra, Biocellvia, Galectin, Fractyl, Immunron, Intercept and Perspectum ; provided consultant advice for  AstraZeneca , for which renumeration was paid to Virginia Commonwealth University; was a member of a Data and  Safety Monitoring Board  for a study funded by Sequana; has received research grants from  Boehringer Ingelheim ,  Bristol Myers Squibb, Conatus, Covance, Eli Lilly, Fractyl, Gilead, Inventiva, Madrigal, Mallinckrodt Pharmaceuticals ,  Merck ,  Novartis  and  Novo Nordisk ; has an ongoing research collaboration without direct funding with  Echosense-Sandhill, Owl ,  Second Genome  and Siemens; received study drug for the  National Institute on Alcohol Abuse and Alcoholism (NIAAA) trial of Imm124  for patients with alcoholic hepatitis from Immuron, without funding; and has received royalties from Elsevier and UpToDate.
Background Access to IVF/ICSI is facilitated when the financial barrier is removed. In a national context where in vitro fertilisation (IVF)/intracytoplasmic sperm Injection (ICSI) treatment is cost-free, how many women do not access IVF/ ICSI and what are the factors associated with non-access? Methods Using French national health insurance databases, the cohort included 20,240 women aged 18-43 years living in France who underwent unsuccessful treatment (no pregnancy) with clomiphene citrate (CC) and/or gonadotropins with treatment started between January and August 2016. The outcome measure was non-access to IVF/ICSI during the 24-month following start of infertility care. Factors associated with non-access to IVF/ICSI were explored using mixed effects logistic regression.
Data source and inclusion criteria In France, national health insurance covers 98% of the resident population. Its databases exhaustively record all individual drug reimbursements, medical devices, laboratory tests, medical procedures, private and public hospital stays and healthcare. They also provide some information on the patient: sex, age, commune of residence and registration with health insurance for lowincome patients. This data source has been described in detail elsewhere  [15]. Access to French health insurance databases is subject to strict national legislation and is granted only by a personal time-limited authorisation for a specific research project. Criteria of inclusion in the cohort study were being a woman living in mainland France, aged 18-43 years, having started CC and/or gonadotropin treatment between 1 January and 31 August 2016, and whose treatment was unsuccessful (i.
Outcomes and factors The outcome of interest was non-access to IVF and ICSI, measured as absence of IVF and ICSI during the 24-month follow-up. The woman's age was the age reached by the woman during the year that ovulation induction was started. Social disadvantage (yes/no) was assessed by registration with the health insurance for low-income patients. This indicates that the annual household income is below the poverty line (i. e. < 50% of median annual household income). A complementary social indicator was used measuring the level of deprivation in the patient's commune of residence, or residence deprivation index  [16]. This validated index combines four indicators measured at the level of the commune (local administrative unit) based on data from the 2013 French census (percentage of unemployed individuals, percentage of workers in the active population, percentage of individuals aged 15 and over with high-school graduation and median income per household).
Statistical analysis The risk of non-access to IVF/ICSI was analysed using bivariate and multivariable mixed effect logistic regressions to take into account some clustering in the data for the women's commune of residence  [17, 18]. We reported non-adjusted and adjusted odds ratios (OR), 95% confidence intervals (CI) and P values. All statistical analyses were performed using SAS Enterprise Guide software (version 4. 3, SAS Institute Inc. , Cary, NC, USA). The GLIMMIX procedure was used to estimate OR and 95% CI.
However, an Australian study concluded on an increased risk of nonaccess to IVF/ICSI in remote areas compared with major cities  [11]. This latter result may be explained by a very low population density in Australia and much longer distances to remote areas. Using French health insurance databases, access to assisted reproduction techniques was investigated for the first time in the general population by considering all national fertility centres. Unlike our study, previous work has investigated access to or pursuit of IVF/ICSI based only on patients recruited in specific fertility centres  [33, 37, 38]. Moreover, these earlier studies were not able to distinguish between non-access and treatment in another fertility centre  [39]. This study was limited by the lack of information on causes of infertility, duration of infertility or parity.
Acknowledgements We thank  Pierre-Louis Bithorel  ( Ined ) for his invaluable assistance in managing data from the complex French health insurance databases. We thank the  StimHo research team  for help and discussions through this work, especially  Elisabeth Morand ,  Arnaud Bringé ,  Elodie Baril ,  Marie-Laure Trudel. We thank  Florian Bayer  from the  Agence de Biomédecine  for sharing with us data on driving time from the commune of residence to the nearest  ART centre , for his help in updating these data and his rapid feedback that made our work easier. We thank  Nina Crowte  for professional assistance in language editing.
Sequencing and phylogenetic analysis Purified amplicons of partial hexon gene fragment were subjected to nucleotide sequencing by Sanger sequencing method using the BigDye Terminator v3. 1, Cycle Sequencing Kit (Thermo Fisher Scientific Inc. , U. S. A) according to the manufacturer's instructions. Sequencher software Version 5. 0 (Gene Codes Corporation, USA) was used to edit and assemble the raw sequence data. The sequences were aligned against reference human adenovirus hexon gene sequences from GenBank using Muscle offered in MEGA X software. The BLASTn program by National Center for Biotechnology Information, Bethesda, MD, USA was used to identify homologous nucleotide sequences in the GenBank database and to identify the genotypes of the isolates. The most related sequences based on their E-score from Genbank were used in the analysis.
Phylogenetic analysis and construction of phylogenetic trees was done using the neighbor-joining and Maximum-composite-likelihood methods offered in MEGA X. The reference sequences from GenBank used in the analysis were: HQ003817, JX423389, AB601020, AJ293901, EF486502, X74662, AY737797, AY737798, NC_003266, AB448767, EF121005, NC_001460, DQ149611, GU191019, AB330121, HM565136. The robustness of the phylogenetic trees was statistically evaluated by bootstrap analysis with 1000 replicates. The nucleotide sequences were compared phylogenetically using the General time reversible model with a Maximum-composite-likelihood and Neighbour joining method to infer the evolutionary history. The phylogenetic trees were edited using.
Availability of data and materials Sequences analyzed in this work can be found in the GeneBank under accession numbers and links: OP784948: https:// www. ncbi. nlm. nih. gov/ nucco re/ OP784 948. OP784949: https:// www. ncbi. nlm. nih. gov/ nucco re/ OP784 949. OP784950: https:// www. ncbi. nlm. nih. gov/ nucco re/ OP784 950.
For each sample in the dataset, the output neuron corresponding to the correct class spikes with a Poisson-distributed signal of high frequency, while the other output neurons are subject to a lower frequency activity (Fig. 5a ), i. e. , a soft one-hot encoding scheme. Correlated activity in between the 16 input and three output neurons is calculated on the entire training dataset by integrating over time the overlapping pulse duration. Heat map reveals that some nodes have higher correlations than others, see Supplementary information, Fig. 7. If we consider 16 input nodes equidistant from three output nodes, the cumulative effect of input/output signal correlation leads to gradual wiring in between nodes. This evolution over time is presented in Fig. 5b  and is consistent with ref. 36. The dendrites propagate, and create connections with a given initial synaptic strength (W init ).
From Fig. 5d , we evaluate that > 80% recognition accuracy can be achieved with as few as 13 plastic connections in case 2. Interestingly, case 1 reaches an 81% peak performance with 9 + 13 = 22 connections, showing that better connectivity matrices exist for this network configuration. We estimate the network accuracy on both the training and testing dataset in Fig. S13. The same maximum accuracy is observed on both datasets, thus ruling out the hypothesis of overfitting by increasing the number of connections. All cases of structural plasticity-backed networks demonstrate that activitydependent topologies can outperform random or full connectivity, with a strong benefit on the number of total connections required for this classification task. An additional benefit that can be evidenced from Fig.
Acknowledgements The authors wish to thank the  European Commission :  H2020-EU. 1. 1. ERC  project  IONOS  (#  GA 773228 ). I. B. acknowledges the support of the  Natural Sciences and Engineering Research Council of Canada (NSERC) , funding reference number  559730. The authors thank the  RENATECH network  and the engineers from  IEMN  for their support.
5a. Surface electromyography (EMG) signals were recorded from the arm with three different movements of the hand corresponding to rock, paper and scissor in ref. 34. The eight temporal analog signals from each sensor are converted into 16 spike trains following the methodology described in ref. 35. The objective is to classify into three classes (i. e. , rock, paper and scissor) the input spiking signals. The training dataset is composed of 300 multi-user samples and a testing set of 150 samples of the same users during a different session.
The concatenation of transversely summed pixels of all individual projections yields the Amsterdam Shroud image, which shows the oscillatory signal. This signal was used to split the CBCT projection data into 10 phases. Successively, the following steps are done to generate a midposition CT (midpCT) from the 4DCT: all phases are registered to a reference phase, for which we chose the maximum expiration phase due to the high reproducibility, yielding deformable vector fields (DVFs). The inverse of the mean motion vector, which is the average of all DVFs, is composed with each of the original DVFs, yielding new DVFs. Applying these new DVFs to their corresponding phase of the 4DCT and taking the median of the generated set of deformed 4DCT phases yields the midposition image. Using the DVFs from this midposition process, the 4DCBCT was reconstructed using MA-ROOSTER,  28  which is implemented in RTK.
Data analysis A comparison between the different modalities was conducted by analyzing difference images as well as mean error (ME) and mean absolute error (MAE) plots. For ME and MAE, the investigated contour was the union of the CBCT FOV with the CT body outline. In the following, when discussing phases of the 4DCT, 4DCBCT, 4DvCT, and 4DCBCT cor , we will use CT, CBCT, vCT, and CBCT cor and omit the 4D prefix. CT should not be confused with pCT. Proton doses were calculated (interplay effects were not considered and the full plan was calculated on each phase), so that a pairwise comparison of the dose calculated on generated images to the dose calculated on the CT (difference vCT-CT and CBCT cor -CT) as well as among the generated images (difference CBCT cor -vCT) could be determined for each phase.
For each subject, comprehensive skin physiological data collected through self-reporting and clinical assessment were also previously reported  22. Sequencing And Quality Control Genomic DNA was extracted from sampling swabs using the PowerSoil DNA isolation kit (MO BIO Laboratories, Carlsbad, CA, USA) following the manufacturer's instructions with minor modi cations  22. Library preparation and sequencing on an Ilumina NovaSeq platform to generate 150-bp paired-end reads were performed by SeqMatic LLC (Fremont, CA, USA) according to the manufacturer's instructions. We processed and sequenced 124 samples (Baoding n = 61, Dalian n = 63) and four negative controls (i. e. , new sterile swabs). The sequenced samples were selected across eight pollution exposure groups from weak to strong as previously described  13, 22  with 7 to 21 samples per group to obtain a balanced representation among exposure levels.
Two samples from Baoding did not yield su cient reads and were removed from downstream analysis. Sequence adapters were removed from the raw reads using AdapterRemoval (v2. 3. 1)  50 and quality ltering and human DNA read removal was performed using Kneaddata (v0. 7. 4) as previously described  22. Sequencing quality information for the samples is shown in Supplementary Table  6. Following species-level taxonomic classi cation of the reads using Bracken (v2. 6. 1)  51 , putative contaminants were identi ed with the R package "decontam" based on the prevalence mode with 0. 1 as the signi cance threshold  52. This method deemed 65 species to be contaminants (Supplementary Table  6 ) and reads that could be mapped to the representative genomes of the contaminant species (Supplementary Table  6 ) were removed an in-house script.
Diversity And Community Composition Analyses Taxonomic classi cation of the ltered and contaminant-free reads was performed using Bracken (v2. 6. 1)  53. The species-level taxonomy was used to identify host factors associated with community diversity and compositional changes. Based on the taxonomic data, prediction strength analysis to estimate the optimal number of clusters in the community was performed based on the "partitioning around medoids" discrete clustering method  53  using the "prediction. strength" command (with 100 random splits) in the R package "fpc" (v2. 2-9). The highest mean prediction strength was 0. 81 when k = 2, where k is the number of clusters. This result formed the basis for the presence of two cutotypes among all samples. FindFungi (v0. 23)  54  was used to assign taxonomy to the members of the fungal communities.