dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical Analyses Statistical analyses of zootechnical performances were performed by Student's test (t-test) or Wilcoxon test, when data were nonparametric. Figure  1. Theoretical delivery curve of feed (g) in this study. Sows were fed using an automatic liquid feeding system following this theoretical delivery curve. This system adapts the feed delivery to each sow in order to avoid feed waste. Shapiro-Wilk normality test was performed to determine whether data were parametric or not. Statistical significance was considered at P < 0. 05. All statistical analyses concerning zootechnical performances were performed using GraphPad Prism 7 (GraphPad Software). The OTU table of abundance was analyzed by discriminant analysis using principal component  (Jombart et al. , 2010)  and blasted using the NCBI 16S ribosomal RNA sequences database.
Similarity between DNA samples from sows were monitored using Bray-Curtis dissimilarity. Statistical analysis of results from sequencing were performed using R software (R Development Core Team, 2008). The package "Biostrings" was used to import fasta files. Phyloseq used to rarefy data. Dunn. test package was used for multiple comparison and ape package was used for phylogenetic data exploration. Vegan and Adegenet packages were used for non-metric multidimensional scaling analysis. Ggplots2 package was used for general plot.
ACKNOWLEDGMENTS The authors thank the commercial farm for assistance with the experiment. The technical support from GetPlage is also gratefully acknowledged. Conflict of Interest: The authors (S. C. , M. E. A. B. , A. B. , M. F. , P. C. ) work within the research and development department of Nor-Feed SAS. Nor-Feed SAS commercializes a product called NOR-SPICE AB, which is Standardized Natural Citrus Extract. Data Availability: 16S rRNA data sets of the 21 discriminating Operational Taxonomic Units generated and analyzed in this study are available from the NCBI database, https://www. ncbi. nlm. nih. gov/bioproject/PRJNA531905/.
Confocal Laser Scanning Microscopy Biofilm observations were performed with a Zeiss LSM710 (Zeiss, Germany) using a 40× oil immersion objective. Bacteria were detected by monitoring the SYTO R 9 green fluorescence. This fluorochrome was excited at 488 nm and fluorescence emission was detected between 500 and 550 nm. Images were taken every micrometer throughout the whole biofilm depth. For visualization and processing of three-dimensional (3D) image data, the Zen 2. 1 software (Zeiss, Germany) was used. Quantitative analyses of image stacks were performed using the COMSTAT 2 software 2   (Heydorn et al. , 2000; Vorregaard, 2008). At least three image stacks from each of three independent experiments were used for each analysis.
Molecular Docking Molecular docking of the putative sensor VicK (WalK) with various ligands: Epi, NE, phentolamine, a reversible, nonselective α-adrenoceptor antagonist  (Clarke et al. , 2006; Laverty et al. , 2014) , and propranolol, a β-adrenoceptor antagonist  (Zhou et al. , 2011) , was performed by AutoDock 4. 2  (Morris et al. , 2009 ) that has been found as the most cited docking program in previous studies  (Sousa et al. , 2006; Chen, 2015). The structures of Epi (CID: 5816), NE (CID: 439260), phentolamine (CDI: 5775), and propranolol (CID: 4946) were downloaded from the PubChem database 8  in SDF format. The specified 3D structure of the ligands in SDF format were converted into PDB format using PyMOL 9. All the detailed steps of structure prediction, modeling, and molecular docking of VicK (WalK) are presented in a supplementary data organigram (Supplementary Figure  S1 ).
2D and 3D Modeling of VicK (WalK) Analysis with PSIPred program  (McGuffin et al. , 2000)  showed that VicK (WalK) consists of 48. 60% α-helix, 33. 99% β-sheets and 17. 41% random coil. MEMSAT-SVM program detected two transmembrane regions between amino acids 13 and 33 and between amino acids and 199. The carboxy-terminus and the amino terminus were predicted to be in the cytoplasm while the sequence between the amino acid 33 and 179 is an extracellular domain, thus representing the region of VicK (WalK) that may be able to interact with the catecholamines ligands, and will be called VicK ex (WalK ex ) in the rest of this manuscript (Figure  8 ). The 3D-structure of the extracellular domain VicK ex (WalK ex ) of the VicK (WalK) putative adrenergic sensor of E. faecalis OB15 was then predicted by the homology modeling servers Raptor X.
, 2007; Ring et al. , 2013). Dimić et al. (2020)  showed that NE binds to the β1adrenergic receptor and β2-adrenergic receptor with a free binding energy of -6. 4441 and -5. 3072 kcal/mol, respectively. These results are consistent with our data, as we found that the binding energy value of the interaction between Epi and VicK ex (WalK ex ) is -4. 08. This data is also in agreement with the study of  Parveen et al. (2012) , which have indicated values of -4. 56 Kcal/mol for Epi. In the same paper, the binding energy between NE and its receptor was measured to be -8. 56 Kcal/mol, a value significantly different from our result. This difference is probably explained by the fact that NE provided the best binding affinity with human Tyrosine hydroxylase  (Parveen et al. , 2012). For phentolamine and propanolol, the two clusters found are relatively the same, so we can suggest that these two molecules can interact with our putative adrenergic sensor VicK (WalK) and be blockers of the sensor.
Currently, gene information available for Oryza sativa species is located in various online heterogeneous data sources. Moreover, methods of access are also diverse, mostly web-based and sometimes query APIs, which might not always be straightforward for domain experts. The challenge is to collect information quickly from these applications and combine it logically, to facilitate scientific research. We developed a Python package named PyRice, a unified programming API to access all supported databases at the same time with consistent output. PyRice design is modular and implements a smart query system which fits the computing resources to optimize the query speed. As a result, PyRice is easy to use and produces intuitive results.
Introduction Rice, a model crop plant, is a major cereal grain widely consumed by a large part of the world's human population, especially in Asia. Since two decades, many digital resources have been developed in rice genomics. However, compared to human genomics, not as much centralized resources and analysis tools are available for rice genomics. Moreover, most of the information currently available are scattered and patchy in nature. Thus, for scientists, the challenge lies in integrating data and finding useful information. In the scope of the project, we aim to build an API to solve the problem of collecting and managing gene and gene products information from different sources. The PyRice package is developed to run remote queries over ten databases and web applications so far. However, PyRice provides generic wrappers to extend this number with more datatypes such as genetics, gene expression and pathways, according  (Garg P.
Materials and Methods Information of Oryza sativa genes are published on several open-access databases using different gene annotation models, e. g. RAPDB  (Hiroaki et al. , 2013) , MSU7 or dedicated IDs (i. e. SNP-SEEK  (Mansueto et al. , 2016)  and IC4R  (IC4R Project Consortium et al. , 2016). PyRice manages a dictionary of ID mapping across databases since each uses either of the two systems RAPDB and MSU7 (e. g. LOC_Os01g01010 = Os01g0100100; while the first ID is from MSU7 and the second is from RAPDB). Supplementary Fig. S1  shows the flowchart of the package. There are two main query types: with genomic coordinates or with a list of gene IDs.
Databases Currently, PyRice supports 10 databases to query gene information: Oryzabase  (Kurata et al. , 2006) , RAPDB, Funricegenes  (Yao et al. , 2017) , Gramene (Tello-Ruiz et al. , 2018), IC4R, MSU7 Rice GAP, Rice SNP-SEEK, EMBL-EBI Expression Atlas  (Papatheodorou et al. , 2017)  and GWAS Atlas  (Tian et al. , 2019). In PyRice, databases information is stored in a unique XML configuration file which allows the users to easily add new databases or update information. In order to help with connection failure due to network or database server's unavailability, some lightweight databases (i. e. SNP-SEEK, Oryzabase, RAPDB, GWAS Atlas) are downloaded and cached locally in PyRice after their first query. They are regularly updated within package by built-in function. The PyRice package builds a cross-reference dictionary between three types of index (i.
Parallel processing We implemented a smart query system which fits the computing resources and manages the query processing (presented in section 2. 3). PyRice runs independently each task in parallel, thus it is able to ignore interrupted tasks due to internet error correction or databases maintenance which may lead to conflict between queries. Moreover, we implemented several internet client authentication methods in order to avoid server rejections. Since computing resources could have different architectures, PyRice implements 3 parallel options (i. e. multi-processing, multi-threading and the combination of two). Thus, users can choose the number of threads and CPUs depending on their computer resource. In Supplementary File 1, we evaluated the benefits of using the parallel architectures.
Query system In PyRice, the query system is based on a database wrapper model. Because online databases usually provide web UI or APIs to query information, we developed a dozen of wrappers for each type of querying methods (e. g. GET, POST), input parameters, and output formats. Furthermore, it is possible to configure some filters to keep the necessary attributes. Results are indexed by IDs and stored in dictionaries along with databases information (presented in section 2. 4). As mentioned previously, Oryza sativa databases use diverse types of IDs to store information. PyRice handles it with a cross-reference dictionary of ID mappings. There are two types of query that is supported in PyRice, based on this dictionary: • Using IDs: PyRice automatically detects the type of query IDs and maps to those used in the requested database.
Results As presented in section 2. 2, PyRice stores results in a dictionary structure (shown in Supplementary File 2). Since gene information exists in several databases, this allows organizing information quickly while saving computing resources. This dictionary is then used to produce final results. Currently, the supported outputs are: • A summary file is created for each gene found in the initial query. This file gathers all information extracted from the databases and uses the HTML or JSON format for convenient browsing (see Supplementary Fig. S3 ); • A spreadsheet stores the resulting gene list along with basic information. PyRice supports output formats of CSV, JSON, HTML, and pickle (see Supplementary Fig. S2 ). Pickle format (i. e. pkl) is a serializing Python object structure which scales up very well with distributed processes, hence can handle a large number of gene queries.
Conclusion PyRice is a python package that simplifies querying Oryza sativa databases, making it easier to synthesize gene information. PyRice allows multiple processes that help to increase the speed of queries when multicore processors are available. The usage is straightforward, producing intuitive results. It can be easily extended with new databases (see Supplementary File 3), potentially applying to other plants as well. In the near future, we will extend PyRice to support more databases and new species. Besides, we will provide user support to add new users' databases. To speed up the query process, which is currently parallelized on a single computer, a distributed version of PyRice will be developed. Thus, the new version will use the resources of HPC clusters.
FUNDING This work was supported by a grant overseen by the  French National Research Agency (ANR)  as part of the  'Investissements d'Avenir' program  ( ANR-11-LABX-0002-01 ,  Lab of Excellence ARBRE ), by the  Pôle Scientifique   A2F  of the  Université de Lorraine , and by the  French PIA  project  Lorraine Université d'Excellence , reference  ANR-15-IDEX-04-LUE.
Apoptosis Detection The apoptotic effect of tested compounds was evaluated using Annexin V-FITC Apoptosis Detection Kit I (BD Bioscience Pharmingen, USA) according to manufacturer protocol. In this regard, HT-29 cells (3 × 10 6 ), were seeded in 3. 5 cm diameter wells and treated with 50 µg/mL of tested compounds. After 24 h, the cells were resuspended in 100 µL of binding buffer and stained with 5 µL Annexin V-FITC and 5 µL propidium iodide for 10 min in dark. At least 10,000 events from each sample were acquired using a Beckman Coulter flow cytometer. The analysis was done using FlowJo v 8. 8. 6 software (Ashland, OR, USA).
Cell Cycle Analysis To assess the influence of new compounds on cell cycle, a number of 3 × 10 6 HT-29 cells were treated with compounds at 50 µg/mL concentration for 24 h. Treated cells were harvested, washed in a cold phosphate-buffered saline solution (PBS), then fixed in cold ethanol (70%) and stored at -20 • C. After 24 h, the cells were washed with PBS, resuspended in 100 µl PBS, treated with 1 mg/mL RNase A and labeled with 100 µg/mL propidium iodide in the dark at room temperature for 30 min. DNA content of cells was quantified on a Beckman Coulter EPICS XL flow cytometer and analyzed using FlowJo 8. 8. 6 software (Ashland, OR, USA).
Similarly, the slight spontaneous ability of strain #20 to block the magnetic microbead migration in cBRT visually manifested as the formation of green micro-colonies. Examination of cultures with β-lactams revealed two distinct phenomena: either a modification of the cell shape or the stimulation of the bacterial adhesion. In fact, it could be easily noticed that bacteria of strains #6 and #22 appeared elongated when they were in the presence of TIM, FEP, CAZ, and MEM, compared to the normal cell morphology of the control suspensions. However, this size elongation seemed to be a strain-dependent process as it was not noticed with strain #31 regardless of antimicrobials. To validate these visual observations, microscopy pictures were analyzed according to the ImageJ software. By image examination, the pixel number depicting a fluorescent object can be converted to a value in µm and the number of bacterial cells can be estimated.
The average length and number of microbial components present for the control strains and cultures with β-lactams are summarized in Table  2. ImageJ software allowed for the size calculation of each spotted fluorescent object by the conversion of their corresponding pixel number in µm. It allowed for the length evaluation of individual bacterial cells but when a strain spontaneously adheres, the formation of microbial micro-colonies could be observed and isolated cells were not easily detectable. In that case, the shape of overall clusters was estimated (values notified by the sign • in the table). The image processing software also enabled the quantification of delimited objects visible on each acquired microscopic field. Either the number of bacteria or the number of corresponding clusters was documented.
Data included in the table are average values arisen from the analysis of nine observation fields (fluorescent microscopy experiments were performed in triplicates and three pictures were captured for each condition). Statistical analyses were performed through one-way ANOVA and Dunnett's methods for the comparison of each antimicrobial condition with their corresponding control strain (*, **, ***, **** adjusted p-values). Compared to the normal size of cells documented for strain #6 (0. 9 µm on average), a statistically significant increase in bacteria length, ranging from 175% to nearly 250%, was noticed for cultures with TIM, FEP, CAZ, and MEM. This reflected a filamentous form of induction by antimicrobials. The cell elongation of strain #22 was significantly more substantial as the bacteria in antibiotic conditions were at least 300% longer than the control standard-sized cells (1.
Bacterial Strains We used a collection of 38 clinical P. aeruginosa strains isolated from the sputum of CF anonymized patients to perform standard cBRT. Antibiotic susceptibility testing with a modified application of the cBRT assay and microscopy experiments were performed on 4 non-adherent isolates (#6, #20, #22, and #31). The induction of the early steps of biofilm formation by antimicrobials being a strain-dependent process, these strains were selected as they showed significant data with in vitro assays. The whole P. aeruginosa strains originated from the sputum of CF anonymized patients and culture stocks were conserved in glycerol at -80 • C. They were subcultured on Brain Heart Infusion (BHI) agar plates before the realization of the different assays.
The microplates were incubated at 37 • C for 5 h and the assays performed in duplicates. For the plate reading, the wells were covered by 120 µL of the contrast liquid solution. Then, the microplate was magnetized for one minute with the block test and scanned with the BioFilm Reader. The magnetic field enables free beads attraction towards the center of the well, forming a brown spot made of aggregated particles, while beads embedded in a biofilm are blocked and remain non-detectable. The adhesion ability of bacteria was expressed as the Biofilm Formation Index (BFI) calculated by the BioFilm Control Elements ® 3. 0 software. The Biofilm-forming Potential (BP), namely, the ability of bacteria to form biofilm ranging from 0 to 1, was specifically developed by Di Domenico et al. for the cBRT assay and is determined as BP = [1 -(BFI sample/average BFIs of negative control)]  [14].
0 camera (C11440, Hamamatsu, Massy, France) and HC Image Live software (Hamamatsu). At least three microscopic fields were acquired for each well. The corresponding pictures were analyzed according to the free software ImageJ (NIH), which allowed for the viewing and the discrimination of live vs. dead bacteria. For one microscopic field, two images were taken with two couples of excitation/emission filters: the GFP-FITC one (470-510 nm) for the revelation of Syto9 green fluorescence and the Texas Red one (585-624 nm) for the detection of red bacteria stained with PI. The software also allowed us to numerically quantify microorganisms/clusters present per microscopic field through the calculation of pixel number. The corresponding variation rates (in %) were also specified to estimate a change in the cell length or in the bacterial body number of microbial cultures with antibiotics, compared to the values found with control conditions.
We found stronger NADH-TR staining in downregulated TERF2 myotubes (Figure  S5b ), suggesting a switch from glycolytic (fast, type II) toward oxidative (slow, type I) fibers, the latter being associated with development, aging, and stronger resistance to oxidative stress  (Lexell, 1995; Miljkovic et al. , 2015). F I G U R E 3 TRF2 binds and modifies expression of the subtelomeric SIRT3 gene. (a) Venn diagrams generated from a TRF2 ChIP-Seq performed in myotubes, and all data are uploaded into the GEO database under the accession number GSE88983. Significant peaks (p <. 05) were identified and annotated. A differential analysis identified the significant peak that was "lost" or "gained" by TRF2 modulations. A final Venn diagram was then produced using the genes associated with the peaks found only in the shScramble condition (e.
Funding information Association Française contre les Myopathies (AFM)   Trampoline grant ;  Inserm Transversal Program on Aging ;  Agence Nationale de la Recherche (ANR) , Grant/Award Number:  TELOPOST  ( ANR-18-CE13-0029-01 ) and  LABEXSIGNALIFE  ( ANR-11-LABX-0028-01 );  National Natural Science Foundation of China , Grant/Award Number:  81471400 ,  81522017 ,  91749126  and  81971312 ;  Shanghai Talent Development Fund , Grant/ Award Number: 2017100; Foundation of  Shanghai Jiaotong University School of Medicine for Translational Medicine Innovation , Grant/Award Number:  15ZH4005.
95, was used to calculate micromolar changes in tissue HbO 2 ( [HbO 2 ]), HHb ( [HHb]), and total hemoglobin [ [tHb] = [HbO 2 ] + [HHb]; used as an index of change in regional blood volume  (van Beekvelt et al. , 2001) ]. The NIRS data were acquired at 10 Hz and then filtered using a tenth-order Butterworth low-pass filter with a 4 Hz cutoff frequency. Analysis of muscle O 2 extraction was limited to [HHb] because this variable is less sensitive than [HbO 2 ] to perfusion variations and abrupt blood volume changes during contraction and recovery  (de Blasi et al. , 1993; Ferrari et al. , 2004). From the filtered signal, one value for each of the maximal and minimal [HHb] and [tHb] was manually identified for every sprint/recovery cycle throughout the RSA test for accurate detection of oxygenation peaks and nadirs  (Faiss et al.
RESULTS Of the 17 participants recruited, 13 completed the entire protocol and were included in the analysis (VHL, n = 7 and CTL, n = 6). One participant could not complete the study because of injury not related to the study. The three others missed more than 3 training sessions and were therefore excluded from data analyses. All participants from the VHL group tolerated the breathing technique without any issues or complications. During training, the averaged SpO 2 recorded during the three sets (including sprints and recovery phases, but excluding the inter-set 3-min recovery) was 87. 7 ± 4. 6% for the VHL group and 96. 9 ± 0. 5% for CTL.
In fact, the cumulated completion time of the last 4 sprints was clearly lower after training in VHL (Figure  2 ), supporting the hypothesis of a delayed fatigue. Further investigations using magnetic resonance imaging or muscle biopsy are required to assess fiber-specific intramuscular PCr content and resynthesis rate after VHL training to support this adaptative mechanism. In the RSA literature, reductions in EMG-derived indices RMS and MPF have been widely described  (Billaut and Bishop, 2009; Girard et al. , 2011)  and are typically taken as reduction in total motor unit recruitment and increased reliance on slow, fatigue-resistant type-1 motor units, respectively, due to the development of neuromuscular fatigue. There is no data on electromyographic behavior of active skeletal muscles after breath-hold training, so the current study highlights for the first time the marked impact of VHL training on these neural strategies (Figure  5 ).
The gene expression data obtained are further detailed in Figure  2C  for WM852 cells and in Figure  S2B  for WM115 cells. Validation of our RNA sequencing data was further conducted by qRT-PCR on 5% of randomly chosen genes within the total number of genes differentially expressed in WM852 cells (Figure  S2C ). Pathways overrepresented in Casp + cells compared with control cells were identified through a pathway analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) via the DA-VID database (https://david. ncifcrf. gov). WM852 cells were used based on their highest PCA differences (Figure  2A ). The most striking result emerging from this analysis is that Casp + cells present a transcriptional signature associated with focal adhesion, cell adhesion molecules, transendothelial migration, and regulation of the actin cytoskeleton (Figures  2D, S2D,  and S2E ).