dataesr/scientific-paragraphs-categorization huggingface dataset:
Indeed, since these two PDB entries remain the only ones available for IL-15, we think that their use as starting points for the relevant simulations is important, rather than using a single entry, in order to take into account their corresponding features, that might be related to the corresponding multimeric state. Nevertheless, we have computed the RMSD (considering Cα carbon atoms) of the IL-15/IL-15Rα chains in the dimer and tetramer crystallographic complexes. The value obtained, of 0. 67 Å, clearly confirms that the two structures are similar. We are therefore confident that the protocol that we have used is safe. The missing side-chain atoms, hydrogen atoms and disulfide bridges were added using the Prime tool in the Maestro program of the Schrödinger package  [22]. A missing loop (residues 25-31 on IL-15) was added by homology modelling with an identical loop present on IL-2 (PDB ID 2B5I) using Prime from the Schrödinger Suite  [22].
Molecular Dynamics Simulations The MD simulations were carried out using the NAMD program  [23] ; all receptors complexes and counter-ions were described using the CHARMM36 force-field  [24, 25]  and explicit TIP3P water molecules  [26]  were added to form a cuboid box of 12 Å dimensions around the protein. Each entire system was neutralized by the number of required counter-ions. These number were: 11, 6, 13 and 9 potassium ions for the monomer, dimer, trimer and tetramer species. Initially, two minimization steps were performed, each for 10,000 steps, wherein, at first, the water molecules and counter-ions were minimized while the protein was kept fixed and, finally, the whole system was minimized. The number of atoms and water molecules ranges from 30,736 (with 9652 water molecules) for the monomer to 190,645 (with 60,394 water molecules) for the tetramer.
Conclusions In this study, new structural features of IL-15 interfaces (IL-15/IL-15Rα, IL-15/IL-2Rβ and IL-15/γc) in relevant IL-15 multimeric states have been reported on the basis of MD simulations. It is important to note that despite the fact that our study investigates the structural features of the various relevant (from a biological point of view) multimeric states of IL-15, namely the full quaternary complex: IL-15/IL-15Rα/IL-2Rβ/γc, the trimeric complex IL-15/IL-2Rβ/γc, the dimeric IL-15/IL-15Rα and monomeric IL-15 forms, the starting geometries used come from the experimental structures available, that is the full quaternary complexes (4GS7 pdb entry for the quaternary, trimeric complexes and the monomer) and the binary IL-15/IL-15Rα complex (2Z3Q pdb entry for the dimer). While this methodology might have limitations, we have not found any other alternative in the absence of the relevant corresponding experimental information.
Funding: This research was funded by the  Région des Pays de la Loire  ( PIRAMID  project), through a  "Dynamiques Scientifiques" grant. This work was also supported by the  CNRS, Inserm , and realized in the context of the  IHU-Cesti  ( ANR-10-IBHU-005 ) project which received French government financial support managed by the  National Research Agency  and supported by  Nantes Métropole and Pays de la Loire Région.
Method Systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and by consulting the five databases: Medline, Science Direct, Web of Science, Dentistry and Oral Science Sources and Cochrane Central Register of Controlled Trials. Following Koch's postulates revisited by Socransky as PICO framework, this collection data was only including full text of clinical trials concerning patients with periodontitis, case-reports and in vitro research published between 1960 and March 2019.
Study selection As shown in Fig  1 , a total of 376 articles were identified from the previously described electronic database search. After duplicate removal and language exclusion, a total of 156 articles were obtained. Finally, after the removal of non-full text and non-relevant papers, 25 articles were deemed appropriate to be included. The main reasons for exclusion were: the absence of periodontal status, lack of precise periodontal parameters, the identification of trichomonads in animal studies but not in human studies, the studies included patients with medication modifying microbiota, the diagnosis of periodontitis as a manifestation of systemic disease, other trichomonads species than T. tenax, the absence of a T. tenax factor of virulence. Some clinical studies were discarded because essential details were missing: 1.
The five databases MEDLINE, Science Direct, Web of Science, Dentistry and Oral Sciences Source and Cochrane Central Register of Controlled Trials were consulted and our research was conducted on all relevant literature up to March 2019 using MeSH, and the following key- words: Trichomonas tenax AND (periodontal diseases), Trichomonas tenax AND (periodontitis), Trichomonas tenax AND (antibody) OR (pathogenicity) OR (virulence) OR (enzyme) OR (cytokines) OR (toxicity) OR (adhesion) OR (adherence) OR (invasion) OR (invasive).
Custom bovine gene expression microarray processing and hybridization Transcriptional profiling was performed using a custom bovine array generated by merging the Agilent bovine 44K microarray (National Center for Biotechnology Information, Gene Expression Omnibus accession no 023647_B. taurus Oligo Microarray V2_1 and V2_4) with a non-commercial bovine INRA 22K (13,257-element bovine oligonucleotides array, Gene Expression Omnibus accession no. GPL2853). This custom bovine microarray was designed based on bovine annotated Ensembl transcripts (http://www. ensembl. org/index. html, genome assembly UMD3. 1) and represented 19,479 transcripts. It was manufactured by Agilent Technologies using 60-mer oligonucleotides probes (Agilent eArray software; https://earray. chem. agilent. com/earray/) and an in situ synthesis printing process.
Temporal regulation of the selected candidate DEGs (n = 9) was investigated in circulating WBC collected at 1-4, 9-11 and 45-55 DPP of 10 healthy females (LP, n = 3, FP, n = 6 and undetermined, n = 1) and 4 SCE females (LP, n = 1; FP, n = 1; undetermined, n = 2). Specific primers (S2 Table ) were designed for every candidate gene using NCBI Primer-BLAST  [30]. To assess that cDNA amplification generated the expected fragment, every amplicon was sequenced and blasted on NCBI RNA bovine database to confirm its identity. First-strand complementary DNA (cDNA) was synthesized from 500 ng of purified total RNA using 0. 025 μg Oligo(dT) 12-18 as primers and 10U of SuperScript II Reverse Transcriptase enzyme (Invitrogen, France) in a 20 μl reaction volume according to the manufacturer's instructions.
The Qbase software (Biogazelle,) based on the geNorm module  [32]  was used for analyzing quantitative PCR data. The geNorm module determined the expression stability of candidate references and the optimal number of reference genes. Five genes (ACTB, B2M, GAPDH, RLP19 and TPRG1L) were tested to identify the most stable genes under the experimental conditions used in this study. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and actin beta (ACTB) were the most stable reference genes in WBC and GAPDH and tumor protein p63 regulated 1 like (TPRG1L) in endometrium. All expression data for gene transcripts of interest were expressed as mean calibrated normalized relative quantity (CNRQ) values in arbitrary units.
were identified in the endometrium (p-value � 0. 05). Three major networks related "Amino Acid Metabolism, Small Molecule Biochemistry, Lipid Metabolism", Cell-To-Cell Signaling and Interaction, Cellular Movement, Hematological System Development and Function" and "Digestive System Development and Function, Organismal Functions, Lipid Metabolism" are presented in S2 Fig. Biological processes affected in the endometrium of cows with subclinical endometritis. To gain insights into the biological processes altered in the endometrium of SCE cows, the 512 DEG were analyzed using the IPA software (S3 Table ). Significant association (pvalue � 2. 0E-3) was established for 140 "disease and biological function" terms containing n � 30 genes (S6 Table ). The five top functions for "diseases and disorders", "molecular and cellular functions" and "Physiological System Development and Function" categories are presented in table in S7 Table.
05) including cytokines, transcription factors, growth factors, endotoxins and miRNA (S9 Table ). Twelve of them were predicted to be significantly associated with a mechanistic network (Z-Score � +2, or Z-Score � -2, pvalue of overlap < 0. 05; S9 Table ). Gene networks associated with mRNA expression changes in circulating white blood cells of cows with subclinical endometritis. The Networks module of IPA identified 25 networks with the DEGs identified in circulating white blood cells of SCE compared with healthy cows at 45-55 DPP (S10 Table ). Three major networks related to "Endocrine System Development and Function, Lipid Metabolism, Small Molecule Biochemistry", "Humoral Immune Response, Protein Synthesis, Hematological System Development and Function " and "Cell Cycle, Reproductive System Development and Function, Cardiovascular Disease" are presented in S4 Fig.
Biological processes affected in the circulating white blood cells of cows with subclinical endometritis. At 45-55 DPC, the 340 DEG found in the circulating WBC of SCE cows compared with healthy cows were analyzed using the IPA software. Significant association (pvalue � 4. 0E-3) was established for 83 IPA Disease and biological functions terms with n � 30 genes (S7 and S11 Tables). The five top functions for "diseases and disorders", "molecular and cellular functions" and "Physiological System Development and Function" categories are presented in table in S7 Table. Biological functions including "Migration of cells" as well as various immune cells-related functions (e. g. cellular infiltration of leucocytes, cell movement of phagocytes and of leucocytes), were significantly increased (S3 Fig).
and S12 Table) Identification of upstream regulators linked to mRNA expression changes in circulating white blood cells of cows with subclinical endometritis. The upstream analysis module of IPA identified 83 putative upstream regulators (p-value < 0. 05). Three of them were associated with a mechanistic network with significant Z-score (Z-Score � -2 or Z-Score � +2, p-value of overlap < 0. 05; S13 Table ). The predicted top activated upstream genes included lipid A, a key component of lipopolysaccharides  (Fig 4) , as well cholesterol, pro-inflammatory cytokines (IL4, IL1), mature microRNA (miR-1900, miR-339-3p), a chromatin-associated enzyme poly (ADP-ribose) polymerase (PARP1) and a multifunctional nuclear protein implicated in DNA repair, NFkB inhibitor alpha complex (NFkB complex). In cows displaying SCE at 45-55 DPP, a chemical-kinase inhibitor (SB203580;  Fig 4) , Transcription factor G Protein Pathway Suppressor 2 (GPS2), 5'-prime-AMP-activated protein kinase (AMPK, a cellular energy sensor), Heme oxygenase 1 (HMOX1) that plays a critical role in inflammation and iron homeostasis were predicted to be top inhibited upstream genes.
In circulating white blood cells, expression levels of ART5, C2, C3, CXCL8, LTF, PF4, PRKCI, TLR2 and TRAPPC13 gene transcripts were quantified by RT-qPCR analyses in cows with subclinical endometritis (SCE, n = 7, including follicular phase, n = 1; luteal phase, n = 4; undetermined estrous cycle, n = 2) compared with healthy cows (n = 10, including follicular phase, n = 5; luteal phase, n = 5) at 45-55 days postpartum (DPP). Relative gene expression was determined by normalization to the two most stable reference genes (GAPDH and ACTB). All expression data for gene transcripts of interest are expressed as mean calibrated normalized relative quantity (CNRQ) values in arbitrary units. The significance of differences in gene expression levels between groups of animals was determined by Kruskal Wallis, Dunn's multiple comparisons test and by Mann Whitney U test at p < 0.
05. Results are mean ± SEM. https://doi. org/10. 1371/journal. pone. 0220244. g005 Additionally, the positions of selected candidate DEGs validated by RT-qPCR analyses in circulating WBC and endometrium were compared to the position on the UMD3. 1 bovine genome assembly  [33]  of know quantitative trait loci (QTLs) deposited in the public database Animal QTLdb  [34]. In total, 13 different genes were located in QTL regions related to female reproduction or infection traits (Table  2 ).
In human, it has been reported a potential linkage of severe preeclampsia to the most central complement gene, C3  [54]. A broader genetic approach to identify SCE-related genes awaits further investigation  [55, 56]. Our data showed that circulating WBC collected from SCE cows expressed higher levels of TRAPPC13 and PRKCI mRNA. TRAPPC13 is a member of a multi-subunit TRAPP complexes (TRAPP; also known as trafficking protein particle), which are key players in the regulation of endoplasmic reticulum-to-Golgi transport and autophagy in yeast and mammals  [57, 58]. Studies have shown that TRAPPC8 is required for cell entry of the human papilloma virus  [59]. In vitro study reported that the loss of mammalian TRAPPC13 in cells protects against Golgi-disrupting agents  [60]. However, to our knowledge, no study has reported a potential molecular or cellular function of TRAPPC13 in peripheral blood leucocytes of cattle.
Relative gene expression was determined by normalization to the two most stable reference genes (GAPDH and ACTB). All expression data for gene transcripts of interest are expressed as mean calibrated normalized relative quantity (CNRQ) values in arbitrary units. The significance of differences in gene expression levels between groups of animals was determined by Kruskal Wallis, Dunn's multiple comparisons test and by Mann Whitney U test at p < 0. 05. Results are mean ± SEM.
5-1 × 10 5 ) were incubated 30 min at 37°C with anti-Env antibodies or with an isotype human IgG1 control (mGO53) at 15 lg ml À1 (unless otherwise stated), or with sera diluted 1:1,000. Cells were washed and incubated 30 min at 4°C with anti-human IgG1 (H + L) Alexa Fluor 647 (1:400 dilution; Life Technologies). Cells were then fixed with 4% PFA and stained for intracellular Gag with the anti-Gag KC57 murine monoclonal antibody as previously described  [24]. Env-expressing Raji cells were stained using the same protocol, except that antibodies were biotinylated and revealed using a Alexa Fluor647-conjugated streptavidin (1:400 dilution; Life Technologies). Data were acquired on an Attune Nxt (Life Technologies) and analyzed using FlowJo software.
After 24 h, the percentage of infected (Gag + ) cells in each condition was determined by flow cytometry. One representative experiment is shown. H Complement-mediated cytotoxicity of HIV-1-infected CD4 T cells (strain NLAD8). For each antibody, the % of CDC was calculated at 24 h as the % of disappearance of Gag + cells in NHS compared to HIHS. Each dot represents a single donor of CD4 T cells. n = 7 donors of CD4 T cells. Data information: Error bars indicate SEM. *P < 0. 05, **P < 0. 01, Wilcoxon test. Only significant comparisons are depicted.
Acknowledgements We thank members of the  Virus and Immunity Unit  for discussion and help. We thank patients who participated in the study and  Cécile Goujard  for supervision of the patients' enrollment. We thank the  NIH AIDS Reagent Program  for providing reagents. We thank  Michel C. Nussenzweig  ( The Rockefeller University ) for providing the pMX-YU2 ENVDCT-GFP-Puro R expression vector. We thank  Frank Kirchhoff  and  Daniel Sauter  ( Ulm University ) for providing  CH058 ,  CH058ΔNef ,  CH058ΔVpu , and CH058ΔNefΔVpu plasmids. Work in OS laboratory is funded by  Institut Pasteur ,  ANRS ,  Sidaction , the  Vaccine Research Institute  ( ANR-10-LABX-77 ), the  Labex IBEID  ( ANR-10-IHUB-0002 ), the " TIMTAMDEN "  ANR-14-CE14-0029 , the " CHIKV-Viro-Immuno "  ANR-14-CE14-0015-01 ,  L'Oréal Sponsorship , and the  Gilead HIV cure program.
HM is supported by the  European Research Council (ERC) - Seventh Framework Program  ( ERC-2013-StG 337146 ), the  G5 Institut Pasteur Program , the  Milieu Intérieur  ( ANR-10-LABX-69-01 ), the  INSERM , and the  ANRS. JD is supported by a grant from the  French Ministry of Higher Education, Research and Innovation.
Both WT-or E430G-mutated antibodies were used. After 24 h, C3 surface levels on infected cells were analyzed by flow cytometry. Results are expressed as MFI of staining on infected (Gag + ) cells. The MFI of C3 staining on Gag À cells was included as a control. Each dot represents a single donor of CD4 T cells. n = 6 donors of CD4 T cells. Data information: Error bars indicate SEM. *P < 0. 05, Wilcoxon test. Only significant comparisons are depicted.
For each microorganism, ADAPTABLE is able to generate SR families containing peptides known to be active against it and classify them, thus highlighting essential traits. Alternatively, each of these peptides can be used as a bait to generate their own SR families by scanning the ADAPTABLE database featuring more than 40,000 entries. Although sequence alignment has been widely used among AMPs with strictly related biological source, we believe that the comparison of evolutionarily distant AMPs with similar activity can highlight the features that are key to their mechanism of action. This unbiased search can be used to spot existing, but untested, sequence-related peptides of similar structure and mechanism of action that also have the properties of more-promising drug candidates (e. g. , less hemolytic).
Several methodologies and software already exist for the classification and prediction of AMP activities  (Brahmachary et al, 2004; Fjell et al, 2007; Wang et al, 2011; Ng et al, 2015; Bhadra et al, 2018). Most provide tools for sequence similarity searches, and only few have algorithms for predicting the activity of any given peptide sequence (e. g. , APD  [Wang, 2014] , CAMPR3  [Waghu et al, 2016] , AVPpred  [Thakur et al, 2012] , YADAMP  [Piotto et al, 2012] , and ToxinPred  [Gupta et al, 2013] ). However, none of these combine a systematic global classification with "adaptability" (hence, the name ADAPTABLE) to the focus of the user's research. A different approach tailored to researchers' aims One important difference of ADAPTABLE with respect to other alignment tools is that it provides the facility to study peptides active against a specific pathogen, even when a researcher does not already have a specific peptide of interest.
A comprehensive and standardized database Whereas the power of the algorithms relies on large number of entries, the concept of property alignment requires standardization. In other words, the development of ADAPTABLE web platform has implied the creation of a comprehensive and standardized database that addresses a further fundamental problem in the study of AMPs: information scattering across multiple web resources. Existing databases have previously been merged  (Aguilera-Mendoza et al, 2015) , but previous standardization only collected and merged sequence information. In contrast, ADAPTABLE merges information for more than 60 properties from 25 databases specialized in both medical and agricultural fields where available and creates a unified, nonredundant entry. This way, each sequence is associated to all available data on its structure (predicted or experimental), activity  (e.
g. , anticancer, antibacterial, antibiofilm, antiviral, antifungal, or antiparasitic) , targets (e. g. , lung cancer, HeLa cells, HIV virus, cell membrane target, Klebsiella pneumoniae, or Plasmodium falciparum), and other information (e. g. , experimental validation, taxonomy, bibliography, or DSSP-"define secondary structure of proteins"  [Kabsch & Sander, 1983 ] data). Merging of data from different sources requires standardization. This task can be challenging because each existing database follows its own format and definitions. For instance, activities are reported in many different units or measured by different tests. Our algorithm converts all activities to micromolar (μM) concentration by calculating the molecular weight of the peptide, even for nonproteinogenic amino acids. Even if different activity values are not always directly comparable because of different experimental conditions or activity tests, an upper threshold value allows the filtering out of less active peptides, while the "activity test" toggle allows restriction to a single test.
To our knowledge, ADAPTABLE is the only tool able to standardize activities and non-proteinogenic amino acids, including modified and non-natural amino acids. Non-proteinogenic amino acids lack a standardized one-letter code, resulting in confusion when comparing sequences across different databases. This ambiguity often leads to redundant entries referring to the same sequence being nonuniformly annotated. Furthermore, some non-proteinogenic amino acids are named by different synonyms rather than a unified nomenclature that, if it existed, would allow unambiguous identification. ADAPTABLE addresses both issues by interpreting the different nomenclatures and providing a single name based on the PubChem database  (Kim et al, 2019 ) and a single one-letter symbol. For non-proteinogenic amino acids, the closest proteinogenic homologue is also identified, where possible.
ADAPTABLE takes the standardization process one step forward, thanks to its inclusion of data from a specialized microbiology database ("The Microbe directory"  [Shaaban et al, 2018] ). This allows the inclusion of potentially missing information such as the full names of organisms, their nature (i. e. , Gram positive or negative bacteria, fungi, or virus, among others), and some of their properties (i. e. , ability to form biofilms). The same approach is followed to complement and store structural information, either predicted or experimental, leveraging ADAPTABLE's integration with the Protein Data Bank  (Berman et al, 2000)  and the usage of PSSpred  (Yan et al, 2013)  and I-TASSER  (Roy et al, 2010; Yang et al, 2015; Yang & Zhang, 2015).
By selecting from among the more than 60 parameters, the user can choose the target organism, activities, or chemical or physical properties, and also stipulate other parameters (source, taxonomy, posttranscriptional modifications, N-terminal or C-terminal modifications, solubility, etc. ). For example, switching on the "Experimental structure" option will filter out all peptides whose structure has not been experimentally obtained. It is also possible to restrict the selection to those peptides tagged "experimentally validated" by their original source database ("Experimentally validated" toggle). Further restriction is possible by selecting only peptides for which (i) the target organism is described or (ii) the target organism is described and a specific value of activity has been measured.
The user can optionally include their own sequences in the calculation ("Append User peptides"). A remarkable feature of ADAPTABLE is its ability to handle non-proteinogenic amino acids in a standardized fashion. Thanks to a character picker (insert at the top of Fig 1 ), the user can insert non-proteinogenic amino acids in the sequence by clicking their symbol. The "Simplify amino acids" option transforms non-proteinogenic amino acids to their most similar proteinogenic counterpart, if possible. Rather than selecting peptides based on their properties, the user can choose to create an SR family using a specific reference sequence ("Create the family of a specific peptide"). This feature can be very useful for classifying new peptides of unknown activity. If very similar sequences are found in the database, this option can even be used to help determine their biological properties.