dataesr/scientific-paragraphs-categorization huggingface dataset:
In the model analysing the risk towards severe diseases, the duration between symptom onset and testing was included as a variable based on its statistical significance. Conversely, in the mortality model, the variables "RSV" (respiratory syncytial virus) and "pertussis" (within the co-infection group of variables) were excluded due to their lack of statistical significance. We report the median and interquartile range (IQR) for age groups and the frequency and percentage for categorical variables. Despite the huge number of univariable tests, we did not explicitly apply a multiple-testing correction since the variable selection technique for the multivariable model was only partially based on p-values. The Pandas software library was used to arrange the data, and the R package "logistf" was utilized for the main analysis  [11, 12].
Governments must not lose sight of the Measles and Rubella Strategic Framework, 2021-2030  [35]. This study has certain limitations. The patients enrolled in this study are those that were admitted to our hospital, whose illness may be more severe and are not representative of all measles cases in Vietnam. Detailed data were partially lacking on the number of MCVs and the place of exposure though the medical files were thoroughly checked, and the percentage of missing data was quite low for almost all variables. Nonetheless, we were able to analyze a large sample of over 2, 000 measles cases with extensive clinical information and other socio-demographic characteristics using the measles suspected case inquiry form. In conclusion, in this study, we report clinical and epidemiological characteristics from a significant measles outbreak that primarily affected unvaccinated children admitted to VNCH, with a 1.
Trial design 'LITE' (LDIL-2 to expand endogenous regulatory T cells and achieve tolerance in liver transplantation; ClinicalTrials. gov identification: NCT02949492) was an open-label, activity, safety and efficacy, prospective, single-arm clinical trial in which stable adult liver recipients on calcineurin inhibitorbased immunosuppression initiated LDIL-2 treatment and attempted to discontinue all immunosuppressive agents if a >2-fold expansion of circulating Tregs was observed after 4 weeks of treatment. The primary endpoint was successful immunosuppression withdrawal, defined by the absence of rejection and a rejection-free liver biopsy at 1 year following discontinuation of immunosuppression. Secondary endpoints were as follows: incidence of rejection, graft loss, patient survival, IL-2-related adverse events, effect of LDIL-2 on blood and liver Treg numbers, sequential immunological changes in blood and liver tissue, development of serum antihuman leucocyte antigen (HLA) antibodies.
Immunosuppression was withdrawn in 6 steps lasting 2 weeks each. LDIL-2 was maintained for a total of 6 months or until the development of allograft rejection (Fig. 1A ). Circulating Tregs and liver tests were monitored weekly during the first 4 weeks and every 2 weeks thereafter until the discontinuation of IL-2 treatment. In individuals tolerating immunosuppression withdrawal, a final protocol biopsy was required 18 months after enrolment. Adverse events were graded according to the Common Terminology Criteria for Adverse Events (version 4. 03) and assessed for their seriousness and relatedness to trial procedures. All severe adverse events and rejection episodes were reviewed by the Data Safety Monitoring Board (DSMB). Urgent safety measures approved by the DSMB were instituted immediately after P02's severe rejection episode, consisting in the following: (i) halting further participant recruitment; (ii) reducing IL-2 dose to 0.
5 and 4, respectively; Table  S4 ). Functional analysis using Gene Ontology (GO) terms identified immune response, IFNc-mediated signalling pathway and major histocompatibility complex (MHC) class II protein complex as the most highly enriched pathways (Fig. 5D ). In addition, an 11  previously described as being highly specific for liver allograft TCMR was significantly over-represented in the differentially expressed dataset (Fig. 6E ). We observed an equally significant enrichment in multiple IFNc-related gene sets known to be involved in TCMR across a variety of different transplant settings (Table  S5 ). Of note, no enrichment in NK-related transcripts was observed.
We then assessed the functional consequence of IL-23R signaling in Treg cells in vivo. First, we used an infectious model of colitis using C. rodentium that induces IL-23 production that is required for pathogen clearance. 15 Foxp3 YFPÀCre and Il23r DTreg mice were gavaged with a bioluminescent strain of C. rodentium 29 and 14 days post-infection, we observed similar colonization, colonic inflammation, and colony-forming unit (CFU) counts despite high levels of Il23p19 transcripts (Figures  S5A-S5D ). These data indicate that IL-23R signaling in Treg cells does not exacerbate disease pathogenesis following infection with C. rodentium. We then used a second model of colitis in which IL-23 is a known driver of disease pathogenesis following the transfer of naive T cells into RAG1/ 2-deficient mice.
IL-23R-deficient Treg cells display altered gene signatures involved in cholesterol homeostasis In effort to define the IL-23R-dependent changes in intestinal Treg cells that might contribute to the impact on Treg cell function and selective advantage, we performed RNA-sequencing (RNA-seq) on live CD4 + FOXP3 + cells sorted from the cLP of Foxp3 YFPÀCre and Il23r DTreg mice, respectively. Principal-component analysis and sample-to-sample distance indicated that Treg cells from Foxp3 YFPÀCre mice and Il23r DTreg mice differed (Figure  4A , a part of Data S1, GEO: GSE208621). Differential gene expression revealed 129 downregulated and 181 upregulated genes in Treg cells from Il23r DTreg mice. One of the genes significantly upregulated in colonic Treg cells from Il23r DTreg mice was ATP-binding cassette a1 (Abca1) (Figure  4B ), as were a cluster of genes associated with cell survival and liver receptor X (LXR) signaling (Figure  S7 ).
To this end, we analyzed a single-cell RNA-seq dataset of immune cells recovered from the ileal lamina propria of patients with CD 51 (Figure  S8A ) and profiled a select subset of immune cells and transcripts pertaining to IL-23R and LXR signaling, and apoptosis. We found that IL-23 is expressed by inflammatory macrophages with IL17A expression elevated in activated conventional T cells, consistent with a role for IL-23 in stabilizing Th17 cells, and that both group 3 innate lymphoid cells and Treg cells exhibited high levels of IL23R expression (Figure  S8B ). Given the negative clinical trial data using IL-17A blockade,  11, 12  we hypothesize that improvement in intestinal inflammation following administration of IL-23 blocking antibodies may be partially attributable to inhibition of IL-23R signaling in intestinal Treg cells.
Data and code availability d Code for analysis of bulk RNA-seq and 16S is included as Data S1 Code for analysis of bulk RNA-seq data and 16S, related to Figures  S4  and 4 , and data have been deposited at GEO and SRA respectively and are publicly available as of the date of publication. Accession numbers are listed in the key resources table. This paper re-analyzes existing publicly available data from Martin et al. 51. d Original single-cell RNA-seq code is available at GitHub and is publicly available as of the data of publication. A link is listed in the key resources table. Original bulk RNA-seq code will be shared by the lead contact upon request. d Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.
RNA-sequencing Quality control for RNA was performed by the Vanderbilt Technologies for Advanced Genomics core using RNA 6000 Pico (Agilent, Santa Clara CA), and for low-input RNA from colonic Treg cells followed by RNA amplification using Ovation RNA-seq System V2 (Tecan, Manne ¨dorf, Switzerland), and cDNA library preparation using a NEB library preparation kit. Paired end 150bp sequencing was performed on a NovaSeq 6000 (Illumina, San Diego, CA). Samples were trimmed with fastp (version 0. 20. 0) using default parameters. Quantification was performed using Salmon (version 1. 4. 0) against a decoy transcriptome (Mus musculus Gencode version 21 or Homo sapiens Gencode version 29). Further analysis was performed in R (version 4. 1. 2) in R studio (version 2021. 09. 2 + 382) based on a pipeline described by Love et al.
78 Rarefaction was performed to ensure even sampling with sequences classified for taxonomic analysis by training a Naive Bayes classifier  79  using the SILVA reference taxonomy dataset  80, 81  (release 132, 16S only, 99%, majority taxonomy all levels, primer sequences as above). Differential abundance was tested with the ANCOM plugin,  82  which assumes less then 25% of features are different between conditions. Preceding differential abundance testing, taxa were collapsed to the appropriate levels. Features that were detected less than 10 times in total or features detected in only one sample were excluded from analysis. A pseudo count of 1 was added to enable log transformation required for ANCOM. LDA Effect Size (LEfSe) was performed using Galaxy developed by the Huttenhower group. 83.
Infect Immun 74, 5391-5396. 10. 1128/ IAI. 00848-06. Tecan, Manne ¨dorf, Switzerland SOURCE N/A Gad Frankel N/A Qiagen N/A This paper GEO: GSE208621 This paper SRA: PRJNA860604 Martin et al. of Crohn's Disease Lesions Identifies a Pathogenic Cellular Module Associated with Resistance to Anti-TNF Therapy. Cell 178, 1493-1508. e20. 10. 1016/j. cell. 2019. 08. 008. This paper N/A Philip Rosenstiel Aden, K. , Rehman, A. , Falk-Paulsen, M. , Secher, T. , Kuiper, J. , Tran, F. , Pfeuffer, S. , Sheibani-Tezerji, R. , Breuer, A. , Luzius, A. , et al. (2016). Epithelial IL-23R Signaling Licenses Protective IL-22 Responses in Intestinal Inflammation. Cell Rep 16, 2208-2218. 10. 1016/j. celrep. 2016. 07. 054. N/A N/A Graphpad RRID:SCR_002798 BD RRID:SCR_001456 FlowJo RRID:SCR_008520 Adobe RRID:SCR_010279 r-project.
Yet, binding of immature TpoR to full length CALR del52 also involves strong interaction between speci c residues of the N-domain and immature glycans on Asn117 (Figure  4E ). We sought to create a complete model of the tetrameric TpoR-CALR mutant complex using our structural data. We used AlphaFold 2. 0 16 to complete our modeling of TpoR to obtain the full extracellular domain of the receptor. TpoR monomers were dimerized through their TM domain with residue L508 in the interface as in the active con guration in presence of CALR del52 (Figure  3C-D ). CALR del52 dimers (Figure  3F ) were docked to dimers of TpoR through glycan binding domains and mutant tail based on experimental data and energy minimization. The nal structure places the mutant tail in a con guration where the main interacting sites are located around the 46 ED 47 motif, in line with our HDx-MS and functional results.
05 M K 2 HPO 4 , 0. 05 M KH 2 PO 4 with 30 mM TCEP, pH 2. 3) prior to injection into a pepsin column (Enzymate BEH Pepsin 2. 1x30 Column, Waters CAT. 186007233) with dynamic owrate of 150 -75µL/min. All mixes were performed automatically by a PAL-RTC robot station. Peptides resulting from the pepsin digestion were captured on a ACQUITY BEH C18 1. 7µM VANGUARD Pre-column (Waters Cat. 186009375), separated on a ACQUITY UPLC C18 1. 7µM 1. 0x100mm column (Waters Cat. 186002346) and electrosprayed into the Waters SYNAPT G2-Si quadrupole time-of-ight mass spectrometer. Measurements were performed in HDMSe mode with ion mobility. Lock mass correction was performed with infusion of leucine-enkephalin (m/z = 556. 277). The peptides were identi ed from triplicates using the PLGS3. 0 software (Waters).
The peptides identi ed were further analyzed with DynamX 3. 0 (Waters) using a tolerance of 10 ppm, a maximum length of 35 a. a. , a minimum products per amino acid of 0. 2 and requiring that each peptide was identi ed in 3 out of 3 replicates. All peptides were visually validated based on retention time, drift time and isotopic m/z. Data was statistically analyzed using Deuteros 2. 0 with peptide-level signi cance testing  31. Fourier Transformed Infrared (FTIR) Spectroscopy 0. 5 µL of sample was loaded on the diamond crystal of the ATR device of the FTIR spectrometer and quickly dried with a constant, gentle nitrogen ow: elimination of the water molecules prevents overlapping of the large water absorption peaks with the sample's absorption spectrum. After each spectrum, the crystal was cleaned with water.
Using a database of 50 protein containing as little fold redundancy as possible, an ascending stepwise method was applied to determine the protein secondary structure. It was demonstrated that three wavenumbers contain all the nonredundant information related to the secondary structure content. The standard error of prediction in cross-validation obtained using the 50-protein database was 5,7% for the α-helix and 6,7% for the β-sheet, 3. 2% for turns and 8% for random  32, 33.
Templates from AlphaFold2 and Rosetta Folding were used to effectively build the tetrameric 3D models and identify the interaction interface between the two CALR Del52 mutants. HDx-MS data was used to identify contacts between TpoR and CALR Del52 in the formation of the tetramer complex. The ER speci c G3M9 glycans of TpoR in contact to CALR were modeled with Glycopack 46 in the con guration consistent with NMR data  47  while the rest are of complex type, built in agreement with SAGS Database  48, 49. The HDx-MS identi ed contacts and the solid-NMR data on the TM region con guration of TpoR dimer were used as constraints in generating the overall 2CALR-2TpoR model. This glycoproteic tetramer was immersed into a full-atom representation of the environment -consisting in a lipid bilayer of 1607 POPC molecules accommodating the TM region of TpoR and in 409966 TIP3P water molecules and 63 Sodium ions describing the solvent region hydrating the rest of the tetramer.
This overall system consisting of ~ 1. 5 million atoms was subjected to a complete molecular dynamics cycle using OpenMM 50. First the system was minimized using L-BFG algorithm till a threshold of 1kJ/mole. Heating was then performed slowly over a 13ns period, from 0 to 300K in an NPT ensemble at 1 bar pressure and a membrane surface tension of 340 bar•nm using a Langevin integrator of 2fs timestep, with hydrogen bonds constrained in order to achieve this high timestep. Production was then continued for 20ns. Visualization & Analysis was performed using VMD 1. 9. 3 and in-house Python 3. 6 scripts, which use the MDTraj 51 library.
Cells were further centrifuged 5 minutes at 500g and re-suspended in lysis buffer (NP-  Comparison of the mean spectra recorded for each sample to analyse the protein secondary structure. Declarations Figures Each sample is identi ed by a unique color indicated in the legend. D. Secondary structure predictions using the method developed on our in-house database. The prediction is realized on each individual FTIR spectrum. The average and the standard deviation for the 5 spectra recorded for each sample is shown in this table. E-F. Top: Relative fractional deuterium uptake differential between the indicated species. The scale represents the relative differential of deuterium incorporation between the left and right species indicated. Regions in dark grey represents regions not covered by detected peptides at the given time point.
Acknowledgments We thank  Didier Colau  for his outstanding work in the production and puri cation of recombinant proteins used in this study,  Lidvine Genet  and  Céline Mouton  for expert technical support, and  Dr. Nicolas Dauguet  for ow cytometry assistance. We also thank  Jean-François Collet  and  Steve O. Smith  for their sound advices in the writing process of the manuscript. Funding to SNC is acknowledged from  Ludwig Institute for Cancer Research, Fondation contre le cancer, Salus Sanguinis and Fondation  " Les avions de Sébastien ", projects  Action de recherché concertée (ARC)   16/21-073  and  WelBio F 44/8/5 -MCF/UIG -10955. NP has received an  FSR PhD Fellowship  from  Université catholique de Louvain  and an  Aspirant PhD Fellowship  from the  FRS-FNRS, Belgium.
DNA Found in every living organism on Earth, DNA is a molecule that carries the genetic instructions for that organism. The sequence of molecules in DNA is unique to each species. we treated the tissue samples with chemicals to remove the DNA from the bacterial cells. Then we put the DNA in a machine called a sequencer, which can read the genetic information like a barcode. We then compared our DNA samples with a database of bacterial DNA, which allowed us to identify which types of bacteria were present in our samples  (Figure ).
Statistical analysis All statistics were performed as previously described using GraphPad Prism (version 5. 00 for Mac, GraphPad Software, San Diego, CA, USA)  [27]. Functional Enrichment Analysis (EA) was performed using the web utility, STRING (https://string-db. org/)  [34]. The STRING was also used for building the weighted proteins networks commonly modulated, rendered by Corel-DRAW2020 (Corel Corporation, Ottawa, Ontario, Canada). In order to perform t-Sne analysis, we used Morpheus, (https://software. broadinstitute. org/ morpheus). The coordinates T1 and T2 obtained by Morpheus were used in GraphPad) in order to represent the distribution of significantly expressed proteins graphically. A p-value < 0. 05 was considered to indicate a statistically significant difference between experimental and control groups.
1-OE cells (Supplementary Fig. 4B, C ). Significant upregulated proteins were uploaded into STRING database in order to evaluate Protein-Protein interactions (PPI). By showing a significant PPI enrichment p-value < 1. 0 × 10 -16 , 62 out of the 80 proteins were involved in the "regulation of biological processes" (n% = 82. 5, FDR = 0. 02; Fig. 3B ). Moreover, considering the knowledge on PPI, the 80 upregulated proteins were established in two main Clusters. The first cluster consisted of 37 proteins in red, 20 of which played a specific role in the "establishment of localization in cell" (n% = 54, FDR = 1. 31 -05 ; Fig. 3C ). The second cluster consisted of 43 proteins of which 10 involved in "cytoskeleton organization" process (n% = 23, FDR = 0. 01; Fig. 3D ). In addition, functional enrichment analysis of the 80 upregulated proteins revealed how they were involved in various biological processes among which the first significant 10 were "cell adhesion molecule binding" (FDR = 1.
mH2A1. 1 increases the methylation index and rewires energetic metabolism of MSCs Our proteomic analysis provides the first evidence on adenosylhomocysteinase (AHCY) overexpression in mH2A1. 1-OE cells. This data prompted us to examine the levels of S-adenosyl-methionine (SAM) and SAH in these cells. While SAM levels were not affected, SAH resulted significantly downregulated in mH2A1. 1-OE compared to CTL (p < 0. 01; Fig. 4A ), overall corroborating the abovedescribed AHCY upregulation. As expected, the SAM/SAH ratio was thus higher in mH2A1. 1-OE compared to CTL (p < 0. 01; Fig. 4B ), suggesting an increased in chromatin methylation in these cells. To confirm these data, we subsequently assessed the levels of 5-mC by flow cytometry. We detected an increase of 5-mC mean fluorescence intensity (MFI) in mH2A1.
Consistent with IKBIP overexpression, proteomic analysis revealed upregulation of factors involved in cytoskeleton organization and cell adhesion structures (vinculin, lamin-B1, Filamin A, αActinin-4 and 1, tubulin α, spectrin α chain, filamin C and cortactin) (dataset identifier PXD039866). We also reported downregulation of the histone H1. 4, associated to a strong interferon response when depleted, thus corroborating mH2A1. 1-induced inflammatory phenotype  [59]. Moreover, mH2A-mediated heterochromatin establishment is orchestrated in synergy with lamin B  [46, 47] , as supported by our data reporting lamin-B1 as one of the prominent upregulated proteins in mH2A1. 1-OE. Besides, we unveil the upregulation of epigenetic remodelers as AHCY and CBX3/HP1γ. AHCY is part of DNA methyltransferase 1 (DNMT1) interactome, responsible for the ex novo DNA methylation  [60] , a process generating SAH  [61].
1a , b and Supplementary Fig. 1 ), and were predicted to be deleterious. All were absent in public databases including gnomAD. LYN variant features, including amino acid conservation and pathogenicity predictions are detailed in Supplementary Table  1. Clinical and laboratory features of the three patients are outlined in Table  1. All three patients developed diffuse purpuric skin lesions (Fig. 2a, b ), fever, and increased C-reactive protein (CRP) within the first hours of life. Patient 1 and Patient 3 had hepatosplenomegaly, transaminitis, and severe thrombocytopenia. Patient 1 underwent a splenectomy for thrombocytopenia and developed leukocytosis, thrombocytosis, and persistent anemia post-splenectomy. At the age of 21 months, he also had transiently elevated circulating autoantibodies including ANA, anti-Sm, anti-SSA, anti-mitochondrial, and anti-phospholipid antibodies without clinical autoimmune manifestations.
Study participants All research investigations were done as part of protocol 17-I-0016/ NCT02974595 and as such were approved by the NIAID and NIAMS/ NIDDK Institutional Review Boards. The patients were referred to the NIH between 2013 and 2021. For Patient 3, the research investigations were also approved by the Institutional Review Board of the Second Faculty of Medicine, Charles University and University Hospital Motol. Written informed consent was obtained from the parents of all patients/healthy controls involved, and assent was obtained from the patients/healthy controls where indicated. The index patient was referred for unexplained systemic inflammation, and recurrent fever and rashes and underwent trio analysis at the NIH Clinical Center. The second patient was identified in Great Ormond Street Hospital for Children, London, UK and the third patient in the University Hospital Motol, Prague, Czech Republic.
Clinical, laboratory and imaging data and unstained slides from clinically indicated skin, gastrointestinal and liver biopsies were obtained and stained for research markers. The data collection period for some parameters is from birth to April 2022 for all patients. The NIH protocol enrolls parents and healthy siblings as controls. The control experiments were conducted with blood from the patients' parents and or controls from the blood bank approved under the protocol. The authors affirm that the patients (or their parents/legal guardians) provided written informed consent for publication of the images in Fig. 2  and Supplementary Fig. 2  and the medical information included in this paper. Dasatinib was initially provided to Patient 1 under a compassionate use protocol. Etanercept was provided to treat the three patients' clinical phenotype on an offlabel basis.
The absorbance was measured by ELx800UV absorbance microplate reader (Agilent Technologies). Serum IL-6 level was determined by routine in-house method (chemiluminescence), and the data were acquired using Immulite 2000 XPi (Siemens Healthcare, Erlangen, Germany). Normalization procedure: In order to plot patients 1, 2, and 3's serum markers IL-6 (Patients 1, 2, and 3), ICAM-1, L-selectin, E-selectin and lipocalin (Patients 1 and 3) on the same graphs, we normalized data using the 2. 5th and the 97. 5th percentiles for the healthy controls (HC) for the respective assays that were used. Normalized values depicted in the graphs correspond to the analyte concentration minus 2. 5%ile of HC, divided by the 97. 5%ile minus 2. 5%ile of HC, as follows: Normalized value = analyte conc: À 2:5%ile of HC 97:5%ile À 2:5%ile of HC Neutrophil characterization and functional assessment PMN surface antigen expression.