dataesr/scientific-paragraphs-categorization huggingface dataset:
The final list of differentially expressed molecules in the model combines literature search and DEA outcomes. To calibrate the RA M1 and RA M2 macrophage models, we use the GSE97779 dataset, a publicly available microarray dataset from the GEO database  70. The dataset contains nine RA synovial macrophage samples from nine patients and five peripheral blood monocyte-derived macrophage samples from five healthy donors. We normalised gene expression using quantile normalisation and the preprocessCore package  71. We performed DEA using the Limma package  72  to identify the DEGs between RA and healthy samples. We filtered the DEGs using an adjusted p-value threshold equal to 0. 05.
/www. ebi. ac. uk/biomodels/login/auth: 1-Log in with username reviewerForMODEL2307180001 and password 8X9PYO to have access to the RA M1 macrophage model 2-Access the model at this link https://www. ebi. ac. uk/biomodels/MODEL2307180001 3-Log in with username reviewerForMODEL2307180002 and password Y3SIBT to have access to the RA M2 macrophage model 4-Access the model at this link https://www. ebi. ac. uk/biomodels/MODEL2307180002 and files generated are available at: https://gitlab. com/genhotel/Large_scale_computational_modelling_of_the_M1_and_M2_syn ovial_macrophages_in_Rheumatoid_Arthritis Models are available through a review account in BioModels https:/.
B. Atmospheric field The detector has been acquiring data for 55 days in an indoor location at CERN, at the ground level, as depicted in Fig. 8. The building has two floors and the experiment took place on the top one. The surface of the detector was covered with Al foils to shield the detector from visible light. The measured energy deposition spectrum is depicted in Fig. 9. Over that period, 1035 energy deposition events above 10 MeV were recorded. The measurement was benchmarked against the FLUKA Monte Carlo simulations, which contained a detailed detector geometry (Fig. 1 ) and neutron beam with the energy spectrum retrieved through the MAIRE toolkit, accounting for the local latitude, longitude and altitude  [25]. The simulation, however, did not account for the energy resolution of the considered detector, therefore the simulated energy deposition spectrum was convoluted (blurring) with the Gaussian profile whose variance was approximately equal to the variance measured for a monoenergetic beam.
It was considered to be constant over time and equal to the proportion of HCV-positive patients among all patients that passed through ward i in our database. For simplicity, the probability of correct infection control in equipment handling was assumed independent of the procedure type. Syringe reuse was taken as a proxy to estimate this probability at 97%, based on a study by Anwar et al. 20  which found that 3% of nurses from two hospital departments in Egypt and Saudi Arabia reused syringes between patients. Finally, to maximize statistical power in the identification of hotspots and at-risk profiles, we performed this individual risk assessment using the data from all 500 patients included in the IMMHoTHep study, irrespective of their HCV status upon admission, even though in reality the initially HCV-positive patients were not at-risk.
22 Explanatory variables included: age, gender, source of admission, patient localization, history of hospitalization, and hospitalization reason, previous anti-schistosomiasis treatment and history of multiple invasive procedures. A backward selection was performed to discriminate the best model based on the Akaike information criterion (AIC). Finally, using logistic regression, we assessed the capacity of a score based on the variables appearing in the best beta regression model to identify at-high-risk patients. We defined high-risk patients as those belonging to the upper 25% of the risk distribution (over the 75 th percentile). The training data was composed of 70% of the entire dataset whereas the other 30% was used for the testing dataset. If data unbalance was detected, up-sampling was used to equalise sample sizes for both groups.
HCV infection risk assessment The estimated per-procedure median risk of HCV infection due to contaminated equipment ranged from 1•961%% [IQR 1•339% -2•923%] for endoscopy up to 3•750% [IQR 2•566% -5•584%] for wound care (Supp. Fig. S1 ). The median patient HCV infection risk over the entire database was 0 •043% [0•026%-0•093%] (Mean: 0•114%, IC95% [0•091%-0•137%] ). This risk differed significantly between patient groups (p<0•001), with a greater risk of getting HCV infected in group 3 (median: 0•470%, IQR [0•081% -0•823%]) (Supp. Table  S1 ).
Given the similarities in the chemical shifts of αS oligomers and fibrils (PDB entry 2N0A (  16 )), we overlaid the structure of αS subunits in 22 different fibril structures with the cryoEM density of aS oligomers (Fig. S4 ). The 2N0A Greek key motif fitted the oligomer density (Fig. 1E ), and was observed in several independent protofilament subunits, including fibrils extracted from multiple system atrophy (MSA) patients (Fig. S4 ). In the Greek key motif of eight of the analyzed fibril structures, residues 71 and 92 face each other at < 10 Å distance (Cα to Cα) (Fig. S4 ). We tested whether this pattern is consistent with the oligomer structure by engineering a disulfide bond (design described in Methods) to covalently link these residues (Fig. S5A ). Oxidized V71C-T92C monomers assembled into oligomers identical in size, morphology, and secondary structure content to those of wildtype (WT) aS (Fig.
Acknowledgements: Authors thank the cryoEM  CNB-CSIC facility  ( CRIOMECORR  project  ESFRI-2019-01-CSIC-16 ), the services of the  CNB-CSIC Mass Spectrometry facility , the  Biomolecular mass spectrometry facility (UL)  funded by the  BBSRC  ( BB/M012573/1 ), the  Microscopy Services (UAB) , the  Laboratori de Luminiscència i Espectroscòpia de Biomolècules (UAB)  and the  Biophysical and Structural Chemistry Platform at IECB ,  CNRS UAR  3033,  INSERM   US001. We thank  James Ault  for technical support with HDX-MS experiments and  David Brockwell  for illuminating discussions on the P1 region of αS.
Funding:  Spanish Ministry of Economy and Competitiveness (MINECO)  grant  BIO2016-78310-R  and  BIO2017-91475-EXP  (SV)  Spanish Ministry of Science and Innovation (MICINN)  grant  PID2019-105017RB-I00  ( SV )  MICINN  grant  PID2019-105872 GB-I00  ( JMV )  MICINN  grant  PID2019-111068GB-I00  (AM)  ICREA-Academia 2015  (SV)  MICINN doctoral  grant  FPU17/01157  (JS)  Early  postdoc mobility project  SNSF   P2EZP2_184258  ( AL )  Basque Government  grant  IT1201-19  (FM)  BBSRC   BB/M011151/1  grant (EJB)  Sir Henry Dale  Fellowship jointly funded by  Wellcome  and the  Royal Society   220628/Z/20/Z  ( ANC )  Royal Society  grant  RGS\R2\222357  (ANC)  University Academic fellowship  from the  University of Leeds (ANC) Royal Society Research Professorship   RSRP/R1/211057  (SER).
Acknowledgements -We thank all families who participated in the study. - Mrs. Awa Dieye ,  Mrs. Nogaye Diouf ,  Mrs. Marema Ndiaye ,  Mr. Mame Thiano Seye  and  Mrs. Aissatou Gaye Fall , community health workers and matron at  Centre de Santé Dominique in Pikine , helped with the conduct of the field work and translations. - Chrissy Roberts  from the  London School of Hygiene and Tropical Medicine Global Health Analytics  kindly provided electronic data solutions.
Patients The current study used data from a pooled data set comprising patients with chronic hepatitis B who discontinued NUC therapy as part of studies or clinical practice in centers in Europe and Asia (the CREATE cohort). 2,10 Patients were eligible for the current analysis if they had been treated with only NUCs (no history of interferon add-on was allowed) and if they were (1) hepatitis B e antigen; (HBeAg) negative at the time of therapy initiation, (2) had undetectable HBV DNA at the time of therapy cessation, (3) had available information on HBV DNA and HBsAg levels at follow-up week 24 (FU W24), and (4) were still HBsAg.
Cohort Characteristics The CREATE database comprised data of 1241 patients who discontinued antiviral therapy; of these, 300 patients were excluded because of a positive HBeAg at baseline, 289 were excluded for missing data at FU W24, 126 were excluded because of clinical relapse or HBsAg loss before FU W24, and 51 patients did not have sufficient follow-up beyond W24 (Supplementary Figure  1 ). Characteristics of the patients included in this analysis and of those who were excluded for clinical relapse in the first 24 weeks after therapy cessation are shown in Supplementary Tables  1  and 2. This left 475 patients for further analysis, most of whom were previously treated with entecavir (54. 9%) and of Asian ethnicity (82%). HBV DNA levels at FU W24 were <100 IU/mL in 177 (37%) and >10,000 IU/mL in 82 (17%).
The full protocol is available at https://github. com/ganorlab/MIP_protocol. Library sequencing was performed by the Genome Quebec Innovation Centre on the Illumina NovaSeq 6000 SP PE100 platform. We used Genome Analysis Toolkit (GATK, v3. 8) for post-alignment quality checking and variant calling  36. We applied standard quality control procedures  37. In brief, only variants with minor allele frequency (MAF) of less than 1% and a minimum quality score (GQ) of 30 were included in the analysis. The average coverage for CTSB in cohorts sequenced at McGill was >4000X with 95% nucleotides covered at 30x (Supplementary Table  3 ). To analyze rare variants, we applied the optimized sequence Kernel association test (SKAT-O, R package)  38  with further meta-analysis between the cohorts using metaSKAT package  39.
Organoid culture, treatment, and imaging The patient derived iPSCs with SNCA triplication mutation (3xSNCA) and corresponding SNCA knockout (SNCA-KO) were previously described  44  and provided by Dr. Tilo Kunath. These cells were used to generate midbrain organoids following a protocol previously established in our labs  45, 46. Three months after organoid induction they were treated with either DMSO (vehicle) or 1 μM CA074me and treatment was maintained for 60 days. All organoids (12 per group) were fixed, cryo-sectioned, and prepared for immunofluorescence using antibodies against Map2, TH, α-syn and pSyn-129 as previously described  45. Verification of expression of TH and absence of α-syn in SNCA-KO in the organoids used in this study is depicted in Supplementary Figure  3. Images were acquired using the Leica TCS SP8 confocal microscope and image analysis was performed with an in-house developed script for quantification of immunofluorescent signal in organoids (https://github.
Spectra were matched against the human protein fasta database obtained from Uniprot(2022). Dynamic modifications were set as Oxidation (M), and Acetylation on protein N-termini. Cysteine carbamidomethyl was set as a static modification, together with the TMT tag on both peptide N-termini and K residues. All results were filtered to a 1% FDR. Pathway analysis of differentially abundant proteins was conducted using STRING  54.
Acknowledgements JJT is supported by a  Parkinson Canada  postdoctoral research fellowship. KS is supported by  Parkinson Canada Movement Disorders clinical fellowship. ZGO is supported by the  Fonds de recherche du Québec -Santé (FRQS) Chercheurs -boursiers award and is a  William Dawson Scholar. We would also like to thank all members of the  Fon and Gan-Or labs  as well as the  Neuro EDDU  for their support and scientific discussions that helped to shape this work. The access to part of the participants for this research has been made possible thanks to the Quebec Parkinson's Network (http://rpq-qpn. ca/en/). We would like to thank the participants in the different cohorts for contributing to this study. This research used the NeuroHub infrastructure and was undertaken thanks in part to funding from the  Canada First Research Excellence Fund , awarded through the  Healthy Brains, Healthy Lives initiative at McGill University, Calcul Québec and Compute Canada.
Funding This work was financially supported by grants to ZGO and EAF from the  Michael J. Fox Foundation ,  Canadian Institutes for Health Research  ( CIHR   FDN-154301  to EAF), the  Canadian Consortium on Neurodegeneration in Aging (CCNA) , and the  Canada First Research Excellence Fund (CFREF) , awarded to  McGill University  for the  Healthy Brains for Healthy Lives initiative  (HBHL). EAF holds a Canada Research Chair 1315 (Tier 1) in  Parkinson 's disease. The  Columbia University  cohort is supported by the  Parkinson's Foundation , the  National Institutes of Health  ( K02NS080915 , and  UL1 TR000040 ) and the  Brookdale Foundation.
Image analysis The acquired images were converted into the TIFF format and then analyzed using Qupath software version 0. 43  (Bankhead et al. , 2017). Nuclei were segmented using the StarDist extension  (Schmidt et al. , 2018). In immunofluorescence assays, a Qupath object classifier was used to identify and count the number of cells positive for CYP3A4, CK19, CD68 and/or vimentin per organoid for each condition. To assess fibrosis in each organoid, the total COL1 intensity was quantified and then calculated per nucleus.
The mass spectrometer was operated in NICI mode using methane as the ionization gas, with a pressure of 1. 5 × 10 -4 Torr. Data were obtained in full scan mode, with a mass range of m/z 50-600 amu. Fatty acids were identified on the basis of their retention time (R t ) vs. authentic standards and the corresponding specific [M-PFB] ion formed in the source. The peak area was integrated using MassHunter Workstation Software Qualitative Analysis (version B. 07. 00 for Windows, Agilent Technologies)  (Guillocheau et al. , 2019). Results were expressed as the mass of FAs divided by the cell count, after normalization against the area of the C17:0 internal standard.
Lipid staining and imaging Organoids were harvested and incubated in a solution of 1 μM BODIPY™ 493/503 (Invitrogen) diluted in PBS for 30 min at 37 • C, prior to fixation in 5% formalin. Stained organoids were mounted on a glass slide and imaged on a Leica DMI6000 Inverted Microscope with a Yokogawa CSU-X1 Spinning Disk Head and driven by Inscoper Imaging Suite (Inscoper, Cesson Sevigné, France). Images were captured at a magnification of 20× and analyzed using ImageJ FIJI software (version 1. 53). Total BODIPY™ intensity was quantified for each organoid and compared with the control conditions.
Treatments with drug compounds 5-Fluorouracil, carbofuran, and valproate were purchased from Tokyo Chemical Industry Co. , Ltd. (Tokyo, Japan). Paracetamol, troglitazone and voriconazole were purchased from Sigma Aldrich. Drugs were prepared in DMSO, and six serial ten-fold dilutions were prepared in culture medium. Troglitazone was tested at a maximal concentration of 0. 2 mM, on the basis of published data  (Allard et al. , 2021; Bucher et al. , 2018). Voriconazole, 5-fluorouracil and valproate were all tested at 2 mM, and acetaminophen was tested at 20 mM; this gave concentrations close to 100× the C max published in the literature  (Lazarus et al. , 2002; Porceddu et al. , 2012; Wy et al. , 2007). To evaluate drug toxicity, HML organoids were generated in 96-well round bottom ultra-low attachment plates.
Measurement of intracellular ATP The intracellular level of ATP was measured using the CellTiter-Glo® Luminescent Cell Viability assay (Promega, Charbonnières, France). In line with the manufacturer's instructions, control and treated organoids were incubated with the CellTiter-Glo® reagent for 10 min at room temperature. Cell lysates were then transferred to white multiwell plates, and the luminescence signal was quantified using a POLARstar Omega microplate reader (BMG Labtech, Ortenberg, Germany). The results were expressed as a percentage of the control value, and IC 50 values were calculated using GraphPad Prism software (version 8, GraphPad Inc. , La Jolla, CA, USA) with the same sigmoidal doseresponse regression model applied to each compound.
Determination of the BMD The viability data were evaluated quantitatively in a BMD analysis, using the PROAST package in R software (version 66. 20) on the EFSA's website (https://r4eu. efsa. europa. eu/app/bmd) and in line with the corresponding technical guidance  (EFSA Scientific Committee et al. , 2017). Based on the interpolation of a fitted dose-response model, the BMD approach estimates the dose associated with a small effect size. The BMD was estimated for a benchmark response of 5% and was reported as the lower confidence bound. The confidence interval for the lower bound was estimated using parametric bootstrap sampling (Table  1 ). Lastly, the BMD estimated from the viability assay data was used to rank the compounds by potency.
Next, 5-fluorouracil (5-FU), paracetamol, valproate, voriconazole or troglitazone was added to the medium from D7 to D14. Toxicity was assessed by measurement of the intracellular level of ATP. Using data from three independent experiments, the dose-response curves were modelled using the Hill slope function in GraphPad Prism software. tolerated; although elevation of the liver enzymes aspartate transaminase and alanine transaminase occurs in up to 70% of treated patients, this phenomenon is usually mild and transient  (Yaegashi et al. , 2020). Hence, our data suggest that obese patients with preexisting NAFLD might have a lower risk of 5-FU-induced hepatic cytolysis. Further investigations are required to confirm this hypothesis. Notably, 5-FU toxicity is favoured by deficiencies in dihydropyrimidine dehydrogenase (DPYD), the initial (and rate-limiting) enzyme in 5-FU catabolism  (van Kuilenburg, 2004).
However, data from microarray experiments on HepaRG cells (GSE102536 https://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE102536) showed that DPYD expression was similar in steatotic and non-steatotic conditions, whereas CYP2E1 expression was higher in steatotic cells and CYP3A4 expression was lower  (Bucher et al. , 2018). Similarly, mRNA expression levels of DPYD were similar in FA-treated and control pHHs; in contrast, expression levels of various genes related to metabolic homeostasis were higher in FA-treated pHHs  (Sullivan et al. , 2022). Hence, further mechanistic investigations are needed so that we can understand why 5-FU is less cytotoxic in steatotic HepaRG cells and HML organoids and establish whether this observation could be translated into the clinic. Lastly, our present results show that the antifungal voriconazole and the antiepileptic valproate had the same cytotoxic potential in steatotic and non-steatotic HepaRG cells and HML organoids.
Rationale & Objective: Outcomes of kidney transplantation for patients with renal AA amyloidosis are uncertain, with reports of poor survival and high rates of disease recurrence. However, the data are inconclusive and mostly based on studies from the early 2000s and earlier. Study Design: Retrospective multicenter cohort study. Setting & Participants: We searched the French national transplant database to identify all patients with renal AA amyloidosis who underwent kidney transplantation between 2008 and 2018. Exposures: Age, cause of amyloidosis, use of biotherapies, and C-reactive protein levels. Outcomes: Outcomes were all-cause mortality and allograft loss. We also reported amyloidosis allograft recurrence, occurrence of acute rejection episodes, as well as infectious, cardiovascular, and neoplastic disease events.
Patients To identify all patients with AA amyloidosis who underwent kidney transplantation during the period of interest, we searched the French national transplant database CRISTAL (Agence de la Biom edecine) using the criteria "nephropathy = amyloidosis" and "transplantation period = 07/ 01/2008-06/30/2018". We then contacted each transplant center, and medical records of identified cases were reviewed. Inclusion criteria were age of at least 18 years at the time of transplantation, a diagnosis of AA amyloidosis nephropathy, and a kidney transplantation during the period of interest. Renal AA amyloidosis diagnosis was confirmed histologically by a kidney biopsy or by the presence of AA amyloid deposition in another tissue and the coexistence of nephropathy. Exceptions were made for cases of proven FMF with a history of progressive proteinuric kidney disease without another plausible cause.
Data Patients' medical files were examined retrospectively, and data were recorded anonymously regarding initial characteristics, characteristics of transplantation, and outcomes after transplantation. Initial characteristics such as demographic data, C-reactive protein (CRP) level at the time of transplantation, cardiovascular disease and diabetes, cause of AA amyloidosis, etiologic treatments before transplantation, duration of dialysis, and number of prior transplantations were recorded. Characteristics of transplantation included combined transplant, type and age of the donor, cold ischemia time, immunologic characteristics (presence of anti-human leukocyte antigen antibodies and anti-human leukocyte antigen donor-specific antibodies), and immunosuppressive regimen. Outcomes after transplantation included all-cause mortality and graft failure at 1 and 5 years; occurrence of a biopsy-proven acute graft rejection, an infection requiring hospitalization, an opportunistic infection (according to the definition by Fishman et al in 2007  21, 22  ), cancer, or a cardiovascular event (myocardial infarction, acute congestive heart failure, pulmonary embolism, ischemic stroke) during follow-up and the time of occurrence for each event; urinary protein-creatinine ratio (UPCR) and glomerular filtration rate estimated by the MDRD (Modification of Diet in Renal Disease) Study formula at different times (3 months, 1 year, and 5 years after transplantation and at last follow-up); and CRP levels annually during follow-up.
8%). These data support the practice of kidney transplantation for patients with AA amyloidosis who experience kidney failure. as a surrogate marker because its reliability in the scope of amyloidosis has been established. 23, 24  Administration of a biotherapy was also recorded. Immunoprophylaxis varied according to each center's practice. In regard to pneumocystosis prevention, the general strategy was to prescribe cotrimoxazole for a minimum of 12 months in the absence of adverse effects; the drug was then continued or stopped depending on the physician's preference. There was no uniform protocol among the different centers in regard to cytomegalovirus prophylaxis. During follow-up, kidney graft biopsies were performed according to each local center's practice. There was no systematic biopsy during follow-up at some centers, whereas others performed protocol biopsies at 3 months after transplantation, at 12 months after transplantation, or both.
Statistical Analysis Quantitative data are presented as medians and IQRs. Categorial data are presented as counts and percentages. Survival functions of time-to-event outcomes were estimated using the Kaplan-Meier estimator (for mortality) or the cumulative incidence function method (for graft loss) and compared using the log-rank test or Gray's test, respectively. Missing data were not imputed, and the proportions of missing data are shown in the tables. Factors associated with patient survival and death-censored graft survival were investigated using a Cox proportional hazards model and a cause-specific hazards model, respectively. Studied factors were selected among initial characteristics for their clinical relevance. A P value <0. 05 was considered statistically significant. All statistical tests were performed using R software (version 2020; R Foundation for Statistical Computing).