dataesr/scientific-paragraphs-categorization huggingface dataset:
First, the items derived from the inventory were strongly correlated when images were acquired using different MR imaging sequences. These results are important since they suggest that the levels of items taken from this inventory in different centers and cohorts could be actually compared. Second, we observed that these imaging items were strongly related to the quantitative measures of lesions obtained using various algorithms and multiple data preparation steps. This demonstration was obtained after summing the different items of hyperintensities in the periventricular, deep, and superficial white matter that we compared to the global volumetric measures of lesions. Identical results were obtained after summing the superficial and deep atrophy items that we compared to the BPF. These results also suggest that such global scores of WMH or atrophy derived from the inventory tool could also be considered for estimating the total amount of white matter lesions or degree of cerebral atrophy across CADASIL patient groups.
This tool was proposed based on a real need to compare easily and quickly patients' imaging data across countries or cohorts. It was developed both by CADASIL and MRI experts of CSVD from data collected from over 600 individuals and 3 distinct cohorts with a large spectrum of clinical and cerebral manifestations. Its reliability was extensively assessed from multiple angles and the derived imaging items were found clinically relevant. The tool was particularly easy to use and fast and could provide directly different imaging items at the patient bed and for clinical research. Based on this inventory, a rapid and more massive combination of data could be envisaged in future research. Some refinements could certainly improve it further for investigating other rare CSVD or answering very specific questions.
The evaluation of lesions remains also dependent on the quality of data and resolution of images, particularly for PVS. Moreover, as the different items of the inventory tool were variously associated with the clinical manifestations of the disease, we could not provide immediately a "total score" of lesions related to the clinical progression of the disease from this inventory. The weights of its multiple items might be probably adjusted in future to obtain a global score of severity according to the aim and design of future studies. In the meantime, the results from our inventory can be easily transformed to the CSVD total score  31  or to the Fazekas score  20  when seeking for a simple comparison with the burden of lesions assessed in other databases or SVDs. In conclusion, we believe that the inventory tool developed and validated in the present study is a new instrument for CADASIL research.
Study Funding R. Zhang is funded by the China Postdoctoral Council (Grant no. PC2020117) and the National Natural Science Foundation of China (Grant no. 82101987). S-C. Tang is supported by the grant from the National science and technology council (NSTC) Taiwan (110-2314-B-002 -155 -MY3). H. Chabriat is supported by grants from the French Ministry of Health (Regional and National PHRC AOR 02-001) and Research (Agence National de la Recherche, ANR, RHU TRT_cSVD), Association de Recherche en NEurologie VAsculaire.
Acknowledgement We warmly thank the team in charge of formatting and cleaning the database using multiple information collected over 14 years from different sources and which made possible this study, particularly Professor Sylvie Chevret and Mrs Claire Pacheco (INSERM UMR1136). We thank very much to Dr Dominique Hervé and Nassira Alili who collected important clinical data for this study, Mr Abbas Taleb for collecting most of information along the cohort study, Mrs Sonia Reyes who is responsible for neuropsychological assessments, Mrs Aude Jabouley, Carla Machado who performed a large number of cognitive evaluation in the cohort, Mrs Solange Hello who managed and organized the appointment of multiple family members involved in the study, Mrs Nathalie Dias-Gastelier and Fanny Fernandes, the research managers in charge of the Cohort Study.
Quantitative imaging data COHORT 1: The segmentation of the whole brain tissue and the intracranial cavity (ICC) were obtained in processing T1w-MRI with ANTs (http://www. picsl. upenn. edu/ANTs). e6  The volume of WMH was calculated in each subject using the BIANCA (Brain Intensity AbNormality Classification Algorithm, https://fsl. fmrib. ox. ac. uk/fsl/fslwiki/ BIANCA) segmentation tool (using T1w and FLAIR as inputs). e7  For 78 patients with insufficient quality of results from BIANCA, the FLAIR images of each subject were further segmented with the Lesion Segmentation Toolbox in SPM12 by applying the best threshold to the probabilistic lesion map to derive the binarized WMH image (https://www. applied-statistics. de/lst. html). The segmented lesions of these patients were then visually checked and manually corrected by an experienced neuroradiologist (RZ).
Regulations and ethics This is a single-center cohort study with retrospective data collection. Patients included in this study received standard of care without any change related to the research. Patient data were handled in accordance with the French regulations (MR004 reference methodology). The study protocol was approved by the Research Ethics Committee of the French Society of Anesthesiology and Critical Care Medicine (CERAR), registered as IRB number 00010254-2021-124. The reporting of this study complies with the STROBE statement  [17]. The STROBE checklist is provided in Additional file 1: Table  S1.
Data collection Baseline covariates and follow-up of patients were collected retrospectively by medical record consultation and computer extraction of biological data. The following covariates were collected at baseline: age, height, weight (with calculation of body surface area according to Boyd's formula), sex, Simplified Acute Physiology Score (SAPS) II at ICU admission, history of chronic left heart failure, hypertension, previous sternotomy, chronic kidney disease, diabetes mellitus, indication for surgery, and type of acute heart failure at beginning of ECMO support. The following covariates were collected daily during the ICU stay: creatinine, total bilirubin, platelet count, ECMO output, ongoing renal replacement therapy (RRT), lactate, total epinephrine dose, total norepinephrine dose, and total dobutamine dose.
As for day 1 nested trial, treatment assignment of cloned copies of eligible patients is based on the treatment received the day of the emulated trial (blue rectangle) and baseline confounders for the second nested trial are measured on day 2. Follow-up is again restarted on the day 2 of the nested trial. Each of these nested emulated trials data is then stacked in a unique dataset, built with cloned copies of participants with assigned treatment, reset follow-up and baseline confounders in each nested trial. A multivariable Cox model is then fitted on the stacked cohort of observations and adjusted for confounders measured at ICU admission and at baseline of each nested trial (lactatemia, ECMO output, VIS, and SOFA score) rate indexed to body surface area, and VIS. SOFA score, ECMO output, lactatemia, and VIS were measured at baseline of each nested trial, all other covariates were measured at ICU admission or at beginning of ECMO support.
Outcomes Regarding the time to successful ECMO weaning, no statistically significant association with levosimendan treatment was found in univariable analysis (cause-specific hazard ratio HR = 1. 34, 95% confidence interval CI95 [0. 92; 1. 96], p = 0. 122, in the analog of the per-protocol dataset) in the cause-specific hazard model for competing risks. Likewise, in multivariable analysis, levosimendan was not associated with successful ECMO weaning (HR = 0. 91, CI95 [0. 57; 1. 45], p = 0. 659), see Additional file 1: Table  4. The effect of levosimendan on ECMO weaning success was also non-significant after exclusion of patients from 2016, (adjusted HR of 0. 73, CI95 [0. 44; 1. 21], per-protocol estimate). Sensitivity analysis with the subdistribution hazard competing risk model found in univariable analysis a statistically significant association between levosimendan treatment and successful ECMO weaning (subdistribution hazard  the previous analog of per-protocol estimate (HR = 0.
Our large cohort allowed us to introduce more explanatory covariates based on most recent literature  [2]  compared with previous studies. Our study also has some limitations. First, even if we used the target trial framework, the study gets some limitations due to its observational nature: data were collected retrospectively, available information restrain the possibilities to define eligibility criteria, and blinding could not be emulated (even if in the setting of this particular study, we would have expected a minimal risk of performance and information biases). Second, missingness was present. Nonetheless, the proportion of missing data was low, and we imputed these data with multiple imputation, in a way that takes advantage of longitudinal collection of the data  [33]. Third, although we estimated the association of levosimendan and ECMO weaning success adjusting on a large number of explanatory covariates, unmeasured confounders can still explain the observed estimates that would  have been absent in a randomized trial.
Conclusion Our study did not find an association of levosimendan administration and VA-ECMO-weaning or mortality in patients with refractory postcardiotomy cardiogenic shock. These results issued from one of the largest cohorts studied to date and the only one using the emulated target trial approach might cast some doubt on the efficacy of levosimendan. The comparison with the results of an ongoing interventional study (LEVOECMO trial, NCT04728932) for the same clinical question may help to resolve the current discrepancies in observational data.
These simulations are performed using MATLAB 2018b in 2. 50 GHz, i5, personal computer. To examine the proposed approach five different scenarios are considered to measure the optimal solution for the DNR and DG installation issues. The details of each scenario are as follows: • Scenario-1: Base case system without DG installation and DNR. • Scenario-2: The test system with only Installation of DG. --Round 1: DG Type-1 --Round 2: DG Type-2 Type-3) Installation after DNR. The solution for each scenario is derived from 100 iterations using an objective function designed to minimize APL and enhance the V p of buses, as defined in (4).
Materials A set of 178 banana individuals was first considered for this analysis (Supplementary data Table  S1 ). These individuals correspond to wild M. acuminata (A genome, 2n=2x=22), M. schizocarpa (S genome, 2n=2x=22), M. balbisiana (B genome, 2n=2x=22) and Australimusa spp. accessions (T genome, 2n=2x=20), to cultivars derived from these species, and to 12 synthetic F1 hybrids generated at the CIRAD breeding platform by crosses between parents also represented in the dataset (Supplementary data Table  S1 ). SNP-based genotyping data (not phased) of these individuals were extracted from a larger vcf file obtained from high coverage Illumina sequencing data used to perform chromosome ancestry painting, described in  (Martin et al. , 2023). SNP positions are located along the DH-Pahang V4 reference genome  (Belser et al.
, 2021). All used scripts are available in the vcfhunter toolbox (https://github. com/SouthGreenPlatform/VcfHunter). Compared to the original file, a new genotype calling was performed (using TotalRecal. 1. 0. py), for accession DB_Pisang_Awak that was tetraploid instead of triploid according to the  (Martin et al. , 2023)  analysis. Among the 178 individuals, 26 were similar to other accessions (i. e. somaclones or duplicates of other accessions). For these similar accessions (Supplementary data Table  S1 ), only one was reported in results tables. Representations of genome ancestry mosaic painting were.
Identification of potential parents-child trios through global SNP analysis This analysis was performed using the ValPar. py tool, added to the vcfhunter toolbox. The tool works as follows: (i) For each potential parent, all possible gametes were generated. These gametes were all combinations of k elements, with repetition and without order, sampled among n non-redundant alleles found at the studied position in the potential parent (k being the ploidy of the potential gamete). For example, for a position where a parent is  Table  S2 ). The filtered vcf contained 8 285 170 polymorphic sites. The statistic was calculated for each trio with a cultivated accession as a child (Supplementary data Table  S3 ). The following criteria were used to consider parental relationships as valid: (i) The proportion of sites in accordance with the tested parentage should be equal to or higher than 0.
Validation of parent-child duos through local SNP analysis along chromosomes Validation of parent child duos (Supplementary data The proportions of sites in discordance with tested parentages were represented along each chromosome and results were visualised using Circos  (Krzywinski et al. , 2009)  and the DrawCircos. py tool added to the vcfhunter toolbox. In silico chromosome ancestry painting of remaining haplotype(s) in polyploid progeny where complete genome restitution of a parent was identified The genotype of the parent was removed from the polyploid child in the vcf using the vcfRemove. 1. 0. py tool. Remaining alleles were considered as a haplotype, representative of  the gamete from the second parent. The in silico chromosome ancestry painting of the remaining haplotype(s) corresponding to the gamete from the second parent was performed using the ancestry specific alleles and the process described in  (Martin et al.
Management of aneuploidy The triploid Lady Finger (Nadan) accession had a supernumerary chromosome 08. To manage this aneuploidy, the genotype calling of Lady Finger along chromosome 08 was recalculated with a ploidy of 4 using the TotalRecal. 1. 0. py script of vcfhunter toolbox. For this accession, the analyses described previously (with exception of the global one) were performed separately on triploid chromosomes and on chromosome 08 and results were pooled. For tetraploid Calypso, aneuploid regions were identified by analysing read coverage of SNP sites along chromosomes, using the vcf2cov. py program added to the vcfhunter toolbox.
ACKNOWLEDGMENTS The authors thank the  CRB Plantes Tropicales Antilles CIRAD-INRA Guadeloupe France  and the  Bioversity International Transit Centre  (https://www. bioversityinternational. org/banana-genebank/) for providing the original plant materials,  Xavier Perrier  for contributing DNA;  Caroline Belser  for her contribution to the DYNAMO sequencing project;  Chantal Guiougou ,  Jean-Marie Delos  and  Jean-Claude Efile  for their contribution to banana crosses and embryo rescue, and  Françoise Carreel  and  Simon Rio  for critical reading of the manuscript. This work has been realized with the support of  MESO@LR-Platform at the University of Montpellier , the financial support of  CIRAD , and the technical support of the bioinformatics group of the  UMR AGAP Institute , member of the  French Institute of Bioinformatics (IFB) -South Green Bioinformatics Platform.
Downloaded from https://academic. oup. com/aob/advance-article/doi/10. 1093/aob/mcad065/7189797 by guest on 04 June 2023vcf file is available from https://banana-genome-hub. southgreen. fr/ in the Download section. Scripts were added to the vcfhunter toolbox (https://github. com/SouthGreenPlatform/VcfHunter). FUNDING This work was supported by the France Génomique (ANR-10-INBS-09-08) project DYNAMO, the Centre de coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), the Agropolis Fondation (ID 1504-006) "GenomeHarvest" project through the French Investissements d"Avenir program (Labex Agro: ANR-10-LABX-0001-01). Downloaded from https://academic. oup. com/aob/advance-article/doi/10. 1093/aob/mcad065/7189797 by guest on 04 June 2023.
Letter https://doi. org/10. 1038/s42255-023-00775-1 NAFLD animal models  11. Our study included 336 samples from patients with histologically characterized NAFLD derived from the European NAFLD Registry  12. The discovery cohort comprised 191 plasma samples and the independent validation cohorts included 115 serum samples together with 30 liver biopsies. Within the discovery cohort, 38. 4% were female, the average age was 55. 2 (±11) years, average body mass index (BMI) was 33. 5 (±6. 7) and 60. 7% had type 2 diabetes (Table  1  and Supplementary Table  1 ). Samples were processed for proteomics using the SomaScan v. 4. 0 platform, measuring 4,730 unique proteins and reads were corrected for sex, centre and T2DM (Extended Data Fig. 1 ). When stratifying patients on the basis of fibrosis stage (F), ranging from 0 to 4 and comparing advanced (F3-4) with mild (F0-2), we found 117 unique proteins (121 probes) to be differentially expressed (Fig.
Patient selection A total of 336 histologically characterized cases were derived from the European NAFLD Registry (NCT04442334); samples were collected as previously described  12. European White patients have been treated and diagnosed for NAFLD on the basis of histology at specialized centres including Angers and Paris (France), Mainz (Germany), Turin (Italy), Linköping (Sweden) and Newcastle upon Tyne (UK). The discovery cohort comprised 191 plasma samples and the independent validation cohorts included 115 serum samples and 30 paraffin liver biopsies sections (Table  1  and Supplementary Table  1 ). A subset of the discovery cohort, comprising 52 of these cases had frozen liver tissue available for RNA extraction. All liver samples were centrally scored according to the semiquantitative NASH-CRN Scoring System by an expert liver pathologist.
RNA-seq As previously described, mRNA was extracted from frozen liver biopsy samples and processed with the TruSeq RNA Library Prep Kit v. 2 and sequenced on the NextSeq 550 System (Illumina)  14. Data are available on the NCBI GEO repository (GSE135251). Raw sequencing quality assessment and alignment to the reference genome (GRCh38, Ensembl release 76) was done using Fastqc (v. 0. 11. 5) and MultiQC (v. 1. 2dev), and gene count tables were produced with HT-Seq. Counts were normalized using the trimmed mean of M values method and transformed using limma's voom methodology. A correction for centre, sex and batch was implemented. Pearson correlation was used to investigate linearity between hepatic mRNA and circulating proteins. A P < 0. 01 was considered significant. Tissue expression analysis was conducted using GTEx (https://gtexportal.
org/). Supervised analysis was done as previously described  14. Deconvolution to identify cell of origin was done using publicly available single-cell RNA-seq data (GSE115469) from liver samples obtained from neurological deceased individuals  13. The transformed normalized and cluster identifiers were obtained from the Human Protein Atlas (https://www. proteinatlas. org/). For each marker of interest, the Z score was calculated to visualize expression per cell cluster. The DAVID annotation tool was used for functional protein pathway enrichment on the basis of UniprotKB Keywords and Homo Sapiens background  20.
Statistics The Kolmogorov-Smirnov and Shapiro-Wilk normality tests, one-way analysis of variance with Dunnett's test, Chi-square, Mann-Whitney U-test and Kruskal-Wallis test with Bonferroni correction were performed in IBM SPSS v. s27 or GraphPad Prism 9. Binary logistic regression analysis was carried out in IBM SPSS v. 27 using Backward Stepwise Likelihood Ratio model including clinical parameters sex, age, BMI, ALT, AST, albumin, platelet count and T2DM, and the uncorrected values of the circulating proteins as measured by SomaScan identified as hepatic markers associated with F3-4 and NAS ≥ 4. The model identifying patients with NASH + F ≥ 2 + NAS ≥ 4 with at least one point deriving from each NAS component, and the FIB-4, NFS and FAST scores were calculated as follows: (1) Classification model = -6.
236112 + (0. 082163 × BMI) + (1. 110341 × T2DM) + (0. 001084 × A DAMTSL2) - (0. 000031 × CFHR4) + (0. 000060 × TREM2) + (0. 000048 × AKR1B10) (2) FIB-4 4 = (age (years) × AST (U l -1 ))/((platelets (10 9 per l)) × √ALT (U l -1 )) (3) NFS 4 = 1. 675 + 0. 037 × age (years) + 0. 094 × BMI (kg m -2 ) + 1. 1 3 × T2DM + (0. 99 × AST:ALT ratio) (0. 013 × platelet (10 9 per l)) (0. 66 × albumin (g dl -1 )) (4) FAST  7  = (e (-1. 65+1. 07×In(LSM)+2. 66×10 -  CAP3-63. 3×AST -1   )/ (1 + e (-1. 65+1. 07×In(LSM)+2. 66×10 -  CAP3-63. 3×AST -1   ) 1 -Specificity Receiver operating characteristic (ROC) analyses and AUC calculations were performed with IBM SPSS v. 27. Paired-Sample Area Difference under the ROC curve was used as statistical test. The binary cut-off for the classification model was set at greater than -0.
Acknowledgements This study has been supported by the  LITMUS (Liver Investigation :  Testing Marker Utility in Steatohepatitis ) consortium funded by the  Innovative Medicines Initiative  ( IMI2) Program  of the  European Union  under grant agreement no. 777377 , which receives funding from the  EU   Horizon 2020 programme and EFPIA ; the  Elucidating Pathways of Steatohepatitis consortium  funded by the  Horizon 2020 Framework Program  of the  European Union  under grant agreement no. 634413 ; the  European NAFLD Registry  and the  Newcastle National Institute for Health and Care Research Biomedical Research Centre. Q. M. A. is a National Institute of Health and Care Research Senior Investigator. by  SomaLogic, Inc. D. T. reports consultation fees from Histoindex Pte Ltd. M. E. is a member of the advisory board at AMRA Medical AB.
Results and discussion We did not detect change in the population status of the species assessed in 2004 and 2022 (Fig. 2 ), (Freeman-Halton extension of Fisher's exact test for RxC table: p = 0. 152; N = 131), including for a 2022 reduced dataset containing only the species listed in the 2004 assessment (p = 0. 826; N = 94). Since 2004, no species have had an improvement in population status from shrinking to steady (Fig. 2 ), even the shrinking species that were rediscovered after 2004 remain shrinking. This is supported by the observation that specimens occur in densities apparently lower than in the past, so that it is hard to consider them 'true' recoveries with the demographic potential to contribute to population expansions. Most of the findings were new discoveries at formerly unknown localities  10.
In addition, ex situ assisted reproductive technologies are being developed to preserve genetic diversity of some harlequin toads, for instance for Ecuadorian species  43. Various local initiatives have been initiated recently to conserve particular species through community-based Fig. 2  Harlequin toad population status 2004-2022. Change in population status of 131 Atelopus species over time, based on two standardized datasets with a span of more than 15 years between them. Not a single species has improved its population status. For details see Supplementary Table  1. conservation action and habitat protection  44, 45  , but their impact remains difficult to assess. The special role of ex situ conservation breeding. For highly threatened species, captive assurance populations are strongly recommended as a potentially powerful tool allowing for reintroductions once the threat(s) can be mitigated.