dataesr/scientific-paragraphs-categorization huggingface dataset:
3c   5B ). The same is true for AAs of HLA-DRB1 and HLA-DPB1, which can also explain residual C4independent association with eight independent AAs (HLA- Depicted are beta values from the logistic-regression analysis of three different models (blocks of rows, see "Methods"). All models contained sex and five genetic principal components as co-variables. Logistic-regression analysis for the first cohort additionally contained cohort as co-variable. Model b was also calculated separately for females and males. Models contain copy numbers as calculated from the imputed C4 alleles per individual as dosages. DRB1: 37SY, 58A, 74RL, 96E, and HLA-DPB1: 8, 76I, 91H, 96x) (Fig. 3d ). To complement our analysis, we repeated our search for residual C4-independent association to SSc, this time conditioning on the C4 genetic signal which was not derived from the expression dataset but from the first dataset as ten independent C4 eQTL signals as described.
Repeating the forward selection of AAs or classical HLA alleles conditioning on the ten first datasetderived independent C4 eQTLs signals resulted in four independent AAs from HLA-DPB1 (9F, 76I, 91H, 96x) or five independent alleles (HLA-DRB1: *11:04 and HLA-DBP1: *13:01, *26:01, *28:01, *30:01) (Supplementary Fig. 4D, E ) supporting the role of HLA-DRB1 and HLA-DPB1 as a C4-independent association.
DISCUSSION In this study, we found a strong association of low C4 and high HERV-K CN with SSc in two independent SSc datasets and their meta-analysis, supporting the protective role of C4 copies in IMIDs. C4A gene copies were slightly more protective than C4B as has been shown in SLE and SjS 28 but our data suggest a complex interaction of C4A and C4B CNs that has to be evaluated in the context of HERV-K copies and sex. We found that in SSc, an equal number of C4A and C4B gene copies grants more protection than (strongly) imbalanced numbers which we found to be a risk for SSc (Fig. 1b ). Our results might differ from recent observations in SLE and SjS where C4A and C4B copies have been described to act in an additive way, but the authors did not describe the interaction with HERV-K copies in detail  28.
Interestingly, it was reported that men had on average 27% more C4 protein per C4 CN than women and that this bias is stronger during reproductive years  28. While we found the difference between men and women to be smaller; men had on average 17% more C4 protein per C4 CN than women; we think our dataset confirms this finding and its timeframe (Fig. 2f ) reinforcing the role of C4 in the differential susceptibility between men and women observed in SSc. The deficiency of C4 may trigger an inappropriate clearance of apoptotic debris and stimulate chronic activation of myeloid cells. Also, it results in a defect to eliminate autoreactive B-cell clones, and a higher tendency to form self-reactive germinal centers  23  and has been previously associated with more severe SLE with earlier disease onset  44.
In this line it has been proposed that IFN-gamma increases the stability of C3 and C4 mRNA  46  and a recent expression analysis in SSc detected a strong IFN signature in a subset of patients  47. More than a third of more than 10,000 C4 eQTLs from the GTEx v8 database are associated with SSc (p GWAS < 10 -5 ) and C4 eQTLs alone can be used to explain most of the association of SSc within the MHC region, further supporting their importance in SSc. Interestingly, C4A-specific eQTLs can explain more SSc association than C4B-specific eQTLs (Supplementary Fig. 4B, C ), which supports a stronger role for C4A in SSc. While C4 eQTLs could in principle be associated with SSc by the strong linkage structure present in the MHC, our data suggest that C4 eQTLs, forward selected to explain expression variance in blood, can also explain most genetic association with the MHC.
Furthermore, we found that the C4-independent genetic association with SSc can be explained by 10 independent classical HLA-Alleles instead of AAs, seven of which overlap with a model of nine independent HLA-Alleles recently described  50  , which supports the independence of C4 and HLA associations with SSc. Our study has some limitations. First, the number of samples in the second dataset is very low in terms of GWAS. While we were able to replicate the association of C4A, C4B, and HERV-K CNs, replication of the most complex model was out of reach and needs to be the subject of further study. Second, we did not stratify the patients by clinical or serological subgroups. While our results on HLA-DRB1 AAs, being associated with SSc independently of C4 genetics, point towards anti-topoisomerase autoantibodies and probably diffuse cutaneous SSc, the topic is too vast to explore in this study.
Cohorts and datasets We (re-)analyzed two independent cohorts of European descent: First cohort: genome-wide genotyped data from 14 independent epidemiological cohorts comprising a total of 28,179 unrelated individuals (9846 SSc patients and 18,333 healthy subjects) from 10 European countries 6. To identify ancestry outliers ~100,000 quality-filtered independent SNPs were selected from each case-control GWAS cohort. Principal component (PC) analysis was performed using PLINK v1. 07. Samples showing >4 standard deviations from the cluster centroids of each cohort were considered outliers and removed from further analyses. The presence of relatives and/or duplicates was assessed by computing identity-by-descent (IBD) estimation using PLINK v1. 07. An individual from each pair of relatives (Pi_Hat > 0.
45) or duplicates (Pi_Hat > 0. 99) was removed. After exclusion of non-European samples, we recalculated genetic PCs using the merge of all imputed datasets, selecting ~100,000 independent markers using PLINK v1. 9. Missing data values due to the different platforms used for genotyping were corrected by PLINK v1. 9 (parameter -correct_for_missingness). We obtained informative principal components as the visualization of the first two PCs can be interpreted as a "map" of the European continent (Supplementary Fig. 1 ). Second cohort: this cohort included genome-wide genotyped data, whole blood expression data and blood serum C4 protein concentrations from 333 SSc patients and 524 healthy individuals from 9 European countries  39. This second cohort is a subset of a larger cohort of seven immune-mediated diseases plus controls described here  60.
C4 haplotypes. A set of 7021 SNPs TOPMed imputed SNPs were selected as they were (a) imputed in all individuals in both cohorts and (b) overlapped the C4 CN reference panel. C4 haplotype imputation was carried separately for both cohorts using the software imputec4  29  and https://github. com/freeseek/imputec4 and the reference panel downloaded from the dbGaP study accession: phs001992. v1. p1  28. Weighted imputation accuracy was calculated by multiplying r  2  Allele by Allele frequency in Supplementary Table  2B. C4 copy numbers. Each C4 haplotype carries a specific number of C4 isotypes (C4A, C4B) and HERV-K elements (Supplementary Table  2C ). We calculated total C4, C4A, C4B, and HERV-K CN dosages by multiplying the allele dosages of the structural haplotype by the number of copies of each C4 isotype and HERV-K that the haplotype contains.
For instance, the haplotype AL-BL contains one C4A gene and one C4B gene and two HERV-K copies. The numbers of short and long forms of C4A and C4B (AL, AS, BL, BS) per haplotype are self-evident for 17 of 29 imputed haplotypes. For the remaining, long and short forms were inferred by the consensus that ~95% of C4A is present in the long form  43, [68] [69] [70]. The haplotype AL-BS for instance can be coded as 0. 95 AL, 0. 05 AS, 0. 05 BL, and 0. 95 BS. CNs per haplotype can be found in Supplementary Table  2C. Classical HLA alleles and HLA amino acids (AA). Data for the classical HLA alleles and AA variants were obtained from the first cohort by imputation using SNP2HLA  71  and the reference panel from the Type 1 Diabetes Genetic Consortium  72  , described in ref. 50. After genotyping QC, all variants were imputed for each case-control dataset separately in the extended MHC region in chromosome 6.
Imputed data were also filtered for 95% success call rate for alleles and amino acids, deviation from HWE considering a P value of <0. 001 for SNPs in controls and 95% total call rate for individuals  50. Pearson correlation of C4 haplotypes and classical HLA Alleles Was calculated among the C4 haplotype dosages and the allele dosages from the HLA imputation. C4 copy number association analysis Logistic-regression models from simple to complex were calculated (using the function glm in R 4. 0. 3) to assess the association of total C4 dosage and its isotype dosages with the disease. We included cohort, five genome-wide principal components (PCs) and sex as covariates, assuming their effects were not collinear: (a) SSc ~C4 + HERV-K + PC1-5 + cohort + sex (b) SSc ~C4A + C4B + HERV-K + PC1-5 + cohort + sex (c) SSc ~C4A short + C4A long + C4B short + C4B long + PC1-5 + cohort + sex The number of subjects in our first cohort permits us to expand the simple additive model to a more complex one investigating the predictors that influence each other.
We included three twoway interaction terms in the logistic-regression model: (d) SSc ~C4A + C4B + HERV-K + PC1-5 + cohort + sex + C4A:C4B + C4A: HERV-K + C4B: HERV-K + C4A:sex + C4B:sex Meta-analysis was conducted with Metasoft 73 using data from model a, b, and c from both datasets.
centered on HLA-DPB1 and HLA-DRB1. Remaining MHC signal after conditioning on C4 genetics highlights HLA-DRB1 and HLA-DPB1 Having attributed most SSc association within the MHC to C4 genetics, we investigated which classical HLA alleles and HLA amino acids (AA) demonstrated C4-independent association to SSc. Conditioning on expression derived independent C4 eQTLs results in residual significance (P < 5 × 10 -8 ) for classical alleles and AAs of HLA-DRB1, HLA-DPB1, HLA-DPA1 and HLA-DQA1, HLA-DQB1, and HLA-B (Supplementary Dataset 2A, B). Forward selection to derive independent residual signals marked HLA classical alleles for HLA-DRB1 (*07:01, *11:03, *11:04, *13:01), HLA-DPB1 (*13:01, *26:01, *40:01, *06:01), HLA-DQA1 (*04:01), and HLA-DQB1*05:01. We tested if classical alleles and AAs of HLA-DRB1 and HLA-DPB1 alone could explain residual C4-independent association.
ACKNOWLEDGEMENTS We would like to thank  Guillermo Barturen Briñas  and  Elena Carnero-Montoro  for fruitful discussions and  Sofia Vargas  and  Gema Robledo  for their excellent technical assistance. We would like to thank  Elena López-Isac  for organizing all SSc GWAS datasets and all members of the  PRECISESADS consortium , especially  Ralf Lesche ,  Sepideh Babaei ,  Anne Buttgereit ,  Suzana Makowska  and  Martina Runge  for preparing the RNA Seq data and  Johan Frostegård  and  Jacques-Olivier Pers  for preparing and normalizing the serum C4 data. We greatly appreciate the patients and healthy donors for their essential participation in these studies. This work was supported by grant  RTI2018101332-B-100  funded by  MCIN/AEI/10. 13039/501100011033by  " ERDF A way of making Europe ",  Red de Investigación en Inflamación y Enfermedades Reumáticas (RIER)  from  Instituto de Salud Carlos III  ( RD16/0012/0013 ).
This work has received funding from the  Innovative Medicines Initiative 1 & 2 Joint Undertaking (JU)  under grant agreements No  115565  ( PRECISESADS ) and No  831434  ( 3TR ). The JU receives support from the  European Union 's  FP7 and Horizon 2020 research and innovation programs and EFPIA. MAH was supported by the  Juan de la Cierva Incorporacion program , grant  IJC2018-035131-I  funded by  MCIN/AEI/10. 13039/501100011033. This work is dedicated to the memory of  Annette Kerick  ( 1945-2020 ).
DATA AVAILABILITY Summary statistics of the SSc meta-GWAS are available through the NHGRI-EBI GWAS Catalog (https://www. ebi. ac. uk/gwas/downloads/summary-statistics): GCST009131. Data from the PRECISESADS consortium are hosted by ELIXIR Luxembourg https:// elixir-luxembourg. org/ and are available upon request. The access procedure is described on the data landing page (https://doi. org/10. 17881/th9v-xt85). All other data are contained in the article file and its Supplementary Information.
Indeed, as we can see in Figures 8 b1 and 8 b2, it is possible to confirm the presence of platinum in patient kidney biopsy. Such data can form part of the patient clinical file and help the clinician to assess the loss of kidney function. The first example concerns nanometer-scale systems developed recently for the treatment of various severe pathologies  [274, 275]. The characterization of such nanomaterials, which can contribute to both diagnosis and therapy, can be easily performed using synchrotron radiation-specific techniques  [276] [277] [278] [279] [280] [281] [282] [283] [284] , in order to determine their size  [276] [277] [278] [279] , their morphology  [280, 281] , the modification of their electronic state during the growth process  [282, 283] , or the adsorption process of molecules at their surface  [284, 285].
Acknowledgments It is a great honour to thank all the people who have played a significant role in building this interface between physics, chemistry and medicine:  Dr. X. Carpentier  ( Nice Hospital ),  Dr. Ch. Chappard  ( Lariboisière Hospital ),  Professor P. Conort  ( La Pitié-Salpetrière Hospital ),  Dr. P. Dorfmüller  ( La Pitié-Salpetrière Hospital ),  Dr. E. Estève  ( Tenon Hospital ),  Professor D. Hannouche  ( Lariboisière Hospital ),  Professor P. Jungers  ( Necker Hospital ),  Professor B. Knebelman  ( Necker Hospital ),  Dr. E. A. Korng  ( Lariboisière Hospital ),  Professor F. Liote  ( Lariboisière Hospital ),  Dr. M. Livrozet  ( Tenon Hospital ),  Professor M. Mathonnet  ( Limoges Hospital ),  Professor P. Méria  ( Saint-Louis Hospital ),  Dr. C. Nguyen  ( Lariboisière Hospital ),  Dr.
A. Somogy  ( SOLEIL Synchrotron ),  Dr. D. Thiaudière  ( SOLEIL Synchrotron ),  Dr. E. Véron  ( CEMHTI ) and  Dr. R. Weil  (LPS). This work was supported by the  Physics and Chemistry Institutes of CNRS  and by contracts  ANR-09-BLAN-0120-02 ,  ANR-12-BS08-0022 ,  ANR13JSV10010-01 , convergence UPMC  CVG1205 ,  Labex Matisse, Labex Michem  and  CORDDIM-2013-COD130042. The authors are grateful to the  SOLEIL Synchrotron Facility  and the  Leon Brillouin laboratory  for beam time allocation.
Ultra-low temperature cryoablation (ULTC) is a novel ablation modality aiming to combine the effectiveness of surgical lesion delivery with percutaneous safety to improve outcomes in catheter ablations of atrial fibrillation, particularly in persistent AF (PsAF). In the Cryocure-2 study (NCT02839304) 78 patients (56. 4% PsAF) received ULTC pulmonary vein isolation plus posterior wall ablation, and linear left and right atrial lesions as needed. The safety and acute success of ULTC appear consistent with current catheter ablation techniques and, together with Kaplan-Meier 85. 9% 1-year freedom from AF observed in Cryocure-2 PsAF patients, warrant further evaluation in larger clinical trials, which are currently ongoing. (.
These data prompted us to generate new lentiviral standards using a diploid cell line HCT116. Clones of transduced HCT116 cells with 1, 2, and 3 VCN were selected and used to determine the performance of several PCR methods used for VCN. Results demonstrate the superior performance of ddPCR over qPCR and helped to develop an improved VCN assay using a ddPCR method that specifically measures provirus integration and not plasmid contaminants. In addition, these new lentiviral standards were used to assess the sensitivity of ligation-mediated PCR (LM-PCR)-based method to determine vector IS and its limits as not all IS could be determined with equal efficiency.
Data processing and statistics To identify IS from sequencing data, raw reads from Sanger sequencing or from Illumina sequencing were first demultiplexed (cutadapt v2. 2) based on the sample TAG added during the nested PCR and both the LTR and the linker sequences were trimmed (cutadapt v2. 2). Resulting sequences longer than 20 bp and not containing the proviral or plasmid sequences were aligned on the reference genome (hg19, bowtie2 v2. 3. 4. 2) and insertion point inferred from the alignment coordinates. Reads mapping to the same IS were aggregated and the number of different sonication fragments was estimated using the sonic-Length method  [16]. Each IS was then annotated using the gencode database release 19. The availability of the code used for this study is subject to restrictions.
FUNDING The authors acknowledge funding from AFM/telethon, from Genopole ® and from grants from the french national research agency (ANR) (Biosupramol grant, ANR-17-CE18-0033-02 and RHU IRIS grant ANR-18-RHUS-0003) and from Région Ile-de-France (DIM-TG grant, IMAGINECR-20l8-02DlM).
Eligible women had singleton or multiple pregnancies, regardless of parity, gave birth to stillborn or live born babies by vaginal delivery, after a gestation of at least 22 weeks. In each case of PPH, the medical and/or surgical treatment and maternal outcomes were recorded. Blood loss was to be estimated at least visually. Professionals in each unit collected data prospectively for 6 months (1 February-31 July 2011). That study identified 3442 women with vaginal deliveries and PPH. In the third step, we analyzed only the 177 maternity units that had participated in both components of the HERA study (PPH incidence and protocol audit), described in steps one and two  [6, 25].
Additionally, women with a PPH > 500 mL (global PPH) were split into two subgroups: mild PPH (blood loss > 500 mL to 1000 mL or less) and severe PPH (blood loss > 1000 mL). The percentages are presented with their 95% confidence intervals (95%CI) and were compared with a Chi2 statistical test; means were compared with an Anova test. Crude relative risks (RRs) were calculated with their 95% confidence intervals (95% CI). A generalized linear model using Poisson regression was applied to adjust for confounding factors for each of our outcome measures, and adjusted relative risks (aRR) were calculated with their 95% CI. Significance was set at 0. 05. Data collection and analysis were performed with SAS software (version 9. 4, SAS Institute, Cary, NC, USA, 2002-2012).
Two research midwives trained in audit performance conducted the clinical audit. Of the 182 maternity units that participated in the HERA incidence study  [6] , 177 also participated in the second component of HERA, auditing the presence and quality of the contents of the protocols that these units used (for a participation rate of 97. 25%). This study covered 101,339 of all 309,532 French vaginal deliveries, and so accounted for around 32. 7% of the vaginal deliveries during the 6-month study period in 2011. This large database has contributed to the continuing debate on the best ways of addressing PPH and guidelines in high-income countries where it remains too often a preventable cause of death. The first limitation of this study is that caesarean deliveries were not included because of the different definitions of immediate PPH for vaginal and caesarean deliveries in the guidelines then in effect and thus in the HERA study: blood loss exceeding 500 mL for vaginal deliveries and exceeding 1000 mL for caesareans.
Since then, the updated 2014 French guidelines have clarified the definition of PPH for all deliveries (≥500 mL)  [26]. The second study limitation is that we unfortunately did not cover all French maternity units. In the HERA incidence study, private maternity units participated at a lower rate than the other types of hospitals, as did the units with the fewest deliveries  [6] ; these two groups overlapped, since most of the private maternity units in France are small. The slightly smaller number of maternity units participating in this study than in the HERA incidence study  [6]  did not modify the overall incidence rate of PPH after vaginal births in the entire cohort (3. 40% in this study vs. 3. 36% in the complete cohort). The last limitation is that the HERA study database does not contain data for the women without immediate PPH, so that blood loss could not be estimated for them.
Funding source Study was funded by the  "European and Developing Countries Clinical Trials Partnership" (EDCTP)  (Grant Nr:  RIA2020EF-2961 ), the  "West African Task Force for the Control of Emerging and Re-emerging Infectious Diseases" (WATER), and "Innovation in Laboratory Engineered Accelerated Diagnosis" (iLEAD)  (Grant Nr. OPP1214434/INV-009631 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed are those of the authors, and the funders are not responsible for any use that may be made of the information contained herein. This work was supported in part through  National Institutes of Health USA  grant  U01 AI151698  for the  United World Antivirus Research Network (UWARN). This article was supported by  WANETAM  as part of the  EDCTP program.
For example, the NAR TC-19 organizational system has now been integrated with the Tuberculosis Information System and sub-national information systems in Central Java, West Java and DKI Jakarta provinces. Therefore, Pusdatin is evolving to provide an integrated national reference point and governmental toolkit for public health which did not exist before, though some systems were tested for their cross-sectoral linking as case studies in previous years as part of zoonotic disease surveillance  (Setiawaty et al. , 2015). This caused an additional strain on resources and concerns over data quality  (Nashr, 2020; West Java Provincial Government, 2020). Secondly, the lack of trained staff was evident in provinces where data input was immediately needed. This occurred across different operational levels, including front-line and quality controller levels (MoH Indonesia, 2020a).
Thirdly, system interoperability due to institutional and geographical fragmentation remains critical for the Indonesian archipelago, where governmental agencies are often replicated across different locations. Thus, the independent creation of datasets can take place from different governmental departments, or from the same department across widely geographically disconnected regions. In addition, this fragmentation is reflected in the extant infrastructure, with some regions having much better-enabling capacities than others. This is most appreciated when a real-time collection of data is implemented, as slow access and electricity blackouts can disrupt the reporting (Internet Di Papua Mati, 2021; Taher, 2020).
Therefore, the Indonesian MoH regulated the COVID-19 laboratory testing quality standards from the outset (MoH Indonesia, 2020b). In order to include new laboratories in the COVID-19 testing network, subnational governments should propose a laboratory. An examiner then assesses it against MoH requirements and reports the outcome to the National Institute of Health Research and Development (NIHRD). Lastly, the NIHRD creates a network permit, allowing the said laboratory to input data into the centralized NAR TC-19 data system. A similar approach was used successfully in Indonesia for the establishment of a surveillance laboratory network for Avian influenza from 2014 onwards (Hartaningsih et al. , 2015).