dataesr/scientific-paragraphs-categorization huggingface dataset:
After a 40% hemolysis level (observed on day 3), a rapid recovery of RBCs was evidenced after 10-16 days (Figure  1A ). Our 6-step model was applied to recapitulate this RBC recovery but, as expected, the recovery time exceeded 1 month, which was totally discrepant from the observed biological data (Figure  1A ). Indeed, different regulatory processes have to be considered for each compartment's cell dynamics. To determine these factors, biological data were requested.
These data collectively suggest that the decreased BM progenitor compartment sizes (but not involving increased proliferation, apoptosis, or egress to the spleen or blood), and the stable number of MEPs displaying a 2-fold increased proliferation in the BM and spleen, is related to a rapid differentiation process, in order to quickly compensate for the loss of RBCs through a versatile mechanism. The dynamics of progenitor compartments (determined using the BrdU data and compartment size) during the recovery from the PHZ treatment were analyzed at days 3, 5, 7, 10, 16, and 28 post injection. Recovery was almost effective in all compartments from day 7 to day 10 (Figure  1A ). On day 10, all compartments displayed a 2-to 3-fold increase in cell numbers before returning to normal values on day 28.
Data acquisition and/or analysis was performed on the Cochin Cytometry and Immunobiology Facility Cytometry analyses using a Fortessa cytometer (Becton Dickinson), and Kaluza software. To assess cell viability, surface labelled cells were resuspended in AnnexinV binding buffer, and AnnexinV (FITC) was added 15 min before analysis. The cells were then evaluated using a FITC-conjugated AnnexinV labeling detection kit (BD Pharmingen). The list of antibodies used for flow cytometry is provided in the key resources table above.
Cytokine bead array Sera were separated from blood cells within 2 hours of blood collection by 2 successive centrifugations, and were immediately frozen at -80 C. Twenty cytokines (G-CSF (CSF-3), GM-CSF, IFNalpha, IFNgamma, IL-1alpha, IL-1beta, IL-2, IL-2R, IL-3, IL-4, IL-6, IL-10, IL-12p70, IL-13, IL-17A (CTLA-8), IP-10 (CXCL10), MCP-1(CCL2), MIP-1 alpha (CCL3), MIP-1 beta (CCL4), TNF alpha) were measured simultaneously using a multiplex magnetic Luminex Assay (ProcartaPlex TM; ThermoFisher Scientific ) with the data read on a Bioplex MAGPIX Multiplex Reader (Biorad). All assays were performed in accordance with the manufacturer's instructions. Results were expressed in pg/mL and if levels were not detectable, as 50% of the lowest standard value.
Calibration of feedback parameters Values of the 13 parameters associated with the regulation functions (namely c, m r , m d , a i and b i ) were estimated from in vivo cell counts in the 6 observed cell compartments following PHZ administration (see  Figure 2). Note that our model has not been designed to encompass the effect of PHZ and the corresponding loss of erythropoietic cells observed during the first three days. Then we considered only data from day 3 and later. We added two artificial data points at days 70 and 90, accounting for a return to equilibrium after two months. Formally, parameters values have been chosen to minimize the residual sum of squares RSS = X i;j 0 @ x i t i j À X t i j x i t i j 1 A 2 (Equation  8 ) where x i and X i denote respectively the in silico and in vivo cell numbers in compartment i and t i j are the days when the cell numbers in the i-th compartment has been measured.
ACKNOWLEDGMENTS The authors are grateful to  Christine Chomienne (MD/PhD ,  INSERM U1131 ) for helpful discussions and assistance with editing the manuscript. The authors greatly acknowledge the  Cochin Cytometry and Immunobiology Facility  and the  IRSL Animal Facility, Universitede Paris  and also the support from  Plan Cancer   2014-2019  ( Mathematical Modeling of Myeloproliferative Neoplasms , M 3 PN). Supported by grants from the  INSERM  and INCa 2018 and fellowships from The  Research Ministry of China.
Study design and population We combined data from the 2010  29  and 2016  28  French National Perinatal Surveys (NPSs), which are routine, nationally representative surveys including all live and stillbirths in all maternity units in metropolitan, mainland France (n=535 in 2010; n=493 in 2016). In each survey, data were collected during 1 week. Data collection, performed by trained study midwives, included a face-toface interview of women prior to hospital discharge (2-3 days following birth) using a standardised questionnaire to obtain information related to sociodemographic characteristics and antenatal care and chart abstraction to obtain information on maternal and neonatal health and delivery. After combining data from both years, the survey sample included 27 828 women (n=14 681 in 2010; n=13 147 in 2016).
Though GWG differed between survey years, patterns of associations between GWG and maternal characteristics were similar regardless of survey year (data not shown) and we did not make inferences or conclusions about changes in GWG over time. Thus, for analyses of associations between maternal characteristics and GWG, data from the 2010 and 2016 surveys were combined and survey year was included in the models as a covariate rather than stratification variable. Due to the small amounts of missing data for covariates in the analytical sample (<5% of women missing data for any covariate included in the multivariable analyses), multiple imputation was not conducted. Covariates with the highest percentages of missing data were: maternal pre-pregnancy BMI (1%), employment during pregnancy (1%), education (1%), smoking status (1%) and diabetes (1%; not included in multivariable models).
Additional methodological strengths are the large sample size and low level of missing data (<5% in multivariable analyses). Our study has some limitations. Measurement error is possible as some data were self-reported and collected retrospectively. Specifically, self-reported pre-pregnancy weight and maternal weight at birth may be biased due to underestimation. 63 However, because reporting of weight gain during pregnancy in medical records is not standardised across France, the NPSs obtain this information through maternal self-report in order to have consistently collected and more complete data. While the resulting bias due to misclassification in measuring associations between GWG and adverse outcomes may be minimal, the impact of misclassification in examining risk factors for weight outcomes has not been evaluated.
Acknowledgements The authors thank the Maternal and  Child Health Service in each French district , the heads of the maternity units, the investigators and all the women who participated in the surveys. Contributors BB and CLR contributed substantially to the design and data acquisition of the  French National Perinatal Surveys. MH designed, and MA, CLR and JZ finalised the concept of the current study. MA conducted data analysis, interpreted the results and developed the draft manuscript under the supervision of CLR and JZ, and with input from BB, KC and MH. All authors critically reviewed and approved the final manuscript. Funding The 2010 and 2016 National Perinatal Surveys were supported by the  French Ministry of Health (Direction de la Recherche, des Études, de l'Évaluation et des Statistiques (DREES) ,  Direction Générale de la Santé (DGS)  and  Direction Générale de l'Organisation des Soins (DGOS) ; award/grant number N/A).
Enhancing rare variant interpretation in inherited arrhythmias through quantitative analysis of consortium disease cohorts and population controls A full list of authors and affiliations appears at the end of the paper. Purpose: Stringent variant interpretation guidelines can lead to high rates of variants of uncertain significance (VUS) for genetically heterogeneous disease like long QT syndrome (LQTS) and Brugada syndrome (BrS). Quantitative and disease-specific customization of American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines can address this false negative rate. Methods: We compared rare variant frequencies from 1847 LQTS (KCNQ1/KCNH2/SCN5A) and 3335 BrS (SCN5A) cases from the International LQTS/BrS Genetics Consortia to population-specific gnomAD data and developed disease-specific criteria for ACMG/ AMP evidence classes-rarity (PM2/BS1 rules) and case enrichment of individual (PS4) and domain-specific (PM1) variants.
Rare variant data from diagnostic sequencing of SCN5A (BrS) and KCNQ1, KCNH2, and SCN5A (LQTS) were provided by the different centers and curated based on the following canonical transcripts: ENST00000155840 (KCNQ1), ENST00000262186 (KCNH2) and ENST00000333535 (SCN5A). Details of all rare variants are provided in Tables S3/S4. Three additional arrhythmia-related data sets detailed in Supplemental Methods and Table  S2  were used for further analyses as described in Results. The gnomAD data set (version 2. 1) comprising 125,748 individuals with exome sequencing was used for population controls, with the following population-specific subsets used for the European and Japanese cases respectively: non-Finnish European (gnomAD-NFE) comprising 56,885 individuals and East Asian (gnomAD-EAS) comprising 9197 individuals.
, 2020; Mechanick et al. , 2020; Simonnet et al. , 2020)  which was not always included in the models, especially as body mass index is a frequent missing data in databases. Besides hypertension, diabetes mellitus, chronic kidney disease, and ischemic heart disease are other conditions frequently treated with RAAS blockers which were reported to be associated with poor outcome early in the pandemic. Diabetes mellitus was independently associated with death in several studies. Petrilli et al. (2020)  reported an adjusted hazard ratio (HR) of 1. 24 (95% confidence interval [95% CI] 1. 03; 1. 5) for mortality among 5279 COVID-19 patients including 35% with diabetes in the United States. Similar results were reported in other occidental cohorts  (Bravi et al. , 2020; Giorgi Rossi et al. , 2020; Iaccarino et al.
(2020)  reported that ACEI/ARB use was not significantly associated with a higher incidence of COVID-19 compared with other antihypertensive drugs  [adjusted HR, 1. 05 (95%CI, ]. In a case-control study conducted in South Korea using data from the Korean National Health Insurance System, 950 COVID-19 cases among 16,281 subjects with hypertension were retrospectively matched with 1,897 not infected controls, and multivariable-adjusted logistic regression demonstrated the absence of a significant association between exposure to RAAS-blockers and risk of ]  (Son et al. , 2020). Finally, in a large Israeli dataset of 14,520 individuals tested for SARS-CoV-2, of whom 1,317 were found positive, although ACEIs/ARBs were more frequent in positive cases than in negative cases, a multivariable logistic regression model found not significant association between the use of these medications and a positive result (adjusted OR = 1.
, 2020). Other studies restricted analyses to hypertensive patients  (Gao et al. , 2020; Pan et al. , 2020; Tedeschi et al. , 2020) , or reported results in the subgroup of hypertensive patients  (Andrea et al. , 2020; Richardson et al. , 2020; Trifirò et al. , 2020). Similarly, the vast majority of these studies found no association between RAAS blockers and outcome, and in hypertensive patients this was true in unadjusted as well as adjusted analyses. Trifirò et al. (2020)  analyzed the charts from 42,926 COVID-19 hospitalized patients by combining multiple Italian databases accounting for approximately a quarter of the Italian population. Almost 50% of the patients had at least one antihypertensive drug claim within 3 months prior to admission. Compared to calciumchannel blockers users, adjusted analyses showed no difference in the risk of death among ACEI (Hazard ratio (HR) 1.
Observational pharmaco-epidemiological studies are not suited to analyze the association between in-hospital exposure to RAAS blockers and outcome of COVID-19. The answer to this issue can only be provided by interventional randomized trials. It is very important to note that most meta-analyses to date meant to analyze the association between RAASblockers and outcome have incorporated studies based on in-hospital exposure  (Baral et al. , 2020; Flacco et al. , 2020; Greco et al. , 2020; Grover and Oberoi, 2020; Guo X. et al. , 2020; Mackey et al. , 2020; Pranata et al. , 2020; Zhang X. et al. , 2020) , so that their conclusions should be interpreted with great caution. 5 ), while results have been published for two trials. The BRACE-CORONA study (NCT04364893) enrolled 659 patients hospitalized with a confirmed diagnosis of COVID-19 from 29 sites in Brazil, with chronic use of ACEIs/ARBs and randomly allocated to continuing or stopping these treatments for 30 days  (Lopes et al.
, 2020). Results were presented at the European Society of Cardiology Congress in September 2020 and published very recently  (Lopes et al. , 2021). No difference was reported in the number of days alive and out of hospital at 30 days (primary outcome) between the suspending ACEIs/ARBs group and the continuing group. There was no difference in all-cause mortality at 30 days either  (HR 0. 97 (95% CI [0. 38; 2. 52) ]. An international randomized trial (REPLACE COVID, NCT04338009) was published in January 2021: 152 patients hospitalized for COVID-19 and receiving an ACEI or an ARB before admission were randomly assigned to continuation or discontinuation of this treatment. No difference in the primary endpoint assessing severity of disease course (a global rank score across four hierarchical tiers incorporating time to death, duration of mechanical ventilation, time on renal replacement or vasopressor therapy, and multiorgan dysfunction during the hospitalization) was observed between patients who continued or discontinued RAAS blocker therapy  (Cohen et al.
, 2021). The authors concluded that RAAS blockers can be safely continued in patients with COVID-19 requiring hospital admission. Clinical Trials: Randomized Studies on the Use of ARBs in Patients Infected With COVID-19 An even larger number of trials are testing the hypothesis that RAAS blockers, and in particular ARBs, might be beneficial in patients with SARS-CoV-2 pneumonia. We have identified 21 such trials, listed in Supplementary Table  5. For instance, two trials sponsored by the University of Minnesota (United States) are testing the efficiency of losartan in patients with COVID-19 either requiring hospitalization (assessing the respiratory severity at day 7, NCT04312009) or not requiring hospitalization (assessing the rate of hospital admission within 15 days of randomization, NCT04311177).
Other trials are focusing on elderly patients: two French trials are assessing the effectiveness of telmisartan in elderly hospitalized patients (COVID-Aging, coordinated in Strasbourg, evaluating the 2-week survival rate, NCT04359953) or in outpatients (COVERAGE, coordinated in Bordeaux, evaluating a composite of hospitalization or death at day 14, NCT04356495). Other ongoing trials worldwide are listed in Supplementary Table  5.
Clinical Trials: Randomized Studies on Discontinuation or Continuation of RAAS Blockers in Previously Treated Patients Hospitalized for COVID-19 As of January 2021, optimal management of ACEIs/ARBs in patients with a COVID-19 infection remains uncertain. Several trials randomizing COVID-19 patients previously treated with RAAS blockers and admitted to hospital for treatment continuation or discontinuation (ACORES-2 in France, NCT04329195; ACEI-COVID in Austria, NCT04353596; RASCOVID-19 in Denmark, NCT04351581; RAASCOVID in Canada, NCT04508985; SWITCH-COVID in Brazil, NCT04493359) are currently recruiting (Supplementary Table.
ELCAPA is registered at ClinicalTrials. gov (NCT02884375). In April 2009, the AFU published its first guidelines on treating prostate cancer in older men  [16]. We considered that it would have taken a further 12 months before the guidelines were considered during GAs. Hence, for this study (ELCAPA-26), we analysed patients with prostate cancer included in the ELCAPA study between April 2010 and November 2019. According to a previous study, the estimated prevalence of GDT among older patients with prostate cancer was 50%  [17]. To estimate this prevalence with an accuracy of 0. 05 and a two-sided type 1 error of 0. 05, we calculated that 384 patients would have to be included in our analysis.
Sensitivity Analysis We performed the analyses for each set of guidelines. Furthermore, we included the centre and the year of inclusion in the propensity score model, to account for differences in these variables. We also analysed the data regarding treatment intensity, clinical stage and geriatric risk profile (G8 score ≤ 14). A specific pseudopopulation was built (using SIPTW) for each sensitivity analysis. Lastly, we calculated the E-value to assess the effect of potential unmeasured confounding in the assessment of GDT. The E-value estimates the strength required by unmeasured confounders to explain away the observed effects  [33]. All statistical tests were two sided. The threshold for statistical significance was set to p < 0. 05. All statistical analyses were performed using Stata software (version 14.
Outside these centres, results might be worse. Third, unmeasured confounding was possible because of unmeasured variables or variables not included in our multivariable regression model. However, the estimated E-value showed that an unmeasured variable would have to be associated at a OR of 2. 82 or greater with clinical stage and GDT to explain away our findings. The probability of such a confounding variable is remote because the ORs for all the included risk factors in the bivariate analysis were lower than the calculated E-value. Lastly, data on the patient's preferences potentially a determinant in treatment selection were not collected. Our study also had strengths. First, we accounted for confounding and selection biases by applying SIPTW to propensity scores. Second, we evaluated three different sets of guidelines simultaneously; this may enable our findings to be more easily extrapolated to contexts in which these guidelines are employed.
Acknowledgments: The  ELCAPA Study Group consists of geriatricians (Amelie Aregui ,  Melany Baronn ,  Mickaël Bringuier ,  Eric Bouvard ,  Philippe Caillet ,  Gaelle Cosqueric ,  Lola Corsin ,  Tristan Cudennec ,  Anne Chahwakilian ,  Amina Djender ,  Eric Dupuydupin ,  Nargess Ebadi ,  Virginie Fossey -.
16 he development of a food fortification program requires detailed data on the consumption of the proposed fortification vehicle for appropriate micronutrient dosing. 11 These efforts should first be focused on the target population: lactating women for thiamine in Cambodia. There are limited data available on salt intake in Cambodia; therefore, the purpose of this study was to assess salt intake among rural lactating women in order to model a fortification scenario of thiamine in salt. Specifically, we assessed salt intakes using three methods: household salt disappearance, repeat 12-h observed-weighed salt and condiment intake records, and repeat 24-h urinary sodium excretions.
Materials and methods Various methods were employed to estimate salt intake. Salt use was estimated at the household level in the Household Salt Disappearance Study (Study 1), and salt intake was estimated among lactating women using observed-weighed intake records and urinary sodium excretions in the Maternal Salt and Sodium Study (Study 2). All participants were taking part in a randomized controlled supplementation trial with the primary aim of determining the daily dose of thiamine required by lactating Cambodian women to optimize milk thiamine concentrations (clinicaltrials. gov entry NCT03616288). 17 Full study details are published elsewhere,  17.
Sociodemographic characteristics Household characteristics and sociodemographic data were collected at 2 weeks postpartum, as part of the larger trial. 17 Data collected include education, daily per capita income, National Wealth Equity Index scores, household size, and maternal age. Education is reported as the highest education level attained by either the mother or father in the household. Daily per capita income was calculated from monthly income and household size, and then categorized based on the World Bank Lower Middle Income Class Poverty Line of $3. 20 USD/day. 18 Households were categorized into the National Wealth Equity Index quintile using the EquityTool survey, a standardized tool based on data from the 2014 Cambodian Demographic and Health Survey. 19 Household size was determined as all members ≥2 years old living and regularly consuming meals in the home, and maternal age was determined at 2 weeks postpartum.
These data are presented as the mean (95% CI) and median (IQR) over the 22-week study period. Repeat 12-h observed-weighed salt and condiment intake records. Weighed intake records are considered the most accurate and precise method of intake assessment, and observed-weighed intake records conducted by a trained field officer are recommended in low-resource settings where literacy rates may be low. 21 Twelve-hour weighed intakes were collected from each woman by a trained field officer on both data collection days. Net weights of meals and snacks prepared, as well as salt and condiment use, were determined by weighing cooking pots and condiment containers before and after food preparation (Amir Technology Co. Ltd; scales sensitive to 0. 1 gram). Maternal intake was estimated by weighing the dishes before and after consumption.
Net discretionary salt and condiment use at mealtime was also recorded. Meals were usually prepared fresh each day, as refrigeration is not common in rural Cambodian households; however, in the rare instance that foods were consumed, but not prepared, during the observation period (i. e. , leftovers), field officers recorded the net weight of the meal consumed and meal duplicates were developed at the end of the study to estimate intake. Descriptive statistics (mean (95% CI) and median (IQR)) were computed for daily unadjusted intakes of salt and condiments. Sodium intakes from soy sauce, fish sauce, and prahok were calculated using the Association of Southeast Asian Nations (ASEAN) Food Composition Database Electronic Version 1,  22  while sodium intakes from table salt and MSG were estimated using chemical composition.
Twenty-four-hour urinary sodium excretions. The gold standard for assessing population sodium intake are repeat 24-h urine collections, although this method cannot distinguish sources of sodium in the diet. 23 Field officers conducted home visits the day before data collection to provide verbal instructions on the 24-h urine collection procedure and to deliver urine collection materials. Participants were instructed to void their bladder the following morning and discard as usual, and then collect all urine voided up to and including the first void of the next morning. 24 Field officers collected these urine samples within 24 h of the final void, weighed the sample, and then mixed it thoroughly before collecting 2-mL aliquots for analysis. Samples were stored at -20 °C for ≤2 weeks before sodium measurement using ion-selective potentiometry (EasyLyte Na/K/Cl Analyser, Medica).
27, 29 The NCI method involves a one-parameter Box-Cox transformation, followed by a linear mixed effects model to estimate adjusted individual intakes, and back-transformation to the original scale. The adjusted estimates can then be used to plot the distribution of usual intakes in the population. 29 In this study, usual daily salt intake from all major sources (table salt, fish sauce, soy sauce, and prahok) was estimated with the NCI method using data from the repeat 12-h observedweighed salt and condiment intake records. This was decided a priori rather than 24-h urinary sodium excretions, as MSG is a known source of sodium in the diet and would be indistinguishable from sodium from salt in urine samples. Fortification scenario with modified EAR cutpoint method. The EAR cut-point method is a common approach to setting fortification targets.