dataesr/scientific-paragraphs-categorization huggingface dataset:
Interestingly, a study on early-life body shape in Hispanic women in the US  43  showed that, while changes in silhouettes was not associated with risk of premenopausal breast cancer risk, an negative association was observed with changes in weight at ages 10, 15 and 20 (heavier/same/lighter than peers) and that this association tended to be stronger in US-born than in foreign-born women. Thus, the absence of associations in Latin American women  could indicate that the influence of early-life body size on breast cancer risk varies between populations, or could also suggest that the silhouette scales, although validated in European  15  and North American 16 populations, might not be a tool fully adapted to other populations. The three trajectories that we obtained between childhood and early adulthood are comparable with some of the five trajectories obtained from the data of the CAMA study (groups 2, 3 and 4).
Acknowledgements The author wish to thank the substantial support provided by the research nurses and health workers as well as  Tracy Lignini ,  Dacia Cristin ,  Cecile Le Duc ,  Jordi de Battle , and  Talita Duarte-Salles ,  Ana Cristina Ocampo  for the logistic and data basis development, and  Vivian Viallon , who provided statistical support. The study is funded by the  International Agency for Research on Cancer (IARC) , the  Union for International Cancer Control (UICC) , the  Pan American Health Organization (PAHO) , the  Ibero-American Programme for the Development of Science and Technology (CYTED) ,  COLCIENCIAS  (grant  n°1115-569-348899 ),  Universidad de Antioquia  (grants  CPT-1801 ,  SIIU-2019-25272  and Estrategia de Sostenibilidad 2013-2014 to Group Infection and Cancer). For MH, the work reported in this paper was undertaken during the tenure of a postdoctoral fellowship awarded by the  International Agency for Research on Cancer , financed by  La Ligue  contre le cancer.
In patients with acromegaly, an increased risk of vertebral fracturas and controversial data on BMD has been reported. Areal dual-energy x-ray absorptiometry (aDXA) does not capture bone quality or discriminate trabecular and cortical compartment. Recent advances in DXA include software to estimate index of bone microstructure in lumbar spine: Trabecular Bone Score (TBS) and volumetric bone mineral density (vBMD) from hip aDXA scans (3D-DXA). We aimed to explore the hypothesis that TBS and 3D-DXA would be useful in the bone evaluation of patients with GHD and acromegaly. We performed a cross-sectional study in 15 patients with GHD and 20 with acromegaly and we compared TBS values (TBS insight® software) and trabecular and cortical vBMD, cortical surface (sBMD) and cortical thickness (3D-DXA SHAPER software) with 34 age-and sex-matched healthy controls.
Acknowledgements Mass spectrometry was performed at the  ZMBH Core facility  for mass spectrometry and proteomics in Heidelberg. We thank  Ulrike Engel  and  Christian Ackermann  from the  Nikon Imaging Center Heidelberg  for their support in microscopic imaging, AG  Stefan Herzig , and  Thomas Fleming  for assistance with Seahorse XF96 Analyzer and  Ulrike Ganserer  for performing electron microscopic imaging. We are also grateful to  Sina Barysch  for stimulating discussion. This work was funded by the  German Research Foundation (DFG, Deutsche Forschungsgemeinschaft ) -Project-ID  314905040 -TRR 209. Open Access funding enabled and organized by Projekt DEAL.
Study population In this international study, we assessed 17 139 patients from the COPD Cohorts Collaborative International Assessment (3CIA) initiative. All were prospective cohorts that recruited patients within the period 1999 to 2017, except for one which was a population-based cohort. All patients had a definition of COPD characterised by spirometry, that is post-bronchodilator FEV 1 to forced vital capacity (FVC) ratio <0. 7 and a clinical diagnosis of COPD. Spirometry was performed using the standards provided by the American Thoracic Society and European Respiratory Society  [13]. The primary investigators of each of the participating 3CIA cohorts provided individual patient's data for pooled analysis. We obtained a minimum individual dataset including the vital status (up to death, right truncation or 2017), age, sex, smoking status, pre-bronchodilator and post-bronchodilator FEV 1 and FVC, and dyspnoea measured with the modified mMRC, among others  [14].
Only in a number of 3CIA cohorts were data of number of exacerbations in the previous year available. For the current study, we selected exclusively those cohorts in which the number of exacerbations in the previous year were available in the database, since this variable is required to calculate the GOLD 2015 and 2019 grading systems. Fifteen out of a total of 22 cohorts contained data on history of exacerbations, so that the final number of patients available to be classified according to GOLD 2015 and GOLD 2019 was 8823. Symptoms were assessed using the mMRC dyspnoea scale. To determine the risk descriptor in the 2015 grouping system, we used exacerbations history and GOLD spirometry stages. The combination of symptoms (mMRC) and the worse risk descriptor (spirometry or exacerbation history) were used to classify patients by the GOLD 2015 system.
Statistical analysis The 3CIA database manager quality-controlled all data centrally and created a clean database with a data dictionary. All implausible or missing variables were queried with the original study investigators, and data were removed from the central database if errors could not be corrected. Because the cohorts had different follow-up times, patients were right-censored at 5 years of follow-up. Descriptive statistics used mean and standard deviation for continuous variables and the number of cases and percentages for categorical variables. Comparisons between groups were performed with the Chi-squared test for categorical variables and the t-test for continuous variables. We estimated 5-year all-cause mortality, according to GOLD 2015 and 2019 staging systems, using Kaplan-Meier survival statistics.
Acknowledgements We are grateful to the pet owners for giving us their permission to sample their pets. We thank all veterinarians that helped us with sampling, particularly  Corentin Buisson ,  Julie Roggy  and  Maud Walliang  for their important contribution to the sample collection and database. We thank  Dr. Thierry Buronfosse  for the kind gift of pre-pandemic sera. We also thank  Kurt McKean  for English editing of the manuscript (https:// octopusediting. com/).
Funding The study was funded by  OIE  through the  European Union   EBO-SURSY  project, the  French National Agency for Research   EBOFAQ  project ( ANR-14-EBOL-003-01 ) and  IDEXLYON  project of  Université de Lyon  as part of the " Programme Investissements d'Avenir"  ( ANR-16-IDEX-0005 ). This work was supported by  French  state funds managed by the  French National Agency for Research (ANR)  within  Programme Investissements d'Avenir, Institut Hospitalo-Universitaire FOReSIGHT  ( ANR-18-IAHU-0001 ) and  Institut de Recherche pour le Développement (IRD).
641, a = 270 (V•nC) -1 , b = 108 Hz, d = 0. 154 s, ω = 0. 9, J N = 0. 2609 nA and I 0 = 0. 3 nA. Each simulation was run for 120 s with time steps of Δt = 1 ms, using a Euler integration scheme. Simulations were run with scripts written in Python.
This work was supported by  Fondecyt  Grants  1181076  (to PO) and  1201822  (to WeD), excitability. The  Centro Interdisciplinario de Neurociencia de Valparaı ´so (CINV)  is a  Millenium Institute  supported by the  Millennium Scientific Initiative (ANID). SC was funded by  Beca Doctorado Nacional   ANID 21140603  and by  Programa de Doctorado en Ciencias, mencion Neurociencia ,  Universidad de Valparaı  ´so. DB acknowledges support from the  EU Innovative Training Network "i-CONN"  ( H2020 ITN 859937 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Analysis of the gingival microbiome/virome data revealed that there is a significant increase in viral content and diversity in Fig. 1  Mouse infection and oral sample collection timeline. Eight polymicrobial infection sessions were carried out once per week from the 3rd to the 10th week. Oral swab samples were collected on the day before antibiotic treatment, the day before infection and at 1, 4, and 8 weeks following the initial infection. Blood and tissue specimen collection was performed at euthanasia following 8 weeks of infection. response to the polymicrobial infection in mice (Fig. 6 ). Although, the bacterial content and diversity was not significantly different. Specifically, the polymicrobial infection group had similar bacterial reads (panel a, p value 0. 92) but significantly more virus reads (panel b, p value = 0.
2  A polymicrobial oral infection can be successfully obtained in a common mouse strain. Oral swab samples were collected from the teeth, oral mucosa, and gingiva of mice with micro cotton tip swabs to evaluate microbial status of the polymicrobial infection model. DNA was isolated and purified from the swab samples, which were collected at different time points (baseline 1; before infection and before an antibiotic wash out; baseline 2; before infection and after an antibiotic washout, and 1, 4, and 8 weeks after infection) and then the four periodontal pathogens (P. gingivalis, T. denticola, T. forsythia, and F. nucleatum) and total bacteria were quantified by standard real-time PCR using primers corresponding to 16S ribosomal RNA. a-d The data are shown as a percentage of each pathogen among total bacteria; mean ± s.
Another virome study in humans with limited periodontal samples identified a new family of redondoviridae associated with periodontal disease  31. Taken in aggregate, Fig. 4  Alveolar bone loss is significantly increased with the polymicrobial infection. a Representative images of alveolar bone loss on the palatal surfaces of maxillary molars in control and infection groups. Scale bar represents 0. 2 mm. b The graphs represent alveolar bone loss in control mice or mice with the polymicrobial infection (Infection). Data represent the means ± s. d. from six mice per group. For each mouse, alveolar bone loss was calculated as the average from 28 sites (3 sites on the first molar, 2 sites on the second molar, and 2 sites on the third molar, on both sides of the left maxilla and mandible). *, the difference in alveolar bone loss was significant (p < 0.
The amplification was conducted using a QuantStudio 3 Real Time PCR system (Thermo Fisher Scientific) with a final reaction volume of 20 μL that included the PowerUp SYBR Green Master Mix (Thermo Fisher Scientific), DNA (15 ng/ μL), and primers. The optimized thermal cycling conditions were as follows: 95 °C for 10 min followed by 50 cycles of denaturing at 95 °C for 15 s, annealing and extension at 60 °C for 1 min. The melt curve protocol followed with 15 s at 95 °C, and then 60 °C for 1 min and 95 °C for 1 s. Data were analyzed using QuantStudio TM Design & Analysis Software v1. 4. 3 (Thermo).
Shotgun sequencing and microbiome/virome data production and analyses The gingiva of 12 mice (6 controls and 6 infected) was collected and used for DNA extraction and isolation using the QIAamp ® DNA Mini kit (Qiagen, Germantown, MD, USA) according to manufacturer's instructions. DNA purity and quantity was deemed suitable and met quality control measures for standard shotgun sequencing by Novogen, Inc. (en. novogene. com). Shotgun metagenome sequencing library preparation has been done by Novogen, Inc. and libraries have been sequenced on Illumina Hiseq4000 machines. FASTQ files were generated from the sequencing machines and used for the analyses of the microbiome and virome as described below.
Outcomes evaluation Preoperative data were collected in electronic records and included medical history, 3-day bladder diary, and urodynamic results. Data about intervention were retrieved from electronic chart including date, type of anaesthesia and dose of toxin. After first injection or after switch to a higher dosage of BoNT-A, all patients were scheduled for a postoperative visit at day 10 for evaluation of urinary flow rate, and post-void residual estimation. If post-void residual volume was higher than 200 mL, patients were asked to perform CISC. Efficacy was estimated at 6 weeks based on a 3-day bladder diary. In case of failure, a repeat injection of the same toxin at a higher dosage (500 U after 250 U and 750 U after 500 U) was proposed at least three months after the first injection.
Statistical analysis Time to discontinuation and failure were calculated from the moment of the first botulinum injection until the last injection plus 6 months. Discontinuation-free and failurefree survivals were estimated using Kaplan-Meier analyses. Statistical analysis was performed using McNemar's test and Khi 2 test for all qualitative variables and Wilcoxon test for paired values of quantitative data. A P-value < 0. 05 was considered significant. Statistical analysis was performed using GraphPad Prism5 software.
Background: Cervical arterial abnormalities are associated with intracranial aneurysm but their frequency and association with outcome in case of aneurysmal subarachnoid haemorrhage (aSAH) remains unknown. Methods: Data were retrospectively extracted from a prospective database. Consecutive angiographies of aSAH patients on a 13-month period were reviewed as well as consecutive angiographies of SAH patients without evidence of aneurysm on a 20-month period. Occurrence of secondary neurological complications was collected with 3-month functional outcome (modified Rankin Scale ! 3 was considered as poor outcome). Cervical arterial abnormalities on angiographies were classified into two subcategories: trajectory and lumen vessel abnormalities. Results: Forty-five patients displayed aneurysmal rupture (aSAH) while 39 patients had no evidence of aneurysm (non-aneurysmal SAH).
We also failed to evidence an association between CAA and radiological characteristics of the initial subarachnoid bleeding evaluated by the Fisher score. Our results must however be interpreted cautiously. First, results concerning 3-month outcome are obtained from a monocentric observational database and the small sample size is a limitation. Another evident limit of our study is due to its retrospective and exploratory nature. Our work is purely observational, and we cannot rule out that confounding factors might have interacted with our observations. One potential confounding factor might be atheroma disease. Atheroma deposits on subtraction angiography could be interpreted as vessels abnormalities. Patients with atheroma lesions can be at greater risk of poor outcome because of their increased cardiovascular risk.
Continuous net reclassification improvement was calculated as it is the most objective and versatile measure of improvement in risk prediction. CIs come from 1000 bootstrap samples selected with replacement of the size equal to the number of observations in the original data set. The biomarker cut-offs in the present analysis were determined through a complement of existing literature and statistical consideration. 4] [25]  The C-index is presented for the clinical model and with the addition of biomarker dichotomized as elevated or not elevated. Data were analyzed using SAS version 9. 4 software (SAS, Cary, North Carolina). Statistical significance was based on a P<0. 05.
As PCVs are expensive, governments require evidence of their health benefits within their populations. However, measuring the impact or effectiveness of PCVs is challenging. To document PCV impact on pneumonia, countries often rely on routinely collected administrative data on hospitalisations, which may not be complete, as well as population denominators, which are often not available. Vaccine effectiveness (VE) is commonly measured using cohort or case-control studies. Cohort studies require followup of vaccinated and unvaccinated participants for the occurrence of study endpoints, which can be expensive and difficult to implement in low-resource settings  [13]. Measuring VE using the standard case-control design is challenging due to difficulties in selecting controls that are representative of the source population of the cases  [13].
Study procedures Study staff screened potential recruits from Monday to Friday each week. For those eligible, following written, informed consent from parents/guardians, information on demographics, medical history and clinical details were collected through parental interview and review of the medical records, and recorded on a data collection form by study staff. The data collected included: date of enrolment; season of enrolment (Wet (May to September) or Dry (October to April)); number of other people living in the household; source of cooking fuel (electricity, coal, wood or gas); whether the household had piped water; ethnicity of the family; residence (within Vientiane Capital or other provinces); comorbidities (concurrent infection, malnutrition, congenital heart disease, chronic lung disease, cancer, asthma, diabetes, prematurity or low birth weight); required assisted ventilation (continuous positive airway pressure (CPAP) or mechanical ventilation); intensive care admission for > 24 hours; outcome (death, discharged alive); and attendance at day-care centre.
Statistical analysis Categorical data were summarised as numbers and percentages. Continuous data were summarised as medians and interquartile ranges. Age was reported as both a continuous and categorical variable. Logistic regression was used to estimate the odds ratios (OR) and associated 95% CI of hypoxic pneumonia by PCV13 vaccination status. The ORs were converted to measures of VE using the formula: VE = (1-OR) * 100. To handle potential confounding, we used inverse probability of treatment weighting (IPTW), which weights individuals by the inverse of the probability of PCV13 vaccination conditional on covariates (i. e. the propensity score (PS)). The PS was estimated using a logistic regression model with PCV13 status as the outcome variable and potential confounders as covariates. The following variables were included in the propensity score model based on prior subject matter knowledge: age, sex, season, day care attendance, number of other people in the household, comorbidities, date of enrolment, and HRSV infection status.
Primary VE analyses included participants with completely observed data on all variables in the adjusted and unadjusted analyses (i. e. complete case analyses). We examined the sensitivity of the results to the handling of missing data by using multiple imputation (See Supplementary methods). The missing data were imputed using multiple imputation by chain equations (MICE) using the mi impute chained command in Stata, with 40 imputed datasets created. The unadjusted and PS analyses were performed separately on each imputed dataset, and the results combined using Rubin's rules  [28]. Data cleaning and analysis were conducted using Stata version 15  [29].
Children with hypoxic pneumonia were also more likely to reside in homes that used wood for cooking (50% v 38%) and more likely to have a comorbidity (19% v 8%). Of the 826 pneumonia patients, 144 (17 • 4%) had missing PCV13 vaccination status, 36 (4 • 4%) had unrecorded oxygen saturation levels and 570 (69%) had complete data for all variables in the propensity score analysis. Compared to children with known PCV13 status, those with unknown PCV13 status were enrolled later in the study (e. g. 60% v 42% enrolled after 2015), more likely to reside in homes that used wood for cooking (55% v 39%), less likely to live in a home with piped water (40% v 55%,), less likely to live in Vientiane Capital (62% v 83%) and less likely to be of Lao Loum ethnicity (77% v 89%) (Supplementary Table  2 ). Children with unrecorded oxygen saturations were enrolled earlier in the study compared to those with recorded levels (e.
g. 86% vs 53% enrolled before 2016) (Supplementary Table  3 ). There were also differences between vaccinated and undervaccinated children (Supplementary Table  4 ). Among participants with completely observed data (n = 570), undervaccinated children were younger (median age: 6 months v 13 months) and enrolled earlier in the study (e. g. 51% v 24% enrolled before 2015) compared to vaccinated children. Vaccinated children were more likely to come from homes with maternal education levels higher than primary (84% v 73%) and homes with piped water (63% v 43%). Following PS weighting, standardised differences between covariates were < 10%, indicating that covariates were balanced between exposure groups (Supplementary Table  4 ). The unadjusted VE against hypoxic pneumonia was 23% (95% CI: -9, 46%; p = 0 • 14) ( Table  2  ).
Additionally, we included pneumonia cases requiring oxygen supplementation in the outcome measure, as oxygen saturations were only recorded on admission. Therefore, using only "hypoxia" would not have captured the cases who deteriorated clinically during their hospitalisation. This is the first study to describe this single-hospital approach to measure VE and provides a simple and feasible approach for other LMICs to adopt. Determining the effectiveness or impact of PCV in LMICs can be challenging. The quality of data and the consistency of clinician admission criteria is variable. For VE, casecontrol studies may be unreliable due to the lack of specificity of the pneumonia case definition and the choice of community controls may be biased. Drawing both cases and controls from patients that were hospitalised for the same condition, reduces bias that may otherwise occur from the association of vaccination and health seeking behaviour  [ 16 , 33 ].
Additionally, children with wheeze were included in the analysis. The WHO criteria for pneumonia has been shown to have poorer sensitivity and specificity in children with wheeze. However, both measures are improved with the addition of fever in the case definition  [40]. Furthermore, the number of children in our study with wheeze was similar between groups. Finally, although this was a prospective study, undertaking research in LMICs can be challenging and missing data still occur even with a prospective design. To address the missing values we used multiple imputation and found a 35% PCV13 VE and a high level of evidence for likely effect, providing further support of the veracity of our findings. In conclusion, these results show PCV13 is effective against hypoxic pneumonia in an Asian setting.
Acknowledgements We would like to thank all those at  MCRI, The Royal Children's Hospital, The University of Melbourne, Mahosot Hospital, LOMWRU  study staff, and most importantly the patients and their families for participation in this study. We would also like to acknowledge  Chanthaphone Syladeth  and  Anonh Xeuatvongsa  for their contributions to this study. The field work was supported by funding from the  Bill & Melinda Gates Foundation  ( OPP1115490 ). We would also like to acknowledge the study and laboratory staff at: Asia- Pacifc Health Research Group, Murdoch Children's Reseach Institute, Melbourne, Australia; Centre for International Child Health, Dept. of Paediatrics, The University of Melbourne, Australia; Translational Microbiology Group, Murdoch Children's Research Institute, Australia; Expanded Programme of Immunization, Ministry of Health Laos; Lao-Oxford-Mahosot Hospital-Wellcome Trust-Research Unit, Vientiane, Laos ; HRSV testing was funded by  Institute of Research for Development (IRD)  and  Aix-Marseille University Centre for Tropical Medicine & Global Health ,  University of Oxford, Oxford, UK ;  London School of Hygiene and Tropical Medicine, London, UK.
Amplification fragment length polymorphisms 9] [20]  Following amplification, the AFLP fragments were ran by capillary electrophoresis. The capillary electrophoresis 20 µL reaction consisted of a 2 µL (1:10 dilution) of the AFLP product, 0. 1 µL of Genescan 600LIZ size marker (Thermo Fisher, Landsmeer, The Netherlands) and 17. 9 µL HiDi Formamide (Thermo Fisher). Data were analyzed using Bionumerics software (Applied Maths, Sint-Martens-Latem, Belgium).