dataesr/scientific-paragraphs-categorization huggingface dataset:
Study design and data sources We designed a two-sample MR study using aggregated summary data 10 from three published meta-analyses of genome-wide association studies. The main analysis was based on data from Kettunen et al  13  (N=24,925) and the CARDIoGRAMplusC4D consortium  14  (N=184,305), and the validation analysis used the METSIM  15 (N=8,372)  and the CARDIoGRAMplusC4D datasets. A more detailed description of the studies is available in Supplemental Materials. We centered our analysis on the genetic variants associated with: 1) the main lipid profile traits in serum (HDL-C, LDL-C, and triglyceride levels); 2) other measurements of HDL quantity (ApoA-I levels); 3) HDL mean diameter; 4) the quantities of cholesterol transported in small, medium-sized, large and very large HDLs; 5) the quantity of other lipid species in HDL particles (triglycerides transported in very large HDLs); and 6) the levels of HDL particles according to the previous HDL size subtypes.
1000genomes. org/phase-3-structural-variantdataset-as reference  19  ); and 3) a minor allele frequency ≥0. 05. As an additional approach to exclude potential pleiotropy, we also removed the variants with a significant result in the HEIDI-outlier test (p-value<0. 01). Finally, we explored and confirmed the exclusion of potential pleiotropic effects using Egger regressions  20. Statistical significance of our results was corrected for multiple comparisons (p-value=0. 05/number of traits). A description of complementary sensitivity analyses using other MR analyses methods such as the median-based and inverse variance weighted, using the Global Lipid Genetic Consortium dataset  21  and post-hoc statistical power estimations  22  is available in Supplemental Materials.
Selected genetic variants We identified genetic variants significantly associated with 13 lipoprotein characteristics in the data published by Kettunen et al. and with 8 lipoprotein traits in the METSIM data. The number of genetic variants for each lipoprotein trait ranged from 6 (level of medium-sized HDL particles) to 22 (ApoA-I). Genetic variants included in the analyses and their unadjusted and adjusted effects are listed in Supplemental Excel File 1. CC-BY-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted March 10, 2020. ; https://doi. org/10. 1101/673939 doi: bioRxiv preprint 5 We observed high inverse genetic correlations (correlation coefficient≤-0.
Unfortunately, we could not validate these results due to the lack of valid genetic variants in the METSIM study. Our results are mechanistically plausible and highlight novel potential therapeutic targets in cardiovascular disease, since genetic variants individually associated with HDL qualitative traits and CAD in our data were located within five HDL-related genes or gene clusters. First, LIPC encodes for hepatic lipase C, an enzyme that hydrolyzes triglycerides in circulating lipoproteins, including HDL particles  29. Hydrolysis of HDL. CC-BY-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted March 10, 2020.
Our study has several methodological strengths. First, our results are based in MR, a useful approach to explore the causality of the association between biomarkers and specific diseases. Second, we included two independent MR analyses to validate the results initially observed. Finally, the validity of the genetic variants for HDL-C, LDL-C and triglyceride levels initially generated was confirmed, supporting the validity of these. CC-BY-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted March 10, 2020. ; https://doi. org/10. 1101/673939 doi: bioRxiv preprint 11 datasets for the analysis of other genetic variants.
ACKNOWLEDGEMENTS We thank  Elaine M. Lilly, PhD , for her critical reading and revision of the English text. Data were downloaded from: www. computationalmedicine. fi/data#NMR_GWAS (Kettunen study), http://csg. sph. umich. edu/boehnke/public/metsim-2017-lipoproteins/(METSIM study), www. cardiogramplusc4d. org(CARDIoGRAMplusC4D), http://csg. sph. umich. edu/abecasis/public/lipids2013/( Global Lipid Genetic Consortium ), http://www. 1000genomes. org/phase-3-structural-variant-dataset(1000 Genome).
Introduction Up to now, French data on paediatric anaesthesia were limited and/or monocentric  (1, 2)  or focused on one type of complication  (3, 4). The participation of French centres to the APRICOT study allows comparison with other practices in Europe  (5). This study not only gives epidemiologic data on paediatric anaesthesia in Europe but also explores perioperative management and complications. One of the finding of the APRICOT study was the great heterogeneity between countries regarding both practices and perioperative complications. Some part of this heterogeneity might come from the presence of national recommendations and the spread of updated medical information and/or particular organisation of human resources that might influence the overall quality of care and rate of complications.
We therefore undertook a secondary analysis of the French data in APRICOT. The primary goal was to obtain a description of patients' characteristics, procedures and perioperative anaesthetic management in France. Secondary outcomes were the incidence and timing of major perioperative complications (especially respiratory, the most frequent ones during paediatric anaesthesia)  (5)  and the determination of human resources organisation (experience of anaesthesiologist and the presence of an anaesthetic nurse) possibly associated with these perioperative complications.
Study design The study design has been widely described in the original publication  (5). The study consisted in a prospective collection of perioperative data from children recruited during a consecutive 2-week period freely chosen by each centre, between April 1, 2014, and January 31, 2015 in each participating centre across 33 European countries. The study was nationally approved by an IRB (CPP Sud Méditerranée I n° 2014-A00666-41). Data were collected in an online electronic database (approved by the French regulatory office for the protection of privacy). The current study used all data collected in the French participating centres after approval by the primary investigators of the APRICOT study and the French national coordinators (AL and CD). The detail of data acquisition is available in the original publication of the APRICOT study but basically, all children up to 15 years old undergoing an inpatient or outpatient diagnostic or surgeries, under regional anaesthesia alone, sedation or general anaesthesia (with or without regional anaesthesia), were eligible for inclusion in the APRICOT study.
Data extraction Concerning the description of practice of paediatric anaesthesia in France, the analysis of data was focused on the epidemiologic characteristics of the children who underwent anaesthesia, the surgical and non-surgical procedures performed and anaesthesia management during the perioperative management (patients were followed for up to 60 min after anaesthesia or sedation). Concerning the analysis of perioperative complications and data in relation with organisation and human resources associated with those complications, the following data were extracted: years of experience of the anaesthesiologists and the presence of an anaesthetic nurse with the physician (either a physician or a resident). In order to account for confounding factors, all previously identified ones (or presumed to be) associated with respiratory and cardio-vascular complications  (1, (3) (4) (5) (10) (11) (12)  were also included in the analysis, namely: age, prematurity, gender, ASA physical status III to V, actual or previous URTI, fever, wheezing, asthma, parental smoking, allergy, snoring, previous anaesthesia complication, preoperative medication (indicating the presence of a preoperative illness) and preoperative handicap or congenital disease, the type of surgery or procedure, the preoperative premedication and the presence of parent at induction, the inpatient management, the emergency anaesthesia, the rapid sequence induction, the general anaesthesia and the use of regional analgesia, the intravenous induction, the device used for ventilation, the method of ventilation used and the use of muscle relaxation.
Results Overall 20 centres (17 teaching hospitals, 1 community and 2 private institutions) in France included 3559 procedures, i. e. 11. 5% of procedures included in APRICOT, and approximately 4 % of all paediatric anaesthetics performed in France during a two-weeks period of time in 2016 (according to the national electronic database on healthcare in France). After cleaning the database for incomplete records, analyses were carried on 3535 procedures.
Description of patients, procedures and perioperative management in the French APRICOT cohort in comparison to the European APRICOT data Characteristics of patients are displayed in table 1. Mean patients' age was 3. 3 [95% CI: 2. 4; 4. 3] years (European cohort: 6. 35 ± 4. 5 years). Their ASA status was predominantly I and II (92. 2% versus 92% in the European cohort). Among included patients, 7. 2% were former premature (7. 6% in the European cohort), 14. 4% were suffering from a handicap and/or a congenital disease (13% in the European cohort) and 26% were taking medications and among those patients 2. 2% specifically cardiovascular and/or anticoagulant treatments. In addition, the preoperative respiratory risk factors found in the French patients were similar to those published in the whole APRICOT cohort apart for snoring (5.
The rates of monitoring and reversal of muscle relaxation were different between cohorts: specifically, the rate of reversal of NDMR blockade was lower in the French cohort. This data cannot be interpreted because we do not know in how many cases reversal was systematic or adapted to the result of neuromuscular monitoring in both cohorts. Although no controlled trial has investigated the usefulness of reversing muscle relaxation in children, a strong relation between residual neuromuscular block and postoperative respiratory complications has been described in adult patients  (18). Further studies evaluating the effects of residual relaxation on postoperative respiratory outcomes are specifically needed in the paediatric population. Finally, rapid sequence induction (RSI) was performed more frequently in the French cohort.
The major and specific limitation of the current study is its limited representativeness of the overall paediatric anaesthesia activity in France, given that the current French dataset represent only 4% of the overall yearly paediatric anaesthesia activity. In addition, one might question the fact that 17 of the 20 facilities that participated to the study were specialised ones. This is reflected by the difference in the rate of ambulatory surgery in France  (23) , which seems to be higher than that reported in Europe by APRICOT, independently of the ENT surgery that has been reported to be performed in private institutions in France  (23, 24). In addition, the practice of paediatric anaesthesia was different from the whole APRICOT cohort (59% versus 85. 3% of participants with more than 80% paediatric anaesthesia practice in the European and French cohorts, respectively)  (10).
We could thus analyse only the tip of the iceberg of the whole paediatric anaesthesia practice in France. Second, the French cohort was compared to the overall European one. This means that French data were included in this comparison. However, this is unlikely to have compromised the comparison, given that French data were representing only 11% of the included patients. In conclusion, despite its limitations, the French APRICOT cohort gives important insights concerning paediatric anaesthesia practice in France. This study allows determining key factors for improving security and quality of healthcare during the perioperative period of paediatric anaesthesia. It might be considered as a starting point for further studies aiming to evaluate and improve the quality of paediatric anaesthesia practice in France.
Legends of tables and figures Table  1 : description of patients' characteristics of the APRICOT French cohort. Data are expressed as percentages or mean with their 95% confidence interval. NR: not reported in the European APRICOT results Table  2 : surgery and procedures characteristics in the APRICOT French cohort. Data are expressed as percentages or mean with their 95% confidence interval. NR: not reported in the European APRICOT results Table  3 : Anaesthesia and perioperative management in the APRICOT French cohort. Data are expressed as percentages or mean with their 95% confidence interval. NR: not reported in the European APRICOT results. Percentages of surgical and non-surgical procedures are expressed as a proportion of overall included patients. Table  4 : Univariate analysis of factors associated with perioperative complications.
Soil measurements The soil water content was monitored using sensors with two 30-cm-long stainless steel rods (FDR CS 616-L; Campbell Scientific, Logan, Utah, USA) inserted horizontally at 2. 5 and 7. 5 cm depths. A type-T copper-constantan thermocouple was installed on the soil surface and at 2. 5 and 7. 5 cm depths to measure soil temperature. Both sensors were coupled to a data logger (CR1000; Campbell Scientific, Logan, Utah, USA), and measurements were taken at a 10-min sampling interval. The water-filled pore space (WFPS) in the 0-5a n d 5-10 cm soil layers was estimated by dividing the volumetric water content by the total soil porosity as determined from the bulk density. Soil samples were collected from the surface layer (0-10 cm) 22 times during the experiment. Soil collection occurred frequently during the first month following straw and urea applications and then less frequently thereafter, but soils were always collected on days that had a GHG measurement.
For the cumulative N 2 O-N at the different levels of straw, a linear regression was fitted. The data were processed using the SISVAR software  (Ferreira 2011). The N 2 O emissions from each straw quantity, soil variables, CO 2 emission, and straw-C remaining were subjected to multivariate analysis (principal component analysis, PCA) using Statistica® software (version 7. 0). PCA was performed to address the variables that drive N 2 O emissions. PCA was performed on the correlation matrix that was obtained from the results of soil temperature and WFPS (0-10 cm), soilexchangeable NH 4 + and NO 3 -contents, CO 2 and N 2 Ofluxes, and C remaining in the sugarcane straw. Only correlation coefficients (r) above 0. 50 between the variables and ordination axes were considered significant. Correlations between the N 2 O and variable drivers of N 2 O emissions were considered significant at P <0.
Methods: A total of 2500 participants (500 in each study site) are recruited to receive the CDSMP intervention. The evaluation study has a pre-post design. Data will be collected from participants before the start of the intervention (baseline) and six months later (follow up). Benefits of the intervention include self-management in healthy lifestyle, depression, sleep and fatigue, medication adherence and health-related quality of life, health literacy, communication with healthcare professionals, prevalence of perceived medical errors and satisfaction with the intervention. The study further includes a preliminary cost-effectiveness analysis with a time horizon of six months. Conclusion: The EFFICHRONIC project will measure the effects of the CDSMP intervention on the target population and the societal cost savings in five European settings.
Study Design The CDSMP intervention has been described in detail elsewhere  [28, 29]. In short, the intervention is based on the self-efficacy theory, and emphasizes problem solving, decision making and confidence building. It consists of a series of six tightly scripted workshops, 2. 5 hours each, which are held once a week for six weeks. The intervention is offered by healthcare professionals as well as lay-persons and is attended by about 15 participants  [11]. The evaluation study of the EFFICHRONIC project has a pre-post design. Data will be collected from participants before the start of the intervention (baseline) and six months later (follow up). In all study sites, every series of six workshops will preferably be led by a healthcare professional and a lay-person together. To this end, healthcare professionals and lay-persons will be recruited and trained in the CDSMP principles in the local language.
Assessment of Outcomes Data collection is done with the use of a baseline and follow up questionnaire, including a variety of outcomes. Caregivers fill out the questionnaires for themselves, not for the citizen with a chronic condition they take care of. The instruments used to measure the outcomes are described below. Instruments for which no validated translation is available are translated. Translations are discussed by the study team and adapted when needed. The baseline questionnaire will be pilot-tested in all study sites to assure its appropriateness, comprehensibility and length. Our first research question is to evaluate the six-month effects in terms of self-management in healthy lifestyle, depression, sleep and fatigue, medication adherence and HR-QoL. Self-management is measured by six items regarding a participant's ability to deal with fatigue, physical discomfort, emotional distress, other symptoms or health problems, different tasks and activities and other things than just taking medications (Chronic Disease Self-Efficacy (CDSE) instrument  [29] ).
Data Management and Statistical Analysis The Erasmus MC University Medical Center is responsible for the data-management, analysis and reporting. All data is handled confidentially and scientific data is stored anonymously. In addition to descriptive statistics, tests for normal distribution of the outcomes and socio-demographics will be performed using a Kolmogorov-Smirnov test. Differences between baseline and follow up measurements will be assessed by means of the paired t test (for variables showing a normal distribution), Mann-Whitney U test (for variables not normally distributed) or Pearson's chi-square test (for variable fractions). To determine the relationship of an outcome (at follow up) with explanatory variables, ordinary least squares (OLS) regression will be performed for continuous outcome variables with the outcome (at baseline) and (change in) other outcomes and socio-demographics as explanatory variables.
Furthermore, cost-effectiveness data regarding self-management programs are limited. The EFFICHRONIC project will provide insight into potential societal cost savings resulting from a reduction in healthcare utilization and productivity losses. The study has some limitations, and we expect to encounter various challenges. Firstly, the recruitment of the target population will be performed in accordance with the capacity, organizational and contextual factors of each of the five study sites. Although this implies that the recruitment will be different in each study site, evaluating the effectiveness of approaches in different (international) settings is valuable. Secondly, we decided that it is not desirable to include a control group. To avoid feelings of exclusion, the intervention will be available to all citizens meeting our inclusion criteria.
Acknowledgments: The members of the  EFFICHRONIC Consortium  are:  Marta M Pisano Gonzalez ,  Raquel Vazquez Alvarez  and  Delia Peñacoba Maestre  ( Health Service of the Principality of Asturias (SESPA), Spain );  An LD Boone  and  José Ramón Hevia Fernandez  ( Public Health General Directorate, Principality of Asturias (CSPA), Spain );  Inés Rey  and  Raquel Ochoa Gonzalez  (the Foundation for the Promotion of applied Scientific Research and  Technology in Asturias (FICYT) ,  Spain) Yves-Marie Pers ,  Christian Jorgensen ,  Verushka Valsecchi ,  Rosanna Ferreira ,  Adrien Durand ,  Cristina Balaguer ,  Céline Cardoso  and  Manuel Ramos  ( Lapeyronie University Hospital,) Montpellier, France );  Graham Baker ,  Danni Brown  and  Suzanne Lucas  (QISMET), Portsmouth, the  United Kingdom) ;  Siok Swan Tan ,  Xuxi Zhang ,  Irene Fierloos ,  Petra de Vries  and  Hein Raat  ( Erasmus MC University Medical Center, Rotterdam, The Netherlands );  Alberto Pilotto ,  Sabrina Zora ,  Alberto Ferri ,  Alberto Cella  and  Alessandra Argusti  ( EO Galliera Hospital, Genua, Italy );  Ascensión Doñate Martínez  and  Jorge Garcés  ( University of Valencia, Polibienestar Research Institute (UVEG), Valencia, Spain ).
In order to get more information into the size and shape of LmPDI and SmERp60, we used SAXS both under flow in a sample changer (Fig. 2 ) and coupled to a HPLC size exclusion chromatography (SEC-SAXS; Supplementary Fig. S2 ). The SAXS data (summarised in Table  2 ) suggested that both proteins are monomers, with LmPDI being compact, and SmERp60 highly flexible. In fact scattering data from LmPDI were fitted with a compact elliptical particle (as shown in the Kratky plot representation in Fig. 2a ), whose radius of gyration (Rg) is 3. 8 nm and the maximal particle dimension (D max ) is 12 nm. In contrast, the scattering data of SmERp60 were compatible with a multi-domain protein carrying flexible linkers (Fig. 2b ). LmPDI is as compact as the protein from baker's yeast (ScPDI) [PDB: 2B5E 31 ], whose monomer can be fitted into the reconstructed LmPDI's envelope (χ 2 = 1.
2b ) with Rg ranging from 3 to 6 nm and D max from 11 to 16 nm. We also used single value deconvolution to extract the 3 most representative conformations, which were interpreted by fitting the deposited crystal structures of HsPDIA3/ERp57 (2H8L,  35  , 3F8U  33  ,) and HsPDIA1 (4EKZ, 4EL1  36  ,), because they shared the highest sequence identity with SmERp60 (Fig. 1a, b ). The results suggested a butterfly movement of the external a and a′ catalytic domains with respect to the central fixed b-b′ domains, from a close to an open conformation (Fig. 2e  left to right). , values are % of identical residues. The codes within the parenthesis are the UniProtKB accession numbers of each protein  78. HsPDIA1, Homo sapiens PDI isoform A1; HsPDIA3/ERp57, H. sapiens PDI isoform A3, also known as ERp57; LmPDI, Leishmania major PDI; SmERp60, Schistosoma mansoni Endoplasmic Reticulum protein 60; ScPDI, Saccharomyces cerevisiae PDI.
Panel (c) Secondary structure analysis of the recombinant proteins by circular dichroism. Spectra of SmERp60 (red) and LmPDI (green) at 25 °C, after buffer subtraction and averaging of seven sequential acquisitions on a Jasco J-810 instrument, are presented. Table  1. Secondary structure content (%) calculated from deconvolved CD spectra performed on the DichroWeb server  65  , using CDSST3 and SELCON3 with sp175 set  66. For comparison, secondary structures of host HsPDIA3/ERp57 and yeast ScPDI derived from the respective crystal structures (PDB 3F8U  33  and 2B5E  31  ) using DSSP on the 2Struc database  79  are also reported in italics.