dataesr/scientific-paragraphs-categorization huggingface dataset:
Nevertheless, the number of sessions needed, rebleeding rate and mortality were similar in both groups. Many studies have compared the use of NSBBs combined with EBL versus one of these treatments in a single therapy  [57] [58] [59]. The results of a recent meta-analysis, combining the data of 23 trials, show a decrease in the risk of recurrent bleeding with a dual therapy, without any positive impact on survival  [60]. However, survival was better in patients treated with NSBBs (single or combined therapy) compared to patients treated with EBL alone. Hence, EBL therapy alone should never be recommended and, if any contraindications to beta-blockers occur, TIPS should be discussed. Few severe patients (Child Pugh C) were included in these studies and it is uncertain whether the previous results are applicable to these patients.
Patients and Methods Participants. Between January 2014 and August 2014, we prospectively assessed 1108 patients who were to undergo unilateral THA or TKA at a single NHS orthopaedic teaching hospital. The study centre is the only hospital to receive adult referrals in a predominantly urban regional population of approximately 850 000 people. Ethical approval was obtained for this project from the institutional review board (11/AL/0079); and patients were recruited with informed consent. All patient undergoing lower limb arthroplasty were eligible for the study. For analysis we required all three assessment time points, thus patients not providing complete follow-up assessment data were excluded. Individual patients could only be entered into the analysis once to prevent bias, and the second operation in cases of staged bilateral procedures was excluded.
198 and THA p = 0. 053). Demographic data is presented in Table  I. The mean age of THA cohort was 69. 9 years with a 45. 5% male and 55. 5% female gender split. The mean age of the TKA cohort was 67. 6 years with a 41. 5% male and 58. 5% female gender split. Assessments took place at a pre-operative assessment clinic and then by postal questionnaire at six and  12 months post-operatively. Sociodemographic data was collated prior to surgery. The participants completed outcome questionnaires independently. The FJS-12 questionnaire and the Oxford Knee or Hip Score (OKS or OHS) were completed at all assessment time points. The shortform (SF)-12 questionnaire 20 was evaluated 12 months post-operatively to place the joint specific scores in the context of broader health domains. Assessment instruments.
20 ach item is rated using a five-point Likert response format. The transformed scores for each health domain reflect a patient's poor (0) to excellent (100) health status. Two separate outputs are generated, a physical component summary score (PCS) and mental component summary score (MCS). Normative-based scoring is used for each component: the population mean score is 50 (standard deviation (SD) 10). Statistical analysis. Sample characteristics are given as means with SD, ranges, and frequencies as appropriate. Dimensionality was explored by means of Cronbach's alpha, exploratory factor analysis (principal component analysis), and confirmatory factor analysis based on polychoric correlations. 21 Model-data fit for a one-factor solution was assessed using the following statistics and thresholds for adequate fit: root mean square error of approximation (RMSEA)  22  < 0.
Overview This needs assessment study was included as part of a broader assessment that also investigated the organisational needs of the ESC, and utilised a mixed-methods approach combining qualitative and quantitative data in order to obtain an in-depth understanding of the perception of participants  [12]. Participants also included leaders from national cardiac societies, representatives of the industry, and key influencers/decisionmakers in the cardiology field. However, for the purpose of this article, which focuses on the educational needs and challenges of cardiologists, only the data collected amongst the cardiologist sub-group will be presented. Interviews with open-ended questions and focus groups (qualitative phase) were conducted with general and sub-specialised cardiologists from a sub-set of nine targeted countries.
Themes that emerged from the analysis of the qualitative data drove the design of an online survey (quantitative phase) that was deployed across 56 countries in Europe and the Mediterranean basin. The study design, protocol and tools were developed by an independent research organisation specialised in behavioural and performance research (AXDEV Group, including co-authors SM and PL). Clinical expertise and contextualisation of the data were provided by subject matter experts comprised of cardiologists and decision-makers of the ESC (including coauthors PV, JLZ, PK, LG, KF and AV). Interpretation of the final data was provided by all co-authors.
Data collection and analysis In the qualitative phase, participants were invited to participate in either a 45-minute semi-structured interview or a 90-minute virtual focus group. Each virtual focus group was formed of 2-4 cardiologists, practising in different countries but with the same type of practice setting (academic vs. community). Interviews and focus groups were conducted by trained facilitators. Broad open-ended questions on different domains were asked; in particular, different aspects of clinical practice (diagnosis, treatment, management) were reviewed with participants to identify potential challenges and causalities for these challenges. Qualitative data were collected in French or English. After each interview or focus group, the trained facilitator filled in a data sheet with information on the relevance of the data and emerging themes.
These data sheets were received by the co-author responsible for the first analysis (PL). Debrief sessions with facilitators were also conducted by PL and SM after the qualitative data collection phase to discuss the emerging themes and develop the coding tree for the in-depth qualitative analysis. Qualitative data of the interviews and the focus groups were coded using N-Vivo 7. 0 software (QSR International, Cambridge, MA). The qualitative analysis process used consisted in a four-step approach integrating both thematic and directed content analysis  [13, 14]. The four steps were: (1) identifying codes within each of the four key domains based on the interviewer's debriefing; (2) coding transcripts according to the developed coding structure; (3) developing new codes for data that did not fit the predefined codes; (4) identifying key emerging themes from the data.
These themes were used to inform the design of the quantitative survey. The quantitative data collection phase consisted of a 20-minute online survey. The survey questions allowed for validation of the challenges and needs that emerged from the qualitative data. Participants were asked to report on their levels of (1) knowledge, (2) skills and (3) confidence regarding clinical practice issues. Participants were also asked about (4) their clinical behaviours and (5) perceptions of certain topics, using ranking and agreement scales. The survey used branching questions based on each participant's subspeciality, as some questions were specific to one or more of the sub-groups of cardiologists. The quantitative data of the online survey were analysed with SPSS 22. 0 software (IBM Corporation, Armonk, NY) using frequencies, cross-tabulations and means.
Results A total of 940 cardiologists and cardiology sub-specialists participated in the study. Qualitative interviews were conducted with 74 cardiologists and the survey was completed by 866 cardiologists. A higher proportion of survey participants were from a community setting rather than an academic setting. Table  1  presents the details of the study sample by regional grouping and by grouping sub-specialities. One of the 18 regional groupings had to be excluded due to a low sub-sample size (Baltic republics, n = 8). Four of the 56 countries were not represented in the final sample (Estonia, Iceland, Malta, Montenegro). The integrated analyses of the qualitative and quantitative data and interpretation by the co-authors revealed three themes related to (1) challenges in the clinical decision-making process, (2) challenges in establishing the patient-physician relationship and (3) sub-optimal team communication and collaboration.
Acknowledgements This study was conducted by AXDEV Group. In addition to co-authors PV, JLZ, PK, LG, KF and AV, the oversight committee of cardiology experts who provided insight to this study included  Thomas Luescher  ( University Hospital Zurich ),  Geneviève Derumeaux  ( Louis Pradel University Hospital, Lyon University ), and  Aldo Maggioni  ( Research Centre, Italian Association of Hospital Cardiologists). The authors would also like to acknowledge the support provided by  Sophie Péloquin  ( Director Performance Strategy, AXDEV Group, Canada ), who supported the analysis and interpretation of the data, as well as the  Communication Division of the ESC  who helped generating interest for the recruitment. The.
Methods The goal was to create parsimonious multivariable prognostic models for three outcomes: (1) the composite of death, WHF during the hospital stay, or re-hospitalization for WHF through 30 days; (2) death or re-hospitalization for WHF through 30 days; and (3) death through 90 days. Readily available data gathered at baseline in the Value of Endothelin Receptor Inhibition with Tezosentan in Acute Heart Failure Studies (VERITAS) were used to create a basic predictive model  14. The additional value of bio-markers, including B-type natriuretic peptides (BNP) and troponins, was then investigated. Patients. Patients enrolled in VERITAS within 24 hours of hospital presentation with WHF sufficient to cause breathlessness at rest or on minimal exertion were included in this analysis. The patient's report of dyspnoea had to be supported by a respiratory rate of at least 24 breaths per minute as objective support of respiratory distress.
Where the association was non-linear, a readily-interpreted transformation was chosen through examination of plots of the predicted log hazard ratio against the value of the predictor and changes in Akaike's Information Criterion. If little information was lost, the same transformation was used to model each outcome. A summary of the model forms chosen for each continuous predictor is shown in Supplementary Table  S1. We used multiple imputation  17  with a method that assumes multivariate normality (SAS PROC MI) to handle missing values. The imputation model included all covariates under consideration for the multivariable models. The ranges of imputed values were restricted to the ranges of the observed values. Ten imputation datasets were used. Parameter estimates were averaged across these datasets using Rubin's algorithm  18  (SAS PROC MIANALYZE).
We constructed two full models (one with and one without biomarker data) for each of the three outcomes that included all of the variables listed in Supplementary Table  S1. Backwards selection in each of the imputed datasets was then used to reduce the number of predictors, with the criterion for retention set at P<0. 10. Predictors that were significant in the majority of the imputed datasets (>5) were kept in each of the final models. The prediction ability of the resulting models was evaluated by computing differences in cstatistics (c-indices) between models with and without the addition of biomarkers. Because multiple imputation was used with 10 imputations, the c-indices were calculated for each imputation dataset using Harrell's method  19  and then averaged using Rubin's algorithm in PROC MIANALYZE.
There are many limitations to our study. This was a clinical trial population. By protocol design, both low and very high risk patients were excluded. Many patients will have declined to participate and it is also likely that investigators decided not to include some patients even though they fulfilled the entry criteria. Accordingly, this is a selected group of patients. It is possible that the prognostic models would be more accurate in clinical practice that does not exclude patients at either extreme of risk, although it is in patients of intermediate risk where the assistance of tests may be most required  43. Many other variables might have been collected. Intuitively, models developed using discharge rather than admission data might be better able to predict post-discharge outcome. Surprisingly, this does not seem to be the case for routine clinical information, with discharge data adding little to that collected at admission 2;44.
Freq. w/wo = selection frequency out of 10 imputation datasets with and without addition of biomarker data. †M1= death, worsening heart failure or readmission for heart failure by Day 30. ‡M2 = death or readmission for heart failure by Day 30. § M3 = all-cause mortality by Day 90. \Systolic and Diastolic BP were highly collinear and latter was dropped from the model. AF= atrial fibrillation; BMI= body mass index; BP= blood pressure; CABG= coronary artery bypass surgery; CHF= chronic heart failure; COPD= chronic obstructive pulmonary disease; DM= diabetes mellitus; ECG= electrocardiogram; IHD= ischemic heart disease; LLOQ= lower limit of quantification; NR= not relevant; PCI= percutaneous coronary interventions; PVD= peripheral vascular disease.
Freq. w/wo = selection frequency out of 10 imputation datasets with and without addition of biomarker data. †M1= death, worsening heart failure or readmission for heart failure by Day 30. ‡M2 = death or readmission for heart failure by Day 30. § M3 = all-cause mortality by Day 90. \Systolic and Diastolic BP were highly collinear and latter was dropped from the model. AF= atrial fibrillation; BMI= body mass index; BP= blood pressure; CABG= coronary artery bypass surgery; CHF= chronic heart failure; COPD= chronic obstructive pulmonary disease; DM= diabetes mellitus; ECG= electrocardiogram; IHD= ischemic heart disease; LLOQ= lower limit of quantification; NR= not relevant; PCI= percutaneous coronary interventions; PVD= peripheral vascular disease. Prevalence (%) Sel. Freq. Sel. Freq. Sel. Freq.
MATERIALS AND METHODS Data from the three studies were selected for the pooled analysis based on the following criteria: i) The challenge test result was available; ii) The CoMiSS TM was completed both at baseline and at one month on an elimination diet (month-1). Pooled analyses were conducted based on regressing the results of the month-1 challenge test on the month-1 CoMiSS TM , adjusting for baseline CoMiSS TM using a logistic regression model. In addition, a logistic regression model was also fitted to the month-1 challenge test result with the change in CoMiSS TM from baseline as a predictor. In the original study for which the CoMiSS TM was developed, the cut-off for inclusion in the study was set at ＞12  [4]. In the second study, the cut-off was set at ＞10  [5] , and in the third study there was no cut-off of the CoMiSS TM for inclusion in the study  [6].
ACKNOWLEDGEMENTS Yvan Vandenplas has participated as a clinical investigator, and/or advisory board member, and/or consultant, and/or speaker for  Abbott Nutrition, Aspen, Biogaia, Biocodex, Danone, Hero, Nestle Nutrition Institute, Nutricia, Mead Johnson Nutrition, Merck, Orafti, Phacobel, Sari Husada, United Pharmaceuticals, Wyeth and Yakult. P Steenhout  and  A Järvi  are employees of  Nestlé Health Sciences. AS Garreau is an employee of  United Pharmaceuticals. R. Mukherjee  reported no  COI.
The separation was performed at a constant current of 4 mA per gel for approximately 1. 5 h at 4 °C in running buffer (96 mM Glycine, 12. 5 mM Tris, 0. 05% LDS). The chlorophyll content of the green bands was analyzed quantitatively using the ImageJ2x image analysis software. After electrophoretic separation, gel strips containing LHCII complexes were cut and used in spectroscopic measurements. The gel thickness was 1 mm. The various LHCII oligomeric forms located in a polyacrylamide gel were studied previously  (Ilioaia et al. 2008; Janik et al. 2015 Janik et al. , 2016)). The pigment composition and spectroscopic characteristic of the LHCII trimers and monomers obtained by the method described above were presented in  (Janik et al. 2015 (Janik et al. , 2016) )  and show that the native gel methods yields fully functional complexes.
Excitation was obtained by a 405 nm pulsed laser with a repetition rate of 20 MHz. The FWHM of the pulse response function was 68 ps (measured by Pico-Quant, Inc. ). The laser beam was collimated in the scan head and focused using ×60 water immersed objective (NA 1. 2, Olympus) on to a sample volume. In order to select a single focal plane and reduce excitation light a pinhole with a diameter of 30 and 50 µm, was used. Time resolution was 4 ps. The observation was made through 680/13 band-pass filter. Scattered light was removed using ZT 473 RDC dichroic filter (Analysentechnik). Fluorescence photons were collected with a single-photon sensitive avalanche photodiode (APD) with processing accomplished by the HydraHarp400 time-correlated single-photon counting (TCSPC) module. Data analysis was performed using Sym-PhoTime 64 software package.
S1 ). Light intensity in each slot was precisely measured using a photometer before commencing each experiment. Upper panel shows exemplary results of the electrophoretic gel analyses with band assignment (FP free pigments fraction). Lower panel presents the quantity analysis of LHCII trimers, dimers, and monomers in the samples. Relative intensities of the bands corresponding to different LHCII forms were quantified by scans analyzed with ImageJ2x software. Experiment was repeated ten times. Similar, exemplary effect of different light intensities on the LHCII trimers and monomers mixture is presented as Supplementary data (Fig. S2 ) monomers. It must be noted that monomers in a detergent solution can interact in the upside-down orientation that is not possible in vivo in the thylakoid membrane environment.
Acknowledgements We are very grateful to Uniper, TNO and the  Karlsruhe Institute of Technology (KIT)  for the collaboration during this experimental work. We are grateful to  Henk de Groot  and  Ton Theunissen  of  ENGIE 's Nijmegen  power plant for their support during the test campaign. This research was feasible thanks to the support from the  ROAD  project and the  ENGIE's CRV research program. Part of this research was carried out within the framework of the  Dutch CATO-2 program.
The structures of the obtained compounds were verified based on 1 H-NMR, 13 C-NMR, elemental analysis and IR spectra. Melting points were estimated with an Electrothermal apparatus (all data presented 4. 6. Coagulation Assay General conditions of coagulation assay were described elsewhere  [15, 27]. The experiments were conducted at λ = 405 nm, by means of a thermostatic spectrophotometer (Cecil CE 2021). The synthesized compounds at five concentrations (in a 10 µL volume) were added to plasma diluted three times with TBS buffer, and the samples were incubated at 37 • C for 3 min. Then a mixture of thrombin (0. 0375 IU/mL) and calcium chloride (0. 015 mmol/mL) was added. The obtained curves were analysed by means of a software  [38]. The following kinetic parameters were established: TGt-thrombin generation time, Fmax-maximum clotting, Tf-plasma clotting time, Fvo-initial plasma clotting velocity, Sf-area under the clot formation curve, Sc-area under the clot stabilization time, and S-area under the curve of coagulation.
Microscopy Studies Two percent erythrocyte suspension was incubated at 37 • C for 60 min with tested compounds at concentrations 0. 04-4 µmol/mL. After this time, the suspension was diluted two-fold on titration plates. RBCs morphology was observed using the phase contrast Opta-Tech inverted microscope (magnification of 400 times), equipped with software (OptaView 7, Opta-Tech, Warsaw, Poland) for image analysis.
Flow Cytometry-SC Parameter The size of the RBCs after incubation with iminodiacetic acid derivatives was assessed by a flow cytometry (FMC) technique performed on FACS Canto II (Becton Dickinson, Franklin Lakes, NJ, USA). FMC gate on erythrocytes was established for data acquisition and the cell sizes were determined with low angle light scattering. The data were displayed in diagrams of the cell number versus the light scattered. The study was limited to 20,000 events and lasted 20-30 s. The tested compounds at concentrations of 0. 2 µmol/mL and 2. 0 µmol/mL were added to RBCs suspension, prepared the same way as in the RBCs lysis test, and incubated for 1 h at 37 • C. Afterwards the samples were diluted 4-fold and analysed by a flow cytometer.
Statistics Statistical analysis was conducted with a commercially available package (Statistica 12. 0, StatSoft, Krakow, Poland). All results are presented as means ± SD. Normal distributions of continuous variables were verified with the Shapiro-Wilk test. Paired t-tests were used for intergroup comparisons of normally distributed variables, while the variables with non-normal distributions were compared using the Wilcoxon signed rank test. The results of all the tests were considered significant at p-values lower than 0. 05.
Materials and methods We validated SOPs used in the PainOmics retrospective study to find -omics biomarker to stratify patients with chronic low back pain recruited in the second middle of 2014. The Institution that granted permission is the Ethics Committee of each Center where patients were enrolled after signed informed consentand it was registered on http://clinicaltrials. gov (NCT02037789). In particular, this study is approved by Ethic Committee of: • University of Parma (UNIPR)-Italy; • Fondazione IRCCS Policlinico San Matteo Hospital (OSM)-Italy; • St. Catherine Specialty (St-Cat)-Croatia; • Ziekenhuis Oost-Limburg Autonomeh Verzorgingsinstelling (ZOL)-Belgium; • The Center for Clinical Research (CPI)-USA; • Edith Cowan University (ECU)-Australia. and the results of this study were already published in our manuscript on BMJ Open  [12].
The amount of DNA and concentration, as well as numbers of required aliquots required for glycomics and activomics were defined and deviations from SOPs are allowed only if properly justified and shared with the laboratory supervisor (S1-S3 Files). Finally, a procedure was set up to manage clinical samples whereby all samples are validated for sample integrity (i. e. frozen, bar coded) and entered into a database for subsequent analyses. The database identifies the storage location, temperature, number of freeze-thaw cycles, remaining volume, and details on multiple aliquoting analyses. The primary database is linked via barcode references to a second database that identifies screening results for the multiple markers to be tested. The database also collates sample data from the same patient in order to manage data collected sequentially over the study.
DNA verification First results of quality control showed sub-par DNA quality in almost all investigated test samples. DNA samples from 4 clinical centres revealed concentrations below 50 ng/μL, mainly caused by having less starting volume of blood and differences in calibration of measuring instruments between the participating centres and the central laboratory. After increasing the amount of blood and adjusting the SOP accordingly, DNA concentrations were sufficient and reached expected values above 50 ng/μL (Fig  1 ). With this updated of the SOP all DNA samples successfully passed quality control and showed satisfying results concerning DNA quality and quantity. Moreover, amelogenin PCR has exactly identified the gender of samples, compared to the study databases. This process was necessary to validate the established SOP and to ensure high quality DNA samples which can then be used for further downstream analysis (e.