dataesr/scientific-paragraphs-categorization huggingface dataset:
The theoretical degradability in the rumen derived from the model (TDm) was calculated from the equation: TDm ¼ a þ ½b Â c =ðc þ kpÞ where kp is the passage rate of solid contents out of the rumen. A unique value of 0. 04 per hour was used for all feeds. Rumen degradability of NDF did not fit to the exponential model due to a linear degradation rate for Calliandra calothyrsus and to erratic variations for the other two forages. For NDF calculations of degradability, we used instead a stepwise method  (Kristensen et al. , 1982) : TDs ¼ R ði ¼0 to nÞ ðDt ðiþ1Þ À Dt i Þ Â p ðt i ; t iþ1 Þ where (Dt (i+1) À Dt i ) is the amount of feed degraded between times t i+1 and t i , and p (t i , t i+1 ) is the proportion of feed remaining in the rumen between times t i and t i+1 with pt i = e -kpti. From VFA production in the in vitro experiment, fermented organic matter (FOM) was calculated by the stoichiometric equation of  Demeyer and Van Nevel (1975) : FOM ¼ 162 ð0:5 acetate þ 0:5 propionate þ butyrate þ valerateÞ where FOM is expressed in mg and VFA in mmol: Data of both experiments were submitted to the same mixed model using the MIXED procedure of SAS including feed (n = 6 for in situ experiment and n = 7 for in vitro experiment) as fixed effect and animal (n = 3 for in situ experiment and n = 4 for in vitro experiment) as random effect.
Differences between feeds were analysed using the Tukey t-test. Effects were declared significant when P < 0. 05. Principal component analyses were performed using Minitab Ò version 17 software (Minitab Inc. , State College, PA). Average values for each of the 6 tannin-rich plants were included for 19 variables: seven from chemical composition, five from experiment 1 and seven from experiment 2.
Acknowledgements The authors thank the staff of  UE 1414 Herbipôle  for their technical collaboration, animal care and management,  A. Torrent  and  L. Genestoux  for their contribution in the experimental set-up and sample analysis, and  A. Roche  (intern student at  INRAE ) for her contribution in the analysis of condensed tannins. We are grateful to the  INRAE MIGALE bioinformatics platform  (http://migale. jouy. inra. fr) for providing computational resources and  A. Bernard  for initial bioinformatic analysis. Version 3 of this preprint has been peer-reviewed and recommended by  Peer Community In Animal Science  (https://doi. org/10. 24072/pci. animsci. 100009).
Safety data on long-term treatment with burosumab are lacking owing to the rarity of XLH. This postauthorisation safety study (PASS) aims to evaluate the safety outcomes in patients aged >1 year. Methods: The PASS is a 10-year retrospective and prospective cohort study utilising data from the International XLH Registry (NCT03193476), which includes standard diagnostic and monitoring practice data at participating centres. The PASS aims to evaluate frequency and severity of safety outcomes, frequency and outcomes of pregnancies in female patients, and safety outcomes in patients with mild to moderate kidney disease at baseline, in children, adolescents and adults treated with burosumab for XLH. It is expected that there will be at least 400 patients who will be administered burosumab. Results: Data collection started on 24 April 2019.
The expected date of the final study report is 31 December 2028, with two interim reports. Conclusion: This PASS will provide data on the long-term safety of burosumab treatment for XLH patients and describe safety outcomes for patients receiving burosumab contrasted with those patients receiving other XLH treatments, to help inform the future management of XLH patients. The PASS will be the largest real-world safety study of burosumab.
However, animal studies have shown evidence of toxicity and the use of burosumab is therefore not recommended during pregnancy or by women of childbearing potential not using contraception. 15 Real-world evidence on the longterm efficacy, safety and drug usage is needed to confirm how burosumab performs outside of clinical trial conditions. The International XLH Registry (NCT03193476) aims to collect data to address knowledge gaps around XLH. 9  Patient registries allow for longterm collection of patient data with fewer exclusion criteria than typical clinical studies, such as interventional clinical trials. 20 The International XLH Registry, which was established in 2017, aims to recruit 1200 patients, and is planned to run for 10 years, with the primary outcome to collect data to characterise the treatment, burden of disease, progression and long-term outcomes of XLH in patients across all age groups.
e. Named Patient Sales, Nominative Temporary Use Authorisation [TUA]) or Investigator-Initiated Study does not preclude a patient from participation in the International XLH Registry. 9 Data from the International XLH Registry will be published in an interim analysis in due course. In addition, a post-authorisation safety study (PASS) for burosumab is nested as a sub-study within this XLH patient registry and, therefore, meets the same patient inclusion and exclusion criteria. 9 As the PASS is also non-interventional, all data collected will arise from the usual clinical management of these subjects. The PASS, which is described in the current paper, aims to evaluate the long-term safety of burosumab treatment in XLH, and will be conducted using data that are routinely collected in the International XLH Registry.
Study population This study is a non-interventional PASS, using data routinely collected in the International XLH Registry. The International XLH Registry contains data on male and female patients of all ages diagnosed with XLH, regardless of their treatment regimen; the methods and rationale for the International XLH Registry have been described previously. 9 Patients included in the PASS are expected to receive treatment with burosumab according to the EU indication; that is, children and adolescents 1-17 years of age with radiographic evidence of bone disease, and in adults,  15  all of whom will also be enrolled in the International XLH Registry. Additional patients investigated for the secondary objective will similarly be taken from the International XLH Registry, with patients having the same characteristics with the exception that they will be treated with either burosumab or with other treatments for XLH.
Study design The PASS is a 10-year retrospective and prospective cohort study, for which data collection started on 24 April 2019. It is an international, multi-centre (Europe and Israel), non-interventional study, journals. sagepub. com/home/taj TherapeuTic advances in chronic disease meaning that all data gathered will arise from the patients' physician's usual clinical practice. Patients investigated for the primary objectives are expected to receive treatment with burosumab in accordance with its marketing authorisation.
Study objectives The primary objectives of the PASS are to evaluate the frequency and severity of safety outcomes in children, adolescents and adults who are being treated with burosumab for XLH, including but not limited to long-term safety, as evidenced by death, hospitalisations, cardiovascular disease, cancer, hyperphosphataemia and its complications, ectopic mineralisation, nephrocalcinosis and increased PTH levels; to prospectively evaluate the frequency and outcomes of pregnancies in female patients treated with burosumab; and to prospectively evaluate the frequency and severity of safety outcomes in patients with mild to moderate CKD at baseline treated with burosumab. The secondary objective is to perform a retrospective cohort analysis using data from the International XLH Registry to compare the safety outcomes in patients treated with burosumab to those in patients receiving alternative treatments for XLH as comparators, that is, typically conventional therapy (oral phosphate and active vitamin D analogues), the use of growth hormone (for children and adolescents), and no therapy.
Study size As this is primarily a prospective observational registry, the sample size was not based on statistical considerations. The sample size was determined based on evidence provided by XLH clinical experts across Europe, suggesting that a total recruitment target of 1200 patients with XLH would be appropriate to enable robust research to be conducted on the data contained within the registry. 9 Assuming 50% enrolment of the eligible XLH patient population, it is projected that the International XLH Registry will contain data on approximately 1200 patients spanning the 10 years of the registry's lifespan. For inclusion in the PASS, data collection will commence from the time the patient provides informed consent for participation in the International XLH Registry and PASS. Patients exposed to burosumab are estimated to number approximately 400 at the end of the 10-year life span of the PASS.
Each potential patient (or their legally designated guardian) will be given adequate verbal and written information regarding the objectives and the procedures of the International XLH Registry and the PASS, and will also be informed about their right to withdraw their permission for entry of their (or their child's) data into the International XLH Registry and the PASS at any time. The written informed consent forms (parental or adult), and adolescent assent forms if applicable, must be signed and dated before any data can be registered in the International XLH Registry and included in the PASS analysis.
Data collection and management The PASS will investigate diagnostic and monitoring practice data collected in the International XLH Registry. Patients will be followed for as long as informed consent exists, and only data collected during standard routine clinical examinations will be recorded (Tables  1  and 2 ). When patients are enrolled into the International XLH Registry, both retrospective data (past medical history) and data available at the time of consent (baseline visit) will be collected. 9 Prospective data collected at subsequent routine clinical visits will be added periodically (at least annually) to the database. No investigations outside of routine clinical practice are required. Baseline and prospective data will utilise normal ranges specific to the laboratory, hospital and/or country and will be age-and sex-adjusted.
Data analysis Given the relatively small projected number of patients who will be treated with burosumab, the sample size in the PASS may not be sufficient for formal comparative analyses. Data analyses will therefore be in the form of descriptive statistics, although the aim of course is to conduct formal statistical analyses wherever final numbers can provide sufficient power for such analyses. For the primary objectives, code lists will be developed in the database and datasets, to identify cardiovascular diseases, cancers, hyperphosphataemia and its complications, and increased PTH levels. Deaths and hospitalisations will be identified using structured data fields in the *Total number of patients to be enrolled in the International XLH Registry during the 10-year lifespan of the registry is projected to be approximately 1200.
Quality control Data entered into the International XLH Registry will be automatically checked using limits set within the database programme. Additional controls will be carried out by the contract research organisation (CRO) managing the International XLH Registry to detect inconsistencies, such as erroneous value entries or the absence of any follow-up assessments. For example, if an entry is made that falls outside the normal range of that particular variable, the EDC system highlights that specific entry/nonentry to the CRO. The queried entry/non-entry is then checked, and the source data are verified to either confirm or correct the data entry.
9  The  To be submitted 5 years after initiation of the PASS in paediatric populations (i. e. a report covering use in all populations) Final report of study results To be prepared 10 years from the start of data collection in the paediatric population To be prepared 10 years from the start of data collection in the adult population et al. 9  Even though the International XLH Registry and PASS are the largest datasets of XLH subjects in the world to date (targets of 1200 and 400 patients, respectively), the sample size may still result in limited statistical analyses; this will not be known until the first interim analysis. In addition, despite patients being under the care of a physician for their condition, data capture on intervening events may be incomplete if data are not entered meticulously and/or if appointments are infrequent, especially during the restrictions associated with the coronavirus disease 2019 (COVID-19) pandemic.
To minimise selection bias, a comprehensive screening process was conducted to identify XLH-treating hospital sites, which were then subsequently approached and invited to participate in the International XLH Registry. All sites that were successful in the screening process and provided consent to participate in the International XLH Registry were then also invited to participate in this embedded PASS. As the patient population may not be large enough to utilise precise case-control matching, a retrospective cohort analysis based on burosumab exposure and burosumab non-exposure will be undertaken. Finally, to standardise the nature of the information collected, every International XLH Registry hospital site will use the same EDC system and undergo the same training for their staff. Source data verification of a representative portion of raw data at participating centres will be implemented to verify the quality of the data collection, although it should be noted that the International XLH Registry does not mandate investigations outside of standard care as determined by the treating physicians.
Conclusion This PASS will enable the collection of data relating to the long-term safety of burosumab treatment for children, adolescents, and adult patients with XLH. It will allow the description of safety outcomes of patients on burosumab. It will also complement other data generated from the International XLH Registry, which will provide comprehensive information on multiple groups of patients with XLH, allowing us to further evaluate the natural history of the disease to ultimately help towards improving multidisciplinary care for all patients with XLH.
Acknowledgements The authors thank the patients/guardians who agreed to take part in the registry/PASS. Medical writing support for this manuscript was provided by  Phil Long, PhD , and  Edward Maguire, PhD  ( 90TEN ), funded by  Kyowa Kirin International plc. The authors maintained full editorial control of the paper and provided their final approval of all content. The International XLH Registry was implemented by  Kyowa Kirin International plc , and supported first by Medialis Ltd. , a CRO, for the first year of the registry; then in March 2019, Kyowa Kirin International plc commissioned a new CRO, that is, IQVIA, to support the  International XLH Registry , taking over CRO duties from the previous CRO. As part of the transition, Kyowa Kirin International plc updated the core documents to refer to the burosumab PASS as a sub-study embedded within the main International XLH Registry and reassigned the role of data controller from the patient to the sponsor.
g. , sex, date of birth, educational level, occupation, smoking status, number of children)  [22] , and diet (see below). An electronic informed consent is provided by each participant. The NutriNet-Santestudy, registered at ClinicalTrials. gov (NCT03335644), is conducted according to the Declaration of Helsinki guidelines and is approved by the Institutional Review Board of the French Institute of Health and Medical Research (Inserm) and the Commission Nationale de l'Informatique et des Libertes (CNIL 908450/909216). All methods have been described in line with the Strengthening the Reporting of Observational Studies in Epidemiology-Nutritional Epidemiology guidelines (S1 STROBE-nut Checklist). The NutriNet-Santestudy was developed to investigate the relationships between multiple dietary exposures and the incidence of chronic diseases, such as cancer.
Artificial sweetener intakes Artificial sweetener intakes were assessed through the 24-hour dietary records, in which brands and commercial names of industrial products were routinely collected, enabling us to assess exposure to each food additive. Additive exposure assessment in the NutriNet-Sante ćohort has been previously described in detail  [30]. Briefly, the presence or absence of each additive in each specific food product consumed was determined using 3 large-scale composition databases: the French food safety agency database Oqali (https://www. oqali. fr/oqali_eng/) [31] , Open Food Facts (https://fr-en. openfoodfacts. org/) [3] , and Mintel's Global New Products Database  [32]. Dynamic matching was applied, meaning that products were matched date-to-date: The date of consumption of each food or beverage declared by each participant was used to match the product to the closest composition data, thus accounting for potential reformulations.
Cancer case ascertainment Participants are asked to report all medications/treatment and major health events on the annual health questionnaire, a specific check-up questionnaire every 6 months, or at any time on their NutriNet-Santeaccount. In order to validate reported incident cancer cases, participants were contacted by a physician of the research team to provide any relevant medical and anatomopathological reports. If necessary, the participant's physicians and/or hospitals were also contacted to provide the requested information. All cases reported up to 22 January 2021 were investigated. In addition, the data are linked to the medico-administrative databases of the national health insurance system database (SNIIRAM) and the national mortality registry (CepiDc) to ensure completeness of morbidity and mortality information and to limit bias associated with unreported cases.
P-trend was obtained using the ordinal score for each group (non-consumers: 1; lower consumers: 2; higher consumers: 3). The proportional hazards assumption of the Cox model was confirmed with the rescaled Schoenfeld-type residuals method (Fig A in S1 Appendix). We assessed linearity by comparing the model with the 3 distinct categories of sweetener intake to a model with a linear trend across these categories, using the Akaike information criterion. Consumer (overall) versus non-consumer analyses were also conducted, and this model with 2 categories of exposure was compared to the main model with a formal test for heterogeneity. Missing values for any covariates were handled using the multiple imputation by chained equations (MICE) method  [37]  (15 imputed datasets) (details in Method B in S1 Appendix).
The main analyses added following the review process were as follows: linearity check in relation to the trend across categories, interaction tests between artificial sweetener exposure and menopausal status, heterogeneity tests to compare exposure coding strategies, models restricted to non-smoker participants, and analyses exploring multiple exposure to several types of sweeteners. All tests were 2-sided, and P < 0. 05 was considered statistically significant. The statistical analysis software SAS, version 9. 4, was used for analyses.
These consumption data were merged with data from several large composition databases and results from thousands of laboratory assays in food matrixes. Also, dynamic matching with the date of consumption was used to select the most appropriate composition data, which reduced potential bias due to reformulations. Thus, total artificial sweetener intake through sources other than just ASBs could be considered. However, several limitations should be acknowledged. First, caution must be taken in extrapolating the results to the whole adult French population. As generally observed in volunteer-based cohorts, participants were more likely to be women, to have higher educational and socio-professional levels, to have health-conscious behaviours (diet and lifestyle)  [59] , and to be older on average (while artificial sweetener intake is lower in older individuals).
Acknowledgments We thank  Thi Hong Van Duong ,  Regis Gatibelza ,  Jagatjit Mohinder , and  Aladi Timera  (computer scientists);  Julien Allegre ,  Nathalie Arnault ,  Laurent Bourhis , and  Nicolas Dechamp  (data manager/statisticians);  Sandrine Kamdem  (health event validator); and  Maria Gomes  ( Nutrinaute support ) for their technical contribution to the  NutriNet-Santestudy  and  Professor Raphae ¨l Porcher  for his help and expertise in biostatistics. We thank all the volunteers of the NutriNet-Santecohort.
This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (grant agreement No  864219 ), the  French National Cancer Institute  ( INCa_14059 ), the  French Ministry of Health  (arrête  ´29. 11. 19 ) and the  IdEx Universitede Paris  ( ANR-18-IDEX-0001 ). This project was awarded the  NACRe (French network for Nutrition And Cancer Research) Partnership Label. Researchers were independent from funders. Funders had no role in the study design, the collection, analysis, and interpretation of data, the writing of the report, and the decision to submit the article for publication.
Data collection methods Unstructured observations. Unstructured observations were designed to provide contextual detail about handwashing. Observations took place in eight case households and eight comparison households. Observations were for 2-3 hours, typically beginning at 6am and finishing when the participant had to depart for work. Observers wrote down all actions that that were done by all household members and the time actions took place. Observers paid attention to 'critical times' for handwashing which were defined as handwashing after using the toilet, or cleaning a child's bottom, and before preparing food, eating food or feeding a child. Observers noted whether hands were washed at these critical times and whether soap was used. In-depth interviews. A total of 51 IDIs were completed, involving 24 people from case households and 27 people from comparison households.
Three FGDs were conducted with men, two of which were with IDPs and one with host community members. Six participatory activities were included in FGDs to explore the prioritisation of hygiene challenges, perceived risk of cholera, attitudes towards people who had cholera, preferences related to infrastructure and soap, and motivations of behaviour. See S3 Table for descriptions of these activities. Data collection. The data was collected by four of the authors (SW, ACM, MMB, FKM). We were a team with mixed cultural backgrounds (British and Congolese). Two days of classroom-based training was provided on the research rationale and the methods. We then piloted the methods in a similar setting and adapted the tools as necessary. All IDIs and FGDs were conducted in Congolese Swahili and audio recorded.
Observation notes were taken by hand. At the end of each day of data collection we reflected on our findings and captured this through written field notes  [24]. Data management and analysis. Preliminary data analysis was done concurrently with data collection. This allowed us make theoretical and methodological notes  [25]  and decide when we had reached a point of saturation. All audio recordings from IDIs and FGDs were transcribed and translated. Methods with semi-quantitative data such as ranked or scaled information were summarised in spreadsheets. Visual data such as drawings, photos and videos were descriptively summarised. All data and the field notes were imported into NVivo 12 software. The data analysis followed the process outlined by Braun and Clarke  [26]. Data were classified according to whether the participant was from a case household or a comparison household.