dataesr/scientific-paragraphs-categorization huggingface dataset:
Data analysis We converted raw LC-MS/MS spectra to Mascot generic files (MGF) using MSConvert from ProteoWizard (v. 3. 0. 11781) by selecting the top 100 peaks. MS/MS database searches were performed using Mascot (v. 2. 6. 0) against available sequences in a custom curated Dairy Database  (Wilkin et al. 2020a ) and SwissProt, with both databases decoyed with a full reverse listing of all sequences in order to calculate the false discovery rate. Mascot settings included the instrument type set to Q-Exactive and the enzyme set to trypsin. Peptide mass tolerance was set at 10 ppm, with fragment mass tolerance of 0. 01 Da, with an allowance for monoisotopic mass shifts. As we reduced and alkylated the disulfide bonds, carbamidomethyl of cystine (C) was set as a fixed modification, and based on previous observations of modifications detection in ancient dental calculus  [29] [30] [31] , we chose deamidation of asparagine (N) and glutamine (Q) and oxidation of methionine (M) as our variable modifications.
Peptide search results were additionally filtered using the custom R script MS-MARGE (Evalue of between 0. 01 or 0. 001, depending on the resulting false discovery rate (FDR))  [32]. MS-MARGE calculates the FDR by comparing the number of forward sequence hits to the number of reverse sequence hits. This allows the user to adjust the E-value cutoff manually in order achieve an appropriate FDR for each sample. After data filtration, our average peptide FDR was 0. 84 with an average protein FDR of 1. 93. Peptide homology was additionally tested using BLASTp. All raw, processed and result files are available via the ProteomeXchange under accession PXD029267. We further conducted an analysis of the overall proteome preservation of each dental calculus sample  [28]. Using a curated Oral Signature Screening Database (OSSD), we looked for a combination of lab contaminants, common contaminants introduced through contact with archaeological and curation contexts, common bacteria found in the human microbiome, and human immune proteins that are regularly identified in the oral cavity.
While Bleasdale and colleagues  [28]  applied the OSSD database to their raw MS/MS data as a screening device, we searched our filtered results against the proteins included in Bleasdale's OSSD as a way to test the relative preservation of all the samples in our study. We compared the number of proteins commonly identified within the oral cavity (oral microbiome and salivary immune proteins) against a total count of proteins identified from the four categories combined. Ancient protein studies on human dental calculus  [28, 33, 34]  have demonstrated that the overall proteome for archaeological samples generally consists of proteins from four major sources: those produced during immune response found within saliva, oral microbiome bacteria, environmental contaminants (from the soil environment, human handling in excavation and curation, and cross contamination from storage or display near other human and animal skeletons), and laboratory contaminants (introduced during extraction protocols and commonly found in mass spectrometry facilities and reagents).
Methods A cross-sectional study was carried out using secondary data collected from CMLG dental consults' patients. The study protocol was analysed and validated by the Rennes University Hospital ethics committee (notice n°20. 143). The study included patients who were registered on the online agenda (Google Agenda) for a dental consultation between December 2, 2016 (opening date of the dental consultation), and September 6, 2019 (end of data collection). Data were extracted from those patients' files on Access and M edaplix database software. Exclusion criteria were incomplete files and/or nonmigrant patients, defined in this context as a patient having French nationality. Oral examinations were performed by 2 dentists with 15 years' experience on a medical examination table, using a probe and a mirror, under ceiling lighting.
Teeth were not cleaned or dried before the exam. Only cavitated dental caries were recorded (caries classified as 5 or 6 according the International Caries Classification and Assessment System), for both permanent and primary teeth. Information concerning the oral sphere was registered in an online document on M edaplix software (word processor). In addition, the administrative file on Access software recorded patient's background information: sex, date of birth, age, country of origin, spoken languages, legal status (asylum-seeker; refugee; European Union citizen; illegal immigrant; unaccompanied underage children; and those with a residence permit "private life and family" or "subsidiary protection," which concerns persons whose asylum application was rejected but who were authorised to stay in France country because of the risks they might face in their country of origin), social security rights, family status (single, with family), accommodation (fixed, temporary, absent), and date of entry in France.
General pathologies were also implemented in Access software. Patients' medical history was used to classify them according to the American Society of Anesthesiologist (ASA) Classification. 13 fter anonymisation, all of the data were extracted from the Access and M edaplix files and coded. The extraction was performed by a single examiner (CP) after a calibration process conducted by 3 of the researchers (CP, VM, and AC) on the first 15 files. Oral diseases' diagnostics were classified according to the 11th revision of the International Classification of Diseases (ICD-11) and binary coded (yes/no). Twelve diagnostic codes were used, including dental caries, disorders of tooth development, disease of pulp or periapical tissues, missing tooth, dislocation of tooth, calculus, periodontal disease, fracture of skull or facial bones, dermatological lesions, cellulitis, disease of salivary glands, disorders of orofacial complex, and temporomandibular joint disorders.
Eventually, in order to evaluate the need for oral care, a binary variable "major need for oral care" was created. Patients were considered positive for this variable when they presented at least one of the following criteria: 4 or more untreated cavitated dental caries, 3 or more teeth needing extraction, need for prosthetic treatment (removable and/or fixed prosthesis), and need for periodontal treatment (excluding simple scaling). These criteria were selected to differentiate patients who might need multiple treatment sessions and potentially more complex technical facilities from patients who might be cared for under more simple conditions. Data were collated in Microsoft Excel software (version 16. 34) and analysed with RStudio software (version 3. 6. 1). Relationships between "major need for oral care" and other qualitative variables were assessed, using chi-square for qualitative variables.
Results Two hundred thirty-two patients consulted CMLG dental consultation during the inclusion period. One hundred patients were excluded for incomplete files: 60 were excluded due to lack of information concerning oral health status (the M edaplix file). This lack of data in the files is mainly explained by the inconsistency in the filling out of the files by the dentists at the start of the dental consultation and, more sporadically, technical difficulties to implementing the computer files. The other 40 exclusions were due to a lack of information in the administrative file (Access software), inducing an absence of data that were essential to the analysis, such as geographical origin or language spoken. Two patients were excluded for not being migrants (French citizens). One hundred thirty patients were eventually included in this study.
Above the levelled remains of 5D-11-2nd and this burial was built structure 5D-11-1st. It is a pyramidal platform with a very unusual shape: it does not have the same number of levels on its east and west façade. Moreover, the north and south façades do not seem to be stepped. The extension of the test pits did not locate any post holes but it is possible that a pole and thatch structure covered the top. 5 Structure 5D-15, which sits to the north, is the main building of the West Plaza. In our view, its architectural sequence is questionable. The axial trench and tunnel excavation leave some doubt about the successive architectural developments. This is indeed the main difficulty of taking over archival data without having been able to observe the stratigraphy in the field. Thus, the author proposes that two successive painted staircases could constitute the only surviving remains of 5D-15-6th and 5th, or those of an earlier buried structure (Sub) with no relation at all to 5D-15.
Data. SIVIC (Système d'information pour le suivi des victimes d' attentats et de situations sanitaires exception- nelles) is a French national database created to keep track of casualties from terrorist attacks. Since 2015, its scope has been extended to include the surveillance of exceptional sanitary situations. It was thus used from mid-March 2020 to register data relative to patients infected with COVID-19. Only Paris-area data were analyzed. The portal is accessible to identified users from different entities: hospitals, ambulance service (Service d' Aide Médicale Urgente-SAMU), regional health agencies (Agence Régionale de Santé-ARS), etc. It is part of a broader crisis management information system covering the complete patient pathway allowing real-time follow-up of healthcare capacities.
SIVIC data used in our study includes anonymized patient information, current patient status (hospitalized, deceased or returned home), type of clinical care received (conventional hospitalization, intensive care, rehabilitation and recuperative care, or psychiatric hospitalization), date of admission into each of the mentioned services, age, gender, hospital name and department. We are thus able to infer patient transfers. To focus on adults patients, we removed patients under 16 years old, patients whose status was updated several times a day; pathways solely comprised of either return home, rehabilitation and recuperative care, or death; pathways starting with either rehabilitation and recuperative care or psychiatric hospitalization; and emergency department (ED) visits.
Ethical and legal considerations. The study was based on a secondary use of a database/pseudonymised data collected from health professionals. The purpose of study is the epidemiological surveillance at the regional level since the article 11 of the Law n° 2020-546 of May 11, 2020. This article extending the state of sanitary emergency, allows the regional health authorities (Agence régionale de santé-ARS) to adapt the existing information systems to fight against the propagation of the epidemic of COVID-19 and for the duration strictly necessary to this objective or, at the latest, until July 31, 2022. Article 14 of Decree No. 2020-551 of May 12, 2020 on the information systems mentioned in Article 11 of Law No. 2020-546 of May 11, 2020 extending the state of health emergency already authorizes the ARS "to implement processing of personal data for the following purposes: […] 3° Epidemiological surveillance at the regional level.
Our study has several limitations. First, the analysis was not done on the whole French territory: the data concerns only the Paris area, which has been strongly impacted by the epidemic and whose population of 12 million represents around 20% of the French population. Second, the data are essentially administrative and contain very few medical elements. It was difficult to describe the patients' clinical state more precisely, in particular the clinical severity. We did not explore the clinical factors explaining the transitions between the different hospital sectors. Nevertheless, an analysis of the data from hospital activity obtained by the French national administrative database (PMSI) will be forthcoming. Third, the pathway analysis did not take into account the daily availability of hospital beds, although this factor can play a determining role in admission type and length of stay.
Criteria for Discontinuing or Modifying Allocated Interventions Any participant could discontinue participation in the research at any time for any reason. The investigator could temporarily or permanently discontinue one's participation in the research for any reason that affected the participant's safety or was in the best interests of the participant. In the event of premature termination of the research, or withdrawal of consent, data collected prior to the premature termination could be used. The reasons for discontinuing participation in the research were to be registered in the participant's file.
Data Management Data management and statistical analysis were performed independently of the sponsor and of investigators by the CRU (Unité de Recherche Clinique, Hôpital Ambroise-Paré, Boulogne-Billancourt, France). Data entry was performed by the investigator at enrolling sites using a web-based data entry system. An electronic case report form (eCRF) was developed by the CRU using dedicated software (CleanWeb) to facilitate data control and monitoring. Each patient was assigned a unique study ID that was used to index the eCRF and related study documents. It captured data from each included patient. All information required by the protocol had to be entered in the eCRFs. Data were recorded in the eCRF as and when they were obtained. Any missing data had to be coded. In-built consistency checks instantly verified the coherence of data.
During these visits, the following elements were reviewed: • Written consent. • Safety and rights of participants being protected. • Compliance with the study protocol and with the procedures defined therein. • Quality of data collected in the eCRF (accuracy, missing data, consistency of the data with the "source" documents, such as medical files, appointment books, original copies of laboratory results, etc. ). • Data were authentic, accurate, and complete. The CRA systematically checked baseline characteristics, eligibility criteria, primary outcome, and serious adverse events reported in the eCRF for all study participants. In addition, for one-third of the study population, all data reported in the eCRF were validated against a patient's original chart. Serious adverse events and major protocol violations were reported to the DRCI APHP and Comité de protection des personnes (CPP; Ethics Committee).
At the end of the study, after clarification of discrepancies (data cleaning) and data validation, the database was frozen and transmitted to the statistician, following procedures established by the sponsor. Each patient participated in the trial for 12 months. Premature study withdrawal was at the request of the patient or next of kin and their reasons were recorded in the eCRF and the patient's medical file. Withdrawn patients were not replaced. However, patients who were lost to follow-up or did not receive the randomly assigned treatment were not considered to be prematurely withdrawn from the trial.
Confidentiality As for any clinical research supported by the AP-HP, processing of personal data complied with the methodological requirements for a clinical trial established by the French Data Protection Authority Commission Nationale de l'Informatique et des libertés Commission Nationale de l'Informatique et des libertés (CNIL) in January 2006 for biomedical research. During and after the clinical research, all collected data sent to the sponsor by the investigators (or any other specialized collaborators) were pseudonymized using only the participant's initials. Under no circumstances the names and addresses of the participants involved had been shown. Only the participant's initials and an encoded number specific to the study indicating the order of enrollment were recorded. Moreover, all nominal data were erased on the copies of the source files that were used for research documentation.
Methods in Analysis to Handle Protocol Nonadherence and Any Statistical Methods to Handle Missing Data Intent-to-treat statistical analysis will be performed after all patients have completed the 1-year follow-up. Accordingly, all patients will be analyzed in the arm they were allocated to, regardless of protocol deviations. In addition, missing outcome data will be imputed. Prior to any data analysis, a detailed statistical analysis plan will be drawn up by the study statistician. There will be a comprehensive report of the statistical analysis, following the CONSORT statement recommendations. Any change in the analysis plan will be justified in this final report. While no missing data are expected, the maximum bias method will be used for analysis of the primary outcome, replacing missing data by a success in the control arm and by a failure in the intervention arm.
Plans to Give Access to the Full Protocol, Participant-Level Data, and Statistical Code Those with direct access in accordance with the laws and regulations in force, in particular articles L. 1121-3 and R. 5121-13 of the Public Health Code (eg, investigators, those responsible for quality control, monitors, CRAs, auditors, and others involved in collaborating on trials), will take all necessary precautions to ensure the confidentiality of information relating to the tested drugs, the trial, and the trial participants, especially with regard to their identity and the results obtained. The data thus collected during quality controls or audits are then made anonymous.
Availability of Data and Materials In accordance with Good Clinical Practice: (1) the sponsor is responsible for ensuring all parties involved in the study agree to guarantee direct access to all locations where the study will be carried out, the source data, the source documents, and the reports, for the purposes of the sponsor's quality control and audit procedures or inspections by the competent authority;  (2)  the investigators allow individuals in charge of monitoring and quality control to have access to the documents and personal data strictly necessary for these tasks, in accordance with the statutory and regulatory provisions in force (Articles L. 1121-3 and R. 5121-13 of the French Public Health Code). The AP-HP had full access to patients' charts and checked all data recorded in the eCRF against original charts.
Results The study was funded by the Ministry of Health in June 2010. It was approved by the Ethics Committee on July 8, 2011. The first and last patient were randomized on December 20, 2012, and September 1, 2017, respectively. A total of 546 patients were enrolled across 11 ICUs. At present, data management is ongoing, and all parties involved in the trial remain blinded. The first patient was recruited on December 20, 2012, and the last patient on September 1, 2017. The study was never suspended. The assessor of the primary endpoint and study statistician remained blinded to study intervention throughout the trial. Data management is ongoing. Release of the results is planned for end of 2022. There were 10 amendments to study protocol (Multimedia Appendix 1). All amendments were approved by investigators, study statistician, AP-HP, CPP, and ANSM.
The DRRC organized data monitoring and quality audits. Baseline characteristics, eligibility criteria, primary outcome, secondary outcomes, and serious adverse events reported in the eCRF were systematically checked against original charts for all research participants. In addition, for one-third of the study population, all data reported in the eCRF were validated against a patient's original chart. Serious adverse events and major protocol violations were reported to the DRRC, ANSM, and CPP. The study coordinator had quarterly face-to-face meetings with the DRRC and AP-HP to monitor trial conduct according to the highest standard for protection of research participants. All randomized patients completed follow-up for the primary outcome. Monitoring of the data has been completed. Freezing of the database and statistical analysis are planned within the next 6 months.
Acknowledgments We thank  Chanez Lazizi ,  Sonya Ouali ,  Sonia Krim ,  Karima Mesbahi ,  Chamssedine Mediouni ,  Layidé Meaudé , and  Nawal Derridj-Ait-Younes of the Center for Clinical Epidemiology ; we also thank all families and staff at participating sites who agreed to take part in the  SUIVI-REA study , and all members of the Trial Steering Committee and Independent Data and Safety Monitoring Committee. This study was funded by the  Clinical Research Hospital Program in 2010 , and the  Ministry of Health  confirmed funding under contract number  AOM10072. The study funder and co-sponsors play no part in study design, data collection or analysis, writing of the report, or the decision to submit for publication; the responsibility for these activities lies with the Trial Management Group.
It is also this function that revolves the Unique Patient Identifier. Integration of the unique patient identifier method in an HIS: Patient ID works within a hospital information system. We test our model by integrating it into the electronic pregnancy monitoring system of the University Hospital of Bobo-Dioulasso (e-Lafia)  (7). E-Lafia is a Pregnancy Tracking Information System. Patient information is collected in e-Lafia through a registration form. This information is stored in a MySQL database. E-Lafia HIS has been selected since it uses healthcare interoperability standards such as HL7v3, FHIR, DICOM, thus facilitating interaction with our unique identification system.
Background: The adoption of health technologies is key to empower research participants and collect quality data. However, the acceptance of health technologies is usually evaluated in patients or healthcare practitioners, but not in clinical research participants. Methods: A 27-item online questionnaire was provided to the 11,695 members of a nutrition clinical research participant database from the Nantes area (France), to assess (1) participants' social and demography parameters, (2) equipment and usage of health apps and devices, (3) expectations in research setting and (4) opinion about the future of clinical research. Each item was described using frequency and percentage overall and by age classes. A global proportion comparison was performed using chi-square or Fisher-exact tests. Results: A total of 1529 respondents (81.
0% women, 19. 0% men) completed the survey. Main uses of health apps included physical activity tracking (54. 7%, age-related group difference, p < 0. 001) and food quality assessment (45. 7%, unrelated to age groups). Overall, 20. 4% of respondents declared owning a connected wristband or watch. Most participants (93. 8%) expected the use of connected devices in research. However, protection of personal data (37. 5%), reliability (35. 5%) and skilled use of devices (28. 5%) were perceived as the main barriers. Most participants (93. 3%) would agree to track their food intake using a mobile app, and 80. 5% would complete it for at least a week while taking part in a clinical study. Only 13. 2% would devote more than 10 min per meal to such record. A majority (60. 4%) of respondents would accept to share their social media posts in an anonymous way and most (82.