dataesr/scientific-paragraphs-categorization huggingface dataset:
The lack of information about qPCR conditions limits interpretation of these quantitative results, but sampling protocol could be a significant parameter. In this study, rather large amounts of dental plaque were collected. According to inclusion criteria, subjects participating in the study had an average whole mouth dental plaque scores of >1. 5 (Plaque Index) and an average gingival score of >1. 0 (Gingival Index). The sampling method consisted in whole lower jaw scraping of supragingival dental plaque, similarly to Adams et al. sampling method. Usually, sulcus fluid samples for qPCR analyses are taken with paper points  [60]. An exclusion criterion for the patients was "untreated caries or significant periodontal disease". But qPCR data for the marker bacteria of caries (S. mutans) and periodontitis (Red complex species: P.
Monitoring Methodology Ultra-high-resolution (3 m) RapidEye satellite images were used in order to delineate the distinctive geological and geomorphological features and their areal changes, provided by Planet Labs Inc. (2020). From the 4-band spectral dataset, only visible wavelengths were used. A monthly interval was chosen based on the supposed and observed rate of changes, the availability of ideal coverage and the required processing time. The availability of cloud-free coverage (to avoid similar reflectance values of salt and cloud pixels, and the eclipse of features) and the orbit of the satellite through Dallol meant that the intervals used varied slightly, but generally, the first day of each month was used. A semi-automated workflow was created (Fig. 6 ), where manual intervention is restricted to data cleaning and supervision.
The workflow was executed separately for Black Mountain and the central crater area of Dallol in order to minimise coverage of areas with little, slow or no change (e. g. salt flats, salt canyons) outside the geothermal areas. The input satellite images were classified by RGB pixel values with ENVI, with the supervised, maximum likelihood classification method of the software. Generally, 7-10 classes were delineated for Black Mountain and 10-15 for Dallol, with at least 3 training sites per class. The accuracy of pixel classification was generally around 70-80% (classified categories versus the extent of expected classes and features); therefore, purging or rectification of data was required. Further phases of the workflow were carried out in QGIS (QGIS Development Team 2020), using the vector output of classification from ENVI.
7 ). Since the start of monitoring in January 2017, nearly 3 years of dataset have been collected. The extraction of the areal extent of each geothermal feature by month allows a quantitative overview of changes and an initial idea about activity patterns. However, care should be taken extrapolating this, and several more years of consistent monitoring are required for a long-term baseline. These should be validated with regular field observation. It is beyond the scope of this paper to give a detailed overview of processes and landforms, and we focus on (i) the description of observations that are visible on the satellite images, (ii) their interpretation, and (iii) establishing a framework for further observations. The accuracy of the automated classification was significantly improved with numerous human validation iterations, but this could not match field observations.
Improving Visitor Resilience Through Web Publication The dataset of the monthly monitoring process obtained in this work, along with general features about visiting the Danakil Depression and Dallol, is made accessible on a website (http:// dallol. lmv. uca. fr/). The principal goal of the monitoring and its dissemination is to give a source of information to visitors, including guides, tourists and researchers, about the changing patterns of geothermal activity. The website's monthly mapping acts like a weather forecast, but it also gives a retrospective snapshot of the most recent situation (Fig. 11 ). The interpretation and the deduced hazard maps are published as downloadable files that could be upgraded in the future to a webmap solution. Slideshows of raw satellite images also help follow up changes at Mount Dallol and Black Mountain.
Designation of Visitor Routes with Respect to Geohazard Mitigation and Resilience At the time of writing (2019), visitors to the area do not follow a well-established trail, but rather a simple ascent through salt blocks from the 'parking lot'. In the geothermal zone, they can wander around freely under the rough supervision of tour guides, and it is easy to ignore potential hazards. Based on the almost 3-year-long dataset of activity patterns, and the level 4 or 5 hazard category areas, a safe visitor circuit was designated in the central area of Dallol and around the Black Mountain (Fig. 24 ). It does not mean that the spectacular, constantly changing landforms and.
Acknowledgements High-resolution satellite images for the monthly monitoring are provided by  Planet Labs Inc. ( 2020 ). The reconnaissance field trips of 2017 ( Benjamin van Wyk de Vries & Miruts Hagos ) and 2019 ( Viktor Vereb ,  Benjamin van Wyk de Vries, Miruts Hagos ) were financed by  Université Clermont Auvergne. The double-degree PhD research of Viktor Vereb on the connection of geoheritage and natural hazards in areas of different geographical environments and heritage management practices is financed by  Campus France  and the Hungarian state. Special thanks go to  Amleset Gebreegzabher Gebrewahd  for her help with contacting the  Afar Region Cultural and Touristic Bureau. We would also like to express our special gratitude to the reviewers, who have further improved the manuscript with their suggestions during the review process.
Design of the study and sample of the population This retrospective cohort study focused on PWS identified from a representative sample of 1/ 97 th of the French population that is known as the EGB (echantillon généraliste de bénéficiaires, general sample of beneficiaries). Follow-up dental care was explored for all people in the EGB over a period of 3 years (2014 to 2017). The EGB was constructed on a national level by the French health insurance agency, which manages the representativeness of the data. It was drawn randomly from a check digit of the beneficiary's identification number. From a stable, representative sample of the French population, these data allowed us to estimate care pathways and follow-up while excluding the effects of the geographical area, health facility or practices.
The EGB was based on the "National System of Health Data" (SNDS) database which collects individual hospital and non-hospital healthcare data. These data include automatically recorded healthcare acts such as biological testing, treatment, medical transport and a register for long-term diseases. Health insurance is compulsory for everyone living in France, and each health act is reimbursed by the French health insurance agency and therefore recorded in SNDS. These data include all types of mandatory health insurance systems (the main national health insurance, health insurance for the agricultural sector, health insurance for the self-employed and 12 other specific health insurance schemes) covering more than 90% of the French population. In 2016, the EGB sample was made up of almost 600,000 health insurance beneficiaries.
Groups constitution Persons with schizophrenia identification. PWS were identified for the year 2014 by an algorithm that included: • Diagnostic Codes F2 in the register of long-term diseases [28] in 2014 AND {(at least three deliveries of antipsychotics in 2014) OR (Diagnostic codes F20 as a main or associated diagnosis in hospital discharge abstracts in 2012 or 2013 (hospital data for medicine, surgery and obstetrics)} The purpose of this algorithm was to identify adult schizophrenia in the SNDS database. It was built using the information obtained from interviews with experts in schizophrenia and based on their procedures to identify in-or out-patients  [29]. Control identification. The control group was composed of all the people who are included in the EGB and not included in the cohort of patients with schizophrenia.
Our algorithm did not include data from psychiatric hospitals. Second, we identified PWS with a less restrictive algorithm, including the presence of • one of the F20 diagnostic codes in the register for long-term diseases, • and/or one of the F20 diagnostic codes as the main or associated diagnoses in discharge abstracts (hospital data for medicine, surgery and obstetrics), • and/or at least three annual deliveries of antipsychotics in 2014. A p-value of 0. 05 was set to define statistical significance for all analyses. SAS 9. 3 software was used for data analyses. The geographic information system MapInfo 11. 0 was used for mapping.
Limitation and strengths The algorithm used to identify PWS did not include the database of psychiatric hospitalizations even though it was included in the reference algorithm. This is because the EGB does not include the French psychiatric database. However, the persons who were covered as part of long-term disease with diagnostic codes F20-represent approximately 70% of people identified by the SNDS as suffering from psychotic disorders. Furthermore, this bias is probably of limited effect. The potential consequence would be an inclusion of unidentified cases of schizophrenia in the control group, therefore reducing the amplitude of the reported associations. One of the strengths of our study is the representativeness of the EGB of the French general population and its high stability over time.
An additional strength is the fact that health insurance is compulsory for all French residents. This means that all health care acts are reimbursed, and all reimbursements are automatically recorded and transferred to the SNDS database. The quantification of dental care can therefore be considered exhaustive. Moreover, our results suggest a spatial prevalence of schizophrenia that is tied to urbanicity. Urbanicity is a well-established environmental risk factor for developing schizophrenia  [49] , and the prevalence of schizophrenia is known to be greater in cities than in rural areas  [49, 50]. In accordance with a number of published studies, our PWS sample was predominantly male  [51]. However, patients were more likely to be aged 35 to 64 even though the initial symptoms of schizophrenia often begin before 20 years of age  [52].
Methods This was a cross-sectional study that collected multi-country data through an online survey. The study was approved by the Research Ethics Committee of the Faculty of Dentistry, Alexandria University, Egypt (IRB 00010556)-(IORG 0008839)/6-11-2016), with further approvals from the University of Giessen in Germany (AZ: 55/20), Nigeria (IPH/OAU/ 12/1556), Bosnia and Herzegovina (18/4. 3. 26/20 and 01-952/ 2), Indonesia (FKGUI/IV/2020, protocol #: 090050420), Iran (IR. TUMS. DENTISTRY. REC. 1399. 001) and Jordan (220/132/ 2020). We included dental academics or educators working in dental academic institutions. Dental students (undergraduate and postgraduate) and dentists who do not work in dental educational institutions were excluded. Table  1  lists the countries included in the study.
The number of dental academics per country was estimated by using a ratio of 1:5 dental academics to dentists, based on information extracted from the World Health Organization's (WHO) Global Health Observatory database  [15]. The required number of dental academics per country to achieve statistical power was calculated, assuming 95% confidence level, 5% margin of error, and 71% adherence to infection control practices among dental academics  [16]. We identified the countries with a large number of dentists from the Global Health Observatory  [15]  with the assumption that these countries also have large numbers of dental academics (there is no data available about the global distribution of dental academics). These countries were Brazil, India, the United States, China, Japan, and Germany, and we invited collaborators from these countries to join our study.
We calculated the percentages of correct responses and plotted them as bar graphs. We assessed the internal consistency with Kuder-Richardson formula 20 (K-R 20), a modification of Cronbach's alpha  [21]. We compared the knowledge domain percentage scores using multivariate analysis of variance (MANOVA), controlling for country effect, to assess whether there were differences in the knowledge about various aspects of COVID-19. We used the linear mixed-model procedure in SPSS version 23. 0 to construct unadjusted multilevel linear regression models, in which we entered the explanatory variables one at a time. Multilevel linear regression models were appropriate to use to account for the clustering of academics within countries: countries' differences were expected to be associated with the level of knowledge.
Acknowledgments We are grateful to all the academics who kindly responded to the survey and answered our questions in these difficult times. 8  Department of Oral & Maxillofacial Surgery, Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India. 9Department of  Preventive Dental Sciences, College of Dentistry, Imam Abdulrahman Bin Faisal University, Dammam ,  Saudi Arabia. 10Department of  Preventive and Biomedical Science, College of Dentistry, University of Science & Technology, Sanaa, Yemen. 11Department of  Preventive Dentistry, Faculty of Dentistry, Jordan University of Science and Technology, Irbid, Jordan. 12Center for Oral Bioengineering, Barts and the  London, School of Medicine and Dentistry, Queen Mary University of London, London, UK. 13  Department of Conservative Dentistry, Faculty of Dentistry, Alexandria University, Alexandria, Egypt.
B The mechanical properties (Young modulus and Shear stress) were measured on wet samples as a function of immersion time (Figure  6 ). While no significant changes in shear stress, within the accuracy of the measurement, were recorded, a net fall in the Young modulus can be seen after immersion for up to three days. As all the measurements were corrected to the swelling of the sample, such a drop can be attributed to the diffusion of water within the composite structure, most likely due to pores being formed during the processing. After the initial drop, the Young modulus does not seem to be, drastically, impacted by either the glass or the polymer dissolution/degradation. Upon immersion of composites in TRIS buffer solution, a decrease in the average molecular weight was measured. However, in this study and in agreement with data reported by Vergnol et al, the decrease of the PLA molecular weight alone could not be correlated to changes in the mechanical properties  [17].
Acknowledgement The authors would like to acknowledge the  Academy of Finland  ( Academy Research Fellow grant  to JM), TTY-säätiö for IL financial support, the  Institute for Advanced Studies (IAE)  for enabling researcher mobility,  Delphine Logeart-Avramouglou (Laboratory of Bioengineering and Biomechanics for Bone and Articulations ,  UMR 7052 ,  CNRS, University Paris Diderot ) for the kind gift of C2C12 cells and  Annette Lane  for proofreading this manuscript.
Acknowledgements This work has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (grant agreement no  682001 , project  ERC  Consolidator Grant 2015 BoneImplant). This project has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sklodowska-Curie Grant  Agreement No  797764.
Patients We conducted a prospective study with patients admitted for ischemic stroke who received thrombolysis and/or MET within 6 h of symptom onset at Bichat Hospital, Paris, France. Only patients arriving within working hours of the research nurse were included in the study. Plasma samples were taken from all patients at arrival, before any treatment was given. We collected data from each patient on demographics, risk factors, previous medications for stroke, baseline National Institutes of Health Stroke Scale (NIHSS)  [13] , and blood pressure at admission. All patients had brain imaging to support the diagnosis. Patients with ischemic stroke were treated with iv recombinant tissue plasminogen activator (rtPA), and in the case of documented arterial occlusion EVT, including intra-arterial (IA) thrombolysis +/-MET was performed.
Data Collection and Definitions Data were collected using a structured questionnaire. Smoking was classified as current (any smoking within the past six months), former (more than six months since cessation), or never smokers. Hypertension and hypercholesterolemia were defined by treatment history. Subjects were classified as diabetic when treated for type 1 or type 2 diabetes. The stroke severity was assessed using the NIHSS score at admission. The arterial status of the occluded artery was monitored with conventional angiography during the endovascular procedure and measured using the Thrombolysis in Cerebral Infarction (TICI) score  [14]. All patients underwent a computed tomography (CT) or magnetic resonance imaging (MRI) scan 24 h after treatment onset, to assess hemorrhagic complications.
p-values for bivariate and multivariate analyses were corrected for multiple comparisons (22 biomarkers tested) by using the Holm-Bonferroni method. Statistical testing was done at the two-tailed α level of 0. 05. Data were analyzed using the SAS software package, release 9. 4 (SAS Institute, 100 SAS Campus Drive Cary, NC 27513-2414, Cary, NC, USA).
Associations of blood biomarkers with each outcome were further investigated in multivariate logistic regression analysis adjusted for the following pre-specified confounders: age, admission NIHSS, documented occlusion (none vs. Internal Carotid Artery (ICA) occlusion vs. others arterial occlusion), and AIS treatments. Strength of associations was assessed by calculating the adjusted odds ratios (ORs) and theirs 95% confidence intervals (CIs) per one SD increase in blood biomarkers. Log-linearity assumptions were checked using restricted cubic spline functions  [18]. P-values for bivariate and multivariate analyses were corrected for multiple comparisons (22 biomarkers tested) by using the Holm-Bonferroni method. Statistical testing was done at the two-tailed α level of 0. 05. Data were analyzed using the SAS software package, release 9.
High osteopontin levels were also related to stroke recurrence in the SPARCL Trial  [33]  and bad outcomes, in the case of stroke recurrence in this trial (unpublished data). All these data points at osteopontin as a key informative biomarker in the case of ischemic stroke. We also found that circulating levels of cathepsin S were associated with reduced likelihood of excellent outcomes and of ENI, but it must be noted that statistical significance was lost after multiple comparison correction. Cathepsins are proteases that promote the degradation of damaged proteins in the lysosome, and they are also secreted extracellularly in a variety of pathological processes, including arthritis, cancer, and cardiovascular disease  [34]. Specifically, cathepsin S has been implicated in elastin degradation in cardiovascular disease, and high levels of cathepsin S have been described in the atheroma plaque  [35].
Objective: The objective of this systematic analysis was to perform a qualitative and quantitative synthesis of the literature concerning salivary and serum leptin variations in patients with chronic periodontitis (CP) compared with healthy subjects. Saliva leptin concentration analysis could be a relevant and non-invasive biological test for the evaluation of periodontal disease in both medical and clinical trials, beyond the clinical and radiographic elements. Material and Method: Querying the PubMed and Web of Science databases identified articles that met our inclusion criteria. Quantitative analysis of the literature data was performed with the Review Manager 5. 3 software. Results: The qualitative analysis included 14 articles and showed a decrease of salivary leptin (5 studies out of 5) and an increase of serum leptin (11 of 12 studies) in patients with CP compared to unaffected subjects of CP.
Quantitative analysis was performed on 4 trials. For salivary leptin, we confirmed a decrease in its level in patients with CP with a standardized mean difference (SMD) of À2. 27, 95% CI [À2. 68, À1. 86]. The difference was highly significant but we detected a very important heterogeneity in this dataset (I 2 = 94%). For serum leptin, we also confirmed an increase in its rate in patients with CP with an SMD of 2. 18, 95% CI [1. 75, 2. 61]. The difference was highly significant but the heterogeneity measured in this dataset was also too high (I 2 = 95%). Conclusion: The current level of evidence was insufficient to assert an increase in serum leptin and a decrease in salivary leptin in CP patients compared to healthy controls due to a great heterogeneity of the values measured in the studies.
Quantitative analysis Quantitative data on serum and salivary leptin and the total number of patients with CP and control subjects were extracted to calculate, for each study, the standardized mean difference (SMD) and the 95% confidence interval (95% CI). All data were presented in the form of a data summary table. Statistical calculations were performed with the help of Review Manager 5. 3. SMD is used as a summary statistic in the meta-analysis when all studies evaluate the same result but measure it in various ways. In these circumstances, it is necessary to standardize the results of the studies on a uniform scale before they can be combined. SMD expresses the magnitude of the effect of the intervention in each study relative to the variability observed in this study.
Quantitative analysis We conducted two series of comparative analyses: • Analysis 1: salivary leptin dosage in CP vs. control • Analysis 2: serum leptin dosage in CP vs. control. The results of each analysis (SMD, 95% CI) are presented using Review Manager 5. 3. 1. Regarding the comparison of salivary leptin, we measured an SMD of À2. 27, 95% CI [À2. 68, À1. 86]. The difference is highly significant, but we detected significant heterogeneity in this dataset (I 2 = 94%) (Fig. 2 ). 2. For the results of the serum leptin comparison, we measured an SMD of 2. 18, 95% CI [1. 75, 2. 61]. The difference was highly significant. The heterogeneity measured in this dataset was also too large (I 2 = 95%) (Fig. 3 ).
We chose to exclude patients whose BMI was >30 because an increase in BMI results in an increase in serum leptin; it is the obese (ob) gene that appears to be involved in this mechanism, with a greater amount of ob mRNA found in adipocytes of obese subjects than in those of subjects with normal weight. The populations studied are also homogeneous in the definition of CP, serum data collection, and independent operators. In agreement with Zhu  [15]  (I 2 = 91. 6%), we also measured an excessive heterogeneity during the serum leptin comparison of subjects with CP versus healthy subjects. The significant heterogeneity modifies the interpretation of our results and presents one of the weak points of our study. However, strict adherence to the inclusion and exclusion criteria limited the sample size of the study.