dataesr/scientific-paragraphs-categorization huggingface dataset:
This body of research will be the main focus of this review. The following literature review was based on a literature survey that was performed by combining the keywords 'Alzheimer's disease'; 'time estimation'; 'time perception'; 'prospective timing'; and 'retrospective timing'. The search was performed on the PubMed and PsycInfo databases from the first available year until 2015; and was limited to studies published in peer-reviewed journals. Exploration of the reference lists of these papers was carried out to identify additional papers. We were careful to select papers in which AD diagnosis was implemented according to the reliable criteria, such as those of the NINCDS-ADRDA (National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's disease and Related Disorders Association) for probable AD.
Acknowledgements JG-S has been supported by the  European Union 's  FP7funded NACLIM project  ( ENV-308299 ) and H2020-funded DPETNA grant ( MSCA-IF-EF 655339 ). MPK acknowledges the  Severo Ochoa Visiting Fellowship  at the  Barcelona Supercomputing Center  and the  Nordforsk   GREENICE  project ( 61841 ). Mehmet Ilicak and Marius A ˚rthun provided suggestions related to ocean heat transport. Suggestions from the reviewer had also led to improvement in the analyses.
Methods Sixty hospitals across France, Italy and the UK (20 per country) were recruited by national coordinators to represent a wide geographical area. Via a questionnaire, hospitals provided institutional data (size and type of institution) and details of current CDI laboratory diagnostic methods and policies (April 2014 to March 2015). We obtained monthly data for hospital in-patients on the numbers of enteropathogen and CDI tests, and CDI-positive cases, along with case demographic data. Cases were defined as 'primary' if the first case in the patient or 'recurrent' if a second positive sample occurred within 2-8 weeks of a previous positive. All data were uploaded prospectively by participating hospitals to a secure, dedicated, webbased, study database. All data analyses were conducted by the European coordinator.
Data analysis The testing methodology, testing/CDI rates and case profiles were compared between countries and different sized institutions. Hospitals were classified as small (<100,000 pbds per annum), medium (100,000-500,000) or large (>500,000). Annual testing and case rates were calculated per 10,000 pbds for each hospital, and mean rates were compared between countries and between different sized institutions. The mean CDI case incidence and patient profiles were compared between hospitals using a recommended testing algorithm (GDH/toxin or NAAT/toxin) versus methods not detecting toxin (e. g. GDH/NAAT or NAAT alone), SATT (e. g. toxin EIA alone) or a nonrecommended algorithm (e. g. GDH/toxigenic culture)  [1]. CDI and testing rates were compared by analysis of variance (ANOVA), age distributions by Kruskal-Wallis and proportions were compared by Chi-squared.
difficile testing. Institutions that participated in this study were chosen by the study coordinators and may have had a higher CDI awareness and/or rates; however, institutional selection was intended to be 'representative' of hospitals nationally, and to cover a wide geographical spread. We did not collect demographic for patients with samples that tested negative for C. difficile/CDI. This would provide better evidence for the age distribution of cases/controls and help to show how testing is targeted. Such data will be collected in the follow-on full LuCID study, which will also expand to include a total of 40 hospitals in each country and two more countries (Spain and Germany). The additional countries and hospitals will increase the sizes of the (at present) small sub-groups, such as small hospitals and CDI recurrences.
As patient bed day data were collected annually rather than per month, we were not able to determine with confidence possible seasonality of either CDI testing or case rates. These limitations will also be addressed in the full LuCID study. Our pilot results show that it is important to understand the context of sampling, testing and methodology in order to interpret reported CDI rates. It is essential that studies either take such potential confounders into account when interpreting data, and, ideally, that large, multi-centre, multi-country studies are used to determine the true epidemiology of CDI. Additionally, we have shown that inclusive testing with recommended diagnostic methodologies is associated with lower reported rates of CDI. Theoretically, increased awareness of true CDI cases enhances opportunities to implement appropriate and targeted infection prevention and control measures.
Acknowledgements Data from this manuscript have been previously presented at the 25th  European Congress of Clinical Microbiology and Infectious Diseases (ECCMID) in Copenhagen, Denmark ,  25-28 April 2015  and at  Infectious Diseases Week (IDWeek) in San Diego, California, USA ,  7-11 October 2015. This study was initiated and funded by  Sanofi Pasteur (France). Although the study was not formally run by the  ESCMID Study Group for Clostridium difficile , the study authors are all active members of this group.
Box highlights the sequence surrounding the conserved Ser residue in each JAK isoform, color coded to show conformity to the AMPK consensus. Bottom right: structure of the human JAK1 FERM-SH2 fusion (PDB: 5IXD) generated using PyMol  (39). Zoom: location of Ser 518 within the αB helix immediately downstream of the EF loop in the SH2 domain. The αA and αB loops, present in all SH2 domains, are also indicated. Figure Legends:.
Data analysis The data obtained for each microcosm were compared, to evidence variations between treatments. All FA of POM (up to 40) were used in these analyzes without transformation and were represented by their relative proportions. A dissimilarity matrix between each pair of samples was calculated using the Bray-Curtis index. Dissimilarities between samples were then graphically represented using an nMDS (non-metric MultiDimensional Scaling,  Zuur et al. , 2007). Differences between groups were tested using analyzes of similarities tests (ANOSIM,  Oksanen et al. , 2010) , without considering temporal variability. When differences were significant, a similarity percentages analysis (SIMPER,  Oksanen et al. , 2010)  was used to determine the relative contribution of each FA to differences between two groups.
Acknowledgments This research is a contribution to the  CARBAMA  project, supported by the  ANR (French National Agency for Research , grant number  08-BLAN-0221 ), and the  CNPq (National Council for Scientific and Technological Development -Brazil ,  Universal Program  grant number  477655/2010-6 ); it was conducted within an international cooperation agreement between the  CNPq (Brazil)  and the  IRD (Institute for Research and Development -France) , and under the auspices of the  Environmental Research Observatory Hydrology and Geochemistry of the Amazon Basin (HYBAM) , supported by the  INSU  and the  IRD. We are grateful to  Jessica Chicheportiche  ( LOG laboratory ) for bacterial abundance estimations. We also want to thanks two anonymous reviewers whose comments helped improve this manuscript.
Materials and Methods First, we started searching for general guidelines in Europe and the USA by entering the search terms: guideline and screening in the web search engine Google and Google scholar and in PubMed. Afterwards we started looking more specific for guidelines for gynaecology and obstetrics and for paediatrics in Europe, USA, Canada, Australia and worldwide by using the additional search terms: pregnancy and prenatal. While browsing through the various guidelines we used the search terms: cytomegalovirus, CMV, screening, pregnancy, congenital infections and infections. The guidelines were required to be in Dutch, English, French, German or Spanish, but no other language. We assessed the guidelines on the 4th of February 2016.
1a, b, c ). Then, based on palaeoreef data compiled for this study (Supplementary Table  1 ), the abundance, composition and distribution of Famennian to early Tournaisian skeleton-and microbe-dominated bioconstructions were quantified, highlighting the evolutionary pattern of bioconstructions during this time interval. Lastly, using the Paleoreefs database of Kiessling et al. 18  and new, recently published data  [6] [7] [8] [19] [20] [21] [22] [23]  , the relative abundance of skeleton-and microbe-dominated bioconstructions during the 'Big Five' and Hangenberg mass extinction transitions, was systematically reviewed, in order to compare the relationship between skeletal and microbial bioconstructors across the different mass extinction events. Hence  this paper aims to unravel (1) changes in the marine biosphere across the end-Devonian mass extinction transition; and (2) the dominant controlling factor on microbial carbonate proliferation after mass extinctions more generally.
Methods All illustrated specimens are deposited in Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing, China. Field photographs were taken using a Canon EOS 6D digital camera. Polished slabs and thin sections were produced using standard techniques, and were photographed with scanner EPSON DS-50000 and microscope Nikon SMZ1500, respectively. The Famennian-early Tournaisian Palaeoreef database in this study was constructed using our own data and published papers on bioconstructions and their biostratigraphy during this time, with inputs from the Paleoreefs database of Kiessling et al. 18. Values of 1, 2, 3 and 4 were assigned to bioconstruction width scales of less than 10 m, 10 to 100 m, 101 to 1000 m and more than 1000 m, respectively, and also to bioconstruction thickness scales of less than 10 m, 10 to 100 m, 101 to 500 m and more than 500 m, respectively.
Values of weighted abundance for bioconstruction = (Assumed width value + Assumed thickness value) × Bioconstruction number. The value of site number for bioconstructions represents the number of bioconstruction locations. The database of 'Big Five' transitions was created by adding new published data to the extensive data of Kiessling et al. 18  (see Supplementary data, Table  3 ). The ranges of the relative abundance of bioconstructions across the 'Big Five' mass extinction transitions were drawn in accordance with the occurrences of bioconstruction numbers in relevant time slices.
Kinematic, force and electromyographic acquisition The change of force of the load placed on the postural side was measured by a strain gauge fitted to the metallic wristband supporting the weight. A second strain gauge measured the change of force exerted by the load placed on the platform on the right side. A potentiometer placed along the elbow joint axis measured the angular displacement of the forearm. EMG data were collected using bipolar surface electrodes (surface area: 2. 5 mm 2 ) placed over the surface of two flexors (biceps brachii and brachioradialis) and one extensor (lateral triceps brachii) on the postural upper arm.
Force, kinematic and electromyographic analysis Each trial was viewed offline on a monitor screen. Measurements were performed with the MatLab software program (The MathWorks, Inc. ). Fig 1B illustrates a single trial recorded in the same participant in each experimental situation. The onset of unloading (T0), used as the reference time, was defined as the first deflection of the force signal transmitted by the strain gauge. To determine T0, a semi-automatic method was used. The mean force signal and its standard deviation (SD) were computed for 0 to 450 ms after the beginning of the trial. A horizontal cursor was positioned when the force signal was statistically significant different from the mean-3 SD. Visual inspection was then used to confirm the goodness of the automatic definition of T0.
MA% MA situation mean MA preimp Â 100 EMG signals were filtered (5-100 Hz band pass) and rectified using the MatLab software program (The MathWorks, Inc). The EMG signals of each muscle were first visually inspected trial-by-trial on a monitor screen. Compared to the tonic activity that enabled the load to be carried by the postural arm, around the unloading, the EMG events consisted of activations characterized by an increase of activity, or inhibitions characterized by an EMG signal nearing zero. Following this visual inspection, one participant, whose EMG traces presented with artifact in the learning situation, had to be discarded. We quantified the presence of activations and/or inhibitions using a semi-automatic algorithm. Activations were defined as a burst that was more than 2 SDs above tonic activity (measured during the stable phase, when the load was supported by the forearm) and that lasted for 50 ms at least.
Statistical analysis The distribution was evaluated using the Kolmogorov-Smirnov test. According to the variable distributions, differences between groups were assessed using one-way analysis of variance (with post hoc Tukey's test), Student's t tests, the Mann-Whitney U test, Wilcoxon's test, or Fisher's exact test. The correlations between ETs and cytokine concentrations were assessed using Spearman's test. A p value <0. 05 was considered significant. All of the reported p values are two-sided. If not mentioned, statistical analysis was conducted using IBM SPSS version 20. 0 software (IBM, Armonk, NY, USA). Graphs were created using GraphPad Prism software (GraphPad Software, La Jolla, CA, USA).
Acknowledgments The authors thank the  Provence Alpes Côte d'Azur region and Capsum SAS  for their financial support of PP's doctoral grant; the  Solvay company (LOF, Pessac, France) , and  F. Bedu  and  I. Ozerov  ( CINaM, CNRS UPR 3118, Marseilles, France ) for technical support with microfabrication;  Labex INFORM  for financial support;  Cyrille Mionnet  for support with cytometry experiments;  C. Farnarier  ( Laboratoire d'immunologie -Hôpital de la Conception, Marseille, France ) for initial treatment of the sera library; and the cell culture platform of  INSERM at Marseille-Luminy.
life-years (QALYs) and number of relapses were assessed over 5 years based on 3-month cycles with a discount rate of 4 % and from a French health insurance perspective. Patients were considered to be stabilised after a schizophrenic episode and would enter the model at an initiation phase, followed by a prevention of relapse phase if successful. Data (e. g. relapse or discontinuation rates) for the initiation phase came from randomised clinical trials, whereas relapse rates in the prevention phase were derived from hospitalisation risks based on real-life French data to capture adherence effects. Safety and utility data were derived from international publications. Additionally, costs were retrieved from French health insurance databases and publications. Finally, expert opinion was used for validation purposes or in case of gaps in data.
Based both on French clinical guidelines  [30]  and on expert opinion, the second-line treatment included second-generation LAI The CGS (Cohort for the General study of Schizophrenia) is a French observational study that aimed to compare the impacts of risperidone LAI with other antipsychotics in terms of hospitalisation rates. At each cycle, patients could move to the health state 'death' from any state (not represented here). AEs adverse events, APn antipsychotic, Hospi hospitalisation, LAI long-acting injectable Fig. 2  The treatment sequence. ALAI aripiprazole long-acting injectable, HLAI haloperidol long-acting injectable, OLAI olanzapine long-acting injectable, OO oral olanzapine, PLAI paliperidone long-acting injectable, RLAI risperidone long-acting injectable antipsychotics. Thus, clinical and economic inputs were elicited by a weighted average in equal proportions of data for paliperidone LAI (25 %), risperidone LAI (25 %), aripiprazole LAI (25 %) and olanzapine LAI (25 %).
Model Parameters and Assumptions Input parameters were derived from an observational study (i. e. CGS)  [26] , clinical trials  [38, 39] , relevant literature  [40, 41]  and assumptions based on expert opinions. We conducted a literature review (until 2014) through MEDLINE Ò and MEDLINE-In-Process Ò databases, focusing on meta-analyses results for efficacy, safety and discontinuation rates for the different comparators. Relevant terms for the pathology were combined with appropriate study types, interventions and outcomes. The electronic search was restricted to English and French publications. Additional ad hoc searches were conducted to complete information on standardised mortality rate (SMR) by health state and utility, as well as hospitalisation costs, treatment costs and treatment-related adverse event costs in France (with an update for treatment costs in 2015).
e. noninferiority analyses showed comparable efficacy between oral and LAI in the initiation phase, in which the close follow up of patients ensures a certain level of compliance irrespective of treatment form)  [42] [43] [44]. In the prevention phase, the risks of relapse were derived from real-life data (i. e. CGS; data allowing the capture of adherence effects) when available  [26]. The hospitalisation rate from the CGS was chosen to estimate the relapse rate based on the conclusion from Olivares et al. [45] , who demonstrated that hospitalisation was the most frequently used factor to track the incidence of relapse. In the CGS, the annual risk of hospitalisation, readjusted for treatment   [25, 28] , resulting in an annual risk of relapse of 29. 15 %). Thus, the 3-monthly risk of relapse for patients treated with risperidone LAI was estimated at 8.
Mortality Rates Different probabilities of death were applied to stable patients and to patients in relapse. Mortality rates for stable patients were derived from a meta-analysis based on 37 studies over 25 countries, including France  [48] [49] [50]. The median SMR for all-cause mortality in schizophrenia was 2. 58 (3. 02 for men and 2. 37 for women) and was used in the model for stable patients. Mortality rates applied to patients in relapse were derived from SMR values in the year following hospital discharge from real-life data from patients with a principal diagnosis of schizophrenia from an English hospital (i. e. SMR 6. 2)  [51].
In clinical practice, patients with prior relapse have a greater probability of relapse than stable patients without relapse, while patients stable after 1 year of treatment have a reduced probability of relapse or switch due to lack of tolerance. Thus, and according to clinical experts 1 , our analysis may underestimate the proportion of patients continuing to receive initial treatment over time compared with real life. However, the evolution of this proportion was consistent with previous analyses when considering similar time-independent transition assumptions  [23, 28]. Probabilities of leaving the hospital during a relapse episode were derived from real-life data from one hospital centre and may not be representative of all centres in France. It was assumed that EPS events lasted for one cycle of 3 months.
Patients faced the same probability of experiencing an EPS event at each cycle regardless of his/her previous EPS event sequence (due to memoryless Markov property), and thus EPS events may have been overestimated. The maintenance cost of schizophrenia was based on an aggregated cost from the SHI database. This cost was applied to stable patients without adverse events, and additional costs have been associated with adverse events. Thus, maintenance cost may also be overestimated. Finally, it should be noted that, although validation of the model by external reviewers would have strengthened the study methods, limited time and resources precluded this. However, extensive PSAs were performed. These analyses aimed to assess the impact of uncertain input parameters and assumptions (mentioned above) on model results.
Data collection strategy for the identification of WRA The characterization of the study subjects with respect to WRA is organized in 3 steps (Fig. 2 ). The data collected for each concept of the project are summarized in Table  1. Step 1 (a priori classification) is a screening step carried out among active workers followed for the mandatory health examinations. It is based on a quick self-administered screening questionnaire (one rectoverso page), adapted from the European Community Respiratory Health Survey  [21]  asthma questionnaire. It comprises items regarding asthma antecedents (childhood asthma), active asthma symptoms, and   [22]. The collected demographic data items are sex, age and occupation. A subject is considered as potentially asthmatic, and invited to undertake the next step if s/he answers positively to at least one of the questions on asthma symptoms (see Additional file 1).
Based on all data collected at the 2 previous steps, the included potential asthmatics are then classified by consensus of two occupational physicians from one UHODD and two epidemiologists into 4 categories: "probably no active asthma", "probably NWRA", "suspected WEA" and "suspected OA". Subjects with suspected WRA are invited to participate in step 3 (clinical examinations) in one of the UHODD. Non-work-related asthmatics are those with childhood asthma, without any exposure to known asthmogen and no work-related pattern in symptoms and in the recorded PEFs. If the symptoms appear to be poorly controlled, they are advised to see a physician. Step 3 (final classification): all suspected WRA patients selected in step 2 will be diagnosed as WEA and OA based on clinical examinations in the UHODD participating.
be/9vLKrygWQWc). Additional epidemiological data collection books and peak-flow meters are sent to the occupational physicians if they estimate more than five are necessary. Screening questionnaires are entered in database by optical scanning device, and • one or several specific inhalation challenge (SIC) with the potential occupational allergen • one bronchial exposure test at the work station • comparative methacholine challenge tests, in working period and resting period. • comparative exhaled Nitric Oxyde measurements before and after exposure • induced sputum cytologic analysis before and after exposure technicians enter other questionnaires and PEF measurements in the computer system. At the 1 st of July 2015, after 6 months, 17 physicians included 1139 subjects in step 1, with 144 potential asthmatics who received the PEF meter and the questionnaires, among which 38 have returned the epidemiological data collection book.
Moreover, most of these cases are due to standard asthmogens  [32]  (flour, persulfate salts, isocyanates…), so that they are easier to detect by occupational physicians or chest physicians. Moreover the severity of asthma is probably more important among clinical cases. The systematic screening of active workers is thus expected to yield more WEA cases but less severe cases. On the other hand this screening might detect an increased asthma prevalence in sectors not exposed to standard asthmogens, as compared with a clinical setting. As step 1 consists of the systematic recruitment of workers, every worker will fill in at least the screening questionnaire, already giving us some data about the potential presence of symptoms of an active asthma, the evolution of the symptoms when away from work and the professional occupation.