dataesr/scientific-paragraphs-categorization huggingface dataset:
Financial support came from the  CNRS  ( Centre National de la Recherche Scientifique ) and from the  MESR (Ministere de l'Enseignement Superieur et de la Recherche). H. Benamara  and  I. Abbes  were supported by a  MESR grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Bone was quantified using the NIS-Elements BR 2. 30 software (Nikon). The surface area of bone (stained in red) was measured in each specimen section and normalized over the whole surface area delineated around each section. The remaining seventh retrieved construct (from the HA/TCP, coral, and BG constructs groups) was fixed in 4% paraformaldehyde (pH 7. 4) for 36 hours, decalcified in Decalcifier II (Surgipath) at 4°C for 48 hours, and embedded in paraffin. Sequential sections were processed for human beta-microglobulin (a membrane protein that enables tracking human cells) immunodetection. Briefly, tissue sections were pre-treated in a proteolytic enzyme solution (Dako, Glostrup, Denmark) at 37°C for 20 min. Cell membranes were permeabilized using 0. 3% Triton X-100 for 15 min; the endogenous peroxidase activity was inhibited by addition of peroxidase block (Kit Envision+, Dako), and the non-specific binding sites were blocked using Protein Block (Dako).
), combined with TaqMan Universal PCR Master Mix using the MyiQTM Single-Color Real-Time PCR thermocycler (Bio-Rad Laboratories) according to the protocol described previously  (40). All samples, including specimens from experiments and standards (n=3 for each condition), were run in triplicate and in parallel. Data were analyzed using the iCycler IQ software (Biorad) and were compared by the ΔΔCt method. The results from hBMSC cultured onto the material granules tested in the present study were normalized to the amount of 18S transcript and were expressed relative to the results obtained from cells at day 0. The results from hBMSC cultured at different pH values were normalized to the amount of 18S transcript, and were expressed relative to the results obtained from hBMSC cultured in non-osteogenic medium for the same time period.
In vivo bone formation by hBMSC contained in the constructs tested De novo bone formation was assessed when hBMSC-containing constructs (prepared with either HA/TCP, coral, BG or composite of either HA/TCP:BG or Coral:BG) were implanted ectopically in a mouse model. After 8 weeks of subcutaneous implantation, there was no bone formation in conjunction with material scaffolds without cells; these scaffolds, however, were infiltrated with fibrous tissue (data not shown). At the same time point, new bone tissue was observed both in the hBMSC-containing HA/TCP and coral constructs as shown in the representative histology results from such explants (Fig. 2A ). The osteogenic outcome of hBMSC contained within the tested coral-and HA/TCP-implants was similar and was characterized by high prevalence of bone formation and by similar amount of deposited new bone tissue (Fig.
Osteogenic differentiation of hBMSC cultured onto the materials tested Another aspect addressed in the present study was the potential for osteogenic differentiation of hBMSC cultured on BG granules as compared to results obtained on either the HA/TCP or coral substrates. For this purpose, the ALP activity of hBMSC cultured in osteogenic differentiation medium on the three materialgranules tested was assessed. ALP activity of hBMSC cultured on either HA/TCP-or coral-granules peaked at 14 days (Fig. 4A ), indicating osteogenic differentiation of hBMSC on these materials. HBMSC exhibited a significant (p< 0. 05) greater ALP activity on HA/TCP and coral than on BG granules at 14 and 21 days of culture (Fig  4A ). In addition, the ALP activity of hBMSC cultured on TCPS (reference substrate) was 3-, 3-, and 7-fold higher than that obtained when the cells were cultured onto the HA/TCP, coral and BG granules, respectively (data not shown).
The pH in the cell-containing BG constructs was 8. 03 ±0. 03 at day 0 and remained similar at the prescribed post-implantation time points (Fig. 5B ). The pH value in these BG constructs was 0. 4-0. 5 unit more alkaline (p<0. 05) than that measured in the other two types of cell-containing material constructs. The pH from both cell-containing HA/TCP:BG and coral:BG composite constructs that contained increasing ratios of BG was also measured in vitro. The data showed a strong correlation (r² = 0. 88 and 0. 99 for the HA/TCP:BG and the coral: BG composites, respectively) between the pH and the content of BG in the scaffolds of cell-containing constructs (Fig. 5C ). Altogether, these results confirmed the alkalinization of the environment of the BG cell-containing constructs.
Acknowledgments The authors gratefully acknowledge  Inoteb Inc. (Levallois-Perret, France ) for donating the coral scaffolds and  Baxter, Inc. , for donating the Tissucol used in the present study. We are grateful to  Brigitte Gaillard  ( INRA, Unité de Microbiologie, Clermont-Ferrand, France ) for conducting the SEM analysis for cell adhesion. We also thank  Professor R. Bizios  for critically reading the manuscript. This project was supported by the  French National Research Agency (ANR)  through the  TecSan program  (project  GLASSBONE n°08-TECS-004 ), and by the  Centre National de la Recherche Scientifique (CNRS) of France.
2. 5. Histomorphometry. Three randomly selected sections per condyle and per animal were analyzed. Each section was examined under a light microscope (Olympus BX 60, Olympus Corporation, Tokyo, Japan) connected to a digital camera (Olympus, E330). New bone formation was quantified using Image Tool 3. 0 software (UTHSCA, SanAntonio, TX, USA). The spatial calibration of the histological sections was done by drawing manually the surface of the newly formed bone and the residual bone substitutes. The total surface was obtained by adding all the delimited areas measurements (in mm 2 ). The distribution of newly formed bone and residual implanted material was also determined by classifying the defect area into an inner zone (IC) of 2. 5 mm and an outer zone (OC), including the remaining of the 5.
Statistical Analysis. Two-way analysis of variance between groups was conducted to determine the effect of bone substitutes with APL on new bone formation and on the resorption of these materials. Variables were tested for normal distribution and equality of variance using the Kolmogorov Smirnov and Levene tests, respectively. Comparison of the data between the different groups tested was performed using the Student's -test. All statistical analyses were performed using commercially available software programs (SPSS for Windows version 16. 0). Significance was defined as a  value of less than 0. 05.
Study design/sample Our study was designed as a cross-sectional study and we enrolled votes from the experts and participating surgeons in the IBRA Symposium 2012, Marseille, France. We analysed the data extracted from the presentations and video recordings. Exclusion criteria included surgeons who were absent or denied to participate in the voting. This study did not involve human subjects (i. e. , patients) directly; thereby, it was exempted from the institutional ethical review at "La Timone" University Medical Centre, France, and University Hospital of Marburg, Germany: the 2 principal institutions of the study. We also obtained the presumed consent from all experts and participants about the use of their votes. The voting process was anonymous via the electronic TED voting system (Ellerbrock Konferenztechnik, Abtsteinach, Germany).
Variables and data collection The predictor variable was type of voters (expert vs. participating surgeon), which was recorded as a nominal data. The outcomes of interest were the panel and TED votes on management of condylar base, neck and head fractures, and panel votes recommendations for endoscopic and paediatric condylar fractures. The classification of condylar fractures in this survey was based on the nomenclature by  Loukota et al. (2005 Loukota et al. ( , 2010)) , which have been adopted by the TMJ section of both the Strasbourg Osteosynthesis Research Group (S. O. R. G. ) and the "Arbeitsgemeinschaft für Osteosynthese" (AO) Foundation. The main outcomes were tested using 12 case scenarios (as 14 multiple-choice questions) and 27 preselected statements (as 27 "agree/disagree" voting).
Histomorphometric analyses Maxillas were collected on postsurgical days 7, 14, 21, and 28 to quantify the amount of new bone generated in response to the implant. All maxilla were embedded in paraffin and sectioned longitudinally. The 0. 6-mm implant was represented across ∼20 tissue sections, each of which was 8 μm thick. Of those 20 sections, we used a minimum of 4 sections to quantify the amount of new bone. All the tissue sections were stained with aniline blue, which labels osteoid matrix. The sections were photographed using a Leica digital imaging system at the same magnification (×10 objective). The resulting digital images were analyzed with Adobe Photoshop CS5 software. We chose a fixed, rectangular region of interest (ROI) that in all images corresponded to 10 6 pixels. The injury site was always represented inside this ROI by manually placing the box in the correct position on each image.
Statistical analysis Statistical tests were performed using the Statistical Package for the Social Sciences (SPSS 18. 0, 2009; SPSS Inc. , Chicago, IL, USA). Quantitative variables were described as mean ± standard deviation and qualitative variables as number (%). Agreement between classification criteria sets and between criteria was evaluated using Cohen's kappa coefficient (κ). To compare patient groups, we used the Mann-Whitney test, Fisher's exact test or the chi-square test as appropriate.
Radiographic Calibration. Two independent investigators studied all the anonymized X-Rays and were previously calibrated against a set of 100 reference teeth. Afterwards, they examined all the radiographs independently. A third observer, a highly experienced endodontist, was consulted for cases for which disagreement occurred. 2. 5. Data. Clinical and radiographic pre-intra and immediate postoperative data were normally recorded in the patient medical record of each patient at the time of treatment by the operator (postgraduate practitioners supervised by the Professor director of the postgraduate cursus). Patients were then invited to a clinic/radiographic recall. Data previously recorded and subsequent data recorded at recall were pooled and evaluated. Demographic characteristics (age and gender) and tooth characteristics (tooth location, type of tooth, and number of roots) were recorded (Figure  1 ).
Sample Size. All teeth evaluated were selected for statistical analysis. The sample size is the number of teeth and not the number of patients. 2. 8. Statistical Analysis. We described the study population and we studied the bivariate associations between success and preoperative, intraoperative, and postoperative factors to identify potential outcome predictors. Fisher exact tests were conducted. All tests were interpreted at the 5% significance level. The number of failures was too small to have sufficient power to carry out multivariable analysis. SAS software (9. 2 version) was used for analyses.
Results Of the 296 patients (363 teeth treated), 148 patients were categorized as lost: one died; 25 changed phone number; 104 did not call back after the message left on their answering machine; 11 did not answer; and 7 patients' telephone numbers could not be retrieved from the database of the hospital. 148 patients (50% of the treated patients/of the eligible sample) were contacted: 7 patients had moved and could not come and 28 refused the follow-up visit (lack of availability, distance, and/or monitored regularly by a dentist). Ultimately, 113 patients were seen for visit. The recall rate is 38% (113 patients evaluated in 296 patients treated). Sample of 113 patients and 139 teeth had been evaluated; 8 teeth extracted were excluded. Finally, 131 teeth were included    The average number of treatments per patient was 1.
This test is based on the concept of immobilization of beads by sessile bacteria that form aggregates with enough strength to overcome the magnetic attraction forces applied on them. Thus, in the absence of sessile cells all the beads gathered in the center of the wells and formed an easily detectable black spot. Images of each well before (I 0 ) and after (I 1 ) magnetization were compared with the Biofilm ControlH Software and the discrepancies between the two images gave rise to values named BioFilm Index (BFI) ranging from 0 to 30. High BFI values correspond to high mobility of beads under magnet action and therefore little or no immobilization of the beads by bacteria  [25]. With TSB as incubation medium, a biofilm was considered installed when the value of BFI was less than or equal to 4.
aureus strains forming protein-dependent biofilm CH937 (affected by supernatant) and CH939 (unaffected). Results indicated that the CH937 strain had an acid and basic character while the nonsusceptible isolate, CH939, harboured a more basic surface (data not shown), a difference that might account in the interactions with the supernatant active molecules. To determine if the effect of K. pneumoniae was due to some released molecules specifically produced in planktonic growth conditions, we investigated the effect of two other types of K. pneumoniae cell-free extracts, biofilm supernatant and acellular Figure  4. Identification of the active fractions in planktonic supernatant extract. Size exclusion chromatograph of planktonic extract from K. pneumoniae together with quantification of total polysaccharides assessed by the phenol sulphuric acid method were performed.
Assessment of methodological quality of Cochrane systematic reviews Two reviewers independently and in duplicate evaluated the methodological quality of systematic reviews using the AMSTAR checklist, a measurement tool of 11 items  [4, 5]. Disagreements were resolved with a third author. We did not use the PRISMA checklist because it is not intended to be a quality assessment tool as compared with the AMSTAR, which is a reliable and valid measurement tool to assess the methodological quality of systematic reviews  [5, 6]. The following characteristics were assessed: a priori design, study selection and data extraction, literature search, status of publication, characteristics of the included and excluded studies, scientific quality of the included studies, methods used to combine the findings of studies, publication bias and conflict of interest.
Actually, the latter involve materials that may be harmful because of some toxicity  [49, 50]. Many of our reviews (78%) produced inconclusive evidence. The most common reasons for failure to provide reliable information to guide clinical decisions are the small numbers of RCTs and patients per meta-analysis. According to a cross-sectional descriptive analysis about characteristics of meta-analyses in the Cochrane Database of Systematic Reviews, the median number of RCTs included in meta-analyses was 3 (Q1-Q3 2-6) and the median number of patients was 91 (Q1-Q3 44-210)  [51]. Our findings are consistent with these figures and emphasize that more high-quality primary research may be frequently needed to reach conclusiveness. However, none of the selected reviews was empty; that is, randomized evidence always existed and was included in the review, even when inconclusive.
Previous methodological surveys assessed the conduct quality of systematic reviews in the field of dentistry  [64] [65] [66]. In a study of 109 systematic reviews published in major orthodontic journals, 26 were published in the Cochrane Database of Systematic Reviews. In all, 21% of the selected reviews satisfied 9 or more of the 11 AMSTAR criteria  [64, 65]. However, to our best knowledge, no methodological survey concerned specifically pediatric oral health. Our study has some limitations. Indeed, we considered only Cochrane systematic reviews in our study, but many non-Cochrane systematic reviews have also assessed interventions in the paediatric oral health field  [67]. Nevertheless, Cochrane systematic reviews are the highest standard in evidence-based health care. Moreover, Cochrane reviews have a standard structure, which always includes implications for practice.
Whilst both of these studies might suggest that, in colony cats, greater food intake occurs during short photoperiods and/or winter months, neither examined possible seasonal effects throughout the year. In recent years, various mathematical techniques have been developed to predict the behaviour of physiological processes from large datasets collected from living organisms. In biomedical research, such in silico experiments are beneficial in that they reduce reliance on in vivo experimentation and decrease experimentation costs  [16]. This is because assumptions can be tested and data generated that would otherwise be difficult to measure. Among the various techniques used, artificial neural networks (ANN) are particularly recognised for their ability to predict very complex and non-linear processes, coupled with a certain ease and flexibility of implementation  [17].
Data Handling and Statistical Analysis All study data were recorded in a computer spreadsheet (see Spreadsheet S1). Statistical analysis was performed using computer software (SAS 9 for Windows, SAS Institute Inc. ), and significance was set at P,0. 05 for two-sided analyses. Given that the residuals of each statistical model were not normally distributed, quantitative variables were ranked to perform non-parametric analyses. In this respect, analysis of variance or covariance were undertaken using linear mixed models. These models included fixed effects and the cat as a random term, taking into account that measures are repeated for each cat throughout the study. Two outcome variables were investigated, namely body weight (in kg) and food intake (in g/day). The body weight model included the following fixed effects: year, month, weight status (overweight [BCS 6-9/9] or ideal weight [BCS 5/9]), sex, neuter status (neutered or sexually intact), housing type (indoor only vs.
Modelling using Artificial Neural Networks (ANN) All the calculations were carried out using R software (v 2. 15. 2) with the NNET package dedicated to ANN modelling. In order to understand better the mechanisms responsible for regulating food intake, ANNs were used  [20] [21]. A multi-layer feed-forward neural network, so-called Multi-Layers Perceptron (MLP) was used, incorporating a back-propagation algorithm as previously described  [22] ,  [23] ,  [24]. MLP is used to predict the mean value of a dependent variable conditionally to a vector of values of a set of predictive variables. In this approach, the network constructs a model based on examples of data with known outputs. The model is built solely from the examples presented, which are assumed to contain the information necessary to establish the relation.
For the MLP of the current study, a coherent scale between the different variables was ensured, by normalising the input and the output variables within a uniform range of 0 to 1 using the following equation: x ' l ~xi {x min x max {x min Where x i is the i th value of a variable x, x min is the minimal value of the variable x, x max is the maximal value of the variable x, and predicted values can be de-normalised at the output of the ANN. Next, the data were divided into two subsets: one was used in the training phase, and comprised 60% of the initial dataset; the other was used for the validation phase, and comprised the remaining 40%. To facilitate this, 29 of the 48 months of the study, with 38 cats, were randomly sampled for the training phase and 19 months with the same cats used for the validation phase.
In order to build confidence intervals for the predictions, a bootstrap process was applied  [25] : the sampling process previously described was repeated 1000 times, and the training-validation process was applied each time. The performance of each MLP generated was measured, by calculating both the training mean squared error (MSEt) and the validation mean squared error (MSEv). To this end, the lower MSEv, the better the model. The average performance and the best performance were calculated. For each individual, a mean food intake prediction was calculated on the 1000 simulations with its standard deviation. MLPs were used to predict all the individual data (both used in training and validation phases), and the predictions were averaged by date. Coefficients of determination R 2 were then calculated between measured and predicted mean values of food intake.
Effects of Average Temperature and Daylight Length on Food Intake Data on average temperature and daylight length were examined, for the duration of the study period. As with food intake, both mean daily temperature and mean monthly daylight length were cyclical, with peaks and troughs in both temperature (peak monthly temperature in July, 25. 162. 4uC; trough monthly temperature in January, 6. 762. 3uC) and daylight length (longest total daylight length July, 541036891 sec; shortest total daylight length, January 337516960 sec) occurring at similar times to food intake. The effects of both temperature and daylight length on food intake were then assessed. Non-parametric ANCOVA was repeated including mean monthly temperature and daylight length, as covariates, instead of month. Once again, there were effects of year of study (P = 0.
The housing conditions, periods available for free activity, and periods of play activity did not vary during the course of the study and definitely did not vary throughout the year. Thus, it is unlikely that differences in activity would be the driving force for the cyclical differences in food intake observed. However, because activity was not measured objectively in the study, for instance using accelerometers, we cannot discount this possibility altogether. In a previous study, which included data from the current study cats, long-term changes in food intake and bodyweight were also assessed when fed a dry extruded diet ad libitum  [18]. Two phenotypes of cats were identified: cats with the 'ideal weight' phenotype regulated their food intake and bodyweight throughout life, despite ad libitum access to food; in contrast, cats with the 'overweight' phenotype grew rapidly, and were already heavier at 12 months of age, then continued to gain weight progressively thereafter.
That said, as with any statistical modelling approach, the model output could change if new data were added to the dataset. Further, performance was not perfect (R 2 results of 0. 59-0. 75) and a significant amount of variability in food intake remained unaccounted for. This variability is likely to be the result of other unmeasured variables, which might be cat-specific (e. g. underlying physiological conditions, taste preferences and feeding habits of the cat) or environmental (e. g. external noise levels). Unfortunately, these factors were not recorded in the current study. ANN modelling works well when the data set is large enough and is an accurate way of maximising the potential of such data in a predictive goal. ANNs are not designed to understand a process, but only to mimic its outcomes.