dataesr/scientific-paragraphs-categorization huggingface dataset:
Data extraction Two independent reviewers (BQ and YL) will extract the data from the original reports using standardised data extraction forms, including study characteristics (such as first listed author, publication year, title, publication type, publication journal, country and sponsor), patient characteristics (such as diagnostic criteria, type of anxiety, level of anxiety symptoms, comorbidities, the age of patients, the number of patients and the gender of patients), intervention details (such as psychotherapy type, intervention formats, treatment conditions and different delivery modalities, the session of psychotherapy, the duration of acute treatment and follow-up and cointerventions) and outcome measures (efficacy outcomes at acute treatment and follow-up, acceptability outcome, QoL/functioning outcome).
Statistics Data were analyzed with GraphPad Prism version 5. 0 for Windows (San Diego, CA). One-and two-way ANOVA was used followed by a Tukey's post-hoc comparisons (or more strictly, Tukey-Kramer, owing to unequal group sizes). t-tests were applied for two-group, two-tailed comparisons. A type I error rate of p < 0. 05 was adopted, and data are shown as mean ± SEM.
Acknowledgements We would like to acknowledge the important contribution of  Drs. Dolores Bonapartes ,  Dinora Lopes ,  Henrique Silveira , as well as the technical help of  Helen Dugua ,  Colette Rousset  and  Olga Karnauch. We thank the  Portuguese Foundation for Science (FCT) ,  New Lisbon University , the European Community (EC:  AGGRES-SOTYPE FP7/No. 602805 ),  NARSAD  for their financial support,  Drs. Oleg Dolgov ,  Alexander Lysko ,  Andrey Proshin ,  Elena Zakharova ,  Vladimir Kovalson ,  Alexander Revischin ,  Almaz Kotovsk Tambov Reg  for supplying the D91 and D140 water and  Mr. Paul Courtel.
Watching a negative movie just prior to the sleep period leads to more NREM2 sleep  [25] , a reduction in the percentage of REM sleep and more awakenings  [26, 27]. It can also increase REM density  [26, 27]  or change the dream content during the earlier part of the night  [28, 29]. Concerning positive movies, the scarce data suggest that positive emotional states prior to sleep can improve sleep problems  [30] , but the details of this influence remain unexplored. In order to investigate sleep architecture further following emotional events, autonomic nervous system (ANS) indicators could be of valuable interest. In particular, the sympathetic division of the ANS is strongly associated with central activations required by the processing of cognitive and emotional information (see Kreibig  [31]  for a review).
In the first step, different videos were extracted from cinematographic movies, and a database of 63 pre-selected video clips was established (29 negative, 14 neutral, and 20 positive). The duration of each video clip varied between 1 and 4 minutes. In the second step, the emotional impact of each of the 63 pre-selected extracts (mean duration: 2. 0 ± 0. 7 minutes) was evaluated by Japanese students, with a methodology similar to that used by Schaefer et al. [44]. Their valence and activation values  [45]  were rated, and the Japanese version of the Positive And Negative Affect Scale (PANAS)  [46]  was completed. In fact, three sets of 21 video clips were created, each comprising 9 or 10 negative, 4 or 5 neutral and 6 or 7 positive video clips. The order of the video clips in each set was randomized, with the condition that a clip never had the same valence as the preceding one.
e. every hour) for relaxation, during which participants were free to do as they wished. In the third step, the video clips with the highest scores in their respective categories (negative, neutral and positive) were compiled with specific software (Premiere Pro v5. 5, Adobe) to create three movies of corresponding valence. Each movie lasted 20. 4 ± 0. 2 minutes, started with the least arousing clip and ended with the most arousing one. A non-lyrical soundtrack was synchronized with the movie, matching the action and the emotion to reinforce the immersion  [24]. The neutral movie was characterized by a mean valence of 5. 2 ± 0. 3, and an arousal of 2. 0 ± 0. 3. In comparison, the values of valence and arousal of the positive movie were higher (valence: 6. 8 ± 0. 5; t 17 = 8. 1; p < 0. 001; arousal: 3.
All electrodes were connected to a headbox (San Ei Electrode Box) linked to a recording system (San Ei Biotop 6512) enabling the filtering (0. 5 Hz-100 Hz pass band), sampling (256 Hz) and amplification of signals, continuously processed during emotional induction and the sleep period using the software Sleep Maister 1. 2 (IAC, Tokyo, Japan). Electrodermal activity was recorded using the conductance technique (constant-voltage method, 0. 5 V) at a sampling rate of 256 Hz, and low-pass filtered at 50 Hz. Two Ag-AgCl electrodes (active area: 1 cm in diameter) were attached to the palmar side of the middle phalanges of the second and third fingers of both hands. Electrodes were connected to a common acquisition system (PowerLab and LabChart 7, AD instruments) for amplification. A back-up of all signals was made with a link to a magnetic band recorder (Cassette Data Recorder XR-7000L, TEAC).
Data analysis Psychometric questionnaire. The two PANAS subscores were extracted and transformed into z scores ([Value of raw score-Mean value of participant] / [Standard deviation of the participant]) for each participant and each measure. Hypnogram. Sleep recordings were scored manually, by two experimenters, according to the standard rules of the American Academy of Sleep Medicine  [51]. Based on epochs of 20 seconds  [51] , the following sleep variables were extracted: total sleep time (TST), sleep onset latency (SOL: from the moment the lights were turned off until the first minute of NREM2), waking after sleep onset (WASO), sleep efficiency (SE); percentage of stage 2 sleep (NREM2), stage 3 sleep (NREM3), and REM sleep after sleep onset; latency of NREM3 and REM sleep. Due to the absence of NREM1 after sleep onset for some nights, this sleep stage was not considered for analysis.
Statistical Analysis The primary endpoint of this study was the association between subjective sleep complaints and overall survival (OS). We explored this association using sleep scores at baseline, while on treatment, and as time-dependent covariates (TDC). In each case, OS was measured from the date of completion of the corresponding questionnaire to the date of death (due to any cause). Patients still alive at the time of database locking were censored at the last date known to be alive. Similarly, time to progression (TTP) was calculated from the date of questionnaire completion until the date of disease progression or death, whichever occurred first. Survival curves and probabilities were estimated using the Kaplan-Meier technique, and differences between survival curves were assessed using the log-rank test.
The Cox proportional hazards regression model was used for both univariate and multivariate analyses of survival. For the prognostic analysis, the subjective sleep complaint was used either as a simple variable or as a time-dependent covariate. A multivariate prognostic model was then built, forcedly entering other possible prognostic factors. The added adjusting factors included: randomized treatment, age, sex, site of primary tumor, resection of primary tumor, Duke's stage at diagnosis, prior adjuvant chemotherapy, World Health Organization (WHO) performance status (PS) at baseline, number of metastatic sites, body mass index (BMI) at baseline, anemia, leukocytosis, and elevated alkaline phosphatases or lactate dehydrogenase (LDH)  25. For survival analysis using sleep data during treatment, PS and BMI at day 1 of the corresponding chemotherapy cycle of questionnaire completion were used instead of baseline values.
Prevalence of subjective sleep problems at baseline and on treatment Prevalence of sleep problems is shown in Figure  1. There were no differences between treatment arms concerning sleep problems reported at either baseline or during treatment. Overall, 131 patients (36. 3%) reported sleep problems at both assessments (baseline and while receiving treatment); no mention of sleep problems was recounted by 102 patients (28. 3%) at both assessments. New onset sleep problems were reported by 57 patients (15. 8%), and 71 patients (19. 7%) experienced sleep remission while receiving chemotherapy. These figures were comparable in patients on FOLFOX2 and on chronoFLO4 (p=0. 74; data not shown).
Loxapine is an antipsychotic used in psychiatry for over 40 years with a well-established profile. Loxapine is a dibenzoxazepine tricyclic antipsychotic agent, available for oral, intramuscular and inhalatory administration. In the light of the recent approval by the regulatory agencies of inhaled loxapine for use in the acute treatment of mild-to-moderate agitation in adults affected with schizophrenia or bipolar disorder, this article aims to critically review the available literature on loxapine, irrespective of its formulation. This review examines the efficacy and tolerability of the various formulations of loxapine in the treatment of agitation and aggression in patients affected with schizophrenia, bipolar disorder and other psychiatric conditions. A comprehensive and systematic literature search of PubMed/MEDLINE was conducted, and relevant pharmacodynamic and pharmacokinetic data was included.
Subjects and training Subjects were recruited from undergraduate and postgraduate programs in Archaeology at Exeter University. Subjects were ages 18-25 at the time the first scan was collected, 5 male and 1 female. All were right-handed by self-report and subsequent observation, had no neurological or psychiatric illness, and provided written informed consent before the study and the study was approved by the Ethics Committee at Exeter University. Imaging took place at the Wellcome Department of Imaging Neuroscience in London. All subjects provided additional written informed consent for imaging data collection and the research was approved by the National Hospital for Neurology and Neurosurgery and Institute of Neurology Joint Research Ethics Committee (Reference #: 1825/003). Stone toolmaking involves striking a stone "core" with a "percussor" of bone, antler, or stone to detach controlled flakes and incrementally achieve design goals.
Probabilistic tractography A binarized mask of the left superior frontal gyrus cluster was used as a seed for probabilistic tractography using FSL  [39] , a software library of analysis tools for neuroimaging data. Each subject's B0 image was registered to their T1-weighted structural image using a 6-degree of freedom, rigid-body registration computed by FSL's FLIRT algorithm. T1 images were first registered to the MNI 1mm template using a 12-degree of freedom, affine registration computed by FLIRT, which was then used to constrain a nonlinear warp computed by FSL's FNIRT algorithm. The T1-to-MNI and B0-to-T1 registrations were then inverted and concatenated to warp MNI-space functional activations into individual subjects' diffusion space. These diffusion-space activation masks were used to seed probabilistic tractography analyses using probtrackx, a tool in FSL's FDT software package.
Statistical analysis. Data are expressed as mean ± SEM. Comparison between two groups was performed by Student's t-test while comparison of multiple groups was performed by one-way ANOVA followed by a Bonferroni's post hoc test using GraphPad Prism version 5. 00 (GraphPad Software, Inc). Statistical significance was defined as p < 0. 05 unless otherwise stated in figure legends. For clinical studies, data were presented as mean values ± SD or when the data failed the D' Agostino-Pearson test for normal distribution as median with 95% confident interval (CI) for continuous variables and as percentage for categorical variables. For categorical variables, a Pearson Chi-square test was used to determine the statistical significance of the association between the variable and obesity status. For continuous variables, a Student's t-test or Mann-Whitney rank sum test when normality test failed was used to determine the statistical significance of the association between the variable and obesity status with a 2-tailed P value determination.
Plasma apeline concentrations were analyzed by two-way ANOVA followed by Bonferroni's post-hoc analysis using GraphPad Prism (version 5. 0) software (GraphPad Software, San Diego, CA, USA). P < 0. 05 was considered statistically significant. Logistic regression analysis was performed using Statistical R (version 3. 0. 1; http://www. r-project. org, MASS package version 7. 3. 37) to analyze the relationship between obesity or ischemic heart failure status and apelin. Two methods were used to select independent variables in the model: enter method, all variables were included without checking; stepwise method, variables were sequentially included, check and possibly remove variables that became non-significant after entering a variable (enter if P < 0. 1 remove if P > 0. 2).
Acknowledgements We thank  Dr. A. Dejean  ( CTPT Toulouse-Purpan )for kindly providing the FoxO3-TM plasmid. This work was supported by grants from the  National Institute of Health and Medical Research (INSERM) ,  Fondation Lefoulon-Delalande ,  Fondation de France ,  Région Midi-Pyrénées  and  Fondation pour la Recherche Médicale (FRM).
Model Fitting We used the MATLAB fmincon function to estimate the value of the two parameters r and q that minimize the mean squared error between the actual adaptations of subjects for Tasks 1 and 2 and model predictions, y(n) (see Eqs 1 and 3). The adaptation data used for the model fit were calculated by averaging the observed adaptations of 21 subjects, excluding missed trials and trials with large (>40°) overshoot. Less than 1% of the total number of trials was excluded. Because of the task sequence counterbalancing, the average was computed after inverting the sign of adaptation for ten subjects starting with Task 2. Using the estimated parameters, we simulated the time series of the 30 states of memory for each task, x k every 1. 8 s, corresponding to scanner repetition time (TR). Because the model equation (Eq 2) updates the states at each trial, we interpolated and resampled the states of memory at the time of image acquisitions, i.
Multivoxel Pattern Analysis (MVPA) We additionally conducted an MVPA to test if the regional brain activity could be used to classify the two rotational types (40°and -40°). The ROIs include the right parietal lobe and the cerebellum. Our previous model-based regression analysis suggested that these regions are related to the middle (the parietal regions) and the slow (the cerebellum) states (blue circles in Fig  3A ). The ROI of the right parietal region was the superior and the inferior parietal lobes according to anatomical map in Pick Atlas (http://fmri. wfubmc. edu/software/PickAtlas). The cerebellar ROI was anatomically defined bilaterally. Fig  5A  shows the parietal and cerebellar regions enclosed by red and cyan curves, respectively. Within the parietal ROI, we applied MVPA to BOLD signals of voxels that were significantly correlated with at least one of the intermediate states (τ k , ranging from 2.
csie. ntu. edu. tw/~cjlin/libsvm/), with default parameters (a fixed regularization parameter C = 1). The separate training and testing datasets were generated with a pseudo-random half split of all the samples. Cross validation was then conducted for 1,000 times for each subject, and the average classification accuracy was estimated. The two-way ANOVA with ROIs and sessions as an intrasubject factor was used to test the differences in classification accuracies.
Stimuli were presented in free field via JBL studio monitors (LRS2325p) installed in front of the participant. Metronome sequences were presented first (i. e. , in the order of 600, 450, and 750 ms), followed by the musical excerpts. Each trial was preceded by a practice trial. During the whole session, the experimenter was present. In addition, in the experimental groups, spontaneous (i. e. , unpaced) tapping was assessed previous to the Experiment by asking the participants to tap as regularly as possible during 1 min at a comfortable, selfchosen pace. The Experiment was run on Max MSP (6. 0) software and lasted 15 to 20 min.
e. , when taps occurred reliably at a given phase relationship relative to the pacing stimulus). In addition, before performing further analyses, vector length values were submitted to a logit transformation to reduce data skewness, which is typical of synchronization data (e. g. ,  Kirschner and Tomasello, 2009; Sowiński and Dalla Bella, 2013). Finally, in the spontaneous tapping task, the mean ITI was calculated as a measure of preferential tapping tempo and the Coefficient of Variation of the ITIs (CV ITI) was computed as a measure of motor variability.
8, ε = 0. 89 p = 0. 07] 3. The other interactions were not significant. To test whether predictive timing differed between the participants who stutter and controls, accuracy data were submitted to 2 × 2 factorial ANOVAs for circular statistics (Harrison-Kanji Test), using the Matlab Circstat toolbox  (Berens, 2009) , one for each IOI 4  , taking Group and Age as factors. At the slowest tempo (IOI = 750 ms) and at the fastest tempo (IOI = 450 ms), children and adolescents who stutter tapped more in advance of the pacing event than controls did [750 ms, F(1,59) = 5. 67, p = 0. 02; 450 ms, F(1,59) = 3. 82, p = 0. 06, marginally significant; 600 n. s. , p = 0. 31]. No age differences (p > 0. 25) and no interaction were found (p > 0. 45). The same analyses as above were carried out for synchronization with music 5.
Acknowledgments The study has been funded by the  European Union   Seventh Framework Program  (FP7/2007-2013;  FP7-PEOPLE-2012-IEF , grant agreement n • 327586) as well as by  SSHRC-MCRI  AIRS research grant, both to SF, and by the  Institut Universitaire de France  to SDB. We thank the team of the SAS course,  I. Mayer ,  G. Thum , and the  Josef-Hofmiller-Gymnasium Freising  for their help with recording participants. We also thank  N. Farrugia  and  V. Begel  for their help with tapping analyses and programming and  J. Harrington  for helpful discussions.
New software nevertheless allow to reduce these subjective elements in the analyses (e. g. , Etho-Vision XT from Noldus Information Technology, The Netherlands, or Mice Profiler from Icy software  [23, 24] ). The elicited interactions are closer to ethological behaviors, even if the motivation of the animals is usually manipulated (through social isolation and habituation to the test cage for the occupant, and group housing for the new-comer, situation considered in the present study). Data extracted allow a qualitative description of the interactions. We designed the present study to test specifically the influence of the cage shape/size and the habituation time that vary in a controlled way. We aimed at testing whether same-sex social interactions occurring in a reasonably sized test cage with reduced habituation time are not forced in comparison with social interactions in larger cages with longer habituation time.
We used the semi-automated module Mice Profiler from Icy software  [23] , that allows a comparison over a large panel of events, states and sequences of events within social interactions to get as much details as possible on these interactions in each condition. We hypothesized that social interactions in the round cage will be the most different from the rectangle and the square cages. Indeed, corners in test cages appear to be very often used by animals (see Fig. 1C ), and therefore their absence might lead to major modifications of the interactions. Given our previous experiments, two habituation times have been chosen close enough not to have a large influence on social interactions. The reason of this comparison is very pragmatic: the shorter habituation time will be convenient to spare some time for each animal and to improve testing efficiency.
Ultrasonic vocalizations were recorded simultaneously (sampling frequency: 250 kHz, 16-bit accuracy). Audio recording hardware (UltraSoundGate 416-200, Condenser ultrasound microphone Polaroid/CMPA) and software (Avisoft SASLab Pro Recorder) were from Avisoft Bioacoustics (Berlin, Germany). Previous experiments suggested that ultrasonic vocalizations were mainly emitted by the occupant; the contribution of the new-comer (if any) was negligible  [22]. At the end of the experiment, mice were returned to their respective home cages and none of the occupants were used again. Between each interaction test, the experimental cage was emptied from bedding, and new fresh bedding was used. Given the important number of conditions tested (6 conditions: habituation time: 20 min or 30 min; cage shape: rectangle, round, or square), we tested and analyzed only 8 pairs of mice per condition to limit the number of animals involved.
853 ms; frequency resolution: 293 Hz; Hamming window). We measured the latency for the first ultrasonic vocalization as well as the total number of ultrasonic vocalization and their duration. We used non-parametric statistical tests given the non-normal distribution of the data and the small sample-sizes (8 pairs of animals per condition). We used a Kruskal-Wallis rank sum test to evaluate the effect of the cage shape for each habituation time separately. When significant differences emerged, we used Wilcoxon-Mann-Whitney U-tests to identify where the difference stemmed from in 2-by-2 comparisons. To evaluate the effect of the habituation time for each cage shape separately, we used Wilcoxon-Mann-Whitney U-tests. All statistical results are compiled in the S2 Table. All analyses were conducted with the computing and statistical software R (R Developmental Core Team 2009).
This might suggest that the lack of corners renders it more difficult to the animals (used to cages with corners throughout their life) to habituate to such environments. The exploratory phase might last longer in round cages than in cages with corners, delaying the social investigation. The Mice Profiler module of Icy software from de Chaumont and colleagues  [23]  was originally tested on mice interacting with a similar protocol as ours, with a rectangular cage and 30 min habituation to the test cage. We compared our data within the rectangular cage and after 30 min habituation to these data for C57Bl/6J male mice. The duration of the follow behavior was slightly shorter in our experiment in comparison with the de Chaumont and colleagues' study both during the first 4 min of interaction and during the 8 min of interaction  [23].
The duration of nose-to-nose contact was lower in our study in comparison with the de Chaumont study, while the total duration of oro-genital sniffing (from both the occupant and the newcomer) was similar between the two studies during the first 4 min of interaction. Overall, most discrepancies were found for the nose-to-nose contact, while data for other behaviors were similar. The fact that mice from the present study were isolated for 3 weeks and those from the de Chaumont study for 4 weeks might explain some of the differences between the durations of the follow behavior and of the types of contacts. Ultrasonic vocalizations were recorded in all conditions, confirming that two interacting males vocalize together and do not show overt aggressive behaviors during 4 min (and even 8 min) of interactions if the occupant has been isolated for 3 weeks before the test.