dataesr/scientific-paragraphs-categorization huggingface dataset:
This was achieved by simulation: under the null hypothesis and assuming independent chemicals, 10,000 simulations were done with the same sample size and the same number of nodes than in our datasets, using a log-normal distribution; p max was estimated as the threshold to use so that the proportion of simulations that give two or more disconnected subgraphs is at most 5%. Practically, to account for simulation uncertainties and deviations to the simulation model, we used the lowest bound of the 95% confidence interval of p max obtained by simulation, truncated to the second decimal, ensuring a conservative test. The Supplementary Data 17 gives the threshold obtained and used for our different datasets in main analyses. This third step was performed twice: first on all metabolites (after exclusion of metabolites with too large non-detectable amounts, as reported above), and secondly only on metabolites from a preselected set of candidate metabolic pathways of interest: polyamine metabolism, tryptophan metabolism, urea cycle, arginine & proline metabolism, bacterial or fungal, plasmalogen or lysoplasmalogen, and primary or secondary BA metabolism.
All the analyses for this third step, including simulations, were done using the SARP. compo package for R  65  , available on the CRAN repository. Last, the fourth step selected metabolites using group membership modeling. One may wonder whether some of the metabolites selected as associated with either group, may have been selected only due to their relationships with the others. Therefore, multivariable analyses were performed, considering (i) the large number of metabolites (491 for the Rs vs Ra comparison) against the small number of observations (overall, 43 in the Saint Louis sample and 56 in the Cryostem sample) and (ii) the low prevalence of GvHD, notably in the Saint Louis sample (with only 12 GvHD). The latter issue avoids any multivariable regression in the Saint Louis sample (indeed, it is commonly reported that at least 10 events should be observed when including one variable in the model).
Acknowledgements The authors thank all members of the  CRYOSTEM Consortium  and of the Francophone Society of  Marrow Transplantations  and  Cellular Therapy  ( SFGM-TC ) for providing patients samples used in this study and for their support:  University Hospital of Angers, University Hospital of Dijon Bourgogne, University Hospital of Besançon, University Hospital of Grenoble, University Hospital of Lille, University Hospital of Lyon, University Hospital of Bordeaux, Paoli-Calmettes Institute, AP-HM, University Hospital of Nantes, AP-HP (Saint Louis Hospital, La Pitié-Salpêtrière Hospital, Saint-Antoine Hospital ,  Robert Debré Hospital ,  Necker Hospital ,  Groupe Hospitalier Henri Mondor ),  INSERM ,  University Hospital of Toulouse, University Hospital of Tours, University Hospital of Rennes, University Hospital of Clermont-Ferrand, University Hospital of Saint-Etienne, Lucien Neuwirth Cancer Institute, University Hospital of Poitiers, University Hospital of Nice, University Hospital of Brest, Military Hospital of Percy, University Hospital of Montpellier, Gustave Roussy Institute, University Hospital of Limoges, University Hospital of Caen, Etablissement Français du Sang.
We thank  Alexion Company  for their financial support. This project was funded by a grant from the  Direction Générale de l'Offre de Soins (DGOS)  and the  Agence National de la Recherche (ANR)  within a  Projet de Recherche Translationnelle en Santé  ( ANR-PRTS 13002 ). G. S. received a research grant from  Alexion Pharmaceutical company (APALEX)  and from the  Institut National du Cancer  (project number  INCa 2014-1-PL BIO-07-IP-1 ). CRYOSTEM  project is supported by a grant from the  Institut National du Cancer (INCa)  and the  Agence Nationale de la Recherche (ANR)  and under the auspices of the  Société Francophone de Greffe de Moelle et de Thérapie Cellulaire (SFGM-TC).
Rats were divided by extracting subgroups of individuals with low or high scores according to the upper and the lower terciles in each task (n = 12 ± 2). One month after the completion of the behavioural experiment, the tissue content of monoamines and metabolites was evaluated using high pressure liquid chromatography coupled to electrochemical detection in 20 brain areas (10 cortical and 10 subcortical areas) involved in cognition. The neurochemical values, expressed as the index of 5-HT and DA turnovers (content of metabolite/content of neurotransmitter), were redistributed according to the behavioural performances of the rats (adapted versus maladaptive as above) for each behavioural test (6 redistributions). Data were analysed using a Student's t-test and correlative analyses between pairs of regions.
9 ± 2. 0 %, p = 0. 04 respectively, Figure  4B ). Another disease indicator measured was colon length/size ratio because DSS typically results in shortening and thickening of the colon, therefore to an increased colon weight/size ratio. We showed that mice treated with 9 had significantly lower colon weight/size ratio (0. 044 ± 0. 0024, p = 0. 004 respectively) compared to control mice (0. 050 ± 0. 0014, Figure  4C ). We then measured colon myeloperoxidase (MPO) activity, reflecting polynuclear neutrophil infiltration (Figure  4D ). A 43 % inhibition of MPO activity was quantified in colons of mice treated with 9 compared to control mice (1. 3 ± 0. 20 vs 2. 2 ± 0. 31, p = 0. 04). These data concordantly bring evidence that intraperitoneal administration of 9 inhibit the development of DSSinduced colitis.
Primary Data-Analysis Analyses of our experimental data were performed in Microsoft Excel and SPSS 24. 0. 0. 0. In line with our analyses for monoamines  [6]  and adenosine  [7] , we selected analyses that limit the effects of outliers on the results. We thus report median values and the interquartile range (IQR) for each phase of the experiment, instead of the generally reported mean ± standard error. The median of the 12h blocks for baseline-light, baseline-dark, sleep deprivation and recovery were determined for each animal. Differences between these phases were analysed with a non-parametric Friedman repeatedmeasures test for each analysed molecule separately. When the Friedman test indicated an overall significant difference, post-hoc Wilcoxon signed rank tests were used to compare the sleep deprivation and recovery periods with their corresponding baseline, and to compare baseline light phase with baseline dark phase.
Search In brief, a comprehensive search for studies on Hist and the amino acids Asn, Asp, GABA, Glu, Gln, Gly, Pro and Tau retrieved relevant publications from two databases: PubMed and Embase. Searches were performed in 2016, on 12 December for PubMed and on 14 December for Embase. Duplicates were manually removed in Endnote. Our previously developed search filter for microdialysis  [18]  was extended by adding the terms "chemitrode", "dialytrode", "brain dialysis", "intracerebral dialysis", "intracranial dialysis", "transcranial dialysis" and "implanted perfused hollow fibre" to retrieve older microdialysis publications. Previously developed filters were used to select animal studies  [19, 20]. The complete search strategies for PubMed and EmBase are described in our protocol  [21]  and available in appendix 1.
Within publications, experiments using techniques other than microdialysis were also ignored (e. g. in  [22] ), as well as data on amino acids other than those we searched for (e. g. in  [23] ). During screening, tags were added by KJ and CL to all studies on circadian rhythms, sleep and sleep deprivation. Tagged studies were subsequently screened for inclusion in this review based on the following criterion (besides being included in our mapping): studies measuring one or more of the molecules of interest during (1) naturally occurring sleep stages that were validated with polysomnographic measurements and/or (2) during sleep deprivation. Studies on e. g. carbachol-induced REM-sleep were thus excluded (e. g. in  [23] ). To ensure capturing all relevant studies, we searched for studies with the terms "*sleep*", "*REM*", "*rest*", "*fatig*", and "*somn*" in the title within the studies included in our mapping review.
Data Extraction and Analysis The following study characteristics were extracted for the included papers: bibliographic details, location of the laboratory, the number of animals (n); their species, strain, age, weight, and sex; the flow-rate, probe length, diameter, membrane, and reuse; brain region, washout, anaesthesia/freely behaving, post-surgical recovery, amino acids analysed, type of analysis, light-dark cycle and type of sleep deprivation. Furthermore, we extracted the study outcomes relevant to this review by summarising the findings, with the units of measurements as provided by the authors. For legibility, we here present the species, brain region and sleep deprivation method. The other data are provided in appendix 2-4. Data were tabulated separately for studies of naturally occurring sleep and for sleep deprivation studies.
Risk of Bias and study quality Assessment of bias due to study design features and other quality aspects were analysed for all references together (sleep and sleep deprivation studies), by reference, and are shown in appendix 4. None of the 17 included references described blinding of sample analysis, which could result in detection bias, particularly when chromatography peaks are manually integrated. Only two out of 17 described missing samples, which could result in attrition bias. Only 2 out of 17 contained a statement describing the absence of conflicts of interest. Of note, for the studies of amino acids during naturally occurring sleep, the performed analyses were not always appropriately conducted; dependence of the data of included animals was regularly ignored (e. g. [27] ). None of the 17 included references described power analyses, which could result in underpowered studies.
Acknowledgements The authors would like to thank  Judith van Luijk  for advice in protocol development;  Alice Tillema  for help in optimising the search strategy; and  Judith van Luijk ,  Katya Tsaioun ,  Jennifer Freymann ,  Koen Jakobs ,  Thomas J. van Ee ,  Janneke Elzinga ,  Rosalie W. M. Kempkes  and  Bea Zoer  for assistance in screening.
Demographic and clinical data of all participants are summarized in Table  1. Nþ and NÀ were recruited among hospitalized braindamaged patients at the Santa Lucia Foundation, Rome, Italy. The study was approved by the independent Ethics Committee of the Foundation. HS were recruited by means of private announcing. Exclusion criteria for patients (both Nþ and NÀ) were: tumour aetiology, presence of left-sided or diffuse/bilateral brain lesions, and presence of speech impairments. Healthy subjects reported no history of psychiatric or neurological disease or drug abuse. All patients and healthy subjects were right-handed, had normal or corrected-tonormal (contact lenses) visual acuity, as well as self-reported normal hearing. After having received instructions, all participants gave their written informed consent.
Vonly Stimuli consisted of 140 videos showing everyday life situations (cf. Nardo et al. , 2016). The videos were non-Italian TV commercial clips, either purchased from an Advertising Archive (http://www. coloribus. com) or downloaded from YouTube. Using a video editing software (Final Cut Pro, Apple Inc. ), we selected 1. 5 sec video-segments that included a single continuous meaningful scene with either one lateralised distinctive event (Lat-trials) or multiple events on both sides (Multi-trials). The majority of distinctive events consisted in one or more persons in the foreground, who either performed an action (e. g. , walking, dancing, manipulating objects, etc. ) or changed posture. In approx. 10% of videos, the event consisted in a moving vehicle (car, motorbike, plane, etc. , equally distributed across conditions).
Eye-movements The dependent variable of the present study was the ratio of time participants spent fixating on the left versus right hemispace (Gaze_idx). Raw eye-tracking data were processed using the MT_TOOLS toolbox. Fixations were defined as gazeposition remaining within an area of 1. 5 Â 1. 5 deg. for a minimum duration of 100 msec. In order to obtain a specific measure of how the presentation of the short videos affected orienting behaviour, we ensured that the participant's gaze was central before the video onset. For each subject and each trial, we considered only eye-traces where the pre-stimulus gaze position was within ±2 deg. of the centre of the screen. The selection of trials with central fixation allowed us to ensure the correspondence between left/right side of the stimulus and left/ right side of the stimulated visual field at the start of each trial.
Furthermore, this enabled us to specifically target overt spatial shifts associated with salience and meaningful events, rather than any stimulus-unrelated sustained bias of gazeposition (see also Table  S1 , in the Supplementary Material reporting the percentages of trials excluded because of prestimulus biases). In addition, we considered only trials where at least 50% of data points during the presentation of video could be categorised as fixations, i. e. , excluding trials including many blinks and/or other artefacts. We counted how many trials satisfied the specified criteria and discarded participants who had less than 4 trials for each experimental condition (see also Participants). The computation of the Gaze_idx comprised several steps. First, for each subject, we extracted the time spent fixating the left and right side of the display (Ltime and Rtime), considering the full stimulus duration in Vonly experiment, and the 1.
Individual lesions were drawn by a trained physician (BS) on either MR (n ¼ 25) or CT (n ¼ 18) scans and doublechecked for accuracy by a senior neurologist (MB) experienced in reading brain scans, both blind to the medical history of patients. Hypointense lesions were outlined directly on the MPRAGE T1-weighted (or hypodense lesions on CT) slices using a semi-automated local thresholding contouring software (Jim 5. 0, Xinapse System, Leicester, UK, www. xinapse. com) and were then normalized to the standard MNI space by using ANTs 1. 9. x (picsl. upenn. edu/software/ants) to obtain an optimized spatial transformation  (Avants et al. , 2011). Lesion overlaps are shown in Fig. 1A. In order to confirm the implication of the ventral frontoparietal cortex in neglect  (Corbetta & Shulman, 2011; Mort et al.
Visual experiment (Vonly) Fig. 2  shows the visual exploration patterns, as a function of condition and group. Our main analyses quantified these patterns in term of the ratio of time spent looking toward the left/right side (see Methods). First, we assessed the influence of high-level signals by comparing videos that included a single event lateralised on one side (Lat-trials) with videos including multiple competing events on both sides (Multitrials). We performed a mixed three-way ANOVA on transformed Gaze_idx data with Group as between factor (NþHÀ, NþHþ, NÀ, HS), and Competition (Lat, Multi) and visual Side (Left, Right) as within factors. We expected that the level of competition would modulate the orienting deficits in the contralesional hemispace in neglect patients, which would be captured by the three-way interaction.
This work was supported by  Institut National de la Santé et de la Recherche Médicale  Grant  U10512F/U1051SE12FE , the  Inserm Grant  ( U1051-Dot 02-2015 ),  Fondation de l'Avenir  Project  Et2-675 ,  Cochlear   France Award  ( R11055FF/RVF11006FFA ),  Agence Nationale pour la Recherche  ( ANR-13-JSV1-0009-01 ) and " Prix Scientifique" from "Fondation pour l'Audition ". The authors acknowledge language services (www. stels-ol. de)for editing assistance.
Methods Subjects. All animals were bred in a C57BL/6 mouse strain background and were housed in standard conditions (12 h light/dark cycle light on at 7 am, water and food ad libitum). All data were obtained during the light phase, in compliance with the European Commission directives 219/1990 and 220/1990 and approved by the Comité d'Ethique En Expérimentation Animale Charles Darwin C2EA-05 (Jerôme Yelnik, project 00896. 01). Experiments were carried out in blind conditions with respect to the genotype. For electrophysiology, eight transgenic L7-PP2B mice and eight wild-type littermate controls were recorded in this study. In L7-PP2B mice, the selective deletion of PP2B in Purkinje cells was obtained using the Cre-loxP-system. L7-PP2B mice display normal cerebellar histology and an intact induction of LTD at the parallel fiber-Purkinje cell (PF-PC) synapse.
If no waveform of sufficient amplitudes was detected, the tetrodes were lowered by 60 µm steps until hippocampal units could be identified. Signals were amplified 2000 times, filtered (band-pass 0. 6-9 kHz) using amplifiers and processed with the animals' position signals using Datawave SciWorks acquisition software. Waveforms of identified units were sampled at 32 kHz and stored. Along with unit data, hippocampal pyramidal LFPs (filtered between 1. 0 and 475 Hz) were recorded from one electrode using a 11. 67 kHz sampling rate. Video recording was performed using a CCD camera (Mintron, PAL) fixed to the ceiling above the arena and the mouse position was tracked by contrast, at a sampling rate of 25 Hz. Hippocampal activity was recorded while animals explore a white circular arena (50 cm diameter, 30 cm high, made of white polypropene and the floor covered with white linoleum).
For some cells (randomly chosen), a 3-sessions cue removal protocol was run immediately after, in order to examine the influence of external information on place cell firing. The mouse stayed in the arena, the light was turned off, the cue (card + object) was removed and sessions 3 and 4 were run. After the mouse returned to its home cage, a last standard session (S5, similar to S1 and S2) was run to check that, whatever the changes in cell firing observed during the cue manipulation sessions, the initial firing pattern could be restored. In the dark condition, the mouse position was tracked by contrast, using infrared light. Analysis of electrophysiological recordings. Spike sorting and cell classification: simultaneously recorded units were clustered manually using Plexon Offline Sorter software.
Similarly, this value was compared to chance level by a permutation test. For each set of place field barycenters, a corresponding set of barycenters was randomly selected for S1 and S2, variations in angles AÔB were computed. This was done for all sets of place field barycenters and allowed to compute a mean random variation in angle (mean random ΔΘ). This permutation procedure was repeated 200 times. Mean ΔΘ computed on data was then compared to the distribution of mean random ΔΘ. First for each of these episodes, the rotation angles of all place cells were determined (i. e. , the place field angular shift, see above). The mean rotation angle and the circular standard deviation (SD) were then computed for each set of simultaneously recorded place cells. This circular SD was then averaged over the experiments and compared to chance level by a permutation test.
To do so, for each set of rotation angles, a corresponding set of angles (matched in sample size) was selected from shuffle data and used to compute a random SD. This was done for all sets of rotation angles and allowed to compute a mean random SD. This permutation procedure was repeated 200 times. Mean SD computed on data was then compared to the distribution of mean random SD. For LFP analysis, the raw data was first notch filtered around 50 Hz to remove noise from electrical current. Power spectrum density (PSD) was calculated between 1 and 150 Hz using the multitaper method of the Chronux toolbox  50  in Matlab. PSD was measured using 1 s windows and averaged only when the speed was superior to 2. 5 cm s -1 and using 5 tapers. For mice behavior during exploration of the familiar environment, to analyze mice behavior during exploration of the recording arena, the traveled distance, number of stops, mean running speed, distance from wall, time spent in the center and the number of entries in the center normalized by the distance were computed.
In either case, the mouse was allowed to remain on the platform for 30 s. Data acquisition was performed at a frequency of 25 Hz using the SMART ® video recording system and tracking software. Data processing was automated using NAT (Navigation Analysis Tool), a Matlab-based software (NAT: Navigation Analysis Tool) developed in our laboratory  51. The traveled distance to reach the platform and the average speed were analyzed. To analyze the proportion of successful trials during training, we used a Gaussian fit on the distribution of traveled distances to separate successful (short) and failed (long) trials. Since the Gaussian fit was centered on the successful trial distances the threshold was defined as the distance above which more than 90% of the distribution was not longer explained by the fit (note that a bimodal Gaussian fit could not be used since the distribution of failed trials could not be fitted by a Gaussian curve).
All the different navigation parameters were analyzed during light and dark conditions. Statistics. All statistics were carried out with Matlab statistics toolboxes and the STATISTICA software. For all statistical tests, data were tested for normality and homogeneity of variances using a Kolmogorov-Smirnov test to ensure they met the necessary assumptions before proceeding to analysis. Statistical tests included Mann-Whitney U-test, Student's t-test, Wilcoxon Signed-Rank tests, Chi-square tests, Fisher tests, and repeated measure analyses of variance (ANOVA). Distributions of similarity coefficients were compared by a Kolmogorov-Smirnov test. Circular statistics were made using Circstat, a Matlab toolbox for circular statistics  52. When multiple comparisons were applied, p value was adjusted with a Bonferroni correction.
Acknowledgements The authors thank  Gregory Lafon ,  Julien Schmitt , and  Aurélie Watilliaux  for technical support;  Nadir Benlismane  and  Audrey Goulian  for animal care; and  Aurélie Watilliaux  for mouse colony supervision and genotyping. The authors thank  Glenn Dallérac  and the CeZaMe team members:  Mehdi Fallahnezhad ,  Anne-Lise Paradis , and  Thomas Watson  for their constructive comments on the manuscript. The authors also thank the  Moser's lab  for sharing part of their Matlab codes. This work was supported by the  Institut DEQ20120323730-France , by the  National Agency for Research   ANR-REG-071220-01-01-France  (L. R. -R. ), and by the  Institut Universitaire de France  (C. R. ). This work also received support under the program Investissements d'Avenir launched by the  French Government  and implemented by the  ANR , with the references, PER-SU (L.
R. -R. ) and  ANR-10-LABX-BioPsy  (L. R. -R. ). The group of L. R. -R. is member of the  Labex Bio-Psy  and  ENP Foundation. Labex are supported by  French State  funds managed by the  ANR  within the  Investissements d'Avenir programme  under reference  ANR-11-IDEX-0004-02. L. J. M. was funded by the  Ministère de l'Enseignement Supérieur et de la Recherche, France  and  FRM. C. I. D. Z. is funded by the  Dutch Organization for Medical Sciences, Life Sciences, and Social and Behavioral Sciences , and  ERC-adv  and  ERC-POC.