dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We thank  Vincent de Sars  for software developing,  Coherent Inc. for the loan of the Fidelity laser, This research received support from the  'Agence Nationale de la Recherche'  (grant  ANR-15-CE19-0001-01 , 3DHoloPAc), the  Human Frontiers Science Program  (Grant  RGP0015/2016 ), the  Fondation Bettencourt Schueller  ( Prix Coups  d'élan pour la recherché française), the  Getty Lab , the  National Institute of Health  (Grant  NIH   1UF1NS107574 -01 ) and Axa research funding. N. A. received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement no. 746173. E. R. received funding from the  European Research Council   SYNERGY Grant  scheme (HELMHOLTZ,  ERC  Grant Agreement #  610110 ). IWC received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Skłodowska-Curie  grant agreement no.
Apparatus Stimuli were displayed on a 17″ Dell M770 CRT monitor with a refresh rate of 60 Hz. All stimuli were produced using the Psychtoolbox toolbox  (Pelli, 1997)  in MATLAB R2012a. The monitor (1024 × 768 pixels) was placed 57 cm in front of the participants and had a spatial resolution of 1. 9 arcmin per pixel. Mean luminance was 47. 6 cd/m 2 , as measured with a Minolta CS110 (Konica Minolta, Canada). A chin-andhead rest was used to keep the head position fixed and the viewing was binocular. The experiment was conducted in a dark room.
Data analysis Visual inspection of the data suggested a possible inhomogeneity in the variance of the training data between the two groups. We confirmed this by means of a Bartlett test (Bartlett's K-squared = 43. 57, df = 11, p-value = 0. 001), therefore we adopted non-parametric (distributionfree) inferential statistical methods. The Aligned Rank Transform for non-parametric factorial ANOVA  (Wobbrock et al. , 2011)  allows a nonparametric analysis of variance to be conducted on factorial models with fixed and random effects for repeated measures. For the main effects, we performed this analysis using the "art" function of the ARTool package available at CRAN  (Kay and Wobbrock, 2018). To test for interactions, we used another non-parametric ART test specifically developed to test for interactions of repeated measures design with one 'within' and one 'between' factors as described by  Beasley and Zumbo (2009)  and  Higgins and Tashtoush (1994).
This test was performed with the "npIntFactRep" function within the homonymous R package  (Feys, 2015). However, because this package does not allow for testing interactions with more than one 'within' factor, we only ran interaction tests for the pre-post comparison in the trained and transfer tasks and for the between session learning but not for the between blocks learning. All the comparisons were pre-planned and we therefore reported their statistical significance without correcting for multiple comparisons. Given the number of performed comparisons (21), if all the null hypotheses were true, we should expect only 1. 05 (5%) of the comparisons to have uncorrected P values less than 0. 05. This consideration is important to better evaluate the strength of the reported results  (Rothman, 1990).
, United States) for an overnight on shaker at 4 • C. After washing, horseradish peroxidase-conjugated species appropriate secondary antibodies were incubated at room temperature. Immunoreactive proteins were detected with an enhanced chemiluminescence Western blotting detection system. The relative density of the protein bands was scanned by densitometry using MyImage (SLB, Seoul, Korea), and quantified by image analysis software for gel documentation (LabWorks Software Version 3. 0, UVP Inc. , United States).
Statistical Analysis Results are presented as means with error bars indicating the standard error of the mean (Mean ± SEM). There was no evidence for significant deviations from normal distribution (p > 0. 05, Shapiro-Wilk test). RM two-way analysis of variance (ANOVA) and RM one-way ANOVA with the greenhouse-Geisser correction test, followed by Tukey's multiple comparisons test, were used for Figures  1A, B , respectively. On the other hand, ANOVA followed by Tukey's multiple comparison test with a single pooled variance was used to analyze all other figures. All statistical tests were two-sided and the level of significance was set at p < 0. 05. GraphPad Prism software version 6. 01 (San Diego, CA, United States) was used to perform statistical analysis. Significance is indicated by * p < 0.
DISCUSSION In the current study, we demonstrated that administration of melatonin at physiological and pharmacological doses ameliorates the severity of EAE by attenuating neuroinflammation, increasing the expression levels of mature oligodendrocytic markers and modulating cerebral energy metabolism, as summarized in Figure  8. Melatonin was previously shown to be inversely correlated with the severity of MS and its relapse  (Sandyk, 1993; Melamud et al. , 2012). Several studies have indicated a beneficial role for melatonin in attenuating neuroinflammation and stimulating remyelination in adult EAE mouse and rat models of MS  (Kang et al. , 2001; Alvarez-Sanchez et al. , 2015; Chen et al. , 2016). Melatonin is also currently used in an open clinical trial in patients of MS (ClinicalTrials.
gov identifier NCT03498131). In this study, the effects of melatonin therapy on the mechanisms of molecular immune polarization were investigated by measuring pro-inflammatory (TNF and IL-1β) and anti-inflammatory (IL-4 and IL-10) cytokine levels in the mouse brain, previously shown to be linked to EAE disability and tissue destruction  (Batoulis et al. , 2010; Bernardes et al. , 2013). Our data in this study confirmed our previous results that pharmacological doses of melatonin significantly recovered the decreased expression levels of IL-4 and IL10 in PBS-treated EAE mice while reducing the elevated levels of TNF and IL-1β  (Ghareghani et al. , 2018a,b). Moreover, this study demonstrated that MBP and MOG, which are myelin-associated proteins localized on the surface of oligodendrocytes, showed marked reduction in EAE mice compared to controls.
Subjects Twenty right-handed healthy volunteers (age 29 ± 7 years; 8 males) participated in the fMRI study. The trial was supported by the Institut National de la Santeet de la Recherche Medicale (INSERM, C08-07, N˚IDRCD/ 2008-A00324-51, ClinialTrial. gov Registration NCT02055261) and received approval from the local ethical committee of Paris 6-Pitie-Salpêtrière Hospital. All volunteers signed an informed consent in accordance with the Declaration of Helsinki. All volunteers were familiarized to walk down a 10-meter-long hallway three times, at their natural speed, recorded using a stopwatch. For each volunteer, an average normalized gait speed (equal to gait speed/height) was calculated across trials.
The virtual gait task A virtual environment that closely mimicked the real hallway used for training was designed using 3D meshes with photorealistic textures and computer-generated lighting effects from 3D graphics software (Blender, The Blender Foundation, Amsterdam). Video game-like oscillations reproduced the pendular movement of the head while walking from a first-person perspective. These oscillations were absent for the control conditions. The virtual gait task consisted of four conditions. The first condition was imagining walking down the virtual hallway (Condition Gait, "GAIT"). The second condition consisted of imagining gliding smoothly on a moving walkway along the same hallway (Condition Walkway, "WALKWAY"). The third condition was imagining walking down the same hallway through a narrow open doorway (Condition Gait with Open Doorway, "GAIT DOORWAY").
Functional MRI data preprocessing Images were preprocessed using the SPM8 statistical parametric mapping software (http:// www. fil. ion. ucl. ac. uk/spm8) implemented in MATLAB1 (The MathWorks, Inc. ). Images were corrected for rigid body motion. Susceptibility artifacts were corrected by unwarping using TOPUP from the FSL suite (http://fsl. fmrib. ox. ac. uk/fsl/fslwiki/). Following co-registration of functional and anatomical images, the anatomical images were segmented and normalized to the Montreal Neurological Institute (MNI) standard space. The functional images were then normalized using similar parameters and smoothed with a 3-mm-full-width-at-half-maximum isotropic Gaussian kernel. The time series were high-pass filtered (cut-off period 128 seconds) to remove low-frequency noise.
Functional MRI data analysis Statistical analyses were carried out using SPM8 to study the two main contrasts of interest: GAIT-WALKWAY to assess the positive effect of gait without doorway, and GAIT DOOR WAY-WALKWAY DOORWAY to assess the positive effect of gait with doorway. As our purpose was to examine deep brain structure activity during imagined walking with versus without doorway, we first performed a preliminary analysis to detect subjects that activated motor cortices, which would be expected with our virtual gait task, as reported previously during imagined or observation walking  [10, 14, 37]. Individuals with a significant increase in BOLD signal for the global effect of gait using the (GAIT+GAIT DOORWAY)-(WALKWAY+WALWAY DOORWAY) contrast in a motor/premotor cortical mask of interest were then included in the final analysis.
The parameters of the general linear model were estimated within an explicit mask of the subject's brain (namely, the canonical brain mask from SPM8). Then, only volunteers showing significant activation (multiple comparisons corrected at the cluster level for p<0. 05 using the false discovery rate procedure; cluster-defining threshold: p<0. 001 uncorrected  [39, 40]  for the global effect of gait within the motor/premotor cortical mask) were considered for the subsequent analyses. Based on this analysis, among the 20 volunteers, 15 were ultimately selected. We removed the data of 5 participants from the final analyses due to: 1) abrupt head movements larger than 2mm in two subjects, 2) a prefrontal hypersignal during the recording of the EPI sequence in another subject, possibly due to a technical problem of the coil channels and 3) no activation in the primary motor cortex of the lower limb in the two remaining subjects (p<0.
Anatomical location of activated clusters Cortical and cerebellar activated clusters were anatomically labeled by overlaying the thresholded activation maps onto Brodmann and Automated Anatomical Labeling atlases using MRIcron software (http://www. nitrc. org/projects/mricron/). For the thalamus, basal ganglia and brainstem, the YeB atlas registered to the MNI152 anatomical template (1 mm isotropic) was used to localize activated clusters  [10].
Funding: Research was funded by the " Investissements d'Avenir " (investing in the future) program  ANR-10-IAIHU-06. This work was supported by a grant from the  "Regie Autonome des Transports Parisiens" (RATP)  and the grant  ANR  " Technologie de la Sante" [N˚ANR-GUI-AAP-05 ECOTECH ]. The contribution of JS was supported by an  ATIP-Avenir  grant to BL from the  Mairie de Paris. The sponsors of this study had no involvement in the study design or collection and interpretation of the data.
The abbreviations used are: NOS, nitric-oxide synthase; CHES, 2-(cyclohexylamino)ethanesulfonic acid; EPPS, 4-(2-hydroxyethyl)-1-piperazinepropanesulfonic acid; Fe II -NO, ferrous heme-NO complex; Fe III -NO, ferric heme-NO complex; H 4 B, (6R)-5,6,7,8-tetrahydro-L-biopterin; H 2 B, 7,8-di-hydro-L-biopterin; k r , reduction rate of the heme by the reductase (flavoprotein) domain of NOS; k d , dissociation rate of NO from the ferric heme-NO complex of NOS; k ox , oxidation rate of the ferrous heme-NO complex of NOS; k on , association rate for the binding of O 2 to the ferrous heme-NO complex; k off , dissociation rate for the ferrous heme-NO-O 2 complex; nNOS, neuronal nitric-oxide synthase; NOSoxy, oxygenase domain of nitric-oxide synthase; nNOSoxy, oxygenase domain of the neuronal nitricoxide synthase; iNOS, inducible nitric-oxide synthase; iNOSoxy, oxygenase domain of the inducible nitric-oxide synthase; eNOS, endothelial nitricoxide synthase; NOD, nitric oxide dioxygenation; DFT, density functional theory; PES, potential energy surface; PDB, Protein Data Bank.
Our results show that stabilization of the N-bound Fe III -N(O)OO Ϫ intermediate can actually be accomplished by a simple hydrogen bond, which is in good agreement with our kinetic data. Based on this result, we re-examined the crystal structure of the nNOS Fe II -NO complex, which in fact shows a H 2 O molecule directly above the Fe II -NO unit in the active site (Fig. 5B )  (34). In this structure, the H 2 O appears to be in hydrogenbonding distance of the oxygen atom of NO and one of the nitrogen atoms of L-Arg, which was co-crystallized in the active site. H 2 O molecules are also observed directly above the heme in the crystal structure of ferric iNOS ox (PDB code 1NOD)  (51) , again indicating that H 2 O molecules are commonly found in the active site of NOS, close to the heme, and in the needed position to interact with a peroxynitrite ligand.
Computational methods All DFT calculations were performed with the Linux version of the program Gaussian 09  (57). All geometry optimizations of the DFT models were performed at the UBP86/TZVP level, using the unrestricted formalism of Becke's 1988 exchange functional  (58)  and the gradient corrections of Perdew, along with his 1981 local correlation functional P86 (BP86)  (59). TZVP is a triple polarized basis set by Ahlrichs and co-workers  (60, 61). All calculations were performed using the polarizable continuum model as implemented in Gaussian 09 with water selected as the solvent. The NOS active site model used for all DFT calculations was generated by starting with the coordinates from the X-ray crystal structure of the Fe II -NO complex of nNOS (PDB code 2G6K)  (34)  and keeping only the coordinates of the Fe-NO protoporphyrin IX complex, Cys-415, Trp-409, and Gly-417.
Regulation of Fe II -NO oxidation in NOS correct initial wave function, with the S ϭ 1 ⁄ 2 heme Fe II -NO complex and 3 O 2 with antiparallel spins, an ON-OO distance of at least 3. 26 Å was found to be necessary. This distance was thus used as the starting point in the following PES scan calculations. The globin active site model used for the DFT calculations was generated from the crystal structure of a WT Mb Fe II -NO complex (PDB code 1NPF)  (62). Here, we used the coordinates of the Fe II -NO protoporphyrin IX complex, the axial His-93 and the distal His-64 residues. Both His-93 and His-64 were truncated to the relevant side chains and modeled as 5-ethylimidazole groups (see Fig. S3 ). The coordinates of the terminal carbon atoms of the 5-ethylimidazole groups and of the protoporphyrin IX propionic acids were frozen, and the rest of the coordinates were fully optimized.
Motion Capture An infrared light-emitting diode (LED) was attached to the chin to follow the movements of the lower jaw, a second reference LED was attached to the brow, and a third one was attached to the laryngeal prominence to follow swallowing events. The LEDs were attached using a double-sided adhesive strap. The positions of the LEDs were recorded using an optical motion capture system (Northern Digital Optotrak, Radolfzell, Germany). The recording of jaw movement during chewing was superimposed to correctly align with the EMG recording to better repair chewing events. It was also used to calculate the average shearing angle of the lower jaw used as a parameter for the chewing simulator. All the data gathered using these three methods were used as input parameters in the chewing simulator methods.
Volatile Compound Release Measurements The nosespace sampled online from a subject or the chewing simulator was drawn at 30 or 80 mL/min and flowed through a heated capillary transfer line (150 • C, 0. 53 mm i. d. ) into an ion-trap mass spectrometer Esquire-LC (Brucker Daltronique, Wissembourg, France) equipped with a modified APCI source  [35]. Aroma compounds were ionized by a 5-kV positive ion corona pin discharge. After checking the main ions for each volatile compound using single aroma compound solutions as references, the data were collected for detectable ions corresponding to protonated aroma compound molecules incorporated in the model cheeses (Table  3 ). The intensity of the signal was expressed in arbitrary units. In all cases, the room air and exhaled air by the subject or by the chewing simulator-before introducing the food sample in the mouth-was recorded and then was subtracted from the records obtained when chewing foods.
In Vivo Aroma Compound Release The oral physiological characteristics of the three subjects (named A, B, and C) were evaluated mainly to limit the decoupled oral functions of the chewing simulator to simulate mastication and salivation with realistic values. The obtained results with the three subjects were in agreement with  The hydrophobicity of the aroma compounds (Log P) was calculated with BIOVIA discovery studio software (version 2017, BIOVIA Corporate Europe, Cambridge, UK) according to Ghose et al. [35].
Statistical Analyses The data were processed using Stat SAS system release 6. 12 (SAS Institute Inc, Cary, NC, USA). Analyses of Variance (ANOVA) were performed at the level α = 0. 05 to study the variation in oral parameters (model including product, subject, and product * subject effects) and aroma compound release parameters (model including product, oral parameter, product * oral parameter). The means were compared using the Newman-Keuls multiple comparison tests.
Acknowledgments: We sincerely thank the  Plateform of Technology (Plateform3D, SAYENS, Le Creusot, France)  for developing the device and their technical help. We acknowledge  Jacques Maratray  ( CSGA, INRA, Dijon, France ) for developing the software to monitor the chewing simulator and  Christine Achilléos  ( URTAL, INRA, Poligny, France ) for the rheological measurements.
ACKNOWLEDGMENTS We thank  K. Willecke  for providing the Cx30 -/-mice. This work was supported by grants from the  European Research Council  (consolidator grant # 683154 ),  European Union 's  Horizon 2020 research and innovation program  ( Marie Sklodowska-Curie Innovative Training Networks, EU-GliaPhD grant  # 722053 ),  Agence Nationale de la Recherche  (grant # ANR-11-BSV4-021 ) and  INSERM  to N. R, from  French Research Ministry and Deutsche Forschungsgemeinschaft postdoctoral fellowships for U. P. and from L. F. C. E. to E. D.
Funding information Agence Nationale de la Recherche , Grant/ Award Number:  ANR-11-BSV4-021 ;  Deutsche Forschungsgemeinschaft  ;  European Research Council  , Grant/Award Number: 683154; French Research ministry; Ligue française contre l'epilepsie (LFCE); European Union's  Horizon 2020 research and innovation program  ( H2020-MSCA-ITN ), Grant/Award Number:  722053  ( EU-GliaPhD ).
Statistical Analysis The data were expressed as means with the standard deviation if the distribution was normal and medians with the interquartile (IQ) range if the distribution was non-normal. For the continuous variables, the groups were compared using the Student's t-test for the parametric variables and the Mann-Whitney test for the non-parametric variables. The categorical variables were compared using Fisher's exact test. The statistical analysis was performed using Stata 13. 0 software (Stata Corporation, College Station, TX, USA), and a p-value of <0. 05 was considered as statistically significant.
Hippocampal-dependent tasks We selected a set of three memory tasks based on their robust accuracy in identifying early AD: a Paired Associates Learning task ("PAL") similar to that incorporated in the CANTAB  (Sahakian, Morris, Evenden, Heald, Levy, Philpot et al. , 1988) , the Free and Cued Selective Reminding Test (FCSRT)  (Buschke & Grober, 1986; Grober & Buschke, 1987)  and the 4 mountains test ("4MT")  (Hartley et al. , 2007). We further describe each of these tasks and provide a brief overview of the evidence accumulated for (1) their relative specificity in identifying hippocampal damage and (2) their efficiency in identifying early AD. The PAL is a visuo-spatial associative learning task requiring participants to encode series of object-location associations, then to recall the correct locations when cued with the object.
We devised a PAL task similar to that reported by CANTAB, which was implemented with E-Prime 2. 0 software (Psychology Software Tools, 2013) as follows. In the study phase, participants were asked to carefully look at an array of 8 boxes, one of which would contain an abstract object, visible during 2 seconds. Subjects were instructed to memorize the location of the object. Immediately after the presentation of the object-location association, the test phase started. The same array of 8 empty boxes remained on the screen, with the object displayed at the centre. The subject had to use the mouse to click on the location (box) where the object was presented during the study phase. After a practice trial instructing the subjects that the number of object-location associations would increase along the test, the first study phase started.
Introduction The field of MRI studies is at a turning point owing to the recent availability of large data sets to researchers, including the UKB  (Miller et al. , 2016)  and HCP  (Van Essen et al. , 2013; Van Essen et al. , 2012b)  samples. These datasets promote not only the replication of previous findings, but also expand the range of phenotypes available for study (e. g. psychiatric symptoms and lifestyle factors). In addition, such data sets can offer insights into the brain markers that may be shared between phenotypes, helping to draw new links between brain and behaviour. Finally, these community samples can complement the typical case-control paradigm by identifying confounders of MRI analyses or by studying related traits (e. g. cognition domains relevant in Alzheimer's disease).
, 2018). We analysed two of the largest MRI datasets available (UKB [split into discovery N=9,888 and replication N=4,561] and HCP  [N=1,110] ) and considered a wide range of phenotypes spanning demographics, blood cell composition, diet, psychiatric and traumatic history, physical capacities or substance use. We have released our image processing and analysis software/scripts as well as all summary statistics to facilitate replication and re-use of the results.
Participants recruitment, inclusion and exclusion criteria The UKB participants were unselected volunteers from the United Kingdom  (Sudlow et al. , 2015). Participants who had participated in the baseline UKB data collection were invited to undergo the imaging study if they lived within travelling distance of the imaging centre. Exclusion criteria were limited to: presence of metal implant, recent surgery and health conditions problematic for MRI imaging (e. g. hearing, breathing problems or extreme claustrophobia)  (Miller et al. , 2016).
In addition, we extracted subcortical radial thickness and log Jacobian determinant (that measures surface deformation from a template, somewhat analogous to a relative surface area  (Roshchupkin et al. , 2016) ) for 27,300 vertices per hemisphere mapping 7 subcortical volumes (hippocampus, putamen, amygdala, thalamus, caudate, pallidum and accumbens)  (Gutman et al. , 2013). Overall, the imaging data used in the analyses comprised 654,386 vertex measurements per individual: 299,893 describing cortical thickness, another 299,893 for cortical surface area, 27,300 for subcortical thickness and 27,300 for subcortical curvature. For comparison with previous ENIGMA publications, we also extracted cortical thickness and surface area of 34 cortical regions delimited by the Desikan atlas  (Desikan et al.