dataesr/scientific-paragraphs-categorization huggingface dataset:
Included studies used various social and non-social cognition training programs, using desk-work or computerized exercises, in individual or group sessions. Neurobiological results seem independent from CR modalities. This observation is consistent with conclusions on the behavioral effect of different CR programs  (McGurk et al. , 2007). However, the variety of training programs and cognitive targets of CR have as a consequence an important discrepancy in the tasks used to assess neural processes. These tasks were selected to be coherent with the programs used, but their multiplicity hinders data comparability. Interestingly, in eight reports where symptomatology was assessed before and after therapy, no significantly greater improvement was observed in the CR group when compared to control groups.
MALDI-TOF-TOF MS spectra were acquired with a MALDI-TOF⁄TOF 5800 mass spectrometer (Applied Biosystems) using linear mode acquisition. External calibration was performed using unmodified α-syn, Aβ42 and HTTExon1. Acquisition and data analysis were performed using the Data Explorer software from Applied Biosystems. The MALDI-TOF mass spectra of Alexa-555-labeled α-syn, Aβ42 and HTTExon1 are shown in Fig. 1a  (from left to right). The spectra show that the fractions of labeled α-syn, Aβ42 and HTTExon1 are 60, 20 and 25 %, respectively with, on average, one Alexa-555 per 1, 5 and 4 molecules of α-syn, Aβ42 and HTTExon1, respectively. The nature of the assemblies was assessed using a JEOL 1400 transmission electron microscope following adsorption onto carbon-coated 200-mesh grids and negative staining with 1 % uranyl acetate.
Acknowledgments We thank  BA Barres  for the gift of the Wld S mouse line. We acknowledge the expert technical assistance of  Karine Madiona  and  Virginie Redeker  for mass spectrometry measurements. This work was supported in part by research funding from  Novartis Institutes of Biomedical Research  and grant  1DP1OD019046  from the  National Institute of Health  (MB, GB, ADG). LB and RM were supported by  Agence Nationale de la Recherche  ( JPND-NeuTAR-GETs - ANR-14-JPCD-0002-02 ), the  Centre National de la Recherche Scientifique  and a ' Coup d'Elan à la Recherche Française ' award from  Fondation Bettencourt Schueller. GB is supported by a  HHMI predoctoral fellowship  and a  Stanford graduate fellowship.
25-0. 75%. Ca 2ϩ -triggered exocytosis was probed after a 10 min infusion into IHCs of 20 M latrunculin A, 20 M cytochalasin D, or 100 M phalloidin via the patch-pipette. For control cells, the intracellular solution contained the corresponding DMSO concentration (0. 5% for latrunculin A and cytochalasin D, 0. 25% for phalloidin, and 0. 75% for latrunculin A plus phalloidin). Control and drug-treated cells were probed over the same time frame for better comparison. Except for the exocytosis amplitude plots against the duration of stimulation (see Fig. 4 ), all of the controls were pooled together. An EPC-10 amplifier (HEKA Elektronik) controlled by Patchmaster software (HEKA Elektronik) was used for all measurements as described previously  (Nouvian et al. , 2011). Membrane capacitance jump (⌬C m ) was estimated as the difference of the mean C m over 400 ms after the end of the depolarization (the initial 250 ms were skipped) and the mean prepulse capacitance (400 ms).
The following clinical trial in patients with PD (http://clinicaltrials. gov/show/NCT00159172) did not demonstrate similar improvements and was interrupted. So, it is not clear to us what the authors are referring to when they refer to a "renaissance of Parkinson's disease research. " Computational (in silico) models can contribute to explore the effects of DBS in PD, and there are today four main modeling approaches including single-compartment spiking neuron models, phase oscillator models, multicompartmental spiking neuron models, and more recently, neural field models. Each type of model has its own assumptions, strengths, limitations, and advocates (for details, see  Modolo et al. , 2010). In the human brain, compensatory mechanisms and plasticity are fundamental issues and biologically realistic models associated with clinical studies conducted in human subjects by design integrate these issues.
Each well was precoated with ECM gel (Sigma-Aldrich, E1270). Briefly, 150 μL of ECM gel was added into a 4-well plate and allowed to solidify for 1 h at 37 °C. Then, cells were incubated with medium containing 10% of FBS and allowed to adhere for 1 h after which the different stimuli were added. Tube formation was examined by phase-contrast microscopy (MOTIC AE21) after 24 h and the average length of capillaries was quantified using ImageJ software. In vivo ECMgel plug assay. All studies involving mice were in accordance with European guidelines and with the agreement of the regional veterinary services (Authorization no. C49063, 11/22/2011). Six week-old male Swiss mice were used. Primary mouse EC were cultured in a 25 cm 2 flask and were treated with DMSO or DEET for 24 h in the absence or presence of pFHHSiD (10 -7 M).
Images were acquired each second for 10 min using an X20 objective. Results are expressed in mean ± SEM of the ratio of maximal fluorescence divided by basal fluorescence. Docking. Primary sequence of M3 receptors are retrieved from Uniprot website (www. uniprot. com). Crystal structures of the muscarinic receptors are retrieved from the Protein Databank at www. rcsb. org. Sequence alignment was performed with ClustalW 29 as implemented at https://npsa-prabi. ibcp. fr/. Surflex-Dock software  30  as implemented in Sybyl-X 2. 1 package (Tripos, MO, USA) was used for the docking simulation. The docking mode was GeomX with default options to have maximum accuracy. Prior to docking, the interaction cavity was defined with a "protomol" which represents the "negative of the cavity" in terms of acceptor, donor and hydrophobic groups.
The protomol was generated according to the putative allosteric site defined by aligning 3D structure of M3 (PDB id: 4DAJ)  31  with M2 (PDB id: 4MQT)  32. To generate the protomol, these options were used: proto_thresh = 0. 5 and proto_bloat = 0. Parameters used for the docking calculation were those by default: no flexibility on the protein, additional starting conformations per molecule multistart = 6, expand search grid grid_bloat = 6 Å, maximum conformations per fragment maxconfs = 20, maximum number of rotatable bonds per molecule maxrot = 100, allow ring flexibility in the molecule (+ring), soft grid treatment (+soft_box), pre-and post-docking minimization (+premin & +remin), fragment molecule (+frag), activate spin alignment method (+spinalign), density of search spindens = 9 for exhaustive accuracy, number of spins per alignment nspin = 12.
53 × 10 -8 ± 0. 28 × 10 -8 and 2. 93 × 10 -8 ± 0. 15 × 10 -8 M, p < 0. 05, for 10 -8 M and 10 -5 M DEET, respectively (Fig. 4c ). Moreover, DEET modulated the Ca 2+ response induced by 10 -8 M of carbachol, which corresponds to EC 50 of carbachol in these conditions, in a window of concentrations beginning at 10 -8 M and extended to 10 -7 M (Fig. 4d ). These results suggest that DEET, via allosteric modulation of the M3 receptor, increases the carbachol-induced calcium rise. To confirm this hypothesis, docking assay was performed through a docking model of the M3 receptor derived from the structure of PDB (PDB id: 4DAJ 31 ) (Fig. 4e, f ). As the homology of rat and human M3 receptors is very high (98% of homology, cf. sequence alignment in Supplementary Figure  S3 ) and because the non-conserved residues are located outward of the receptor, the 4DAJ structure was used as our docking model.
The rat M3 receptor (PDB id: 4DAJ  31  ) showed a well-defined orthosteric site and revealed the presence of a potential allosteric site (Fig. 4e, f ) as compared to the crystal structure of M2 receptor  32. Thus a docking study was performed to explore the possibility that DEET binds at this putative allosteric site instead of the orthosteric site. The «best pose» ranked by the affinity score had a calculated affinity -Log10(Kd) of 5. 04 and 4. 35, respectively, for the orthosteric and allosteric site (Fig. 4e, f ). In the same manner, a binding assay   was performed to confirm that DEET does not act on the orthosteric site of M3 receptor. As shown in Table  3 , for concentrations ranging from 10 -11 M to 10 -4 M, DEET was not able to displace  3  [H] 4-DAMP on M3 receptor.
Acknowledgements The authors wish to thank  Dr Gary Willars  ( Department of Cell Physiology and Pharmacology, University of Leicester, United Kingdom ) and also  Pr Catherine Passirani  and  Dr Anne Clavreul  ( UMR 1066 Inserm, France ) for their generous gifts of HEK/M3 and U87MG cell line, respectively. They also wish to thank  Dr Jérémie Riou  ( UMR 1066 Inserm, France ) for his kind help in statistical analysis and  Isabelle Brunois Debu  and  Jessica Faulkner  for the reading of this manuscript.
They were instructed not  Statistical comparisons between groups were performed on a voxel-by-voxel basis t statistics, using "two-sample t-test" design of the SPM8 generating SPM (t) maps. We investigated brain areas with reduced FDG-uptake, a stringent level of significance of p < 0. 05 corrected for multiple comparisons (SPM family wise error-FWE) was adopted with an extent threshold of 100 voxels. For visualization the significant voxels were projected onto the 3D rendered brain or a standard MRI template allowing anatomic identification. A MNI to Talairach coordinates conversion was done using Yale Bioimage Suite software (http://www. bioimagesuite. org). On subsequent analyses by lowering p-values successively, we searched for the brain area with the most severe reduced FDG-uptake.
) and 5 µМ of each primer. Primers were designed using NCBI/Primer-BLAST and tested with FastPCR 4. 0. 13 (PCR Team) software for the "Primer quality" parameter to exceed 70. Their sequences were as follows: TRPA1: 5'-TCCT-GTGAAGCGCTGAATGT-3' (F), 5'-ACAGCTATGTGAAGGGGTGC-3' (R). Beta-actin (Actb): CTGTGTG-GATTGGTGGCTCT (F), GCTCAGTAACAGTCCGCCTA (R). Quantitative PCR (qPCR) was carried out on 7500 Fast Real-Time PCR System (Applied Biosystems) according to the program: 50 cycles of 95°C for 15 s and 60°C for 60 s followed by a melting curve from 60°C to 95°C with 1% steps. Analysis of the results was performed with 7500 Software v2. 0. 5 (Applied Biosystems). The data on TRPA1 expression was normalized to beta-actin expression and averaged for each group of animals.
The following primary antibodies and dilutions were as follows: alpha-tubulin-FITC (Sigma); Microtubule Associated Protein -2 (Sigma; MAP-2, mouse or rabbit monoclonal (1/500); beta3-tubulin (Sigma; mouse monoclonal 1/500); cytochrome c (Cell Signaling 1/300). Species-specific secondary antibodies coupled to Alexa 350, 488, or 555 were used (1/500, Life Technologies,) to visualize bound primary antibodies. Image Acquisition. Images were acquired with an Axio-observer Z1 (Zeiss) fitted with a cooled CCD camera (CoolsnapHQ2, Ropert Scientific). The microscope was controlled with Metamorph software (Molecular Imaging) and images were analyzed using ImageJ software (ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA). Quantification of axonal degeneration and neuronal survival.
Acknowledgements This work was supported by a grant from the  European Commission: MicroDEG, ERA-NET Neuron   JTC2012  "Novel Methods", http://www. neuron-eranet. eu/en/317. php. French ANR grant "PrionSensiTNF :  Blan-1312-02" 2011-14  » and " PRIONTRAF "  ANR-09-BLAN-0122 , and d by  Association Française contre les Myopathies-Téléthon. We thank  Vanessa Tan  for careful revision and proof reading of the manuscript.
ACKNOWLEDGMENTS H. N. T. , M. P. , A. A. Z. , J. -L. S. , and  J. -R. H. acknowledge financial support from the  ANR GAMBIT project ,  Grant  No. ANR-13-BS10-0014  of the  French Agence Nationale de la Recherche , and the  International project of Scientific Cooperation with Vietnam  ( CNRS PICS 6457 ). We acknowledge the  Dr. T. X. Tinh  for the synthesis of individual nanotubes. J. -C. B. , A. A. , A. S. -M. , F. V and N. D. F. acknowledge financial support from  ANR  programme  P2N  under Contract No. ANR-11-NANO-025. V. N. P. acknowledges financial support from Project  316309 :  INERA -"Research and Innovation Capacity Strengthening of ISSP-BAS in Multifunctional Nanostructures. "The TEM studies were conducted at the  Laboratorio de Microscopias Avanzadas, Instituto de Nanociencia de Aragon, Universidad de Zaragoza ,  Spain.
Some  of the research leading to these results has received funding from the  European Union Seventh Framework Programme  under Grant Agreement No. 312483-ESTEEM2  ( Integrated Infrastructure Initiative -I3 ). R. A. gratefully acknowledges the support from the  Spanish Ministerio de Economia y Competitividad  ( FIS2013-46159-C3-3-P ) and from the  European Union   H2020 program ETN project  " Enabling Excellence " Grant Agreement No. 642742.
-Results The simulations are performed using the Python language and mpi4py, a full-featured Python bindings package for OpenMPI 1. 4 that we deployed on the Rhenovia Pharma cluster composed of DL380 HP Servers, equipped with 256 processing cores clocked at 2. 5 GHz and with 128 Go of RAM. The GPU code was developed with the parallel computing platform and programming model provided by NVIDIA: CUDA 6. 0. The compilation of GPU code was performed on a NVIDIA Kepler Tesla K20c board, with compute capability 3. 5, running at a frequency of 706 MHz and equipped with 5120 MB of GDDR5 memory. We define the acceleration of the algorithm as the ratio between the sequential resolution time and the parallel resolution one. This parameter is a simple measure of the gain between two methods of resolution.
1A ). Complex III is a main site of proton gradient generation, thus of energy conservation. It is also a main site of reactive oxygen species (ROS) production. ROS are involved in signaling pathways that coordinate both the nucleus and mitochondria to drive beneficial homeostatic responses, but they can also damage cellular components that induce cell death. In the human population, the mt-cyb exhibits a high level of variation. Over 410 missense changes from the Homo sapiens mitochondrion complete genome reference sequence (rCRS: GenBank NC 012920. 1) have been reported (http://mitomap. org) and 90 in MSeqDR-LSDB (https://mseqdr. org/MITO/genes/MT-CYB), with some overlap between the various databases. While a number of these variations are likely to be silent, some variations, especially those located in regions involved in the catalytic activity and inhibitor binding, may induce subtle changes in complex III function.
Data Collection For each human mutation under investigation, information on the prevalence and heteroplasmy level in normal/healthy 934  HUMAN MUTATION, Vol. 37, No. 9, 933-941, 2016  and pathologic tissues was obtained from the following five databases: MITOMAP (http://www. mitomap. org/MITOMAP), HmtDB (http://www. hmtdb. uniba. it/hmdb/), mtDB (http://www. mtdb. igp. uu. se/), and MSeqDR-LSDB (https://mseqdr. org/ MITO/genes/MT-CYB)) and an in-house glioblastoma (GBM) database  [Lloyd et al. , 2015]. Known genotype-phenotype correlations were explored using OMIM (http://www. omim. org/).
Spectrum of Human mt-cyb Variations Analyzed in Yeast The 22 human polymorphisms chosen for analysis in yeast are presented in Table  1. With the exception of one variation (m. 15048G>C), reported in a single GBM-patient  [Lloyd et al. , 2015] , all variations were reported as polymorphisms in one or more of the mitochondrial databases. Eleven polymorphisms have no known disease association: m. 15122A>G, 15147C>T, 15171G>A, 15191T>A, 15258GA>AG, 15048G>C, 15404G>C, 15138A>G, 15152G>A, 15153G>A, and 15502C>G, and were rare, being found in typically 10 cases or less in the normal/healthy human population. Nine polymorphisms had one or more reported disease associations: m. 15140G>A, 15164T>C, 15257G>A, 15258A>G, 14798T>C, 14841A>G, 14858G>A, 15047G>A, and 15500G>A. The top three most frequently recorded polymorphisms in normal healthy cases, were also the most frequently recorded in disease-associated cases (in descending order of patient frequency): m.
14798T>C, 15257G>A, and 15047G>A. The individual mt-cyb variations were associated with one or more of the following type of disorders: cardiological (e. g. , cardiomyopathy and Noonan syndrome); neurological (e. g. , LHON, Parkinson's and schizophrenia); metabolic (e. g. , diabetes); and cancers (e. g. , breast, thyroid, GBM, pituitary adenoma, oral squamous cell carcinoma, and lung), there were no genotypephenotype correlations in the OMIM database, with the exception of m. 15257G>A, which is associated 9% of LHON cases  [Heher and Johns, 1993; Johns and Neufeld, 1993; Johns et al. , 1993]. The polymorphisms were chosen on the basis of the location of the residues in the structure of complex III. Nine variations  (at positions 126, 132, 134, 140, 142, 149, and 171)  are located in or nearby the Q o site.
Mutations Within or Nearby the Q o Site Influence Atovaquone Sensitivity Atovaquone (used in combination with proguanil, and marketed as Malarone R ) is a popular prophylactic drug that also shows high efficiency in the treatment of uncomplicated Plasmodium falciparum malaria. The compound is also used to treat Pneumocystis jirovecii pneumonia, Toxoplasma gondii toxoplasmosis, and other infections. Atovaquone inhibits complex III by binding in the Q o site, as revealed by the resolution of the atomic structure of yeast complex III with bound atovaquone (PDB code 4PD4)  [Birth et al. , 2014]  and by the Q o site location of point mutations found in the mt-cyb of atovaquone-resistant parasites  [Hill et al. , 2003; Mather et al. , 2005]. The complex III of the malaria parasite-and yeast-is highly sensitive to atovaquone, whereas the mammalian complex III is naturally more resistant to atovaquone, which is expected of an antimalarial compound used to treat humans.
Statistical Analysis Behavioral data were analyzed by one-way or two-way factorial analyses of variance, followed when adequate, by post hoc (Dunnett test) comparisons using the least significant difference test, with a p < 0. 05 statistical threshold. Data were represented as mean ± standard-error of the mean. For correlation analyses, the Spearman's correlation coefficient, R, was determined. For immunohistochemistry, in so far as no difference was found in the naïve condition, data were analyzed similarly using the rough number of immunopositive cells , with a p < 0. 05 statistical threshold.
14 ± 7. 9; NS in FIGURE 4 | (A) Effects of aging on SCM scores (Experiment 2). As can be seen, 14 months-old middle-aged mice exhibited a significant reduction of SCM score as compared to 5 months-old young-adult mice. Between-groups difference: * * * p < 0. 001. (B) Effects of aging on pCREB immunoreactivities. Counting was made in the PFC, dCA1, vCA1, medial septum, dorsal striatum, and BLA. No significant differences were observed between the groups in all brain areas in naïve condition (data not shown). Middle-aged mice showed reduced behavioral testing-related pCREB immunoreactivities in the dCA1, vCA1, and medial septum as compared to young adult mice. In contrast, a significant increase of pCREB was observed in the BLA in middle-aged animals, as compared to young ones. Results are expressed as mean number of positive pCREB nuclei per mm 2.
Given that a majority of cellular functions are regulated at several levels, we studied the oscillations of hepatic metabolites as a clear output of the observed gene expression or other regulatory modifications. Metabolite abundance changes are expected to reflect modifications in the intricate metabolic activities from gene expression to protein activity. We found that metabolites oscillated in both GF and SPF mice but that their rhythmic abundances largely differed between these mice. Recent work with a comprehensive dataset of over 500 metabolites highlighted the coordinate clock-controlled oscillation of many metabolites comprising the amino acid, carbohydrate, lipid, nucleotide, and xenobiotic metabolic pathways  38. We found that this coordination was severely altered in the GF mice, which was anticipated from the disrupted regulation of liver clock gene function.
The arrays were scanned with a GeneChip ® Scanner 3000 7G (Affymetrix). Normalized expression signals were calculated from Affymetrix CEL files by the Robust Multi-array Average algorithm, using the Affymetrix Expression Console Software (version 1. 3. 0. 187). Hybridization quality also was assessed with Expression Console Software. All data were analysed using R (www. r-project. org). Microarray data analysis was conducted using Bioconductor packages (www. bioconductor. org, v 2. 12,  50  as described in GEO entry GSE71628). A model was fitted using the limma lmFit function  51. A correction for multiple testing was then applied using Benjamini-Hochberg (BH) procedure for the false discovery rate (FDR)  52. ProbeSets with (BH) adjusted P values ≤ 0. 01 were considered to be differentially expressed between conditions.
In this representation, each cell contains the correlation between two genes and the corresponding p-value. The tables are color-coded by correlations according to the color legend (red for positive correlations and green for negative correlations). We colored in grey the cells corresponding to non-significant correlations (p-value threshold of 5%). For real-time quantitative polymerase chain reaction (qPCR), total RNA samples (2 μ g) were reverse-transcribed using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Primers for SYBR Green assays are listed in Supplementary Table  S7. Amplifications were performed on an ABI Prism 7300 Real Time PCR System (Applied Biosystems). qPCR data were normalized by TATA-box binding protein mRNA levels and analysed with LinRegPCRv2012.
2  56. Statistical analyses for qPCR data were performed with Student's t-test at each time point between SPF and GF mice. In case of unequal variances between the two groups, the Wehch's two sample t-test was used. P values were corrected for multiple testing using BH procedure and FDR < 5% threshold is considered as significant differences. Metabolomic analyses by 1 H nuclear magnetic resonance (NMR) spectroscopy. See Supplementary Methods online.
Multivariate analysis of metabolomic data. The pre-processed NMR data were imported into Simca-P + software (version 13. 0. 2, Umetrics AB, Umea, Sweden) for multivariate statistical analysis. First, principal component analysis was used to detect intrinsic clusters and outliers. Then, partial least squares-discriminant analysis (PLS-DA) was used to study the relationship between time and NMR spectral data. Seven-fold cross validation was used to determine the number of latent variables to include in PLS-DA models. R 2 (proportion of explained variation) and Q 2 (predictive ability) values were used to assess PLS-DA model validity. Typically, a valid model has R 2 > 50% and Q 2 > 0. 4. A permutation test (200 iterations) was used to assess PLS-DA model robustness. Discriminant NMR buckets were selected using the very important variable (VIP) value, a global measure of the influence of each variable on the PLS-DA model.