dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion In this paper, we showed that the current software package provided with the SpiNNaker platform was insufficient for certain applications requiring temporal resolution below a millisecond. To overcome this limitation, we introduced new software tools and models allowing to go beyond the millisecond barrier and reach microsecond precision. To assert these new functionalities, we needed information about the timing involved at the level of SpiNNaker's fabric itself. We characterized the timing requirements of the hardware on one hand and of the software API on the other. This allowed us to fully characterize our implementation and provide insights about its computational limits for an user wanting to simulate a given network. We then demonstrated that our newly introduced architecture can simulate networks implementing sub-millisecond tasks and using plasticity by achieving, in realtime, sound localization, and sound patterns extraction with realistic spike trains.
Acknowledgments The research leading to these results has received funding from the  European Union Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement n • 604102 (HBP). This work was also performed in the frame of the  LABEX LIFESENSES  [ ANR-10-LABX-65 ] and was supported by  French  state funds managed by the  ANR  within the  Investissements d'Avenir programme  [ ANR-11-IDEX-0004-02 ]. The  SpiNNaker  project is supported by the  Engineering and Physical Sciences Research Council (EPSRC)  under Grant  EP/G015740/01. The work proposed in this paper results from discussions at the Telluride Neuromorphic Cognition Engineering Workshop; the authors would like to thank the sponsors and the organizers.
Acknowledgments: We acknowledge partial financial support of the  Région de Franche-Comté  (Convention  2013C-5493 ), the  European  project  PHOCUS  ( FP7  Grant No. 240763 ), the  Labex ACTION program  (Contract No. ANR-11-LABX-01-01 ), and  Deployment S. L. LG  acknowledges financial support from the  Faculty for the Future Program of the Schlumberger Foundation.
Statistical analysis. GraphPad Prism 6 (GraphPad Software) was used for data analysis and graphic representation. All values are reported as mean Ϯ SEM (unless specified in the legend). Two-group experiments were analyzed with the nonparametric Mann-Whitney test. One-way ANOVA and Bonferroni multiple-comparison post-tests were used to compare the means of multiple groups. One-way ANOVA and Dunnett's post-tests were used to compare the means of multiple groups to a control value. The p values are indicated in the figures.
Observations were made using the 60 × objective (oil immersion NA 1. 25). Cells were analyzed by acquiring axial z stacks of confocal images (8 μm from the base to the top in 0. 5-μm steps). Image processing was done using ImageJ software  [28]. Residual blurring was removed by spatial deconvolution: Point-Spread Function (PSF) was calculated using the ImageJ plugin PSF Generator  [29] , and deconvolution properly speaking was carried out using the Richardson-Lucy algorithm used with the Deconvolution Lab ImageJ plugin  [30]. The latter two freeware are available from the EPFL (Ecole Polytechnique Fédérale de Lausanne [Biomedical Imaging Group]), Lausanne. Switzerland. « Fire » look-up table was used in merged representations to improve visibility of the NRP-1 labeling, without altering linearity of the signal.
Secondly, to confirm the role of NRP-1 in cell invasion, we analyzed the effect of the anti-NRP-1 blocking antibody on PTN-induced invasion of PC3 cells. Accordingly, the anti-NRP-1 antibody inhibited PTN-induced PC3 cell invasion in a dose-dependent manner, and total inhibition was achieved at 5 μg/ml (Figure  6B ). The nonimmune IgG control had no effect on PTN-induced PC3 cell invasion (data not shown). We next evaluated NRP-1 involvement in PTN-mediated migration of endothelial cells. As shown in Figure  6C , without Microtiter plates were coated with rNRP-1 or BSA and incubated with increasing concentrations of PTN (0 to 8 μg/ml). Bound PTN was detected by ELISA-based measurement of streptavidin-HRP staining. The results represent the means of three experiments. PTN, the silencing of NRP-1 expression did not alter HUVEC migration.
Study selection and data extraction Electronic databases MEDLINE, EMBASE, SCOPUS, Science Direct, ISI Web of Science, and CINAHL were searched from January 1966 to April 2014 for English language papers. We used the same search strategy as a recent systematic review to identify neuropathic pain  48  and combined this with broad search terms for "genetic studies. " These search terms are listed in Supplementary Digital Content 1 (available online as Supplemental Digital Content at http://links. lww. com/PAIN/A147). We excluded studies in which: (1) it was not possible to distinguish between participants with neuropathic pain and those with nonneuropathic pain (including mixed pain conditions); (2) the pain was cancer related; (3) the condition was not currently defined by the IASP as neuropathic pain (complex regional pain syndrome, temporomandibular disorders, migraine, chronic widespread pain [CWP], and fibromyalgia)  26  ; or (4) the study was in children.
Database searches were conducted by one author (O. v. H. ). Article titles and then abstracts were reviewed for possible inclusion by 2 authors (O. v. H. and B. H. S. ), before full-text versions of the remaining articles were reviewed and the final selection was confirmed. We extracted data on: (1) study characteristics (country, sample population, study design); (2) phenotyping methods described; (3) sample size (cases and controls); (4) the specific neuropathic pain condition(s) under study; and (5) genetic factors investigated. We differentiated between "brief" and "detailed" phenotype descriptions to give an indication of the level of detail provided by the authors and whether or not it allowed replication by other researchers. For example, "Clinical examination by pain specialist"  15  was regarded as "brief," whereas "Clinical examination: straight leg raising test, manual testing of motor and sensory defects of the lower extremities concordant with magnetic resonance imaging findings,"  35  was regarded as "detailed.
Procedure The meeting was held in Versailles, France, from June 12 to 13, 2014, and consisted of 18 experts, identified by NeuPSIG based on their experience in the fields of pain phenotyping, epidemiology, and/or pain genetics. Represented disciplines included neurology, anaesthesiology, pain medicine, palliative care, primary care, basic neuroscience, and genetics. Activities on the first day included: (1) describing the aims of the meeting and defining the questions that were to be addressed; (2) presentation of data from the systematic literature review and the results of the first 2 rounds of the Delphi survey; and (3) short presentations by panelists on the differences and commonalities between "phenotyping" (what information to collect and how to collect it) to collect vs "phenomics" (which pain phenotypes should be used in genetic association analysis), phenotyping of complex diseases, phenotyping by questionnaires, phenotyping by clinical examination, phenotyping using standard and dynamic QST, and phenotyping for clinical trials.
The first two analytical measurements were chosen as a very simple way to evaluate how the pitch and durational content of the instances change with parameter variation. For instance, as our model is deterministic (no stochastic process is involved), one would expect that the more voices the canon has, the higher is the mean-frequency and the bigger is the last onset, showing a linear relationship. That being the case, the Model Xplorer functions as a way of validating the consistence of the model construction, each parameter variation reflecting a 'reasonable' equivalent effect on the piece's features. On the other hand, the measurements of the 'cognitive-sonance' module should show a less linear relationship with parameter variation. This analytical function is part of a library developed for OpenMusic called Sonic Object Analysis Library (SOAL).
Its description is given as the following: A vector from "maximum consonance" to "maximum dissonance", evaluates the contiguous dyads of the input file (s) on the basis of a weighting of their relative dissonance, according to a pre-defined cognitive/cultural background, and extracts an average value for the whole MIDI file, its "sonance" rate. (Guigue 2010). In other words, "sonance" indicates how consonant or dissonant a musical file could be perceived according to a weighted table of intervals given as an input based on "cognitive or cultural  'Generate-instances' passes every parameter value in a loop to the subpatch called 'ModelandAnalysis', which contains the functional implementation of the model and the analytical modules. This process could take hours or days to calculate; some information about the current state and results is printed in the OpenMusic console at each step.
5 ) in the presence of D1R agonist which may reflect an adaptive change in subunits composition of NMDARs when 5-HT1ARs are lacking and this effect could favor LTD induction. It is striking that in our experiments in 129/Sv mice, activation of D1Rs impaired LTD induction. This result paralleled a recent study where a high level of DA has been reported in the rat PFC to impair LTD induction through D1Rs activation  [28]. The specific D1Rs activation in these experimental conditions is corroborated by many other observations  [28, 73]  and supported by the high affinity of D1Rs for DA (National Institute of Mental Health Psychoactive Drug Screening Program database), however the mechanism involved in the impairment of the LTD induction is not yet elucidated. It is well known that D1Rs activation recruits G s -dependent cAMP pathway that lead to PKA-dependent phosphorylation of AMPAR and thereby modulating synaptic plasticity  [24, 74, 75].
Immunoblotting Samples (40 μg proteins of cell lysates) were prepared for electrophoresis by adding NuPAGE Gels were transferred to nitrocellulose membranes using the iBlot 1 Dry blotting system set to program 20V for 7 min. Membranes were washed for 10 min in Tris-buffered saline/Tween (TBST: 20 mM Tris-HCl, 150 mM NaCl, pH 7. 5, 0. 05% Tween 20) and blocked 2 hours in TBST containing 5% bovine serum albumin (BSA). Blots were incubated with primary antibody in blocking buffer overnight at 4°C. Antibodies used were rabbit anti-Beclin-1 (1:500), rabbit anti-p62/SQSTM1 (1:500), rabbit anti-LC3 (1:500). Membranes were washed twice with TBST and then incubated with the HRP-conjugated secondary anti-rabbit antibody (1:1,000) during 1 hour at RT. Membranes were washed again and exposed to the chemiluminescence Luminata Forte western HRP substrate (Millipore, St Quentin en Yvelines, France) followed by signal capture with the Gbox system (GeneSnap software, Syngene, Ozyme distributor).
After 2 washes in TBST, membranes were probed with mouse antibody against β-actin (1:100,000) overnight at 4°C. They were then washed with TBST, incubated with HRP-conjugated secondary anti-mouse antibody (1:1,000) for 1 hr, exposed to the chemiluminescence Luminata Classico western HRP substrate and signals were captured. Automatic image analysis software was supplied with Gene Tools (Syngene, Ozyme distributor). Ratios protein/β-actin were calculated and shown in the corresponding figures.
Plate were put on the magnetic support (microbead stayed around the well) then fluid was removed by using a multichannel pipette with very thin tips for not touch the periphery where are the beads. Each well was washed twice with 200 μL of wash buffer with plate shaker at 450 rpm during 2 min at RT. 25 μL of biotinylated detection antibodies were added per well, and plate were incubated in dark room at RT on a plate shaker at 750 rpm during one hour. Then 25 μL/well streptavidin-phycoerythrin solution was added, and plates were incubated on a plate shaker at 750 rpm during 30 min at RT, protected from light. Plates were washed twice with 200 μL of wash buffer. Microbeads were resuspended in 150 μL/well of sheath fluid on plate shaker at 450 rpm for 5 min at RT. Assessment was made using luminex-200 1 instrument and xPONENT 1 software.
Statistical analysis All statistical analyses were carried out using the SAS 9. 2 software package (SAS Inc, Cary, NC, USA). Inflammatory and autophagic factors are described by mean and standard error of the mean (SEM), clinical variables are summarized by mean and standard deviation (SD). Intra group comparisons between DMSO and C16 conditions were performed using non parametric Wilcoxon matched-pairs signed rank test. Biological and clinical values measured at D0, M12 and M24 for AD patients and those measured in three experimental conditions (serum medium, serum free medium and 20μM Aβ42 in serum free medium) for healthy patients were compared by ANOVA for repeated measures followed by post-hoc Sheffe's test if necessary. Non parametric Friedman's test was also used. The correlations between the levels of inflammatory factors, the rate expression of autophagy markers and cognitive scores were investigated with the Spearman correlation coefficient (rho) calculation.
The inflammatory effect on autophagy was initially reported at the periphery in various diseases including Crohn's disease  [33] [34] [35] , which stimulated our research to modulate the inflammatory environment of PBMCs by treating the cultures with the C16 compound, known as a specific inhibitor of PKR with antiinflammatory properties  [25, 26]. In this clinical study, we had the opportunity to monitor the impact of inflammation on autophagy PBMCs at baseline and after 12 and 24 of follow-up. B, F, G  and H ) and LC3 II (B, I, J and K) in PBMCs of AD patients at the Day of inclusion (D0) and after a follow-up at 12 months (M12) and 24 months (M24). PBMCs were isolated from blood and cultured either with 1 μM C16 or its vehicle (0. 8% DMSO) for 48hr as described in method section. Semi-quantitative analysis of immunoblot was performed using Gene Tools software (Syngene, Ozyme France).
National Institute of Neurological and Communicative Disorders and the Stroke Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria. Inclusion criteria were as follows: Mini Mental-State Examination (MMSE) scores from 16 to 25, and patient naive of symptomatic treatment for AD (cholinesterase inhibitors and memantine). Exclusion criteria were: inflammatory disease, chronic or acute infection, and neoplasia, treatment with non-steroid anti-inflammatory drug or corticosteroids and C-reactive protein (CRP) level > 10 mg/L. The institutional review board ('comité de protection des personnes Ouest 3') approved the study, and patients signed a written informed consent. The study was declared on ClinicalTrial. gov. NCT01351142.
National Institute of Neurological and Communicative Disorders and the Stroke Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria. Inclusion criteria were as follows: Mini Mental-State Examination (MMSE) scores from 16 to 25, and patient naive of symptomatic treatment for AD (cholinesterase inhibitors and memantine). Exclusion criteria were: inflammatory disease, chronic or acute infection, and neoplasia, treatment with non-steroid anti-inflammatory drug or corticosteroids and C-reactive protein (CRP) level > 10 mg/L. The institutional review board ('comité de protection des personnes Ouest 3') approved the study, and patients signed a written informed consent. The study was declared on ClinicalTrial. gov. NCT01351142. 1 4-20% Tris-Glycine gels, NuPAGE 1 4X LDS sample buffer, NuPAGE 1 sample reducing agent (10X), Novex 1 Tris- Glycine SDS running buffer and NuPAGE 1 antioxidant, iBlot 1 transfer stack regular (Nitrocel- lulose) from Gibco-Invitrogen (Fisher Bioblock Scientific distributor, Illkirch, France); the imi- dazolooxindole compound C16 from Merck Chemicals Calbiochem 1 (Merck Millipore, Billerica, Massachusetts, USA).
HRMAS 1 H-NMR spectroscopy NMR spectra were acquired on a Bruker Avance 700 spectrometer (proton frequency 700. 09 MHz) equipped with a standard double resonance ( 1 H-13 C) 4 mm HRMAS probe head with z gradient. Samples were spun at 3500 Hz. A Bruker Cooling Unit was used to maintain the samples at 283 K throughout the process. One-dimension (1D) NMR spectra were acquired using a Carr-Purcell-Meiboom-Gill pulse sequence with presaturation of the water signal during the 2 s relaxation delay, a 1 ms echo time, and an acquisition time of 1. 36 s. A total of 32 K data points with 512 scans were acquired using a spectral width of 8403 Hz, for a total acquisition time of ϳ30 min. All free induction decays were multiplied by an exponential function equivalent to a 0. 3 Hz line-broadening factor before Fourier transformation.
Metabolite quantification Quantification was performed with jMRUI version 5. 0 software package  (Stefan et al. , 2009)  (http://www. mrui. uab. es/mrui/) using the QUEST (Quantification based on Quantum ESTimation) quantitation algorithm  (Ratiney et al. , 2004 (Ratiney et al. , , 2005;; Graveron-Demilly, 2014). This procedure uses a metabolite database set simulated by quantum mechanics with NMR-SCOPE (NMR Spectra Calculation using OPErators)  (Graveron-Demilly et al. , 1993)  using spin parameters from  Govindaraju et al. (2000). Seventeen metabolites were quantified: acetate (Ace), alanine (Ala), aspartate (Asp), creatine and phosphocreatine (Cr), choline (Cho), GABA, glutamate (Glu), glutamine (Gln), glutathione (GSH), glycerophosphocholine (GPC), glycine (Gly), lactate (Lac), myo-inositol (m-Ins), N-acetyl-aspartate (NAA), phosphocholine (PC), taurine (Tau), and scyllo-inositol (s-Ins).
Gene/protein expression mRNA extraction and reverse transcription. Sixteen rats were used: 8 oxaliplatin-treated rats and 8 control rats (5% glucose). At day 31 after the first oxaliplatin or vehicle injection, rats were killed and the posterior insular cortices were dissected out from the left hemisphere and stored at Ϫ80°C until analysis (as presented in the "Sample preparation"). Total RNA was extracted from pIC samples using RNeasy Mini-Kit (QIAGEN). RNA was then stored at Ϫ80°C until cDNA synthesis and amplification reaction. RNA quality was checked by electrophoresis using a Bioanalyzer 2100 with RNA 6000 Nano LabChip and BioSizing A. 02. 11 software (Agilent Technologies). Forty nanograms of total RNA were reverse transcribed in a total volume of 20 l using a High Capacity cDNA reverse transcription Kit (Applied Biosystems).
The array was centrifuged twice at 331 ϫ g for 1 min to distribute the samples from the loading port into each well. The card was then sealed, and PCR amplification was performed using an Applied Biosystems Prism 7900HT sequence detection system (thermal cycler conditions: 2 min at 50°C, 10 min at 94. 5°C, and 30 s at 97°C, and 1 min at 59. 7°C for 40 cycles). The threshold cycle (C t ) was given automatically by the SDS version 2. 2 software package. Relative quantities (RQs) were determined using the equation: RQ ϭ 2 Ϫ⌬⌬Ct  (Livak and Schmittgen, 2001). All data are presented as log base 2 (Log2) of normalized fold change (FC) relative to samples from the vehicle injected rats. We used the Log2 to allow visualization of the fold change in the positive (upregulated) and negative (downregulated) directions where 0 equals no change in gene expression, 1 and Ϫ1 equal twofold upregulation and downregulation, respectively.
MS experiments were performed with a multiple reaction monitoring condition in positive mode, and settings were optimized to reach the highest signal intensity. The multiple reaction monitoring transitions of m/z 146. 1 ¡ 87. 0 for ACh and 160. 1 ¡ 100. 9 for ␤-methyl-ACh were monitored simultaneously. The concentrations of Ach in microdialysates were determined by their area ratios to that of the internal standard using a weighting quadratic fit. The quantification limit for Ach was 50 pg/ml. Analyst version 1. 5. 2 and Multiquant 2. 1 were used for data acquisition and analysis, respectively.
Statistical analysis Data were evaluated via three-way ANOVA with sex, group, and genotype as between-subject factors followed by Bonferroni post hoc tests for significant main effects and independent t tests for significant interactions. Repeated measures ANOVAs (with time as withinsubject factor) were performed when appropriate. Data were analyzed using IBM SPSS Statistics 21 and expressed as mean±SEM; p<0. 05 was considered significant. Data were illustrated with GraphPad Prism version 5. 03 for Windows, GraphPad Software, La Jolla, California USA.
HPA response Three-way ANOVA revealed a significant sex×group×genotype interaction for Cm (F (2,82) =3. 79, p=0. 027). Thus, Cm data were analyzed separately for males and females. In males, ANOVA detected a significant genotype effect (F (2,42) =10. 39, p<0. 001) and a tendency toward significant time×genotype interaction (F (8,168) =1. 91, p=0. 062) for Cm (Fig. 1c ). On average, Tph2 -/-males displayed significantly lower Cm values than Tph2 +/-and Tph2 +/+ mice (both p<0. 01). Moreover, 3 weeks of CMS or standard housing did not affect Cm, while SIH and further behavioral tests significantly increased Cm in Tph2 +/-and Tph2 +/+ males (all p<0. 05 compared to baseline Cm). In contrast, these procedures had no effect on Cm in Tph2 -/-mice. In females, ANOVA found a significant time × group (F (2.
45, p = 0. 036), center crossings (F (2,83) =4. 00, p =0. 022) and defecation (F (2,83) =6. 01, p=0. 004). Here, Tph2 -/-females entered the center less frequently, traveled shorter distances in the center, and defecated more than Tph2 +/+ females (all p<0. 05), reflecting increased immobility and anxiety-like behavior as well as increased stress-related autonomic reactivity in the OF. Enhanced acquisition and retention of fear memory in Tph2 -/- mice Acquisition of cued and contextual fear conditioning Repeated measure ANOVA revealed a significant phase× sex×group (F (6,426) =4. 96, p<0. 001) and phase×group×genotype interaction (F (12,426) =5. 12, p<0. 001) for the time spent freezing during fear conditioning (Fig. 3a ). Thus, data were analyzed separately for males and females. Follow-up ANOVAs showed a significant phase×group×genotype interaction for freezing during FC in males (F (12,210) =1.
Retention of cued fear memory Retention of cued fear memory was tested 24 h and 7 days after conditioning. Repeated measures ANOVA revealed a significant phase×sex (F (2,142) =7. 54, p=0. 001) and phase× genotype (F (4,142) =4. 07, p=0. 004) interaction for freezing in the 24-h cue test (Fig. 3b ) and a significant phase×sex interaction (F (2,142) =5. 94, p=0. 003) for freezing in the 7-day test (data not shown). Thus, data were analyzed separately for males and females according to each phase of testing. In the 24 h test, Tph2 -/-males tended to freeze more than Tph2 +/+ males during and after the tone presentation (both p<0. 1). In the 7-day test, however, enhanced freezing in Tph2 -/-males was specifically observed in the tone phase (p<0. 1) (data not shown). In females, stressed Tph2 -/-mice displayed increased freezing during the adaptation period (pre-tone) in the 24-h test (p<0.
05) and tended to swim less than Tph2 +/+ mice (p =0. 1). However, total floating Freezing was measured at baseline (BL) to the novel context, during the tone presentations, the shock, the intertrial interval (ITI), the post-shock (PS) phase, and the second tone presentation. b Freezing duration in the cued fear retention test of male (left panels) and female (right panels) before, during, and after tone presentation c Mean freezing duration in the contextual fear retention test of male (left panels) and female (right panels) in a novel context. CTRL males: n=8 Tph2 +/+ , n=6 Tph2 +/-, n=8 Tph2 -/-; CMS males: n=6 Tph2 +/+ , n=6 Tph2 +/-, n=7 Tph2 -/-; CTRL females: n=8 Tph2 +/+ , n=8 Tph2 +/-, n=7 Tph2 -/-; CMS females: n=7 Tph2 +/+ , n=6 Tph2 +/-, n=6 Tph2 -/-. Data are shown as means±SEM.