dataesr/scientific-paragraphs-categorization huggingface dataset:
000055, Holm's 0. 02   1 ). When the data of  Premzl and Gamulin (2009)  were examined alone or in combination with our expanded data set, three codons were found to be under episodic diversifying selection in both data sets (Fig. 1  and data not shown)  (Premzl and Gamulin 2009). However, in both analyses, the codons reported by  Premzl and Gamulin (2009)  were not the same as observed in either of the datasets as analyzed in the current study. When modeled on the tertiary protein structure of human PrP, purifying selection could be observed throughout both the ahelices and the b-sheets that link them (Fig. 2a, b ). Relaxation of purifying selection was localized in residues that link the first and second a-helical domains.
1997; Perrier et al. 2002). We could not confirm these specific results for PRNP using the original data set of  (Premzl and Gamulin 2009)  or by expanding our dataset to 48 taxa and by utilizing more powerful selection detection computational methods, other than a burst of positive selection on the branch leading to the Perissodactyla clade (BSREL, p = 0. 04) given the  Premzl and Gamulin (2009)  sequences alone. Once we added our sequences this result was no longer significant (BSREL, p = 0. 147). Our contrasting findings with respect to  Premzl and Gamulin (2009) , who previously reported the action of positive selection on specific codons in PRNP, are very likely due to the taxonomic and-subsequentlysequence variability between their 19-taxon and our 48-taxon datasets. While an earlier study  (Mead et al.
2010). Therefore, we specifically extended the PRNP and PRND data sets for diverse rodent species. Consistent with other taxa, rodent PRNP and PRND were under a strict regime of negative selection. This is consistent with the difficulty of establishing rodentadapted scrapie models which involves intracerebral inoculation. Therefore, we conclude that the prion gene and its homolog doppel have been evolving under purifying selection among mammalian taxa.
Acknowledgments We thank the  French ANR Biodiversity , Grant  ANR 07 BDIV 012   CERoPath project (Community Ecology of Rodents  and their Pathogens in a changing environment (www. ceropath. org),and the  French ANR CP&ES , Grant  ANR 11 CPEL 002   BiodivHealthSEA project (Local impacts and perceptions of global changes: Biodiversity and health in Southeast Asia ) (www. biodivhealthsea. org)and all the CERoPath participants for their great help in field works. We also thank the  Conservation Genetics Unit of the University of Lie  `ge and the  Belgian Funds for the Scientific Research (FNRS)  for supporting  Johan Michaux. The provision of samples and support of the investigations by  Jona Freise  (Oldenburg),  Hanan Sheikh Ali  ( Greifswald-Insel Riems ) are kindly acknowledged. We acknowledge the help of  Sergei L.
Stimulating electrodes (bipolar microelectrodes) were placed in the stratum radiatum to stimulate the Schaffer collaterals pathway. Field EPSPs (fEPSPs) were recorded in the stratum radiatum using a recording glass pipette filled with ACSF and amplified with an Axon Axopatch 200B amplifier (Molecular Devices). Data were digitized through an Axon Digidata 1440A and acquired with pCLAMP 10 software (Molecular Devices). The initial slope of the fEPSPs was measured to avoid population spike contamination. For LTP experiments, test stimuli (0. 2 ms pulse width) were delivered once every 15 s and the stimulus intensity was set to give baseline fEPSP slopes that were 50% of maximal evoked slopes. Slices that showed maximal fEPSP sizes Ͻ1 mV were rejected. LTP was induced by applying 4 trains of 100 stimuli at 100 Hz with an intertrain interval of 5 min.
Membranes were incubated with the HRPconjugated secondary antibodies rabbit (1:40,000) and mouse (1:5000) (both from Sigma) for 45 min at room temperature. Specific proteins were visualized with an enhanced chemiluminescence ECL Detection System (Bio-Rad). Chemiluminescence detections were performed with the Bio-Rad Chemidoc system and analyzed with the software Imagelab (Bio-Rad). Statistics. Results are expressed as the mean Ϯ SEM from independent biological samples. Statistical analyses were performed with GraphPad Prism 6. 0 software by two-way ANOVA followed by Bonferroni's test for confocal analysis, one-way ANOVA for phalloidin precipitation analysis, and Student's t test for Western blot analysis.
Synaptic activation induces translocation of tau to the synaptic compartment To determine how and under which circumstances tau enters into the postsynaptic compartment, we monitored EGFP-tau fluorescence under various conditions. First, we induced a longlasting synaptic activation by exposing cultured cortical neurons to Bic (50 M), a GABAergic antagonist, in the presence of 4-aminopyridine (4-AP, 2. 5 mM), a weak potassium channel blocker that prevents neuronal repolarization (Leveilleet al. , 2008), for 30 min (Fig. 2A ). In control conditions, EGFP-tau showed a weak but detectable fluorescence in Ͼ60% of the spine, but the calculation mode used to quantify the imaging data (⌬F/ F 0 ) brings our quantification to zero to highlight changes from base line fluorescence. As early as 15 min after the beginning of the treatment, we measured an increase in EGFP-tau fluorescence in dendritic spines from 0 Ϯ 0.
4A ) and actin bundles (Fig. 4B ). It is worth noting that the filamentous nature of actin in the presence of tau was confirmed by electron cryomicroscopy (data not shown). We also performed transfection with 1N4R-GFP and we observed similar synaptic-activity-dependent translocation as observed with the full-length tau  (Fig 4C). Similarly, a phalloidin precipitation of neuronal lysate that selectively collected the neuronal F-actin and its binding partners revealed the presence of tau by Western blotting. This result illustrates that tau interacts with F-actin in neurons (Fig. 5A ). After synaptic activation, we observed an increase in the amount of F-actin harvested (***p ϭ 0. 0003, 2-tailed Student's t test; control 17. 67 Ϯ 2. 08; Bic/4-AP 31. 76 Ϯ 1. 882, N ϭ 7 independent cultures; Fig.
Participants This study was approved by the UCL Research Ethics Committee. The patients were self-selected and signed an online consent form. Patient data are stored on a secure university server. Inclusion criteria for the analyses were sequentially applied as follows: (1) Patients with a clear hemianopia who completed assessments at two or more time points (n = 142). (  2 ) No evidence of neglect: 14 had neglect (79% of these with a left-sided hemianopia) and seven had an uninterpretable test: all (n = 21) were excluded. (3) A further 43 of the remaining patients (36%) who had <10% search time deficit into the affected visual field pretherapy, were excluded because the presence of a deficit is necessary in order to assess the effects of rehabilitation. This left 78 patients for data analysis.
Statistical methods Primary and secondary outcome measures were entered into repeated-measures analysis of variance (ANOVA)s using SPSS v22 software Armonk, NY: IBM Corp. with time as the within-group factor. An additional withingroup factor: field (affected/unaffected), was entered for the visual search analysis. Where sphericity assumptions were violated, Greenhouse-Geisser measures are reported. Significance was set at the conventional P < 0. 05 level. We also calculated effect sizes for the main outcome measure using both unstandardized ((T0 À T2)/ T0 9 100 = % improvement in RT) and standardized (Cohen's d) methods.
Area at risk and infarct size determination At the end of the 2-hour reperfusion period, the left coronary artery was reoccluded using the monofilament suture kept in place and 1% Evans blue was injected for the purposes of delineating the area at risk (AAR). The heart was then cut into five equal slices and incubated with 1% triphenyltetrazolium chloride (TTC, Sigma-Aldrich) pH 7. 4 at 37uC for 15 min. The infarcted myocardium within the AAR was not stained and became pale, while the viable was stained deep red. Following overnight storage in 10% formalin, the slices were photographed. IS and AAR were evaluated blindly using Image J software (National Institutes of Health, Bethesda, MD). IS was expressed as a percentage of AAR, and AAR as a percentage of total ventricular area (AAR%LV).
6, and 0. 1% Tween-20, the membranes were incubated overnight at 4uC with rabbit antibodies for 473 Ser-phospho-Akt, total Akt, phospho-ERK1/2, total ERK1/2, 9 Ser-phospho-GSK-3b, total GSK-3b, 705 Tyr-phospho-STAT-3, and total STAT-3 (all from Cell Signaling Technology). GAPDH (Sigma-Aldrich) was used as a loading control. Once washed in TBS containing 0. 1% Tween, the membranes were incubated with horseradish peroxidase conjugated secondary antibodies for 1 hour. Specific antibody binding was detected using electrochemiluminescence. A quantitative analysis of the band densities was performed using Image J software (National Institutes of Health, Bethesda, MD).
Histological and immunohistochemical analysis of inflammation For the purposes of investigating histological architecture and leukocyte infiltration, the hearts were sliced into 7 mm-thick transverse sections using Cryostat CM3050 S (Leica Biosystems, Nussloch, Germany). Mid-ventricular sections were stained with hematoxylin and eosine (H&E) then viewed under a light microscope (Leica DMR microscope, Image J software). Immunohistochemical staining for CD45 was performed in order to confirm leukocyte infiltration in infarcted tissues. Mid-ventricular sections were fixed with 4% paraformaldehyde for 30 min, then washed with phosphate-buffered saline and blocked for 30 min with 5% bovine serum albumin at room temperature. They were then incubated overnight at 4uC in a solution of the primary antibody against CD45 diluted to 1:100 (F10-89-4, Mouse, Millipore).
The slices were submitted for stringent wash and incubated with the secondary antibody (1:300, goat anti-mouse Alexa-Fluor 488, Invitrogen) for 1 hour at room temperature. The nuclei were counterstained with 49,6-diamidino-2-phenylindole (DAPI) (1:300, Sigma-Aldrich) for 10 min at room temperature. The slices were washed and coverslips were applied to slides with Fluoromoun aqueous based mounting medium (Sigma-Aldrich). Immunohistochemistry images were taken by means of a Leica microscope (Leica DMR microscope, Image J software). The number of CD45 + leukocytes was semiquantitatively evaluated according to the following procedure. Positivity against the antibody was examined and the number of positive cells per field was counted, using 400x magnification. The specimens were scanned randomly, the same field never chosen more than once, by sequential movement of the mechanical stage.
Statistical analysis All values were expressed as mean6standard error of the mean (SEM). Statistical analyses were performed using SPSS 17. 0 (SPSS Inc, Chicago, IL, USA). After testing their linear distribution, the differences between infarct sizes were evaluated using one-way ANOVA, followed by the post-hoc Bonferroni test. For the Western blot data, the Mann-Whitney U test was used. A p value,0. 05 was considered statistically significant.
We denote by P the probability measure, by E its corresponding expectation and by Var its corresponding variance. Also 1 A denotes the indicator function of the event A, which takes value 1 when A is true and 0 otherwise. Fundamental notions for the present article are given in the following definition (see also  (Staude et al. , 2010)  for this kind of distinction). ' & $ % Definition 1: Real single unit data are recorded with a certain resolution h, which is usually 10 -3 s or 10 -4 s depending on the experiment. Formally time is cut into intervals of length h and of the form [ih -h/2, ih + h/2). Then one associates to any point process, N , its associated sequence at resolution h, i. e. a sequence of 0 and 1, (H n ) n , where H i = 1 corresponds to the presence of (at least) one point of N in [ih -h/2, ih + h/2).
Description of the data Behavioral procedure The data used in this theoretical article to test the detection ability of the MTGAUE method were already partially published in previous experi-mental studies  (Riehle et al. , 2000; Grammont & Riehle, 2003; Riehle et al. , 2006). These data were collected on a 5-year-old male Rhesus monkey who was trained to perform a delayed multidirectional pointing task. The animal sat in a primate chair in front of a vertical panel on which seven touch-sensitive light-emitting diodes were mounted, one in the center and six placed equidistantly (60 degrees apart) on a circle around it. The monkey had to initiate a trial by touching and then holding with the left hand the central target. After a delay of 500ms, the preparatory signal (PS) was presented by illuminating one of the six peripheral targets in green.
Acknowledgments We first of all want to thank  Alexa Riehle , leader of the laboratory in which the data used in this article were previously collected. We wish also to thank  Y. Bouret  and  F. Picard  for fruitful discussions and programming help at several stages of this work. Finally, we thank two anonymous referees for helpful remarks and comments. This research is partly supported by the  french Agence Nationale de la Recherche  ( ANR 2011 BS01 010 01  projet Calibration ), by the PEPS BMI 2012-2013 Estimation of dependence graphs for thalamo-cortical neurons and multivariate Hawkes processes and the PEPS BMI 2012-2013 NeuroConf.
Brain imaging In order to correlate the effects of stimulation with changes in brain metabolism, the patients underwent two [ 18 F]FDG PET scans before and after Acb stimulation. The data, acquired on different PET cameras, were analyzed using statistical parametric mapping software (SPM2; Wellcome Department of Cognitive Neurology, London) written in Matlab version 7 (MathWorks). This analysis, using an isotropic smoothing 12-mm full-width at half-maximum Gaussian kernel filter to compensate for interindividual anatomical variability and render the imaging data more normally distributed, allowed us to overcome technical differences in machines. Significant modifications in the brain metabolism of the four patients were pinpointed by comparing their pre-and post-surgery 18 FDG PET scans. We used the "single subject, conditions and covariates" routine.
Values of access resistance ranged from 12 to 20 MΩ and were not compensated. Measurements were made 2 to 3 minutes after obtaining the whole cell to ensure dialysis. Cell capacitance and resistance were measured in voltage clamp using the pClamp Clampex software (Axon Instruments, Union City, USA) by applying 5 mV voltage steps. Solutions were applied in the bath. Current-clamp recordings were made in the IClamp mode of the Axopatch 200B. Voltage clamp data were digitized at 0. 5 kHz using a Digidata interface coupled to a microcomputer running p-Clamp 9 (Axon Instruments). All electrophysiological chemicals were from Sigma-Aldrich.
52 ± 2. 32 in saline-treated brain, P < 0. 05; data not shown). This may indicate a proliferation of resident macrophages and/or a higher number of infiltrating cells from the periphery. Our data does not show significant proliferation of microglia upon LPS treatment (Figure  2A ). However, microglia proliferation might have been masked by the dramatic increase of CNS-associated phagocytes in the brain or might occur at a different time after LPS challenge. To further characterize which cell types migrate from the periphery to the brain in cases of inflammation, we performed detailed analysis of CD11b + /CD45 high+ cells by flow cytometry. Ly6C and Ly6G surface marker labeling allowed us to discriminate between three subpopulations among immune brain CD11b + /CD45 high+ cells. Neutrophils were identified as CD11b + /CD45 high+ / Ly6C intermediate+ /Ly6G high+ cells and macrophages were identified as CD11b + /CD45 high+ /Ly6G neg-cells.
Among them, resident macrophages were identified as Ly6C neg- and inflammatory monocytes as Ly6C high+ cells (Figure  2B , middle panel). SSC plots confirmed this discrimination, since neutrophils are known to be SSC high (Figure  2B , upper panel). The specificity of Ly6C and Ly6G signals was verified by labeling with isotype control antibodies (data not shown). Our results showed that peripheral LPS administration promoted a selective migration of inflammatory monocytes to the brain, 24 hours after treatment (44. 70 ± 6. 80% of parent cells in LPS-treated mouse brain versus 17. 46 ± 0. 91% in saline-treated brain, P < 0. 05; Figure  2B , left histogram). Resident macrophage percentage was not significantly affected by LPS treatment (14. 5 ± 1. 66% of parent cells in LPS-treated mouse brain versus 13.
Bars represent the mean ± SEM. *P < 0. 05 versus saline control; ns, non significant; n = 4. FSC, front scatter. increased to a larger extent by LPS i. p. injection (26. 4 ± 2. 26% of parent cells in brains of LPS-i. p. mice versus 5. 8 ± 1. 27 in brains of saline-treated mice, P < 0. 005; Figure  3D , left histogram), suggesting an important role of the CCL2/CCR2 signaling pathway in attraction/migration of immune cells to the brain during inflammatory processes. Antibody specificity was checked using isotype control antibody labeling on microglia and macrophages (data not shown). Figure  3B ,D (right histograms) confirmed that microglia and CNS-associated phagocytes expressed both TLR4 receptor and CD14, and that LPS treatment increased their expression. Figure  3C, E  shows that CD80 expression level was upregulated by LPS i.
STATISTICS The data were analyzed using one-way or two-way ANOVA followed by Bonferroni post-hoc test for specific comparisons. Student's t-test with equal variances was used for groups of two, when relevant. In all cases, significance threshold was set at p < 0. 05. Statistical analyses were performed using GraphPad Prism 5. 0 (GraphPad Prism Software Inc. , San Diego, USA).
RECOGNITION MEMORY FUNCTIONS ARE DISRUPTED Ca v 3. 2 NULL MICE Previous studies have shown that T-type Ca v 3. 2 is critical for hippocampal LTP, cued-context fear conditioning and passive avoidance tasks  (Chen et al. , 2012). We then investigated two hippocampal recognition memory tasks, the novel and the spatial object recognition (NOR and SOR, respectively). As shown in Figures  3A, B , Ca v 3. 2 deficient mice do not show preference for the novel or the relocated object during the recall session 24 h later as opposed to the WT. This altered response is not the result of an impairment of the exploratory drive since the exploration of the two objects is not significantly different from the WT animal during the familiarization phase (data not shown). Interestingly, the spatial working memory, assessed using the spontaneous alternation in the Y-Maze, was unaffected in Ca v 3.
ACKNOWLEDGMENTS We are grateful to  Dr. V. Uebele  ( Merck and Co. , Inc. ) for the TTA-A2 molecule. This work was supported by  Inserm  and grants from  ATIP-Avenir (Inserm) ,  Sanofi-Aventis  R and D, from the  Agence Nationale de la Recherche  ( ANR-2010-JCJC-1412 ) to Valjent Emmanuel, and by grants from the  ANR  ( ANR-09-MNPS-037 ) and the  AFM (AFM-PainT)  to  Bourinet Emmanuel. Laffray Sophie  is supported by fellowships from the  FRM  and the  Labex ICST.
Acknowledgments This work was conducted with the support of the ' Fondation Thérèse et René Planiol pour l'étude du cerveau', Cyclopharma laboratories and the 'Centre pour l'Etude et la Recherche sur les Radiopharmaceutiques '. The authors are also grateful to  C. Roussel, PhD ,  S. Dupont  ( CIC-IT INSERM 0806 ),  A. Matysiak ,  M. Brachet  and  F. Brault  for their contributions to the clinical investigation.
; 18 stands for the neuron, j = 1;. ; 18 stands for the stimulation condition, and k = 2,. ,49 stands for the trial. The dimensionality of these vectors ranged from two to seven, de-pending on the duration of the observation interval. We used a simple linear classifier, implemented by the ''classify'' function of Matlab (R2011b). The classifier took as inputs the spikes-count vectors of all considered neurons. The input vector to the classifier for j -th experimental condition was defined by taking one trial for each neuron and concatenating the corresponding spikes-count vectors, ; where k 1 ,. , k 18 are the selected trials. Depending on the length of the observation interval, the dimensionality of V j ranged from 34 to 119. At the learning phase for each stimulus condition, we produced 24 input vectors V j , using random trials for each neuron.
For example, if a 12elemental subset included neurons with numbers from 1 to 12, then the six-elemental subsets were also selected out of these neurons. The curves in Figure  4C  present the average classification results obtained for two 12element, five six-element, and six three-element subsets of neurons. In order to illustrate the partitioning of responses of the cuneate neurons when all 18 neurons are used to produce spike-count vectors, we computed 48 V j vectors for every condition, concatenating the trials with the same numbers. For illustration purposes, these high-dimensional data were embedded into a plane using curvilinear component analysis space  (Demartines and Herault, 1997) , implemented in the ''cca'' function of SOM Toolbox 2. 0 for Matlab (http://www. cis. hut. fi/somtoolbox/).
Response Patterns To substantiate the observation that responses of two compared neurons had different temporal ''topography'' to the same stimulus, we employed the twosample KS test. This test takes a pair of data samples as input and tests the null hypothesis that they are drawn from a same, yet unknown, distribution. The samples were obtained from the time-spike sequences of individual trials. The sequence for i -th trial comprised the spike times, t i 1 ; t i 2 ;. ; t i Ni , measured from the stimulus onset, where t i Ni is the time of the last spike in i -th trial. The pair of samples was produced by pooling sequences from 48 trials (the first and the last trial were excluded) for the same neuron and the same stimulation condition. All possible pairs of 16 out of 18 neurons (120 pairs on total) were used in the analysis; the response in the two excluded neurons was too weak (less than ten spikes per trial), making the results of Kolmogorov-Smirnov test unreliable.
ACKNOWLEDGMENTS This study was supported by the  European Research Council  ( FP7 )  ERC Advanced Grant  (PATCH) to V. H. (no. 247300 ), by a  European Commission  grant The  Hand  Embodied (THE, no. 248587 ) within the European  FP7 , and by the  Swedish Medical Research Council. Accepted: July 17, 2014 Published: August 28, 2014.
QUANTIFICATION The number of BrdU+ (10 sections/animal, 800 µm between sections) and Ki67+ cells (6 sections/animal, 950 µm between sections) was assessed by counting peroxydase/DAB-stained frontal sections of the MOB and the DG through different levels along the rostrocaudal axis, using a light microscope (Axioskope 2, Zeiss, Germany) on a magnification of x20 and cell count analysis software (computerized image analysis Mercator, Explora Nova, La Rochelle, France). The counter was blind to the experimental group. Areas of the MOB (granular and periventricular layers) and the DG (GCL and SGZ) were measured with this system through an x2. 5 objective (MOB) and an x10 objective (DG). Cell densities were then calculated by dividing the numbers of BrdU+ or Ki67+ cells by the layer area. The Ki67+ cell density corresponds to the mean of cell density measured in the granular and the periventricular layers for the MOB and in the GCL and the SGZ for the DG.