dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The authors thank  P. Gaspar ,  R. Mongeau , and  B. Allolio  for support and discussion, as well as  T. Wultsch  and  N. Steigerwald  and  E. Klobetz-Rassam  for technical assistance. JW was supported by a grant of the  German Excellence Initiative  to the  Graduate School of Life Sciences, University of Würzburg. This study was supported by the  German Research Foundation  (DFG:  SFB 581 ,  SFB TRR 58 , and  KFO 125 ) and the  European Community  (EC:  AGGR ESSOTYPE FP7/No. 602805 ).
The images were recorded with a Gatan Orius CCD camera (Gatan Inc. , Pleasanton, CA). Fourier Transformed Infrared Spectroscopy (FTIR)-HttEx1Q25, HttEx1Q48, and HttEx1Q48 in the presence of equimolar concentrations of Hsc70 were assembled as described above. Fibrillar samples (5 mg) were spun at 16,000 ϫ g at 25 °C for 20 min and then extensively washed in D 2 O. The spectra were recorded on a Jasco FT/IR-600 Plus spectrometer equipped with a nitrogen-cooled MTC detector, using the attenuated total reflectance mode. A total of 512 interferograms were collected at a resolution of 2 cm Ϫ1. The sample chamber was continuously purged with CO 2 -free air. The background consisted of D 2 O and water vapor. All of the spectra were baseline-corrected, smoothed, and normalized prior to further data processing.
Because the same small quantity of Hsc70 was found in the pellet when the chaperone was incubated alone or in the presence of aggregating HttEx1Q48, the contribution of Hsc70 was subtracted from the spectra recorded for HttEx1Q48 fibrils formed in the presence of Hsc70. Spectral analyses were performed using the curve-fitting analysis software of the Spectra Manager package (Jasco). The amide I band (1575-1725 cm Ϫ1 ) of each spectrum was subjected to a fitting procedure using seven Gaussian distributions centered at the frequencies of well characterized secondary structures and lateral chains  (27, 28). Each Gaussian was char-acterized by its frequency and an interval of given width. Each peak width was limited to 25 cm Ϫ1 , whereas peak heights were left free. The contribution of each curve to the amide I band was assessed by integrating the area under the curve and normalizing to the total area under the amide I band.
Peptide Preparation and NanoLC-Linear Ion Trap (LTQ)-Orbitrap Mass Spectrometry Analysis-Cross-linked protein complex spots separated by two-dimensional gel electrophoresis were excised and subjected to tryptic or GluC digestion using the Progest robot, and the digested peptides were extracted as described previously  (29). Tryptic peptides were analyzed by nanoLC-LTQ-Orbitrap mass spectrometry analysis, and the nanoLC-MS/MS data were processed as described previously  (29) , except that the data analysis included lysine, serine, threonine, tyrosine, and the N-terminal amino acid residues as possible cross-linked sites  (30)  and that the cross-linker was BS3-d0 and BS3-d4. Briefly, nanoLC-MS data were deisotoped using the Decon2LS software (available at the Pacific Northwest National Laboratory Web site).
The resulting csv files were further analyzed with viper (available at the Pacific Northwest National Laboratory Web site)  (31)  to identify, within the nanoLC-MS analysis, the d0/d4 peptide pairs presenting mass differences of 4. 0247 Da as a signature of peptides that have reacted with one molecule of BS3-d0/d4. Mass modifications were set to 138. 0681 and 142. 0928 Da for BS3-d0-and BS3-d4-cross-linked peptides, respectively. A list of peptide pairs with a maximum mass deviation of less than 10 ppm between the experimental mass and the theoretical mass of each possible cross-linked peptides was generated and used to identify the BS3-d0/d4-cross-linked peptides using their MS/MS spectra and the GPMAW  (32)  and xQuest (33) software. Finally, identification of cross-linked peptides and location of cross-linking sites were manually validated by comparison of the experimental masses and the theoretical masses of the d0/d4 ion fragment pairs calculated for each cross-linked peptide.
List of the identified Hsc70-HttEx1Q25 cross-linked peptides For each identified cross-linked peptide in the Hsc70-HttEx1Q25 complex, the table gives the experimental mass (M exp), the charge state (z), the m/z ratio for both the BS3G-d0-and the BS3-d4-cross-linked peptides, the amino acid segment, the cross-linked residues (XL site) in lowercase boldface type, and the amino acid sequence for both the Hsc70 and the HttEx1Q25 peptides. ⌬M (ppm) corresponds to the mass deviation between the experimental mass and the theoretical mass of the identified BS3-d0-cross-linked peptides, given by the XBobCat software (available on the ETH Web site)  (33). M(Ox), oxidized methionine. residues (the most abundant allele in the human population), we conjecture that we would all develop HD if we lived for 145 years.
* This work was supported by  Agence Nationale de la Recherche  Grant  ANR-11-BSV8-021-01 ,  CNRS , the  Human Frontier Science Program , the  European Community 's  Seventh Framework Program   FP7/2010 ,  Marie Curie Actions Grant   264508 , and a " Coup d'Elan ala Recherche Francaise " award from  Fondation Bettencourt-Schueller. R. M. dedicates this work to the late  Professor Paul Cohen.
2 ). This pattern of alignment of the photodiodes, which is particularly suitable for detecting luminous contrasts in the main direction, also makes it possible to sense light variations in any other direction. The analog signals originating from each pixel were digitized on-chip so that they could be directly processed by an external microprocessor or microcontroller, saving the power consumption and the computational resources of the latter for further data processing. Since the pixel type is selected by a digital input, only one set of pixels can be converted at a time. The twelve M 2 APix outputs are low-pass filtered with a cut-off frequency of 300 Hz before being digitally converted, giving a minimum sampling frequency of 600 Hz in order to prevent the occurrence of aliasing. An integrated DC reference voltage was connected to the ADC as an additional pixel output for testing and calibration purposes.
The following main tools were used for this purpose: • The Lighting Box described above. • A NI Single-Board RIO-9683 Acquisition Device provided by National Instruments. The board features a 400 MHz real-time processor with 128 MB DRAM and includes an integrated real-time controller and a 2-Million-Gate reconfigurable FPGA programmed using LabVIEW software including Real-Time and FPGA modules. • An Explorer 16 development board provided by Microchip, which includes a dsPIC 33FJ128GP804 micro-controller working at a sampling rate of 2 kHz. This device was programmed using Matlab/Simulink with a toolbox specifically developed for use with Microchip dsPIC micro-controllers. The block diagram in Fig. 8  gives an overview of the hardware setup and communication flow involved in the method of characterization.
3. After waiting for a time (T wait ), which is usually the time required for the pixel output to reach its steady-state value, the FPGA sends Explorer 16 a trigger signal (Trigger 1) making it start sending the data acquired. The steady-state value of the pixels is thus acquired before the lighting change occurs. 4. A short instant later (T s ), the FPGA sends the Lighting Box a second trigger signal (Trigger 2) making it switch the LED intensity from I LED 0 to I LED i (see Fig. 5 ). 5. The Explorer 16 sends the FPGA the appropriate number of samples (Pixel Data), depending on the sampling frequency. 6. The FPGA stores the data acquired in a FTP server and goes back to step 1 to deal with the next pair I LED 0 , I LED i. The current-irradiance characteristic of the LED was assessed by measuring the LED's irradiance with a radiometer (ILT1700, International Light Technologies).
Acknowledgments We thank the referees for their fruitful comments. We are most grateful to  R. Potheau ,  A. Calzas  and  P. Breugnon  for their expertise in VLSI designing and testing, to  R. Leitel  for the packaging and to  J. Diperi  for his involvement in the mechanical design. We thank  F. Roubieu ,  A. Manecy ,  F. Colonnier , and  R. Goulard  for their helpful suggestions and comments during this study,  A. Servel  and  S. Allano  for their assistance and  J. Blanc  for correcting and improving the English manuscript. This research was supported partly by the  CNRS (Life Science; Information and Engineering Science and Technology) ,  Aix-Marseille University , the  French National Research Agency -ANR -( EVA  project under  ANR-ContInt  grant number  ANR-08-CORD-007-04  and  IRIS  project under  ANR-INS  grant number  ANR-12-INSE-0009 ).
Flow cytometry Freshly isolated monocytes were cultured in the presence or absence of TsSP (40 μg/ml) for 16 h and subsequently harvested. Next, monocytes were washed twice with PBS and labelled for 1 h at 4 °C with primary antibody (Table  1 ) diluted in PBS containing 0. 1 % BSA. Cells were washed twice in PBS and incubated for 1 h (4 °C) with fluorescent labelled secondary antibodies diluted in PBS/0,5 % BSA (FACS buffer), washed twice and resuspended in FACS buffer prior to FACS analysis. We used either four or eight colour flow cytometry. Four colour flow cytometry (FACS-Calibur, Becton Dickinson, Belgium) was used in combination with Cell Quest software (Becton Dickinson) and FlowJo software version 9. 4. 0 for Microsoft (Tree Star, San Carlos, CA) to analyse expression of markers. For eight colour flow cytometry, we used a Cyan ADP High Performance Research Flow Cytometer (Beckman Coulter) and results were analyzed with Summit Software v4.
Cytokine assays The production of pro-and anti-inflammatory cytokines was assessed by enzyme-linked immunosorbent assay (ELISA) in cell-free supernatant samples using the Human Inflammatory 5-Plex Panel (Invitrogen, USA). This multiplex bead assay was performed according to the user manual supplied by Invitrogen. Samples were measured by Luminex® 200TM (Bio-Rad, California, USA) and analysed using Bio-plex ManagerTM 6. 0 software.
RNA isolation and quantitative real-time PCR Messenger RNA (mRNA) was isolated using a mRNA Capture kit (Roche, Switzerland), and subsequently transcribed into cDNA using the Reverse Transcription System kit (Promega, USA), as described previously  [24]. Quantitative real-time PCR was performed with the SYBR Green method as previously described  [24]. Oligonucleotides were designed using Primer Express 2. 0 (Applied Biosystems, USA) computer software. All primer sequences are listed in Table  2  and expression levels of transcripts obtained with real-time PCR were normalized to GAPDH expression levels.
Live cell imaging for assessment of monocyte motility Real-time video recordings of monocytes were performed with an inverted phase-contrast microscope (Olympus, IX81-ZDC, Suffolk, U. K. ) housed in a humidified, 5 % CO 2 gassed, temperature-controlled (37 °C) chamber. For this, 3 × 10 5 freshly isolated monocytes were applied in each well of an IBIDI slide in the presence or absence of TsSP (40 μg/ml), and randomly selected fields were recorded for 240 min. Pictures were taken every 3 min with an Olympus ColorView II camera (Olympus Nederland BV). Recordings were analyzed using CELL F trackIT software (Olympus Soft Imaging Solutions, Münster, Germany).
Mecp2 Regulates Transcriptional Activation of Axon Guidance Cues The known function of MeCP2 mainly involves its binding to methylated-CpG islands as well as activating and suppressing transcription. We therefore sought to examine the role of Mecp2 in regulating gene expression in zebrafish. Expression profiling was undertaken using a 135K-zebrafish gene expression array (∼38,000 known transcripts), comparing the transcriptome of wild-type controls with Mecp2 morphants. A total of 1123 genes had a minimum of 2-fold change over control (p < 0. 05), but only 1005 of which had a mammalian (human or mouse) ortholog (http://www. ncbi. nlm. nih. gov/geo/ -accession number GSE71173). Out of these 1005 genes, 607 were downregulated and 398 were up-regulated (minimum twofold change; significance was established at p < 0.
05) in Mecp2 morphants, and 118 genes (43 down-regulated and 75 up-regulated) are without human orthologs (Figure  4A ). These results strongly suggest that knocking down Mecp2 could either activate or repress transcription. Functional analysis of these 1123 genes in silico using the program Database for Annotation, Visualization and Integrated Discovery (DAVID) yield the following. Mecp2regulated genes in zebrafish appear to function in diverse cellular processes (Figures  4B, C ). Many of the up-regulated genes had roles in proliferation, cell communication and metabolism. By contrast, many of the down-regulated genes had functions related to neuronal development, including neurogenesis, neuronal projection morphogenesis, cell migration and synaptogenesis (Figures  4B, C ). Since Mecp2 knockdown resulted in projection defects in sensory neurons, we searched for genes with axon guidance functions in our microarray that can potentially be involved in Mecp2-mediated effects.
Zebrafish Gene Expression Microarray Three independent pools of 24 hpf zebrafish Mecp2 morphant embryos were compared to three independent pools of 24 hpf control embryos. RNA extraction was done using RNeasy mini kit (QIAGEN). The triplicate embryo pools made a total of six hybridizations. cDNA synthesis, cDNA labeling, microarray hybridization and washing were performed following the manufacturer's instructions (Roche NimbleGen). The 135K NimbleGen array contains 135,000 probes targeting 38,489 transcripts derived from the Ensembl database built on the Zv7 assembly (37,157 zebrafish genes identified). Array hybridization was done using Maui Hybridization System and was scanned using Axon GenePix 4000B Scanner. Data extraction and image processing were performed using NimbleScan software v.
Quantitative Real-Time PCR One microgram of total RNA was used as starting material. Reverse transcription was carried out with Invitrogen's SuperScript III First-Strand Synthesis kit using oligo(dT) primers. Gene specific primers were used to amplify sema3f (fw-5 CAACCAGTACTGCCAAGACT AC 3 ; rv-5 TCCTGGTGGTGTCTCCTATT 3 ), sema5b (fw-5 CTGCTGTCTTTCCTGGTGTATG 3 ; rv-5 GTGGTGTTGCCCTTGTAGTT 3 ) and robo2 (fw-5 GACATACCTCCATCAGGGTTTAG 3 ; rv-5 GAAACTG CAGCAGGAGAAGA 3 ) by qPCR on a Biorad CFX96 RT PCT using SYBR Select master mix (Invitrogen). A sample volume of 12 μl was used for all assays. All samples and standards were run in triplicates. Three biological replicates were performed for each set of data normalized using housekeeping gene beta-actin.
Imaging, Analysis, and Figure Preparation Stained embryos were dissected from their yolk and mounted in 70% glycerol. High-resolution images of embryos were captured using a Zeiss LSM 710 confocal microscope (Carl Zeiss Pte Ltd, Singapore). Low-resolution images were obtained using a Zeiss SteREO Discovery V8 stereoscope equipped with an Axiocam ICc3 color digital camera (Carl Zeiss Pte Ltd, Singapore). For analysis of the neurite structure of TG cells, three-dimensional (3-D) reconstructions of the processes of all labeled cells were made from Z-series stacks of confocal images. The projection images were semi-automatically traced with NIH ImageJ using the NeuronJ plugin. The total length of processes in each individual embryo were subsequently measured and analyzed. All data were scrambled and only decoded after analysis was done blinded.
ACKNOWLEDGMENTS We thank  G. Augustine ,  S. Jesuthasan ,  S. Shenolikar ,  R. Krishnan ,  D. Purves , and  B. L. Tang  for comments on the manuscript and helpful discussion,  K. Kwan  for Robo2 cDNA,  H. Okamoto  for HuC:kaede construct,  S. Choksi  for advice on microarray analysis and  Agency for Science, Technology and Research (A * STAR) ,  Singapore core zebrafish facility  for providing embryos,  J. Tay  for technical support. This work was supported by  Duke-NUS   Graduate Signature Research Program  funded by  A * STAR  and the  Ministry of Health, Singapore , the  Academic Center of Excellence (ACE)  research award from  GlaxoSmithKline (GSK) ,  Abbott Nutrition  and the  National Research Foundation Singapore  under its  Competitive Research Program  ( NRF 2008 NRF-CRP 002-082 ) to EG.
The two signals were presented in an additive Gaussian noise, and participants were asked to indicate whether the target was /aba/ or /ada/. Each participant's response was then linked to the specific noise configuration in the corresponding trial with a Generalized Linear Model (GLM) with smoothness priors. The rationale underlying this technique is that if the time-frequency coordinates at which the noise interferes with the decision of the observer are known, then the regions on which the observer focuses to perform the task would also be known. By fitting the decision weights corresponding to every pixel of the representation, it became possible to draw a timefrequency map of the categorization strategy and directly visualize which parts of the stimulus are crucial for the decision. In the first report on ACIs, we only reported individual data on three volunteers and used two speech productions as targets, thus leaving the question of the specificity of the obtained ACIs to these particular utterances unanswered.
Cochleograms The same preprocessing was applied to all noise and speech sounds before analysis. Cochleograms were generated from the waveforms using Lyon's Cochlea Model  [36] , implemented in the classic Matlab Auditory Toolbox by Malcom Slaney (https://engineering. purdue. edu/m alcolm/interval/1998-010/). This algorithm involves a bank of simulated auditory filters of constant quality factor (Q = 8), spaced quasi-logarithmically and overlapping by 40% (this step factor was chosen to be slightly greater than the default parameter proposed by Slaney to ensure sufficient spectral resolution). The vertical axis of the cochleogram represents the center frequencies of each auditory filter. Two additional processing levels are implemented in this function to mimic the non-linear behavior of the hair cells: a half-wave rectifier followed by an Automatic Gain Control modeling the neural adaptation mechanism and a difference between adjacent filters to improve the frequency response.
Lambda optimization However, consistent with the literature on STRF and CI estimations using penalized likelihood  [37, 38, 40] , we do not want to presume an a priori value for λ. Instead, we aim to determine how much smoothing is appropriate based on our data. Because we aim for the ACIs to be generalizable to an independent dataset, models corresponding to different smoothing values are evaluated with a cross-validation approach, and we determine an optimal regularization parameter, denoted l, according to this criterion. Individual optimization. For example, in our previous paper  [26] , we computed a 10-fold cross-validation for a wide range of λ values by randomly partitioning the dataset each time between a "training" set and "test" set, thereby estimating the model parameters on the training set (9,000 trials) through MAP for all considered λ values, as explained previously, and then comparing the predicted responses on the test set (1,000 trials) to the actual responses of the participant.
However, the increase of this function for high lambda values is sometimes relatively small, thus causing an oversmoothing of the estimate. Thus, we rather selected the smallest λ value at which the CVD becomes smaller than the minimum plus one standard deviation, denoted l. A similar criterion, the "one-standard-error" rule, is presented in  [43]  and is implemented with the MATLAB function lassoglm. Conjoint optimization. Gathering data from N participants enables the selection of the lambda values conjointly. Rather than estimating N distinct optimal hyperparameters, we can select a single value l to apply to all models. Considering the sum of the individual CVDs enables the derivation of two optimal lambda values for the group identically as performed above (with the standard deviation estimated over the group of participants' CVDs).
Statistical tests were performed on the z-scored individual ACIs. In both cases, the tests involved as many comparisons as there are parameters in one ACI (4,374 in our case); therefore, it is important to correct for multiple comparisons  [44]. When comparing ACIs between two conditions, we used a cluster-based non-parametric test. This statistical procedure, originally developed to analyze neuroimaging data  [45] [46] [47] , allows the correlation inherent to the natural images to be taken into account (i. e. , each pixel depending on the values of the adjacent pixels). Statistical analyses were conducted using FieldTrip, an open-source MATLAB toolbox developed for processing electrophysiological data  [48]. The test is performed at two statistical levels. First, a running paired t-test is performed on all participants and compares weights at each time-frequency bin between the two conditions of interest.
8B. Whereas the accuracy of individual estimates decreases steadily with a decreasing number of trials involved in the estimation, the mean ACI for all 16 participants in total remains high (r>0. 75) until approximately 3,000 trials (the estimation noise being reduced by the averaging). Overall, the data collected from 16 participants enable the number of trials required from each participant to be reduced to approximately 3,000 by selecting the lambda value conjointly and considering the mean image for all participants. More importantly, this multi-participants study offers the opportunity to apply statistical tests at the group level rather than at the individual level. Future directions. Here we have described a new methodology to investigate the way in which the human speech perception system achieves fast and efficient categorization of phonemes in noise.
Funding: LV is funded by a PhD grant from the  Ecole Doctorale Neurosciences et Cognition  (http://nsco. universite-lyon. fr/),Lyon-1 University, France. This research was partially supported by a  European Research Council  (http://erc. europa. eu/)grant for the  SpiN  project (No. 209234 ) attributed to FM and by a public grant overseen by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" program  (reference:  ANR-10-LABX-0083 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Bursts were evoked either by injecting 5 ms depolarizing current pulses sufficient to evoke a single action potential in one neuron in current-clamp mode or by a 5 ms depolarization to 0 mV in voltage-clamp mode. Network burst duration was estimated empirically as the time from the onset of the evoked action potential generating the burst to the time point when the falling phase of the polysynaptic current (PSC) crossed the threshold (at half of the averaged PSC amplitude). Signals were amplified with a Multiclamp-700B amplifier and recorded with Clampex 9. 2 software (Axon Instruments, Union City, CA). Experiments were approved by the Weizmann Institutional Animal Care and Use Committee in accordance with EU directives Protocol Number:02740413-2 Electrophysiology in acute brain slices Experiments were carried out according to the guidelines of the European Community Council Directives of January 1st 2013 (2010/63/EU) and were approved by the local animal welfare committee (certificate A751901, Ministere de l'Agriculture et de la Peche).
3 mM while MgSO 4 was increased to 2. 5 mM. Recordings were acquired with Multiclamp-700B amplifiers, digitized at 10 kHz, filtered at 2 kHz, and stored and analyzed on a computer using pClamp 10 and Clampfit 10 software. All data are expressed as mean ± SEM. Statistical significance for comparisons was determined by Student's paired t-test. Picrotoxin was obtained from Sigma and CNQX was from Tocris. All simulations were run with Matlab. The computation of the reverberation time is presented in the S1 File.