dataesr/scientific-paragraphs-categorization huggingface dataset:
c SEC profiles of mb-PMCA products generated with 127S seeds at different dilution factors, as indicated. Thirty minutes after the last sonication, the amplified products were solubilized and SEC-fractionated. The mean relative levels of PK-resistant PrP Sc per fraction were obtained from the immunoblot analysis of n = 3 independent fractionations of PMCA reactions. Note the formation of at least two distinct set of assemblies as function of seed concentration distribution variation as a function of time showed bimodal behavior, as was experimentally observed (Fig. 7a ). Furthermore, the theoretical size distribution centroid presented similar sigmoidal patterns to those of the experimental data (Fig. 7b ), arguing in favor of an autocatalytic kinetic model describing the overall quaternary structure evolution of PrP Sc assemblies during the quiescent phase.
Nitrocellulose membranes were probed for PrP with 0. 1 μg/ml biotinylated anti-PrP monoclonal antibody Sha31  59. Immunoreactivity was visualized by chemiluminescence (ECL, Pierce or Clarity, Bio-Rad). The protein levels were quantified with ImageLab software after acquisition of chemiluminescent signals with a Chemidoc digital imager (Bio-Rad, Marnes-la-Coquette, France). For all SDS-PAGE analyses, a fixed quantity of human recombinant PrP was employed for consistent calibration of the PrP signals in different gels. To improve the sensitivity of the western blot detection method for the samples containing low levels of PrP res (e. g. , samples at early stage of replication and SEC fractions) a double-deposit was made to electro-concentrate the sample. Typically, after a first round of sample loading in SDS-PAGE wells, a short migration time was performed to allow running within the acrylamide gel for 2 mm.
The ordinary differential equations of the biochemical reactions 1-6 (in the manuscript) were established and coded in MATLAB for simulations. Statistics and reproducibility. The SV and SEC experiments reported here result from at least three independent experiments (biological repeats). For SV fractionation of in vivo brain material, pools of three brains collected at different time points were used to minimize individual brain-to-brain variations. At least three independent fractionations were done using these pools. For fractionation of in vitro material, a new batch of mb-PMCA amplified products was prepared for each fractionation. The 127 S mouse bioassay was done with n = 5 mice per group at two different dilutions to ensure statistical significance with this fast prion model, while keeping the number of mice as low as possible for ethical reason.
Acknowledgements We thank the staff of the  Animal facility  ( INRA-UEAR, Jouy-en-Josas ) for animal care. This work was supported by grants from the  Fondation pour la Recherche Médicale  (Equipe FRM  DEQ20150331689 ), the  European Research Council  ( ERC Starting Grant  SKIPPERAD, number  306321 ), and the  Ile de France region (DIM MALINF).
Animals This study was performed on 2 females (M1-M2) Macaca fascicularis (CRP, Port Louis, Mauritius), weighing from 6. 3 and 7. 3 kg. All studies were carried out in accordance with European Communities Council Directive of 2010 (2010/63/UE) as well as the recommendations of the French National Committee (2013/113). The authorization (#00132. 01) for conducting our experiments was approved by the Committee on the Ethics of Animal Experiments (#04). All experimenters received proper training and certification for animal experimentation. Every effort was made to minimize animal's suffering while maximizing the data obtained. Before surgery, in order to minimize stress, the NHPs were progressively trained to stay on a primate chair.
Data analysis Isolation of the ANT single-unit activity was performed using a template-matching algorithm (Spike 2; CED Software) to evaluate the firing rate (FR). Semiautomatic isolation of interictal HPC event was was performed using a template-matching algorithm and systematically verified and corrected on the basis of the quality of the event waveforms and by principal components analysis. A peristimulus histogram (PSTH) was performed for every neuron in order to evaluate the change of the ANT FR in correlation with the interictal events in the HPC (Spike 2; CED Software). Time-frequency analysis of LFPs was performed from collection of seizures recorded in each NHP (49 seizures from 7 experiments for M1, 33 seizures from 5 experiments for M2). Seizures were selected so that they contained no artifact throughout their duration, which was comprised between 6 s and 135 s (average duration: 35.
82 ± 13. 71 s). The first and last spikes of each discharge were used to define its onset and termination, respectively. Time window of analysis started 20 s before the seizure onset and finished 10 s after seizure termination. The amplitude (square-root of power spectral density) of oscillatory activity between 0. 4 and 90 Hz was obtained using standard timefrequency analysis based on the Morlet wavelet transform computed using the ImaGIN toolbox (https://f-tract. eu/software/imagin/) based on Matlab software (The Mathworks, USA) and SPM toolbox (http://www. fil. ion. ucl. ac. uk/spm). For each frequency, the amplitude was computed on 40 periods length sliding time-window. Time-frequency sampling of the time frequency plane was 49 ms / 1Hz. Time-frequency data were normalized using the standard procedure: for each frequency, the mean of the baseline (periods of at least 10 s without interictal spikes chosen prior to each seizure) was subtracted to the data and then demeaned data were divided by the standard deviation of the baseline.
Baseline was defined for every seizure as a period of at least 10 s without interictal spikes chosen just before seizure onset. Finally, the typical time-frequency pattern of recorded seizure was defined as the median value over seizures of the normalized time-frequency charts computed as such. Before median averaging, time-frequency charts were resampled linearly on a time scale to normalize seizure duration. The coherence between simultaneously recorded LFP in ANT and HPC was computed with the same software (ImaGIN), which used the cohere. m function of Matlab. For this analysis, the parameters were: frequency resolution of 0. 39 Hz, frequency range from 0. 39 to 90 Hz, time window duration of 5. 12 s (512 time samples), time window step of 0. 1 s. The coherence value varies between 0 and 1, where 0 indicates that the two signals are not related and 1 indicates a perfect relationship.
Statistical analysis For each experiment, the beginning and the end of each seizure were marked and quantified online and, at the same time, a complete clinical description of changes of behavior was performed. Afterwards, another independent observer quantified the ictal events offline. The online and offline measures, obtained by the two independent observers, were then compared, and no differences were detected. Statistical tests were performed using software GraphPad InStat3 (GraphPad Software Inc. , California, USA). A difference was considered statistically significant for a p value < 0. 05. Characterization of the model: For 4 experiments by animal, the mean duration of a seizure, the mean total time spent in seizure and the mean number of seizures were quantified and expressed in mean ± standard deviation.
Present research 1 We report three studies that investigate the construction of affective experience as a function of the sequential presentation of multiple, affectivelycharged, informational inputs. In all studies, the inputs are related to a single judgment target which was presented in the form of a potential reward to win (Studies 1 and 2) or an experience to participate in (Study 3; e. g. Bateman, Dent, Peters, Slovic, & Starmer, 2007; Rottenstreich & Hsee, 2001). Examples include "concert tickets", "a boat trip" and "restaurant dinner". The rewards and experiences were hypothetical in nature, in all three studies. The inputs were descriptive in Studies 1 and 2 (e. g. "there are more tickets sold than there is space", "the tickets are for your favorite band"), but we used validated images from the OASIS database in Study 3  (Kurdi, Lozano, & Banaji, 2017).
Mediation by affect Next, we aimed to demonstrate that affect mediated the differences between the affective input trials and the valuation judgment. In within-subject designs, multilevel mediation modelling is recommended, but it can be difficult to do with more than two  (MacKinnon, Fairchild, & Fritz, 2007)  experimental groups as here. Therefore, we decided to focus on two trials i. e. PP and NN. This contrast has the greatest difference in input affectivity as well as the greatest difference in overall affective experience, allowing us to more directly demonstrate that the change in the judgment valuation is transmitted through affect. We used the "blml" package in R for multilevel mediation  (Vuorre & Bolger, 2017)  and conducted two mediation analyses with the X variable having two levels: PP and NN.
EMG Two muscles were of interest: the corrugator supercilii more active for unpleasant, and the zygomaticus majormore active for pleasant affect  (Larsen, Norris, & Cacioppo, 2003). EMG activity was measured during the presentation of the inputs and was collected using BIOPAC's MP150 hardware with the Bionomadix wireless EMG module (Biopac, Goleta, CA). Instructions by  Fridlund and Cacioppo (1986)  were followed for the positioning of electrodes. Re-usable Ag/ AgCl electrodes were used. No mention of affect or emotion was made. The signal was online filtered with a high pass of 20 Hz and a low pass at 500 Hz at a sampling frequency of 2000 Hz. Offline, the data were rectified and smoothed with a root mean square analysis  (Principe & Langlois, 2011). A 50 Hz notch filter was also applied in order to eliminate any noise that could have emanated from other electrical sources.
Image Acquisition and Statistical Analysis Image acquisition was performed on a Zeiss laser-scanning microscope LSM780 equipped with 63× 1. 32 NA oil-immersion objective for cell culture and 20× or 63× objectives for hippocampal slice imaging. Images of AlexaFluor-stained cells were obtained using the 488 nm band of an Argon laser and the 405, 568, and 647 nm bands of a solid-state laser for excitation. Fluorescence images were collected automatically with an average of two-frame scans at airy 1. Maximum intensity projection of images and plot profiles of immunofluorescence intensity (10 pixels width) were carried out using ImageJ software (NIH). Images are single confocal sections unless the number of z-steps is indicated. The percentage of SST and PV neurons positive for TAG-1, Caspr2, and Kv1.
2 was determined by examining at least 50 neurons on 2 coverslips per condition (wild type, TAG-1 KO and 4. 1B KO mice). 4-z step confocal sections (410 nm) were acquired with the same settings (laser intensity and gain) and maximum intensity projections were generated before analysis. Results were expressed as mean ± SEM of at least three independent experiments. Statistical analyses were performed using the GraphPad Prism software. The data normal distribution was tested using d'Agostino and Pearson's test. The Student's paired t-test or the one-way analysis of variance (ANOVA), followed by Dunnett post hoc test was performed.
MRI image analysis The brain volumes from all animals were analyzed using VivoQuant (v2. 5, InviCRO, LLC, Boston, MA, USA). Brain images were segmented to identify the volumes of the left putamen, right putamen, left caudate nucleus, right caudate nucleus, and the remaining whole brain using the software's Whole Body Atlas Tool; this tool uses a templatedriven volumetrics approach to segment images based on a user-created atlas of known segmented volumes  22. Such a template was created by entering the brain volumes of 6 manually segmented animal brains into the Whole Body Atlas Tool using the group 2 (n=2) and group 3 (n=4) images from Exam 1. The manually segmented brain images and their known volumes were registered to a single exemplary set of images prior to being entered into the atlas.
MRI statistical analysis For volumes acquired during Exam 1, a one-way ANO-VA model was applied to the means of each group and the pooled variance to perform between-group analyses. For volumes acquired during Exam 1 and Exam 2 for groups 3 and 6, within-group analyses were performed using a linear mixed-effects model  23. Both the one-way ANOVA and linear mixed-effects modeling were implemented using the R package autoLDA. P-values below 0. 05 were deemed significant.
Study termination and postmortem examination Necropsy: Food was withdrawn overnight prior to necropsy. Monkeys were weighed and humanely euthanized by intravenous injection of pentobarbital followed by exsanguination. Necropsy consisted of comprehensive gross evaluation and collection and weighing of the brain. Brain weight data were reviewed as absolute weights and weights as a percent of body weight. Brains were fixed in 10% neutral buffered formalin.
3 → m/z 191. 2, 110. 2, and 82. 2 for risperidone; m/z 427. 2 → m/z 207. 0, 109. 9, and 81. 9 for paliperidone; and m/z 329. 2 → m/z 162. 1 for the internal standard (IS). MS data acquisition and peak integration was performed using the Sciex Analyst 1. 6. 2 and MultiQuant 3. 0. 1 software, respectively. The concentrations of risperidone and paliperidone were determined within Watson LIMS version 7. 4. 1 using linear 1/x 2 weighted regression.
The increased GFAP staining was not observed at the end of the treatment-free period. ment in healthy monkeys, as determined by histomorphology evaluation, may be too minimal to be captured by MRI analysis. Therefore, the value of routine structural MRI as an appropriate tool to monitor the striatum of the brains of preclinical species, in the context of the development of antipsychotic drugs, may be limited. In humans, rats, and dogs, risperidone is metabolized to the active metabolite 9-hydroxy-risperidone (also known as paliperidone) through alicyclic hydroxylation at the 9-position of the tetrahydro-4H-pyrido[1,2-a]-pyrimidin-4-one moiety as the main metabolic pathway. Paliperidone is the main metabolite in plasma  27, 28. Data on the pharmacokinetic profile of risperidone in rhesus monkeys are limited.
This work was funded by Merck Sharp & Dohme Corp. , a subsidiary of Merck & Co. , Inc. , Kenilworth, NJ, USA. Authors and others employed by the sponsor contributed to study design, collection, analysis, and interpretation of data; writing of the report; and in the decision to submit the article for publication. All authors contributed to study conception, design, and planning; GF, CH, SK, JM, and FP acquired and analyzed data; and GF, CH, SK, FP, and TF interpreted the results. GF, CH, SK, JM, FP, TF, and RB contributed to drafting and reviewing the manuscript; all authors critically revised the manuscript for important intellectual content and approved the final version of the manuscript. This work was supported by Merck Sharp & Dohme Corp. , a subsidiary of Merck & Co. , Inc. , Kenilworth, NJ, USA.
Acknowledgments: The authors thank the following  MSD  colleagues for their valuable contributions to this research project:  Amy McCue ,  Joseph Knox ,  Claudette Lazarus ,  Tracy Strowger , and  Dawn Toros  in the  Toxicological Sciences laboratory  for their support of the dosing, formulation preparation, data collection, and imaging procedures;  Brian McCullough  for coordination of all pathology activities;  Caron Leach ,  Phil Manfre ,  Tara McNutt , and  Christine Reichard  for their efforts in the immunohistochemical/histochemical staining of brains; and  Jason Flor  for capturing the photomicrographs.
Role of the Funding Source: This work was funded by Merck Sharp & Dohme Corp. , a subsidiary of Merck & Co. , Inc. , Kenilworth, NJ, USA. Authors and others employed by the sponsor contributed to study design, collection, analysis, and interpretation of data; writing of the report; and in the decision to submit the article for publication. All authors contributed to study conception, design, and planning; GF, CH, SK, JM, and FP acquired and analyzed data; and GF, CH, SK, FP, and TF interpreted the results. GF, CH, SK, JM, FP, TF, and RB contributed to drafting and reviewing the manuscript; all authors critically revised the manuscript for important intellectual content and approved the final version of the manuscript. This work was supported by Merck Sharp & Dohme Corp. , a subsidiary of Merck & Co.
Cepheid studies do not always clarify how the v rad were computed. Furthermore and most often, the template used to crosscorrelate the spectra is not described or provided, except in very few cases  (Brahm et al. 2017). However, given the context developed above, authors should always make clear what spectral lines were used to derive the v rad and how the v rad were computed, as stressed by  Anderson (2018). We present here a consistent spectroscopic survey of 64 Classical Milky Way (MW) Cepheids. It includes for each target the CCFs, various line profile observables, and several v rad time series built from different correlation templates and computation methods. In Sect. 2, we describe our Cepheid sample, the observations performed and the data used in this study. We introduce the principles of our framework and the main outputs in Sect.
HARPS - We collected more than 400 archive spectra obtained with the High-Accuracy Radial-velocity Planet Searcher spectrograph mounted on the 3. 6m telescope at La Silla observatory 1 http://atlas. obs-hp. fr/sophie/. 2 http://archive. eso. org/wdb/wdb/adp/phase3_main/ form (HARPS,  Pepe et al. 2002). The HARPS spectrograph has the highest spectral resolution (R ∼115 000) and the best v rad precision among all spectrographs currently implemented in our framework (Table  1 ). This highlights the importance of these data. We already presented most of these spectra in previous studies  (Nardetto et al. 2006 (Nardetto et al. , 2007 (Nardetto et al. , 2009)). We retrieved the remaining spectra from the ESO database.
FEROS - We finally retrieved almost one hundred FEROS spectra from the ESO public database. The FEROS instrument is a fibre-fed spectrograph mounted on the 2. 2m MPG telescope at La Silla Observatory with a spectral resolution of R ∼48 000  (Kaufer & Pasquini 1998). The FEROS data allowed us mostly to add three medium-to long-period Cepheids to our sample (UZ Cet, AV Sgr and V340 Ara, see Table  A. 1).
Standardising the spectra The main inputs of our framework are high-resolution spectra, pre-processed using the dedicated instrument pipelines. They are in a one-dimensional (1D) format (i. e. wavelength versus flux; typically the s1d format produced by ESO spectrograph data reduction systems or DRS), with the spectral orders already reconnected and re-sampled in wavelength. We chose the 1D format because it is a default product of the DRS of all the instruments included in this study, contrary to the 2D (e2ds) format which is not produced for UVES and FEROS to our knowledge. Furthermore, using the spectrum 1D format instead of the 2D format allows us not to have to correct for the instrumental response by spectral order (i. e. the blaze function), which would otherwise oblige us to introduce additional processing steps that might be less consistent from instrument to instrument.
Building tailored correlation templates This step forms the focal point of our approach. Indeed, we use our custom correlation templates to cross-correlate all observed spectra on a given wavelength range regardless of the target and of the spectrograph. We illustrate our template building process in Fig. 3  and we display the main properties of our templates in Table  2. To build our templates, we first generated a reference Cepheid synthetic spectrum over our three wavelength ranges. To do so, we used the radiative transfer PHOENIX code  (Hauschildt & Baron 1999 , 2010). PHOENIX is a non-Local Thermodynamic Equilibrium (nLTE) atmosphere model code, that uses spherically symmetric radiative transfer in the case of giant stars such as Cepheids  (Hauschildt et al. 1999). In terms of stellar physics, we adopted solar metallicities, which are suitable for Classical MW Cepheids with typical spectral types in the F8 to G5 range.
van Leeuwen, F. 2007 , Astronomy & Astrophysics, 474, 653 Vasilyev, V. , Ludwig, H. -G. , Freytag, B. , Lemasle, B. , & Marconi, M. 2017 , A&A, 606, A140 Wesselink, A. J. 1946, Bull. Astron. Inst. Netherlands, 10, 91  Appendix A: Detail of our Cepheid sample Table A. 1. Detail of our Cepheid sample. Columns 2 to 4 give the pulsation period P, the yearly period drift dP/dT (if known) and the adopted reference epoch for period phasing T 0. Column 5 indicates if the target is a clear (singlelined) spectroscopic binary based on its v rad (y) or if there is some v rad scatter (s) that make it a possible SB1 (based on the present data only; other Cepheids in the list are known binaries but with no significant effect on our present v rad time series). In case of a SB1, column 6 gives the most recent reference providing the best companion orbital parameters, if any.
CCF biGaussian fit -As done with the Gaussian model, we fit the CCF core with a five-parameter biGaussian function (B): B (v rad ) = C 2g ×       1 -D 2g exp (-4 ln 2 (v rad -RV cc-2g ) 2 F 2 i )       where F i = F L if v rad < RV cc-2g (equivalent to the FWHM of a Gaussian model of the CCF blue wing) and F i = F R if v rad > RV cc-2g (FWHM of a Gaussian fitted to the CCF red wing). Other parameters (continuum, depth, v rad ) are analogous to the Gaussian ones. We point out that our biGaussian model is slightly different from the one used by  Nardetto et al. (2006) , as the radial velocity RV cc-2g is one of the free parameters. For both the Gaussian and biGaussian fits, we use a non-linear Least-Square method as implemented in the curve_fit function of the scipy. optimize Python package.
2018). Such v rad precision makes sense e. g. for exoplanet surveys around (generally) nonpulsating stars, for which the CCF can be properly fitted with a Gaussian model. However, Cepheids (and other radially pulsating stars) pose a different kind of challenge, due to the Cepheid v rad accuracy being strongly dependent on the correlation template and the v rad computation method used. We decided here to compute our v rad (and other line profile observable) uncertainties based on our CCFs and their character- For each plot, the data that we obtain from the cross-correlation of the δ Cep HARPS-North (1D) spectra with the G2 template adapted to our green wavelength range (see Sect. 4. 5. 2) are plotted against the corresponding observables retrieved from the available DRS data (automatically produced from the 2D spectra and the default G2 template).
Acknowledgements. The authors acknowledge the support of the  French Agence Nationale de la Recherche (ANR)  under grant  ANR-15-CE31-0012-01  (project  UnlockCepheids ). WG and GP gratefully acknowledge support from the  Chilean Centro de Astrofisica y Tecnologias Afines (CATA) BASAL  grant  AFB-170002. WG also acknowledges support from the  Chilean Ministry of Economy, Development and Tourism's Millennium Science Iniciative  through grant  IC120009  awarded to the  Millenium Institute of Astrophysics (MAS). The research leading to these results has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (grant agreement No. 695099 ). The Swiss 1. 2m Euler telescope and the CORALIE spectrograph are supported by the  Swiss National Science Foundation.