dataesr/scientific-paragraphs-categorization huggingface dataset:
7 , three mice were used to assess the threshold of functional hyperaemia and three mice were used to assess response reliability over days. Statistical tests. Sample sizes were chosen to be consistent with previous studies  20, 46. Exponential fits of the odour concentration vs. neuronal Ca 2+ plots (insets Fig. 3 ) were performed with IGOR 4 (Wavemetrics Inc. , Lake Oswego, Oregon). We tested the validity of every fit that properly converged to a minimum of the optimization function (least-square method) by verifying that every coefficient was statistically different from zero with a confidence level of 95% (value > 2*SD). Linear fits of the input/output distributions within each imaging technique were computed in Matlab and the degree-of-freedom adjusted coefficient of determination (R 2 adj ) calculated for each plot (see Fig.
Acknowledgements We thank  E. Chaigneau ,  Y. Goulam-Houssen  and  B. Djemai  for technical support along with  Etienne Audinat , and  Philippe Ascher  for their critical comments. We thank  Christophe Pouzat  for assistance with statistical analyses and  Charlie Demene  for assistance with fUS analyses. Financial support was provided by the  Institut National de la Santé et de la Recherche Médicale (INSERM) , the  European Research Council  ( ERC-2013-AD6 ;  339513 ), the  Agence Nationale de la Recherche  ( ANR/NSF 15-NEUC-0003-02  and  NR-16-RHUS-0004  [ RHU TRT_cSVD ]), and the  Fondation Leducq Transatlantic Networks of Excellence program  ( 16CVD05 , Understanding the role of the perivascular space in cerebral small vessel disease). R. L. R. had a postdoctoral fellowship award from  EMBO  ( ALTF 384-2015 ).
Note that the estimation of a full AR model is usually limited to the number of nodes with available information in the network. In neuroscience, the variables of the AR model represent different brain units or regions, where the time-series are the recordings (e. g. EEG, fMRI, MEG) of these areas. However, the measurement of all the elements of the circuit is generally unfeasible and the inferred AR model is constrained by the data. These unknown or unrecorded variables introduce a confounding effect in the AR that may drastically affect the estimation of the functional connectivity  41, 44. Several algorithms and methods can be used to compute GC, including different statistical analyses to check both the AR model and the result of the analysis  23, 45, 46. In this paper, we used the Matlab toolbox recently proposed by Barnett and Seth  23  , which overcomes some limitations of previous toolboxes  47  , including the estimation of GC with a single full regression.
2. 3-Statistical significance To assess the statistical significance of the defined index, the whole time-series were divided into time windows of the same length, being the main condition that the variables within these windows are covariance stationary  48  (i. e. , they have constant mean and variance). If the data is acquired in an event-related task, i. e. , the response to a stimulus is recorded, the fast changes of the signal may exhibit nonstationary epochs in each repetition. An adaptive multivariate AR model can be employed in those cases  49  , where a single model is achieved based on the entire data set. Furthermore, the interaction between brain regions is time-varying. This means that a single model cannot reproduce the behaviour of the network. New algorithms involving the estimation of time-variant AR models have been developed to overcome that limitation and contribute to the study of the dynamics in brain connectivity  50.
The sGC was assessed as the average of the sGC over all windows. The window length was fixed to 5 seconds in this work. To estimate the statistical significance associated to the sGC, we used a surrogate data analysis ( = 2000 in this work) by block-resampling, where each signal was cut at a random time point and the blocks were permuted. The size of the blocks was the same as that of the segments used for the estimation of the sGC, so that the difference between the surrogates and the original data, if any, could not be attributed to the different number of samples in each case. The block shuffling procedure has the advantage, unlike the phase reshuffling one, to preserve the possible relationship among the phases within each time series, which is known to be a confound when using surrogate data to estimate the existence of correlation between two data sets  51.
The significance was then assessed, as usual, by comparing the value obtained from the original data with the distribution of the values obtained from the surrogates. For this, the normality of the distribution was firstly confirmed using the Kolmogorov-Smirnov test, estimating its associated mean and standard deviation. Finally, the p-value was obtained by evaluating the surrogated cumulative distribution at the sGC original value. Note that an optimal strategy would be to generate a surrogate data set with the same GC as the original time series but with balanced excitatory and inhibitory interactions. As this situation is unpracticable without knowing the specific anatomical structure of the recordings, what we tested was the error induced in the estimation of the  coefficients with signals of common properties, with the same amplitude and frequency as the original signals but without a G-causal link.
2. 5-Electrophysiological recordings To test the proposed methodology in real brain signals, we used a dataset of hippocampal electrophysiological recordings in rats  40. Briefly, a total of N = 5 animals were implanted with a multichannel electrode along the dorsal hippocampus. For each subject, we selected three LFP signals, recorded at the stratum radiatum and stratum lacunosum-moleculare in CA1 and one in the dentate gyrus (DG), with the animal freely moving in an open field for 10 minutes. These layers have specific patterns of activity largely contributed by inputs from different afferent pathways to the CA1 region, including the Schaffer collaterals from CA3 to the str. radiatum, the layer III of the entorhinal cortex (EC) to the str. lacunosum-moleculare  57, 58  and the layer II of the EC to the DG through the performant pathway  57.
They were firstly identified using their electrophysiological activity, with the presence of sharp-waves in str. radiatum and a maximal theta activity in str. lacunosum-moleculare and the inversion of the theta rhythm in the DG. The location of the electrodes was further verified post-mortem with the histological analysis. The data was acquired at 5 KHz, high-pass filtered at 0. 5 Hz to remove the continuous component and Notch-filtered at 50 and 100 Hz to remove the net noise and its first harmonic. For the analysis, the data was downsampled at 250 Hz after low-pass filtering at 250 Hz to avoid aliasing.
Furthermore, previous works have demonstrated the utility of AR models to observe positive and negative couplings in fMRI  61. This methodology generally estimates an order-1 model to compute the GC, identifying "excitatory" or "inhibitory" pathways based on the sign of the only coefficient extracted. However, several limitations, e. g. , the invariable model order  62  , have prevented their application to datasets with quite diverse time scales. Our approach overcomes these issues, as it considers all the significant coefficients without prior restrictions of model order, proposing a generic methodology that can be extrapolated to every GC study. Moreover, we have proposed two strategies to mitigate the effect of artefactual parameters included in the AR models, by imposing zero constraints to those elements that are not significantly contributing to the prediction.
First, it must be considered that LFP signals are affected by volume conduction that may create spurious correlations between recordings  63. Second, the multivariate AR model allows the discrimination of direct and indirect links between the signals included in the model as long as all the relevant links are represented. Therefore, this limitations needs to be considered when applying these methods to a particular dataset  41. Moreover, the GC is also sensitive to the signal-to-noise ratio of both time-series  64  , thus, the high theta power in LM may be affecting the prediction on RAD and DG. With these limitations in mind, we interpret the sGC results as follows: the activity reaching the distal part of the dendrites of CA1 pyramidal neurons from the EC (LM) positively interacts with the inputs arriving downstream in the dendrite from CA3 (RAD).
We have tested this proposal in a theoretical paradigm to demonstrate its efficacy, but several aspects need to be considered to prevent misinterpretations. First, in order to be interpretable, the polarity of the used signals needs to be known. The polarity of the simulated currents in our model is known, yet it is more difficult to establish in most of the LFP and EEG recordings  63, 67. Therefore, the sign of the GC in these datasets might not be directly interpreted as a readout of excitation and inhibition. Secondly, some conditions such as signal non-stationarity and non-linearity were not considered in this work but might be present in biological signals. Recent implementations of GC overcome these issues  49, 68, 69  , opening the possibility to implement sGC concepts on these indices.
datasets and Dr. Daniele Marinazzo and Dr. Simona Obreja for providing useful comments on the manuscript. This work was supported by the Spanish Ministry of Economy and Competitiveness (Project Nos. TEC2016-800 63-C3-3-R, TEC2016-80063-C3-2-R, and BFU2015-64380-C2-1-R), the European Union through the Horizon 2020 programme (Grant Agreement No. 668863, SyBil-AA), the Spanish State Research Agency (SEV-2013-0317), the Brazilian Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Grant Nos. 88881. 120309/2016-01 and 88881. 068077/2014-01), the Brazilian Conselho Nacional de Desenvolvimento Cientìfico e Tecnològico (Grant No. 432429/2016-6) and the US National Science Foundation (grant NSF IIS-1515022). V. J. L. was supported by a predoctoral fellowship La Caixa-Severo Ochoa from Obra Social La Caixa.
ACKNOWLEDGMENTS This Research Topic is one of the two special issues dedicated to RegPep2018, whose co-chairs (LZ and LE) express gratitude for generous support from the  School of Medicine  of the UNAM, through  Dean Dr. German Fajardo ,  Secretary General Dr. Irene Durante ,  Chief Administrative  and  Legal officers Lics. Luis Arturo Gonzalez Nava , and  Luis Gutierrez. We thank the  Mexican Academy of Sciences , the  International Brain Research Organization , the  British Society for Neuroendocrinology, and Elsevier  for their generous support. RegPep2018 was also supported by  CONACYT-292881 ,  CB-238744 , and  IN216918. LE acknowledges the support of  NIMH-IRP  through  MH002386. DV acknowledges the support of  INSERM  ( U1239 ),  Rouen University , and  Normandy Region and European Union (ERDF).
If the latter undergoes a nn-division, it will produce two neurons of generation 2, so in the end the content of the clone after Work in FP's laboratory is supported by the Centre National de la Recherche Scientifique, Université P. Sabatier, Ministère de L'Enseignement Supérieur et de la Recherche (MESR), the Fondation pour la Recherche sur le Cancer (ARC; PJA 20131200138) and the Fédération pour la Recherche sur le Cerveau (FRC; CBD_14-V5-14_FRC). Work in JG's laboratory is supported by the Centre National de la Recherche Scientifique, Université P. Sabatier, Ministère de L'Enseignement Supérieur et de la Recherche (MESR), the Agence Nationale de la Recherche (ANR-15-CE13-0010-01). Manon Azaïs is recipient of MESR studentships. Angie Molina is a recipient of IDEX UNITI and Fondation ARC.
The evolutionary advantage for those phylogenetically distant species of having conserved the N-terminal hydrophobic domain represents one puzzling unsolved issue. Although they were isolated more than 20 years ago  (10) , technical limitations impeding the production of sufficient quantities of big defensins have precluded investigations on their structure and antimicrobial activities and of the roles of their respective domains. Sufficient amounts of native Tt-BigDef were obtained from horseshoe crab hemocytes to determine its 3D structure (Protein Data Bank [PDB] identifier: 2RNG), which remains the only one solved to date. Tt-BigDef is tightly packed in solution: the hydrophobic N-terminal domain adopts a ␤1-␣1-␣2-␤2 fold, whereas the cationic C-terminal domain shows the cysteine pairing expected for ␤-defensins  (11).
RESULTS Big defensins are mainly found in marine organisms. We performed an exhaustive search for sequences containing a ␤-defensin domain in publicly available genomic and transcriptomic databases. Sequences of ␤-defensins were found in diverse groups of vertebrates (from fish to mammals) and invertebrates (mollusks and crustaceans), whereas big defensins were present in a limited number of species belonging to Lophotrochozoa, Arthropoda, and Cephalochordata (Fig. 1 ). Remarkably, of the 78 obtained distinct big defensins, only one sequence (GenBank accession no. AEP26934) was found in a nonmarine species, the sequence corresponded to the freshwater mussel Hyriopsis cumingii  (21). Mollusks (Lophotrochozoa) represented the superphylum containing the highest diversity of big defensins by far (see Fig.
S1  in the supplemental material). Multiple-sequence alignments revealed a canonical conserved motif but differently spaced cysteines for big defensins [Cys-Xaa (4 -14) -Cys-Xaa (3) -Cys-Xaa (13-14) -Cys-Xaa (4 -7) -Cys-Cys] and ␤-defensins [Cys-Xaa (4 -6) -Cys-Xaa (3-4) -Cys-Xaa (7-12) -Cys-Xaa (5-7) -Cys-Cys] (Fig. 1 ). The two defensin families also differed by the presence of a hydrophobic N-terminal domain (20 to 64 residues) in big defensins only (Fig. 1 ). This domain, which contains some highly conserved amino acids (Fig. 1 ), does not show any homology with sequences present in public databases outside big defensins. Native chemical ligation-based chemical synthesis gives access to the exploration of multiple-domain Cg-BigDef1 structure and activity. To explore the role of the ancestral N-terminal domain in big defensin structure and activity, we focused on the mollusk big defensin Cg-BigDef1 (GenBank accession no.
CFU were then counted by plating at 10, 20, 30, 60, and 120 min. In this assay, the limit of detection was 100 CFU/ml. (B) Membrane permeabilization of S. aureus SG511 was measured by the Sytox green assay. Bacteria were exposed to 1. 25 or 10 M Cg-BigDef1 or an equal volume of water (control). Data are represented as percentages of permeabilized bacterial cells relative to complete cell lysis with Triton X-100 as a positive control. In both assays, standard deviations were calculated using results from three independent experiments.
MATERIALS AND METHODS Database searches and sequence analysis. Sequences containing the ␤-defensin domain were collected from publicly accessible databases and were used for the search of homologous sequences in both annotated and nonannotated databases (tBLASTx at NCBI). All obtained sequences were manually inspected and translated using the ExPASy Translate Tool (http://web. expasy. org/translate/). Predictions of signal peptides and furin-like cleavage sites were performed with the ProP 1. 0 Server (http://www. cbs. dtu. dk/services/ProP/). Multiple alignments of the deduced amino acid sequences were generated using the MAFFT program (https://mafft. cbrc. jp/alignment/server/). Chemical synthesis. Peptides were synthesized by solid-phase peptide synthesis on a Prelude peptide synthesizer (Gyros-Protein Technologies) using standard Fmoc/tBu chemistry at the 25-mol scale starting from a Tentagel resin equipped with a Rink's amide linker and including automated introduction of the N-2-hydroxy-5-nitrobenzyl (Hnb) group trough on resin reductive amination  (22).
1 H chemical shifts were referenced to the water signal (4. 77 ppm at 298 K). NMR data were processed using Bruker's Topspin 3. 2 and analyzed with CCPNMR software (version 2. 2. 2)  (46). Structures for both proteins were calculated using the Crystallography and NMR system (CNS) suite  (47, 48)  through the use of ARIA2 automatic assignment software (version 2. 3) (49) with NOE derived distances and hydrogen bonds and three ambiguous disulfide bridges. For Cg-BigDef1  [44 -93] , backbone dihedral angle restraints were added (determined with the DANGLE program  [50] ). See detailed protocol in Text S1 in the supplemental material. Strains and media. Strains and media are listed in Table  S3  in the supplemental material. Marine strains from the genera Aliivibrio, Corynebacterium, Microbacterium, and Vibrio were grown at 20°C in liquid Zobell 1/3 medium.
CFU counts were performed by plating on LB agar plates at the indicated times. Data are expressed either as CFU per milliliter or as a percentages of killing compared to untreated samples. Tests were performed in triplicate, and mean values were calculated. Membrane permeabilization assay. Stationary-phase cultures of S. aureus SG511 grown at 37°C in LB medium were washed and resuspended at 10 9 CFU/ml in 10 mM phosphate-buffered saline (PBS), supplemented with 138 mM NaCl and 2. 7 mM KCl; pH was adjusted to 7. 4 before addition of 1 M Sytox green. Bacteria (100 l) were dispensed into 96-well microtiter plates containing 10 l Cg-BigDef1 (10 M or 1. 25 M final concentration), water (negative control), or Triton X-100 (0. 1% final concentration; positive control). Fluorescence was measured every 5 min over 4 to 6 h ( excitation [ex] ϭ 480 nm; emission [em] ϭ 550 nm) at 20°C.
ACKNOWLEDGMENTS This work received financial support from  Vaincre la Mucoviscidose  ( Big-Def  project),  CNRS PEPS X-life  ( DefenSel  project), and  Air Liquide Foundation. C. Barreto  and  R. D. Rosa  were funded by  CNPq  ( PVE 401191/2014-1  and  Universal   406530/2016-5 ). We thank  A. Masnou ,  C. Ossun ,  E. Robino , and  G. Charrière  ( University of Montpellier ) for precious help in microbiology and confocal imaging. We thank  N. Bierne  ( CNRS, Montpellier ) and  G. Charmantier  ( University of Montpellier ) for fruitful discussions. We thank  P. C. Morand  ( Hôpital Cochin, Assistance Publique-Hôpitaux de Paris ) and  F. Le Roux  ( Ifremer, Roscoff ) for microbial strains. We thank the staff members of the Montpellier RIO imaging platforms (https://www. mri. cnrs. fr)and  C.
Heart rate measurements and statistical analyses For each group, we calculated the heart rate from five one-minute long sequences that were randomly selected along the 10 minutes recording time. Heartbeats were counted for each of these one-minute sequences. Heart rates (heartbeats/minute) were averaged within and across individuals. For measurements made during feeding, sequences were chosen with taking care of excluding the probing phase  (Friend and Smith, 1971, 1977). After assessing the normality of the data distribution, a two-way ANOVA was performed using R (R Development Core Team, 2017) followed by a Tukey post-hoc test.
Acknowledgments We are indebted to  Carole Labrousse  for her technical support in Rhodnius prolixus rearing. We are very grateful to  Clément Vinauger  and  Teresita Insausti  for their valuable comments on the manuscript and helpful discussions. This work received financial support from the  Agence Nationale de la Recherche  (grant  ANR-08-MIE-007 , EcoEpi), the  Centre National de la Recherche Scientifique , and the  University of Tours (France).
A conditioning cell (5020, ESA) was placed before the manual injector and set at +450 mV. Then, after the column, two coulometric cells (5011, ESA; two electrodes each) were placed in series, each cell being connected to one coulometric detector (CoulochemII, ESA). The potential at the four electrodes was as follows: +125, +350, +500, and -300 mV (reduction). The detectors were connected to the CED 1401 interface (Cambridge Electronic Design Ltd. ), and signals were acquired using the spike 2 software (Cambridge Electronic Design Ltd. ). B. Chromatograms (mV as a function of time, in minutes) obtained for each electrode for different groups of molecules: First column (B1,B2): L-DOPA, NA, adrenaline, DA; second column (C1,C2): NA and octopamine; third column (D1,D2): VMA, DHPG, DOPAC, HVA, 3-MT, and 5-hydroxytryptamine (5-HT).
Acknowledging that some trace amines and L-DOPA derivatives are less sensitive to MAO activity  [35] , the inhibition of MAO could favor the presence of biogenic amines in the vesicles of exocytosis and enhance the predictability of responses to L-DOPA. On the other hand, the increase in newly synthesized DA in the cytoplasm of cells could also lead to enhanced auto-oxidation and raise the presence of reactive oxygen species  [20, 133]. It is now clear that the benefits and side-effects of L-DOPA are multifactorial, and the proper determination of each component, including the direct effects of L-DOPA, is needed. These considerations might be important to better address the full spectrum of metabolic and functional responses triggered by L-DOPA in PD in order to select the best strategies to combat the numerous motor and non-motor side effects.
Methods In order to assess the actions and commentary in this field we conducted searches through PubMed to retrieve a total number of publications containing word CRISPR in their abstracts or in their keywords during the period from 2002 up to 2018 (the search being conducted at the end of February 2019). For the purpose of a focus on the EU-model, data on proposals/projects having CRISPR in the keywords or mentioned in abstracts were received by the courtesy of the Ethics and Research Integrity Sector, Directorate General for Research & Innovation of the European Commission (EC) from the EC statistic tool called 'Corda' (as of the end of January 2019). Data for 2018 are incomplete and thus not fully visible in Corda since the negotiating phase for some proposals applied for in 2018 was still ongoing at the time of this paper submission.
5] [26] [27]  In these mechanisms, chirality is a transient property of whole cell morphology at key points in embryonic development. 24 A role of actin-related genes in establishing cellular chirality has been observed in both invertebrate (Drosophila, snail)  [24] [25] [26] [27]  and vertebrate models (cultured cells, frog, zebrafish),  24, 28, 29  suggesting that this mechanism is important to establish left-right organ asymmetry across bilaterian groups. Apart from the cilia-related nodal signaling pathway, cellular chirality is the only biological mechanism that has been shown to give rise to organ asymmetry in multicellular animals, of which we are aware. Recent analyses using the UK biobank data set, based on more than 300 000 participants, have reported that alleles of the microtubule-associated gene MAP2 have very small effects on the probability of becoming left-handed, as well as some other loci which did not clearly implicate individual genes.
30, 31 However, the rarer trait of RHLD, found in only roughly 10% of left-handers and less than 1% of right-handers, has not been subject to any previous molecular genetic studies. By analogy with SIT, here we investigated whether RHLD might sometimes arise due to high-penetrance genetic mutations. We sequenced the genomes of 33 people with RHLD as assessed using fMRI, as well as 34 typically lateralized subjects (20 right-handed, 14 left-handed) and interrogated the data with reference to large population genetic databases (Figure  1 ). As this was an exploratory study, we performed separate analyses under recessive and dominant models, allowing for allelic heterogeneity (different causative mutations within a given gene) or genetic heterogeneity (causative mutations in different genes).