dataesr/scientific-paragraphs-categorization huggingface dataset:
de novo genome assembly construction and comparison For the UMY321 isolate, a total of three MinION Mk1 runs were performed with the R7. 3 chemistry using 2D library types with 8 kb mean fragmentation size. A total of 115,559 reads, representing a cumulative size of 1. 15 Gb were generated, among which 41,686 2D reads showed an average quality greater than 9 (2D pass reads). We focused on these 2D pass reads, that represent a total of 376. 8 Mb, with the longest read being 70,058 bp (mean = 9,033 bp and median = 8,676 bp) (Figure  S1 ). Four subsets of our 2D pass reads (10x, 15x, 20x of the longest 2D pass reads and all of them) (Table  S1 ) were submitted to four assemblers: ABruijn  (Lin et al. 2016) , Canu  (Berlin et al. 2015) , miniasm  (Li et al. 2016)  and SMARTdenovo (https://github.
com/ruanjue/smartdenovo). As the MinION sequencing technology is known to be associated to high error rates (~10% for 2D pass reads)  (Jain et al. 2016) , we polished the assemblies with Pilon (Walker et al. 2014) using 100x of Illumina paired-end reads. The lengths of the constructed assemblies were all in the same order of magnitude and ranged from 11. 7 to 13. 7 Mb (Table  S2 ). Using these various datasets and assemblies, the objective was to define the best assembler and the minimal coverage needed. Hence, we computed the standard contiguity metrics for all assemblies to evaluate their quality, which is related to both the assembler and the dataset (Figure  1 , Table  S2 ). First, we observed that, considering the results by assembler, the number of scaffolds obtained with the 10x dataset is much higher compared to the other datasets, which suggests that a 10x coverage of MinION reads is too low to obtain a good quality assembly.
5% for the Abruijn and SMARTdenovo assemblies. By comparing standard metrics and the proportion of unmapped reads, the most accurate assembly was obtained with the 20x 2D reads dataset combined with the SMARTdenovo assembler. This assembly is composed of 9 scaffolds, i. e. very close to the estimated number of chromosomes, which appears to vary between 4 and 9 among different strains of this species  (Hellborg and Piskur, 2009) , for a complete assembly size of 12. 97 Mb. This latter was then submitted to SSPACE-longreads, which reduced the number of scaffolds to 8 after grouping the 2 smallest ones, based on our long reads information, and a further Pilon run. The final assembly contains 8 scaffolds and shows a cumulative size of 12,965,163 bp (Table  2 ). We also evaluated the completeness of our assembly at the gene content level by running CEGMA  (Parra et al.
Acknowledgements We are grateful to  Warren Albertin  and  Isabelle Masneuf-Pomarede  for fruitful discussions and invaluable advices. We thank  Jure Piskur  and  Anna Schifferdecker  for generously providing the UMY321, UMY315 and 133 Dekkera bruxellenis isolates. We also thank the  BioImage platform (IBMP-CNRS, Strasbourg)  for their support. This work was supported by  France Génomique  ( ANR-10-INBS-09-08 ), and the  Agence Nationale de la Recherche  ( ANR-16-CE12-0019  to JS). TF and JSG are supported by a grant from the  French "Ministère de l'Enseignement Supérieur et de la Recherche ". JS is a Fellow of the  University of Strasbourg Institute for Advanced Study (USIAS)  and a member of the  Institut Universitaire de France.
Association efficiency of pollutants on PLGA nanoparticles Free versus associated pollutants were separated by centrifugation of the formulations on a 10kDa NanoSep 1 (Pall, France) at 5. 000g for 5 min. The amount of pollutants in the filtrates were quantified by high-performance liquid chromatography (HPLC) using calibration curves of free pollutants. The percentage of association efficiency (AE) was calculated as follows: %AE ¼ theoretical pollutant amount À calculated pollutant in the filtrate theoretical pollutant amount ! Â 100 The chromatographic analyses were performed on an Ultimate 3000 Autosampler (Ther-moScientific, France) and chromatographic data were collected and processed with the Chromeleon software. The analytical column (Accucore aQ C18, 150x3 mm, 2. 6μm particle size) was purchased from ThermoScientific, France.
7 V/cm (25 V/300 mA). After electrophoresis, slides were neutralized for 2 x 5 min in a neutralization solution (0. 4 M Tris, pH 7. 5), and gels were dehydrated by immersion in absolute ethanol for 5 min. Finally, slides were air-dried and stained by addition of 25 μl of propidium iodide (20 μg. ml -1 in distilled water) and a coverslip. Slides were then examined at 250x magnification using a fluorescence microscope (Leica Microscopy and Scientific Instruments Group, Heerbrugg, Switzerland) equipped with an excitation filter of 515-560 nm and a 590 nm barrier filter, connected through a gated CCD camera to Comet Image Analysis System software (version 4, Perceptive Instruments Ltd. , Haverhill, United Kingdom). Four hundred randomly selected cells per condition (100 cells from each of the 2 duplicate slides in the 2 cultures) were scored.
Tail intensity, defined as the percentage of DNA that had migrated from the head of the comet into the tail, was used as the measure of DNA damage. The nonparametric Mann-Whitney U-test was used to evaluate the statistical difference between groups since the tail intensity measurement in the comet assay did not follow a Gaussian distribution  [39]. The Mann-Whitney U-test was also used, for each dose, for the comparison between free and nanoparticle-adsorbed pollutants. Differences with a p<0. 05 were considered statistically significant. All statistical analyses were performed with StatView 1 Software (version 5. 0, SAS Institute Inc. , SAS Campus Drive, Cary, North Carolina 27513, USA).
Determination of the LC50 of the pollutants The LC50 of each pollutant was evaluated by the MTT test on the H292 cells. NA is a common polycyclic aromatic hydrocarbon (PAH) possibly carcinogenic for Humans (IARC class 2B). The LC50 was evaluated at 500μM. B(a)P is a carcinogenic PAH for Humans (IARC class 1) and the LC50 was 50μM. Finally, the LC50 of the endocrine disruptor Di-Ethyl-Hexyl-Phthalate (DEHP), a possible carcinogen for Humans (IARC class 2B), was determined at 150μM (data not shown). These doses were retained for all the following experiments.
The micronucleus test was used to assess the induction of chromosomal damage (clastogenicity and/or aneuploidy). No primary DNA damage was observed while the dose of NA increased from 0 to 500μM and there was no significant difference between free NA and the PLGA(-) NA (Fig  4A ). Similar   4B ). The micronucleus test did not show any chromosomal aberrations upon exposure to free or PLGA(-) NA, even at the highest doses, and no difference was observed between free and nanoparticle-adsorbed NA (Fig  4C ). Together, these data showed that nanoparticle-adsorbed NA is not more cytotoxic nor genotoxic than free NA, and that the vectorization of NA by nanoparticles did not enhance the toxicity of this pollutant.
oryzae strain WAA42, both showed labelling on the membrane of the mesenteric caeca. This result suggests that the V-ATPase and the caspase-3 activity are close-localized and, therefore, apoptotic activity occurs where V-ATPase is present. Upon binding to its receptor, PA1b inhibits the proton pump activity of V-ATPase, thus generating stress in the cell which leads to the induction of apoptosis and insect death. This data reinforces the conclusion that the binding of PA1b to the insect V-ATPase is required to trigger apoptosis. The active form of caspase-3 in the insensitive insect of T. castaneum was investigated. Slight caspase-3 activity was detected only at very high doses of PA1b, and this activity was absent in the control insect midguts. Thus, in the insensitive T. castaneum, it would appear that a molecular mechanism of PA1b toxin sensitivity is present, i.
4, until post-fixation in 1% osmium tetroxide. They were then contrasted in 1% uranyl acetate, dehydrated through an ethanol series and embedded in epoxy resin (Epon). Ultra-thin sections (70 nm) were prepared using a REICHERT Ultracut S ultramicrotome (Leica microsytems) and stained with lead citrate before examination with a Philips CM120 electron microscope. Afterwards, the contrast of the images was optimized using the PlugIn "Enhance Local Contrast (CLAHE)" on ImageJ software  40. Immuno-localization of the caspase-3 and of the V-ATPase proteins. For the immuno-histochemical detection of caspase-3, insect midguts were sampled in dissection buffer (25 mM KCl, 10 mM MgCl 2 , 250 mM sucrose, 35 mM Tris-HCl pH 7. 5). Then, these midguts were impregnated in a 15% saccharose, 5% glycerol, PBS buffer, pH 7.
Screening and data collection Patients first completed a dedicated questionnaire (S1 Appendix) with the assistance of a medical student or a nurse and performed a rapid PFT with a hand-held COPD-6 spirometer. The questionnaire searched for respiratory symptoms (chronic bronchitis, recurrent acute bronchitis, dyspnea), history of hospitalization for respiratory-related conditions, known COPD or chronic bronchopathy, smoking history, use of illicit drugs (cannabis, intra-venous drug use), occupational respiratory exposure and socio-economical status. To characterize COPD, according to recent definitions, COPD frequent exacerbator phenotype was defined as a patient with 2 or more acute bronchitis per year  [1, 21]. Patient-orientated definitions of chronic bronchitis, recurrent acute bronchitis and dyspnea used in our questionnaire had previously been tested for their understandability and validated as conform by pneumologists  [1, 2, 21].
All patients with respiratory symptoms, a previous mentioned COPD or chronic bronchopathy diagnosis, a history of hospitalization for a respiratory-related condition, or an abnormal COPD-6 test, underwent a conventional spirometry performed by a pneumologist (FGdS and KR). Data concerning HIV infection (date of HIV infection, AIDS-defining diagnosis according to Centers for Disease Control and Prevention staging, nadir CD4, CD4 and CD8 cell count within the last 6 months with CD4/CD8 ratio and HIV RNA load, treatment history, previous respiratory opportunistic infections) and comorbidities were collected from the Nadis 1 electronic patient medical record  [22].
Study population characteristics The study's flowchart is presented in Fig 1. We enrolled 623 HIV-infected patients. These patients did not differ from our entire cohort (n = 2453) for age, gender distribution (data not shown), percentage of patients under-ARV therapy (93. 5%), with undetectable viral load (80%) or CD4> 500 (64%). Forty-two patients screened by questionnaire or COPD-6 with an indication to perform a conventional spirometry refused to undergo the exam and were therefore excluded. Characteristics of patients included and excluded in our study are detailed in Table  1. Briefly, 73. 8% of patients were men, mean age was 48 years with a mean duration of HIV infection of 15. 5 years. At the time of the study, 93. 5% of patients were receiving ART, with an undetectable HIV viral load for 85.
Acknowledgments All medical doctors and paramedicals participating in patient enrollment and logistic management during outpatient consultations:  C. Hamille ,  A. Belliard ,  J. Lallement ,  J. Gevers ,  C. Ceppi ,  B. Dunais ,  S. Ferrando ,  V. Mondain ,  S. Pillet ,  B. Provost-Keller ,  B. Oreggia ,  M. Pastorino ,  S. Bloch ,  Marie Danduran ,  David Chirio. K. Risso  and  F. Guillouet-de-Salvador  are members of the « Groupe pour la recherche et l'enseignement en Pneumo-infectiologie » (GREPI).
Bremer Support The most parsimonious tree is not always the true tree. In fact, optimization of the data over a model can result in overfitting. This is a serious bias (see Fig. 2  for a simple illustration of this notion). In classical cladistic analysis, Bremer support of a clade in the most parsimonious tree is the minimum number of extra steps required to draw a near-most-parsimonious tree that does not contain this clade  (Bremer, 1988 (Bremer, , 1994)). In order to evaluate the support of the putative clades,   This software is able to map characters' transformations according to several optimization algorithms (ACCTRAN, DELTRAN or MINF) but a particular branch cannot be directly forced to have a length of zero. However, if we add a new OTU identical to the putative ancestor (here «anc1» has exactly the same character states as G.
However, in both cases it is hard to know if this comes from a real tendency to evolve frequently or from the lack of a precise and reproducible morphometric measure (in which case the dataset should be corrected and re-analysed). The absence of a sporophyte (36) is not a reliable character either; therefore it seems that the loss of sexuality is very easy to evolve in Pottiaceae. Finally, two character transformations are unique to one species each (autapomorphies). These are character 8 for F. subandreaeoides which uniquely have dimorphic leaves, and character 22 for V. nevadense which uniquely have multi-layered photosynthetic cells on the ventral costal surface. These two unique traits strongly indicate that these two species cannot be an ancestral to another one, which is also the case in Zander's analysis (see below).
Character reliability In the dataset, although many characters may be considered quite reliable at about 8 or 10 dB, very few seem to be extremely reliable. Indeed, only three non autapomorphic characters have a weight of 13 dB (see Table  IV ). These are characters 14, 20 and 21, or respectively margin ornamentation of the leaf, the presence or absence of a bulge on the abaxial face, and the presence or absence of a thin-walled pad of cells on the adaxial face. The first one is a synapomorphy defining the large clade made of the genera Vinealobryum, Didymodon sensu stricto, Geheebia, Exobryum and Trichostomopsis, but not Fuscobryum. The second one defines the clade of the genus Didymodon sensu stricto. And the third one defines the clade made of the genus Trichostomopsis and the species V.
First, we created a large dataset of ''musical social scenes", by asking dyads of expert improvisers to use music to communicate a series of relational intentions, such as being domineering or conciliatory, from one to the other. In contrast to other music cognition paradigms which relied almost exclusively on solo monophonic extracts (e. g. , 40 out of the 41 studies reviewed in  Juslin & Laukka (2003) ) or well-known pre-composed pieces  (Eerola & Vuoskoski, 2013) , this allowed us to show that a variety of relational intentions can be communicated in music from one musician to another (Study 1), and that third-party listeners too were able to perceive the social relations of the two interacting musicians (Study 2). Second, by recording these duets in two simultaneous but separate audio channels, we were able to present these channels dichotically to third-party listeners.
Study 2: decoding study In this study, we took the preceding decoding task offline and measured decoding accuracy for a selection of the best-rated duets recorded in Study 1. Because we recorded these duets in two simultaneous but separate audio channels, we were able to present these channels dichotically to third-party listeners, and thus sepa-rate the contribution of acoustical cues coming from one channel from those only available when processing both channels simultaneously. Finally, to test for an effect of musical expertise on decoding accuracy, we collected data for both musicians and nonmusicians.
Stimuli in the CTL+ group were manipulated in order to shift musician B backward in time by a few seconds while preserving the timing of musician A. Because extracts in the CTL+ group corresponded to caring attitudes, the original recordings had a primarily decoder-to-encoder temporal causality (Study 3), with musician A reacting to, rather than preceding, musician B. By shifting musician B backward in time (or, equivalently, shifting musician A ahead of musician B), we intented to artificially reverse this causality by creating situations where musician A was perceived to temporally lead, rather than follow, the interaction. Time shifting was applied with the Audacity software, by inserting the corresponding amount of silence at the beginning of the track. Because the amount of time shifting was small (M = 2.
Finally, stimuli in the AFF-group were manipulated in order to detune musician A by one or more semitones while preserving the tuning of musician B, thus creating artificial dissonance (or decreasing harmonic coordination) between the two channels. Pitch-shifting was applied with the Audacity software  (Team, 2016) , using an algorithm which preserves the signal's original speed. Therefore, the manipulation only affected the interaction's vertical coordination, but preserved both cues of simultaneous playing time and temporal causality, as well as the singlechannel cues of both channels considered separately. See Table  2  for details of the manipulations in the three groups. Procedure: The n = 30 extracts (15 original and 15 manipulated versions) were presented in two semi-random blocks of n = 15 trials, separated with a 3-min pause, so that the two versions of a same recording were always in different blocks.
Acknowledgments The authors wish to extend their most sincere thanks to Uta and  Chris Frith  for their support and feedback at various stages of writing this manuscript. We acknowledge  Emmanuel Chemla  for kindly suggesting the idea behind Study 5, and thank  Hugo Trad  who helped with data collection for Study 2. Finally, the authors thank all the improvisers who participated in Study 1 for their inspiring music-making. All data reported in the paper are available on request. The work described in this paper was funded by  European Research Council  Grant StG-335536  CREAM  (to JJA) and  Conseil Régional de Bourgogne  (to CC).
Background: Overtraining occurs when an optimization process is applied for too many steps, leading to a model describing noise in addition to the signal present in the data. This effect may affect typical approaches for species tree reconstruction that use maximum likelihood optimization procedures on a small sample of concatenated genes. In this context, overtraining may result in trees better describing the specific evolutionary history of the sampled genes rather than the sought evolutionary relationships among the species. Results: Using a cross-validation-like approach on real and simulated datasets we showed that overtraining occurs in a significant fraction of cases, leading to species trees that are more distant from a gold-standard reference tree than a previously considered (and rejected) solution in the optimization process.
1A ). In other words, overtraining would lead to a final tree (obtained at the end of the optimization procedure) topologically more distant to the species tree than a tree that was met earlier in the optimization. To investigate this possibility, and assess to what extent overtraining could affect species tree reconstruction, we used a cross-validation approach. We separated each dataset into a large set of concatenated gene alignments used to reconstruct a reference tree, and multiple small sets of concatenated genes not containing the genes present in the large alignment (Fig. 1B ). Then, for each small alignment, a tree was reconstructed and the topologies of the intermediate best trees considered during the optimization process were stored (Fig. 1B ). By "considered" we refer only to the "current best trees" used as starting point in each of the optimization steps (see above).
Results We analyzed three real datasets spanning various evolutionary distances and containing different numbers of taxa: a fungal dataset (246 genes for 21 species  [14] ), a primate dataset (7018 genes for 10 species, available in PhylomeDB  [15] ), a cyanobacterial dataset (203 genes for 43 species, [16]), and one simulated dataset derived from the fungal sequences using the program Rose v1. 3  [17]  following Marcet-Houben et al. [18].
Detection of Overtraining in Tree Reconstruction Methods. For each dataset, we used a maximum likelihood tree reconstruction method (PhyML or RAxML) to reconstruct the maximum likelihood tree and kept track of all the trees encountered during the optimization process. All trees encountered were then compared in terms of topology or likelihood against a reference dataset, either a tree (the reference species tree) or a very large alignment (the reference alignment; see Methods for details). Regardless of the dataset used, overtraining in terms of tree topology was observable: that is, the final tree returned by the program was often more distant to the reference tree than a tree considered at an earlier point in the optimization process (Fig. 2  and Fig S1 ). This effect was stronger for smaller sets of concatenated genes and nearly always absent for sets of the same size as the large alignment (Fig.
3 ). The latter result confirmed that the reference tree was reconstructed from a sufficiently large number of genes. For the simulated dataset, where all genes followed the same evolutionary history, overtraining still occurred, albeit to a limited extent. This indicates that overtraining cannot be completely explained by differences in the underlying gene evolutionary histories, even if increasing the proportion of alternative topologies under simulated controlled conditions clearly leads to an increase in the proportion of cases where overtraining is detected (Fig. S2  and Fig. S3 ). In addition, the two major reconstruction implementations produced similar patterns of overtraining when applied to the same dataset (Fig. 2 ), revealing that the problem we point out is not software-specific but rather more generally present in the ML methodology when the goal is to reconstruct a species tree from a small sample of genes.
Overtraining and Node Support It is a common procedure in phylogenetics to evaluate the quality of a tree by measuring the stability of each node to data resampling. To investigate whether the nodes that are incorrect in the final tree due to overtraining are distinguishable and could thus be corrected or removed a posteriori, we inspected bootstrap and approximate Likelihood Ratio Test (aLRT) supports in the fungal dataset. As expected, the incorrect nodes (with respect to the reference tree) had much lower support than the correct ones but among them, nodes introduced by overtraining (see Material and Methods) were practically indistinguishable by their bootstrap support values from the other incorrect nodes (Fig. S6A ), and also by their aLRT support (Fig. S6B ). Therefore, node support metrics cannot be used to single out the overtraining-induced errors in tree topology.
Overtraining is not simply a stochastic effect We tested whether the overtraining effect that we detected could be simply the result of stochastic effects during the tree optimization process. First, by chance alone, in the path from the initial tree to the final ML tree, some search runs will show trees passing closer to the reference tree and these runs will be erroneously identified as overtraining by our approach. If this is true, the effect should be independent of the reference tree topology. That is, the proportion of detected cases with such apparent overtraining should be constant regardless of the reference tree topology chosen. To test this, for the fungal dataset and a small size of alignment (5 genes), we generated 100 random trees and evaluated each time the number of runs where overtraining was detected (Fig S8 ).