dataesr/scientific-paragraphs-categorization huggingface dataset:
Any remaining adapter/primer sequences were trimmed, and reads were checked for quality (≥30) and length (≥200 bp) using cutadapt  [28]. Reads were further corrected for known sequencing errors using SPAdes  [29]  and then merged using PEAR  [30]. A total of 3,259,918 reads was produced, with an average of 83,588 ± 15,247 reads per sample. Sequencing data are deposited in NCBI under the accession number PRJNA663256. OTUs were identified using a Vsearch pipeline  [31]  designed to dereplicate (-derep_ prefix-minuquesize 2) and cluster (-unoise3) the merged reads, as well as check for chimeras (uchime3_denovo). Taxonomic classification of OTUs was performed using the classifier from the RDPTools suite  [32]. Representative OTU sequences were taxonomically assigned using the RDP classifier with a SAB score ≥ 0.
Microbiota Composition Analysis Statistical analyses were conducted using the R programming language and software (R Development Core Team 2012), specifically using the packages gplots, gdata, vegan  [33] , ade4  [34] , phyloseq  [35] , and phangorn  [36]. OTU counts were normalized via simple division to their sample size and then multiplication by the size of the smallest sample. α-diversity and richness were estimated using the OTU table data and the functions "diversity" and "estimateR". A distance matrix for β-diversity analysis was computed using the "vegdist" function and the Bray-Curtis method. Principle coordinate analysis was conducted on the distance matrix data using "dudi. pco". Differential enrichment in bacterial taxa among groups was assessed using the linear discriminant analysis (LDA) effect size (LEfSe) algorithm  [37].
Statistical Analysis Statistics were calculated with Prism software (version 9. 4). A normality test (Shapiro-Wilk test) was systematically performed on the data. In the case of normal distribution, one-way ANOVA, followed by Tukey's multiple comparison test, was used. In case of lack of normal distribution, data were analyzed using the Kruskal-Wallis test, followed by Dunn's multiple comparison test. The level chosen for statistical significance was 5%.
Correlation between Microbiota Composition at Family-Level and Physiological Parameters In order to evaluate the correlation between metabolic parameters and microbial composition, PCAs were individually carried out on microbiota composition at (family level) and host metabolic composition and then subjected to co-inertia analysis in order to highlight associations between the two datasets. Interestingly, mice clustered according to probiotic treatment (16%), diet (73%), and bacterial composition (Figure  8 ). As expected, HFD correlated positively with all metabolic parameters (body weight gain, OGTT, LDL, and FFA levels), including inflammation IL-17 and IL-22 (Figure  8 ). At the family level, the abundance of Bacteroidaceae (rho: -0. 37; p≥ 0. 05) and Prevotellaceae (rho: -0. 35; p ≥ 0.
Taken together, the modifications observed as a result of treatment with L. plantarum CNCM I-4459 argue in favor of a restoration of the physiological state since this treatment seemed to normalize levels of both tight junction proteins and IL-22 to those observed in CD-fed mice. Additionally, these regulations seemed to be independent of oxidative stress since no modification was observed for Nrf-2. However, only Nrf-2 gene expression was assessed, and not oxidative activity; thus, these data should be interpreted with caution. Finally, accumulating reports reinforce the relationship between microbiota dysbiosis and metabolic disorders, such as diet-related obesity  [56, 57]. Here, we demonstrate that treatment with L. plantarum CNCM I-4459 was able to partially reverse HFD-induced dysbiosis by increasing microbial richness.
beklemishevi, An. labranchiae, An. macullipennis, An. freeborni, and An. sacharovi). Transcriptomes from the two geographically distant populations of An. daciae in Europe and Asia (Moscow and Tomsk regions, respectively) were also obtained and compared. After transcriptome assembly and annotation using the Transdecoder pipeline, we obtained between 14,404 and 22,326 proteins per species (Additional file 1: Table  S1 ), with contig N50 ranging from 681 to 1329 bp and the total coding sequence (CDS) lengths ranging from 9. 38 to 21. 5 Mbp, which are typical transcriptome assembly metrics for non-model organisms. The singlecopy orthologs benchmarking against the Diptera dataset demonstrated that 28. 2-73. 3% of genes per species were completely assembled during the analysis and 12. 8-21. 8% were fragmented.
The duplication level, which can arise as a result of a separate assembly of different haplotypes especially in highly polymorphic species, was generally low and ranged from 0. 2% (An. beklemishevi) to 3. 6% (An. quadrimaculatus). Orthofinder analysis returned 1271 single-copy orthologs, which were present in all 13 species. These genes were aligned and concatenated, resulting in a 1,643,691 bp-long alignment. After the removal of gapped regions, the final alignment consisted of 898,101 bp. JModelTest2 results demonstrated that the best substitution model for our dataset was GTR + G + I, which was used as GTRGAMMAI during RaxML analysis.
Next, a split between the European clade and the Northern Eurasian clade took place around 10. 5 Mya. The most recent species divergence occurred between An. daciae and An. messeae between 3. 6 and 1. 1 Mya (a mean estimate of 2 Mya) in the Pliocene-Pleistocene Epoch at the end of the Eogene Period. The mean divergence time of 1. 4 Mya between the Tomsk and Moscow populations of An. daciae is probably an overestimation as population divergence time can be better assessed using population samples and coalescent analysis, taking into account migration events and demographic features of populations  [50]. This analysis used previously established divergence time of the An. sinensis split from the rest of the species (35-45 Mya)  [6]. To confirm the obtained tree topology and divergence times, we performed additional analysis using of the whole-genome dataset from only six species including the outgroup An.
In this situation, two allopatric species can demonstrate genetic admixture indirectly mediated by a third species which is sympatric for both of them. To prove the existence of such a scheme one will need to sample major populations from diverse geographic regions of several species. The phenomena of widespread historical introgression and current incomplete reproductive isolation have been demonstrated in the African An. gambiae complex using whole genome datasets  [7]. It is possible that genetic introgression can be a factor contributing to the acquisition of adaptations related to malaria vectorial capacity. For example, a study of introgression between members of the An. gambiae complex suggested that traits enhancing vectorial capacity can be acquired from nonsister vector species through a rapid process of interspecific genetic exchange  [7].
2 pmol of either forward or reverse primers and Sanger sequenced at the Genomics Sequencing Center of Virginia Tech. The samples were sequenced with both forward and reverse directions to confirm the presence of the same SNPs on both DNA strands. Sequences were trimmed, aligned, and analyzed using a Lazergene software (DNASTAR, Inc. , Madison, WI, USA) with modules EditSeq, Seqman Pro, and NCBI BLAST (optimized for highly similar sequences from nucleotide collection). Species identification was done based on the percent identity of the query with the subject sequence of at least 99%. Sequences that match the previously described SNPs, in positions 150, 211, 215, 217, 412, and 432, were used to distinguish the ITS2 sequences of An. messeae from An. daciae  [2].
Transcriptome and genome sequencing We performed transcriptome sequencing for An. messeae, An. daciae (Moscow and Tomsk populations), An. quadrimaculatus, An. beklemishevi, An. labranchiae, An. maculipennis, An. freeborni, and An. sacharovi. Total RNA was isolated from 15 individual specimens from each of the 8 species. The polyA-selection method was used and quality control of the RNA sequencing libraries was performed, including size evaluation by a bioanalyzer and by quantitative assay (HudsonAlpha Institute for Biotechnology Huntsville, AL, USA or Fasteris, Inc. , Geneva, Switzerland). Transcriptome sequencing was done using HiSeq 2500 1 × 100 or 1 × 125 bp, depending on the service provider. We received from 8. 2 to 12. 56 Gb of data for each sample. For the genome sequencing of An. martinius, An.
Transcriptome assembly and annotation The raw reads were trimmed and the remains of adapters were removed using Trimmomatic software  [87]  with the following settings: ILLUMINACLIP:2:30:10 LEADING:24 TRAILING:24 SLIDINGWINDOW:4:24 MINLEN:50. The transcriptomes were assembled using Trinity 2. 1. 1 software  [88]  with strand-specific settings. Open reading frames (ORFs) were extracted from the assemblies with Transdecoder utility [89] and translated ORFs were blasted against a collection of mosquito proteins from VectorBase  [84]  with an e-value threshold 1e -5 using the blastp software  [90]. Proteins with blast hits were used in the TransDecoder. Then, the Predict module was employed to find additional coding sequences that did not have any blast hits within datasets based on hidden Markov model (HMM) profiles derived from the training set of proteins homologous to other mosquitoes.
To remove redundancy caused by the possible assembly of different isoforms, haplotypes, and fragments of genes, the resulting sets of proteins were clustered using CD-HIT software  [91]  with a 97% identity threshold (-c 0. 97 -n 5 -M 2000). Thus, the final sets of proteins consisted of collapsed proteins with either blast hits against the Anopheles proteins or predicted using TransDecoder, Predict, or the HMM-based module algorithm. The corresponding mRNA and CDSs were extracted from each species and subsequently used for the downstream analysis. To assess the quality and completeness of the assembled transcriptomes, benchmarking of single-copy orthologues using BUSCO V. 1. 22 [92]  was applied with a Diptera-specific dataset consisting of 2799 single-copy genes and the following settings: -m OGS -species aedes.
Pseudoassembly of whole-genomic sequences Genomic reads were aligned to the An. atroparvus AatrE3 genome using Burrows-Wheeler Aligner (BWA) mem software  [93]. The resulting reads were sorted using Samtools  [94]. Binary Alignment Map (BAM) files were used to create consensus sequences with the following settings: samtools mpileup -q 50 -Q 26 | bcftools call | vcfutils. pl vcf2fq -d 8 -D 80. To reduce possible errors caused by interspecies alignment, stringent criteria were used during the consensus construction including a minimum phred-scaled mapping quality equal to 50 (-q 50), a minimal phred-scaled quality of a base to call a substitution equal to 26 (-Q 26), and minimum and maximum depths equal to 8 and 80, respectively. The maximum depth threshold was utilized to reduce the likelihood of calling substitutions in highly duplicated or repetitive regions in addition to the mapping quality threshold.
Orthology inference and alignment Amino acid sequences were assigned to the orthogroups using OrthoFinder 1. 1. 4 software  [95]  using the total set of 15 species. Orthogroups were manually filtered to exclude orthogroups containing missed species and any paralogs. The nucleotide sequences from the single-copy orthogroups (CDSs) were aligned in the codon-aware mode (F + -codon) using Prank software  [96]. The aligned sequences were concatenated and cleaned using Trimal  [97]  utility, which removed all codons with any gaps in alignment (-nogaps).
Phylogenetic tree reconstruction To determine the optimal substitution model for the dataset, jmodeltest2  [98]  software and Bayesian Information Criteria (BIC) were utilized. The maximum likelihood tree was constructed using the RAxML 8 package  [99]  and the GTRGAMMAI model. The topology was tested with 1000 bootstrap replications. The phylogenetic concordance was calculated as a percentage of individual gene trees supporting the species tree topology using the sumtrees. py script of the DendroPY package  [100]. The individual gene trees were calculated in a similar way with the species tree but with 200 bootstrap replications. To determine the divergence time of the main Maculipennis lineages, we extracted 126,025 fourfold degenerated sites using MEGA 7 software  [101]  from the final alignment.
The divergence time was estimated using MCMCtree from the PAML 4. 8  [102]  package using the approximate likelihood calculation and the GTR + G model of nucleotide substitution after 10 million MCMC generations (including the first one million being discarded as a burn-in). We used independent clock rate model, the alpha parameter for gamma rates (n = 4) at site was set up at 0. 5. Due to the lack of well-established fossil calibrations for the studied and closely related taxonomic groups, we used a root calibration reflected divergence of An. sinensis for the rest of the group (from 35 to 45 Mya) based on previous work  [6].
Analysis of introgression To test our hypothesis for interspecies introgression, we used Hybridcheck software  [103]. This software uses well-established statistics: D statistics (ABBA-BABA test)  [104]  and the f statistic  [105]  to test hypotheses about phylogenetic discordance caused by putative hybridization events for 4-taxon sets. The significance of the D statistic was tested using the jackknife method with 10 blocks and then corrected using the Bonferroni approach. The software generates all possible 4 taxon trees and calculates statistics for each of them. After the calculation, all significant results were manually checked for correspondence to the maximum-likelihood phylogeny, and discordant trees and redundant species combinations were removed from the analysis.
Preparations were then covered by a piece of filter paper for additional tapping. The quality of the chromosome spreading was analyzed under phase contrast microscopy using AxioImager A1 (Carl Zeiss, OPTEC, Novosibirsk, Russia) and AxioVision 4. 8. 1. software (Carl Zeiss, OPTEC, Novosibirsk, Russia). Only high-quality preparations were used for further procedures. Coverslips were removed by a razor blade after freezing the preparation by dipping it in liquid nitrogen and then slides were immediately placed in ice-cold 50% ethanol for 5 min. Subsequently, slides were kept in 70% and 96% ethanol for 5 min and air-dried. After 1-week storage at room temperature, chromosomal preparations were used for FISH.
Acknowledgements We thank  Gayane H. Karagyan  and  Marine S. Arakelyan  for their help with mosquito collection in Armenia and  Janet Webster  for editing the text. of  Genetics and Cell Biology and the Laboratory of Ecology, Genetics and Environmental Protection ,  Tomsk State University, Tomsk, Russia. 5Laboratory of Cell Differentiation Mechanisms, the  Federal Research Center, Institute of Cytology and Genetics, Novosibirsk, Russia. 6Department of Medical Entomology and Vector Control,  Tehran University of Medical Sciences, Tehran, Iran. 7Department of  Medical Entomology and Parasitology, Tarbiat Modares University, Tehran, Iran. 8Department of  General Biology and Ecology, State University of Education, Mytishchi, Russia. 9Dipartimento  Di Sanità Pubblica E Malattie Infettive, Università Sapienza, Rome, Italy.
Fig. 2  depicts example numerical interfaces for three different impact scenarios, revealing excellent agreement with experiments. In computational datasets t ¼ 0 corresponds to the theoretical time of contact between the droplet and pool if neither deformed, a definition which has proven a robust counterpart to its experimental equivalent introduced at the end of Section 2. The key quantitative outputs we consider are interfacial shapes, as well as information on velocities, viscous stresses, pressures, and vorticity that aid our understanding of the rich impact landscape. Moreover, using the three-phase method allows us to individually track, among many other properties, the contribution from each of the phases to the ejected jet and thus splashing characteristics, and therefore quantify the effect of the viscosity ratio on the jet composition: Resulting fluid-fluid interfaces are processed in order to extract the jet composition, as illustrated in Fig.
Data collection For each patient, demographic, laboratory and clinical data, in particular thromboembolic events and pregnancy morbidity, were collected through a dedicated case report form. Obstetrical complications were defined according to the Sydney criteria (1 or more unexplained deaths of morphologically normal fetus beyond the 10th week of gestation (WG), or 1 or more premature births before 34 WG, or 3 or more unexplained consecutive spontaneous abortions before 10 WG). Relapse was defined by the occurrence of a new thrombotic event and/or a new adverse obstetrical event (as defined in Sydney criteria). Data about the associated autoimmune diseases (systemic lupus erythematosus (SLE) or other connective tissue disease) were collected. Cardiovascular risk factors were recorded as follows: diabetes mellitus, chronic hypertension, hypercholesterolaemia, obesity and smoking habit.
CONCLUSIONS: WHERE SHOULD THE FOCUS OF FUTURE RESEARCH LIE? Technical advances are making it increasingly possible to obtain measures of metabolic rates that are high-throughput, taken under natural field conditions, and across scales of biological organisation (Table  2 ). However, the greatest gains in knowledge will be achieved if the field is also open to incorporating ideas, expertise and methods from other disciplines, such as genomics and quantitative genetics. For instance, selection studies have yet to show whether metabolic rate itself is under selection, or evolves through, for example, a genetic correlation with (an)other trait(s) under selection, possibly body size  [98]  and/or growth. [99, 100] With increased accessibility of genetic analyses and tools (online databases, gene ontologies, etc.
ACKNOWLEDGMENTS The authors thank the  Rank Prize Funds  for funding a symposium on 'Variation in metabolic rate -where does it come from and does it matter?' at which the ideas presented in this article were developed. The authors also thank three referees for comments that improved the manuscript. Neil B. Metcalfe was funded by  ERC Advanced  Grant  834653 ,  Tommy Norin  by research grants from  VILLUMFONDEN (40713)  and the  Independent Research Fund Denmark  ( 1054-00020B ) and  Pat Monaghan  by  ERC  Advanced Grant  101020037.
com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Question Method Description Ideal study system References shallower as animals get 15211878, 2023, 6, TA B L E 3 (Continued) 1. How can we better standardise measurements? All Provide reference conditions for measurements that include previous nutritional state and activity of animal, full description of environmental conditions of measurements (time of day, temperature, light and noise levels. ) and appropriate baseline against which other states are measured Any [93] 2. How reproducible and repeatable are measures of MR at whole-animal and cellular levels? Respirometry (whole-animal and tissue/mitochondrial level) Assess whether measurements from MR, mitochondrial function and associated traits are robustly reproducible, and repeatable in the same individual over time Species that are studied by multiple laboratories with the same equipment and where results are openly shared (data transparency) [82] 3.
Electrophysiology Electrophysiological recordings of stretch-evoked spindle responses from rat lumbrical and mouse soleus muscles  (Bewick et al. , 2005; Lin et al. , 2016)  were as described previously. Briefly, nerve-muscle preparations were dissected and placed in gassed (95% O 2 -5% CO 2 ) bicarbonate-buffered physiological saline at room temperature (RT; 17-20 • C), and then the evoked electroneurogram was recorded by laying the nerve across silver wire electrodes (rat lumbrical) or taking it into a tight-fitting glass suction electrode (mouse soleus). Amplified signals were processed and analysed using Spike2 software (Cambridge Electronic Design, Cambridge, UK) (Supporting information S2).
ACKNOWLEDGEMENTS We would like to thank:  Prof. Christophe Mulle ,  University of Bordeaux, France  for the generous donation of the GluK2-Neo mice; Prof. Roberto Pellicciari  and  Prof. Maura Marinozzi ,  University of Perugia, Italy  for the generous gift of PCCG-13; the  Microscopy and Histology core facility  at the  Institute of Medical Sciences, University of Aberdeen  for their support and assistance in some of the imaging in this work. We would also like to thank  Prof. Gernot Riedel ,  University of Aberdeen UK  and  Prof. David Jane ,  University of Bristol UK  for helpful comments during the work and discussion about drafts of this manuscript.
GluK2, GluK5 and mGluR5 were detected in spindle homogenates, but only GluK2 was in spindle mechanosensory terminals. It is not clear why in western blots GluK2 ran at a lower molecular mass in hippocampus than spindles, although it may be because of splice variants since there are 41 known transcripts of the GRIK2 gene (Ensembl database). Further experiments are needed to determine F I G U R E 7 mGluR5 is expressed on non-spindle sensory axons. (a) A band for mGluR5 was present in spindle homogenates (S) but at a substantially lower molecular mass than in hippocampus (H, positive control). No bands were detected in lateral deep masseter (DM; negative control). (b) In whole-mounts, the mGluR5 antibody (red) labelled thin, unmyelinated axons (arrow), presumptive nociceptive sensory axons, near spindle capsules but not primary mechanosensory terminals (green, arrow).
, Worcestershire, UK). Atomic force microscopy (AFM) images of the exfoliated bentonite nanosheets were recorded in the dry state using Tapping Mode with a scan rate of 1 Hz with a Dimension ICON (Veeco, Bruker). The samples were prepared by spin-coating diluted bentonite solutions onto a silicon wafer. The data were analyzed with Nanoscope Analysis software. The mechanical properties of the PVDF-based films were characterized via uniaxial tensile tests on a Zwick Z2S apparatus.
Acknowledgements This research was supported by the project  3Dielectric  from  Agence Nationale de la Recherche  ( ANR-21-CE06-0001-01 ), and by the  Thomas Jefferson Fund  from the  Make The Planet Great Again Initiative of the French Presidency. This study also received financial support from the  French government  in the framework of the  University of Bordeaux 's  IdEx "Investments for the Future" program /GPR PPM. All authors thank  Arkema company  for the donation of PVDF materials used in this research.
The goal of this study was to analyze the metabolite changes that occurred during the competitive interaction between CA and CM, using untargeted metabolomic approach, in order to potentially detect antifungal or quorum-sensing molecules. C. albicans was co-cultured with a strain of C. mamane isolated from Bixa orellana, in potato dextrose broth medium (PDB). Metabolomic analyses and annotations were performed using MSDIAL, MSFINDER, MET-LIN, Xcalibur, and SciFinder platforms. We intended to carry out all of the experiments in a liquid culture medium because it is homogeneous and allows for the most interactions between co-cultivated microorganisms when compared to solid culture, making it more reliable and reproducible  [13]. The limitations of the fungal database are overcome by combining several analysis platforms such as MSDIAL, MSFINDER, METLIN, Xcalibur, and SciFinder to produce valid data.