dataesr/scientific-paragraphs-categorization huggingface dataset:
DNA and RNA preparation for sequencing We performed DNA sequencing on 10 strains of the auto-pseudogamous species M. belari coming from different locations in Europe (accession numbers PRJEB30104 and PRJEB61636). For each strain, one gravid female was initially collected in the wild and left to lay eggs in a Petri dish. This constituted a single strain, which was frozen in our collection. For sequencing, we amplified the animals and extracted the DNA for each strain. Briefly, we collected mixed stage worms, washed them in M9, and we froze a pellet of ~300 μl of worms in liquid nitrogen. After thawing, we added 600 μl of cell lysis buffer (Qiagen Cell Lysis Solution, #158906), as well as 6 μl of proteinase K at 17 μg/μl and incubated the mix for 3 hours at 65°C. We next incubated the mix for 1 hour at 37°C, supplemented with 40 μl of ribonuclease A (at 5 mg/ml).
Heterozygosity analysis For each of the 10 strains of M. belari, we mapped the reads to the assembled genome of M. belari (accession number PRJEB30104) with BWA (Burrow-Wheeler Aligner)  (41). The assembled genome is still fragmented, containing 217 contigs. We therefore analyzed heterozygosity along all 217 contigs (see fig. S1  and zenodo archive; https://doi. org/10. 5281/zenodo. 8112093). We produced BAM files with SAMtools (42), and we estimated the heterozygosity for each strain using ANGSD (18) using the Site Frequency Spectrum (SFS) estimation for a single sample. Recombination at the extremities of the chromosomes could explain a limited decrease in heterozygosity, with the rest of the chromosome remaining nonrecombining. To test this, we calculated the heterozygosity on 5000bp windows.
Genotype inheritance RNA-seq was performed for three sisters in each of the two autopseudogamous species M. belari and M. monhystera and the two sexual species M. spiculigera and M. longespiculosa (accession number PRJEB61636). For each species, reads from the three individuals where pooled to assemble a transcriptome: Adapters were clipped from the sequences, low-quality read ends were trimmed (phred score < 30), and low-quality reads were discarded (remaining length <36 bp) using trimmomatic [v0. 39;  (43) ]. Paired-end transcriptomes were de novo assembled using Trinity v2. 13. 2  (44). We mapped the reads on their respective assembled transcriptome with BWA (41), and we produced the BAM files with SAMtools  (42)  and called the SNPs using reads2SNP  (45)  focusing on sufficiently covered contigs (minimum contig average coverage = 15×) and positions (minimum = 20×).
Recording and behavioural analyses The arena was placed under a stereomicroscope (Leica S8APO, Leica Microsystemes, France), which was connected to a camera (Leica MC 190HD) and a screen (Iiyama). A female adult V. destructor was inserted in the arena and its movements were recorded for 10 min. The videotracking of the parasite over 10 min was then analysed using EthoVision Ò XT 17 (Noldus Information Technology BV, Wageningen, Netherlands  [40] ). The proportion of time spent in each zone (bubble, disc or rest of the arena) along with the number of stops, the duration of stops and the velocity were all measured directly by the software. Based on preliminary observations, the females were considered immobile if they moved less than 0. 2 mm between two track points. When the parasite was immobile, short but clear vibrations or pulsations of its body were frequently observed (Movie S1).
Statistical analyses The results were analysed using R. 4. 0. 4  [49]  and graphs were generated using the ggplot2 package  [68]. Generalised linear models (GLMs) with Binomial distribution were used to analyse the binary data resulting from the artificial feeding experiments. The feeding success and the survival rate at 24 and at 48 h were compared according to the rearing condition of the V. destructor females. If significant differences were detected, the groups were further compared using the multcomp package in R. Some conditions resulted in 100% fed female mites, so the parasite feeding rate was analysed using a bias-reduced GLM. The parameters considered in the videotracking experiments were measured per zone of the arena. Because in the case of random movements, the probability to be in a zone is proportional to the surface of the zone, our measurements of stops and durations by zone had to be weighed by the surface of each zone.
Genomic dataset and population definition The S. cerevisiae genome data used in this study was generated by  (Peter et al. , 2018)  as part of the "1,002 Yeast Genomes Project". Relevant populations of isolates were defined based on the clades as determined in the original publication, followed by manual filtering of isolates based on ecological-and geographical origins to assure population homogeneity. We included populations with a minimum sample size of five isolates for further analyses. The Italian Wine population had a large sample size and it was randomly sampled to a subset of isolates for computational tractability. Combined, this yields a total of 17 S. cerevisiae populations from both domesticated and wild origins (Supplementary Table  1 ).
Genome alignment and gene extraction For each population, we generated full genome alignments and extracted the protein-coding DNA sequence (CDS). The genomes in each population and the reference genome R64 (Downloaded from ftp://ftp. ensemblgenomes. org/pub/fungi/release-49/fasta/saccharomyces_cerevisiae/dna/; last accessed December 2020) were aligned using the MultiZ v11. 2 alignment program from the Threaded-Blockset Aligner tool suite  (Blanchette et al. , 2004). The resulting alignments were then projected onto the reference sequence, and the resulting alignment blocks were realigned and filtered using MafFilter v1. 3. 1  (Dutheil, Gaillard, & Stukenbrock, 2014). Alignment blocks were split into windows with a maximum size of 10 kb, which were subsequently realigned using MAFFT v7. 38  (Katoh & Standley, 2013).
Reconstructed gene-coding sequences were checked for premature stop codons to ensure accurate reconstruction. No genes were removed at this step. In these and subsequent procedures, genomic data was handled with scripts using the Biopython package v1. 78  (Cock et al. , 2009) , available at https://gitlab. gwdg. de/molsysevol/saccharomycespopgen. The total number of nucleotide sites and final number of genes for each lineage are summarised in Supplementary Table  2.
cerevisiae (sacCer3) genome using the 'maf_project' program (v12) from the TBA package  (Blanchette et al. , 2004)  and the pairwise alignment of S. cerevisiae with S. paradoxus (sacPar) was extracted and merged, replacing non-aligned positions by missing data. The 16 chromosomes were further concatenated before being input to the IMCoalHMM program (v0. 7. 0, https://github. com/mailund/IMCoalHMM).
Quantifying adaptive evolution For reconstructed gene alignments, an outgroup sequence was identified using the closest match of a 'blastn' v2. 9. 0+ search  (Altschul, Gish, Miller, Myers, & Lipman, 1990 ) on the S. paradoxus genome (downloaded from https://ftp. ncbi. nlm. nih. gov/genomes/refseq/fungi/Saccharomyces_paradoxus/latest_assembly_versions/G CF_002079055. 1_ASM207905v1/). Specifically, the reference sequence of each S. cerevisiae gene alignment (R64) was queried against the reference CDS file of S. paradoxus (Downloaded from https://yjx1217. github. io/Yeast_PacBio_2016/data/) (Yue et al. , 2017). Protein-coding sequences, including the outgroup sequence, were re-aligned using the codon alignment program MACSE v2  (Ranwez, Douzery, Cambon, Chantret, & Delsuc, 2018). We calculated statistics on synonymous and nonsynonymous divergence between the species, transversion per transition ratio, and inferences on ancestral alleles from these alignments using the BppPopStats v2.
To determine the quality of model fit, Akaike's Information Criterion (AIC) was calculated for the complete SFSs per population  (Akaike, 1973). Here, the GammaExpo and ScaledBeta models performed comparably well, but the ScaledBeta model failed to estimate   in more cases than the GammaExpo model. Therefore, the GammaExpo model was determined as the best performing model, which is in accordance with previous results obtained from data in animals  (Galtier, 2016) , plants  (Moutinho et al. , 2019)  and fungi  (Grandaubert, Dutheil, & Stukenbrock, 2019). Finally, sites were bootstrapped to create 150 SFS replicates for each dataset enabling a more comprehensive analysis of ,   and. For some replicates, optimisation failed and the corresponding replicates were discarded. The minimum number of replicates for which estimates could be obtained was 90 for the North American Oak population in the Metal Stress gene category.
Normality and independence of the residues were assessed using the Shapiro and Ljung-Box test, as implemented in the 'stats' package. In some cases, the non-normality of the residues was still significant after using the Box-Cox transform, owing to the distribution of   being zero-inflated. Therefore, for comparison, we fitted another set of models where all points with   < 1 -3 were discarded. While these models were fitted on reduced datasets, their residues were generally in better agreement with the Gauss-Markov assumption and had possibly more accurate P-values. Results were visualised with the 'ggplot2'  (Wickham, 2016) , 'cowplot' (Claus O. Wilke, 2020), and 'ggpubr' (Alboukadel Kassambara, 2020) packages.
Our analysis reveals that all populations follow a general trend of population decrease since the divergence with S. paradoxus, and this trend becomes even more evident when disregarding the artefactual increase of population size in the most recent times. As SMC-based methods have been benchmarked on Primates dataset  (Schiffels & Wang, 2020) , we conducted a simulation analysis to assess their accuracy on yeast datasets (see Supplementary Methods). We assessed the power of the MSMC2 method by simulating data under a neutral model of sequence evolution, which fulfilled the hypotheses of the inference model (homogeneous recombination and mutation rate, no selection). We simulated 10 datasets of 5 diploid individuals (10 haploid genomes), with the same chromosome structure as the reference S.
Acknowledgements We would like to thank  Ana Filipa Moutinho ,  Adam Eyre-Walker , and  Nicolas Galtier  for discussions on this project. We thank  Ana Filipa Moutinho  for help with running the NetSurfP-2. 0 software and  Haozuan Liu  and  Jianzhi Zhang  for kindly providing data on recombination rates across the S. cerevisiae genome,  Fernanda Trancoso  and  Chrats Melkonian  for critical reading of the manuscript. J. Y. D. would like to thank  Lucie Vivier , wine grower and winemaker in Charente, France, for her explanations on yeast industrial usage in winemaking. J. Y. D. acknowledges funding from the  Max Planck Society.
Furthermore, NK cells get activated by cytokines like IL-12 and IL-15, mediated by DCs. Additionally, probiotic microbes, especially a number of lactic acid bacteria (LAB), encourage the synthesis of Interferon-gamma (IFN-γ) by NK cells, which were stimulated by DCs  [20]. The dataset from 2011 to 2023 has been taken into consideration, including research articles retrieved from the Web of Science (WOS) database by using the terms "probiotics". The output obtained provided the dataset of 12,504 articles (peer-reviewed), which primarily focused on the term probiotics. The complete information of the records and their cited references were procured in a plain text format. Moreover, to gain an overview of the research landscape of this discipline, the analytical tool "VOSviewer version 1. 6. 19 was used.
Methodology We thoroughly searched the scientific literature across multiple databases to compile this review. The comprehensive investigation of electronic databases, namely Google Scholar, EBSCO, Scopus, PubMed, and Web of Science was undertaken using a specific set of keywords that involves words such as "Lactobacillus," "Bifidobacterium," "Bacillus," "yeast," "probiotics," "inflammation," "plant-based fermented products," "polyphenols," "paraprobiotics," "commercial probiotic products," "in-vivo," "in-vitro," and "human studies. " The criteria for article inclusion were established as follows: (1) adherence to an experimental study design and (2) publication in the English language. Following the elimination of duplicate submissions, 69 articles were determined to be eligible based on the established criteria and were included in the analysis.
Dermanyssus gallinae specimens were used as positive controls during DNA extraction and PCR amplification. Purified water was used as negative control in PCR. PCR amplicons were visualized by electrophoresis in 1. 5% agarose gel stained with SYBR Safe DNA gel stain (Invitrogen, Waltham, MA, USA). Gel Doc XR + Gel Documentation System (Bio-Rad) was used to visualize specific fragments. The length of the amplified DNA fragments was compared to the 100 bp genetic markers (O'GeneRuler 100 bp DNA Ladder, ready-to- use, Thermo Scientific). The PCR product was purified using FavorPrep GEL/PCR Purification Mini Kit (Favorgen Biotech Corp. , Taiwan) and further sequenced (Macrogen Europe). The obtained sequences were compared with the available sequence in GenBank. PCR amplification yielded a product of ∼710 bp for both types of specimen (analyzed mites, and D.
gallinae). BLAST analysis of the analyzed mites showed between 98. 4 and 99. 51% identity with Ornithonyssus bacoti of unknown (acc. no. FM179677. 2) (14), and Chinese (acc. no. MH553336. 1-MH553338. 1) origin, respectively. The sequence of our specimen was submitted to GenBank under accession number OQ195774. • C for 45 s, annealing at 47 • C for 45 s, extension at 72 • C for 90 s, and a final extension cycle at 72 • C for 10 min.
Puri cation and isolation of active compounds The bioactive compound of the fungus comb extract was isolated using HPLC-UV. On the rst puri cation using a phenyl Spherisorb column, the chromatogram of the extract showed several intense peaks. Following the agar test of all six fractions for antimicrobial activity against M. luteus (data not shown), only a single fraction showed antibacterial activity (Fig. 2A ). This retention zone could indicate a polar compound which is poorly retained on this reverse phase column. The active fraction was then submitted to a second separation using a SunFire C18 column. Here, the HPLC chromatogram showed ve major peaks and the fraction of each peak was tested for antibacterial activity. Only one fraction showed antibacterial activity (Fig. 2B ). Here the compounds were more retained compared to the C6 Phenyl column.
This could indicate a lack of aromatic functions on the active chemical backbone. Finally, to purify the active fraction (double peak) obtained after C18 separation, a third injection was performed using the XBridge BEH Amide Column. This last separation, dedicated to retaining polar compounds, showed a cleaner chromatogram and well separated peaks. Among the four fractions obtained, one fraction showed antibacterial activity against M. luteus (data not shown) (Fig. 2C ). The puri ed antibacterial compound produced by the fungus comb showed a UV spectrum with maximum absorption at 206 nm, probably linked to carbonyl functions. Thus, the bioactive compound puri ed by HPLC-UV using three different columns was subjected to NMR analysis for structural determination. 2 ). The HMBC spectrum showed cross-peak correlation between the proton H-6 of the methyl at 1.
Then, 50 μL (2. 5 mg) of crude extract was placed in the agar wells of each strain. HPLC water was also tested as a negative control. The Petri dishes were then incubated under suitable conditions depending upon the tested microorganism. The crude extract was considered active if it caused a growth inhibition around the well to which it was applied. After the incubation period, culture inhibition diameters were measured and compared to normalized values  [41]. The diameters of the inhibition zones were measured in millimetres (mm) using the Graph Pad software version 6. 0 at the signi cance level of 5% and the results were recorded separately. Positive controls were conventional antibiotic test discs (SIRscan, Montpellier, France) including oxacillin (5 μg) and erythromycin (15 μg). The tests were performed in duplicate under the same conditions.
Introduction: The Family of pathogenesis-related proteins 10 (PR-10) is widely distributed in the plant kingdom. PR-10 are multifunctional proteins, constitutively expressed in all plant tissues, playing a role in growth and development or being induced in stress situations. Several studies have investigated the preponderant role of PR-10 in plant defense against biotic stresses; however, little is known about the mechanisms of action of these proteins. This is the first systematic review conducted to gather information on the subject and to reveal the possible mechanisms of action that PR-10 perform. Methods: Therefore, three databases were used for the article search: PubMed, Web of Science, and Scopus. To avoid bias, a protocol with inclusion and exclusion criteria was prepared. In total, 216 articles related to the proposed objective of this study were selected.
, 2021; Santos et al. , 2023) , as well as on reducing the abiotic factor effects  (Santos et al. , 2018; dos Santos et al. , 2022; Oliveira et al. , 2022; Nascimento et al. , 2023). Much knowledge about PR-10 roles in biotic stress has been accumulated in literature databases. However, it is presented as loose pieces of a puzzle, particularly regarding the PR-10 action mechanism. Therefore, this SR aims to elucidate the mechanism of action of PR-10 against biotic stresses, based on systematizing the literature published between the years 2003-2021.
Materials and methods The SR was conducted using the software StArt (State of the Art through Systematic Review) version Beta 3. 4, developed by the Research Laboratory in Software Engineering (LAPES) of the Federal University of São Carlos (UFSCar) (Available at: http:// lapes. dc. ufscar. br/tools/start_tool). The review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines  (Page et al. , 2021) , which consist of three steps: planning, execution and summarization.
Execution To answer the research questions (Table  1 ), articles were searched in three databases, PubMed, Scopus, and Web of Science, using a single search string (PR10 OR "PR 10" OR PR-10) AND ("biotic stress" OR "biotic stresses"). Boolean connectors "OR" and "AND" were used in the string to group synonymous keywords and main terms. The selected files were imported in BIBITEX and MEDILINE format into the StArt software (vs. Beta 3. 4) where the automated selection was made based on reading the titles and abstracts, using the inclusion and exclusion criteria established in the protocol as a reference (available in the Supplementary material at https://www. frontiersin. org/articles/10. 3389/fpls. 2023. 1193873/full#supplementary-material), thus characterizing articles as accepted or rejected and excluding duplicates.
Summarization At this stage, the information extracted from the studies was summarized in graphs, tables and figures. Bibliometric analyzes were performed based on the selected articles' metadata using the bibliometrix package  (Aria and Cuccurullo, 2017)  of the R statistical environment (R. C. Team, 2021)  in the following manner: (i) identifying journals that contributed with the largest number of studies included in the review; (ii) generating collaboration networks between authors, institutions and countries; (iii) and generating co-occurrence network of terms in the works' titles. Vosviewer software (van Eck and Waltman, 2014) was used for graphical visualization of collaboration and co-occurrence networks. To reduce any bias in preparing the SR, the PRISMA checklist was used (available in the Supplementary material at https://www.
Selection of studies and bibliometric indicators A total of 579 articles were returned from searches in the databases, with 518, 28 and 33 from the databases PubMed, Web of Science, and Scopus, respectively. Electronic searches in each database corresponded to 89. 46%, 4. 83% and 5. 69% of studies in the aforementioned databases. Although the same string was used in different databases, PubMed contributed to the SR with more studies. In the first selection of articles in the StArt software, 329 articles were excluded because they were ineligible for the review's inclusion criteria, with 279 being excluded based on reading the titles and abstracts and 50 based on reading the complete articles. The automatic tool detected 34 duplicate articles. Therefore, a resulting sample of 216 articles, which met at least one inclusion criterion, was included in the SR (Figure  1 ).
Statistical Analyses for D. pinodes Disease Severity, Architectural Traits, and Frost Tolerance The generalized linear model (PROC GLM) from the SAS software (SAS Institute Inc. 2000) was used to analyze phenotypic data through ANOVA, using a mixed model including genotype and block factors and their interaction. For each trait, the normality of residuals was checked with the Shapiro and Wilk's test (PROC UNIVARIATE, p > 0. 05), and the homogeneity of variances was checked using the Bartlett's test (HOVTEST, p > 0. 05). ANOVA results allowed the broad sense heritability of the different traits to be determined as h 2 = σ 2 g/[σ 2 g + (σ 2 e/n)], with the genetic variance σ 2 g, the number of replicates per genotype n, and the residual variance σ 2 e. RILs' LSMeans were calculated for each trait from ANOVA results and used for QTL analyses.
The 1-LOD confidence intervals were finally defined for each validated QTL. A composite map including the three individual maps with all their respective markers and QTLs was constructed using the BioMercator software  [50]. Four different metaQTL analyses were performed in BioMercator with the Gerber and Goffinet meta-analysis model  [51] , choosing the smallest AIC value for QTL integration: a first analysis with all D. pinodes resistance one-trait QTLs generated Dp. x. x metaQTLs; a second analysis with all field and controlled conditions frost tolerance one-trait QTLs generated FR. x. x metaQTLs; a third analysis with all architectural and phenological one-trait QTLs (Ht, StLe, NbNo, NbBr, dflo/DBF) generated A. x. x metaQTLs; and finally, a joint analysis, carried out with all one-trait QTLs, generated MDA (standing for Meta Disease Architecture) or MDAF (standing for Meta Disease Architecture Frost) metaQTLs.
pinodes disease severity on LGV and LGVI, detected a new one on LGVII, but interestingly showed no QTL detection on LGIII, where the Hr and Le major genes map. It also allowed to detect QTLs controlling plant height specific to this population on LGIII and LGVII. Finally, the new phenotypic data for D. pinodes disease severity (from two new strains and detached stipules conditions data for the JIxDP population, from all strains and all conditions for the other two populations) and for most architectural and phenological traits, combined with the high level of common and colinear markers between the three maps, allowed to strengthen QTL detection across strains, evaluation conditions, and populations (Table  2 ).
Confirmation of Identity (ITS-based Phylogeny) Sequences representing a broad range of species within Pisolithus were retrieved from GenBank and UNITE following  Lebel et al. (2018) , for comparison to those generated in this study. The dataset comprised 158 ITS sequences, consisting of 599 bp, with P. abditus included as outgroup. Phylogenetic analysis was performed with Maximum Likelihood (ML) in RAxML v. 8. 2. 12 (Stamatakis 2014) using standard algorithm and 1,000 bootstrap replicates on the CIPRES Science Gateway v. 3. 3  (Miller et al. 2010). The resulting tree (supplementary fig. S13 , Supplementary Material online) was visualized using FigTree v1. 3. 1  (Rambaut 2009).