dataesr/scientific-paragraphs-categorization huggingface dataset:
We found that 94% of query sequences have a contiguous match against the Dhole genome, indicating the vast majority of dimorphic SINECs inserted in the dog lineage following the split from the Dhole common ancestor (SI Appendix, section 5). LINE-1 transcription often bypasses the polyadenylation signal encoded within the element, resulting in the inclusion of flanking genomic sequence in the LINE-1 RNA (66-69). Thus, after retrotransposition, the resulting 3′-transductions can be used as sequence signatures to identify the progenitor source elements of individual LINE-1 insertions  (70, 71). We identified 18 transduced sequences among the dimorphic LINE-1 sequences in our dataset. Of these transduced sequences, 17 aligned elsewhere in the genome at a location that is not adjacent to an annotated LINE-1.
A recent study collated these findings, along with other published datasets, and identified a total of 13,572 dimorphic Alu elements in humans  (84) , although we note that these estimates are based on Illumina sequencing data, which have limitations in mapping to repetitive regions and in fully capturing insertion alleles  (81). Finally, an approach specifically designed to identify dimorphic human LINE-1 insertions utilizing long-read sequencing data identified 203 nonreference insertions in the benchmark sample NA12878, of which 123 which were greater than 1 kbp in length  (85). Illumina sequencing data indicate that Zoey differs from the CanFam3. 1 reference at 3. 57 million single-nucleotide variants (SNVs). This number is lower than the number of differences typically found in a globally diverse collection of human genomes (4.
1 million to 5. 0 million SNVs)  (83) , and is comparable to the number found in the National Heart, Lung, and Blood Institute's (NHLBI) TOPMed dataset (86) (median of 3. 3 million SNVs among 53,831 humans sequenced as part of the NHLBI's Trans-Omics for Precision Medicine program). Relative to the number of SNVs, the level of LINE-1 and SINEC dimorphism we found between two dog genomes is disproportionately large. This total represents an ∼17-fold increase in SINE differences  (16,221/915 ) and an eightfold increase in LINE differences (1,121/128) compared to the numbers found among humans. Remarkably, more dimorphic SINEs were found between these two breed dogs than have been found in studies of thousands of humans  (84, 87). Our data will aid systematic studies of the potential contribution of these elements to canine phenotypes, including cancers  (88).
Methods Genome assembly and analysis utilized long-read and short data from a female Great Dane named Zoey, a pooled fosmid library (89) constructed from Zoey, sequence data generated from a female Boxer, named Tasha, as part of the CanFam genome assembly (4), and results from a custom comparative genomics hybridization array (array-CGH). Data accessions and detailed methods are available in SI Appendix. Genome assembly of ∼50-fold whole-genome, single-molecule, real-time sequencing data from Zoey was performed on DNAnexus using the Falcon 1. 7. 7 pipeline (41) and the Damasker suite  (90). Chimeric contigs were identified based on mapped reads from the Zoey mate-pair jumping library, the Zoey fosmid pools, the Tasha BAC end sequences, and Tasha fosmid end sequences. Regions that showed a lack of concordant paired end coverage were identified as potential chimeric junction sites and split apart prior to scaffolding.
Primary contigs were supplemented with contigs obtained from a local assembly of reads aligning to gaps between contigs on CanFam3. 1 using Canu v1. 3  (42). Contigs were linked into scaffolds using mapping of the Zoey mate data, Tasha BAC end sequence data, and Tasha fosmid data using the BESST scaffolding algorithm (version 2. 2. 7) (43) and assigned to chromosomes based on alignment to CanFam3. 1. Chain files for use with the UCSC liftOver tool were constructed based on blat (47) alignments. A UCSC TrackHub hosting the Zoey assembly, as well as relevant annotations of both the Zoey assembly and CanFam3. 1, is available at https://github. com/ KiddLab/zoey_genome_hub. Common repeats in both the CanFam3. 1 and Zoey assemblies were identified using RepeatMasker version 4. 0. 7 with option "-species dog," using the rmblastn (version 2.
2. 27+) search engine and a combined repeat database consisting of the Dfam_Consensus-20170127 and RepBase-20170127 releases. Self-alignment analysis of each assembly was performed using SEDEF (44) with default parameters. Results were filtered for alignments at least 1 kb in length and at least 90% sequence identity. Read depth analysis was performed using fastCN as described previously  (45). Copy number estimates were constructed in nonoverlapping windows each containing 3 kbp of unmasked sequence. Segmental duplications were identified as runs of four windows in a row with an estimated copy number of ≥2. 5. To provide an unbiased assessment of duplication content, read depth analysis was performed based on Illumina data form Penelope, an Iberian Wolf, in addition to sequences from Zoey and Tasha.
Forty-two canine RNA-Seq runs representing 11 tissue types were used to annotate genes in the Zoey genome  (5). De novo gene models were created based on alignment of RNA-Seq reads using Cufflinks (v2. 2. 1)  (48, 49)  and, in a non-reference-guided fashion, using Trinity (v2. 3. 2) (50). Gene models were merged and annotated using PASA-Lite  (91)  and the transdecoder pipeline (version 5. 0. 1) (92). Gene names and functional annotations were determined using BLAST2GO  (93). Expression levels for each of the 22,182 protein-coding gene models were estimated using Kallisto (version 0. 46. 0) (94). Long noncoding RNAs in the Zoey genome were identified using the FEELnc program  (51). To identify large insertion and deletion variants, the Zoey assembly and 6,857 secondary contigs were aligned to CanFam3.
1 using minimap2 (version 2. 9-r720) with the -asm5 option  (95). The output from the alignment was parsed using the paftools. js program released as part of minimap2 to identify candidate variants. Breakpoint coordinates were refined by performing targeted alignment of the flanking and variant sequence for each candidate using AGE  (96). Individual fosmids containing potentially full-length L1_Cf elements were isolated from pools using a lifting procedure coupled with hybridization of a probe containing digoxygenin-labeled dUTP. Isolated fosmids were sequenced in small pools via RS II PacBio sequencing and assembled using the HGAP2 software  (97). An intact L1_Cf was subcloned from fosmid 104_5, equipped with an mneoI retrotransposition indicator cassette, and tested for retrotransposition in HeLa-HA cells  (72, 73).
We replaced the AluYa5 sequence with the SINEC_Cf consensus sequence, obtained from Repbase  (98). The resultant construct was used to assay SINEC_Cf mobilization, in trans, in the presence of either an active human LINE-1 or the newly cloned L1_Cf-104_5 expression plasmid that lacks the retrotransposition indicator cassette (JM101/L1. 3Δneo or ADL1Cf-104_5Δneo, respectively). The construction of the SINEC_Cf expression vector and the conditions used to assay for retrotransposition are detailed in SI Appendix, section 6. Data Availability. Data have been deposited in National Center for Biotechnology Information GenBank database under accessions GCA_ 005444595. 1, SWLD00000000. 1, MK829534-MK829589, and MT811810; to the Sequence Read Archive under sample name SAMN04851098; and to the Gene Expression Omnibus database under accession GSE153608.
ACKNOWLEDGMENTS. This work was supported, in part, by  NIH  Grant  R01GM103961  to J. M. K. and A. R. B. ,  NIH  Grant  R01GM140135  to J. V. M. and J. M. K. ,  NIH   Academic Research Enhancement Award   R15GM122028  to J. V. H. , and  NIH   Training Fellowship   T32HG00040  to A. L. P. DNA samples were provided by the  Cornell Veterinary Biobank , a resource built with the support of  NIH  Grant  R24GM082910 , and the  Cornell University College of Veterinary Medicine. Additional DNA samples were kindly provided by  Brian Davis ,  Elaine Ostrander , and  Linda Gates. We thank  Dorina Twigg ,  Chai Fungtammasan ,  Brett Hannigan ,  Mark Mooney ,  Dylan Pollard , and DNAnexus for assistance with sequence data processing, and the  University of Michigan Advanced Genomics Core  for assistance with data production.
For measurements, an ocular micrometer was used; all measurements are in millimetres (mm). Geographical coordinates are presented in the WGS 84 system. For identification we relied on several bibliographical sources  (Georgescu 1989 , Wunderlich 1992 , Weiss & Sárbu 1994 , Bosmans 1999 , Bosselaers 2009 , Deltshev & Wang 2016 , Boubakri et al. 2020 ) and databases  (Nentwig et al. 2021 , Oger 2021). The taxonomic status follows the World Spider Catalog (2021). Abstract. The female of Agraecina agadirensis was discovered during a scientific internship in autumn 2019 in a cave system of the Moroccan High Atlas. Since then, several surveys were needed to find a male of the species, which was finally collected in April 2021. Based on this specimen, a detailed description, an extended taxonomic diagnosis, photos of the habitus, as well as drawings of the male pedipalpus are presented.
Acknowledgements We thank the  Museum of Natural History of Marrakech , the  Cadi Ayyad University of Marrakech ,  S'khifa Abderrahim  for his help during the last expedition and  Pierre Oger  for taking the photos. Our thanks also go to the reviewers and the entire editorial team. We are especially grateful to  Jan Bosselaers  and  Tobias Bauer  for valuable comments that helped to improve the manuscript.
Methods : We searched OVID Medline, EMBASE, and the Cochrane and Campbell Databases for Systematic Reviews published up to April 15 th 2021. Focusing on community (meso-level) and society (macro-level) level NPIs, we included all study designs, while a geographic restriction was limited to the EU, UK and European Economic Area (EEA) countries. Using the PICO framework, two reviewers independently extracted data and assessed quality using appropriate quality appraisal tools. A qualitative synthesis was performed, with NPIs grouped initially by a) Physical Distancing measures, b) Case detection and management measures, and c) hygiene measures and subsequently by country. Results: Of 17,692 studies initially assessed, 45 met all inclusion criteria. Most studies (n=30) had a modelling study design, while 13 were observational, one quasi-experimental and one experimental.
Search Results and PICO Relevant peer-reviewed studies were identified through systematic electronic searches using OVID Medline, EMBASE and the Cochrane and Campbell Databases for Systematic Reviews. The detailed search strategies for the biomedical databases are presented in Supplementary File 1 and included a timeframe between July 27 th , 2020 and until  April 15  th , 2021 and were limited to the EU, UK and EEA countries, within the context of a service contract commissioned by European Center for Disease Prevention and Control (ECDC). Study designs included peer-reviewed studies including but not limited to: Simulation studies using mathematical models or transmission models, cluster and parallel randomised controlled trials (RCTs), cluster and parallel non-RCTs, quasi-experimental studies (including controlled before-after studies, uncontrolled before-after studies, time series, and interrupted time series) that assess the effectiveness of community nonpharmaceutical measures.
Study selection Studies identified from the searches were uploaded into a bibliographic database, and duplicates were removed. Initially, a pilot training title/abstract screening process was used, where a random sample of 100 titles was independently screened for eligibility by two reviewers to enable consistency in screening and identify areas for amendments in the inclusion criteria. A high measure of inter-rater agreement was achieved (percentage agreement>90%), and hence the remaining titles were distributed between the two reviewers and screened independently. For the full-text screening, a similar process was followed. Ten randomly selected studies were independently screened for eligibility by two reviewers (percentage agreement>90%), while the two reviewers subsequently screened the remaining full texts.
Data extraction, synthesis and presentation Data extracted were related to the study characteristics (first author's name, year of publication), geographical context (country/area), setting (where the measures were implemented), population characteristics, sample size, study type, numerical or descriptive findings with regards to the effectiveness of non-pharmaceutical measures in comparison to no intervention or current situation. Two reviewers independently piloted the data extraction template on a random sample of five included studies to assess consistency in data extraction and identify where amendments need to be made to the template. The remaining studies were then data extracted independently by the two reviewers. The results from the studies for each intervention grouping are synthesised initially using a narrative synthesis.
Study Selection A total of 17,692 studies were identified through systematic electronic searches across Medline and Embase. After removing duplicates, 17,661 passed onto the title/abstract review process. Subsequently, 634 studies were found to meet the inclusion criteria after the completion of abstract screening and were further screened for eligibility based on full-text assessment. Through the full-text screening, 588 studies were excluded due to the reported study type (reviews, conference abstracts), little relevance to the topic, limited outcomes of interest, limited data and not eligible geographical area. Hence, 45 studies were eventually considered in our systematic review. The flowchart of study selection and exclusion is presented in Figure  1.
Study Characteristics Among the 45 studies included in this current systematic review, 30 studies were modelling, one was an RCT, one followed a quasi-experimental approach, three were time series, three used a time-trend analysis, and seven were cohort studies. Concerning the type of NPI intervention, 40 studies evaluated different physical distancing measures, while 4 studies focused on case detection and contact tracing strategies and 3 on the implementation of hygiene measures. With regard to the geographical area, studies assessed data from Italy (n=7), Spain (n=3), England (n=9), Scotland (n=1), France (n=3), Germany (n=4), Portugal (n=2), Greece (n=1), Sweden (n=1), Denmark (n=2), Belgium (n=2), Norway (n=1) and the Netherlands (n=1), while 8 studies considered multiple European countries in their analyses.
Strengths and limitations Our systematic review has several strengths, including the systematic approach during study identification, data extraction and quality appraisal that was applied. Some limitations should also be acknowledged. We assessed peer-reviewed and published evidence available until April 2021, much of which included the period before December 2020, and hence the information provided does not adequately cover NPIs in place during the circulation of all variants of concern. As per our inclusion criteria, only studies based in EU/EEA and UK were assessed, and accordingly, the results may not reflect the effectiveness of NPI implementation in other contexts globally -although other systematic reviews of a broader scope indicate similar findings  (66, 67). Furthermore, a significant percentage of identified studies were based on mathematical modelling studies that require many assumptions related to the model design, which may lead to variability in model predictions and uncertainty for decision-makers.
ACKNOWLEDGEMENTS We would like to thank  Chrysa Chatzopoulou  and  Katerina Papathanasaki  for contributing to data archiving and management. We would also like to thank  Rene Niehus  for his helpful comments on an earlier version of this work. This report was commissioned by the  European Centre for Disease Prevention and Control (ECDC) , to the  PREP-EU Consortium , coordinated by the  School of Medicine, University of Crete , under specific contract No. 7 ECD. 23661 within Framework contract  ECDC/2019/001 Lot 1B.
Sample The present study is based on the case-control sample from the EUGEI study (EUropean Network of national schizophrenia networks studying Gene-Environment Interactions); a multisite incidence and case-control study of genetic and environmental determinants involved in the development of psychotic disorders  26. The baseline sample comprises a total of 2627 participants, including 1130 patients aged 18 to 64 years who were resident within the study areas and presented to the adult psychiatric services between May 1, 2010 and April 1, 2015 in 17 sites across 6 countries: England, the Netherlands, Italy, France, Spain and Brazil. All participants provided informed, written consent. Ethical approval was provided by relevant research ethics committees in each of the study sites. All data was stored anonymously.
Genotyping and Polygenic risk scores building DNA from blood tests or saliva sample were obtained from the majority of participants at baseline (73. 6% of cases and 78. 5% of controls), with no sociodemographic differences observed with those without genetic data except for minor age differences (please refer to the Supplementary material section1. 7). All DNA data collected was genotyped at the Cardiff University Institute of Psychological Medicine and Clinical Neurology, using a custom Illumina HumanCoreExome-24 BeadChip genotyping array covering 570,038 genetic variants; and quality control was performed locally (details provided in Supplementary material). In order to control for population stratification, a Principal Component Analysis generating 10 principal components (PC) was run on pruned variants.
Depression PRS was built from a GWAS combining PGC, 23andMe and UK Biobank  7, 10, 34. Finally, we further included the recently developed PRS for IQ  35. All PRS were built using PRSice software  36  , and the selected p-value threshold of 0. 05 for SNP inclusion was chosen across the phenotypes on the basis of the published literature explaining the most variance in case-control analysis  11, 34, 35, 37. Each PRS was standardized to a mean of zero and standard deviation of 1  38.
Acknowledgements EU-GEI  is the acronym of the project ' European network of National Schizophrenia Networks Studying Gene-Environment Interactions ". The research leading to these results has received funding from the  European Community 's  Seventh Framework Programme  under grant agreement No. HEALTH-F2-2010-241909  (Project  EU-GEI ). Victoria Rodriguez  was funded by a PhD scholarship supported by  Lord Leverhulme's Charitable Trust  and by the  Velvet Foundation. Evangelos Vassos  is funded by the  National Institute for Health Research (NIHR) Biomedical Research Centre at South London  and  Maudsley NHS Foundation Trust  and  King's College London. The views expressed are those of the authors and not necessarily those of the  NHS , the  NIHR  or the  Department of Health and Social Care.
Meteorological data Records of daily minimum temperature (°C), daily maximum temperature (°C), and daily rainfall (mm) were obtained from the meteorological station of Calvi in Corsica. This weather station is situated at a maximum of 20 km from each of the study plots and thus gives reliable information on regional meteorological variation (see also  Grosbois et al. 2006). We averaged the daily minimum and maximum ambient temperature to estimate daily average ambient temperature. For each nest during the two weeks following hatching we calculated the average ambient temperature and the average amount of rainfall. This period corresponds to the time when Protocalliphora larvae develop in blue tit nests by intermittently feeding on nestling blood, while spending the rest of the time hidden amongst nest materials  (Hurtrez-Boussès et al.
Statistical analyses This study includes data from 535 broods covering an 18-year period (Table  1 ). Our study only focused on first-clutch broods for which the number of eggs and nestlings was not manipulated, nests that were not experimentally treated against parasites, and nests for which there was no evidence of predation (the main predator at these nestbox study sites is the green whip snake Hierophus viridiflavus). We used the mean number of Protocalliphora larvae per nestling (i. e. the number of larvae and pupae found in a nest divided by the number of chicks present at time of sampling) as a measure of parasite load. All analyses were performed in the statistical programming environment R 3. 2. 2 (http://rproject. org). Model validation was performed by visual inspection of residuals.
Within-year variation in parasite intensity To investigate the relation between parasite intensity and current biotic and abiotic factors, we used linear mixed-effect models with log-transformed parasite load as a dependent variable (lmer from the lme4 package). We applied forward, AIC-based model selection starting with a set of models with nest thickness, cotton bag treatment (with vs without a cotton bag), egg-laying date (in Julian dates), female age, and weather during the nestling stage (average ambient temperature and rainfall) as explanatory variables. Year (n=18), valley (n=2), study site (n=7), nestbox identity (n=243), and female identity (n=385) were included as random effect factors.
Acknowledgements We thank the many students and co-workers that helped maintain the study sites for so many years and all the colleagues for discussions or advice. Monitoring of the long-term studies was financially supported by the  CNRS , the  OSU (OREME) , the  Mediterranean Centre for Environment and Biodiversity (LabEx CeMEB ), and several national or international organizations in the past ( European Commission , European  METABIRD  project , French ANR ). The communities that hosted the study plots kindly allowed access to the different (private) study areas. We also wish to thank  Fango-MAB  and APEEM for logistic support. Finally, we are grateful to two anonymous referees for their suggestions that helped improve the quality of a previous version of this article. A previous version of this article has been reviewed and recommended by  Peer Community In Ecology  (https://doi.
It included protocols for laboratory imaging and sampling, DNA extraction and sequencing, DNA analysis, and data and sample management pipelines. General recommendations for contractors are given by ISA for macrofauna (ISA 2015) and for nematodes, the dominant meiofaunal phylum  (ISA, 2013). Ideally, the morphological (high-resolution photographs and measurements) and genetic data obtained for all sampled taxa should be stored in a reference database. When publishing genetic data in peer-reviewed journals, sequences should be submitted to any of the three International Nucleotide Sequence Databases (GenBank, ENA, or DDBJ) and/or to BOLD (http://www. boldsystems. org/). When facing low barcode amplification or sequencing success, a potential strategy could be to focus on a group that can be sequenced rather successfully (e.
2017). Studies mainly differ in (1) the type of barcode gene used, (2) the precision of the taxonomic identification they allow, considering their marker gene and the reference databases available, and (3) the level of degradation of the DNA extract, determining the length of the barcode region that can be used  (Taberlet et al. 2012). Given that the majority of reference sequences deposited in public databases such as GenBank and Silva (https://www. arb-silva. de/) for meiofauna taxa are ribosomal (V1-V2 region of the 18S small ribosomal subunit), one would preferentially target this locus in order to capitalize on the collective output of past barcoding work. However, because ribosomal RNA (rRNA) genes are under less selective pressure than mitochondrial genes, they provide lower taxonomic resolution and therefore rarely allow accurate taxonomic identification beyond genus level.