dataesr/scientific-paragraphs-categorization huggingface dataset:
Apoptosis assay Control and PRMT1-depleted SK-OV-3 cells were grown for 72 hours in the presence or absence of 20 mM CDDP and apoptosis was measured by means of APC-conjugated Annexin V (Thermo Fisher Scientific) and propidium iodide (Thermo Fisher Scientific), in accordance with the manufacturer's instructions. The samples were acquired using the FACSCalibur platform (BD Bioscience) and analyzed using the FlowJo software. Statistical analysis was performed using ANOVA (Microsoft Excel; Microsoft, Redmond, WA, USA). Statistics analysis included in the Apoptosis assay were performed on samples which were normally distributed and showing the same variance by applying the Two-Factor Without Replication -ANOVA test. Biological replicates n = 3.
4 (n = 3). (C) Functional analysis of the PRMT1 interactome. Proteins enriched in both the native and cross-linked PRMT1 IPs (coIP and ChroP, respectively) were analyzed using the STRING interaction database and the proteins belonging to the same STRING network were visualized using Cytoscape. Primary and secondary interactors of PRMT1 are displayed in dark and light orange, respectively; PRMT1 and DNA-PK are indicated in red and green, respectively. (D) CoIP followed by WB analysis from SK-OV-3 cells treated with 20 mM CDDP and 10 mM NU7026; coIPs were carried out in the presence and absence of 2003 molar excess of PRMT1 blocking peptide, as indicated. The image displayed is representative of 3 biological replicates (n = 3). (E) WB analysis of PRMT1 levels in the soluble and chromatin-enriched fractions of SK-OV-3 cells treated for 24 h with CDDP 20 mM, with or without pre-treatment with NU7026 (10 mM).
Data represent mean ± variation from 2 biological replicates (n = 2). (E) Clonogenic survival assay of SK-OV-3 cells pre-treated with MS094 or MS023 in response to the indicated doses of CDDP. Cells were pre-treated for 24 h with either MS094 or MS023 and then treated for 2 h with CDDP before drug washout. Cells were grown for 6 days and then stained with Crystal violet and quantified using ImageJ. Data represent mean ± SD from 4 biological replicates (n = 4). Statistical significances were determined applying the unpaired 2-tailed t test. *p < 0. 05. (F) Apoptosis assay after 72 h of CDDP (20 mM) exposure of control and PRMT1 knockdown SK-OV-3 cells (shPRMT1#1, #3) analyzed by flow cytometry. Data represent mean ± SD from 3 biological replicates (n = 3). Statistical significances were determined using ANOVA two-factor test; *p < 0.
ACKNOWLEDGMENTS We thank  F. d'Adda di Fagagna  and  V. Costanzo  for critical reading of the manuscript, the  Structural Genomic Consortium  ( SGC, Toronto, Canada ) for providing the MS023 and MS094 compounds,  C. Toscani  for support with the ChIP-qPCR experiment,  C. Soriani  and  S. Rodighiero  of the  IEO Imaging Unit  for generating the ImageJ plug-in for the automatic analysis of IF images,  Fabio Bedin  for the assistance with the analysis of the RNA-seq data, and all members of the  T. Bonaldi laboratory  for helpful discussions. Research activity in the T. B. laboratory has been supported by grants from the  Italian Association for Cancer Research  ( IG-2018-21834 ) and the  CNR-EPIGEN  flagship project and the  Italian Ministry of Health (Bando Giovani Ricercatori, Conv. n. 061/ GR-2009-1580495 ).
Reactions were modeled as first order kinetics. The model was simulated in a mesh of 0. 5 µm 3 voxels 10 µM of diffusible fluorescent mCherry (diffusion coefficient: 20 µm 2 /s) was equally distributed in the neuron. For simulating FLIP experiments, the catalyzer ("laser") was activated in the soma every 30 s. Simulation results were quantified in the same way as the experiments. For simulation of the AIS, two other species were added to the model: a slow diffusible fluorescent mCherry (5 µm 2 /s) and a non-diffusible AIS catalyzer spatially restricted between 10 and 30 µm in the proximal segment of the axon. This chemical reaction mimicked the diffusion barrier of the AIS that locally slows down the diffusion of soluble molecule. The core of the model can be found in the Virtual Cell public database via the VCell software.
Statistics Curve fitting and statistical analyses were performed in Prism (GraphPad). Data are presented as means ± SEM. The number of neurons used for quantification are indicated in the figure legends. Experiments were done in the indicated number of neurons, which were taken from 4 to 8 individual cultures dishes from 2 to 4 neuronal cultures. Multiple comparisons (N > 2 groups) were assessed with Kruskal Wallis' and Dunn's multicomparison tests. Comparisons of matched pairs were assessed with Wilcoxon's test. Comparisons of fractions were assessed with Fisher's exact test.
ACKNOWLEDGMENTS We thank  Ina Bartnik ,  Nicole Fürst , and  Julie NGuyen  for excellent technical assistance. We thank  Erin Schuman  for her generous support. We thank  Zolt Lenkei  for giving us access to the STORM setup of his lab. We thank the imaging facility of the IPNP and especially  Lydia Danglot  and  David Geny  for their assistance in setting up FLIP experiments at the IPNP. The spinning disk microscope of the IPNP was purchased thank to the support of the Foundation Bettencourt. We also thank  Lisa Kochen  for her critical reading of the manuscript.
FUNDING Part of this work was done in the laboratory of Erin Schuman at the  Max Planck Institute for Brain Research  and was supported by the  Max Planck Society , the  European Research Council ,  DFG CRC 902 ,  1080 , and the  DFG Cluster of Excellence for Macromolecular Complexes. Work in the laboratory of CH was supported by  Inserm ,  Université de Paris , the  NRJ Foundation  and the  Agence Nationale de la Recherche  ( ANR-16-CE16-0009-01 ).
Helminth infections are ubiquitous in grazing ruminant production systems, and are responsible for significant costs and production losses. Anthelmintic Resistance (AR) in parasites is now widespread throughout Europe, although there are still gaps in our knowledge in some regions and countries. AR is a major threat to the sustainability of modern ruminant livestock production, resulting in reduced productivity, compromised animal health and welfare, and increased greenhouse gas emissions through increased parasitism and farm inputs. A better understanding of the extent of AR in Europe is needed to develop and advocate more sustainable parasite control approaches. A database of European published and unpublished AR research on gastrointestinal nematodes (GIN) and liver fluke (Fasciola hepatica) was collated by members of the European COST Action "COMBAR" (Combatting Anthelmintic Resistance in Ruminants), and combined with data from a previous systematic review of AR in GIN.
All major GIN genera survived treatment in various studies. In cattle, prevalence of AR varied between anthelmintic classes from 0-100% (BZ and ML), 0-17% (LEV) and 0-73% (MOX), and both Cooperia and Ostertagia survived treatment. Suspected AR in F. hepatica was reported in 21 studies spanning 6 countries. For GIN and particularly F. hepatica, there was a bias towards preferential sampling of individual farms with suspected AR, and research effort was biased towards Western Europe and particularly the United Kingdom. Ongoing capture of future results in the live database, efforts to avoid bias in farm recruitment, more accurate tests for AR, and stronger appreciation of the importance of AR among the agricultural industry and policy makers, will support more sophisticated analyses of factors contributing to AR and effective strategies to slow its spread.
Resume-Importance croissante de la résistance aux anthelminthiques chez les ruminants européens : création et méta-analyse d'une base de données ouverte. Les helminthes sont omniprésents dans les systèmes de production de ruminants au pâturage et sont responsables de coûts et de pertes de production importants. La résistance aux anthelminthiques (RA) des parasites est maintenant répandue dans toute l'Europe, bien qu'il existe encore des lacunes dans nos connaissances dans certaines régions et certains pays. La RA est une menace majeure pour la pérennité de la production moderne de ruminants, en diminuant la productivité, en compromettant la santé et le bien-être des animaux, et en augmentant les émissions de gaz à effet de serre au travers d'une augmentation du parasitisme et des intrants agricoles.
Une meilleure compréhension de l'étendue de la RA en Europe est nécessaire pour développer et préconiser des approches de lutte antiparasitaire plus durables. Une base de données intégrant des informations publiées et non publiées en Europe concernant la RA des nématodes gastro-intestinaux (NGI) et de la douve du foie (Fasciola hepatica) a été compilée par les membres de l'action européenne COST « COMBAR » (« Combattre la résistance aux anthelminthiques chez les ruminants ») et combinée avec les données d'une précédente étude systématique concernant la RA des NGI. Au total, 197 publications sur la RA des NGI étaient disponibles pour analyse, représentant 535 études dans 22 pays et couvrant la période 1980-2020. Des signalements de RA étaient présents sur tout le continent européen et certains rapports indiquaient une forte prévalence nationale.
Data collection and processing A standardised spreadsheet model was populated with data from the previous systematic review  [42]. Members of the COMBAR consortium were then invited to populate the spreadsheet with published and unpublished data for completed research for their respective country and surrounding countries, if no representative was present in the consortium (e. g. Finland). The database consequently included reports from 1980-2020. In adherence to the PRISMA guidelines, contributing authors were asked to search electronic databases (e. g. PubMed, ISI Web of Science) and unpublished studies with no language or date restrictions. Data requested included the host species, region, number of farms tested, anthelmintic drug class and active compound tested, whether AR was detected  (1)  or not (0), the proportion of farms tested where AR was detected, reference, DOI (if applicable) and publication type (unpublished, peer-reviewed paper, Master or PhD thesis, report, or conference abstract/proceeding).
Each publication was screened for eligibility (i. e. a study reporting the presence or absence of AR in ruminant livestock helminths on the European continent), duplicates eliminated, and the eligible studies fully reviewed. The data were then edited for consistency and checked against the relevant publication (if applicable) by the lead author, before being checked a second time by participating consortium members. The consortium member responsible for the final check is recorded in the database. Each publication or unpublished dataset, hereafter referred to as "publication", was given a unique identifying number. Within each publication, multiple anthelmintic classes and livestock classes tested were entered as separate entries, hereafter referred to as "studies". Therefore, one "publication" may contain several "studies".
When a publication presented separate data for different regions within the same country, these data were split into separate rows (studies) in the database (e. g. [20] ). When a publication presented data together for different regions within the same country, the data were entered as a single row (study) in the database (e. g. [17] ). For GIN, data were stratified primarily by host species and anthelmintic class, with the exception of the ML, which were divided into avermectins (e. g. ivermectin) and milbemycins (i. e. moxidectin, MOX). Hereafter, MOX is analysed separately to the other ML. Other classes were benzimidazoles (BZ), imidazothiazoles, i. e. levamisole (LEV), amino-acetonitrile derivatives, i. e. monepantel (MPTL), and salicylanilides, i. e. closantel (CLOS). Studies testing more than one anthelmintic simultaneously in the same animals were entered as combination treatments (COMB), except where the combination involved MOX and ivermectin; in this case the anthelmintic class was entered as MOX due to its relatively high efficacy against some ivermectin-resistant populations of GIN, and observations that the extent of cross-resistance is greater in ivermectin than MOX-resistant populations (reviewed by  [39] ).
Data analysis Prevalence, uncertainty and heterogeneity Data analysis was completed in R v3. 6. 1  [40]. Figures were prepared using the base R, "ggplot2"  [54]  and "ggpubr"  [28]  packages. Tables were prepared using the sjPlot R package  [32]. Maps were prepared using the "rnaturalearth"  [48] , "rgeos"  [5]  and "ggspatial"  [13]  packages. GIN AR prevalence for each anthelmintic class and ruminant species were estimated from the reported prevalences and were weighted by sample size (number of farms in each study) to give a weighted mean ( x w ), using the "weighted. mean" function in R. Analyses were performed within each country with data, and overall across Europe. Corresponding sample size weighted standard deviations were estimated using Equation  (1) , where x = the proportion of farms with AR, w = weights (sample size divided by the sum of all samples): r w ¼ X ðw Â ðx À x w Þ 2 Þ: Heterogeneity in AR prevalence estimates between studies (aggregated by anthelmintic class and host species) was estimated using the I 2 statistic  [21] , calculated as described by Neyeloff et al.
7, 0. 8, 0. 4 and 0. 1, would score (1 + 0. 7 + 0. 8 + 0. 4 + 5 = 7. 9). For liver fluke, seven actives were included in both p and n a (see Results). Confidence was not estimated from prevalence; rather, it is an index of research effort, taking into account the depth and breadth of investigation into the AR situation nationally: Confidence research effort ð Þ¼ log 10 S ð Þ max log 10 S ð Þ ð Þ þ log 10 F ð Þ max log 10 F ð Þ ð Þ þ A; where, for each country, S is the number of separate publications (or unpublished reports) in the database, F the total number of farms included, and A the total number of anthelmintic classes investigated. F is the sum of the total number of farms used per study, regardless of how many anthelmintics were assessed on each, to prevent double counting. Both S and F were log 10 -transformed to stabilise variance, and scaled to the maximum value across countries (i.
e. , divided by the highest national value), to provide a measure of the relative research effort among countries in the database at the time of the analysis. One publication from Ireland included data from 4211 farms but used pooled faecal samples collected by farmers: for this case, the number of farms was divided by an arbitrary value of 10 before entry into the equation, to avoid unfair comparison with studies using full FECRT. The confidence index itself is arbitrary, but standardised across countries, and aims to assess the relative extent to which AR has been thoroughly investigated, to aid interpretation and prioritisation of future research. Results of Level versus Confidence (= Research effort) were plotted for each country: separately for GIN in either sheep, goats or cattle, and for fluke for all host species combined.
Change in anthelmintic resistance over time Anthelmintic Resistance is a dynamic process, evolving as helminth populations experience repeated treatment, and as farmers change to more effective anthelmintics when treatment failure is recognised. Research on AR is also dynamic, often responding initially to reports of treatment failure on particular farms, before expanding to prospective surveys, with highly variable selection criteria, and assessing additional anthelmintic groups as they become available or fall under suspicion of failure. Because of this, prevalence data averaged over a long period are unlikely to accurately capture the current situation in any given country, or trends in AR over time. To address these confounders, change in prevalence was evaluated over time. Reports of AR on single farms were excluded, since these are often conducted in response to suspected treatment failure.
Studies in sheep and goats were combined to increase power, given that helminth species are largely shared between these hosts. Italy was excluded because its combination of low AR prevalence and high level of reporting in recent years (19/20 reports in sheep and goats coming after 2007) strongly affected the overall trajectory across countries, and a single large study in the UK focusing only on Nematodirus battus was also excluded. Initially, average prevalence was plotted for each anthelmintic group for each decade, to visualise trends in AR over time. The database was then searched separately for each anthelmintic group in GIN in sheep, goats and cattle, and fluke in all hosts. For each country meeting these criteria (including Italy), correlation between prevalence and year was assessed as above.
Change in reported anthelmintic resistance over time Prevalence of AR tended to increase over the 41 years included in the database (Fig. 5 ), gradually for BZ and more abruptly for ML (including MOX). Aggregated results in sheep and goats since 2010 returned average prevalence of resistance to benzimidazoles (BZ) of 86%, levamisole (LEV) 48%, macrocyclic lactones except moxidectin (ML) 52%, and moxidectin (MOX) 21%. Reports of farms with GIN resistant to LEV became more common between 1980 and 2009, but then decreased in 2010-2020. Taking reports from sheep, goats and cattle separately for each anthelmintic group, there was no significant correlation between farm-level prevalence of AR and year. In cattle, the prevalence of AR varied widely between anthelmintic classes from 0-100% (BZ and ML), 0-17% (LEV) and 0-73% (MOX).
Only 6 of the 61 studies of cattle GIN in the database were conducted prior to 2009, however, and the median number of farms included was six, so the power to track change over time was very limited. Similarly, database entries for liver fluke comprised 34 studies from 18 sources, of which three were prior to 2009, and the median number of farms per study was one, precluding further exploration of temporal trends in AR. For GIN in sheep, six countries reported at least three studies in different years, excluding single-farm case reports: France (BZ), Italy (BZ, LEV, ML), the Netherlands (BZ, ML), Slovakia (BZ) Switzerland (BZ), and the United Kingdom (BZ, LEV, ML). No countries met this criterion for GIN in goats or cattle, or fluke. Further analysis of these 11 countryanthelmintic group combinations for GIN in sheep, on arcsine-transformed prevalence and with a Bonferroni-adjusted critical p-value of 0.
Discussion In the present study, we reviewed the published and unpublished literature on AR in ruminant livestock in Europe from 1980 to 2020 to strengthen the current evidence base of this phenomenon at country and continental levels. A database of European AR research was compiled by experts to summarise research effort and AR status throughout Europe. The analyses provide heuristic prevalence estimates based on the best available data, which serve as a baseline for future AR research, guided by updated statistical guidelines  [26]. This analytical approach also helps identify research limitations and opportunities for improvement. Despite available evidence of widespread AR in Europe, this study showed that harmonised surveys Figure  3. Estimated prevalence of resistance against the benzimidazoles (BZ), levamisole (LEV), avermectins (ML; macrocyclic lactones), and moxidectin (MOX) in gastrointestinal nematodes in sheep.
Points and whiskers represent the weighted prevalence estimate and standard deviation, respectively. The weighted prevalence and standard deviation across all studies are represented by the dashed black and grey vertical lines, respectively. Note that points without whiskers represent single studies, for which standard deviations could not be estimated (i. e. they do not represent points which the prevalence is known with a high level of confidence). Corresponding figures for goats and cattle, and for sheep, goats and cattle using only studies with n > 9 can be found in the Supplementary Material. Table  1. Mean (SD in parenthesis) sample size-weighted prevalence of anthelmintic resistance stratified by anthelmintic class and host livestock sector. BZ = benzimidazole; LEV = levamisole; ML = avermectins; MOX = moxidectin; MPTL = monepantel; CLOS = closantel; -= no data available.
Current status of anthelmintic resistance in Europe and reporting bias Anthelmintic resistance in GIN was reported throughout Europe and was detected wherever studies were conducted (with some notable exceptions, e. g. Italy). Prevalence of AR in GIN against BZ, LEV, ML and MOX ranged between 0% and 48% when averaged over the entire database, but confidence intervals were wide and there was a high level of heterogeneity between studies. There was also considerable variation within and between regions depending on host species and anthelmintic class. Ten studies were largely in agreement that AR against MPTL in sheep is currently rare in Europe, although these studies were focussed on only six countries. AR in F. hepatica was reported in only five countries, and there were insufficient data to draw conclusions on AR in GIN against CLOS.
Although consultation with regional experts to compile unpublished datasets (almost a quarter of all publications), and implementing looser inclusion criteria, allowed the inclusion of data from more countries than in previous reviews  [42] , publications were still biased towards Western European countries. This appeared to be somewhat needs-led and justified by the estimated economic impact of helminth infections in these countries  [9]. Nevertheless, spatial sampling bias, e. g. due to research expenditure, convenience sampling (e. g. close to research institutions or close to highways) or cultural differences (e. g. regional variability in response rates), can limit the analysis and interpretation of AR data. Furthermore, with some notable exceptions (e. g. studies of AR in cattle in Italy), there was a bias towards publishing positive findings: this is evident in the fact that the spatial country-level distribution of AR in Europe (Fig.
Research effort and priorities for future investment The relationship between research effort and observed AR was investigated semi-quantitatively using composite indices of level of AR across anthelmintic groups and research effort or confidence, per country. Level of AR included the number of anthelmintic groups to which AR was reported and observed prevalence of resistance to each (i. e. proportion of farms with AR). Research effort, indicative of relative confidence in the levels of AR, comprised the number of studies in the database, the total number of farms investigated, and the number of anthelmintic groups tested. The positive relationship between level of AR and research effort in the better-studied systems (especially GIN in sheep) is to be expected for two main reasons. Firstly, as more studies are conducted and more anthelmintic groups tested, the chance of finding AR increases.
The gold standard for assessing AR, the CET, requires slaughter of both control animals and treated animals, and is not suitable for monitoring on commercial farms. Each FECRT or in vitro method is open to error, e. g. FECs are an indirect measure of anthelmintic efficacy against adult helminths. Sample size within the existing database was not sufficiently high to compare AR prevalence across countries while taking account of variation in method and would be further undermined by concealed variation and bias.