dataesr/scientific-paragraphs-categorization huggingface dataset:
Explanatory variables We gathered two sets of explanatory variables: the first set came directly from the 500-ENI network and reflects agricultural practices assessed directly on the sites (see  Andrade et al. , 2021) ; the second set was compiled from external open access databases. These include soil, climate and landscape data (see below). Agricultural practices were reported yearly from interviews of farmers into an online database according to a national standardized acquisition protocol. This data related to fertilization, pesticide use, tillage and boundary management (Appendix A, Fig. SA. 3). Soil characteristics in the 0-5 cm layer were acquired at a resolution of 250 m from SoilGrids  (Hengl et al. , 2014). Climatic data by year and season were obtained from the Chelsa database for the period 1979-2013, at a resolution of 1 km  (Karger et al.
, 2017). By using this dataset, we assumed that climate did not change dramatically between this period and our sampling period, or that any change that did occur conserved a similar spatial structure of climatic variability across sites. We also extracted landscape descriptors from OSO land cover maps at a 10 m resolution for 2016  (Inglada et al. , 2017). We considered percent cover of eight landscape classes (Appendix A, Fig. SA. 3) within buffers of 1 km radius, and used the Shannon diversity index (SHDI)  (Turner & Gardner, 2015)  to characterize compositional landscape heterogeneity. Shannon diversity was also estimated for crop landscape diversity within a buffer of 1 km, considering 17 types of crops (Appendix A, Fig. SA. 3) retrieved from the external databases OSO  (Inglada et al.
, 2017) , TOPO (IGN, 2019) and the Graphical Parcel Register (IGN & ASP, 2019). Our dataset contained missing values for agricultural drivers that were occasionally left empty by the local observers. We used a multivariate imputation method based on a random forest algorithm (package mice of R v. 4. 0. 0,  Buuren & Groothuis-Oudshoorn, 2011)  to complete these data (see Appendix B for details). For compositional analyses, all explanatory variables were standardized to have equal mean and standard deviation. We limited the number of explanatory variables to seven (Table  1 ) so that we could include the same ones at different resolutions (see section on data analysis below). We aimed at representing the essential variables in different categories (climate, soil, landscape and practices) ensuring that they were not highly correlated (Pearson correlation coefficient < 0.
Data analysis We used two statistical methods: spatial simultaneous autoregressive models (SAR) with species richness as response variable, and generalized dissimilarity models (GDM) to study species composition while dealing with nonlinear relationships between environmental distance and species turnover  (Ferrier et al. , 2007). These two types of analyses were applied at the national extent using different resolutions, and then at regional and national extents using the site-level resolution. SAR models were implemented with the package spdep (function errorsarlm) using a correlated spatial error term, which is a function of distance between sites up to a threshold distance, which corresponds to the distance at which autocorrelation becomes non-significant (Appendix C)  (Cressie, 2015).
Overall, this led to some variation in the number of sites and grid cells across analyses, which were investigated by resampling (Table  2 , Appendix D). Whenever possible, explanatory data were directly extracted at the scale of interest (climate, soil and landscape). All other factors were averaged by grid cell from site-level data, including the frequency of occurrence by site. Species richness in each grid cell was obtained by aggregating site-level species lists to recalculate richness at the aggregated scale. In all spatial analyses involving aggregated datasets, we used the coordinates of the grid cell centroids. Lastly, we carried out the same analysis using site-level data at two different extents: national and regional. For this purpose, sites were grouped within ten biogeographical regions standing for the wide pedoclimatic and floristic gradients in France (Fig.
, 2010). We therefore encourage agricultural stakeholders and scientists involved in monitoring programs to further evaluate the changes in field margin flora and its protection measures across different spatial scales, and implement regulatory measures that incorporate landscape-level management planning adapted to each biogeographic and agricultural region. like to thank everyone that has collected data in the field, the farmers who provided information on their practices, and everyone involved in the coordination of the 500-ENI data network. We would also like to thank the three anonymous reviewers who contributed to improving previous versions of this article.
Funding This work was supported by an  INRAE-ANSES  thesis fellowship to  Isis Poinas  and by the  Ecophyto II+  project  GTP 500   ENI  ( OFB-21-1642 ), as well as from the  BIODIVIN  project funded by the  Office Français de la Biodiversité (OFB)  and the  Fédération Régionale des Chasseurs d'Occitanie (FRC Occitanie).
Amplifications were carried out in a thermal cycler LifeEco (BIOER Technology, France) using the following PCR program: initial denaturation at 94˚C for 1 min followed by 35 cycles at 95˚C for 30 s, 60˚C for 1 min, and 72˚C for 1 min and a final extension at 72˚C for 10 min. Amplification products were then subjected to direct Sanger sequencing, using the same primers as for PCR amplification (GATC Biotech, Germany). To analyse cytb gene partial sequence and investigate point mutations in resistant strains, the new sequences were aligned with Jalview  [26]  against a P. viticola cytb sequence used as reference (accession number DQ459459. 1).
PCR products (3 μl of the initial reaction mixture) were separated on a 1. 2% agarose gel stained with SYBR 1 Safe (Invitrogen™, France). Gel production and electrophoresis were conducted using TAE buffer (40 mM Tris-acetate pH 8. 0, 1 mM EDTA). Pyrosequencing reactions were performed in a PyroMark Q48 Autoprep instrument (Qiagen, France) using PyroMark 1 Q48 Advanced Reagents kit (Qiagen) with 3 μl of PyroMark Q48 magnetic beads (Qiagen) and 10 μl of biotinylated PCR products following manufacturer's instructions. The sequencing primers provided in dedicated PyroID kit (CONIPHY, France) were used to detect E203-DE-V204 and L201S or E203-VE-V204. For validation of assays, 5 replicates of total DNA extracted from sensitive and resistant single sporangia isolates were analysed. Allele frequencies were estimated using PyroMark software.
Illumina barcoded libraries were sequenced with a Reagent kit v2 in PE 2x250 bp on a MiSeq sequencer. Nanopore libraries were finalized and barcoded with the PCR Barcoding kit protocol (SQK-PBK004, ONT) and sequenced on Flongle flow cells (FLO-FLG001, ONT) with Mk1C or MinION coupled with MinIT. High accuracy basecalling was performed for all Nanopore runs with Guppy version 3. 2. 9 or 4. 3. 4. Short and long raw reads datasets were deposited to SRA database under BioProject accession PRJNA892502.
NGS data analyses Ion Torrent reads were analysed using the AmpliSeq design above and DQ459459. 1 as a reference. Torrent Variant Caller (TVC) plugin proposed by ThermoFisher Scientific in the Torrent Suite Software was launched with a generic configuration for somatic and low stringency parameters. In this configuration, 2000 reads are considered to characterize new variants and low frequency detection is optimized (usually detection is not given below 5%). Illumina reads were analysed with Galaxy Europe (https://usegalaxy. eu) or with our own instance. Roughly, for each sample, R1 and R2 reads were paired and then sorted by type of fragment. Five thousand reads were sampled for each of the 5 fragments and mapped with minimap2  [27]  on the DQ459459. 1 reference. The Bayesian genetic variant detector FreeBayes  [28]  was used (option simple diploid calling with filtering and coverage) to find polymorphisms and VCFlib  [29]  used to extract the variable positions in a table format with reads count.
Nanopore reads were analysed with a dedicated pipeline designed in command lines. Only reads higher than Q7 were considered. Five thousand reads were sampled for each sample and mapped on the DQ459459. 1 reference with minimap2. Six regions or positions identified by this study as variable were searched with either a BLAST  [30]  approach or a Nanopolish (https://github. com/jts/nanopolish) analysis. Frequency at each position was estimated by counting the number of reads with the variant versus the total reads number. To identify complete cytb sequence with multiple polymorphisms, each single polymorphism was searched independently among the previous 5000 long reads sampled. All unique reads containing at least one polymorphism were then considered as a whole and proportion of reads containing one or multiple variants along the same read were computed.
On the contrary, long ONT reads have a lower quality (reads with QV<12), which sometimes makes it more difficult to identify low frequency substitutions. Still, the diversity within a population of long fragments can be confidently evaluated, allowing the clear identification of different haplotypes and their proportion on the long sequences. Taking advantage of these NGS specificities, we investigated in our datasets whether in some cases certain variants could be present in combination along the same cytb sequence or whether each variant corresponds to different cytb sequences. As the variants searched for in this study were amplified on different short fragments, only the long reads, i. e. complete cytb sequences, were explored. The reads obtained for 12 populations with at least 2 types of variants were analysed in more detail (Table  3, Fig 2).
However, although we detect the possible simultaneous presence of some variants (e. g. G143A and E203-DE-V204), a low frequency could simply be the result of the background noise of the method. For this reason, the same 5% threshold was applied to consider a proportion of reads with a combination of variants as significant, leading to the restriction of the dataset to 4 populations only. In the CONI-P16 sample, approximately 40% of the reads identified with the S34L variant, also contained the E203-DE-V204 variant (Fig  2 ). Very few reads (5. 8%) were affected by this combined pattern, suggesting that only a few strains of P. viticola may be double resistant to cyazofamid and ametoctradin at present, or that the simultaneous presence of both cytb modifications may be deleterious to P. viticola.
Acknowledgments We thank the  Freiburg Galaxy Team  for developing and giving free access to the  Galaxy Europe platform. We also gratefully acknowledge the support of the  Centre Blaise Pascal 's IT test platform at  ENS de Lyon (Lyon, France) , and in particular  Emmanuel Quemener , for the development and maintenance of the local ENS Galaxy platform. This platform operates the SIDUS solution [60] developed by  Emmanuel Quemener.
These paradoxical outcomes depend, to some extent, on the ability of the host immune response to support the management of pathogenic bacteria through immunophage synergy. The recent reports reviewed here have shown that in vitro-selected phage-resistant clones display mutational convergence with in vivo-selected clones. We can, therefore, anticipate that the characterisation of each putative therapeutic phage will, in the future, include the sequencing of phage-resistant clones selected in vitro. Moreover, these resistant clones should also be further exploited to determine their susceptibility to other phages. The incorporation of these data into public databases will help guide the choice of the phages to be assembled into therapeutic cocktails  [57]. The mutational convergence between in vitro and in vivo conditions argues against a direct role of the immune system in the type of selection acting on phage-resistant clones.
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants has led to the development and approval of the Omicron-containing bivalent messenger ribonucleic acid (mRNA) COVID-19 vaccines  1  , and more recently, approval of a Beta-variant containing recombinant protein based booster vaccine with AS03 adjuvant (MVB. 1. 351) in Europe and United Kingdom 2. We previously reported safety and immunogenicity data measured at 15 days after booster from a head-to-head randomized trial comparing monovalent (MV) ancestral and MVB. 1. 351 vaccines (Sanofi) to the mRNA BNT162b2 vaccine (Pfizer-BioNTech)  3. Our study showed that the MVB. 1. 351 induced higher neutralizing antibodies (nAb) against a broad panel of variants (i. e. , ancestral strain, Beta, Delta, Omicron BA. 1) than homologous boosting with BNT162b2 vaccine.
Here, we report the persistence of cross-neutralizing antibodies, including against Omicron BA. 4/5, extended up to 1 and 3 months after booster from the same study. The design of this multicenter, randomized, single-blind trial (ClinicalTrials. gov NCT05124171; EudraCT number 2021004550-33) has been previously described  3. Briefly, between December 2021 and January 2022, adult participants who had received primary vaccination with two doses of BNT162b2 (second administration received between 3 and 7 months earlier) were recruited and randomly assigned to receive one of 3 vaccines as a third administration (first booster): MVB. 1. 351, MV ancestral recombinant protein (MVD614), or BNT162b2. A subset of participants from the original per protocol population (PPAS) with available blood samples collected at Day 0 (D0, before vaccine administration), at 28 days (D28), and 3 months (M3) postbooster were contacted to reobtain their informed consent for additional testing (195/208 participants).
Animal Sampling Soon after a pet owner's COVID-19 positive test and with their consent, we visited their home to sample pets. At the home visit, we also collected data on the pet's breed, age, sex, main clinical signs, and date of onset of clinical signs, as well as owner data, such as the date of onset of symptoms, the date of their COVID-19 positive result, and the nature of their interactions with the animal. Animals were sampled at home with the cooperation of veterinarians under the direction of the Congolese Minister of Agriculture, Fisheries, and Livestock (MAEP). The veterinarians were provided personal protective equipment and collected two nasopharyngeal and one rectal swabs from each animal. Each nasopharyngeal and rectal swab was suspended in 500 µL of phosphate-buffered saline (PBS) in 2 mL cryotubes and placed in a coolbox until arrival at the Congolese National Public Health Laboratory (LNSP), where they were immediately analyzed or kept in a -80 °C freezer until analysis.
Animal Sampling Soon after a pet owner's COVID-19 positive test and with their consent, we visited their home to sample pets. At the home visit, we also collected data on the pet's breed, age, sex, main clinical signs, and date of onset of clinical signs, as well as owner data, such as the date of onset of symptoms, the date of their COVID-19 positive result, and the nature of their interactions with the animal. Animals were sampled at home with the cooperation of veterinarians under the direction of the Congolese Minister of Agriculture, Fisheries, and Livestock (MAEP). The veterinarians were provided personal protective equipment and collected two nasopharyngeal and one rectal swabs from each animal. Each nasopharyngeal and rectal swab was suspended in 500 µL of phosphate-buffered saline (PBS) in 2 mL cryotubes and placed in a coolbox until arrival at the Congolese National Public Health Laboratory (LNSP), where they were immediately analyzed or kept in a -80 • C freezer until analysis.
Genome Sequencing and Phylogenetic Analysis We performed whole-genome sequencing of 14 SARS-CoV-2 samples using a previously described method combining an Ampliseq approach with MinION Nanopore technology, used for routine SARS-CoV2 sequencing in the virology department of the Caen University Hospital, Normandy, France  [29]. Unfortunately, pet owner samples were unavailable in the LNSP for sequence comparison. Phylogenetic analyses included the 10 SARS-CoV-2 genomes of pets sequenced in this study, the reference strain NC_045512-Wuhan-Hu-1, all sequences of SARS-CoV-2 detected in humans in RoC, and representative sequences of VOCs detected in South Africa, Brazil, Botswana, and the UK available from the Global Initiative on Sharing All Influenza Data (GISAID). SARS-CoV-2 genomes originating from Congo were extracted in January 2022 from the GISAID database and filtered on the following parameters: complete genomes, high coverage, and low coverage excluded (n = 89).
The dataset was then aligned using MAFFT version 7. 407  [30]  with auto parameters and visually inspected using Seaview  [30]. Phylogenetic reconstruction was performed using Beast Suite version 1. 10. 4 [31] , using the GTR model of evolution with gamma distribution and invariable site parameters, a coalescent constant size model, collection dates as tree priors, and an uncorrelated relaxed clock model with lognormal distribution  [32]. Posterior probability values were used as an estimation of node support. Four hundred million iterations of the Markov chain were launched on an 18 double-core computer in order to reach an effective sampling size over 200 for each statistic parameter. A total of ten thousand trees were computed to obtain the final maximum credibility tree. Genomic sequences were aligned using MAFFT version 7.
Our seroprevalence data suggest that infection rates are likely higher than those observed using RT-qPCR, as SARS-CoV-2 RNA had not been detected in 25. 7% (18/70) of the serologically positive pets later tested by MIA. This difference in detection between MIA and RT-qPCR may be due to a smaller detection window in RT-PCR than in MIA. Pet samples that remained positive for SARS-CoV-2 RNA following an initial positive test included those collected with nasopharyngeal swabs 1 to 12 days and 1 to 17 days in dogs and cats, respectively, as well as rectal swabs collected 1 to 3 days later in dogs. Variable viral shedding periods ranging from one to 31 days have been reported in naturally infected dogs and cats  [15, 17, 28, 34]. These results highlight a potentially lengthy period of SARS-CoV-2 viral shedding in pets, which may increase the risk of contamination of humans or wildlife via close contact or via contaminated biological material such as respiratory drops, saliva, or even feces.
Contributions: E. M. L. and F. R. N. designed the study, L. H. L. , C. M. and R. J. N. collected samples, L. H. L. , D. d. R. D. F. , S. C. , W. S. M. and J. E. L. D. , N. -T. conducted laboratory work, D. d. R. D. F. , S. C. and M. A. G. conducted phylogenetic analyses, L. H. L. , M. F. , E. M. L. , M. F. , P. B. , P. I. M. , N. -T. and F. K. -K. drafted the manuscript. All authors have read and agreed to the published version of the manuscript. Funding: The study was funded by the French National Agency for Research (ANR-20-COV2-0003-01, SPILLBACK: SARS-CoV-2 endemization in wildlife of an African tropical rainforest through COVID-19 spread in the Republic of the Congo) and by the World Organization for Animal Health (WOAH) through the European Union (EBO-SURSY: FOOD/2016/379-660: Capacity building and surveillance for Ebola virus disease).
Author Contributions: E. M. L. and F. R. N. designed the study, L. H. L. , C. M. and R. J. N. collected samples, L. H. L. , D. d. R. D. F. , S. C. , W. S. M. and J. E. L. D. , N. -T. conducted laboratory work, D. d. R. D. F. , S. C. and M. A. G. conducted phylogenetic analyses, L. H. L. , M. F. , E. M. L. , M. F. , P. B. , P. I. M. , N. -T. and F. K. -K. drafted the manuscript. All authors have read and agreed to the published version of the manuscript. Funding: The study was funded by the French National Agency for Research (ANR-20-COV2-0003-01, SPILLBACK: SARS-CoV-2 endemization in wildlife of an African tropical rainforest through COVID-19 spread in the Republic of the Congo) and by the World Organization for Animal Health (WOAH) through the European Union (EBO-SURSY: FOOD/2016/379-660: Capacity building and surveillance for Ebola virus disease).
Numerical implementation Simulations are conducted with the open-source software SedFoam, a two-phase flow solver used for sediment transport applications  (Chassagne, Bonamy, & Chauchat, 2023; Chauchat et al. , 2017; Mathieu, Chauchat, Bonamy, & Nagel, 2019; Mathieu, Cheng, Chauchat, Bonamy, & Hsu, 2022; Montellà et al. , 2021; Tsai, Mathieu, Montellà, Hsu, & Chauchat, 2022)  based on the open-source finite volume library OpenFOAM (Jasak & Uroić, 2020) (v2212 release from ESI). The solver is available for download from GitHub (https://github. com/SedFoam/SedFoam). Several interpolation/discretization techniques can be used to evaluate the face fluxes. Table  2  shows schemes used for temporal and spatial discretization. It is worth noting that the Gauss upwind scheme is only adopted for the divergence discretization of 𝜙 pl and p s s fields.
Acknowledgements. The authors also would like to acknowledge the  Strategic Environmental Research and Development Program , USA  ( MR20-1478 ). We would also like to acknowledge the support from the  US National Science Foundation  ( CMMI-2050854 ). Most of the computations presented in this paper were performed using the GENCI infrastructure under Allocations  A0060107567  and  A0080107567  and the GRICAD infrastructure. Finally, we are also grateful to the developers involved in OpenFOAM. Funding statement. This work received funds the  Strategic Environmental Research and Development Program, USA , through grant number  MR20-1478.
5b -e and Supplementary Table  1 ). In the nuclear fractions the levels of Vps15 and Vps34 protein were lower during the dark phase compared with the light phase, coinciding with transcriptionally active Bmal1 (Extended Data Fig. 5d ). Next, we tested their nuclear localization using immunofluorescence microscopy. Although we could not validate commercially available antibodies to Vps34, endogenous Vps15 showed cytosolicnuclear staining (Fig. 3b ). Moreover, nuclear staining of Vps15 was unmasked by treatment with high-sucrose buffer (CSK), which removes cytosolic proteins before fixation (Fig. 3b ). Furthermore, treatment of MEFs with ivermectin, an inhibitor of importin α and β, decreased the nuclear levels Vps15 and Vps34, suggesting their active nuclear transport (Extended Data Fig. 5f ).
6e ). To test whether the Vps15-Vps34 complex is required for the Vps15-Bmal1 interaction, we used a VPS15 point mutant, which we showed does not interact with Vps34 and cannot restore the autophagy when expressed in Vps15-null MEFs (Fig. 4g, h ). Similar to VPS15WT, the VPS15Mut1 protein co-precipitated with endogenous BMAL1 (Fig. 4g ). Moreover, expression of VPS15Mut1 in Vps15-null MEFs partially restored the levels of Rev-Erbα (Fig. 4h ). Finally, to investigate the interaction region of Bmal1 mediating binding with VPS15, we employed a panel of truncated Bmal1 mutants that span its identified domains (Fig. 4i ; Protein Data Bank, 4F3L)  46, 47. Note that although the exact boundaries of the PAS-A and PAS-B domains essential for heterodimerization of the Bmal1-Clock vary somewhat in different sources (Protein Data Bank, 4F3L  47, 48  ), consistent with the published observations  47  , Clock binding was abrupted even by partial deletion of the PAS-A (Bmal1 domain (Bd) 2) or PAS-B (Bd4) domains in Bmal1 (Fig.