dataesr/scientific-paragraphs-categorization huggingface dataset:
Dietary exposure Exposure to lactic acid from the intended use was based on consumption of pork and pork products reported in the Comprehensive European Food Consumption Database (see Appendix B), and in the absence of specific information from the applicant on analytically determined residual levels of lactic acid in pork meat, concentration data reported in the literature  (Rose et al. , 2004)  was used. Based on Rose et al. (  2004 ), 12. 5 g of beef meat pieces treated with 2. 5% lactic acid wash (i. e. 30 g lactic acid/L) had an uptake of 0. 6 mg of lactic acid from the wash treatment, equivalent to 48 mg/kg meat. The corresponding concentration in meat resulting from use of 5% (vol/vol) lactic acid was extrapolated, based on reported increased uptake between dose intervals (i. e. 0. 38 mg/dL from 0.
Exposure assessment methodology For each individual, the lactic acid concentration data was combined with the average daily consumption of pork and pork products. Food groups containing pork were, where necessary, adjusted for pork content (see Appendix B -Table  B. 1). The resulting exposure was then summed in order to obtain total chronic exposure at individual level from all food sources. The mean and the higher percentile (i. e. 95th percentile) of the individual exposures were calculated for each dietary survey and each age class separately.
+/À NA In the applied exposure model, the Panel assumed that all pork carcasses and cuts were treated only once, whereas the applicant indicated that in some cases a repeat treatment may take place (e. g. treatment of a carcass followed by treatment of an individual cut), which may lead to an underestimation of exposure. The Panel further assumed that all pork and pork products consumed always contained residual lactic acid as a result of treatment with the decontamination agent, which would lead to a considerable overestimation of exposure. The concentration data applied was extrapolated from data reported in the literature for beef, and the influence of this uncertainty on the exposure assessment cannot be estimated. Given these observations, the Panel considered overall that the uncertainties identified would, in general, result in an overestimation of the exposure to lactic acid from its use as a decontamination agent in European countries considered in the EFSA European database.
Dietary exposure Exposure to acetic acid from the intended use was based on consumption of pork and pork products reported in the Comprehensive European Food Consumption Database (see Appendix B), and, in the absence of specific information from the applicant on analytically determined residual levels of acetic acid in pork meat, concentration data reported in the literature  (Anderson et al. , 1980)  was used. Based on  Anderson et al. (1980) , 100 kg of beef meat took up 300 g of washing water containing 3% (v/v) acetic acid (31. 5 g acetic acid/L, given the density of acetic acid, i. e. 1. 049 g/mL), corresponding to 94. 5 mg/kg meat. This level of residue does not take into account any volatile losses of acetic acid during storage or cooking and hence presents a conservative estimate. Assuming the same mode of uptake as reported for the 3% wash, treatment with 4% acetic acid would result in a final concentration of 125.
Exposure assessment methodology For each individual, the acetic acid concentration data was combined with the average daily consumption of pork and pork products. Food groups containing pork were, where necessary, adjusted for pork content (see Appendix B -Table  B. 1). The resulting exposure was then summed in order to obtain total chronic exposure at individual level from all food sources. The mean and the higher percentile (i. e. 95th percentile) of the individual exposures were calculated for each dietary survey and each age class separately. The Panel assumed that pork carcasses and cuts were only treated once, which may lead to an underestimation of exposure, since repeat treatment may be applied (same methodology as described in Section 3. 1. 5. 1).
Exposure to acetic acid Table  10  shows that exposure to 4% acetic acid used as decontamination treatment from consumption of pork and pork based dishes ranged on average from 0. 1 to 17. 6 mg/person per day and from 0. 1 to 44. 0 mg/person per day, at the 95th percentile across, all population groups. In order to put the exposure to acetic acid from use as a decontamination agent on pork into context with acetic acid intake obtained via the typical diet, the Panel decided to assess the intake of acetic acid from consumption of vinegar as reported in the Comprehensive Database (see Table  11 ). An acetic acid content of 6% (w/v) in vinegar was assumed. The intake of acetic acid from consumption of vinegar (6% w/v) ranged from 0 to 123. 3 mg/person per day at the mean and from 0 to 480 mg/person per day at the 95th percentile, and was found to far exceed the exposure to acetic acid as a result from its use as a decontamination agent on pork meat.
Study selection and identification of relevant experiments The studies on efficacy included records provided by the applicant which were complemented with studies on efficacy retrieved by searching two bibliographic databases for recent records (since 2015) and by prescreening the reference lists of three review papers for relevance  (Belluco et al. , 2015; Totton et al. , 2016; Young et al. , 2016). A total of 227 records were screened at title/abstract level and further screened for eligibility based on the full text (part I), with 43 records being eligible. In total, 99 experiments were defined. Of these, 12 records and 19 experiments fulfilled the criteria for inclusion (see Figure  2  for PRISMA flow chart). Of these, 71 comparisons (reduction estimates) were derived. Considering the substance, lactic acid was included in 11 records, 16 experiments and 67 comparisons; acetic acid was included in 2 records, 3 experiments and 4 comparisons.
Knowledge about the origin and evolutionary history of the bison has been improved recently owing to several genomic and paleogenomic studies published in the last two years, which elucidated large parts of the evolution of bison populations during the Upper Pleistocene and Holocene in Eurasia. The produced data, however, were interpreted in contradicting manners. Here, we have gathered, reanalyzed and compared previously published or unpublished morphometric and genetic data that have not yet been integrated and that we synthesize in a unified framework. In particular, we re-estimate dates of divergence of mitogenome lineages based on an extended dataset comprising 81 complete ancient bison mitogenomes and we revisit putative gene flow between the Bos and Bison genera based on comparative analyses of ancient and modern bison genomes, thereby questioning published conclusions.
We gathered various bone measurements, maximal length (Lmax), transverse and anteroposterior diameters (TD and APD respectively), at the proximal (prox) and distal (dist) ends and at the midshaft (dia) that altogether summarize overall bone morphology. Other variables were not taken into account since they were not provided by all authors and would have restricted the number of bison populations available for analysis. The values of TD and APD discriminate well the sexes. This can be seen in a scatter diagram of the proximal TD and APD (data not shown), as well as with the measurements 3, 4, 5, and 7 presented in the Results sections. Thus, we considered only bones that could be clearly attributed to females to avoid the confounding factors of sexual dimorphism. We collected measurements representing bison populations originating from various Pleistocene and Holocene sites from Eurasia and America, several of which were analyzed paleogenetically  [10] [11] [12].
We also used osteometric data from various Eastern Eurasian populations identified as Bison priscus, as well as their sub-species from Siberia (B. p. priscus: sites of Krasny Yar (Riss-Würm: R-W), Taradanovo (W1-2), Krasny Yar (W2), Kurtak and Chumysh (W3)), Yakutia (B. p. crassicornis (W2) and B. p. occidentalis (W3) [these two sub-species are considered to be synonymous]), and Ukraine (B. p. mediator (W3)  [24]. Moreover, we have included in our analyses the extant Bison bonasus according to the individual measurements based on sex  [21, 25]. Finally, several North American populations from the Late Pleistocene-Early Holocene sites of Scottsbluff (Nebraska), Lipscomb (Texas) and Folsom (New Mexico) have also been analyzed, which had been attributed to Bison antiquus and some modern forms of B.
P. Brugal unpublished). The choice of a different reference from LSI analysis is justified due to better discrimination for factorial analysis. We calculated the VSI* for available parameters for all studied series (Lmax, proxTD, diaTD, proxAPD) to which we added an index of slenderness 100*distTD/Lmax instead of distTD and these values for the various populations were used for a PCA analysis performed with the software package Multi-SIST (  [29] ; package elaborated by G. Escarguel  [30]  and available upon request at UMR CNRS 5023, Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés, Univ. Lyon 1, France). To evaluate the statistical significance of the relationships between populations identified with the PCA, we performed a bootstrapped spanning network analysis  [31]  using the Multi-SIST software.
Phylogenetic Analyses of Published Bison Mitogenomes Ancient bison mitochondrial sequences were gathered from five recent publications  [1, [9] [10] [11] [12] , and the modern sequences were from Massilani et al. [10]. Sequence alignments and phylogenetic analyses conducted under the Bayesian framework with the BEAST software were performed as described in Massilani et al. [10]  with the following modifications: we used the bison mitogenome substitution rates estimated by Massilani et al. to set the priors (lognormal priors: HVR, mean = -15. 0 stdev = 2. 0, corresponding to a median of 3. 0 × 10 -7 and a 95% highest density interval of [6 × 10 -9 -1. 5 × 10 -5 ]; RNA, mean = -17. 55 stdev = 2. 0, corresponding to a median of 2. 4 × 10 -8 [4. 7 × 10 -10 -1. 2 × 10 -6 ]; 1st and 2nd positions, mean = -17.
They included nine Bison bonasus individuals: (i) 3569 and 3574 from Gautier et al. [7]  and Z3 and 868 from Wecek et al. [9]  that all belong to the so-called modern Lowland line; (ii) Dy from Wecek et al. [9]  that belong to the Modern Lowland-Caucasian line; (iii) PLANTA  one of the founder of the modern Lowland line and her male offspring  PLATEN (1926 PLATEN ( -1933) )   [9] ; and (iv) Cc1-8853 (1911) and Cc2-22533 (1949) two early 20th century Caucasian wisent  [9]. We also included WGS from 20 bovine individuals belonging to the European Angus (n = 10)  [32]  and the West-African N'Dama (n = 10)  [33]  breeds. The resulting 29 WGS were mapped onto the UMD3. 1 bovine genome assembly  [34] , using default options of the mem program from the bwa (version 0. 7. 12) software package  [35].
Read alignments with a mapping quality score < 20 and PCR duplicates were further removed using the view (option -q 20) and marked-up (with option -r) programs from the samtools (version 1. 6) software package  [36]. Variant and genotype calling was then performed on all the samples using the program call from the bcftools (version 1. 2) software package implementing the multi-allelic caller option (-m). To be consistent with the above mild filtering criteria, only the genotypes supported by less than two reads were considered as missing. In total, 8611 out of the above 9038 SNPs retained from the data set by Soubrier et al. [11]  could be unambiguously genotyped and the corresponding data sets were further combined. Note that only autosomal SNPs were considered. Last, the third type of genotyping data was obtained from the public WIDDE repository  [37]  and consisted of genotypes obtained with the BovineSNP50 and BovineHD (that include most of the SNPs from the Bovine SNP50 assay) Illumina Beadchip for (i) 10 individuals different from above belonging to the European Angus bovine breed; (ii) 10 individuals different from above belonging to the West-African N'Dama bovine breed; (iii) 10 individuals belonging to the Indian zebu breed; (iv) 4 modern American bison (Bison bison) individuals  [38] ; (v) two modern Yak individuals (Peophagus grunniens); and (vi) the two B.
bonasus individuals 3569 and 3574 from Gautier et al. [7] , mentioned above, that were also newly genotyped on the BovineHD BeadChip. These Illumina BeadChip genotyping data were recoded using home-made awk scripts and combined with the two above data sets, keeping only SNPs that were common to the three experiments. The final data set thus consisted of 7572 SNPs genotyped for 68 individuals among which three were genotyped on two different experiments: (i) the B. bonasus individuals 3569 and 3574 genotyped with both the BovineHD Illumina BeadChip and using WGS data; and (ii) the 1911 Caucasian sample analyzed in Soubrier et al. [11]  under the ID A15654 is identical to Cc1-8853 sequenced to 1X coverage by Wecek et al. [9]  and correspond to a skull from Kuban Oblast stored in the Zoological Institute of the Russian Academy of Science from Saint Petersburg (numbered 8853).
Estimation of the Divergence between European and American Bison under the CoalHMM Framework Following Gautier et al. [7] , the estimation of divergence between the B. bonasus and B. bison lineages was performed under the coalescent hidden Markov models (CoalHMM) framework  [40]  considering an isolation (I) model that assumes that the ancestral population split into two populations at time τ into the past  [41]. To that end, the alignments of the B. bison genome assembly (GCA_000754665. 1) onto the recently published B. bonasus assembly by Wang et al. [8]  were extracted from the synteny alignments (bovine. SixSpecies. maf file) accompanying the latter publication using the program MafFilter  [42]. The bovine sequence was used as a reference to merge the identified synteny blocks between the two lineages with a maximum distance of 50 kb between them and a minimal size of 10 Mb.
In total, 37 non-overlapping autosomal segments (based on anchoring onto the bovine assembly) of 12. 6 Mb on average (ranging from 10. 1 to 17. 5 Mb) were identified. Maximum-likelihood inference of the divergence time was then carried out independently for each segment using the script isolation-model. py (version 1. 1) from the IMCoalHMM software package (https://github. com/mailund/IMCoalHMM). More precisely, the parameters underlying the I-model include (i) the split time τ in units of µ y T where µ y represents the mutation rate per year and T the time in years before present; (ii) the ancestral effective population size in scaled units of θ = 4N e µ y g where g is the generation time; and (iii) the recombination rate ρ in scaled units µ y g that both parameterize the underlying coalescent process.
1. 2-0. 5 Mya), survived up to the Late Pleistocene  [47, 48]. These two considerations prompted us to revisit the osteometric measurements of bison bones from the Early Pleistocene to modern times in order to evaluate whether it was possible to identify morphological changes that remained unidentified or poorly established up to now. We gathered morphometric data from multiple previous studies and our own database for one of the best preserved and most frequent bison bones from fossil assemblages that show sufficient morphological diversity and correlation to overall skeletal morphology to be diagnostic for skeletal evolution: the metacarpal bone (Figure  3C ). When the length of this element is measured in the Pleistocene series and plotted chronologically separating the males from the females, it appears that there is, despite notable fluctuations, a general tendency of decreasing size over time during the Middle Pleistocene (Figure  3A ).
bonasus individuals 3569 and 3574  [7]  genotyped with both the BovineHD Illumina BeadChip and using WGS data; and (ii) a 1911 Caucasian sample analyzed in Soubrier et al. [11]  under the ID A15654 that is identical to Cc1-8853 sequenced to 1X coverage by Wecek et al. [9]. In PCA plots, individuals whose data originate from WGS data are represented with square, whereas circles were used for SNP-chip genotyping data. (A) PCA on the whole data set retaining only the 5196 SNPs that were called in at least 95% of the samples. Note that the positioning of the individuals genotyped with the Illumina assay and using WGS data are consistent since all Angus (ANG) individuals cluster together, as well as the two Bison bonasus individuals 3569 and 3574. In contrast, in accordance with their known variable proportion of indicine ancestry  [33] , N'Dama (NDA) individuals genotyped with the BovineHD assay separate from those genotyped using WGS  [33]  that are closer to the B.
Sex-Specific Differences The extended periods with limited gene flow could account for most of the discrepancies discussed herein between the mitogenomes, nuclear genomes and morphological features. To account for the observation that the mitogenomes appear to characterize distinct populations, whereas the nuclear genomes and bone morphometrics suggest that regular gene flow between populations were occurring simultaneously, there could have been sex-specific differences in the direction of the gene flow, where females are preserving the distinct identities of each population, whereas males are ensuring gene flow between these distinct populations. There are multiple lines of evidence that support such a scenario. First, we observed that the morphological differences between the sexes are more or less pronounced depending on the chronological period.
[9]. In PCA plots, individuals whose data originate from WGS data are represented with square, whereas circles were used for SNP-chip genotyping data. (A) PCA on the whole data set retaining only the 5196 SNPs that were called in at least 95% of the samples. Note that the positioning of the individuals genotyped with the Illumina assay and using WGS data are consistent since all Angus (ANG) individuals cluster together, as well as the two Bison bonasus individuals 3569 and 3574. In contrast, in accordance with their known variable proportion of indicine ancestry [33] , N'Dama (NDA) individuals genotyped with the BovineHD assay separate from those genotyped using WGS [33]  that are closer to the B. p. indicus individuals. (B) PCA on the data set without the bovine individuals and retaining only the 1703 SNPs that were called in at least 95% of the samples.
Funding: This research was funded by the  French National Scientific Research Center CNRS. The genotyping of the two modern European bison (3569 and 3574) was funded by the  National Institute of Agronomic Research (INRA, Animal Genetics Division). The genomics and bioinformatics facility of the  Institut Jacques Monod  were supported by grants to T. G. from the  University Paris Diderot , the  "Fondation pour la Recherche Médicale " ( DGE20111123014 ), and the  "Région Ile-de-France " (grant  11015901 ), as well as to E. -M. G. from the  University Paris Diderot ,  ARS 2016-2018.
Cc3_KX553934_5690Figure 1. 1 Figure 1. Bayesian phylogeny of complete mitogenomes of Bos and Bison. We used the 86 complete mitogenomes of ancient Bison available in Genbank at the end of 2017, and all 420 modern Bison bison, Bison bonasus, Poephagus grunniens, and Bos primigenius taurus mitogenomes available in Genbank in 2015. The B. bison, P. grunniens and B. p. taurus sequences have been collapsed to preserve only their subclade structure. The estimates of the age of the nodes, in kya, are indicated in red, with the 95% HPD indicated by blue bars. The statistical supports of the nodes are indicated in red (Bayesian posterior probability). Sequence names were colored according to period and geographical origins of the samples following the color code depicted in the table insert in panel A.
Recordings Up to four tungsten electrodes etched to a tip diameter of ϳ5 m were used for the extracellular recordings. The signals were amplified 1000-fold and filtered to pass frequencies of 0. 1 Hz to 10 kHz (AM Systems, 1700). The extracellular signals were digitized at 10 kHz with a 12-bit, 16-channel A-D converter (Digidata 1200A, Molecular Devices) and monitored and saved to a PC with Axoscope (Molecular Devices).
Sequencing Before sequencing, the PCR products were purified by the MSB R Spin PCRapace Kit (Invitek GmbH, Berlin, Germany). The nucleotide sequences of the PCR products from the p25 gene were obtained using an ABI377 Sequencer-Genetic Analyser and the "Big Dye Terminator Cycle Sequencing Kit" (Applied Biosystems). The sequences were analyzed by a Blastn search in NCBI. The Clustal W program of the Genetic Computer Group  (Devereux et al. , 1984)  at EMBL-EBI was used to obtain multiple sequences alignment. The Expasy Proteomics Server tools (http:// www. expasy. org/) were used to translate nucleotide in amino acids and the Invitrogen Vector NTI Advance 10 program (Life Technology) was used to manage the data. Each RNA3 type was characterized by SNPs (single nucleotide polymorphisms) analysis as biological markers and compared with French sequence references of each BNYVV type (A-type, AF197545; B-type, M36894; P-type, DQ682454; J-type, NC_003516).
ACCESSION NUMBER The partial BNYVV RNA3 sequences in this study have been deposited in GenBank. GenBank accession numbers for partial RNA sequences are MG839229 to MG839249 for the BNYVV RNA3-coded p25 of isolates AYHR, TYHR, ASHR, AYHT, AYHS, SYHG, SYHR, SYHN, SFHG, SCHG, AYPR, AFPR, TFPR, AYHG, AFHG, AFHR, AFLG, VCHG, VYHG, VYHR, VLHX, respectively.
ACKNOWLEDGMENTS The authors would like to thank the  ITB France (Institut Technique français de la Betterave sucrière) , especially  Marc Richard-Mollard ,  Hervé Escriou  and  Agnès Champeil , and the  UFS (Union Française des Semenciers)  for their grateful support. We also highly thank  Stevens , M. from the  British Beet Research Organisation (UK)  for reviewing the manuscript. We also thank Weyns, J. , Nyssens, G. , Fabry, G. , Hermès, J. , Vanpee, B. ,  Van Hese , V. , Lootgieter, L. , Nagy, C. , Sandri, L. , and Gérard,  J. -M. for their excellent technical support.
Results The pufM dataset used in this study was assembled from sequences previously generated from 27 samples collected during 4 cruises (PROSOPE, BOUM, ARCTIC and MALINA) which took place between 1999 and 2009 in different oceanic regions (Mediterranean, North Pacific to Western Beaufort Sea, Barents and Norwegian seas; Fig. 1a ). The cruise transects encompass three major oceanic biomes (polar, westerly winds and coastal boundary zone) and six oceanic provinces [Atlantic Subarctic, Atlantic Arctic, Boreal Polar, Canary coastal, Pacific Subarctic gyres and Mediterranean Sea-Black Sea, Table  S1 ] encompassing large ranges of salinities (Fig. 1b ) and temperatures (Fig. 1c ), distinct nutrient status (Fig. 1d-h ) and oceanic regimes (Table  S1 ) and various depths (Table  S1 ). All of the ~300 pufM sequences were generated by classical cloning-sequencing approaches after amplification by a same primer pair, to give 245 bp PCR products, avoiding biases in the comparison of the relative abundance of OTUs.
The sequences were grouped into OTUs, at 94% nucleic acid sequence similarity, using the furthest neighbor clustering method. The number of OTUs in each set of pufM sequences was variable (20 to 48 OTUs), presumably due to a different number of sequences in the primary datasets (Table  S2 ). Despite those differences, coverage values indicated that most diversity in most sequence sets has been retrieved (Table  S2 ). A total of 107 OTUs were identified for the overall dataset with a coverage value of 96% (Table  S2 , Supplemental material SI1). Only 6 OTUs exhibited a degree of paraphyly (paraphyly index (PI) comprised between 0. 01 and 0. 08), the other 101 OTUs were monophyletic (PI = 0, data not shown). Comparisons of pufM datasets. We used community ecology methods to analyze the structure of AAP bacterial communities using two metrics that each emphasized different community characteristics.