dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2018). Our knowledge of donkey genes encoding milk proteins, particularly CN genes, remains limited and scarce are the studies performed at the genome level. The first study performed at the nucleotide level, and to date the only one, was carried out once more on Ragusana donkey and concerned αs2-CN  (Cosenza et al. , 2010). This study revealed the existence of 2 mRNA arising from the expression of two distinct genes (CSN1S2 I and CSN1S2 II), very likely duplicated at the CSN locus. The first one comprises 19 exons, of which 17 are coding for a full-length αs2-CN A or I of 236 amino acid residues including the signal peptide (GenBank: CAV00691. 1), corresponding to the mature protein described by  Saletti et al. (2012)  and related deleted isoforms. The second consists in 16 exons and encodes a 160 amino-acid predicted pre-protein named αs2-CN B or II (GenBank: CAX65660.
The positive ion mode was used and mass scans were acquired over a range of 50 to 3,000 m/z. End plate offset voltage was set at -500 V and capillary voltage to 4,500 V. Nebulizer gas (N2) pressure was maintained at 250 kPa and drying gas (N2) flow was set at 4. 0 L/min at 200 • C. The LC-ESI-MS system was controled by Hystar software v. 2. 3 (Bruker Daltonics). The charge number of multicharged ions, the deconvoluted mass spectra, and the determination of average molecular mass (Mr) were obtained from Data Analysis v. 3. 4 software (Bruker Daltonics). A blank sample (clarification solution) was injected after every milk sample to avoid carryover effects. A reference milk sample was analyzed after every 10 milk samples to determine reproducibility. We implemented the LC-ESI-MS method developed at INRAe (UMR1313 GABI, domaine de Vilvert, 78,350 Jouy-en-Josas) to simultaneously measure the relative concentrations of the major milk proteins and their isoforms, notably their phosphorylation isoforms  (Miranda et al.
13 Da), are easily deduced. Sequencing of messenger RNAs isolated from milk fat globules confirmed such events as well as exon skipping and much complex splicing events thus allowing to resolve the molecular complexity of Amiata donkey milk proteins. A donkey mass reference database was then created for the main milk proteins using the data available in UniProtKB (ExPASy SIB Bioinformatics Resource Portal) and the National Center for Biotechnology Information (NCBI). To illustrate the efficiency and limits of such an approach, a typical protein profile obtained with a donkey milk is shown in Fig. 1 , and the identification of proteins from observed molecular masses is given in Table  1. In fraction I (peak 4) we found a molecular mass of 14,638. 39 Da (Fig. 2 ), with a signal intensity of 24,877, that we identified as the calcium-binding lysozyme C (milk isozyme or LYZ-C1).
This molecular mass is ascribable to a new variant, named C (M r = 14,638. 56 Da), revealed from cDNA sequences and characterized by two amino acid substitutions at positions 52 (Y52S) and 61 (S61N) in the peptide chain, as compared to variant A (M r = 14,687. 63 Da) initially reported  (Godovac-Zimmermann et al. , 1988). Variant C differs from the B variant  (Herrouin et al. , 2000)  by the D/N amino acid substitution in position 49 (Fig. 3 ). Variant C appears to be very predominant in the Amiata population, since the 30 donkeys analysed were homozygous C/C. Molecular masses detected in fraction II (peaks 7 and 8), were assigned to an αs2-CN encoded by the second CSN1S2 gene (alternatively named A, a, like or II, according to the species), since observed masses did not match with any mass derived from the protein recorded in the UniProtKB database (C1L3G3).
This exon was absent from the cDNA sequences previously reported by  Cosenza et al. (2010). On the other hand, we were not able to detect in the 10 clones sequenced (3 clones from each of the first 2 donkeys and 4 from the third one, randomly taken), the duplication AAA CAG TTG coding for the tripeptide KQL found by these authors, at the beginning of exon 11. In addition, all cDNA sequences showed a transversion G/T at position 86 in exon 16, responsible for the amino acid substitution S143I (numbering of the full-length protein) when compared with the mRNA recorded in the EMBL database (FN298386). Finally, these two proteins, in which peptides EIKHVSSSE and EFTSISQE (encoded by exons 3 and 12 ′ , respectively) are lacking, and displaying the additional sequence KIELTKEEKLYLKQL, encoded by exon 10 (quite perfectly duplicated as exon 15: EIELSDEEKNYLKQL), have the same peptide chain (140 aminoacid residues) with 8 and 9 phosphate groups, respectively.
Fraction VIII (peak 22, Fig. 1 , Table  1 ) associated with a molecular mass of 14,222. 24 Da, with a signal intensity of 49,371, was easily identified as α-lactalbumin given it matched perfectly with the mass (14,222. 30 Da) recorded in the UniProtKB database (P28546) for Equus asinus LALBA. A molecular mass of 19,147. 73 Da with a mass signal intensity of 3,823 was found in peak 23 (fraction IX, Fig. 1 , Table  1 ) of each of the 30 milk samples analysed. This molecule of which the identity remains to be confirmed is very likely ascribable to a further γ-CN-type degradation product corresponding to the f(56-226) of β-CN variant B whose theoretical mass is 19,147. 57 Da. Finally, the protein corresponding to peak 27 (Fraction XI, Fig. 1 , Table  1 ) with a molecular mass of 18,514. 44 Da was easily identified as being the B variant of β-LG I.
However, 6 donkey milk samples displayed chromatographic profiles in which peak 27 was preceded by an additional peak (peak 26, see Fig. 1  framed profile top right). A single mass (20,429. 24 Da) that did not match with any of the theoretical masses listed in the database built in the laboratory, was found in this peak, with an intensity ca. the half of the mass signal observed in peak 27 (Fig. 8 ). Thus, from this data we were unable to associate this mass to a known protein. Interestingly, in a seventh and single donkey milk sample, peak 26 was the only one, whereas peak 27 is apparently absent, suggesting that the molecule under peak 26 might correspond to a rare variant of β-LG I. The remaining 23 donkeys only have peak 27 (fraction XI). In order to identify this protein of 20,428. 5 Da, present in peak 26, that did not correspond to any donkey milk protein identified so far, we implemented several additional and complementary approaches.
This new C-terminal sequence is given below the reference nucleotide sequence (black letters). A silent transition (G/A) is highlighted in yellow. Caution! The sequences of the CSN1S2 or B (or I) and CSN1S2-like or A (or II) genes are reversed in the NCBI database. The LOC106835119, identified as the CSN1S2-like or A gene is located close to the PRR27 locus, whereas in the other species the CSN1S2-like or A gene is usually closest to the CSN2 locus and CSN1S2 or B (LOC106828076 in the donkey genome) should be located close to the ODAM locus. Furthermore, from genome data these two genes appear to be convergently transcribed in the donkey, whereas they are transcribed in the same direction in the other species. The translation in amino acids is given above the nucleotide sequence and the numbering begins with the first amino acid of the mature protein.
Acknowledgements The authors would like to warmly thank the  Regional Forestry Agricultural Complex Bandite di Scarlino  ( Grosseto, Italy ) for help in milk sampling and the  Doctoral School of Veterinary Sciences  from the  University of Pisa , for the scholarship granted to BA which allowed her to do an internship at the  INRA Research Center of Jouy-en-Josas  in the framework of her PhD. This work was partly supported by a grant  PRA 2017  ( Ateneo Research Project, University of Pisa) Improvement of productive performance of dairy donkey (Miglioramento delle performance produttive della specie asinina allevata per la produzione di latte )  nI52F17000260005. The authors thank PAPPSO and  @BRIDGe teams at INRAe (Jouy-en-Josas, France)  for providing necessary facilities and technical support.
Introduction Propolis is well known for its extraordinary bioactivity but also for its chemical complexity, making it an outstanding source of continuous research. Every day we are able to find new publications on this bee product describing a new singularity, a novel substance with high bioactivity never yet described, or a new application. To date, more than 7700 documents can be found on the Scopus database with a clear increase year rate (above 670 publications/year), focusing on different fields of science such as agriculture, biology, chemistry, and biochemistry, where production and quality issues are discussed, but also in pharmacology, medicine, immunology, dentistry, veterinary, engineering or environmental sciences, exploring the potential applications. Just in 2021, more than 100 review papers have been published, dealing with propolis plants sources and production  (Dezmirean et al.
Statistical analysis All participant laboratories received a standard form codified for the lab and the samples, into which the results were entered in triplicate. A previous preevaluation of the data was performed by the study coordinator to detect any discrepancy and the need to repeat experiments. Once conclude the experimental design, the individual data were evaluated following the international guidelines ISO 5725(ISO, 1994), which are supported by the analysis of variance. If the individual data significantly differ from the normal distribution above 95% of confidence, the result is considered as a straggle. If the confidence level of 99% was reached, the value is defined as an outlier. Extreme values, or outliers, were removed based on Mendel's k statistics and Cochran's test, to guarantee the homogeneity of variances at certain levels, and using Mendel's h statistics and Grubb's test, to guarantee the consistency of the laboratories average  (Dispas et al.
Acknowledgements The authors are grateful to the  Foundation for Science and Technology (FCT, Portugal)  for financial support by national funds  FCT/MCTES  to  CIMO  ( UIDB/00690/2020 ). Thanks to the Programa Ap ıcola Nacional  2020-2022  ( National Beekeeping Program ) for funding the project " Standardization of production procedures and quality parameters of bee products " and to Project  PDR2020-1. 0. 1-FEADER-031734 : " DivInA-Diversification and Innovation on Beekeeping Production ". National funding by  FCT -Foundation for Science and Technology , through the  institutional scientific employment program -contract with  Soraia I. Falcão. A special thanks is given to  Hartmut Scheiter  and  Allwex Food Trading GmbH, Bremen, Germany , for providing, handling and delivering the propolis blind samples.
Secondary Data and Limitations The secondary data we used in this study are from the national censuses (every 10 years for the population and every 5 years for agriculture), as well as major national surveys carried out occasionally on smaller samples: the NSS (National Sample Survey) and the IHDS (India Human Development Survey). But even in India where we find one of the best data collection systems on labor issues among developing countries, they have limitations especially when it comes to agricultural wage labor. In large household surveys,  Oya and Pontara (2015)  highlighted for example: (i) the problematic notion of 'main job-holding' and reference periods in contexts of multiple, irregular and highly seasonal occupations; (ii) the unclear distinction between wage employment and self-employment; (iii) under-reporting of stigmatized jobs (such as physical work for higher castes or women in many regions of India); (iv) inadequate translations into vernacular language of statistical categories and concepts.
), and livestock farming practices (choice of breeds, breeding, feeding and animal health management, use of outputs, associated working calendar and workload, yields, etc. ). It also includes flows of matter and energy between crops and livestock, as well as the work organization at the farm level. The social relationships considered involve land (e. g. , land rental or sharecropping), work (e. g. , employment of daily laborers to carry out certain tasks), capital (e. g. , loan to dig a borewell), agricultural inputs and products (e. g. milk delivery to a cooperative). Data on prices, agricultural laborers' wages and equipment lifetime were collected through the same interviews to calculate the economic indicators. Archetypes of each production systems can then be modeled. Similar to Weberian ideal-types, they do not correspond to real farms nor to the averages of the three to eight farms surveyed by farm type.
ACKNOWLEDGMENTS We would like to thank all the farmers who agreed to be interviewed in the 13 study areas, as well as the translators from local languages to English who helped us for these interviews. We also thank  CSH, IRMA, NDDB, BAIF, ILRI  and the dairy cooperatives for their help in identifying study areas and facilitating the fieldwork. This paper was presented in March 2021 at the second ISWA Symposium the future of work in agriculture : we thank the workshop' convenors for their comments and the participants for the discussion, as well as  Renuka George  for the translation of the article. Finally, we thank the four reviewers for their stimulating comments and their help in greatly improving the writing of this article.
As an alternative hypothesis, we predict that ecological similarity and, thus, competitive exclusion due to fitness differences generates transient patterns in the abundance of these species. Under a neutral scenario, with species lacking major niche and fitness differences, a random distribution of cryptic bladed Bangiales along intertidal elevations and seasons of the year is expected. To test these hypotheses, bladed Bangiales were collected from five rocky intertidal sites (platforms and/or boulders located between the 39 • S and 43 • S) across four intertidal elevations and four seasons for one year. Cryptic species determination was based on partial sequences of the mitochondrial cytochrome c oxidase 1 (COI) gene and we assembled a large dataset of morphological attributes and molecular data for these key primary producers of the Chilean intertidal zone.
Morphological Traits Using the photographs taken of the blades spread flat, the maximum lengths and maximum widths of the thalli were measured using the software ImageJ (version Java 1. 8. 0) (http://imagej. nih. gov/ij/, accessed on 24 May 2021). Some other characteristics such as color (brown, green, yellow, and red), and form (rosette, elongated rosette, and lanceolate blade) were also noted.
Species Determination Based on Molecular Data Algal material was subjected to cell disruption for 30 s in a Mini-BeadBeater (BioSpec Inc. , Bartlesville, Oklahoma, United States) and DNA was extracted using the Plant DNA kit (Omega BIO-TEK, Norcross, Georgia, United States) following the provider's protocol. Quantity and quality of the extracted DNA was determined using a NanoDrop Lite spectrophotometer (Thermo Scientific, Waltham, Massachusetts, United States). A fragment of the mitochondrial cytochrome c oxidase 1 (COI) gene was amplified using the primer pair GazF1 (5'-TCA ACA AAT CAT AAA GAT ATT GG -3') and GazR1 (5'-ACT TCT GGA TGT CCA AAA AAY CA -3') following the PCR protocol described by Saunders  [88] , with a melting temperature of 56 °C. The PCR products were checked using 1. 5% agarose electrophoresis gels.
Sanger sequencing was performed using the GazF1 primer in the AUS-TRAL-omics Core-Facility (Universidad Austral de Chile). The sequences were checked by hand using Chromas v. 2. 6. 6 (http://technelysium. com. au/wp/chromas/, accessed on 10 May 2021), and species identification was performed using the GenBank Basic Local Alignment Search Tool (BLAST) to compare the newly obtained COI sequences with the ones already deposited in the public databases in NCBI GenBank (https://www. ncbi. nlm. nih. gov/, accessed on 20 December 2021). Species determination was based on the percent identity BLAST metric and a minimum identity threshold of 3% was used (i. e. , reflecting the congeneric interspecific divergences observed for Chilean bladed Bangiales for the COI)  [6]. The nucleotide sequences obtained in this study were deposited in the GenBank database; all accession numbers are available in the Supplementary Table  S2.
Species Determination Based on Molecular Data Algal material was subjected to cell disruption for 30 s in a Mini-BeadBeater (BioSpec Inc. , Bartlesville, OK, USA) and DNA was extracted using the Plant DNA kit (Omega BIO-TEK, Norcross, GA, USA) following the provider's protocol. Quantity and quality of the extracted DNA was determined using a NanoDrop Lite spectrophotometer (Thermo Scientific, Waltham, MA, USA). A fragment of the mitochondrial cytochrome c oxidase 1 (COI) gene was amplified using the primer pair GazF1 (5 -TCA ACA AAT CAT AAA GAT ATT GG -3 ) and GazR1 (5 -ACT TCT GGA TGT CCA AAA AAY CA -3 ) following the PCR protocol described by Saunders  [88] , with a melting temperature of 56 • C. The PCR products were checked using 1. 5% agarose electrophoresis gels. Sanger sequencing was performed using the GazF1 primer in the AUSTRAL-omics Core-Facility (Universidad Austral de Chile).
The sequences were checked by hand using Chromas v. 2. 6. 6 (http://technelysium. com. au/wp/chromas/, accessed on 10 May 2021), and species identification was performed using the GenBank Basic Local Alignment Search Tool (BLAST) to compare the newly obtained COI sequences with the ones already deposited in the public databases in NCBI GenBank (https://www. ncbi. nlm. nih. gov/, accessed on 20 December 2021). Species determination was based on the percent identity BLAST metric and a minimum identity threshold of 3% was used (i. e. , reflecting the congeneric interspecific divergences observed for Chilean bladed Bangiales for the COI)  [6]. The nucleotide sequences obtained in this study were deposited in the GenBank database; all accession numbers are available in the Supplementary Table  S2.
Moreover, the spatial patterns of the community structure were described in a constrained principal coordinates analysis (PCoA) ordination  [90]. This method allowed us to show the multivariate axes that accounted for most of the variation in the species abundance dataset according to our predictive model (i. e. , separate and joint elevation by season effects on species composition). Individual counts of numerically dominant species were separately analyzed with zero-inflated hierarchical generalized linear models. The error structure was modeled as a negative binomial distribution and model parameters were estimated by means of maximum likelihood. The models included elevation and season as fixed and crossed factors and site as a hierarchical factor. Model goodness-of-fit was assessed by means of conditional and marginal pseudo-coefficients of determination (R 2 c and R 2 m , respectively;  [83, 84] ).
Acknowledgments: We thank  Enrique Higuera ,  Alvaro Aguilar , and  Oscar Alvarado  for their support in sampling the Melinka site;  Suany Quesada ,  María Paz Melo Gaymer ,  Francisca Heise , and  Lorena Gallardo  for their help in the field; and  Sarai Morales ,  Suany Quezada , and  María Paz Melo Gaymer  for helping with DNA extraction and sequencing. F. P. C. A. would like to give special thanks to  Michel Abanto Marin , postdoc advisor, and  María de La Luz Mora  for guidance and support. Three anonymous reviewers provided useful criticism that improved a previous version of this paper.
Funding: This work was funded by the  FONDECYT  Postdoctoral Grant no. 3200728  ( ANID, ex CONICYT, Chile ) awarded to F. P. C. A. N. V. and M. -L. G. were supported by the  FONDAP  grant no. 15150003  ( FONDAP IDEAL ). While writing, N. V. was supported by  FONDECYT  grant no. 1190529. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
Fungal Strains and Culture Media This study used the following 3 fungal strains (with their accession number in brackets), i. e. , Coriolopsis gallica strain CLBE55 (ON340792) and two ascomycetes, Thielavia sp. HJ22 (KX618207), and Thielavia sp. CH1 (KX618201), to test their abilities to degrade levofloxacin (https://www. ncbi. nlm. nih. gov/, accessed on 13 August 2022). Solid cultures of the three strains were performed on potato dextrose agar (PDA) media, i. e. , 39 g of dehydrated media (Accumix ® , Geel, Belgium) suspended in 1000 mL of distilled water and sterilized by autoclaving at 120 • C for 30 min. Liquid preculture was performed in 25 mL of malt extract medium (Sigma-Aldrich, St. Louis, MO, USA) containing (per L) 30 g malt extract at pH 5. 5 and sterilized by autoclaving at 120 • C for 30 min.
Branches corresponding to partitions reproduced in less than 50% of the bootstrap replicates were collapsed. Percentage of replicate trees clustering together associated taxa in the bootstrap test (500 replicates) is shown next to the branches  [65]. The evolutionary distances were computed using the maximum composite likelihood method  [66]  and expressed as number of base substitutions per site. This analysis covered 20 nucleotide sequences. All ambiguous positions in each sequence pair were removed (pairwise deletion option). The final dataset contained a total of 609 positions. The evolutionary analyses were performed in MEGA11  [67]. The fungal strains were deposited at the 'Centre International de Ressources Microbiennes-Champignons Filamenteux' (CIRM-CF) under reference number BRFM 3473.
2 µL min -1 flow rate. The peptides were analyzed by MS/MS with a Q-Exactive HF instrument (Thermo Scientific) operated as described in Grenga et al. [71]  in data-dependent acquisition mode with a full scan of peptide ions acquired at a resolution of 60,000. High-energy collisional dissociation and MS/MS scans were performed after each MS scan at a resolution of 15,000 on the 20 most abundant precursor ions with 2+ or 3+ ion charge and with a dynamic exclusion of 10 sec. MS/MS spectra were assigned to peptide sequences by the MASCOT Daemon 2. 3. 2 search engine (Matrix Science) using either a Coriolopsis gallica CLBE55specific database constructed after draft genome sequencing and totaling 168,204 contig sequences  [72]  or a Coriolopsis gallica annotated protein sequences database (23 9APH sequences; https://www.
uniprot. org/uniprot/?query=coriolopsis+trogii&sort=score, accessed on 13 August 2022). Standard search parameters were used: trypsin as proteolytic enzyme with two possible miscleavages at maximum, tolerances of 5 ppm and 0. 02 Da for the MS and MS/MS signals, respectively, oxidation of methionine and deamidation of glutamine and asparagine as possible modifications, carbamido-methylation of cysteine as fixed modification, and a peptide p-value < 0. 01. A protein was considered validated when at least two different peptides were detected, resulting in a protein identification false discovery rate below 1%, as verified with a reverse decoy database search. Protein quantitation and comparison between conditions was done with the number of MS/MS spectra assigned per protein, as recommended by Gouveia et al.
[73]. The mass spectrometry and proteomics data have been deposited with the ProteomeXchange Consortium via the PRIDE  [74]  partner repository under dataset identifiers PXD035019 and 10. 6019/PXD035019. (The dataset is available for the reviewers during the peer review process with the Username: reviewer_pxd035019@ebi. ac. uk and Password: AYROnpGZ, and will be publicly released once the manuscript is published).
A 609 bp ITS rDNA fragment obtained from strain CLBE55 was aligned with sequences from GenBank to construct the tree. The consensus tree built contained 20 sequences and formed two main clades (Figure  1 ). In the first clade, seven strains were from Coriolopsis gallica, which strain CLBE55 fitted. In the second clade, Coriolopsis gallica strains were grouped with Trametes trogii, Funalia trogii, and Coriolopsis trogii strains, and the bootstrap value for this branch was 100%. Consensus results also revealed that C. gallica strain CLBE55 shared 99% similarity with C. gallica strain CBS 428. 34.