dataesr/scientific-paragraphs-categorization huggingface dataset:
MS data processing, analysis and statistics Raw data were analyzed using MaxQuant software version 1. 5. 5. 1 (input and IP) or version 1. 6. 10. 43 (whole cell proteome)  (Tyanova et al. , 2016)  using the Andromeda search engine  (Cox et al. , 2011). The MS/MS spectra were searched against the UniProt M. smegmatis (strain ATCC 700084/mc 2 155) database containing 6601 proteins, usual known mass spectrometry contaminants and reversed sequences of all entries. Andromeda searches were performed choosing trypsin as specific enzyme with a maximum number of two missed cleavages. Possible modifications included carbamidomethylation (Cys, fixed), oxidation (Met, variable), N-terminal acetylation (variable). The mass tolerance in MS was set to 20 ppm for the first search then 4. 5 ppm for the main search and 20 ppm for the MS/MS.
Maximum peptide charge was set to seven and seven amino acids were required as minimum peptide length. The ''match between runs'' feature was applied for samples having the same experimental condition with a maximal retention time window of 0. 7 min. One unique peptide to the protein group was required for the protein identification. A false discovery rate (FDR) cutoff of 1 % was applied at the peptide and protein levels. Quantification was performed using the XIC-based LFQ algorithm with the Fast LFQ mode  (Cox et al. , 2014)  and skip normalization was applied only for IP. Unique and razor peptides, included modified peptides, with at least 2 ratio count were accepted for quantification. For the differential analysis, proteins identified in the reverse and contaminant databases and proteins ''only identified by site'' were first discarded from the list of identified proteins.
Then, only proteins with at least four LFQ values in a condition were kept when comparing M. smegmatis rne overexpressing and silenced strains, and at least two LFQ values in a condition were kept when comparing M. smegmatis Rne pull-down versus control samples, to find potential interactors while ensuring a minimum of replicability of the measured LFQ values. After Log 2 transformation, LFQ values were normalized by median centering within conditions, using wrapper normalizeD function of the R package DAPAR  (Wieczorek et al. , 2017). Remaining proteins without any LFQ value in one of the both conditions have been considered as proteins quantitatively present in a condition and absent in another. They have, therefore, been set aside and considered as differentially abundant proteins. Next, missing values were imputed using the impute.
Additionally, a standard deviation of this quantity was computed for each protein. The protein-protein interaction networks (Figure  2 ) for the whole-cell proteome analyses were created in Cytoscape (version 3. 8. 2) using STRING  (Szklarczyk et al. , 2019). Medium confidence interactions (coexpression, experiments, neighborhood, co-occurrence and database with a score of 0. 4) relative to the query proteins were considered. Predicted proteins and protein with an unknown function were excluded from the protein-protein networks.
Figure2. Whole-cell mass spectrometry in M. smegmatis following deregulation of RNase E (A and B) STRING protein-protein interaction analyses of the whole-cell proteome after rne overexpression (A) and silencing (B). Proteins were grouped according to their functional category using Mycobrowser and color-coded. Symbols represent exclusive, upregulated and downregulated proteins compared to control bacteria. The PANTHER classification system was used for gene ontology analysis, to identify additional clusters. Data are from five independent replicates. See also TableS1.
Pearson r correlation coefficients were computed on (x, y) datasets. Two-way ANOVA, followed by correction for multiple comparisons, was performed to evaluate statistical significance between multiple groups. Brown-Forsythe, Welch and one-way ANOVA was computed to compare the variation of a single parameters over multiple groups. Chi square test of independence was used to compare two variables in a contingency table and check their relatedness. Plots merge datasets deriving from at least two independent replicates. Significant p-values, sample size and statistical tests are reported in the legends.
ACKNOWLEDGMENTS We thank  Blaise Li  ( Institut Pasteur Bioinformatics and Biostatistics Hub ), for support in writing a python script for sorting image analysis data. We thank  Delphine Vergoz  for her contribution to constructing the DVS2 strain. This work was funded by grants to G. M. from the  French National Research Agency  ( ANR-17-CE11-0007-01 ;  ANR-10-LABX-62-IBEID ). This project also received funding from the  Innovative Medicines Initiative 2 Joint Undertaking (JU)  under grant agreement No  853989. The JU receives support from the  European Union 's  Horizon 2020 research and innovation program  and  EFPIA and Global Alliance for TB Drug Development non-profit organization, Bill & Melinda Gates Foundation ,  University of Dundee. Work in G. M. 's laboratory also received financial support from the  Institut Pasteur  and a donation from  Mr.
Data and code availability All data reported in this paper will be shared by the lead contact upon request. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE database  (Perez-Riverol et al. , 2019) , with the unique dataset identifier PXD025674. This paper does not report original code. The scripts used in this study are available upon request to the lead contact. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.
Pearson r correlation coefficients were computed on (x, y) datasets. Two-way ANOVA, followed by correction for multiple comparisons, was performed to evaluate statistical significance between multiple groups. Brown-Forsythe, Welch and one-way ANOVA was computed to compare the variation of a single parameters over multiple groups. Chi square test of independence was used to compare two variables in a contingency table and check their relatedness. Plots merge datasets deriving from at least two independent replicates. Significant p-values, sample size and statistical tests are reported in the legends. T, 50 msec; FITC (Ex 475/28, Em 525/48) 100% T, 200 msec; TRITC (Ex 556/25, Em 611/47) 100% T, 600 msec. QUANTIFICATION AND STATISTICAL ANALYSIS Statistics Plots and statistical analyses were generated using Prism 8.
Methods The NP-SC simulator was designed to high-level standards by BONE 3D (Paris, France). The different development steps were segmentation, computer-aided design (CAD), and 3D printing. The segmentation step was performed using anonymized CT-and MRI-scans of the nasal and pharyngeal cavities using open-source software (3D Slicer software, version 4. 10. 2). The segmented elements were then reconstructed using CAD software (3-Matic 14. 1, Materialise, France). Finally, the simulator was designed to include main anatomic landmarks: nasal bones (including turbinates), nasopharynx, hard palate, facial skin, and mucosa. The model was 3D printed using PolyJet technology (J750™ 3D printer, Stratasys, Israel). Among the various 3D print technologies, this particular technique allows multimaterial printing using hard and soft materials with a Shore A hardness of between 30 and 90 (i.
Quantification of Brain Phenotypes For anatomy analysis, brains from larvae of 7 days after egg laying (dAEL) were dissected, fixed, and labelled with DAPI. The ratios area of neuroepithelium/area of the brain lobe (area NE/BL) and area of central brain/area of the brain lobe (area CB/BL) were calculated by using images acquired with a SP8 Leica confocal image microscope and by measuring the areas corresponding to the NE, the CB, and the brain lobe using FIJI software (version 1. 53q). The results were represented in boxplots, and p-values were calculated using nonparametric Mann-Whitney U tests using GraphPad Prism 9. 00 for MacOS X (GraphPad Software, La Jolla, CA, USA) (www. graphpad. com).
cDNA was hybridized to the GeneChip Drosophila Genome 2. 0 Array (Affymetrix, (Santa Clara, CA, USA), catalogue # 520087) for 16 h at 45 • C in a GeneChip Hybridization oven 645 (Affymetrix). Washing and staining of microarrays were performed using a GeneChip Fluidics Station 450 (Affymetrix) and arrays were scanned with GeneChip scanner GSC3000 (Affymetrix). Affymetrix GeneChip Command Console software (AGCC) was used to acquire GeneChip images and generate. CEL files for analysis.
A "soft" intensity-based filtering was applied as recommended by the limma user guide  [22]. The row-wise medians from the expression data were computed, as they represent the transcript medians, and a median intensity cut-off was chosen based on the data histogram; this resulted in 6624 transcripts excluded. Gene annotation was retrieved for the corresponding probe identifiers of the GeneChip Drosophila Genome 2. 0 Array (Affymetrix, catalogue # 520087), from the drosophila2. db R library  [23]. Here, only those probes that mapped to an annotation were kept because transcript cluster identifiers can refer to multiple gene symbols and, therefore, they cannot be unambiguously assigned. In summary, 12,043 transcripts were left for the downstream differential gene expression analysis. Different contrasts were considered when computing limma linear models, taking into account pair-wise comparisons of male versus female.
Acknowledgments: We are very grateful to  Manel Bosch  from the  CCiT-UB Imaging Facilities  for support;  J. I. Pons ,  D. Fernández , and  F. De Oliveira Monteiro  from the  IRB-Barcelona Functional Genomics  for their technical assistance; the  Developmental Studies for Hybridoma Bank  and the  Bloomington Stock Center  for antibodies and fly strains.
SARS-CoV-2 qPCR screening for variant-specific mutations identified an Omicron variant BA. 1/21K, BA. 4/22A, or BA. 5/22B. A SARS-Co-2 BA. 5/22B variant genome was recovered from one of the spouses. Aside from BA. 5/22B-defining amino acid substitutions, four other amino acid changes were encoded including Q556K in ORF1a, K2557R in ORF1b, and A67V and A829T in spike; only 13 genomes in sequence databases harbored these four mutations concurrently. Structural analysis of this BA. 5/22B variant predicted that A829T in spike may result in a compaction that may affect conformational plasticity. Overall, our findings warrant performing genome-based genotypic surveillance to survey accurately the emergence and circulation of SARS-CoV-2 variants worldwide and point out that their first occurrence in a country is often through international travel despite implemented countermeasures.
It harbored 37 nucleotide and amino acid mutations in its spike protein, which was dramatically more than for previous variants, and 72 along the whole genome, compared to the Wuhan-Hu-1 isolate (genome GenBank accession no. NC_045512. 2). The Omicron BA. 2/21L variant arose in late 2021 and early 2022, and replaced the Omicron BA. 1/21K variant worldwide during the first months of 2022. Its genome harbored 76 nucleotide and amino acid mutations, including 38 nucleotide and amino acid mutations (21 amino acid mutations in the spike) in common with the Omicron BA. 1/21K variant. The Omicron BA. 4/22A and BA. 5/22B variants arose in late 2021 and in early 2022, respectively, possibly in South Africa where early sequences were predominantly detected. They replaced the Omicron BA. 2/21L variant worldwide during summer 2022.
SARS-CoV-2 Genome Sequencing and Analysis SARS-CoV-2 genomes were obtained and analyzed as described previously  [1, 19]. Briefly, next-generation sequencing was carried out with the Illumina COVID-seq protocol on the NovaSeq 6000 instrument (Illumina Inc. , San Diego, CA, USA). Sequence read processing and genome analysis were performed as described previously  [1, 19]. Briefly, base calling was carried out with the Dragen Bcl Convert pipeline (v3. 9. 3; https://emea. support. illumina. com/sequencing/sequencing_software/bcl-convert. html; accessed on 11 July 2022; (Illumina Inc. )), mapping was carried out by the bwa-mem2 tool (v2. 2. 1; https://github. com/bwa-mem2/bwa-mem2; accessed on 11 July 2022) on the Wuhan-Hu-1 isolate genome (GenBank accession no. NC_045512. 2) before cleaning using the SAMtools program (v.
1. 13; https://www. htslib. org/; accessed on 11 July 2022)  [20]. Variant calling was performed by FreeBayes (v1. 3. 5; https://github. com/freebayes/freebayes; accessed on 11 July 2022)  [21] , and consensus genomes were built using the Bcftools program (v1. 13; https://samtools. github. io/bcftools/bcftools. html; accessed on 11 July 2022). Nucleotide and amino acid changes compared to the Wuhan-Hu-1 genome were identified with the Nextclade tool (https://clades. nextstrain. org/; accessed on 11 July 2022)  [4, 5]. Nextstrain clades and pangolin lineages were determined with the Nextclade web application (https: //clades. nextstrain. org/; accessed on 11 July 2022)  [4, 5]  and the pangolin tool (https://covlineages. org/pangolin. html; accessed on 11 July 2022)  [22] , respectively. Phylogeny was reconstructed by the IQTree (v2.
1. 3; http://www. iqtree. org/; accessed on 11 July 2022)  [23]  following sequence alignment with MAFFT (https://mafft. cbrc. jp/alignment/server/; accessed on 11 July 2022)  [24] , and trees were visualized with MEGA X  [25]. The genomes most similar to the sequence obtained here, among those of the entire EpiCoV database (https://www. gisaid. org/; accessed on 11 July 2022)  [26, 27] , were selected through a search with the AudacityInstant tool (https://www. epicov. org/epi3/frontend#4adee9; accessed on 11 July 2022)  [26, 27] , then incorporated in the phylogenies together with the Wuhan-Hu-1 genome sequence.
SARS-CoV-2 Spike Structure Analyses The structure of the BA. 5/22B spike protein was obtained by molecular modeling as previously described  [28]. Briefly, a complete structure of the spike protein was generated from the original 20B strain (Wuhan Hu-1 isolate with the D614G substitution in the spike protein, Protein Data Bank (pdb) number 7BNM (doi: 10. 2210/pdb7BNM/pdb)  [29]. All gaps in the PDB file were fixed by inserting the missing amino acids with Robetta (https: //robetta. bakerlab. org; accessed on 1 July 2022)  [30]. The structure was then submitted to several rounds of energy minimization with the Polak-Robière algorithm as described previously. This source file model was used to introduce the specific mutational profiles of BA. 5/22B, which was then simulated with the same method.
SARS-CoV-2 Genotyping SARS-CoV-2 qPCR screening for variant-specific mutations showed positivity for spike deletion 69-70 and spike mutation N501Y, and negativity for spike mutation E484K. This pattern was indicative of an Omicron variant BA. 1/21K, BA. 4/22A, or BA. 5/22B. The sample from the index case's spouse showed the same reactivities. Next-generation genome sequencing allowed obtaining a full-length genome that harbored all signature nucleotide substitutions and deletions of the Omicron BA. 5/22B variant (Figure  1 ) and was identified as of this genotype by the Nextclade and Pangolin tools, and by the phylogenetic analysis (Figure  2 ). The genome sequence obtained and analyzed, here, was deposited in the NCBI Gen-Bank nucleotide sequence database (https://www. ncbi. nlm. nih. gov/genbank/; accessed on 11 August 2022)  [31]  (Accession no.
No other genome of the Omicron BA. 5 variant has been deposited in the GISAID database (https://www. gisaid. org/; accessed on 11 July 2022) whose origin is the Seychelles or Monaco; but the number of genomes is only 30 since April 2022 for the Seychelles and zero for Monaco. In the eventuality of contamination during the stay in the Seychelles, this may have occurred though contact with the autochthonous population or with other travelers. This observation is likely an additional example of the difficulty of limiting the circulation of new variants between countries during international transport and of the inadequacy of the measures put in place for this goal. This has been shown very clearly by a recent study which detected the Omicron BA. 1 variant in the wastewater of aircraft arriving in Marseille (France) from Addis-Ababa (Ethiopia), while the passengers had been considered uninfected on boarding  [15].
Data Availability Statement: The genome sequence obtained and analyzed, here, was deposited in the NCBI GenBank nucleotide sequence database (https://www. ncbi. nlm. nih. gov/genbank/; accessed on 11 July 2022)  (Sayers et al. , 2022)   [31]  (Accession no. ON989858) and on the IHU Méditerranée Infection website (https://www. mediterranee-infection. com/tout-sur-le-coronavirus/ sequencage-genomique-sars-cov-2/; accessed on 11 July 2022; no. IHUCOVID-080068).
Chinook samples genotyping Family panels and genetic samples were the same as the ones described in Williamson and May  (Williamson and May 2005)  and were produced from a fall-run Californian Chinook population harvested at the Merced Hatchery. These family panels include crosses from a genotypic/phenotypic female (female XX 84) with a XY male (male B) and a phenotypic female with a XY genotype (Female 126 and Female 118) with a XY male (male D and male C). The OtY1, OtY2, and GH-pY genetic markers were used to assess the sex of each individual (parents and progeny). PCR sequencing analysis of exon 2, intron 2, and exon 3 was performed using a long-range PCR protocol and primers designed upstream and downstream of the sdY Chinook gene sequence (GenBank ID ¼ KC756279. 2), followed by targeted Sanger resequencing of these PCR fragments with internal primers for exon 2, intron 2, and exon 3.
Chinook testis RNA-seq Chinook testis was sampled from an adult male from the Umatilla river (OR), and the testis library was prepared using the TruSeq RNA sample preparation kit, according to manufacturer instructions (Illumina, San Diego, CA) as previously described  (Pasquier et al. 2016 ). These testicular transcriptome reads were mapped on a female Chinook genome assembly (Otsh_v1. 0, GCA_002872995. 1) plus the sdY Chinook gene sequence (GenBank ID ¼ KC756279. 2) using BWA  (Li and Durbin 2009)  with stringent mapping parameters (maximum number of mismatches allowed -aln 2). High-quality reads (MAPQ >40) remapping on the sdY gene were visualized and analyzed with the IGV software  (Robinson et al. 2011).
Protein structure prediction The 3D model of SdY-I183N was predicted using the X-ray structure of the dimeric interferon regulatory factor 5 transactivation domain at 2 A ˚resolution (PDB ID 3DSH) as template  (Chen et al. 2008). The 3D views of SdY-N183 were obtained with PyMOL software (Molecular Graphics System, Version 1. 7. 4; Schro ¨dinger, LLC).
Following the washes, membranes were incubated with SuperSignal West Pico Chemiluminescent Substrate (Thermo Scientific) for 1 min. The signal from the membranes was detected using the Photo Image Station 4000MM (Kodak). At least 2 independent experiments were performed and representative protein blot images are shown. Quantitative analysis was performed with ImageJ 1. 48v software (www. imagej. nih. gov).
The I183N substitution predicts potential local SdY misfolding To examine more precisely what conformational changes are produced by the I183N substitution, we modelled the SdY-I183N protein 3D structure using the IRF5 domain (PDB code 3dsh) as a template (Fig. 3a ). The model revealed that the I183N substitution is localized at the amino terminal end of the b 7 -strand shaping the hydrophobic b-sandwich core element of the protein (Fig. 3b ). The mutation induces a hydrophobic (I) to hydrophilic (N) amino acid pattern change likely modifying at least locally the folding of the b-sandwich. We then tried to find the most suitable model of SdY-I183N in which the hydrophilic side chain may have less negative impact on the folding and protein stability. Being exclusively surrounded by hydrophobic amino acids and with a similar size as the isoleucine (I183), it has not been possible to model the asparagine (N183) in an energetically favorable state.
2015). Interestingly,  Cavileer et al. (2015)  published a Chinook salmon sdY genomic DNA sequence (GenBank: KC756279) from Tozitna River, Alaska and a sdY cDNA sequence (GenBank: KF006343) from embryonic males from Clearwater River, Idaho. The alignment of those sequences with ours revealed the same nucleotide substitution (A/T) in exon 3 but not the (A/G) substitution in exon 2. We also report in the present study RNA-seq data from a Chinook male from the Umatilla river in Oregon that also has these 2 mutations. The presence of this nonfunctional mutation in 3 different populations across the North America coast (Alaska, Oregon and California) supports the hypothesis that this mutational event occurred before the establishment of these different populations and that this mutation could be widespread in many Chinook populations.
Acknowledgments We acknowledge  Wang Deshou  for the olacyp19a1a promoter. SB, AH, EJ, and AY performed experiments and analyzed the data, JB, HP, LJ, RG, KW, MM, and PS provided samples, TM modelled the SdY and IRF proteins, YG and MS designed the study and supervised the project, SB, AH, GM, YG, and MS wrote the paper.
For (C), 7 control (Prox1-CreER T2 without floxed transgenes) and 3 mutant (carrying both Prox1-CreER T2 and Prkar1a tm2Gsm alleles) mice were analyzed; for (D), 9 control (Vegfr3-CreER T2 without floxed transgenes) and 8 mutant (carrying both Vegfr3-CreER T2 and Prkar1a tm2Gsm alleles) mice were analyzed; for (E), 7 control (Vegfr3-CreER T2 without floxed transgenes) and 6 mutant (carrying both Vegfr3-CreER T2 and Prkar1a tm2Gsm alleles) mice were analyzed. Data are presented as scatter plot with individual values, means ± SD. Data were analyzed using two-tailed unpaired Student's t-test. ns, not significant. diaphragm (Figure  4A ) and ventral abdominal skin (Figure  4B ) of the Vegfr3-CreE and dnPKA:Vegfr3-CreERT2 mice expressed GFP, demonstrating successful recomb tion. Importantly, no enlargement of lymphatic vessels was observed in these mice (Fig 4A  , B ).
Here, 9 control (black) and 10 dnPKA iEC (red) mice from 4 different litters were analyzed. Mice (males and females) were injected with tamoxifen at the age of 30-34 days, and blood was taken by cardiac puncture at the age of 68-93 days. Data presented as box and whiskers plot. Means are indicated with a plus. Data were analyzed using two-tailed unpaired Student's t-test. (C,D) Induction of dnPKA specifically in blood vessel endothelial cells using Pdgfb-iCre led to a much slower and modest development of edema than in dnPKA iEC (C) and no hypoglycemia (D). Here, 10 control (Tg(Pdgfb-icre/ERT2) 1Frut without floxed transgenes; black) and 5 mutant (red) mice were analyzed (for (C)). For (D), 5 control (black) and 3 mutant (red) mice were analyzed. For panels (C,D), mice (males and females) were injected with tamoxifen at the age of 1-3 days weights, and blood glucose levels were measured starting with the day 40 after injection (40 dpi).
Gluconeogenesis but Not Albumin Expression Is Perturbed in dnPKA iEC Mice While edema is a frequent consequence of vascular defects, hypoglycemia is more difficult to explain by the intrinsic defects of endothelial cells. Since our data suggest involvement of the liver in the development of hypoglycemia, we tested whether metabolic Figure  6. (A) Plasma albumin levels showed a negative correlation with the degree of edema (manifested in a weight gain) in dnPKA iEC mice was observed. (B) No differences in blood insulin levels were detected between ad libitum fed dnPKA iEC mice and their control (Tg(Cdh5-cre/ERT2) 1Rha without floxed transgenes) littermates. Here, 9 control (black) and 10 dnPKA iEC (red) mice from 4 different litters were analyzed. Mice (males and females) were injected with tamoxifen at the age of 30-34 days, and blood was taken by cardiac puncture at the age of 68-93 days.