dataesr/scientific-paragraphs-categorization huggingface dataset:
Data were reconstructed with 100-μm isotropic voxel size using a regularized statistical (iterative) image reconstruction algorithm  (56). On the SkyScan1278, hamsters were scanned in supine position under isoflurane anesthesia, and the following scan parameters were used: 55 kVp X-ray source voltage and 500-μA current combined with a composite X-ray filter of 1-mm aluminum, 80-ms exposure time per projection, acquiring four projections per step with 0. 7°increments over a total angle of 220°, and 10 cm field of view covering the whole body, producing expiratory weighted three-dimensional data sets with 50-μm isotropic reconstructed voxel size  (57). Each scan took ∼3 min. Visualization and quantification of reconstructed micro-CT data were performed with DataViewer and CTan software (Bruker Belgium).
As primary outcome measure, a semiquantitative scoring of micro-CT data was performed as previously described  (56). Visual observations were blindly scored (from 0 to 2, depending on severity, both for parenchymal and airway disease) on five different, predefined transversal tomographic sections throughout the entire lung image for both lung and airway disease by two independent observers, and averaged. Scores for the five sections were summed up to obtain a score from 0 to 10, reflecting severity of lung and airway abnormalities compared to scans of healthy, wild-type control hamsters. As secondary measures, imaging-derived biomarkers (nonaerated lung volume, aerated lung volume, total lung volume, and respective densities within these volumes) were quantified as previously  (15, 57, 58)  on a manually delineated volume of interest covering the lung, avoiding the heart and main blood vessels.
The threshold used to distinguish aerated from nonaerated lung volume was manually defined and kept constant for all datasets  (57, 58). Statistics. GraphPad Prism (GraphPad Software, Inc. ) was used to perform statistical analysis. Statistical significance was determined using the nonparametric Mann-Whitney U test. P values of ≤ 0. 05 were considered significant. Data Availability. All data supporting the findings of this study are available in the main text and/or SI Appendix.
ACKNOWLEDGMENTS. We thank  Eef Allegaert ,  Sabrina D'Haese , and  Kathleen Van den Eynde  for excellent technical assistance. We are grateful to  Piet Maes  for kindly providing the SARS-CoV-2 strain used in this study. We thank  Molecubes and Bruker Belgium  for their support with the implementation of the micro-CT installation,  Jef Arnout  and  Annelies Sterckx  ( KU Leuven Faculty of Medicine, Biomedical Sciences Group Management ) and  Animalia and Biosafety Departments of KU Leuven  for facilitating the studies. This project has received funding from the  Covid- 19-Fund KU Leuven/ Universitair Ziekenhuis Leuven  and the  COVID-19 call of Fund for Scientific Research Flanders (FWO)  (grant  G0G4820N ), the  European Union 's  Horizon 2020 research and innovation program  under Grant Agreement  101003627  ( Swift COronavirus therapeutics REsponse project ), funding from  Bill and Melinda Gates Foundation  under Grant Agreement  INV-00636 , and the  Stichting Antoine Faes.
G. V. V. acknowledges grant support from  KU Leuven Internal Funds  (grant  C24/17/061 ). The deep sequencing was funded by the  James Black charitable foundation  (grant  559133 ). C. C. was supported by the  FWO  ( FWO grant   1001719N ). S. J. is supported by a  PhD fellowship of the Fund for Scientific Research Flanders  ( FWO grant   1S21918N ). S. t. H. and L. Langendries are supported by a  KU Leuven  internal project. B. H. is a postdoctoral fellow of the  Flemish Research Council  ( FWO grant   12R2119N ). J. P. is funded by a  Rosetrees  studentship (grant  M876 ). J. B. receives funding from the  National Institute for Health Research University College London/ University College London Hospitals Biomedical Research Centre.
Insect Rearing A. grandis was reared under controlled temperature (27 ± 2 • C), relative humidity (70 ± 10%) and photoperiod (14 light:10 dark). Insects were fed daily with an artificial diet  (Monnerat et al. , 2000). Identification, cDNA Cloning and Sequence Analyses of AgraLac2 tBLASTn analyses were performed to search for Lac2 orthologue sequences in the A. grandis transcriptome  (Firmino et al. , 2013)  using Lac2 sequences from T. castaneum (AAX84202. 2 and AAX84203. 2) as queries. Two orthologous sequences corresponding to the Lac2 gene were retrieved from the A. grandis transcriptome (A_grandis_454_c23509 and A_grandis_454_rep_c1717). Thereafter, BLASTx searches were performed against the NCBI non-redundant protein database using A. grandis contigs to confirm their identity. To obtain a clone of AgraLac2, a partial sequence of AgraLac2 was amplified from larval A.
Bioinformatic Analyses Phylogenetic analysis with different insect Lac2 protein sequences was performed to evaluate possible orthology relationships among the predicted AgraLac2 protein (Supplementary Data 3) and the other selected Lac2 proteins from four different insect orders (Coleoptera, Diptera, Hymenoptera, and Lepidoptera). DELTA-BLAST searches were performed in public databases (NCBI, 1  ) using the AgraLac2 protein sequence as a bait. DELTA-BLAST constructs a Position-Specific Scoring Matrix (PSSM) using the results of a Conserved Domain Database (NCBI) and searches a sequence database. Only complete protein sequences belonging to four insect orders were selected. Additionally, the selected sequences showed similarity to AgraLac2 greater than 80%, alignment coverage greater than 85% and e-value lower than or equal to 10 -40.
These parameters allowed the selection of 127 different Lac2 protein sequences from four different insects orders (42 from dipterans, 19 from coleopterans, 45 from hymenopterans, and 21 from lepidopterans). After the selection, all the sequences with the chosen outgroup (Nannophya pigmaea; accession number BBC20924. 1) were aligned using the software Mafft (Mafft -version 7 2  )  (Katoh et al. , 2019)  by applying the iterative refinement method with global alignment (G-INS-i) guided by a preliminary phylogenetic tree (default mode). In the following step, phylogenetic reconstruction was performed by the Maximum Likelihood method using the Randomized Axelerated Maximum Likelihood software (RAxML -version 8. 2. 12)  (Stamatakis, 2014)  with the options # autoMRE (the software decided how many bootstrap replicates must be run) and -m PROTGAMMAAUTO (the best protein substitution model was auto-selected).
The best phylogenetic tree was analyzed and annotated using the online tool Interactive Tree of Life (iTOL -version 4 3  )  (Letunic and Bork, 2019). The search for the characteristic domains in the selected Lac2 protein sequences was carried out with the software HMMER v3. 3. 1  (Wheeler and Eddy, 2013) , which is used to search for homologous sequences on databases using probabilistic models called Hidden Markov Models (HMMs)  (Terrapon et al. , 2012). The version of the database selected for the construction of the HMM profile was Pfam 33. 1 4. Domain sequences that had similarity with HMM profile with e-value less than or equal to 10 -20 were selected. The same selected domain protein sequences identified with HMM analysis were also identified with MEME v5. 1. 1 5 (Bailey et al. , 2009) , which included Cu-oxidase (PF00394.
Additionally, morphological analysis of larval tissues was performed to aid in cuticle and epidermis recognition and avoid data misinterpretation. The tissues were fixed and dehydrated as described previously. Then, the tissues were embedded in Technovit 7100 (Heraeus Kulzer, Wehrheim, Germany) as described by the manufacturer. The embedded tissues were sectioned (3 µm), stained in 0. 05% toluidine blue, and imaged with a digital camera (Axiocam, Carl Zeiss, Jena, Germany). dsRNA Synthesis Gene-specific primers designed using BLOCK-iT TM RNAi Designer software 7  containing the T7 promoter at 5 end were used to amplify the DNA template for dsRNA synthesis (Table  1 ). The dsAgraLac2 was designed to target a fragment of 332 bp length, starting at nucleotide position 785 and ending at nucleotide position 1114 of the cloned AgraLac2 transcript sequence (Supplementary Figure  1 ).
RNA Extraction, cDNA Synthesis and RT-qPCR Analysis Total RNA was extracted from A. grandis insects using TRIzol reagent (Invitrogen, Carlsbad, CA, United States) according to the manufacturer's instructions. The RNA samples were treated with 2 U of DNase I RNase-free (Ambion, Austin, TX, United States) for 30 min at 37   (Zhao and Fernald, 2005). The relative expression level of the target gene was calculated with qBasePlus software (Biogazelle, Zwijnaarde, Belgium) using the E -Ct method  (Pfaffl, 2001). Glyceraldehyde 3-phosphate dehydrogenase (Gapdh) and β-tubulin (β-tub) were used as reference genes for normalization. For AgraLac2 gene expression analysis in different developmental stages of A. grandis, three biological replicates of eggs, larvae (1st -3rd instar), pupae and 10 days old adults (females or males) were used.
Identification, Cloning and Sequence Analyses of AgraLac2 We identified two contigs in the A. grandis transcriptome (contig A_grandis_454_rep_c1717 and contig A_grandis_454_rep_c23509) (Supplementary Data 1) putatively encoding Lac2. Significant hits to A. grandis contigs were retrieved using BLASTx against the NCBI non-redundant protein database (Supplementary Table  1 ). Based on the AgraLac2 contigs, specific primers were designed, and a partial cDNA sequence of AgraLac2 was cloned. The consensus sequence of the cloned fragment and AgraLac2 contigs was identified as Lac2 gene by BLASTx, confirming the identity of the sequence. The partial cDNA AgraLac2 sequence has been deposited in the NCBI under the accession number MW029454.
AgraLac2 Phylogenetic Analysis An important step in the RNAi studies is the in silico characterization of the target sequence. Even with the advances achieved with traditional homology tools, phylogenetic analyses are still the most indicated and the most precise for predicting orthology relationships among sequences, since the quality of the functional annotation of genes deposited in public databases is not always accurate. For this purpose, phylogenetic trees are constructed with sequences whose function has been previously validated. According to the literature, Lac2 has been well characterized in Manduca sexta and T. castaneum  (Arakane et al. , 2005; Dittmer et al. , 2009). Thus, as shown in Figure  1A , the clustering of the AgraLac2 protein sequence in the same group as the sequences of M.
sexta and T. castaneum is a strong indication of orthology among these proteins that possibly share the same function. Furthermore, the phylogenetic analysis of Lac2 proteins from species of four orders of holometabolous insects (Coleoptera, Diptera, Hymenoptera, and Lepidoptera) showed that these sequences underwent a small evolutionary pressure since these protein sequences probably underwent few nonsynonyms mutations during the evolution. This hypothesis can also be confirmed with the identification and in silico evaluation of the main protein domains of these sequences. According to the analyses of hidden Markov models (HMMs) with the Pfam database, the Lac2 from the insects analyzed are composed of 3 domains multicooper oxidases (Cu-oxidase 3 -PF07732. 15, Cu-oxidase -PF00394. 22, and Cu-oxidase 2 -PF07731.
Bootstrap values between this range are represented by black circles with increasing diameter. Nannophya pigmaea (BBC20924. 1) is the outgroup. (B) Schematic representation of Lac2 protein from the analyzed insects (including AgraLac2), where an N-terminal region with variable sequence (absent in AgraLac2, since this study identified only partial AgraLac2 sequence) and three multicooper oxidase domains are highlighted: Cu-oxidase (PF00394. 22; blue box), Cu-oxidase 2 (PF07731. 14; pink box), and Cu-oxidase 3 (PF07732. 15; green box). (C) Consensus sequence of three multicooper oxidase domains characteristic of insect Lac2 proteins. The consensus sequence was obtained from 127 different Lac2 proteins selected for this study.
Participants and Treatments This study is part of a single-arm multi-site Phase Ib clinical trial that evaluates the safety, tolerability and feasibility of eliciting adequate IgG response with P10s-PADRE vaccine and MONTANIDE TM ISA 51 VG as an adjuvant. P10s-PADRE peptide synthesis and vaccination was described before (1). This clinical trial was approved by the Institutional Review Board (IRB) of the University of Arkansas for Medical Sciences (UAMS) and was registered with the NIH clinicaltrials registry at http://clinicaltrials. gov (NCT02229084). The study was first released on clinicaltrials. gov on 08/26/2014. The IRB was approved on 12/02/2014 and the trial was opened to enrollment on 01/14/2015. The first subject was enrolled on 02/26/2015. Women 18 years of age or older, of all races, with clinical stage I, II or III ER-positive breast cancer were eligible, and subjects were enrolled after providing written informed consent.
05% Tween-20 (PBS-T), 25 µL of detection antibody was added to each well. The plate was then placed on a plate shaker and mixed at 700 rpm for 2 h at room temperature. Following incubation, the plate was washed 3 times with PBS-T and 150 µL of 2X Read Buffer was added to each well. The plate was analyzed using the MSD Electrochemiluminescence (ECL) charge-coupled device (CCD) and QuickPlex SQ 120 imager and the results were reported using the Discovery Workbench 4. 0 software (MSD). The preimmune (collected at week 1) and post-immune sera (collected at weeks 7 or 8, depending on the treatment schedule, see Supplementary Table  S1 ) were used for IFN-γ measurement. Subject A3 had its week 7 blood missing and therefore the week 10 serum of this subject was used to determine the post-immune cytokine levels.
Analyses of DNA Methylation Data Illumina intensity data (. idat) files from the chip were extracted using the Methylation module (v. 1. 8. 0) of the GenomeStudio (v. 2011. 1) software from Illumina. CpG probes with a detection p > 0. 01 and rsSNPs were removed using this software. DNA methylation levels were reported as β values, which are measurements of the degree of methylation at a specific CpG locus that range from zero (0%) to one (100%), where zero indicates a non-methylated probe and one indicates a fully methylated probe. The. idat files were transferred into Partek Genomics Suite (St. Louis, MO) and probes located in the X and Y chromosomes and those with polymorphic targets and cross-hybridization potential [non-specific probes described on  (25) ] were filtered out. At the end of all filtrations, we had a total of 527,362 CpG probes that were functionally normalized.
Pathway and Network Analyses In order to interpret the BeadChip array data, we used Ingenuity R Pathway Analysis (IPA R ) tool, version 01-12. IPA is based on the Ingenuity Knowledge Base that contains manually curated content related to studies and observations from biomedical literature and also integrated from other data bases  (26). The lists of DM CpGs and their respective pvalues were uploaded as excel files into IPA, and by using the Core Analysis, the canonical pathways and networks associated to them were developed. The selected pre-analysis parameters were: file format selected as flexible, the reference dataset was Illumina Human Methylation 450 v1-v2, the relationships to consider were direct and indirect based on published interactions, all the nodes (molecules) were selected, the number of molecules per network was 35, the confidence chosen was experimentally observed (not predicted), information associated to tissues and cell lines and the species was human.
The networks are shown as genes or their products (nodes) and their biological relationships (edges). Networks contain a score based on the number of eligible molecules they contain. The score is calculated through Fisher's Exact Test. The higher the score, the probability to find the molecules present on the network by random chance is lower and considering this, the network with the highest score was the one selected for each analysis. The same test is used for the pathways' discovery. The p-value in the canonical pathways depends on the size of the pathway and is less significant when the proportion of the reference set molecules present in the pathway is larger. Another measurement is the ratio and it is estimated by considering the number of genes from the uploaded data set that are on the canonical pathway and is divided by the total number of genes present in the pathway, hence the ratio shows the percentage of genes in a given pathway that were also present in the uploaded gene list.
Association of Differentially Methylated Loci With Antibody Levels in Immunized Subjects Eight BC patients (Table  1 ) were included in the present study. The anti-P10s antibody titer was measured in preand post-immune sera (Supplementary Table  S1 ) and the fold change in serum antibodies in post-immune serum compared to pre-immune serum was determined (Table  1 ). Global DNA methylation was performed using the Infinium Human MethylationEPIC BeadChips in pre-immunized PBMCs collected from each subject. The data were processed after filtering undesirable probes (see methods), and the analysis proceeded with 527,362 probes. Using a linear regression model, we assessed the association between DNA methylation and IgG levels elicited after the third vaccination with P10s-PADRE. 182 DM CpGs were identified among the subjects (P ≤ 0.
Thus we could note two groups in one cluster formed by methylomes from non-responders (A4, B1) and low antibody titers responders (C2, D1: 4-fold) indicating their methylation signatures are more similar in comparison to those from the patients with higher IgG levels: 16-, 32-, and 64-folds which were clustered together, although methylomes of subjects C1 and A3 (32-and 64-folds, respectively) were separated clades. Predicted interactions of the differently regulated genes were generated by IPA using the dataset of the 182 DM CpG profiles and their respective P-values. Eighty-two out of 182 DM CpGs mapped into the IPA database and were significantly enriched in five affected canonical pathways, including: remodeling of epithelial adherens junctions, CTLA4 signaling in cytotoxic T lymphocytes, NOTCH signaling, tyrosine biosynthesis IV and phenylalanine degradation I (Figure  2A , Table  2 ).
79-folds) were grouped together while those with higher IFN-γ levels were clustered separately (Figure  3B ). Following the same strategy of the previous analysis, 398 DM CpGs were uploaded into IPA and 193 out of 398 DM CpGs were mapped into the IPA database. The top five canonical pathways affected by IFN-γ levels were found, including growth hormone signaling, telomere extension by telomerase, STAT3 pathway, IGF-1 signaling and neuropathic pain signaling in dorsal horn neurons (Figure  4A , Table  3 ). Fourteen focused molecules were mapped to the top network that was associated with cellular movement, cell death and survival, cell-to-cell signaling and interaction, with four of the canonical pathways mentioned above.
(2009)  calculated a between competition performance variation of ∼1% with data from 242 elite Paralympic swimmers. Further,  Pyne et al. (2004)  calculated a between competition performance variation of 0. 8%; 0. 73-0. 86%, with data from 51 Olympic level swimmers. Interestingly, a more recent study of 19 elite swimmers during their 8 months build up to the Rio Olympics reported variations of between ∼0. 7-0. 5% with greater variation for sprinters compared to middle distance swimmers and males compared to females  (Clephas and Wilhelm, 2019). As evidenced above, researchers recognize the importance of quantifying competition-to-competition variability in swimming performance. This enables estimation of the smallest worthwhile performance change, which in turn helps coaches to define realistic goals and training methods  (Pyne et al.
Procedures The publicly available Swimming New Zealand 1  which can be accessed through the Swimming New Zealand website (https:// swimming. org. nz/) collates data from official swimming events from club championships, inter-club, regional and international meets that Swimming New Zealand members compete in. Using this database, we retrospectively extracted and collated the official race times of backstroke events for swimmers aged 8 to 18 years over an 11-year period, from 2006 to 2017 inclusive. Data was categorized as either long or short-course (25 or 50 m pool length) and further categorized by race distance (50, 100, and 200 m) and swimmer age and gender. As we were interested in year to year performance change, swimmers needed to have swum for more than 1 consecutive year to be included in the analysis.
RESULTS The collated 11 years of data provided an accumulated total of 9,956 swimming years. At the youngest ages the longest events were the least competitive with the lowest number of competitors in both short and long-course contests (see Table  1 ). The mean performance times improved by approximately one third (34-42%) from age 8 to 18 years, with similar percent changes in long and short course and for each gender (see Table  2 ). The greatest improvements were at the younger ages, and overall there was a trend for larger performance improvements the shorter the distance. Interestingly, the female 200 m short course showed the only performance detriment (negative performance improvement), see Table  3. Normative stability values were all high and ranged between 0. 66 and 0. 98 for short course performance whereas long course performance ranged between 0.
LAMP2 Emerged Concomitantly with the Origin of the Vertebrate Lineage Homology-based searches in the publicly available RNA-seq databases (PhyloFish), providing comprehensive gene expression data from 23 different ray-finned fish species  (Pasquier et al. 2016) , resulted in the identification of several contigs displaying high-sequence homology with mammalian LAMP2A  (Lescat et al. 2018). These results strongly suggested that the Lamp2a protein was present in fish and therefore could have appeared earlier in evolution than initially  Lescat et al. doi:10. 1093/molbev/msaa127 MBE thought. We therefore sought to further clarify the evolutionary history of the LAMP2 gene in vertebrates. To this end, phylogenetic analyses have been conducted using sequences of LAMP family members (LAMP1, LAMP2, LAMP3, and LAMP4/CD68/MACROSIALIN) including human, three fish species (the zebrafish Danio rerio, the medaka O.
The phylogenetic and syntenic analyses were performed for human (Homo sapiens), spotted gar (Lepisosteus oculatus), zebrafish (Danio rerio), medaka (Oryzias latipes), ascidians (Ciona intestinalis), fruitfly (Drosophila melanogaster), and worm (Caenorhabditis elegans). The genomic organization of lamp2 was analyzed in four tetrapod species and nine fish species. (A) Phylogenetic tree, based on full-length amino acid sequences of Lamp1, Lamp2b/a/c (concatenated sequences), Lamp3, and Lamp4 proteins, was built using the maximum likelihood method (the Whelan and Goldman þ Freq. model) with 500 bootstrap replicates. The number shown at each branch nodes indicates the bootstrap value (%). The tree was rooted using urochordata and invertebrates Lamp sequences. Accession numbers from Ensembl database are available in supplementary data set S1, Supplementary Material online.