dataesr/scientific-paragraphs-categorization huggingface dataset:
Partnership map Despite the increased global commitment toward the elimination of human deaths from dog-mediated rabies, rabies control efforts remain fragmented and uncoordinated in many areas, resulting in duplicated efforts, poor use of resources and ineffective or unsustainable activities. To address these challenges and to improve coordination, transparency and equitable support to canine rabies endemic countries, the UAR Forum is developing a partnership map. This map will provide a regional and global overview of rabies stakeholders and will foster collaboration between stakeholders, helping them to better align efforts, avoid duplication and identify synergies. This workstream is currently collecting data on UAR Forum member activities (types of activity, and where these are being conducted), after which this will inform the development of a publicly available map which will be displayed on the UAR Forum website.
Oral rabies vaccine recommendations Oral rabies vaccination (ORV) is conducted in numerous countries for the control of wildlife rabies, but has not been used in any meaningful capacity to control dog-mediated rabies. One constraint to use of ORV in dogs is the lack of international guidance for the selection of safe and effective products and how to incorporate ORV into a large-scale dog vaccination programmes. Guidance for ORV in dogs was last updated in 2007  (43) , and does not reflect major advances in the production, safety, efficacy and recent field-use data for ORV in dogs. This workstream is revising the 2007 WHO Recommendations on ORV of dogs, and will focus on developing practical guidance for field implementation of ORV as a complementary measure to parenteral vaccinations. The revised recommendations will be published as a formal Tripartite publication in 2023, and this will be made available on the UAR Forum website.
The growing interest in microRNAs (miRNAs) over recent years has led to their characterization in numerous organisms. However, there is currently a lack of data available on miRNAs from triatomine bugs (Reduviidae: Triatominae), which are the vectors of the protozoan parasite Trypanosoma cruzi, the causative agent of Chagas disease. A comprehensive understanding of the molecular biology of vectors provides new insights into insect-host interactions and insect control approaches, which are key methods to prevent disease incidence in endemic areas. In this work, we describe the miRNome profiles from gut, hemolymph, and salivary gland tissues of the Rhodnius prolixus triatomine. Small RNA sequencing data revealed abundant expression of miRNAs, along with tRNA-and rRNA-derived fragments. Fifty-two mature miRNAs, previously reported in Ecdysozoa, were identified, including 39 ubiquitously expressed in the three tissues.
Additionally, a small fraction of tissue-specific miRNAs was observed, with 3 miRNAs unique to G and 1 unique to H (Fig. 3 ). MiRBase serves as a comprehensive public repository of miRNA data, and its latest release (v. 22, 2022) contains entries from 271 organisms, with a total of 48,860 mature miRNA sequences  56. Due to the relatively limited diversity of insect sequences in miRBase, however, the recovery of conserved miRNAs in samples may have been somewhat restricted. In our workflow, a single library was sequenced per tissue, which can pose challenges when discussing abundance in data analysis. To minimize this issue, we increased the number of individuals batched together and employed deep sequencing to maximize biological variability and coverage in a unique RNA-seq dataset. The expression levels of R.
4  The number of genome-mapped reads aligned against the star sequence (the sequence that aligns to the mature sequence) of a miRNA from miRBase. 5  Number of mature miRNAs detected by miRDeep2 against miRBase (using Ecdysozoa taxa as reference database) within the following parameters: number of mature read count > 10; number of star read count equal to or greater than 1; miRDepp2 score equal to or exceeding the cut-off of 1; "yes" in significant randfold p-value.
Validation of miRNA expression by qPCR. The enrichment of selected miRNAs was analyzed by RT-qPCR amplification. A subset of five highly-and two lowly-abundant miRNAs from the SGs was selected for correlation analysis using slRT-PCR approach  74. The Ct values obtained for miR-283, miR-12a, miR-281, bantam, and miR-8 (up-regulated) were much lower than those for miR-315 and miR-92b (down-regulated). The correlation between miRNA abundance (read counts) and Ct values was measured and is presented in Supplementary Fig. S2. The obtained data show RT-qPCR Ct values that reflect the read abundance in small RNA-seq analysis. The novel miRNAs from Rhodnius prolixus gut, hemolymph, and salivary glands. Prediction of novel miRNAs is based on secondary structures and lack of homology with miRNAs in other species  75.
prolixus samples can be seen in Supplementary Table  S2. The overlap analysis of these three subsets can be observed in Fig. 5. The sncRNA collection from Rhodnius prolixus is enriched with miRNA reads and possesses tRNA-and rRNA-derived RNA fragments. By aligning the genome-mapped reads against a collection of sncRNAs from Triatominae, we successfully classified the extracted sncRNA types, which included snoRNA, snRNA, tRNA-and rRNA-derived fragments. The R. prolixus miRNA sequences (both conserved and novel) obtained from our analysis were also included in this dataset to estimate the diversity and abundance distribution of sncRNA types within the three libraries. Supplementary Fig. S4  illustrates the diversity distribution of the identified sncRNA types from R. prolixus as a percentage-based representation.
More than 200 million reads were generated across the three libraries. After sequencing, raw reads were checked for data quality using FastQC v0. 11. 9 (Babraham Institute, Cambridge, UK)  82. Reads were then trimmed or discarded depending on their quality and size using Cutadapt v3. 3  83. Only processed reads with a minimum of 18 nt and a maximum of 50 nt were maintained. This process yielded high-quality and reliable data. In-house Python scripts were designed to shape the input data along the pipeline as well as R scripts for plots and command lines, which are available at https:// github. com/ walde yr/ Rhodn ius_ proli xus_ miRNA_ proje ct. The processed reads were mapped to the RprolixusV48 reference genome obtained from the VectorBase (https:// vecto rbase. org)  84. For this task, miRDeep2.
0. 1. 2 75 employed Bowtie v1. 2. 3 85 through the mapper. pl script. Only perfect alignments were retained (full length, 100% identity). Using the mapped reads and a file (downloaded from miRBase database, release 22. 1  56  ) containing 8763 known miRNA sequences from Ecdysozoa taxa, R. prolixus miRNAs were annotated, and novel miRNAs were predicted using miRDeep2. pl script with default options. The miRDeep2 core algorithm evaluated the presence of typical miRNA hairpin structures. If the reads fit in the hairpin as would be expected from Dicer processing, then the potential precursor was assigned as a Complementarily, the quantifier module from the miRDeep2 tool summed up miRNA read counts. The extracted known miRNAs were named according to their most similar miRNAs in the miRBase database.
Results were manually curated and integrated into a Microsoft® Excel spreadsheet that contains detailed information about the miRNAs extracted by the miRDeep2 package in the sequencing datasets (Supplementary Table  S4 ). Mature and novel miRNAs were considered high-confidence and selected as valid when filling parameters Significant randfold p-value: Yes; miRDeep2 score: > = 1; Mature read count: > 10; and Star read count: > = 1. We assumed the rRNA population is present proportionally to total RNA in tissues and applied a normalization strategy that considers rRNA read counts as a biological internal standard  86, 87. This internal control was used to manage between-sample biases enabling a comparison of miRNA expression levels. The term "abundance index" (AI) was employed to compare the relative expression of miRNAs, which here is defined as the number of reads mapped to total rRNA counts divided by the number of reads mapped to a single miRNA (both known and novel).
AI > 70 was set as the enrichment cut-off (miRNAs were considered highly expressed with AI values until tenfold less expressed than miR-283 from SG tissue, AI = 718, the most expressed miRNA across the three tissues). χ2 test and p-value were calculated to detect the significance level of changes. During the text, the discussed abundance levels are based on this outlined strategy. In parallel, to classify the sncRNA types in the samples, such as ribosomal RNA (rRNA), Piwi-interacting RNA (piRNA), transfer RNA (tRNA), small nuclear RNA (snRNA), and small nucleolar RNA (snoRNA); the reads that mapped to the R. prolixus genome were also aligned against Triatominae non-coding RNAs downloaded from the RNAcentral database release 10. 0 88 using Blast  89. The graphical representations of miRNAs secondary structures were obtained by using RNAfold with default settings  90.
mRNA blood transcripts were downloaded from Ensembl, using the BioMart tool  93. An over-representation analysis (ORA) method available in the WebGestalt tool  94  was used to perform enrichment analysis of the set of the predicted targeted genes to gain insight into enriched metabolic pathways in Reactome  95  and biological processes in Gene Ontology  80, 96. The parameters used were as follows: option "Top 20" on "Significance Level", meaning the categories are first ranked based on the FDR threshold, and then the 20 most significant categories are selected; 0. 05 on FDR threshold; and BH on Multiple Test Adjustment.
8% temperature increment. All reactions were performed in triplicate. The degree of linear association between read counts and Ct values was measured by calculating the Pearson coefficient correlation using Graph-Pad Software®, San Diego California USA. To estimate the strength of the relationship between data, p-value (derived from t-test) was used. A list of primer sequences, including the specific stem-loop and reverse primers, as well as the universal primer can be accessed in Supplementary Table  S5.
Acknowledgements This work was supported by grants awarded by the  Fundação de Amparo à Pesquisa do Distrito Federal  ( FAP-DF , grants  0193. 001802/2017 ,  00193-00000825/2021-19  and  00193-00002600/2022-70 ),  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES , grant  923/18 CAPES-COFECUB ),  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq ,  INCT-MCTI/CNPq/CAPES/FAPs 16/2014 ),  Financiadora de Estudos e Projetos (Finep , grant  CT-Infra 0439/11 ). KLSB was the recipient of a Ph. D. grant supported by the  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). We thank  Renato Junio Ribeiro  for triatomine picture assistance and  Robert N. G. Miller  for English language editing.
Data availability Small RNA-seq raw datasets were deposited in the National Center for Biotechnology Information (NCBI) in the Sequence Read Archive (SRA) under BioProject ID: PRJNA925536, Biosamples SAMN32800154 (G), SAMN32800155 (H) and SAMN32800156 (SG); and Sequence Read Archive (SRA) accessions SRR23130199, SRR23130198, and SRR23130197.
Recent evidence produced in the literature focused attention on the use of NETs' markers in clinical trials which were considered for the completeness of the review. Our effort was aimed at providing a synthesis between the evidence suggested in the experimental literature and the results emerging from the large body of clinical information relating to NET. We believe the evidence dispensed here could supply a basis for further discernment on the knowledge of the NET and could help the physician-patient discussion of the risks, benefits, and expectations about the role of the NET. Consider, if feasible to do so, reporting the number of records identified from each database or register searched (rather than the total number across all databases/registers). ** If automation tools were used, indicate how many records were excluded by a human and how many were excluded by automation tools.
Data Extraction, Quality Assessment, and Aims Data extraction was performed independently by 2 investigators (S. S. A. S. , F. B. ). The following variables were included: study demographics (sample size, number of centers, publication year, study period), type of study (animal, human), aims, and major findings of the data. Only animal models, RCTs, and observational studies of high quality were included in the final analysis. The primary objective of the systematic review was, in light of recent discoveries, the evaluation of the mechanisms that determine an alteration of inflammatory responses with the release of NETs in arterial thrombosis. The secondary objective was the evaluation of the potential clinical cardiovascular implication of bi-   S1 ).
Data Extraction, Quality Assessment, and Aims Data extraction was performed independently by 2 investigators (S. S. A. S. , F. B. ). The following variables were included: study demographics (sample size, number of centers, publication year, study period), type of study (animal, human), aims, and major findings of the data. Only animal models, RCTs, and observational studies of high quality were included in the final analysis. The primary objective of the systematic review was, in light of recent discoveries, the evaluation of the mechanisms that determine an alteration of inflammatory responses with the release of NETs in arterial thrombosis. The secondary objective was the evaluation of the potential clinical cardiovascular implication of biomarkers of NETs and the therapeutic implication of NETs in cardiovascular conditions.
We have a growing experimental literature, which agrees with the data above, reporting that NET-derived products can be detected in systemic chronic diseases complicated by cardiovascular disease. This condition is typical of patients who associate atherosclerosis with rheumatoid arthritis  [118, 126]. A total of 60 maintenance hemodialysis patients were studied in a cross-sectional analysis. Of these, 30 matched for age and sex were healthy individuals and represented the negative control while the other 30 patients manifested an acute infection and represented the positive control. In the latter, a correlation was reported between the increased production of NETs associated with uremia and with a worsening of atherosclerosis disease  [119]. Of no less importance is the evidence linking the formation of NETs to the vexing clinical problem of thrombotic complications associated with cancer  [127].
015 mg/L to 256 mg/L) against all isolates. Additionally, the susceptibility and MIC of resistant P. aeruginosa isolates-MDR, XDR, CAZ-AVI-resistant (CAZ-AVI-R), and those carrying MBL genes (NDM, VIM, IMP)-was also determined. Isolates were screened for the presence of bla IMP , bla VIM , and bla NDM using multiplex polymerase chain reaction, followed by amplification and sequencing of the full-length genes and comparison to publicly available databases as previously described  [3]. MDR was defined as non-susceptibility to any three drug classes, including cephalosporins, carbapenems, quinolones, aminoglycosides, polymyxins, monobactams, and penicillin combinations. XDR was defined as resistance to at least one agent in all but two or fewer antimicrobial classes (ie, bacterial isolates remain susceptible to only one or two classes), including aminoglycosides, carbapenems, cephalosporins, cephamycins, fluroquinolones, penicillin and penicillin combinations, glycylcyclines, monobactams, polymyxins, phosphonic acids, and tetracyclines  [14].
aeruginosa. Among the comparator agents, amikacin and colistin were active overall against the isolates of P. aeruginosa. However, only colistin was active against all the resistant phenotypes, including CAZ-AVI-R isolates of P. aeruginosa. These data are in line with previous reports of colistin being the only active agent against all isolates, thereby indicating the limited treatment options available against resistant strains of P. aeruginosa  [ 3 , 11 ]. This study had some limitations. A pre-defined number of isolates were collected from each site every year. Hence, the data on the distribution of isolates in this study cannot be interpreted as prevalence of infection or used for general epidemiological assessment. Clinical and epidemiologic information about the patient population was not available for the isolates collected in this study.
Background: Pertussis is a highly contagious respiratory disease, and those with chronic respiratory illnesses may be at higher risk of infection and severe pertussis. Acellular pertussis-containing vaccines (Tdap) are recommended in the United States for those with risk factors, such as asthma and chronic obstructive pulmonary disease (COPD). Objective: To determine Tdap vaccination rates among people with asthma or COPD compared with matched controls with type 2 diabetes and the general population. Methods: This observational database study identified adults with asthma or COPD, and their matched controls, from a large US administrative health claims system between January 2008 and December 2014. Vaccination with Tdap was identified using current procedural terminology and national drug codes, and vaccination rates per 1000 patient-years and adjusted rate ratios (RR) were calculated using a generalized linear model with a Poisson distribution and 95% confidence intervals (CI).
Study Design and Data Source This observational, database study was conducted to assess Tdap vaccination rates in the United States, among adults with either asthma or COPD compared with the general adult population or adults with T2D. The T2D cohort was included as a comparator group of adults with a nonrespiratory comorbidity that had similar health care needs and similar health care-seeking behavior (ie, requiring frequent engagement with health care providers) to those with asthma or COPD. The population data set was obtained from Optum's deidentified Clinformatics Data Mart Database (2007-2021), which is an administrative health care claims system from a large national managed care company across all 50 US states. The data set included commercial health plan members and Medicare Advantage members with both medical and prescription drug coverage recorded between January 1, 2007 and December 31, 2019.
Claims data are collected for reimbursement purposes and not for clinical research, and databases may include incomplete or inaccurate coding. In addition, when assessing vaccination coverage, it is assumed that pharmacy and procedure claims are complete and accurate. However, these data do not capture vaccinations that are not covered by a patient's health insurance. The average length of enrollment in the database was approximately 3 years, yet Tdap vaccination was unlikely to be administered at intervals of under 10 years for adults, meaning that, for some patients, their longitudinal history in the database may not be long enough to capture all vaccinations. However, this limitation applies across all the cohorts and is unlikely to confound our comparisons. Finally, the study assessed Tdap vaccination rates among a Medicare Advantage and commercially insured population; therefore, interpretations regarding vaccination coverage in the Medicaid or feefor-service Medicare population should be made with caution.
ARIC Cohort We used the data of the ARIC study, a longitudinal populationbased cohort study of cardiovascular disease (CVD) and its risk factors ongoing since 1987. A detailed description of the ARIC study design and methods has been published elsewhere. 14 he analysis reported herein was conducted among individuals who participated in ARIC visit 5 (age 69-88 years), conducted between June 1, 2011 and August 30, 2013. Participants with HF history at the 5th visit were not considered eligible for this analysis. We performed a classical nested matched case-control study (ie, controls were study participants who did not develop HF up until the end of follow-up). Controls were matched within each cohorts on follow-up time, age, and sex.
The FHS Cohort The FHS is a community-based longitudinal study that began in 1948. Residents of Framingham, Massachusetts were invited to participate in a study of the prevalence, incidence, and natural history of CVDs. Participants attend on-site clinical examinations and provide information on cardiovascular health through face-to-face interviews, self-administered questionnaires, physician examinations, and provide blood samples for laboratory tests. For the current study, the 7th examination FHS Offspring cohort examination, conducted from 1998 to 2001, was used. Information on CVDs diagnosis was abstracted from the Framingham Heart Study 3-physician verified medical record data file using December 31, 2016 as the deadline of update. A total of 43 (1. 22%) participants had a diagnosis of HF prior to their seventh examination date who were excluded from eligibility for this study.
HOMAGE Cohort The HOMAGE consortium (NCT02556450) is a European Union funded program that aims to identify and validate omics biomarkers associated with incident HF in order to potentially develop new and personalized preventive strategies. The HOMAGE consortium included 20 completed and ongoing studies conducted in 8 European countries that enrolled healthy subjects, patients with HF, and patients at high risk of CVD, all of which were pooled in a common database. 15 From the HOMAGE population with >20 000 patients, we identified cohorts in whom individuals without a history of HF at baseline had been followed up until first hospitalization for HF. Participants from 2 suitable cohorts and 1 clinical trial population were identified: PREDICTOR  16  (patients recruited from 2007 to 2010), HEALTH-ABC  17  (recruited from 1997 to 1998), and PROSPER  15, 18  (recruited from 1997 and 1999).
Sample Handling All sample shipments and sample data acquisition within the HOMAGE consortium (including the ARIC and FHS databases) are according to predefined standard operating procedures and material transfer agreements to maintain uniformity. Figure  S1  shows the sample handling and storage per cohort and the sample flow until protein measurement at the TATAA-Biocenter (Gothenburg, Sweden) and OLINK Proteomics (Sweden). The cases and controls were separately identified and selected by the study statistician. All participants' information was then removed and a randomly sorted list of patient/sample IDs for each cohort was sent to Maastricht University Medical Center. Aliquoting of the samples at Biobank Maastricht was performed using a multi-pipette in 1 run to reduce freeze/thaw cycles and batch effects.
When binding to their correct targets, they give rise to new DNA amplicons with each ID-barcoding their respective antigens. The amplicons are subsequently quantified using a Fluidigm BioMark HD realtime PCR platform. The OLINK platform provides log2-normalized protein expression data. A detailed description of the Olink technology is depicted in the Supplemental Material. For 9 proteins measured in both the inflammation panel and CVD panels, the one from CVD panels was used for further data analyses (the results for these pairs of proteins were strongly correlated ≥0. 9). In addition, 15 proteins that were below the limit of detection (LOD) were not included in the analysis. The Olink® quality control samples are considered as flagged if they deviate more than 0. 3 log2-normalized protein expression from the median of all samples in 1 of 2 control assays for incubation and detection.