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Record W2759172222 · doi:10.1161/hyp.70.suppl_1.p279

Abstract P279: Mapping of Chromosome 2 Differentially Expressed Aortic Genes Linked to Vascular Inflammation Using Congenic Rats Fed a High-salt Diet

2017· article· en· W2759172222 on OpenAlexaff
Olga Berillo, Sofiane Ouerd, Ku-Geng Huo, Chantal Richer, Daniel Sinnett, Anne E. Kwitek, Pierre Paradis, Ernesto L. Schiffrin

Bibliographic record

VenueHypertension · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineJewish General Hospital
Fundersnot available
KeywordsCongenicGeneBiologymicroRNAGene expressionRNAInternal medicineEndocrinologyMolecular biologyGeneticsMedicine

Abstract

fetched live from OpenAlex

Background: Three congenic rat strains (SB2a, SB2b and SB2e) were created by chromosome (Chr) 2 fragment introgression from normotensive Brown Norway (BN) rats into hypertensive Dahl salt sensitive (SS) background. SB2a and SB2b rats fed a normal-salt diet presented reduced blood pressure (BP) and inflammation when compared to SS rats. We hypothesized that BN-Chr2 contains antihypertensive and anti-inflammatory genes that could prevent high-salt diet (HSD)-induced BP elevation and vascular injury in SB2a and SB2b rats. These genes will be identified using microRNA (miRNA) and total RNA expression profiling analysis in aorta of congenic rats fed a HSD. Methods and Results: Four-to-6 week-old male SS, SS, SB2a and SB2b rats were fed a HSD (4% NaCl) for 8 weeks or until they developed a stroke as manifested by seizures. Systolic blood pressure (SBP) was measured by telemetry. Systolic BP was higher in SB2b but not SB2a when compared to SS (185±8, 167±7 vs 168±5 mm Hg). Total RNA was extracted from aorta and used to construct libraries for small and total RNA sequencing using Illumina HiSeq-2500. The bioinformatics pipeline included: FastQC for quality control, STAR for genome (Rattus norvegicus, release-86) alignment, mirdeep2 for miRNA annotation and counting, Htseq-count for mRNA and long non-coding RNA annotation and counting; R for differential expression analysis. Differentially expressed miRNAs and genes (mRNAs and non-coding RNAs) were identified in SB2a vs SS (miRNAs: 11 up and 10 down; genes: 92 up and 91 down) and in SB2b vs SS (miRNAs: 3 up and 2 down; genes: 10 up and 13 down) with FDR<0.05. Differentially expressed genes encoded within different BN-Chr2 congenic portions were identified in SB2a vs SS (genes: 7 up and 2 down) and SB2b vs SS (genes: 6 up and 4 down). Conclusions and Perspectives: Differentially expressed BN-Chr2 encoded genes were identified in aorta of congenic SB2a and SB2b rats fed HSD. Whether these genes play a role in HSD-induced BP elevation and vascular inflammation remains to be determined.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.275
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes1
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