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Abstract 18802: Transcriptome Profiles of Chronically Closed or Cycling Aortic Valve Leaflets are Highly Similar Compared to Chronically Open Valves: Distention Drives Leaflet Homeostasis

2015· article· en· W3206084706 on OpenAlexaff
Katsuhide Maeda, Xiaoyuan Ma, Frank L. Hanley, R. Kirk Riemer

Bibliographic record

VenueCirculation · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMerck Canada Inc. (Canada)
Fundersnot available
KeywordsAortic valveTranscriptomeMedicineCardiologyHomeostasisInternal medicineLeaflet (botany)Heart valveAnatomyGene expressionBiologyGene

Abstract

fetched live from OpenAlex

Introduction: Throughout the valve cycle mechanical forces of multiple types and intensities are exerted on the leaflets, sinus and annulus. The mechanisms through which these forces regulate the homeostatic maintenance of valve leaflet architecture are still poorly understood. Ventricular mechanical support with a continuous flow device results in chronic closure of the outflow valve. Whether chronic valve closure affects valve leaflet homeostasis is a significant but unsettled clinical concern. Hypothesis: We asked if chronic closure of the aortic valve (AV) impairs leaflet homeostasis by comparing the transcriptome profiles of AV cultured under different mechanical force conditions: Normally cycling (Flow); Not cycling but open (Static); or Not cycling but closed (Static-Closed, SC). Methods: Ex vivo culture of native rat aortic valves, (8 valves per bioreactor, 4 valves per condition) was conducted in a flow bioreactor for seven days at 37C in endothelial cell culture media under conditions approximating the normal stroke volume of the rat heart. In each of 4 independent experiments, flow-induced valve cycling (Flow) was compared with either Static or SC condition in paired groups. After culture, leaflets were dissected from 3 valves/condition and pooled, mRNA was extracted and expression was evaluated using whole genome microarrays. Results: Statistical-based unsupervised hierarchical clustering analysis of the leaflet transcriptome profiles revealed only two distinct patterns of leaflet gene expression between the three groups of AV. Flow and SC groups had nearly identical profiles whereas the Static valve group was distinctly different (p<0.05). Conclusions: These results reveal that the stretching of valve leaflets by a filling volume inducing full coaptation is apparently sufficient to largely preserve their architecture and phenotypic gene expression in the seven day culture period tested. In contrast, the absence of valve closure produces a markedly different pattern of gene expression. Therefore, the absence of flow through the closed AV valve does not appear to be inherently destructive compared with conditions in which the valve remains open.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.374
Teacher spread0.306 · 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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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