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Abstract 4143866: The Effect of S100A6 Gene Therapy on Cardiac Function in a Rat Model of Ischemic Cardiomyopathy

2024· article· en· W4404359414 on OpenAlexaff
Leila Gholami Chookalaei, James N. Tsoporis, Michael A. Kuliszewski, Howard Leong‐Poi

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicS100 Proteins and Annexins
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineIschemic cardiomyopathyCardiomyopathyCardiac function curveCardiologyGenetic enhancementInternal medicineGeneHeart failureEjection fractionGenetics

Abstract

fetched live from OpenAlex

Background: S100A6 is a small calcium-binding protein that is important in managing calcium storage and myocyte contractility. This protein has a low basal cardiac expression and is upregulated following Myocardial Infarction (MI). Previous experiments have demonstrated that S100A6 gene transfer improves left ventricular function after acute ischemia/reperfusion injury. Hypothesis: Delivery of S100A6 by Ultrasound-Targeted Microbubble Destruction (UTMD) after established MI model results in improved left ventricular function and prevention of adverse ventricular remodeling. Aim: Assess the impact of UTMD delivery of S100A6 on cardiac function following experimental MI. Methods: MI was induced through permanent left anterior descending (LAD) coronary artery ligation in 8-week-Spragues Dawley (SD) male rats on day 0. On day 28, by using UTMD methods, we delivered microbubbles (1×109) coupled with either 200 μg of human S100A6 mini-circle DNA or empty minicircles to the left ventricle (LV), while control animals received no therapy. The three groups were monitored weekly for four weeks post-gene delivery using serial echocardiography to follow LV function, followed by tissue collection from various regions of the myocardium. Results: At day 28 post-MI, all groups showed reduced LV ejection fraction (LVEF) and fractional shortening (FS), with LVEF and FS values of 39.47±1.49% and 19.75±2.38%, respectively. Meanwhile, healthy animals showed LVEF and FS values of (63.75±2.38% and 36.20±1.29% (p<0.001). Four weeks after the UTMD delivery of the S100A6, LVEF increased to 51.14±3.7% and FS increased to 29.66±3.2% (p<0.05). In contrast, the empty minicircle and control groups showed no significant improvement (38.35±2.6% and 20.66±5.2%, p<0.05). The S100A6-treated group at 28 days post-treatment showed a 2.7±1.2-fold increase in the expression level of S100A6 in the border zones. Interestingly, the peri-infarct zone of S100A6-treated myocardium also had a lower expression level of the hypertrophic marker, β-MHC (0.77±0.7-fold), as compared to those of the control groups (2.48±1.63-fold). S100A6 transfection reduced infarct size (24.75±3.3%); vs control (36±4.58%), p<0.05 and decreased collagen content in viable myocardium compared to the control and empty minicircle group, p<0.01. Conclusion: S100A6 overexpression in the peri-infarct zone decreased both hypertrophy and fibrosis and was beneficial to the preservation of cardiac function in a model of chronic MI.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.238
Teacher spread0.226 · 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 designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

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