Abstract MP233: Investigating Genotoxic-induced Innate Immune Pathways Leading To Heart Failure With Preserved Ejection Fraction For Developing Effective Treatments
Bibliographic record
Abstract
Background: A hallmark of heart failure pathologies is excessive and cumulative DNA damage, leading to an increased and accelerated cardiac cellular senescence. We aimed to investigate the role of DNA breaks in inducing inflammation leading to adverse remodeling, premature senescence, and cardiac dysfunction leading to onset of Heart Failure with preserved Ejection Fraction (HFpEF), a specific type of disease prevalent in the aging population. Results: We use heart-focused ionizing radiation, a novel in vivo technique to induce aging related DNA damage and onset of diastolic dysfunction and HFpEF (n= 4-5 per group & per species; animals used: Rattus norvegicus and Mus musculus). We performed functional analysis, histological tissue assessment and molecular investigations to evaluate and validate this novel animal model technique. DNA damage response is upregulated in aging-related Heart Failure, and here demonstrated in our novel heart-focused radiation technique. Using in vitro ionizing radiation exposure alters cardiomyocyte morphology and activates inflammation, leading to upregulation of fibrosis and senescence markers. Finally using experimental inhibitor compounds targeting the cGAS-STING axis of innate immunity, we show effective attenuation of this relevant pathway, leading to decreased systemic inflammation, cardiomyocyte remodeling, and senescence associated with DNA damage injury. Conclusions: We present a novel technique to induce genotoxic outcomes and inflammation of the heart, leading to HFpEF pathology. We elucidate novel connections from the onset and accumulation of unresolved DNA damage, to activation of specialized innate immune cellular responses, and ultimately upregulation of cardiac tissue specific inflammation, fibrosis and senescence. Finally we demonstrate that antagonizing the cGAS-STING pathway could allow a precision medicine approach to treating genotoxic and inflammatory HFpEF.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".