Cardiomyocyte‐specific Srsf3 deletion reveals a mitochondrial regulatory role
Bibliographic record
Abstract
Serine-rich splicing factor 3 (SRSF3) was recently reported as being necessary to preserve RNA stability via an mTOR mechanism in a cardiac mouse model in adulthood. Here, we demonstrate the link between Srsf3 and mitochondrial integrity in an embryonic cardiomyocyte-specific Srsf3 conditional knockout (cKO) mouse model. Fifteen-day-old Srsf3 cKO mice showed dramatically reduced (below 50%) survival and reduced the left ventricular systolic performance, and histological analysis of these hearts revealed a significant increase in cardiomyocyte size, confirming the severe remodeling induced by Srsf3 deletion. RNA-seq analysis of the hearts of 5-day-old Srsf3 cKO mice revealed early changes in expression levels and alternative splicing of several transcripts related to mitochondrial integrity and oxidative phosphorylation. Likewise, the levels of several protein complexes of the electron transport chain decreased, and mitochondrial complex I-driven respiration of permeabilized cardiac muscle fibers from the left ventricle was impaired. Furthermore, transmission electron microscopy analysis showed disordered mitochondrial length and cristae structure. Together with its indispensable role in the physiological maintenance of mouse hearts, these results highlight the previously unrecognized function of Srsf3 in regulating the mitochondrial integrity.
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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) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".