Impaired peroxisomal import in <i>Drosophila</i> hepatocyte-like cells induces cardiac dysfunction through the pro-inflammatory cytokine Upd3
Bibliographic record
Abstract
Abstract Age is a major risk factor for cardiovascular diseases. Currently, the non-autonomous regulation of age-related cardiac dysfunction is poorly understood. In the present study, we discover that age-dependent induction of cytokine unpaired 3 (Upd3) in Drosophila oenocytes (hepatocyte-like cells), due to a dampened peroxisomal import function, is the primary non-autonomous mechanism for elevated arrhythmicity in old hearts. We show that Upd3 is significantly up-regulated (52-fold) in aged oenocytes. Oenocyte-specific knockdown of Upd3 is sufficient to block aging-induced cardiac arrhythmia. We further show that the age-dependent induction of Upd3 is triggered by impaired peroxisomal import and elevated JNK signaling in aged oenocytes. Intriguingly, oenocyte-specific over-expression of Pex5 , the key peroxisomal import receptor, restores peroxisomal import, blocks age-related Upd3 induction, and alleviates aging- and paraquat-induced cardiac arrhythmicity. Thus, our studies identify an important role of the evolutionarily conserved pro-inflammatory cytokine signaling and hepatocyte-specific peroxisomal import in mediating non-autonomous regulation of cardiac aging.
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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".