Matrisome gene expression is altered during non-allometric heart growth in genetically enlarged <i>Drosophila</i>
Bibliographic record
Abstract
Abstract The cardiac extracellular matrix (ECM) is critical to defining the biophysical properties of the heart that adapt to changing stresses with growth or disease. The ECM is commonly dysregulated in chronic disease such as hypertension, diabetes, and cardiomyopathies, often leading to the development of fibrosis. There are no treatment options to address most ECM cardiomyopathies, but developing therapeutic targets necessitates an understanding of the regulation of ECM remodelling. Here, we employ a larval Drosophila overgrowth model (“giant larvae”) to overload the heart and alter ECM remodelling in vivo . These larvae grow to immense sizes without exhibiting hallmarks of obesity. Remarkably, cardiac ECM organization scales allometrically despite overload. The main effect observed is a change in Collagen fibril thickness, possibly reflecting changes to tension in the system. Overgrowth-induced changes in gene expression similarly suggest changes in Collagen assembly, such as a dramatic increase in LOXL2, the main Collagen crosslinking enzyme. This could indicate that larvae may compensate for the stress of overgrowth by stabilizing the Collagen network. The enlarged hearts of giant larvae cannot contract fully at systole. Taken together, this reveals non-allometric changes to cardiac form and output with increasing body size. Overall, our overgrowth model presents an intriguing opportunity to examine the ability of a system to tolerate overgrowth without the metabolic inputs of obesity.
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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) | 0.002 | 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".