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Record W4393276347 · doi:10.1101/2024.03.25.586620

Matrisome gene expression is altered during non-allometric heart growth in genetically enlarged <i>Drosophila</i>

2024· preprint· en· W4393276347 on OpenAlexaff
Rachel M. Andrews, J. Roger Jacobs

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAllometryDrosophila (subgenus)BiologyGene expressionGeneExpression (computer science)GeneticsEvolutionary biologyEcologyComputer science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.236
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.232
Teacher spread0.220 · 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 teacher head, not a consensus.

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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