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Record W4402494409 · doi:10.1101/2024.09.11.612516

flt1 inactivation promotes zebrafish cardiac regeneration by enhancing endothelial activity and limiting the fibrotic response

2024· preprint· en· W4402494409 on OpenAlexaff
Zhenyu Wang, Armaan Mehra, Quian-Chen Wang, Savita Gupta, Agatha Ribeiro da Silva, Thomas Juan, Stephan Günther, Jan Detleffsen, Mario Looso, Didier Y. R. Stainier, Rubén Marín‐Juez

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicCoronary Artery Anomalies
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsZebrafishLimitingRegeneration (biology)Cell biologyFibrosisChemistryBiologyMedicineInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

VEGFA administration has been explored as a pro-angiogenic therapy for cardiovascular diseases including heart failure for several years, but with little success. Here we investigate a different approach to augment VEGFA bioavailability: by deleting the VEGFA decoy receptor VEGFR1/FLT1, one can achieve more physiological VEGFA concentrations. We find that following cryoinjury, zebrafish flt1 mutant hearts display enhanced coronary revascularization and endocardial expansion, increased cardiomyocyte dedifferentiation and proliferation, and decreased scarring. Suppressing Vegfa signaling in flt1 mutants abrogates these beneficial effects of flt1 deletion. Transcriptomic analyses of cryoinjured flt1 mutant hearts reveal enhanced endothelial MAPK/ERK signaling and downregulation of the transcription factor gene egr3 . Using newly generated genetic tools, we observe egr3 upregulation in the regenerating endocardium, and find that Egr3 promotes myofibroblast differentiation. These data indicate that with enhanced Vegfa bioavailability, the endocardium limits myofibroblast differentiation via egr3 downregulation, thereby providing a more permissive microenvironment for cardiomyocyte replenishment after injury.

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)0.001
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 score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.220
Teacher spread0.210 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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