MétaCan
Menu
Back to cohort
Record W4312698804 · doi:10.7554/elife.77014.sa2

Author response: Mettl3-mediated m6A modification of Fgf16 restricts cardiomyocyte proliferation during heart regeneration

2022· peer-review· en· W4312698804 on OpenAlexaff
Fu-Qing Jiang, Kun Liu, Jiaxuan Chen, Yan Cao, Wu-Yun Chen, Wan-Ling Zhao, Guohua Song, Chi-Qian Liang, Yi-Min Zhou, Huanlei Huang, Ruijin Huang, Hui Zhao, Kyu‐Sang Park, Zhenyu Ju, Dongqing Cai, Xufeng Qi

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsRegeneration (biology)Cell biologyBiology

Abstract

fetched live from OpenAlex

Cardiovascular diseases are one of the world’s biggest killers. Even for patients who survive a heart attack, recovery can be difficult. This is because – unlike some amphibians and fish – humans lack the ability to produce enough new heart muscle cells to replace damaged tissue after a heart injury. In other words, the human heart cannot repair itself. Molecules known as messenger RNA (mRNA) carry the ‘instructions’ from the DNA inside the cell nucleus to its protein-making machinery in the cytoplasm of the cell. These messenger molecules can also be altered by different enzymes that attach or remove chemical groups. These modifications can change the stability of the mRNA, or even ‘silence’ it altogether by stopping it from interacting with the protein-making machinery, thus halting production of the protein it encodes. For example, a protein called Mettl3 can attach a methyl group to a specific part of the mRNA, causing a reversible mRNA modification known as m6A. This type of alteration has been shown to play a role in many conditions, including heart disease, but it has been unclear whether m6A could also be important for the regeneration of heart tissue. To find out more, Jiang, Liu, Chen et al. studied heart injury in mice of various ages. Newborn mice can regenerate their heart muscle for a short time, but adult mice lack this ability, which makes them a useful model to study heart disease. Analyses of the proteins and mRNAs in mouse heart cells confirmed that both Mettl3 and m6A-modified mRNAs were present. The amount of each also increased with age. Next, experiments in genetically manipulated mice revealed that removing Mettl3 greatly improved tissue repair after heart injury in both newborn and adult mice. In contrast, mouse hearts that produced abnormally high quantities of Mettl3 were unable to regenerate – even if the mice were young. Moreover, a detailed analysis of gene activity revealed that Mettl3 was suppressing heart regeneration by decreasing the production of a growth-promoting protein called FGF16. These results reveal a key biological mechanism controlling the heart’s ability to repair itself after injury. In the future, Jiang et al. hope that Mettl3 can be harnessed for new, effective therapies to promote heart regeneration in patients suffering from heart disease.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.188
Threshold uncertainty score0.628

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.1880.064

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 head0.040
GPT teacher head0.328
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicRNA modifications and cancerFrench-language works237,207