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Record W4379384673 · doi:10.7150/ijbs.83348

The crosstalk between ferroptosis and mitochondrial dynamic regulatory networks

2023· review· en· W4379384673 on OpenAlexaff
Jie Li, Yuchen Jia, Yi-xuan Ding, Jian Bai, Feng Cao, Fei Li

Bibliographic record

VenueInternational Journal of Biological Sciences · 2023
Typereview
Languageen
FieldMedicine
TopicFerroptosis and cancer prognosis
Canadian institutionsPancreas Centre (Canada)
FundersBeijing Municipal Science and Technology CommissionCapital Medical UniversityNational Natural Science Foundation of China
KeywordsMitophagymitochondrial fusionMitochondrial fissionMitochondrionCell biologyCrosstalkBiologyOxidative stressProgrammed cell deathFunction (biology)Mitochondrial DNAApoptosisGeneticsAutophagyBiochemistryGene

Abstract

fetched live from OpenAlex

Ferroptosis is an iron-driven cell death modality characterized by iron accumulation and excessive lipid peroxidation. Ferroptosis is closely related to mitochondrial function, as indicated by studies showing that mitochondrial dysfunction and damage promote oxidative stress, which in turn induces ferroptosis. Mitochondria play crucial roles in cellular homeostasis, and abnormalities in their morphology and function are closely associated with the development of many diseases. Mitochondria are highly dynamic organelles, and their stability is maintained through a series of regulatory pathways. Mitochondrial homeostasis is dynamically regulated, mainly via key processes such as mitochondrial fission, mitochondrial fusion and mitophagy; however, mitochondrial processes are prone to dysregulation. Mitochondrial fission and fusion and mitophagy are intimately related to ferroptosis. Therefore, investigations into the dynamic regulation of mitochondrial processes during ferroptosis are important to provide a better understanding of the development of disease. In this paper, we systematically summarized changes in ferroptosis, mitochondrial fission and fusion and mitophagy to promote an in-depth understanding of the mechanism underlying ferroptosis and provide a corresponding reference for the treatment of related diseases.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.125
GPT teacher head0.420
Teacher spread0.295 · 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
GenreReview

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

Citations321
Published2023
Admission routes1
Has abstractyes

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Same venueInternational Journal of Biological SciencesSame topicFerroptosis and cancer prognosisFrench-language works237,207