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Record W1948304460 · doi:10.1111/nyas.12883

Mitochondrial dynamics regulating chemoresistance in gynecological cancers

2015· review· en· W1948304460 on OpenAlexafffund
Bao Kong, Hideaki Tsuyoshi, Makoto Orisaka, Dar‐Bin Shieh, Yoshio Yoshida, Benjamin K. Tsang

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchMinistry of Science and Technology, Taiwan
KeywordsFIS1Mitochondrial fissionApoptosisMitochondrionCancer researchmitochondrial fusionCancer cellProgrammed cell deathBiologyCancerTumor microenvironmentCell biologyTumor cellsMitochondrial DNAGeneticsGene

Abstract

fetched live from OpenAlex

Chemoresistance enables cancer cells to evade apoptotic stimuli and leads to poor clinical prognosis. It arises from dysregulation of signaling factors responsible for inducing cell proliferation and death and for modulating the microenvironment. In gynecologic cancers, p53 is a pivotal determinant of cisplatin sensitivity, while BCL-2 family members are associated with taxane sensitivity. Mitochondria fusion and fission dynamics are required for many mitochondrial functions and are also involved in mitochondria-mediated apoptosis, which is closely associated with chemosensitivity. Mitochondrial dynamics are controlled by a number of intracellular proteins, including fusion (Opa1 and mitofusion 1 and 2) and fission proteins (Drp1 and Fis1), which can be proapoptotic or antiapoptotic, depending on the cell types, status, and stimuli from the microenvironment. This paper describes the role of mitochondrial dynamics in the mechanism of chemoresistance and the evidence supporting a significant contribution of a hyperfusion state to chemoresistance in gynecological cancers. Moreover, we discuss our findings showing that enforced fission induces apoptosis of cancer cells and sensitizes them to chemotherapeutic agents. Understanding the regulation of mitochondrial dynamics in chemoresistance may provide insight into new biomarkers that better predict cancer chemosensitivity and may aid the development of effective therapeutic strategies for clinical management of gynecologic cancers.

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 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 score0.786
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.123
GPT teacher head0.379
Teacher spread0.256 · 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.

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

Citations81
Published2015
Admission routes2
Has abstractyes

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