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Record W4311301274 · doi:10.1111/cbdd.14192

Protective effect of a mitochondria‐targeting peptide against paclitaxel‐induced peripheral neuropathy

2022· letter· en· W4311301274 on OpenAlexafffund
Kensaku Itoh, Megumi Shimoyama, Peter W. Schiller, Satoshi Toyama

Bibliographic record

VenueChemical Biology & Drug Design · 2022
Typeletter
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversité de MontréalMontreal Clinical Research Institute
FundersNational Institute on Drug AbuseJapan Society for the Promotion of ScienceCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsPaclitaxelPeripheral neuropathyMedicineChemotherapy-induced peripheral neuropathyPharmacologyChemotherapyMitochondrionConcomitantTetrapeptidePeripheralApoptosisCancerInternal medicinePeptideEndocrinologyChemistry

Abstract

fetched live from OpenAlex

Chemotherapy-induced peripheral neuropathy (CIPN) is a major side effect of several anticancer agents including paclitaxel, a chemotherapeutic drug widely used in cancer treatment. CIPN deteriorates patients' quality of life and compromises cancer treatment. Dysfunction or injury of mitochondria has been suggested to be involved in the induction of this neuropathy. SS-20 is a tetrapeptide that targets mitochondria and restores mitochondrial bioenergetics. This study was aimed to examine the protective effect of SS-20 against paclitaxel-induced peripheral neuropathy using a murine model. Repeated administration of paclitaxel to mice induced peripheral neuropathy as demonstrated by the presence of mechanical allodynia and the loss of intraepidermal nerve fibers in the hind paw. Concomitant administration of SS-20 protected against the development of the neuropathy. Our results suggest that SS-20 may be a drug candidate for the prevention of CIPN.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.289
Teacher spread0.269 · 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 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

Citations7
Published2022
Admission routes2
Has abstractyes

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