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Record W4318923940 · doi:10.1042/bsr20220765

Role of calcium-sensor proteins in cell membrane repair

2023· review· en· W4318923940 on OpenAlexafffund
Ziwei Li, Gary S. Shaw

Bibliographic record

VenueBioscience Reports · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsWestern University
FundersHeart and Stroke Foundation of Canada
KeywordsExocytosisDysferlinCell biologyMembrane proteinEndocytosisCalciumCell membraneBiologyCellMembraneChemistryMuscular dystrophyBiochemistryGenetics

Abstract

fetched live from OpenAlex

Cell membrane repair is a critical process used to maintain cell integrity and survival from potentially lethal chemical, and mechanical membrane injury. Rapid increases in local calcium levels due to a membrane rupture have been widely accepted as a trigger for multiple membrane-resealing models that utilize exocytosis, endocytosis, patching, and shedding mechanisms. Calcium-sensor proteins, such as synaptotagmins (Syt), dysferlin, S100 proteins, and annexins, have all been identified to regulate, or participate in, multiple modes of membrane repair. Dysfunction of membrane repair from inefficiencies or genetic alterations in these proteins contributes to diseases such as muscular dystrophy (MD) and heart disease. The present review covers the role of some of the key calcium-sensor proteins and their involvement in membrane repair.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.031
GPT teacher head0.290
Teacher spread0.259 · 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

Citations16
Published2023
Admission routes2
Has abstractyes

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