MétaCan
Menu
Back to cohort
Record W2886327955 · doi:10.1002/cm.21485

Regulation of mechanotransduction: Emerging roles for septins

2018· review· en· W2886327955 on OpenAlexfundno aff
Maxine Lam, Fernando Calvo

Bibliographic record

VenueCytoskeleton · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsnot available
FundersInstitute of Cancer ResearchMinisterio de Economía y CompetitividadCancer Research UK
KeywordsMechanotransductionBiologySeptinCell biologyExtracellular matrixHomeostasisCytokinesisCytoskeletonCellCell divisionGenetics

Abstract

fetched live from OpenAlex

Cells exist in dynamic three-dimensional environments where they experience variable mechanical forces due to their interaction with the extracellular matrix, neighbouring cells and physical stresses. The ability to constantly and rapidly alter cellular behaviour in response to the mechanical environment is therefore crucial for cell viability, tissue development and homeostasis. Mechanotransduction is the process whereby cells translate mechanical inputs into biochemical signals. These signals in turn adjust cell morphology and cellular functions as diverse as proliferation, differentiation, migration and apoptosis. Here, we provide an overview of the current understanding of mechanotransduction and how septins may participate in it, drawing on their architecture and localization, their ability to directly bind and modify actomyosin networks and membranes, and their associations with the nuclear envelope.

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.032
GPT teacher head0.333
Teacher spread0.302 · 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

Citations45
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCytoskeletonSame topicCellular Mechanics and InteractionsFrench-language works237,207