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Osmotic stress and the cytoskeleton: the R(h)ole of Rho GTPases

2006· review· en· W2099091461 on OpenAlexaff
Caterina Di Ciano‐Oliveira, Ana C.P. Thirone, Katalin Szászi, András Kapùs

Bibliographic record

VenueActa Physiologica · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsGTPaseCytoskeletonActin cytoskeletonCDC42Cell biologyContext (archaeology)ActinBiologyOsmotic shockCellGenetics

Abstract

fetched live from OpenAlex

Hyperosmotic stress initiates a variety of compensatory and adaptive responses, which either serve to restore near-normal volume or remodel and reinforce the cell structure to withstand the physical challenge. The latter response is brought about by the reorganization of the cytoskeleton; however, the underlying mechanisms are not well understood. Recent research has provided major breakthroughs in our knowledge about the link between message and structure, i.e. between signalling and cytoskeletal remodelling, predominantly in the context of cell migration. The major components of this progress are the in-depth characterization of Rho family small GTPases, master regulators of the cytoskeleton, and the discovery of the actin-related protein 2/3 complex, a signalling-sensitive structural element of the actin polymerization machinery. The primary aim of this review is to find the place of these novel and crucial players in osmotically induced (volume-dependent) remodelling of the cytoskeleton. We aim to address three questions: (1) What are the major structural changes in the cytoskeleton under hyperosmotic conditions? (2) Are the Rho family small GTPases (Rho, Rac and Cdc42) regulated by osmotic stress, and if so, by what mechanisms? (3) Are Rho GTPases involved, as mediators, in major adaptive responses, including cytoskeleton rearrangement, changes in ion transport and genetic reprogramming? Our answers will show how fragmentary our current knowledge is in these areas. Therefore, this overview has been written with the hardly disguised intention that it might foster further research in this field by highlighting some intriguing questions.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
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 head0.019
GPT teacher head0.283
Teacher spread0.263 · 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

Citations96
Published2006
Admission routes1
Has abstractyes

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