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Record W2011563930 · doi:10.1196/annals.1391.027

Membrane Regulation of the Stress Response from Prokaryotic Models to Mammalian Cells

2007· review· en· W2011563930 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMembrane fluidityMembraneMembrane proteinCell biologyChemistryMembrane lipidsBiophysicsRaftLipid raftSignal transductionOxidative stressMembrane potentialBiologyBiochemistry

Abstract

fetched live from OpenAlex

"Membrane regulation" of stress responses in various systems is widely studied. In poikilotherms, membrane rigidification could be the first reaction to cold perception: reducing membrane fluidity of membranes at physiological temperatures is coupled with enhanced cold inducibility of a number of genes, including desaturases (see J.L. Harwood's article in this Proceedings volume). A similar role of changes in membrane physical state in heat (oxidative stress, etc.) sensing- and signaling gained support recently from prokaryotes to mammalian cells. Stress-induced remodeling of membrane lipids could influence generation, transduction, and deactivation of stress signals, either through global effects on the fluidity of the membrane matrix, or by specific interactions of boundary (or raft) lipids with receptor proteins, lipases, ion channels, etc. Our data point to membranes not only as targets of stress, but also as sensors in activating a stress response.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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: Review · Consensus signal: Review
Teacher disagreement score0.150
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
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 head0.127
GPT teacher head0.366
Teacher spread0.239 · 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