Plasma membranes are poised for activation of raft phase coalescence at physiological temperature
Bibliographic record
Abstract
Cell membranes are not randomly organized, but rather are populated by fluctuating nanoassemblies of increased translational order termed lipid rafts. This lateral heterogeneity can be biophysically extended because cooling formaldehyde-isolated plasma membrane preparations results in separation into phases similar to the liquid-ordered (Lo) and liquid-disordered (Ld) states seen in model membrane systems [Baumgart T, et al. (2007) Proc Natl Acad Sci USA 104:3165-3170]. In this work we demonstrate that raft clustering, i.e., amplifying underlying raft-based connectivity to a larger scale, makes an analogous capacity accessible at 37 degrees C. In plasma membranes at this temperature, cholera toxin-mediated cross-linking of the raft ganglioside GM1 induced the sterol-dependent emergence of a slower diffusing micrometer-scale phase that was enriched in cholesterol and selectively reorganized the lateral distribution of membrane proteins. Although parallels can be drawn, we argue that this raft coalescence in a complex biological matrix cannot be explained by only those interactions that define Lo formation in model membranes. Under this light, our induction of raft-phase separation suggests that plasma membrane composition is poised for selective and functional raft clustering at physiologically relevant temperature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".