Fluorescence-quenching and resonance energy transfer studies of lipid microdomains in model and biological membranes (Review)
Bibliographic record
Abstract
Measurements of contact-dependent fluorescence quenching and of fluorescence resonance energy transfer (FRET) within bilayers provide information concerning the spatial relationships between molecules on distance scales of a few nm or up a few tens of nm, respectively, and are therefore well suited to detect the presence and composition of membrane microdomains. As described in this review, techniques based on fluorescence quenching and FRET have been used to demonstrate the formation of nanoscale liquid-ordered domains in cholesterol-containing model membranes under physiological conditions, and to investigate the structural features of lipids and proteins that influence their partitioning between liquid-ordered and liquid-disordered domains. FRET-based methods have also been used to test for the presence of 'raft' microdomains in the plasma membranes of mammalian cells. We discuss the sometimes divergent findings of these studies, possible modifications to the 'raft hypothesis' suggested by studies using FRET and other techniques, and the further potential of FRET-based methods to test and to refine current models of the nature and organization of membrane microdomains.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".