Link between Fluorescent Probe Partitioning and Molecular Order of Liquid Ordered-Liquid Disordered Membranes
Bibliographic record
Abstract
Fluorescence microscopy is an important technique for studying lipid membranes and is increasingly being used for examining liquid ordered-liquid disordered phase coexistence. Liquid–liquid phase coexistence is a phenomenon of biological interest because it led to the lipid raft hypothesis, which postulates the existence of lateral heterogeneities in cell membranes. Observation of membrane heterogeneity relies on differential distribution of fluorescent membrane markers, but this can also modify the phase behavior, complicating the observation. We have used 2 H NMR to measure the physical changes to 35:35:30 (mol/mol) DOPC/DPPC-D62/chol membranes introduced by fluorescent probes Laurdan and naphthopyrene. We measured miscibility transition temperature ( T mix ) and DPPC-D62 chain order for a range of probe concentrations. We found that up to 0.5 mol% of the equipartitioning probe Laurdan does not influence DPPC-D62 acyl chain order or phase behavior. In contrast, 2.0 mol% Laurdan slightly increases the fraction of DPPC-D62 in the liquid disordered phase below the T mix and increases T mix by 1 °C. Conversely, the nominally liquid ordered phase preferring probe naphthopyrene slightly perturbs the membrane even at concentrations as low as 0.3 mol%. This suggests that the strength of fluorescent probe partitioning between liquid ordered and liquid disordered phases correlates with the degree of perturbation to membrane phase behavior.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".