Elucidation of the mechanism and energy barrier for anesthetic triggered membrane fusion in model membranes
Bibliographic record
Abstract
Membrane fusion is vital for cellular function and is generally mediated via fusogenic proteins and peptides. The mechanistic details and subsequently the transition state dynamics of membrane fusion will be dependent on the type of the fusogenic agent. We have previously established the potential of general anesthetics as a new class of fusion triggering agents in model membranes. We employed two-photon excitation fluorescence cross-correlation spectroscopy (TPE-FCCS) to report on vesicle association kinetics and steady-state fluorescence dequenching assays to monitor lipid mixing kinetics. Using halothane to trigger fusion in 110 nm diameter dioleoylphosphatidylcholine (DOPC) liposomes, we found that lipid rearrangement towards the formation of the fusion stalk was rate limiting. The activation barrier for halothane induced membrane fusion in 110 nm vesicles was found to be ∼40 kJ mol−1. We calculated the enthalpy and entropy of the transition state to be ∼40 kJ mol−1 and ∼180 J mol−1 K−1, respectively. We have found that the addition of halothane effectively lowers the energy barrier for membrane fusion in less curved vesicles largely due to entropic advantages.
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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 | 0.000 |
| 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".