Singlet Oxygen Flux, Associated Lipid Photooxidation, and Membrane Expansion Dynamics Visualized on Giant Unilamellar Vesicles
Bibliographic record
Abstract
The physical properties of lipid membranes depend on their lipid composition. Photosensitized singlet oxygen ( 1 O 2 ) provides a handle to spatiotemporally control the generation of lipid hydroperoxides via the ene reaction, enabling fundamental studies on membrane dynamics in response to chemical composition changes. Critical to relating the physical properties of the lipid membrane to hydroperoxide formation is the availability of a sensitive reporter to quantify the arrival of 1 O 2 . Here, we show that a fluorogenic α-tocopherol analogue, H 4 BPMHC, undergoes a >360-fold emission intensity enhancement in liposomes following a reaction with 1 O 2 . Rapid quenching of 1 O 2 by the probe ( k q = 4.9 × 10 8 M –1 s –1 ) ensures zero-order kinetics of probe consumption. The remarkable intensity enhancement of H 4 BPMHC upon 1 O 2 trapping, its linear temporal behavior, and its protective role in outcompeting membrane damage provide a sensitive and reliable method to quantify the 1 O 2 flux on lipid membranes. Armed with this probe, fluorescence microscopy studies were devised to enable (i) monitoring the flux of photosensitized 1 O 2 into giant unilamellar vesicles (GUVs), (ii) establishing the onset of the ene reaction with the double bonds of monounsaturated lipids, and (iii) visualizing the ensuing collective membrane expansion dynamics associated with molecular changes in the lipid structure upon hydroperoxide formation. A correlation was observed between the time for antioxidant H 4 BPMHC consumption by 1 O 2 and the onset of membrane fluctuations and surface expansion. Together, our imaging studies with H 4 BPMHC in GUVs provide a methodology to explore the intimate relationship between photosensitizer activity, chemical insult, membrane morphology, and its collective dynamics.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".