Structure and pH Dependence of Membranolytic Mechanisms by Truncated Oxidized Phospholipids
Bibliographic record
Abstract
Membrane lipid oxidation is a universal process that occurs in situations of oxidative stress and is encountered in numerous physiological and pathological situations. Oxidized truncated phospholipids make up a large part of the oxidation products and alter the membrane properties in a way that can lead to cell death. However, the underlying mechanisms are not well understood nor is it clear whether environmental factors, such as pH, can modulate these effects. Using model membranes, we investigate how individual lipid aldehydes and carboxylic acids with truncated acyl chains alter the membrane structure. Our data shows that lipid aldehydes and carboxylic acids have different permeabilization efficiencies towards molecules of varying charge and size and that ΔC9 truncated lipids are usually more efficient in permeabilizing membranes than ΔC5. In terms of physical mechanisms, the ΔC9 truncated lipid carboxylic acid induces permeabilization and membrane curvature in a pH-dependent fashion. This is explained by ionization-dependent exposure of the carboxyl group to the water-bilayer interface, which increases the intrinsic molecular curvature of the oxidized lipid. Conversely, ΔC9 truncated lipid aldehydes and nonionized carboxyls do not induce curved structures but are more efficient in increasing permeability toward larger molecules. We further show that truncated lipids can escape the bilayer and accumulate at interfaces, implying that they might act on neighboring cells. This study indicates that oxidized phospholipids with truncated acyl chains disrupt membrane structure, depending on their specific molecular structure and the pH of the environment, opening a possible route for the design of lipid nanoparticles with pH-dependent drug release.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".