Investigating the Alteration of Membrane Properties Caused by Doxorubicin: Application of Phospholipid Mono- and Bilayer Biomembrane Models
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide In this study, we examined the effects of doxorubicin (DOx) on DMPC monolayers formed at the air–water interface and bilayers formed at the gold-solution interface. Monolayer studies indicated DOx incorporation during compression. Polarization modulation infrared reflection absorption spectroscopy (PM-IRRAS) data showed limited interaction with DMPC polar headgroups. We also demonstrated that charged DOx molecules induce structural and functional modifications in zwitterionic DMPC-supported bilayers. Atomic force microscopy imaging showed an increase in the bilayer thickness and phase segregation with DOx. Electrochemical measurements supported this, revealing alterations in the dielectric properties of these films. PM-IRRAS studies of supported bilayers confirmed changes in lipid packing, specifically a decreased tilt angle of acyl chains in the presence of DOx, which correlated with elevated resistance observed via electrochemical impedance spectroscopy. Our findings demonstrate that DOx is inserted into the bilayer of zwitterionic DMPC (a membrane typical for healthy cells), causing its swelling and increasing its fluidity and barrier properties, contrasting with the predominant electrostatic interactions observed for cancer membrane models. These molecular-level insights are essential for advancing the development of effective anticancer therapies.
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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) | 0.001 | 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".