Interaction of DNA with Cationic Lipid Mixtures—Investigation at Langmuir Lipid Monolayers
Bibliographic record
Abstract
Four different binary lipid mixtures composed of a cationic lipid and the zwitterionic colipids DOPE or DPPC, which show different DNA transfer activities in cell culture models, were investigated at the soft air/water interface to identify transfection efficiency determining characteristics. Langmuir films are useful models to investigate the interaction between DNA and lipid mixtures in a two-dimensional model system by using different surface sensitive techniques, namely, epifluorescence microscopy and infrared reflection-absorption spectroscopy. Especially, the effect of adsorbed DNA on the properties of the lipid mixtures has been examined. Distinct differences between the lipid composites were found which are caused by the different colipids of the mixtures. DOPE containing lipid mixtures form fluid monolayers with a uniform distribution of the fluorescent probe in the presence and absence of DNA at physiologically relevant surface pressures. Only at high nonphysiological pressures, the lipid monolayer collapses and phase separation was observed if DNA was present in the subphase. In contrast, DPPC containing lipid mixtures show domains in the liquid condensed phase state in the presence and absence of DNA in the subphase. The adsorption of DNA at the positively charged mixed lipid monolayer induces phase separation which is expressed in the morphology and the point of appearance of these domains.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".