Lateral Distribution of a Poly(ethylene glycol)-Grafted Phospholipid in Phosphocholine Monolayers Studied by Epifluorescence Microscopy
Bibliographic record
Abstract
Mixed monolayers of distearoylphosphatidylcholine (DSPC) and a poly(ethylene glycol)-(PEG)-grafted distearoylphosphatidylethanolamine with a PEG molecular weight of 2000, DSPE-PEG2000, spread on phosphate-buffered saline (PBS) were used as models of bio-non-fouling membrane-mimetic surfaces in order to visualize the lateral distribution of PEG2000-phospholipid in the host phospholipid matrix. Epifluorescence microscopy (EFM) was used to locate DSPE-PEG2000 molecules in the DSPC matrix by detecting the fluorescence from a fluorescein fluorophore attached to the distal end of the PEG2000 chain. Comparative analysis of surface pressure-area isotherms and EFM images revealed that DSPE-PEG2000 mixes nonideally with DSPC in monolayers on a PBS subphase. A transition from a phase-separated monolayer to a homogeneous mixture was observed with increasing surface pressure and PEG content. The effect of nonideal mixing behavior of DSPE-PEG2000 on its lateral distribution in the DSPC matrix was interpreted in terms of excluded volume interactions between the PEG2000 chains and a mismatch in the tilt of aliphatic chains on DSPC and DSPE-PEG2000 molecules.
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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 | 0.001 |
| 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".