Ganglioside Partitioning and Aggregation in Phase-Separated Monolayers Characterized by Bodipy GM1 Monomer/Dimer Emission
Bibliographic record
Abstract
The distribution of Bodipy GM1 in monolayers of binary and ternary lipid mixtures with coexisting fluid and ordered phases has been examined using a combination of atomic force microscopy and near-field scanning optical microscopy. Monolayers deposited at high (30 mN/m) and low (5 or 10 mN/m) surface pressures were examined and compared to those containing the same concentration of unlabeled ganglioside. Measurements of monomer and dimer Bodipy emission were used to distinguish aggregated from dilute ganglioside levels. For binary DPPC/DOPC monolayers, Bodipy GM1 is distributed throughout both the fluid and ordered phases at low surface pressures, and both labeled and unlabeled gangliosides result in a reduction in the size of ordered DPPC domains at 0.4% and the appearance of small aligned ganglioside-rich domains at 4%. In agreement with earlier studies, GM1 is heterogeneously distributed in small islands in the condensed DPPC domains at high surface pressure. By contrast, Bodipy GM1 causes the disappearance of large DPPC domains at 0.4% and the formation of a new GM1-rich phase at 4%. The addition of both gangliosides leads to a comparable loss of large ordered domains at low surface pressure and the appearance of a new GM1-rich phase at 30 mN/m for ternary lipid mixtures containing cholesterol. The results demonstrate the complexity of GM1 partitioning and illustrate the utility of complementary AFM and high spatial resolution two-color fluorescence experiments for understanding Bodipy GM1 aggregation and distribution.
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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".