Molecular Structures of Fluid Phosphatidylethanolamine Bilayers Obtained from Simulation-to-Experiment Comparisons and Experimental Scattering Density Profiles
Bibliographic record
Abstract
Following our previous efforts in determining the structures of commonly used PC, PG, and PS bilayers, we continue our studies of fully hydrated, fluid phase PE bilayers. The newly designed parsing scheme for PE bilayers was based on extensive MD simulations, and is utilized in the SDP analysis of both X-ray and neutron (contrast varied) scattering measurements. Obtained experimental scattering form factors are directly compared to our simulation results, and can serve as a benchmark for future developed force fields. Among the evaluated structural parameters, namely, area per lipid A, overall bilayer thickness DB, and hydrocarbon region thickness 2DC, the PE bilayer response to changing temperature is similar to previously studied bilayers with different headgroups. On the other hand, the reduced hydration of PE headgroups, as well as the strong hydrogen bonding between PE headgroups, dramatically affects lateral packing within the bilayer. Despite sharing the same glycerol backbone, a markedly smaller area per lipid distinguishes PE from other bilayers (i.e., PC, PG, and PS) studied to date. Overall, our data are consistent with the notion that lipid headgroups govern bilayer packing, while hydrocarbon chains dominate the bilayer's response to temperature changes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".