Molecular Dynamics Simulation of a Model Brain Membrane with and without a 14-3-3 tau Protein
Bibliographic record
Abstract
Abstract An unbalanced composition of lipids and proteins in brain membranes is related to the appearance neurodegenrative diseases and recent investigations show that the 14-3-3 tau protein might relate to some of these diseases. This article reports results from a coarse-grained model brain membrane with and without a 14-3-3 τ/θ protein inside the membrane. We investigated the symmetrized partial density, thickness, diffusion coefficients, and deuterium order parameters of the membrane with and without protein. We observe a slight increase in heads and linkers in the symmetrized partial density of the membrane with the protein inserted and higher values of the deuterium order parameters for the brain model membrane with protein. We observe a reduction in the diffusion coefficient of the fluid membrane in the presence of the transmembrane tau protein. Our findings show that the protein can modify the structural and dynamical properties of the membrane. This work will serve as a guide for future investigations on the interactions of tau proteins with brain membrane models and their relation to neurodegenerative diseases.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".