Modeling and simulation of crossing magnetic nanoparticles through Blood Brain Barrier (BBB)
Bibliographic record
Abstract
Crossing the Blood Brain Barrier (BBB), despite its tight junctions, is of the great importance in a plethora of medical applications. As a result, this work is dedicated to molecular dynamics (MD) simulation of crossing through the BBB particularly under the effect of magnetic force. For this purpose, two cases of a coated gold nanocparticle with insulin and uncoated gold nanoparticle have been considered; there, the dominant governing parameters in each case are changed to identify the optimized condition for crossing nanoparticles. These parameters are of biological (ligand-receptor binding affinity), biophysical (membrane surface receptor density ratio and non-specific interaction parameter) or geometrical (size of components) origin. The most important part of this study is MD simulation of nanoparticles under the effect of magnetic field and the result shows that for crossing through BBB what force profile must be provided by the magnetic field.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".