Neutron Scattering at the Intersection of Heart Health Science and Biophysics
Bibliographic record
Abstract
There is an urgent quest for improved heart health. Here, we review how neutron radiation can provide insight into the molecular basis of heart health. Lower cholesterol, a daily intake of aspirin and supplemental vitamin E are argued to all improve heart health. However, the mechanisms behind these common regimens, and others, are not entirely understood. It is not clear why a daily intake of aspirin can help some people with heart disease, and the benefits of vitamin E in the treatment of reperfusion injury have been heavily debated. The molecular impact of cholesterol in the body is still a hot topic. Neutron scattering experiments present a unique opportunity for biophysicists attempting to address these problems. We review some recently published studies that are advancing our understanding of how cholesterol, vitamin E and aspirin work at the molecular level, by studying the impact of these molecules on the cell membrane. These insights engage the broader health science community with new ways of thinking about these 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".