Heart‐on‐a‐Chip Platform for Assessing Toxicity of Air Pollution Related Nanoparticles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Accumulating evidence indicates that air pollution contributes to serious and fatal damage to the cardiovascular system, yet the mechanisms that drive air pollution associated cardiovascular disease and dysfunction remain unclear. In an effort to create a more predictive in vitro model, a 3D platform, known as integrated vasculature for assessing dynamic events is used, that supports the combination of dense human induced pluripotent stem cell derived cardiac tissue and vascular interface, to unravel the impact of nanoscale air pollution on endothelial cells and cardiac tissue. Air pollution relevant nanoparticles (CuO, SiO 2 ) and a control (Au) are used to predict the toxic effects on the cardiovascular system under perfusion. It is demonstrated that CuO nanoparticles are highly toxic, as they are able to translocate into the cardiac tissue and induce electrical and contractile dysfunction through generation of reactive oxygen species and subsequently lead to disruption of cardiac troponin T and secretion of biomarkers associated with cardiac injury (B‐type natriuretic peptide, N‐terminated pro‐hormone BNP, and Troponin I). SiO 2 , on the other hand, causes the secretion of pro‐inflammatory cytokines, and modulates the intracellular Ca 2+ handling. This microengineering approach may offer new opportunities to more accurately model cardiovascular responses to nm‐sized air pollution.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 it