Influence of Nanoparticle Inhalation on Cardiac Mitochondrial Function
Bibliographic record
Abstract
Particle inhalation affects directly contacted tissues. Nanoparticles may elicit more robust effects due to their greater surface area. However, the effects to extrapulmonary tissues, such as the heart, are unclear. Mitochondria play a critical role in cardiac function and may be negatively influenced by particulate exposure. Cardiac mitochondria are situated in a spatially distinct manner, with those between the myofibrils (IFM) and those beneath the sarcolemma (SSM). The goal of this study was to determine the effect of titanium dioxide (nano‐TiO2) inhalation on mitochondrial function. Sprague‐Dawley rats were exposed to nano‐TiO2 aerosols (CMAD=140–150 nm) at 4–5 mg/m3; for 4–6 hrs to achieve a pulmonary deposition of 30 ìg/rat. Twenty‐four hours later, echocardiography revealed a decrease in cardiac ejection fraction. Mitochondrial functional analyses indicated a decrease in electron transport chain complex III, IV, and V activities, with the IFM most affected (P<0.05, for all three). Lipid peroxidation and protein carbonyl contents were increased in exposed IFM, as compared to control. Caspase 3 and 9 activities were increased in exposed hearts with no effect on caspase 8 activity. The results suggest that nanoparticle inhalation is associated with cardiac mitochondrial damage which may be subject to subcellular spatial influence. (Support: NIH DP2DK083095, 5T32HL090610, ES015022 , ES018274 )
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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 | 0.000 |
| 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) | 0.001 | 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".