Para‐tertiary butyl catechol (PTBC), an industrial antioxidant induces human platelet apoptosis
Bibliographic record
Abstract
The catecholic derivative para-tertiary butyl catechol (PTBC) is a conventional antioxidant and polymerization inhibitor, which exhibits melanocytotoxic effects and contact dermatitis often leading to occupational leucoderma or vitiligo. Although numerous industrial workers will be in constant exposure to PTBC and its chances of getting entry into blood are most expected, its effect on blood components is still undisclosed. As platelets play a prominent role in dermatitis, inflammation, and immunity, in this study we have evaluated the effect of PTBC on human platelets in vitro. Exposure of platelets to PTBC showed increased reactive oxygen species (ROS), intracellular calcium, cardiolipin oxidation, mitochondrial permeability transition pore (MPTP) formation, activation of caspases, phosphatidylserine (PS) externalization and decreased mitochondrial membrane potential. In addition, there was a significant decrease in cellular glutathione level, increased γ-glutamyltransferase (GGT) activity and cell death. These findings demonstrate that PTBC could induce toxic effects on blood components, which is often ignored field of research. Since dermal exposure of humans to toxic chemicals covers an important issue in various industries, there is a need of such work to understand and update the long-term toxicities induced by PTBC usage in industrial sectors and public domain.
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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".