Cigarette whole smoke solutions disturb mucin homeostasis in a human in vitro airway tissue model
Bibliographic record
Abstract
Many cigarette smoke-associated airway diseases involve alterations in mucin homeostasis. With the rationale that relevant tissue responses can be measured to evaluate the adverse health effects of tobacco products, we assessed changes in mucin secretion and the density and size of goblet cells in an in vitro human air-liquid-interface (ALI) airway tissue model after exposure to a tobacco smoke solution. Cultures were exposed daily for up to five consecutive days to a whole smoke solution (WSS) prepared by machine smoking Marlboro Red or Marlboro Silver cigarettes using the Canadian Intense (CI) protocol. Both WSSs induced concentration- and time-related hypersecretion of mucins 5AC and 5B, accompanied by up-regulation of the respective mucin genes. Mucin secretion returned to baseline levels following a 14-day recovery period. Mucin-secreting goblet cells exhibited increased cell density and decreased size after 5 daily treatments then recovered to their normal size, but with decreased cell density, 14 days after the last treatment. The beating frequency of ciliated cells, which plays a key role in mucociliary clearance, was increased by 5 daily treatments with the CI WSSs then reverted to baseline levels following a 7-day recovery. Taken together, our results indicate that ALI cultures can be used to measure the modulation of mucin production, secretion, and clearance, disturbances that are manifested in tobacco smoke-related diseases, such as chronic obstructive pulmonary disease. Measuring tissue responses directly relevant to the respiratory toxicity of cigarette smoke may provide useful information in support of science-based regulatory decisions.
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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 | 0.000 |
| 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 | 0.001 |
| 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".