Cigarette smoke increases TLR4 and TLR9 expression and induces cytokine production from CD8+T cells in chronic obstructive pulmonary disease
Bibliographic record
Abstract
BACKGROUND: Cigarette smoke is a major risk factor for chronic obstructive pulmonary disease (COPD), an inflammatory lung disorder. COPD is characterized by an increase in CD8(+) T cells within the central and peripheral airways. We hypothesized that the CD8(+) T cells in COPD patients have increased Toll-like receptor (TLR) expression compared to control subjects due to the exposure of cigarette smoke in the airways. METHODS: Endobronchial biopsies and peripheral blood were obtained from COPD patients and control subjects. TLR4 and TLR9 expression was assessed by immunostaining of lung tissue and flow cytometry of the peripheral blood. CD8(+) T cells isolated from peripheral blood were treated with or without cigarette smoke condensate (CSC) as well as TLR4 and TLR9 inhibitors. PCR and western blotting were used to determine TLR4 and TLR9 expression, while cytokine secretion from these cells was detected using electrochemiluminescence technology. RESULTS: No difference was observed in the overall expression of TLR4 and TLR9 in the lung tissue and peripheral blood of COPD patients compared to control subjects. However, COPD patients had increased TLR4 and TLR9 expression on lung CD8(+) T cells. Exposure of CD8(+) T cells to CSC resulted in an increase of TLR4 and TLR9 protein expression. CSC exposure also caused the activation of CD8(+) T cells, resulting in the production of IL-1β, IL-6, IL-10, IL-12p70, TNFα and IFNγ. Furthermore, inhibition of TLR4 or TLR9 significantly attenuated the production of TNFα and IL-10. CONCLUSIONS: Our results demonstrate increased expression of TLR4 and TLR9 on lung CD8(+) T cells in COPD. CD8(+) T cells exposed to CSC increased TLR4 and TLR9 levels and increased cytokine production. These results provide a new perspective on the role of CD8(+) T cells in COPD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".