Single-cell transcriptomics reveals subset-specific metabolic profiles underpinning the bronchial epithelial response to flagellin
Bibliographic record
Abstract
Airway epithelial cells represent the first line of defense against respiratory pathogens. Flagellin drives the motility of many mucosal pathogens and has been suggested as an immune enhancing adjunctive therapeutic in infections of the airways. This study leveraged single-cell RNA sequencing to determine cell-specific effects of flagellin in primary human bronchial epithelial cells growing in air-liquid interface. Seven cell clusters were identified, including ciliated cells, ionocytes, and several states of basal and secretory cells, of which only inflammatory basal cells and inflammatory secretory cells demonstrated a proportional increase in response to flagellin. Inflammatory secretory cells showed evidence of metabolic reprogramming toward aerobic glycolysis, while in inflammatory basal cells transcriptome profiles indicated enhanced oxidative phosphorylation. Inhibition of mTOR prevented the shift to glycolysis and reduced inflammatory gene transcription specifically in inflammatory secretory cells. These data demonstrate the functional heterogeneity of the human airway epithelium upon exposure to flagellin.
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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".