Bronchial epithelial cells in asthma: Do they produce energy the right way?
Bibliographic record
Abstract
Introduction: To meet their energy demands, cells rely on glycolysis and mitochondrial respiration. Few studies evaluated the contribution of cell metabolism in asthma pathogenesis. For instance, some showed that Thelper-cells (Th2, Th17) undergo glycolytic shift to produce pro-inflammatory cytokines. Bronchial epithelial cells (BEC) are key contributors to asthma pathophysiology. In addition to altered barrier integrity, BEC release pro-inflammatory/pro-fibrotic factors and produce high amount of mucus. Some studies suggest that metabolic reprogramming might be occurring asthmatic BEC, but data remains limited. Objective: To evaluate the metabolic profile of BEC in asthma. Method: BEC were isolated from bronchial biopsies of mild and severe asthma as well as from non-asthmatic controls. Glycolytic and oxidative phosphorylation (OxPhos) profile were evaluated by conducting seahorse experiments. Proteins expression and activity of key enzymes in glycolysis and OxPhos pathways were then evaluated by Western blot. Results: Seahorse experiments showed that, in contrast to healthy control BEC, asthmatic cells have lower mitochondrial coupling efficiency and consume more oxygen in processes unrelated to mitochondria. Furthermore, asthmatic BEC are more glycolytic. These observations were supported by Western blots experiments where asthmatic BEC have a higher expression of enzymes favoring glycolysis such as HK2, PKM2, LDHA, PDK1 and phosphorylated PDH. Interestingly, these effects were more prominent in severe asthmatic cells. Conclusion: Severe asthmatic BEC harbor unique metabolic alterations that might fuel their altered phenotype, thus providing new therapeutic avenues to be considered in asthma treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".