Leptin Inhibits Neutrophil Apoptosis in Children via ERK/NF-κB-Dependent Pathways
Bibliographic record
Abstract
INTRODUCTION AND RATIONALE: Previous studies have shown that delayed neutrophil apoptosis is associated with chronic airway diseases. Leptin is an adipocyte-derived hormone that acts as a regulator of energy homeostasis and food intake. Emerging evidence suggests that leptin can regulate immune responses including the release of proinflammatory cytokines and protection of inflammatory cells from apoptosis. Serum leptin is increased during allergic reactions in the airways. However, the expression and function of leptin receptor in neutrophils isolated from children is not known. METHODS: Flow cytometry was used to detect leptin receptor expression in neutrophils isolated from allergic asthmatic (n = 14), allergic non asthmatic (n = 21), non allergic asthmatic (n = 7) and healthy children (n = 23); confocal laser scanning microscopy combined with immunofluorescence was performed to detect intracellular pool of leptin receptor; Annexin-V/PI staining and caspase 3 activity was used to determine neutrophil survival. Pharmacological inhibitors were utilized to understand the role of MAPK and NF-κB pathway in leptin-induced neutrophil survival. RESULTS AND CONCLUSION: A heterogeneous leptin receptor expression was observed on neutrophils isolated from children. Neutrophils isolated from healthy children expressed more leptin receptor than those from allergic asthmatic (P<0.05) but not allergic non-asthmatic (P>0.05) or non-allergic asthmatic children (n = 7, P>0.05). Neutrophils isolated from children express an intracellular pool of leptin receptor that was mobilized to the cell surface upon GM-CSF stimulation. Finally, leptin exhibited anti-apoptotic properties on neutrophils via NF-κB and MEK1/2 MAPK pathway. Collectively, our data suggest that leptin may enhance airway inflammation by promoting neutrophil survival.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".