PFKFB2‐Driven Glycolysis Promotes Dendritic Cell Maturation and Exacerbates Acute Lung Injury
Bibliographic record
Abstract
Acute lung injury (ALI) is a life-threatening condition with excessive immune activation and dysregulated inflammation. Dendritic cells (DCs) play a pivotal role in immune regulation; however, their exact contribution to ALI pathogenesis remains unclear. This study demonstrates that the upregulation of the glycolytic regulator 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 2 (PFKFB2) by hypoxia-inducible factor-1α (HIF-1α) enhances glycolysis, drives DC maturation, and exacerbates inflammation, contributing to the pathogenesis of ALI. The findings reveal that HIF-1α directly binds to the PFKFB2 promoter and drives its transcription, leading to increased glycolysis, accelerated DC maturation, and amplified immune activation. In paraquat (PQ)-ALI and lipopolysaccharide (LPS)-ALI mouse models, DC-specific PFKFB2 knockout and DC-targeted delivery of HIF-1α inhibitor-loaded nanoparticles each significantly suppressed DC maturation and alleviated ALI severity. Analyses of lung tissues from patients with PQ poisoning, secondary bacterial pneumonia (2°BP), and Coronavirus Disease 2019 (COVID-19), as well as from normal controls, confirmed these findings, showing increased PFKFB2 expression and DC maturation during ALI. These findings highlight the HIF-1α-PFKFB2 signaling pathway as a critical regulator of glycolysis-driven DC maturation and immune activation, offering novel insights into immunometabolic regulation and a promising therapeutic target for ALI.
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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) | 0.001 | 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".