Metabolic regulation of neutrophil functions in homeostasis and diseases
Bibliographic record
Abstract
Neutrophils are the most abundant leukocytes in humans and play a role in the innate immune response by being the first cells attracted to the site of infection. While early studies presented neutrophils as almost exclusively glycolytic cells, recent advances show that these cells use several metabolic pathways other than glycolysis, such as the pentose phosphate pathway, oxidative phosphorylation, fatty acid oxidation, and glutaminolysis, which they modulate to perform their functions. Metabolism shifts from fatty acid oxidation-mediated mitochondrial respiration in immature neutrophils to glycolysis in mature neutrophils. Tissue environments largely influence neutrophil metabolism according to nutrient sources, inflammatory mediators, and oxygen availability. Inhibition of metabolic pathways in neutrophils results in impairment of certain effector functions, such as NETosis, chemotaxis, degranulation, and reactive oxygen species generation. Alteration of these neutrophil functions is implicated in certain human diseases, such as antiphospholipid syndrome, coronavirus disease 2019, and bronchiectasis. Metabolic regulators such as AMPK, HIF-1α, mTOR, and Arf6 are linked to neutrophil metabolism and function and could potentially be targeted for the treatment of diseases associated with neutrophil dysfunction. This review details the effects of alterations in neutrophil metabolism on the effector functions of these cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".