Macrophage Responses to Environmental Stimuli During Homeostasis and Disease
Bibliographic record
Abstract
Work over the last 40 years has described macrophages as a heterogeneous population that serve as the frontline surveyors of tissue immunity. As a class, macrophages are found in almost every tissue in the body and as distinct populations within discrete microenvironments in any given tissue. During homeostasis, macrophages protect these tissues by clearing invading foreign bodies and/or mounting immune responses. In addition to varying identities regulated by transcriptional programs shaped by their respective environments, macrophage metabolism serves as an additional regulator to temper responses to extracellular stimuli. The area of research known as "immunometabolism" has been established within the last decade, owing to an increase in studies focusing on the crosstalk between altered metabolism and the regulation of cellular immune processes. From this research, macrophages have emerged as a prime focus of immunometabolic studies, although macrophage metabolism and their immune responses have been studied for centuries. During disease, the metabolic profile of the tissue and/or systemic regulators, such as endocrine factors, become increasingly dysregulated. Owing to these changes, macrophage responses can become skewed to promote further pathophysiologic changes. For instance, during diabetes, obesity, and atherosclerosis, macrophages favor a proinflammatory phenotype; whereas in the tumor microenvironment, macrophages elicit an anti-inflammatory response to enhance tumor growth. Herein we have described how macrophages respond to extracellular cues including inflammatory stimuli, nutrient availability, and endocrine factors that occur during and further promote disease progression.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".