Metabolic needs of brain‐infiltrating leukocytes and microglia in multiple sclerosis
Bibliographic record
Abstract
Metabolism, the umbrella term for complex biochemical pathways that sustain the basic functions of life, has garnered attention in recent years for its role in immune activation. Indeed, metabolic pathways and their intricate and complex connections with immune mechanisms constitute a new area of immunology termed 'immunometabolism'. One highlight is the existence of a switch in the key metabolic programs in immune cells, which executes their effector functions. 'Metabolic reprogramming' is observed in conditions of both peripheral diseases as well as in neurodegenerative conditions associated with inflammation such as multiple sclerosis. Moreover metabolic reprogramming occurs for almost every immune cell type. Whether metabolic changes are cause or effect of immune activation, however, remains to be fully understood. Being central to cellular activation, metabolism has become very topical in terms of exploring therapeutic targets. This review covers the major metabolic programs in immune cells, discuss metabolites as regulators of immune cell functions, and consider metabolic enzymes or pathways as therapeutic targets using examples from multiple sclerosis and its animal models.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".