Resolution-Associated Molecular Patterns (RAMPs) as Endogenous Regulators of Glia Functions in Neuroinflammatory Disease
Bibliographic record
Abstract
Glial cells, including microglia and astrocytes, facilitate the survival and health of all cells within the Central Nervous System (CNS) by secreting a range of growth factors and contributing to tissue and synaptic remodeling. Microglia and astrocytes can also secrete cytotoxins in response to specific stimuli, such as exogenous Pathogen-Associated Molecular Patterns (PAMPs), or endogenous Damage-Associated Molecular Patterns (DAMPs). Excessive cytotoxic secretions can induce the death of neurons and contribute to the progression of neurodegenerative disorders, such as Alzheimer's disease (AD). The transition between various activation states of glia, which include beneficial and detrimental modes, is regulated by endogenous molecules that include DAMPs, cytokines, neurotransmitters, and bioactive lipids, as well as a diverse group of mediators sometimes collectively referred to as Resolution-Associated Molecular Patterns (RAMPs). RAMPs are released by damaged or dying CNS cells into the extracellular space where they can induce signals in autocrine and paracrine fashions by interacting with glial cell receptors. While the complete range of their effects on glia has not been described yet, it is believed that their overall function is to inhibit adverse CNS inflammatory responses, facilitate tissue remodeling and cellular debris removal. This article summarizes the available evidence implicating the following RAMPs in CNS physiological processes and neurodegenerative diseases: cardiolipin (CL), prothymosin α (ProTα), binding immunoglobulin protein (BiP), heat shock protein (HSP) 10, HSP 27, and αB-crystallin. Studies on the molecular mechanisms engaged by RAMPs could identify novel glial targets for development of therapeutic agents that effectively slow down neuroinflammatory disorders including AD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".