A Novel Phospholipid-Based Drug Formulation, VP025, Modulates Age- and LPS-Induced Microglial Activity in the Rat
Bibliographic record
Abstract
BACKGROUND: A common change that occurs with age in the central nervous system is an increase in microglial-associated inflammation. This is usually coupled with an increase in the concentration of the inflammatory cytokine interleukin-1beta (IL-1beta) in the hippocampus and an inhibition in long-term potentiation. OBJECTIVES: To assess the effects of a novel preparation of phospholipid nanoparticles incorporating phosphatidylglycerol, VP025, on inflammatory changes in hippocampus of aged and lipopolysaccharide (LPS)-treated rats. METHODS/RESULTS: We report that a possible initial target cell of the putative anti-inflammatory actions of VP025 may be macrophages, as VP025 is engulfed by, and has the capacity to alter the activity of, these cells. VP025 reversed the increase in IFN-gamma concentration in supernatant taken from peritoneal macrophages harvested from LPS-treated rats. In addition, markers of microglial activity, major histocompatibility complex class II (MHC II) mRNA expression, CD40 expression and IL-1beta concentration were increased, and CD200 expression was reduced, in the hippocampus of these rats. VP025 reversed changes in CD40, IL-1beta and CD200 in aged rats, and also restored long-term potentiation in aged and LPS-treated rats. CONCLUSIONS: We conclude that VP025 has the ability to modulate the activity of macrophage, microglia and neurons in response to stressors such as ageing and LPS treatment.
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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 | 0.001 | 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".