First trimester human umbilical cord perivascular cells (HUCPVC) modulate the kynurenine pathway and glutamate neurotransmission in an LPS-induced mouse model of neuroinflammation
Bibliographic record
Abstract
BACKGROUND: The Kynurenine Pathway (KP) of tryptophan degradation and glutamate toxicity is implicated in several neurological disorders, including depression. The therapeutic potential of mesenchymal stromal cells (MSC), owing to their well documented phagocytosis-driven mechanism of immunomodulation and neuroprotection, has been tested in many neurological disorders. However, their potential to influence KP and the glutamatergic system has not yet been investigated. Hence, this study sought to investigate the effect of HUCPVC, a rich and potent source of MSC, on Lipopolysaccharide (LPS)-activated KP metabolites, KP enzymes, and key components of glutamate neurotransmission. METHODS: The immunomodulatory effect of peripherally administered HUCPVC on the expression profile of kynurenine pathway metabolites and enzymes was assessed in the plasma and brain of mice treated with LPS using LCMS and QPCR. An assessment of the glutamatergic system, including selected receptors, transporters and related proteins was also conducted by QPCR, immunohistochemistry and Western blot. RESULTS: HUCPVC were found to modulate LPS-induced activation of KP enzymes and metabolites in the brain associated with neurotoxicity. Moreover, the reduced expression of the glutamatergic components due to LPS was also found to be significantly improved by HUCPVC. CONCLUSIONS: The immunomodulatory properties of HUCPVC appear to confer neuroprotection, at least in part, through their ability to modulate the KP in the brain. This KP modulation enhances neuroprotective regulators and downregulates neurotoxic consequences, including glutamate neurotoxicity, which is associated with neuroinflammation and depressive behavior.
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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 | 0.000 | 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".