Metabolic Syndrome and Schizophrenia: Adding a Piece to the Interplay Between the Kynurenine Pathway and Inflammation
Bibliographic record
Abstract
The biology of schizophrenia is highly complex and multifaceted. Numerous efforts have been made over the years to disentangle the heterogeneity of the disease, gradually leading to a more detailed understanding of its underlying pathogenic mechanisms. Two cardinal elements in the pathophysiology of schizophrenia are neuroinflammation and alterations of neurotransmission. The kynurenine (KYN) pathway (KP) is of particular importance because it is inducted by systemic low-grade inflammation in peripheral tissues, producing metabolites that are neuroactive (i.e., modulating glutamatergic and cholinergic neurotransmission), neuroprotective, or neurotoxic. Consequently, the KP is at the crossroads between two primary systems involved in the pathogenesis of schizophrenia. It bridges the central nervous system (CNS) and the periphery, as KP metabolites can cross the blood-brain barrier and modulate neuronal activity. Metabolic syndrome plays a crucial role in this context, as it frequently co-occurs with schizophrenia, contributing to a sub-inflammatory state able to activate the KP. This narrative review provides valuable insights into these complex interactions, offering a framework for developing targeted therapeutic interventions or precision psychiatry approaches of the disorder.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".