Crosstalk between metabolic and neuropsychiatric disorders
Bibliographic record
Abstract
Evidence supporting the concurrence of metabolic disturbances (e.g. insulin resistance, diabetes and obesity) and neuropsychiatric disorders has been demonstrated in both human and animal studies, suggesting the possibility that they have shared pathophysiological mechanisms. During the past decade, our understanding for the role of insulin in both normal and abnormal central nervous system (CNS) processes has become increasingly refined. Evidence indicates that insulin is a pleiotropic peptide, critical to neurotrophism, neuroplasticity, and neuromodulation. Moreover, the role of insulin underscores its importance in the development of several neuropsychiatric disorders, including, but not limited to, mechanisms involved in the pathogenesis and progression towards diabetes, obesity, and neurodegenerative disorders, such as Alzheimer's disease. This review focuses on the insulin-mediated effects on normal and abnormal brain function and discusses why targeting insulin-related pathways in the brain may emerge as a new approach for refining treatment of neurological and psychiatric disorders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".