Perturbations of Zinc Homeostasis and Onset of Neuropsychiatric Disorders
Bibliographic record
Abstract
Zinc (Zn2+) is a trace element essential for its catalytic, antioxidant, and immunomodulatory roles extending to synaptic signalling in the central nervous system. In this narrative review, we aim to offer the reader evidence linking perturbations of the Zn2+ homeostasis, including deficiency, excess, or transportation anomalies, to neuropsychiatric conditions such as Alzheimer’s disease (AD), Parkinson’s disease (PD), autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD). A targeted, unsystematic PubMed search followed by an extensive pearl-growing strategy was applied to further augment study selection based on the extensive expertise of study authors. Overall, most of the evidence currently available suggests a modest benefit for a Zn2+ supplement of around 25–30 mg/day as an augmentation to MDD treatment, with potential benefits of smaller magnitude in paediatric ADHD. Evidence for perturbations of Zn2+ as a biomarker of risk for these neuropsychiatric disorders remains unconvincing. The role of Zn2+ supplements in the treatment of the selected conditions remains largely unknown due to the lack of specific, randomised controlled trials conducted to explore their efficacy. The long-term safety, optimal doses for specific applications, and the exploration of possible biomarkers to stratify patient selection to identify the optimal candidate for Zn2+ supplements remain unanswered questions.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".