Putative neuroprotective pharmacotherapies to target the staged progression of mental illness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: Neuropsychiatric disorders including depression, bipolar and schizophrenia frequently exhibit a neuroprogressive course from prodrome to chronicity. There are a range of agents exhibiting capacity to attenuate biological mechanisms associated with neuroprogression. This review will update the evidence for putative neuroprotective agents including clinical efficacy, mechanisms of action and limitations in current assessment tools, and identify novel agents with neuroprotective potential. METHOD: Data for this review were sourced from online databases PUBMED, Embase and Web of Science. Only data published since 2012 were included in this review, no data were excluded based on language or publication origin. RESULTS: Each of the agents reviewed inhibit one or multiple pathways of neuroprogression including: inflammatory gene expression and cytokine release, oxidative and nitrosative stress, mitochondrial dysfunction, neurotrophin dysregulation and apoptotic signalling. Some demonstrate clinical efficacy in preventing neural damage or loss, relapse or cognitive/functional decline. Agents include: the psychotropic medications lithium, second generation antipsychotics and antidepressants; other pharmacological agents such as minocycline, aspirin, cyclooxygenase-2 inhibitors, statins, ketamine and alpha-2-delta ligands; and others such as erythropoietin, oestrogen, leptin, N-acetylcysteine, curcumin, melatonin and ebselen. CONCLUSIONS: Signals of evidence of clinical neuroprotection are evident for a number of candidate agents. Adjunctive use of multiple agents may present a viable avenue to clinical realization of neuroprotection. Definitive prospective studies of neuroprotection with multimodal assessment tools are required.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it