Ketamine as an antidepressant: overview of its mechanisms of action and potential predictive biomarkers
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
Ketamine, a drug introduced in the 1960s as an anesthetic agent and still used for that purpose, has garnered marked interest over the past two decades as an emerging treatment for major depressive disorder. With increasing evidence of its efficacy in treatment-resistant depression and its potential anti-suicidal action, a great deal of investigation has been conducted on elucidating ketamine’s effects on the brain. Of particular interest and therapeutic potential is the ability of ketamine to exert rapid antidepressant properties as early as several hours after administration. This is in stark contrast to the delayed effects observed with traditional antidepressants, often requiring several weeks of therapy for a clinical response. Furthermore, ketamine appears to have a unique mechanism of action involving glutamate modulation via actions at the N-methyl-D-aspartate (NMDA) and [Formula: see text]-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, as well as downstream activation of brain-derived neurotrophic factor (BDNF) and mechanistic target of rapamycin (mTOR) signaling pathways to potentiate synaptic plasticity. This paper provides a brief overview of ketamine with regard to pharmacology/pharmacokinetics, toxicology, the current state of clinical trials on depression, postulated antidepressant mechanisms and potential biomarkers (biochemical, inflammatory, metabolic, neuroimaging sleep-related and cognitive) for predicting response to and/or monitoring of therapeutic outcome with ketamine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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