The Interactive Effects of Ketamine and Magnesium Upon Depressive-like Pathology
Bibliographic record
Abstract
Approximately one third of patients with major depressive disorders (MDD) are resistant to current treatment and the majority of cases relapse at some points during therapy.This has resulted in novel treatments being adopted, including sub-anaesthetic doses of ketamine, which affects aberrant neuroplastic circuits; glutamatergic signaling and the production of brain derived neurotrophic factor (BDNF).Ketamine rapidly relieves depressive symptoms in treatment resistant MDD patients with effects that last for up to two weeks even after one administration.However, it is also a drug with abusive potential and can have marked side effects.Hence, we conducted studies aimed at enhancing the anti-depressant-like effects of ketamine (allowing for lower dosing regimens) by co-administering magnesium hydroaspartate (Mg 2+ normally affects the same receptors as ketamine).To this end, we found that ketamine alone induced rapid antidepressant-like effects in the forced swim test and influence brain levels of BDNF.However contrary to our hypothesis, magnesium had no effect on these outcomes nor did it enhance the effects of ketamine.Thus, these data do not support the use of magnesium as an adjunct agent and instead suggest further research involving other antidepressant and animal models is required to confirm the present findings.
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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) | 0.000 | 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) | 0.004 | 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".