Therapeutic potential of N,N-dimethyltryptamine in the treatment of psychiatric and neurodegenerative disorders
Bibliographic record
Abstract
This led researchers to consider the potential role of DMT as a neurotransmitter crucial for the survival of the organism under hypoxic conditions.The discovery of its immunomodulatory, neuroplastic, and body-protective properties against the effects of oxidative stress or damage sparked the scientific community's interest in DMT's therapeutic potential.In the first part of this paper, we show how DMT, as a psychoplastogen, i.e. a substance significantly stimulating mechanisms of structural and functional neuroplasticity in cortical areas, can be used in the treatment of Alzheimer's disease, brain damage, or frontotemporal dementia.Next, we show how neuroplastic changes occur through activation of sigma-1 and 5-HT 2A receptors.We also focus on its anti-inflammatory effects, protecting nerve and glial cells from oxidative stress, which shows therapeutic potential, especially in the treatment of depression, anxiety, or addiction.Finally, we outline the important effects of DMT on the biogenesis and proper functioning of mitochondria, whose dysfunction underlies many psychiatric, metabolic, neurodegenerative, and immunological disorders.Conclusions.The effects of DMT show therapeutic potential in the treatment of post-stroke, post-traumatic brain injury, transplantation or neurological and mitochondrial diseases, such as Alzheimer's and Parkinson's, frontotemporal dementia, amyotrophic lateral sclerosis, or multiple sclerosis.DMT shows therapeutic potential AbstrAct Objectives.Outlining the therapeutic potential of dimethyltryptamine (DMT) from the perspective of its unique properties, mainly neuroplasticity and neuroprotection.Literature review.The first information on the therapeutic potential of DMT, commonly found in plants, humans and animals, appeared in the 1960s.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".