Methylenedioxymethamphetamine (MDMA, ‘Ecstasy’): a stressor on the immune system
Bibliographic record
Abstract
Drug abuse is a global problem of considerable concern to health. One such health concern stems from the fact that many drugs of abuse have immunosuppressive actions and consequently have the potential to increase susceptibility to infectious disease. This article is focused on the impact of the amphetamine derivative, methylenedioxymethamphetamine (MDMA; 'Ecstasy') on immunity. Research conducted over the last 5 years, in both laboratory animals and humans, has demonstrated that MDMA has immunosuppressive actions. Specifically, MDMA suppresses neutrophil phagocytosis, suppresses production of the pro-inflammatory cytokines tumour necrosis factor-alpha (TNF-alpha) and interleukin (IL)-1beta, and increases production of the endogenous immunosuppressive cytokine (IL-10), thereby promoting an immunosuppressive cytokine phenotype. MDMA also suppresses circulating lymphocyte numbers, with CD4+ T cells being particularly affected, and alters T-cell function as indicated by reduced mitogen-stimulated T-cell proliferation, and a skewing of T-cell cytokine production in a T helper 2 (Th2) direction. For the most part, the aforementioned effects of MDMA are not the result of a direct action of the drug on immune cells, but rather caused by the release of endogenous immunomodulatory substances. Consequently, the physiological mechanisms that are thought to underlie the immunosuppressive effects of MDMA will be discussed. As many of the physiological changes elicited by MDMA closely resemble those induced by acute stress, it is suggested that exposure to MDMA could be regarded as a 'chemical stressor' on the immune system. Finally, the potential of MDMA-induced immunosuppression to translate into significant health risks for abusers of the drug will be discussed.
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.
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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".