MétaCan
Menu
Back to cohort
Record W2623481990

A medicinal chemistry investigation of 3,4-Methylenedioxymethamphetamine (MDMA)

2011· article· en· W2623481990 on OpenAlexaboutno aff
Katie D. Lewis

Bibliographic record

VenueUWA Profiles and Research Repository (University of Western Australia) · 2011
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMDMAChemistryEcstasyPharmacologyMedicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

3,4-Memylenedioxymethamphetamine (MDMA) 1, the active chemical constituent of the illicit drug ecstasy, is a psychotropic agent whose effects are primarily modulated through the serotonergic system. In recent years numerous researchers have identified MDMA as possessing therapeutic activity towards a variety of disease states. Parkinson's disease (PD) is a common and disabling neurodegenerative disorder. The primary symptomatic treatment of PD utilises the dopamine precursor levodopa. Long-term levodopa therapy typically elicits deleterious side-effects, the most significant being levodopa-induced dyskinesia (LED), the severity of which may negate the therapeutic benefit of levodopa. MDMA has been demonstrated in primate models to possess both anti-parkinsonian and anti-LED activity. Burkitt's lymphoma (BL) is a malignant disease of the lymphatic system, affecting B-cell lymphocytes in particular. Recent characterisation of a functioning immunoreactive serotonin reuptake transporter (SERT) in B-cell lines has been impetus for the investigation of SERT as a target for drug therapy in BL. MDMA, a known SERT substrate, exhibitss an anti-proliferative and pro-apoptotic response in a BL cell line (L3055). This thesis, prompted by recent reports of the therapeutic activity of MDMA in various disease states, details a medicinal chemistry investigation of MDMA, Chapters One, Two and Three document the analogues synthesised. These analogues were intended for evaluation as anti-neoplasties for Burkitt's lymphoma and for evaluation as therapeutics for the treatment of PD. This work was conducted in collaboration with Prof. John Gordon and coworkers (Centre for Immune Regulation at The University of Birmingham), and Dr Jonathan Brotchie and coworkers (Toronto Western Research Institute). Additionally a series of putative monoamine oxidase (MAO; EC 1.4.3.4) inhibitors was conceived, synthesised and assayed (Chapter Four). These compounds were structurally analogous to selegiline 10, a clinically useful MAO-B inhibitor.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.245
GPT teacher head0.415
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueUWA Profiles and Research Repository (University of Western Australia)Same topicForensic Toxicology and Drug AnalysisFrench-language works237,207