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Record W4391995075 · doi:10.1021/acschemneuro.3c00677

Uncovering Structure–Activity Relationships of Phenethylamines: Paving the Way for Innovative Mental Health Treatments

2024· article· en· W4391995075 on OpenAlexafffund
Sedat Karabulut, Harpreet Kaur, James W. Gauld

Bibliographic record

VenueACS Chemical Neuroscience · 2024
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsPhenethylaminesMonoamine neurotransmitterReuptake inhibitorDopamineModalitiesReuptakePsychologySerotoninMedicineNeurosciencePharmacologyPsychiatryAntidepressantInternal medicineAnxiety

Abstract

fetched live from OpenAlex

The rapidly evolving psychedelic industry has garnered considerable attention due to 3,4-methylenedioxymethamphetamine-assisted psychotherapy’s ground-breaking success in treating moderate-to-severe Post-traumatic Stress Disorder in two Phase 3 clinical trials. This has opened Pandora’s box for the development of innovative therapeutic modalities. Of particular interest are the phenethylamines and their ability to inhibit monoamine transporters. In this study, we employed the quantitative structure–activity relationship methodology to develop three vigorous models for the reuptake of serotonin, dopamine, and norepinephrine through monoamine transporters. These models were thoroughly validated using various criteria, including fitting ( R 2 DAT = 0.869, R 2 SERT = 0.828, and R 2 NET = 0.887), internal ( Q 2 loo DAT = 0.795, Q 2 loo SERT = 0.784, and Q 2 loo NET = 0.820), and external (RMSEext DAT = 0.373, R 2 ext DAT = 0.831, RMSEext SERT = 0.200, R 2 ext SERT = 0.955, RMSEext NET = 0.318, and R 2 ext NET = 0.711) criteria.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.308
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.068
GPT teacher head0.370
Teacher spread0.302 · 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 teacher head, 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

Citations4
Published2024
Admission routes2
Has abstractyes

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