MétaCan
Menu
Back to cohort
Record W4403159363 · doi:10.7759/cureus.70912

Serotonin Availability Shapes the Effects of Phenelzine on Inflammatory Response and Gene Expression in Macrophages

2024· article· en· W4403159363 on OpenAlexaff
Saeed Mahdianipur, Mahafarin Maralani, Saeed Mohammadi, Seyed Reza Khandoozi, Afifeh Jaefari, Homa Davoodi

Bibliographic record

VenueCureus · 2024
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsDr. Georges-L.-Dumont University Hospital CentreAtlantic Cancer Research Institute
FundersGolestan University of Medical Sciences
KeywordsMedicinePhenelzineGene expressionGeneInflammatory responseSerotoninInflammationGeneticsImmunologyPharmacologyInternal medicineBiochemistryEnzymeBiology

Abstract

fetched live from OpenAlex

Background Serotonin (5-HT) is a neurotransmitter with extensive physiological influence in the central nervous system (CNS) and various behavioral and biological functions, including immune regulation through 5-HT receptors (5-HTRs) expressed by immune cells. A variety of serotonin-modulating drugs have been developed to treat neurological disorders. Phenelzine, a drug indicated for the management of treatment-resistant depression, is a potent, non-selective inhibitor of monoamine oxidase (MAO), the enzyme that metabolizes serotonin to 5-hydroxyindole acetic acid (5-HIAA). Given the emerging evidence of a bidirectional link between depression and inflammation, as well as the potential therapeutic applications of serotonin-modulating drugs in autoimmune diseases and cancer, our study investigated the pro-inflammatory and anti-inflammatory factors influenced by serotonin and phenelzine. Methodology We conducted experiments on RAW264.7 macrophages, exposing them to various combinations and concentrations of serotonin, 5-HIAA, and phenelzine. We assessed the relative gene expression of monoamine oxidase-A (MAO-A), CYP1B1, cyclooxygenase-2 (COX-2), and inducible nitric oxide synthase (iNOS) using real-time PCR and measured the production of IL-6, TNF-α, and IL-10 cytokines using enzyme-linked immunosorbent assays (ELISA). Results Our findings revealed that phenelzine can downregulate genes associated with the production of reactive oxygen and nitrogen species, reduce aryl hydrocarbon receptor (AHR)-related gene expression induced by serotonin, and enhance the production of inflammatory cytokines. These effects were significantly influenced by the concentration of available serotonin. Conclusions Our study demonstrates that various mechanisms, including AHR activation, modulation of reactive oxygen and nitrogen species production, and others, in addition to the increased availability of serotonin due to phenelzine treatment, can significantly influence the inflammatory state.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.012
GPT teacher head0.258
Teacher spread0.246 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCureusSame topicTryptophan and brain disordersFrench-language works237,207