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Role of Proinflammatory Cytokines in Dopaminergic System Disturbances, Implications for Anhedonic Features of MDD

2017· review· en· W2605549847 on OpenAlexaff
Zihang Pan, Joshua D. Rosenblat, Walter Swardfager, Roger S. McIntyre

Bibliographic record

VenueCurrent Pharmaceutical Design · 2017
Typereview
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsUniversity of TorontoSunnybrook HospitalSunnybrook Health Science CentreUniversity Health Network
Fundersnot available
KeywordsAnhedoniaProinflammatory cytokineKynurenineDopaminergicKynurenine pathwayNeuroscienceTetrahydrobiopterinContext (archaeology)Major depressive disorderDopaminePsychologyMedicineInflammationBiologyInternal medicineAmygdalaBiochemistryTryptophan

Abstract

fetched live from OpenAlex

Anhedonia, characterized by a loss of interest and/or pleasure in previously enjoyable activities, is an important diagnostic criterion of Major Depressive Disorder (MDD). Converging evidence implicates a causal relationship between proinflammatory cytokines and behavioural disturbances that characterize anhedonia in the context of MDD. Additionally, anhedonia has been implicated in disturbances of key central dopaminergic modulatory pathways. Emerging research into the roles of tetrahydrobiopterin, a cytokine-targeted co-enzyme in the synthesis of dopamine, and kynurenine, a product of inflammation-sensitive breakdown of tryptophan via indoleamine 2, 3-dioxygenase, have shed new light into the role of inflammation in mediating anhedonic behaviours. The following narrative review is not meant to be comprehensive, but highlights the roles of both tetrahydrobiopterin and kynurenine pathways in anhedonia, and discusses a potential mechanism of action via oxidative stress and excitotoxicity. Treatment implications are discussed, with an emphasis on anti-inflammatories as complements to current treatments of anhedonia and MDD.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.257
GPT teacher head0.443
Teacher spread0.187 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations34
Published2017
Admission routes1
Has abstractyes

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