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Record W2758746528

THE EFFECTS OF ACUTE PSYCHOLOGICAL STRESS ON ENZYMES REGULATING THE KYNURENINE PATHWAY

2014· article· en· W2758746528 on OpenAlexaffvenue
Chaitanya P. Gandhi

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2014
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsKynurenine pathwayKynurenineEndocrinologyInternal medicineIndoleamine 2,3-dioxygenaseTumor necrosis factor alphaTryptophanCorticosteroneBiologyMedicineBiochemistryHormone
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION An emerging body of literature recognizes the relationship between stress and inflammation. The kynurenine pathway is particularly relevant because it accounts for the majority of tryptophan’s metabolism [1]. Activation of the kynurenine pathway depletes the tryptophan pool for serotonin, and has been associated with the emergence of depressive-like symptoms and “sickness behaviour” (anhedonia, anxiety, and sleep disturbances) in animals [1]. The first and rate limiting step of the kynurenine pathway converts tryptophan to kynurenine and can be catalyzed by tryptophan 2,3-dioxygenase (TDO), which operates under basal conditions, or by indoleamine 2,3-dioxygenase 1 (IDO1), which predominates under inflammatory states [2]. Indeed, previous research has shown that IDO1 can be induced by cytokines, such as tumor necrosis factor alpha (TNFα) [1,2]. Recent data from our lab indicates that TNFα protein is increased in the amygdala 4 h after exposure to an acute stressor. Hence, this investigation attempted to determine the effects of acute stress on mRNA levels of enzymes regulating the kynurenine pathway. METHODS Adult, male, Sprague Dawley rats ( N =48) were subjected to 120 minutes of restraint stress and rapidly decapitated 1 h, 2 h, 4 h, 6 h, or 24 h later. Trunk blood was collected and analyzed for circulating corticosterone and TNFα levels. Brains were extracted and excised into amygdalae, hypothalami, prefrontal cortices, and hippocampi. RNA was isolated, followed by cDNA synthesis, and quantitative PCR (qPCR) to quantify mRNA levels of IDO1, TDO, kynurenine aminotransferase 1 (KAT1), kynurenine 3-monooxygenase (KYNM), kynureninase (KYNU), and 3-hydroxyanthranilate 3,4-dioxygenase. RESULTS Results indicated that plasma corticosterone levels were elevated 2 h after the acute stressor, while circulating levels of TNFα were increased at the 1 h and the 2 h post stress time points. Analysis of amygdalar qPCR data indicated an upregulation of IDO1 mRNA at the 1 h time point, and increased KYNM and KYNU mRNA at the 4 h time point. There were no amygdalar mRNA changes in the other genes. Regarding hypothalamic data, there was an increase in TDO mRNA at the 4 h time point and KYNU mRNA at the 1 h time point. DISCUSSION AND CONCLUSIONS Increases in expression of kynurenine pathway enzymes in the amygdala occurred in a time dependent manner. Taken together, the data is concordant with previous reports, which indicate that IDO1 and TDO can be induced by TNFα and corticosterone, respectively [1,2]. The result of increased amygdalar KYNM and KYNU mRNA following acute stress represents a novel finding and suggests that stress shifts the kynurenine pathway towards neurotoxic metabolites, such as 3-hyroxykynurenine and quinolinic acid, which may aggravate the symptoms of inflammation-induced depression. Follow up work on this study would investigate mRNA changes in other brain regions, such as the prefrontal cortex and the hippocampus. In addition, plasma and brain concentrations of tryptophan, kynurenine, kynurenic acid, and quinolinic acid would be determined to see if they are in accordance with the mRNA data. Ultimately, the present study highlights the kynurenine pathway as a potential therapeutic target for inflammation-induced depression.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.361
Teacher spread0.315 · 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 designObservational
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".

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Citations0
Published2014
Admission routes2
Has abstractyes

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