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Record W2007043862 · doi:10.1017/s1461145702003140

Changes in the immune system in rodent models of depression

2002· review· en· W2007043862 on OpenAlexaff
Brian E. Leonard, Cai Song

Bibliographic record

VenueThe International Journal of Neuropsychopharmacology · 2002
Typereview
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImmune systemDepression (economics)GlucocorticoidMonoamine neurotransmitterNeuroscienceGlucocorticoid receptorInflammationCytokineImmunologyPsychologySickness behaviorProinflammatory cytokineChronic stressReceptorRodentMedicineBiologyInternal medicineSerotonin

Abstract

fetched live from OpenAlex

This review summarizes some of the evidence which implicates an increase in the peripheral and central secretion of pro-inflammatory cytokines in the behavioural changes seen in some stress-induced and brain lesion models of depression. Following a consideration of the role of cytokines in the periphery and the brain, evidence is presented suggesting that pro-inflammatory cytokines alter the function of monoamine neurotransmitters which have been implicated in severe stress and in major depression. These changes occur in the presence of elevated glucocorticoid concentrations which suggests that immune activation is correlated with a decrease in the sensitivity of the glucocorticoid receptors on immune cells in addition to those occurring in the brain. The review concludes with a brief account of the various rodent models of depression in which evidence of immune activation as been demonstrated.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.101
GPT teacher head0.388
Teacher spread0.287 · 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

Citations46
Published2002
Admission routes1
Has abstractyes

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