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Record W1760516212 · doi:10.1177/153537020422901003

Unraveling the Molecular Details Involved in the Intimate Link between the Immune and Neuroendocrine Systems

2004· review· en· W1760516212 on OpenAlexaff
Nicolas P. Turrin, Serge Rivest

Bibliographic record

VenueExperimental Biology and Medicine · 2004
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsProinflammatory cytokineImmune systemCircumventricular organsSignal transductionNeuroscienceReceptorInflammationInnate immune systemBiologyCell biologyHomeostasisEndogenyImmunologyCentral nervous systemEndocrinology

Abstract

fetched live from OpenAlex

During systemic infections, the immune system can signal the brain and act on different neuronal circuits via soluble molecules, such as proinflammatory cytokines, that act on the cells forming the blood-brain barrier and the circumventricular organs. These activated cells release prostaglandin of the E(2) type (PGE(2)), which is the endogenous ligand that triggers the pathways involved in the control of autonomic functions necessary to restore homeostasis and provide inhibitory feedback to innate immunity. Among these neurophysiological functions, activation of the circuits that control the plasma release of glucocorticoids is probably the most critical to the survival of the host in the presence of pathogens. This review revisits this issue and describes in depth the molecular details (including the emerging role of Toll-like receptors during inflammation) underlying the influence of circulating inflammatory molecules on the cerebral tissue, focusing on their contribution in the synthesis and action PGE(2) in the brain. We also provide an innovative view supporting the concept of "fast and delayed response" involving the same ligands but different groups of cells, signal transduction pathways, and target genes.

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 score0.002
Threshold uncertainty score0.008

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 studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.029
GPT teacher head0.331
Teacher spread0.303 · 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

Citations108
Published2004
Admission routes1
Has abstractyes

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