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Record W3092338564 · doi:10.1155/2020/3497920

Molecular Mechanisms of Glial Cells Related Signaling Pathways Involved in the Neuroinflammatory Response of Depression

2020· review· en· W3092338564 on OpenAlexaff
Junhui Wang, Jie Qin, Peng Wang, Yu Sun, Qi Zhang

Bibliographic record

VenueMediators of Inflammation · 2020
Typereview
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsLunenfeld-Tanenbaum Research InstituteWestern UniversityMount Sinai Hospital
FundersFundamental Research Fund of Shandong UniversityCapital Medical UniversityShandong University
KeywordsNeuroinflammationMicrogliaNeurosciencePathologicalDepression (economics)Signal transductionBiologyMedicineImmunologyCell biologyInflammationPathology

Abstract

fetched live from OpenAlex

Dysfunction of the glial cells, such as astrocytes and microglia, is one of the pathological features in many psychiatric disorders, including depression, which emphasizes that glial cells driving neuroinflammation is not only an important pathological change in depression but also a potential therapeutic target. In this review, we summarized a recent update about several signaling pathways in which glial cells may play their roles in depression through neuroinflammatory reactions. We focused on the basic knowledge of these signaling pathways by elaborating each of them. This review may provide an updated image about the recent advances on these signaling pathways that are essential parts of neuroinflammation involved in 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.255
Teacher spread0.230 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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