MétaCan
Menu
Back to cohort

Sex differences in pain

2015· review· en· W2344980370 on OpenAlexafffund
Josiane C.S. Mapplebeck, Simon Beggs, Michael W. Salter

Bibliographic record

VenuePain · 2015
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersMedical Research CouncilCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsMicrogliaDisinhibitionNeuroscienceNeuropathic painPurinergic receptorMedicineNociceptionNeurotrophic factorsNociceptorSpinal cordReceptorPsychologyInternal medicineInflammation

Abstract

fetched live from OpenAlex

Substantial evidence has implicated microglia in neuropathic pain. After peripheral nerve injury, microglia in the spinal cord proliferate and increase cell-surface expression of the purinergic receptor P2X4. Activation of P2X4 receptors results in release of brain-derived neurotrophic factor, which acts on neurons to produce disinhibition of dorsal horn neurons which transmit nociceptive information to the brain. Disinhibition of these neurons produces pain hypersensitivity, a hallmark symptom of neuropathic pain. However, elucidating this microglia-neuronal signalling pathway was based on studies using only male rodents. Recent evidence has shown that the role of microglia in pain is sexually dimorphic. Despite similar microglia proliferation in the dorsal horn in both sexes, females do not upregulate P2X4Rs and use a microglia-independent pathway to mediate pain hypersensitivity. Instead, adaptive immune cells, possibly T cells, may mediate pain hypersensitivity in female mice. This profound sex difference highlights the importance of including subjects of both sexes in preclinical pain research.

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)0.001
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.131
GPT teacher head0.363
Teacher spread0.232 · 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

Citations225
Published2015
Admission routes2
Has abstractyes

Explore more

Same venuePainSame topicPain Mechanisms and TreatmentsFrench-language works237,207