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Record W1982147131 · doi:10.1586/14737175.2.5.677

Transcriptional mechanisms underlying neuropathic pain: DREAM, transcription factors and future pain management?

2002· article· en· W1982147131 on OpenAlexaff
Hai‐Ying Mary Cheng, Josef Penninger

Bibliographic record

VenueExpert Review of Neurotherapeutics · 2002
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeuropathic painReprogrammingNerve injuryNeuroscienceMedicineChronic painTranscription factorSensitizationSensory systemHyperalgesiaBioinformaticsBiologyGeneGeneticsNociceptionReceptorInternal medicine

Abstract

fetched live from OpenAlex

Injury to peripheral nerves triggers a large-scale alteration in gene expression in sensory neurons as well as glial and immune cells. Neuropathic pain is believed to be the culmination of the plastic changes brought on by this 'genetic reprogramming'. However, an individual gene alteration may contribute to different processes induced by nerve injury, such as sensitization, regeneration or adaptation of endogenous analgesic mechanisms. Knowing which genes are altered in expression following nerve damage and perhaps, more importantly, understanding the transcription factors responsible for these changes, is a critical step toward more efficacious treatments for neuropathic pain. Recent genetic studies have revealed an important role for the novel transcriptional repressor, DREAM, in modulating acute and chronic pain and suggested the possibility of targeting this or other transcription factors for pain management in the future.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.063
GPT teacher head0.304
Teacher spread0.241 · 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 designTheoretical or conceptual
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".

Quick stats

Citations11
Published2002
Admission routes1
Has abstractyes

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