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Record W4210717978 · doi:10.1002/advs.202104317

<i>Cdyl</i> Deficiency Brakes Neuronal Excitability and Nociception through Promoting <i>Kcnb1</i> Transcription in Peripheral Sensory Neurons

2022· article· en· W4210717978 on OpenAlexaff
Zhao‐Wei Sun, Jarod M. Waybright, Serap Beldar, Lu Chen, Caroline A. Foley, Jacqueline L. Norris‐Drouin, Tian‐Jie Lyu, Aiping Dong, Jinrong Min, Yu‐Pu Wang, Lindsey I. James, Yun Wang

Bibliographic record

VenueAdvanced Science · 2022
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsStructural Genomics ConsortiumUniversity of Toronto
FundersNational Cancer InstituteNational Institute on Drug AbuseNational Natural Science Foundation of China
KeywordsEpigeneticsNeuropathic painNociceptionChromodomainNeuroscienceGene knockdownNociceptorSensory systemTranscription factorGene silencingHistoneBiologyCell biologyGeneticsReceptorRNAGene

Abstract

fetched live from OpenAlex

Abstract Epigenetic modifications are involved in the onset, development, and maintenance of pain; however, the precise epigenetic mechanism underlying pain regulation remains elusive. Here it is reported that the epigenetic factor chromodomain Y‐like (CDYL) is crucial for pain processing. Selective knockout of CDYL in sensory neurons results in decreased neuronal excitability and nociception. Moreover, CDYL facilitates histone 3 lysine 27 trimethylation (H3K27me3) deposition at the Kcnb1 intron region thus silencing voltage‐gated potassium channel (K v ) subfamily member K v 2.1 transcription. Loss function of CDYL enhances total K v and K v 2.1 current density in dorsal root ganglia and knockdown of K v 2.1 reverses the pain‐related phenotypes of Cdyl deficiency mice. Furthermore, focal administration of a novel potent CDYL antagonist blunts nociception and attenuates neuropathic pain. These findings reveal that CDYL is a critical regulator of pain sensation and shed light on the development of novel analgesics targeting epigenetic mechanisms.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

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

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 head0.020
GPT teacher head0.283
Teacher spread0.262 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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