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Record W4309315777 · doi:10.26689/par.v6i6.4512

Analysis of the Epigenetic Mechanism and Treatment of Huntington’s Disease

2022· article· en· W4309315777 on OpenAlexaff
Yi Shen, Yuze Tang

Bibliographic record

VenueProceedings of Anticancer Research · 2022
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of Alberta
FundersJohns Hopkins University
KeywordsHuntington's diseaseEpigeneticsHuntingtinChoreaMechanism (biology)DiseaseGeneticsBiologyDNA methylationHuntingtin ProteinMedicineNeuroscienceGeneBioinformaticsInternal medicine

Abstract

fetched live from OpenAlex

Huntington’s disease (HD) is an irreversible neurodegenerative disorder that is inherited in an autosomal dominant manner. In HD, many regions of the human brain are affected, including the striatum, thalamus, and cortex. The mechanism is by the expansion of CAG repeats, which encode glutamine (Q) in the Huntingtin gene on chromosome 4p16.3. Patients with more CAG repeats tend to have a younger age of onset and a higher risk. Mutant HTT protein, translated from mtHtt, would congregate or interact with other proteins, causing damage to the human body. Patients with HD show symptoms like chorea, which is an involuntary motor disability, cognitive deterioration, and psychiatric disturbances. Except for the genetic pathology of HD, the epigenetic mechanism of this disease has made a lot of progress in recent years. This paper primarily focuses on the alternation of deoxyribonucleic acid (DNA) methylation, histone modification, and non-coding ribonucleic acids (ncRNAs) in HD as well as the advancements of epigenetic therapy and healthcare in HD.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.082
GPT teacher head0.356
Teacher spread0.274 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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