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Record W4200068599 · doi:10.1126/sciadv.abg6363

Chromatin architecture at susceptible gene loci in cerebellar Purkinje cells characterizes DNA damage–induced neurodegeneration

2021· article· en· W4200068599 on OpenAlexaff
Young Don Kwak, Timothy I. Shaw, Susanna M. Downing, Ambika Tewari, Hongjian Jin, Yang Li, Lavinia C. Dumitrache, Sachin Katyal, Kamran Khodakhah, H. R. Russell, Peter J. McKinnon

Bibliographic record

VenueScience Advances · 2021
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsCancerCare Manitoba
FundersNational Institute of Neurological Disorders and StrokeNational Cancer Institute
KeywordsNeurodegenerationBiologyGenome instabilityAtaxiaDNA damageRNA splicingGeneCerebellumChromatinPurkinje cellGeneticsNeuroscienceCell biologyRNADNADiseaseMedicinePathology

Abstract

fetched live from OpenAlex

. Abundant genotoxic R loops were also found at these Purkinje cell gene loci, further exacerbating DNA damage and transcriptional disruption. Using ATAC-seq to profile global chromatin accessibility in the cerebellum, we found a notably unique chromatin conformation specifically in Purkinje chromatin at the affected gene loci, thereby promoting susceptibility to DNA damage. These data reveal the pathogenic basis of DNA damage in the nervous system and suggest chromatin conformation as a feature in directing genome instability–associated neuropathology.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.267
Teacher spread0.247 · 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.

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

Citations31
Published2021
Admission routes1
Has abstractyes

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