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Record W2000561563 · doi:10.1002/ajmg.1379

Diseases caused by nuclear genes affecting mtDNA stability

2001· review· en· W2000561563 on OpenAlexaff
Anu Suomalainen, Jyrki Kaukonen

Bibliographic record

VenueAmerican Journal of Medical Genetics · 2001
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersSuomen Kulttuurirahasto
KeywordsMitochondrial DNAGeneticsGeneNuclear geneBiology

Abstract

fetched live from OpenAlex

Diseases caused by nuclear genes that affect mitochondrial DNA (mtDNA) stability are an interesting group of mitochondrial disorders, involving both cellular genomes. In these disorders, a primary nuclear gene defect causes secondary mtDNA loss or deletion formation, which leads to tissue dysfunction. Therefore, the diseases clinically resemble those caused by mtDNA mutations, but follow a Mendelian inheritance pattern. Several clinical entities associated with multiple mtDNA deletions have been characterized, the most frequently described being autosomal dominant progressive external ophthalmoplegia (adPEO). MtDNA depletion syndrome (MDS) is a severe disease of childhood, in which tissue-specific loss of mtDNA is seen. Mitochondrial neurogastrointestinal encephalomyopathy (MNGIE) patients may have multiple mtDNA deletions and/or mtDNA depletion. Recent reports of thymidine phosphorylase mutations in MNGIE and adenine nucleotide translocator mutations in adPEO have given new insights into the mechanisms of mtDNA maintenance in mammals. The common mechanism underlying both of these gene defects could be disturbed mitochondrial nucleoside pools, the building blocks of mtDNA. Future studies on MNGIE and adPEO pathogenesis, and identification of additional gene defects in adPEO and MDS will provide further understanding about the mammalian mtDNA maintenance and the crosstalk between the nuclear and mitochondrial genomes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.320
Teacher spread0.295 · 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 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

Citations110
Published2001
Admission routes1
Has abstractyes

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