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Record W3025068857 · doi:10.1089/dna.2020.5398

Damage in Mitochondrial DNA Associated with Parkinson's Disease

2020· review· en· W3025068857 on OpenAlexaff
Rebeca Martín-Jiménez, Olivier Lurette, Étienne Hébert-Chatelain

Bibliographic record

VenueDNA and Cell Biology · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsBiologyMitochondrial DNAMitochondrionGeneticsMitochondrial diseaseHuman mitochondrial DNA haplogroupDiseaseOrganelleHuman mitochondrial geneticsmitochondrial fusionHaplogroupDNAJA3Cell biologyGeneAlleleHaplotypePathology

Abstract

fetched live from OpenAlex

Mitochondria are the only organelles that contain their own genetic material (mtDNA). Mitochondria are involved in several key physiological functions, including ATP production, Ca2+ homeostasis, and metabolism of neurotransmitters. Since these organelles perform crucial processes to maintain neuronal homeostasis, mitochondrial dysfunctions can lead to various neurodegenerative diseases. Several mitochondrial proteins involved in ATP production are encoded by mtDNA. Thus, any mtDNA alteration can ultimately lead to mitochondrial dysfunction and cell death. Accumulation of mutations, deletions, and rearrangements in mtDNA has been observed in animal models and patients suffering from Parkinson's disease (PD). Also, specific inherited variations associated with mtDNA genetic groups (known as mtDNA haplogroups) are associated with lower or higher risk of developing PD. Consequently, mtDNA alterations should now be considered important hallmarks of this neurodegenerative disease. This review provides an update about the role of mtDNA alterations in the physiopathology of PD.

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)0.001
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: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.016
GPT teacher head0.255
Teacher spread0.239 · 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

Citations42
Published2020
Admission routes1
Has abstractyes

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