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Record W4308569227 · doi:10.1186/s42269-022-00914-w

Neuroradiological findings in a young patient bearing a new single mitochondrial gene mutation (case report)

2022· article· en· W4308569227 on OpenAlexaff
Paolo La Montanara, Annamaria Albergo, Roberto Castellana, Concetta Fiorentini, Caterina Romano, Annalisa Rossiello, Moritz Steinruecke, Giuseppe Vella

Bibliographic record

VenueBulletin of the National Research Centre/Bulletin of the National Research Center · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsConversant (Canada)
Fundersnot available
KeywordsLeigh diseaseMitochondrial DNAMitochondrial diseaseMutationExternal ophthalmoplegiaGeneticsBiologyGenePathologyGene mutationMedicine

Abstract

fetched live from OpenAlex

Abstract Background We present the clinical, MRI and CT findings in a case of a new mitochondrial genome mutation (tRNA arginine gene), characterized by brain calcifications which are indicative of Kearns–Sayre syndrome (KSS). Some radiological features resembled those of Fahr’s disease (affecting the PDGFRB gene). Case presentation A 36-year-old male presented some typical clinical features of KSS, including onset before 20 years of age, pigmentary retinopathy, progressive external ophthalmoplegia and ptosis. However, the hallmark radiological finding of diffuse calcifications in the nuclear ganglia resembles some cases related to the PDGRFB mutation. Genetic investigation revealed a new mutation in the mitochondrial tRNA-arginine gene. Conclusions Brain calcifications are a common feature of mitochondrial diseases, but little is known about their pathophysiology. Here, we describe radiological similarities between a new mitochondrial DNA mutation and other genetic conditions, which are related to Fahr’s disease. These similarities could provide new insights into putative genotype–phenotype correlations.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.074
GPT teacher head0.342
Teacher spread0.269 · 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 designCase report
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

Citations0
Published2022
Admission routes1
Has abstractyes

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