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Record W1966828804 · doi:10.1016/j.febslet.2004.07.022

Frataxin overexpressing mice

2004· article· en· W1966828804 on OpenAlexaff
Carlos J. Miranda, Keiichi Ohshima, Marco Tessaro, Jorge Sequeiros, Massimo Pandolfo

Bibliographic record

VenueFEBS Letters · 2004
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de MontréalHôpital Notre-Dame
FundersNational Institute of Neurological Disorders and Stroke
KeywordsFrataxinAtaxiaIron-binding proteinsGenetically modified mouseTransgeneOxidative stressFunction (biology)ChemistryBiologyHaematopoiesisCell biologyBiochemistryGeneNeuroscienceStem cell

Abstract

fetched live from OpenAlex

Friedreich ataxia, the most common autosomal recessive ataxia, is caused by frataxin deficiency. Reduction of frataxin has been associated with iron accumulation and sensitivity to iron induced oxidative stress. To better understand the function of frataxin, transgenic mice (tgFxn) overexpressing human frataxin were generated. Iron metabolism parameters in tgFxn were normal and no signs of ataxia or other obvious abnormalities were observed, indicating that overexpression of frataxin in mouse is innocuous. Several hypotheses for frataxin function were evaluated in tgFxn mice. In particular, we observed that TgFxn mice show an altered response during hematopoietic differentiation, suggesting that frataxin may directly affect heme synthesis.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.033
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.026
GPT teacher head0.251
Teacher spread0.225 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2004
Admission routes1
Has abstractyes

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