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Record W4413164614 · doi:10.1016/j.neurot.2025.e00665

PANK activators for the treatment of pantothenate kinase-associated neurodegeneration

2025· article· en· W4413164614 on OpenAlexaff
Jessica Regan, Anasuya Pal, Choukri Ben Mamoun

Bibliographic record

VenueNeurotherapeutics · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeurological diseases and metabolism
Canadian institutionsViron Therapeutics (Canada)
Fundersnot available
KeywordsNeurodegenerationNeurologyMedicineNeuroscienceInternal medicinePsychologyDisease

Abstract

fetched live from OpenAlex

Pantothenate kinase-associated neurodegeneration (PKAN) is a rare, progressive genetic disorder caused by mutations in the human pantothenate kinase 2 gene, manifesting as a debilitating neurodegenerative condition, leading to early immobility and often death by early adulthood. No established therapy exists for PKAN, with current treatment directed towards symptom management. We hypothesize that activation of the human PANK3 enzyme would result in stimulation of CoA production in PANK2 mutated cells, thus representing an ideal treatment for PKAN.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.066
GPT teacher head0.323
Teacher spread0.257 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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