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Record W4410557387 · doi:10.3389/fped.2025.1601409

Emerging therapeutic strategies for cystinosis

2025· review· en· W4410557387 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Pediatrics · 2025
Typereview
Languageen
FieldMedicine
TopicBiomedical Research and Pathophysiology
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsCystinosisCysteamineMedicineBench to bedsideIntensive care medicineBioinformaticsPediatricsInternal medicineCystineBiology

Abstract

fetched live from OpenAlex

For over 40 years, oral cysteamine has been the mainstay of therapy for cystinosis. While it has been of great benefit, slowing organ deterioration and prolonging life, cysteamine is not well tolerated and may not rescue all pathogenic mechanisms driving the disease. Of late, research groups around the world have been pursuing various novel therapeutic strategies. Here we select just four of many examples - two that address events downstream of the missing Cystinosin protein and two that aim to address the upstream CTNS mutation. Our aim is to update the cystinosis community on some of the exciting work in progress. We have drawn from preliminary reports and oral presentations at cystinosis meetings. While each approach requires further work and critical analysis, the sheer number and variety of these potential therapies is cause for hope.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.939
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.391
Teacher spread0.347 · 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