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Record W6884644316 · doi:10.11575/prism/33006

Wolfram Syndrome: A Case Report and Review of Clinical Manifestations, Genetics Pathophysiology, and Potential Therapies

2018· other· en· W6884644316 on OpenAlexfundno aff

Bibliographic record

VenueUniversity of Calgary · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsWolfram syndromeDiabetes mellitusGestational diabetesPathophysiologyNatural historyAtrophyType 2 diabetesMutation

Abstract

fetched live from OpenAlex

Background. Classical Wolfram syndrome (WS) is a rare autosomal recessive disorder caused by mutations in WFS1, a gene implicated in endoplasmic reticulum (ER) and mitochondrial function. WS is characterized by insulin-requiring diabetes mellitus and optic atrophy. A constellation of other features contributes to the acronym DIDMOAD (Diabetes Insipidus, Diabetes Mellitus, Optic Atrophy, and Deafness). This review seeks to raise awareness of this rare form of diabetes so that individuals with WS are identified and provided with appropriate care. Case. We describe a woman without risk factors for gestational or type 2 diabetes who presented with gestational diabetes (GDM) at the age of 39 years during her first and only pregnancy. Although she had optic atrophy since the age of 10 years, WS was not considered as her diagnosis until she presented with GDM. Biallelic mutations in WFS1 were identified, supporting a diagnosis of classical WS. Conclusions. The distinct natural history, complications, and differences in management reinforce the importance of distinguishing WS from other forms of diabetes. Recent advances in the genetics and pathophysiology of WS have led to promising new therapeutic considerations that may preserve β-cell function and slow progressive neurological decline. Insight into the pathophysiology of WS may also inform strategies for β-cell preservation for individuals with type 1 and 2 diabetes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.463
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.280
Teacher spread0.261 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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