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Record W4405942403 · doi:10.1080/01913123.2024.2447853

Heterozygous missense mutation of the fibrinogen gene associated with cryptogenic liver disease in a 15-months-old Canadian caucasian child

2024· article· en· W4405942403 on OpenAlexaffabout
Mohit Kehar, Robert J. Klaassen, Consolato Sergi

Bibliographic record

VenueUltrastructural Pathology · 2024
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsHypofibrinogenemiaMissense mutationPathologyLiver biopsyFibrinogenCoagulopathyCompound heterozygosityLiver diseaseAfibrinogenemiaBiologyInternal medicineMedicineMutationBiopsyGeneticsGene

Abstract

fetched live from OpenAlex

Hepatic fibrinogen storage disease is an uncommon autosomal dominant hereditary illness marked by hypofibrinogenemia and the accumulation of variant fibrinogen in the hepatic endoplasmic reticulum. We present an asymptomatic 15-month-old male with elevated liver enzymes. Test results indicate hypofibrinogenemia. The liver biopsy revealed circular eosinophilic inclusion bodies within the hepatocyte cytoplasm. After diastase pretreatment, the inclusion bodies did not stain using the periodic acid – Schiff procedure. Ultrastructural examination revealed the characteristic fibrinogen storage curvilinear inclusions. Sequence analysis using the Blueprint Genetics (BpG) FLEX Bleeding Disorder/Coagulopathy Panel identified a heterozygous missense variant FGG c.1075 G>C, p. (Gly359Arg). Thus, the patient was diagnosed with hepatic fibrinogen storage disease. Our findings suggest that in patients with asymptomatic elevated liver enzymes presenting with unanticipated hypofibrinogenemia, hepatic fibrinogen storage disorder must be included in the differential diagnosis. Furthermore, our results underscore the significance of molecular diagnosis in patients diagnosed with cryptogenic liver disease.

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 score0.713
Threshold uncertainty score0.571

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.204
Teacher spread0.196 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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