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Record W3165681012 · doi:10.1080/24745332.2020.1770638

Novel folliculin gene mutation and an elevated serum vascular endothelial growth factor-D level in the context of cystic lung disease

2020· article· en· W3165681012 on OpenAlexaff
Nathan Hambly, Anurag Bhalla, Gianni R. Lorello, Chantal F. Morel, V. Hoffstein

Bibliographic record

VenueCanadian Journal of Respiratory Critical Care and Sleep Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicTuberous Sclerosis Complex Research
Canadian institutionsSt. Michael's HospitalUniversity Health NetworkToronto Western HospitalUniversity of TorontoMcMaster University
Fundersnot available
KeywordsFolliculinBirt–Hogg–Dubé syndromeLymphangioleiomyomatosisContext (archaeology)PathologyLungPneumothoraxMedicineTuberous sclerosisGermline mutationMutationCancer researchBiologyInternal medicineGeneGeneticsAnatomy

Abstract

fetched live from OpenAlex

Birt-Hogg-Dubé syndrome (BHD) is a rare autosomal dominant genetic disorder characterized by the development of benign cutaneous neoplasms, renal tumors, and pulmonary cysts. Caused by mutations in the folliculin (FLCN) gene on chromosome 17, the pulmonary manifestations observed in BHD include multiple subpleural cysts that are frequently associated with pneumothorax. Diffuse cystic lung disease is also commonly encountered in lymphangioleiomyomatosis (LAM), either in isolation or in the context of tuberous sclerosis complex (TS). The diagnosis of BHD is confirmed by identifying pathogenic FLCN germline mutations. Modern evidence, however, supports using serum vascular endothelial growth factor-D (VEGF-D) levels in differentiating LAM from other cystic lung diseases, including BHD, with high specificity. This case report describes the unique finding of an elevated VEGF-D serum level (1290 pg/ml) in a patient with cystic lung disease, bilateral pneumothorax and a novel disease-causing mutation (E280X) in the FLCN gene.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
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 head0.088
GPT teacher head0.328
Teacher spread0.240 · 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 designObservational
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
Published2020
Admission routes1
Has abstractyes

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