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Record W2618043144 · doi:10.1002/humu.23261

Mutation of <i>serine/threonine protein kinase 36</i> ( <i>STK36</i> ) causes primary ciliary dyskinesia with a central pair defect

2017· article· en· W2618043144 on OpenAlexaff
Christine Edelbusch, Sandra Cindrić, Gerard W. Dougherty, Niki T. Loges, Heike Olbrich, Joseph Rivlin, Julia Wallmeier, Petra Pennekamp, Israel Amirav, Heymut Omran

Bibliographic record

VenueHuman Mutation · 2017
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversity of Alberta
FundersDeutsche Forschungsgemeinschaft
KeywordsPrimary ciliary dyskinesiaSitus inversusBiologyCiliumKartagener SyndromeAxonemeMutationMotile ciliumAnatomyLungCell biologyPathologyGeneticsBronchiectasisInternal medicineMedicineGene

Abstract

fetched live from OpenAlex

Primary ciliary dyskinesia (PCD) is a genetic condition of impaired ciliary beating, characterized by chronic infections of the upper and lower airways and progressive lung failure. Defects of the outer dynein arms are the most common cause of PCD. In about half of the affected individuals, PCD occurs with situs inversus (Kartagener syndrome). A minor PCD subgroup including defects of the radial spokes (RS) and central pair (CP) is hallmarked by the absence of laterality defects, subtle beating abnormalities, and unequivocally apparent ultrastructural defects of the ciliary axoneme, making their diagnosis challenging. We identified homozygous loss-of-function mutations in STK36 in one PCD-affected individual with situs solitus. Transmission electron microscopy analysis demonstrates that STK36 is required for cilia orientation in human respiratory epithelial cells, with a probable localization of STK36 between the RS and CP. STK36 screening can now be included for this rare and difficult to diagnose PCD subgroup.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.298
Teacher spread0.280 · 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

Citations71
Published2017
Admission routes1
Has abstractyes

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