Primary ciliary dyskinesia phenotypes and correlation with genotype
Bibliographic record
Abstract
PURPOSE OF REVIEW: Primary ciliary dyskinesia is a rare, inherited disease, and over 60 genes have been linked to motile ciliopathies. During the past quarter century, our understanding of the complex genetics and biological function of motile cilia has greatly advanced. RECENT FINDINGS: Our growing knowledge of genetics and pathophysiology of primary ciliary dyskinesia has yielded insights into novel clinical features and genotype-phenotype relationships in motile ciliopathies. Children with biallelic CCDC39 or CCDC40 mutations have greater lung disease, related to both cilia motility-dependent and motility-independent effects. Pathogenic variants in genes involved in cilia generation, like CCNO , are also associated with more severe lung disease. Conversely, people who have defects in other genes, like DHAH11 and RSPH1 , have less severe lung disease, possibly related to residual ciliary motility. Finally, a growing number of primary ciliopathies are associated with abnormal motile cilia ultrastructure and function, and specific pathogenic variants can lead to distinct clinical presentations, best illustrated by structure-function studies in TUBB4B . SUMMARY: These findings have yielded new insights into the clinical heterogeneity of motile ciliopathies, thus broadening their clinical spectrum. Additional research to elucidate the underlying pathophysiology in these overlapping conditions is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".