Immunofluorescence Analysis and Diagnosis of Primary Ciliary Dyskinesia with Radial Spoke Defects
Bibliographic record
Abstract
Primary ciliary dyskinesia (PCD) is a genetically heterogeneous recessive disorder caused by several distinct defects in genes responsible for ciliary beating, leading to defective mucociliary clearance often associated with randomization of left/right body asymmetry. Individuals with PCD caused by defective radial spoke (RS) heads are difficult to diagnose owing to lack of gross ultrastructural defects and absence of situs inversus. Thus far, most mutations identified in human radial spoke genes (RSPH) are loss-of-function mutations, and missense variants have been rarely described. We studied the consequences of different RSPH9, RSPH4A, and RSPH1 mutations on the assembly of the RS complex to improve diagnostics in PCD. We report 21 individuals with PCD (16 families) with biallelic mutations in RSPH9, RSPH4A, and RSPH1, including seven novel mutations comprising missense variants, and performed high-resolution immunofluorescence analysis of human respiratory cilia. Missense variants are frequent genetic defects in PCD with RS defects. Absence of RSPH4A due to mutations in RSPH4A results in deficient axonemal assembly of the RS head components RSPH1 and RSPH9. RSPH1 mutant cilia, lacking RSPH1, fail to assemble RSPH9, whereas RSPH9 mutations result in axonemal absence of RSPH9, but do not affect the assembly of the other head proteins, RSPH1 and RSPH4A. Interestingly, our results were identical in individuals carrying loss-of-function mutations, missense variants, or one amino acid deletion. Immunofluorescence analysis can improve diagnosis of PCD in patients with loss-of-function mutations as well as missense variants. RSPH4A is the core protein of the RS head.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".