A reference to assess cilium phenotype in ciliopathy patients
Bibliographic record
Abstract
The cilium presence and constitution of human fibroblasts are accessible and measurable cellular markers for ciliary homeostasis. Fibroblasts are most commonly generated from skin biopsies and comparison of the ciliary phenotype of patients vs controls can be used to identify or evaluate a potential ciliary defect. Subtle differences are difficult to detect, but critical to establish a genotype-phenotype correlation. The aim of this study is to establish the parameters to detect subtle differences in cilium phenotype, and develop a reference for cilium phenotype that can be used to improve diagnosis and prognosis of ciliopathies. We derived fibroblast cell lines from skin biopsies from ciliopathy patients and healthy controls. Ciliogenesis was induced by adding culture medium containing 0.2% FCS prior to immunocytochemistry. The cells were stained with antibodies against different ciliary proteins to study cilium presence, length, morphology, and intraflagellar transport proteins. Fibroblasts from three controls and five patients with different ciliopathies were studied so far. We found major and subtle differences in cilium frequency and phenotype in patients and subtle differences in controls, partly influenced by the culturing conditions. This suggests that there is a significant natural and experimental variation that needs to be taken into account when evaluating the statistical relevance of such findings. We detected major and subtle differences in cilium phenotype between patients. In addition, we found a natural variation in the cilium phenotype of control fibroblasts. By including more samples, we intend to improve and expand this reference for ciliopathy-associated cilium phenotypes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".