Urine-Derived Epithelial Cell Lines: A New Tool to Model Fragile X Syndrome (FXS)
Bibliographic record
Abstract
Fragile X syndrome (FXS) is an X-linked neurodevelopmental condition associated with intellectual disability and behavioral problems due to the lack of the Fragile X mental retardation protein (FMRP), which plays a crucial role in synaptic plasticity and memory. A desirable in vitro cell model to study FXS would be one that can be generated by simple isolation and culture method from a collection of a non-invasive donor specimen. Currently, the various donor-specific cells can be isolated mainly from peripheral blood and skin biopsy. However, they are somewhat invasive methods for establishing cell lines from the primary subject material. In this study, we characterized a cost-effective and straightforward method to derive epithelial cell lines from urine samples collected from participants with FXS and healthy controls (TD). The urine-derived cells expressed epithelial cell surface markers via fluorescence-activated cell sorting (FACS). We observed inter, and the intra-tissue CGG mosaicism in the PBMCs and the urine-derived cells from participants with FXS potentially related to the observed variations in the phenotypic and clinical presentation FXS. We characterized these urine-derived epithelial cells for FMR1 mRNA and FMRP expression and observed some expression in the lines derived from full mutation mosaic participants. Further, FMRP expression was localized in the cytoplasm of the urine-derived epithelial cells of healthy controls. Deficient FMRP expression was also observed in mosaic males, while, as expected, no expression was observed in cells derived from participants with a hypermethylated full mutation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".