Molecular genetic diagnostic techniques in choroideremia.
Bibliographic record
Abstract
PURPOSE: To optimize and streamline molecular genetics techniques in diagnosing choroideremia (CHM). METHODS: PCR primers were designed for exons 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, and 15 of the CHM gene. Each PCR protocol was optimized so that all exons could be amplified with the same component ratio and PCR conditions. Sense and antisense primers were tested for their ability to be used as sequencing primers. Fibroblast cells were cultured, and an immunoblot analysis was performed to detect the presence or absence of Rab escort protein 1 (REP-1) in a suspected CHM patient sample when no mutation was detected with sequencing. Multiplex ligation-dependent probe amplification (MLPA) of the CHM gene was performed and used to detect deletions and duplications in affected males and female carriers. RNA analysis using cDNA was used to detect the presence or absence of the CHM transcript and to search for splice defects. RESULTS: The newly designed PCR primers allow for more efficient PCR preparation and sequencing to detect point mutations in affected males and female carriers. Immunoblot successfully detects the absence of REP-1 in a CHM patient. MLPA identifies deletions and duplications spanning multiple exons in the CHM gene. RNA analysis aids in detecting splice variants. CONCLUSIONS: The development of new molecular biology techniques and ongoing optimization of existing methods allows for an improved integrated approach to confirm CHM diagnosis and carrier status in consideration of patient family history and available patient sample materials. CHM can be confirmed with an immunoblot assay. To detect the molecular cause of CHM, an examination of the genomic DNA or the mRNA must be performed. Presymptomatic carriers with no identifiable fundus signs can be identified only through molecular analysis of genomic DNA or through quantitative assays.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".