Exon Sequencing for the Presence of Late Onset Tay‐Sachs
Bibliographic record
Abstract
Tay‐Sachs is a disease that causes rapid developmental stagnation and death in infants. It primarily affects people of French Canadian, Cajun, and Ashkenazi Jewish descent. In recent years an alternate form of the disease, called late onset Tay‐Sachs (LOTS), has been described. LOTS is caused by the inheritance of one null allele and a pseudodeficiency allele of the hexosaminidase A ( HEXA) gene. The mutation rate of the pseudodeficiency is not well known. The aim of this experiment was to examine the DNA of the descendants of an Ashkenazi Jewish individual who was believed to have undiagnosed LOTS. The purpose of this case study is to attempt to confirm this suspected diagnosis by identifying potential mutations in the family members. DNA of the HEXA gene from three family members of the suspected LOTS patient (wife and 2 daughters) and one control set (unrelated female) was sequenced. The sequences were aligned and compared both by hand and using the NCBI Blast database and the Benchling tool. No known mutations or confirmed novel mutations have been found in all fourteen exons sequenced. Currently re‐sequencing of some regions that showed potential single nucleotide polymorphisms (SNPs) as well as sequencing the promoter region of the gene is underway. If a mutation is confirmed this research could help pave the way for further genetic testing in the broader population in order to fully grasp the prevalence of LOTS pseudodeficiency alleles within the Ashkenazi population. Support or Funding Information Hamline Undergraduate Collaborative Research Ridgeway Forum Fund This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".