Development of a High-Throughput Diagnosis Method for Detecting the ALDH2 Gene Using Fingernail DNA
Bibliographic record
Abstract
A clinical method for effective genetic screening of the aldehyde dehydrogenase 2 (ALDH2) gene was developed, using the fingernail as a source of DNA material.A highly effective protease that could solubilize fingernail keratin and inactivate any DNase co-existing in the tissue was obtained by cloning and sequencing the gene for alkaline protease from Bacillus alcalophilus, followed by expression of the gene in Bacillus subtilis.The amino acid sequence of MIB029 protease contained common regions found in four other subtilisin-like proteases.In the fingernails of 113 female university students (average age 20.8 ± 0.7 years; body mass index, 20.4 ±1.6), ALDH2 frequency was 0.66 for the typical Glu homozygote, 0.32 for the heterozygote (Glu487Lys), and 0.020 for the atypical Lys homozygote.Through a questionnaire, it was found that the subjects had not previously received information regarding the relationship between their genetic background and consumption of alcoholic beverages.We found that the genetic single nucleotide polymorphism (SNP) background to alcoholism can be easily detected by collecting fingernails, which is convenient for subjects or patients.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".