Detection of VPS13B gene mutation responsible for trapped neutrophil syndrome in selected dog breeds used for assistance activities
Bibliographic record
Abstract
This bachelor thesis Detection of VPS13B gene mutation responsible for Trapped neutrophil syndrome in selected dog breeds used for assistance activities starts with theoretical part and continue with experimental part, which had done in Department of genetics and breeding. The theoretical part is focused on Trapped neutrophil syndrome and Cohen syndrome. Both of theese syndromes are caused by mutation of same gene and this is the reason, why a dog is a suitable genetic model for human disease research. Based on the theoretical part is obvious that Trapped neutrophil syndrome is a autosomal recessive genetic disease and is caused by deletion of 4 bases (GTTT) on 13th chromosome in 19th exon. This mutation is only in border collie breed. The Trapped neutrophil syndrome causes very serious problems and for individuals theese problems may be letal. If they survive, they have a very poor quality life. They have diarrhoea, pyrexia, vomite and have a typical facial ferret-like snout. The experimental part is focused on isolation DNA from buccal mucosa of border collie breed, golden retriever, labrador retriever and Nova Scotia duck tolling retriever, than it is focused on design PCR markers and sequencing PCR amplicons. The experimental results had confirmed hypothesis that the causal mutation is affected by pedigree and it is easy to identificate it by sequencing PCR amplicons.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.011 | 0.002 |
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".