DILATED CARDIOMYOPATHY IN THE DOMESTIC DOG (CANIS LUPUS FAMILIARIS) – IN SILICO ANALYSIS OF SELECTED GENES
Bibliographic record
Abstract
Dilated cardiomyopathy (DCM) is a progressive loss of contractility of the heart muscle as the disease progresses. It causes a decrease in the heart’s minute capacity, i.e. the volume of blood pumped by the heart into the blood vessels in one minute. DCM leads to congestive heart failure and sudden death. The aim of this study was to identify in silico genes within which mutations have occurred that may cause DCM in the domestic dog (Canis lupus familiaris), to identify dog breeds at risk, and to propose breed-specific diagnostic molecular tests. For bioinformatic analyses of sequences retrieved from GenBank (NC_006587.3 – FGGY, NC_006583.3 – DCC and CM023383.1 – PDE3B) and from scientific publications (PDK4 – from patent publication number US 2011/0307965 A1 and STRN – Meurs et al. 2010), the following programs were used: Primer3 v. 0.4.0, NEBcutter v. 2.0 and BLAST. Based on literature data, domestic dog breeds such as Doberman Pinscher, Boxer, Portuguese Water Dog, Newfoundland, Irish Wolfhound and Great Dane were found to be among the breeds with the highest risk of DCM. In order to identify relevant mutations in the genes studied (FGGY, DCC, PDE3B, PDK4 and STRN) that may cause the occurrence of dilated cardiomyopathy, the use of specific restriction enzymes has been proposed in molecular diagnostic tests: BmiI for mutations in the PDK4 gene and Tth111I for SNPs in the FGGY gene (Doberman Pinscher) and TaqI for SNPs in the DCC gene and HinfI for SNPs in the PDE3B gene (Irish Wolfhound). This work, may serve as a prelude to analysis for targeted genetic testing to enable correct diagnosis of DCM in asymptomatic dogs
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".