Identification, Molecular Characterization and Alternative Splicing of Three Novel Members of the Canine Kallikrein (Klk)-related Peptidase Family.
Bibliographic record
Abstract
BACKGROUND/AIM: Kallikrein-related peptidases (KLKs) comprise a serine protease family with prominent roles in tissue physiology and disease pathogenesis, including cancer. Previously, we have characterized canine Klk4-10 and -14. Herein, we continue our efforts by characterizing three novel members of the canine family, i.e. Klk11-13, and investigating their expression in mammary cancer. MATERIALS AND METHODS: Reverse transcription-polymerase chain reaction (RT-PCR) and DNA sequencing were used for investigating the expression and determining the nucleotide sequence of all transcripts identified, respectively. RESULTS: It was demonstrated that (i) unlike other Klks, (CANFA)Klk12 probably possesses a non-AUG translation initiation codon, (ii) all three Klks undergo alternative splicing, with exon 2 and 3 concurrent elimination serving as the most prominent event, (iii) all transcripts identified were detected in both tumor and normal tissues, yet with different frequencies. CONCLUSION: Having completed this work, Klk15 is the only gene remaining to experimentally resolve the entire canine Klk family. Our data lay sufficient groundwork for validation studies and await further incorporation into genetic/evolutionary studies with translational impact.
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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 | 0.000 | 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) | 0.001 | 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 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".