PCR detection of pathogenic <i>Leptospira</i> genomospecies targeting putative transcriptional regulator genes
Bibliographic record
Abstract
The genus Leptospira comprises multiple genomospecies that demonstrate varied pathogenic potential. The availability of rapid and precise diagnostic procedures to differentiate pathogenic from nonpathogenic Leptospira spp. is therefore essential to prevent an otherwise easily treatable malaise from developing into a life-threatening disease. In this report, we conducted an investigation on the diagnostic potential of Leptospira genes encoding putative transcriptional regulators. While PCR primers derived from transcriptional regulator gene la1137 recognized all 24 pathogenic Leptospira strains representing seven species, those from la1937, la3231, la3825, and la4130 detected 19 of the 24 Leptospira strains. However, none of these primers reacted with four nonpathogenic Leptospira species or other common bacteria. The putative transcriptional regulator genes la1137, la1937, la3231, la3825, and la4130 are present in pathogenic Leptospira strains, making them potential targets for diagnostic applications. Further characterization of these genes and their proteins may help elucidate the molecular mechanisms of leptospiral virulence and pathogenicity and pave the way for potential development of novel control strategies against leptospirosis.
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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) | 0.001 | 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) | 0.001 | 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".