Molecular Detection and Characterization of Streptococcus suis Isolated from Pneumonic Lungs of Pigs
Bibliographic record
Abstract
Background: Among various diseases, respiratory disease is considered a leading cause of mortality in pigs. Streptococcus suis affects respiratory tract and causes pneumonia as an opportunistic pathogen, that impairs animal health and lowers individual and herd performance in swine. Therefore, it becomes important to have an insight of bacterial pneumonia with special reference to Streptococcus suis in pig, so that control measures could be practiced effectively. Methods: Detailed post mortem examination was carried out on 180 pigs. Bacterial isolation was carried out from 127 (70.55%) lungs samples with pneumonic lesions. Further, suspected colonies of S. suis were subjected to Polymerase Chain Reaction for detection of glutamate dehydrogenase gene. Phylogenetic analysis was carried out for the positive S. suis samples. Results: Bacteria isolated were Pasteurella multocida (34.44%), S. suis (28.89%), E. coli (16.67%), Staphylococcus spp. (14.44%), Klebsiella spp. (3.33%) and Salmonella spp. (2.22%). Out of 26 suspected S. suis colonies subjected to Polymerase Chain Reaction, 17 isolates with amplicon size 688 bp were confirmed to be positive for glutamate dehydrogenase gene. The Phylogenetic analysis of glutamate dehydrogenase gene of S. suis from pigs of Assam showed percent identity above 99% with Germany, Canada and China strain of S. suis.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".