Prevalence of Serum Antibodies against Six Leptospira Serovars in Buffaloes in Tabriz, Northwestern Iran
Bibliographic record
Abstract
Leptospirosis is an important zoonotic infectious and its prevalence is unknown in buffalo in Iran particularly in Tabriz, northwest of the country. To survey the prevalence of Leptospira infection in buffaloes in Tabriz, blood samples were collected from 85 female buffaloes slaughtered in Tabriz industrial slaughterhouse from December 2008 to November 2009. Sera were stored at -20°C until they were examined. Sera were initially screened at serum dilution of 1:100 against six live antigens of Leptospira interrogans, Pomona, Canicola, Hardjo, Ballum, Icterohaemorrhagiae and Grippotyphosa by using the microscopic agglutination test (MAT).The samples were considered positive if 50% or more of agglutination of leptospire in a dilution tests serum of l:100 were observed. 30 serums (35.29%) at dilution 1:100 were positive against 1 or 2 of serovars. the highest prevalent serovar in buffalo was Grippotyphosa (51.3%), and fallowed whit Pomona (29.7%), canicola (10.8%) and Icterohaemorrhagiae (8.1%). All of the samples were seronegative for serovar Ballum and Hardjo. Statistical analysis of the results showed that the rates of the infection in the autumn-winter and spring–summer didn’t have significant difference (p > 0/05). The rate of the infection has been statistically increased with the aging (p<0/05) and the animals with 3 and 4 pair’s permanent teeth had the highest infection rates. The serological infection rate in buffaloes in Tabriz is relatively high and it appears that it is because of living type of buffaloes in water and swamp, thus consequently the preventive methods must be applied to control of the disease.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".