Prevalence of Black Quarter in Association with Patho-Morphological Alterations in Affected Tissues at Different Zones of Punjab-Pakistan
Bibliographic record
Abstract
Background: Blackleg or Black Quarter (BQ) is a serious bacterial disease caused by Clostridium chauvoei. It causes edematous and gaseous changes in skeletal muscles of animals. The study was designed to find prevalence of BQ in 6 districts of Punjab, Pakistan from June 2018 to June 2019.Methods: Animals were randomly monitored, and selected in each union council regardless of age, sex and species, but lameness and hyperthermia were the selection parameters. A proforma was used to record the experimental readings of each animal. A total of 1500 swab samples from bovines (cattle and buffaloes) were processed through conventional PCR and culture sensitivity tests to examine the comparative diagnostic efficacy and suitability of the test.Results: Sensitivity and specificity of culture tests were 87.6% and 34.19% respectively, whereas PCR demonstrated 81% and 47.3% results for the said aspects, respectively. Alpha toxin gene (Ccta) was amplified at 52.2oC yielding an amplicon size of 1400 base pairs. Area wise and season wise prevalence of each animal was also determined. The prevalence of BQ in cattle was significantly higher (P<0.05) in Muzaffargarh (25.6%), Layyah (24.8%), Rahim Yar Khan (23.2%), and Bhakkar (29.6%) that belonged to the arid and dessert zones of Punjab-Pakistan whereas, it was non-significant (P > 0.05) in Lahore (0%) and Nankana Sahib (8%) which belonged to the canal irrigated zones.Conclusion: There was higher prevalence of BQ in different areas of Punjab, Pakistan that show the higher risk of disease transmission. A systematic surveillance system is essential to regularly monitor the disease incidence and prevalence in these areas of Pakistan.Keywords: Black Quarter; Prevalence; Pathological; Ruminants; Zones
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".