High sero-prevalence of caseous lymphadenitis identified in slaughterhouse samples as a consequence of deficiencies in sheep farm management in the state of Minas Gerais, Brazil

<p>Abstract</p> <p>Background</p> <p>Caseous lymphadenitis (CLA), caused by <it>Corynebacterium pseudotuberculosis</it>, is one of the most important diseases of sheep and goats, causing considerable economic losses for herd owners.</p> <p>Results</p> <p>We assessed the seroprevalence of infection with <it>C. pseudotuberculosis </it>in 805 sheep from 23 sheep farms that supply slaughterhouses in the state of Minas Gerais; we also analyzed management practices that could be associated with CLA occurrence, used on these and nearby farms that also supplied animals to the slaughterhouse (n = 60). The serum samples for assaying CLA infection were taken at the slaughterhouse. Frequency of infection with <it>C. pseudotuberculosis </it>was estimated at 43.7%, and farm frequency was estimated at 100%. Management practices were analyzed through a questionnaire. All farmers (60/60) had extensive/semi-extensive rearing system; 70.0% (42/60) identified sheep individually; 11.7% (7/60) had periodical technical assistance; 41.7% (25/60) disinfected the facilities; 86.7% (52/60) used barbed wire fences and did not implement adequate CLA control measures; only 11.7% (7/60) of breeders reported vaccination against <it>C. pseudotuberculosis</it>; 13.3% (8/60) took note of animals with clinical signs of CLA; 1.7% (1/60) opened and sanitized abscesses, and isolated the infected animals; 10.0% (6/60) knew the zoonotic potential of this disease and 1.7% (1/60) of the farmers culled animals in case of recurrence of abscesses.</p> <p>Conclusions</p> <p>It can be concluded that <it>C. pseudotuberculosis </it>infection is widely spread in sheep flocks in Minas Gerais state in Brazil and that there is a lack of good management measures and vaccination, allowing transmission of this infectious agent throughout the production network.</p

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

BMC Veterinary Research

p. 1-5Background Caseous lymphadenitis (CLA), caused by Corynebacterium pseudotuberculosis, is one of the most important diseases of sheep and goats, causing considerable economic losses for herd owners. Results We assessed the seroprevalence of infection with C. pseudotuberculosis in 805 sheep from 23 sheep farms that supply slaughterhouses in the state of Minas Gerais; we also analyzed management practices that could be associated with CLA occurrence, used on these and nearby farms that also supplied animals to the slaughterhouse (n = 60). The serum samples for assaying CLA infection were taken at the slaughterhouse. Frequency of infection with C. pseudotuberculosis was estimated at 43.7%, and farm frequency was estimated at 100%. Management practices were analyzed through a questionnaire. All farmers (60/60) had extensive/semi-extensive rearing system; 70.0% (42/60) identified sheep individually; 11.7% (7/60) had periodical technical assistance; 41.7% (25/60) disinfected the facilities; 86.7% (52/60) used barbed wire fences and did not implement adequate CLA control measures; only 11.7% (7/60) of breeders reported vaccination against C. pseudotuberculosis; 13.3% (8/60) took note of animals with clinical signs of CLA; 1.7% (1/60) opened and sanitized abscesses, and isolated the infected animals; 10.0% (6/60) knew the zoonotic potential of this disease and 1.7% (1/60) of the farmers culled animals in case of recurrence of abscesses. Conclusions It can be concluded that C. pseudotuberculosis infection is widely spread in sheep flocks in Minas Gerais state in Brazil and that there is a lack of good management measures and vaccination, allowing transmission of this infectious agent throughout the production network

Small Ruminant Research

Trabalho completo: completo restrito, p.86–91Corynebacterium pseudotuberculosis is the etiologic agent of caseous lymphadenitis, which is a serious, economically important problem for sheep production. We examined the seroprevalence of infection by C. pseudotuberculosis and possible risk factors associated with caseous lymphadenitis in sheep herds of the state of Minas Gerais, Brazil. Samples were collected from 642 sheep from 97 farms. Sera of all of the sheep were tested with ELISA for antibodies against C. pseudotuberculosis. A questionnaire was applied to gather data on the farm, the sheep herd, the farmer, and individual animal data (breed, sex and age). This is the first sero-epidemiological survey for caseous lymphadenitis in sheep herds in Minas Gerais. We found a high real prevalence, much higher than that suggested from information obtained with the questionnaire, which points to the scarcity of vaccination against caseous lymphadenitis in the sample evaluated. Only a small proportion of the farmers declared that cases of this disease were present in their flocks. The frequency of seropositive sheep varied significantly with breed (χ2 test, P = 0.021). Age group also significantly affected the percentage of seropositivity (χ2 test, P = 0.049), the highest frequency being found in adult animals (more than 12 months old), when compared to the 5–12 months old group (χ2 test, P = 0.021). The prevalence of infection with C. pseudotuberculosis in sheep in the state of Minas Gerais was estimated to be 70.9% (95% confidence interval (CI): 64.7–77.0%) and the prevalence of infected flocks being 95.9% (95% CI: 89.8–98.9%). We concluded that C. pseudotuberculosis infection is widely disseminated in sheep flocks in Minas Gerais and that caseous lymphadenitis control and eradication programs are necessary in this state