Carvedilol in dogs with dilated cardiomyopathy

BACKGROUND: Dilated cardiomyopathy (DCM) is characterized by reduced systolic function, heightened sympathetic tone, and high morbidity and mortality. Little is known regarding the safety and efficacy of beta-blocker treatment in dogs with DCM. HYPOTHESIS: Carvedilol improves echocardiographic and neurohormonal variables in dogs with DCM over a 4-month treatment period. METHODS: Prospective, placebo-controlled, double-blinded randomized study. Dogs with DCM underwent echocardiography, ECG, thoracic radiographs, and neurohormonal profiling, followed by titration onto carvedilol (0.3 mg/kg q12h) or placebo over a 4-week period and subsequently received 3 months of therapy. Primary study endpoints included left ventricular volume and function. RESULTS: Sixteen dogs received carvedilol and 7 received placebo. At study end, 13 carvedilol dogs and 5 placebo dogs were alive. There was no difference in the mean percentage change in left ventricular volume at end-diastole (LVVd), left ventricular end-systolic volume (LVVs), and ejection fraction (EF) between treatment groups, suggesting that both groups experienced similar amounts of disease progression. Carvedilol treatment did not result in significant changes in neurohormonal activation, radiographic heart size, heart rate, or owner perceived quality-of-life. Baseline B-type natriuretic peptide (BNP) predicted dogs in the carvedilol-treated group that maintained or improved their EF over the study duration. CONCLUSIONS AND CLINICAL IMPORTANCE: Carvedilol administration did not improve echocardiographic or neurohormonal indicators of heart function. The lack of effect may be related to severity of disease, carvedilol dose, or brevity of follow-up time. Statistical power of the present study was adversely affected by a high fatality rate in study dogs and small sample size.     

Risk factors associated with sero-positivity to Toxoplasma gondii in captive neotropical felids from Brazil

From September 1995 to February 2001, blood samples were collected from 865 neotropical felids belonging to 8 different species. These animals were housed in 86 institutions located in 78 cities of 20 Brazilian states. Our goal was to identify the risk factors associated with sero-positivity to Toxoplasma gondii in captive neotropical felids from Brazil. All serum samples were tested by the modified agglutination test (MAT), using formalin-fixed whole tachyzoites and mercaptoethanol. For each animal an individual questionnaire was filled with questions about tattoo number, felid species, age, sex, origin, number of animals in the group, introduction of new animals in the group, time in the institution, eating meat previously frozen for a period <7 days in the last 6 months, eating meat of run-over or euthanized animals in the last 6 months, predation of rodents or birds in the last 6 months and presence of domestic cats near the enclosures in the last 6 months. The total sero-prevalence was 55% (95% CI: 52%, 57%). We estimated a prevalence of 46% (95% CI: 40%, 54%) for jaguarundi (Puma yagouaroundi); 58% (95% CI: 53%, 63%) for ocelot (Leopardus pardalis); 50% (95% CI: 45%, 56%) for oncilla (L. tigrinus); 54% (95% CI: 46%, 62%) for margay (L. wiedii); 12% (95% CI: 4%, 31%) for Pampas-cat (L. colocolo); 83% (95% CI: 65%, 93%) for Geoffroy's-cat (L. geoffroyi); 64% (95% CI: 50%, 68%) for jaguar (Panthera onca) and 48% (95% CI: 42%, 54%) for puma (Puma concolor). Multiple logistic regression was used to evaluate the association between the variables in the questionnaire and sero-positivity to T. gondii. We concluded that the independent risk factors for toxoplasmosis were: age >3 years (OR = 4.75 [2.75; 8.2]), eating meat previously frozen for a period <7 days (OR = 2.23 [1.24; 4.01]), and consumption of animals that were run-over or euthanized (OR = 1.64; [1.14; 2.37]).     

Detection of Ecballium elaterium in hedgerow olive orchards using a low-cost uncrewed aerial vehicle and open-source algorithms

BACKGROUND

Ecballium elaterium (common name: squirting cucumber) is an emerging weed problem in hedgerow or superintensive olive groves under no tillage. It colonizes the inter-row area infesting the natural or sown cover crops, and is considered a hard-to-control weed. Research in other woody crops has shown E. elaterium has a patchy distribution, which makes this weed susceptible to design a site-specific control strategy only addressed to E. elaterium patches. Therefore, the aim of this work was to develop a methodology based on the analysis of imagery acquired with an uncrewed aerial vehicle (UAV) to detect and map E. elaterium infestations in hedgerow olive orchards.

RESULTS

The study was conducted in two superintensive olive orchards, and the images were taken using a UAV equipped with an RGB sensor. Flights were conducted on two dates: in May, when there were various weeds infesting the orchard, and in September, when E. elaterium was the only infesting weed. UAV-orthomosaics in the first scenario were classified using random forest models, and the orthomosaics from September with E. elaterium as the only weed, were analyzed using an unsupervised algorithm. In both cases, the overall accuracies were over 0.85, and the producer's accuracies for E. elaterium ranged between 0.74 and 1.00.

CONCLUSION

These results allow the design of a site-specific and efficient herbicide control protocol which would represent a step forward in sustainable weed management. The development of these algorithms in free and open-source software fosters their application in small and medium farms. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

Histomorphological changes between short and long days in ovary guanacos (Lama guanicoe)

This is the first morpho-histological comparison of guanaco ovaries between reproductive (long-days) and non-reproductive (short-days) seasons, and oestrogen receptor-alpha (ERα) and beta (ERβ) detection. Different stages of follicle development were found in the cortical area, but no corpus luteum was detected. The size and frequency of antral follicles and large atretic follicles were higher in long-day ovaries than short-days, consistent with ovarian activity in this season. Differential expression of ERα and ERβ was observed in follicles at different stages of development between short and long days. These data reveal histological and molecular differences between reproductive and non-reproductive seasons of guanaco ovaries.     

Habitat quality,not habitat amount,drives mammalian habitat use in the Brazilian Pantanal

Landscape Ecology - An understanding of species-habitat relationships is required to assess the impacts of habitat fragmentation and degradation. To date, habitat modeling in fragmented landscapes...     

Contrasting edge and pasture matrix effects on ant diversity from fragmented landscapes across multiple spatial scales

Landscape Ecology - Harmful effects of habitat loss and fragmentation can be detected across multiple spatial scales, yet most studies that aim to characterize these effects take place at a single...     

Landscape composition is the major driver of the taxonomic and functional diversity of tropical frugivorous birds

Landscape Ecology - Anthropogenic land use and cover changes impact biodiversity worldwide. However, ecological groups are differently affected by landscape composition and configuration....