Avacta Animal Health

York, United Kingdom

Avacta Animal Health

York, United Kingdom

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Zimmer A.,Kleintierpraxis Pedot | Bexley J.,Avacta Animal Health | Halliwell R.E.W.,University of Edinburgh | Mueller R.S.,Ludwig Maximilians University of Munich
Veterinary Immunology and Immunopathology | Year: 2011

Serum food allergen-specific antibody testing is widely offered to identify suitable ingredients for diets to diagnose adverse food reaction (AFR) in dogs with allergic skin disease. Antibody concentrations in blood samples obtained during an unsuccessful diet to help in the choice of diet changes may be influenced by the previous diet. The objective of this paper was to measure food antigen-specific IgE and IgG for the most commonly used 16 food antigens before and after an elimination diet. Levels of food-specific serum IgE and IgG antibodies were measured by enzyme-linked immunosorbent assay (ELISA). Dogs had detectable IgE antibodies to beef, pork, lamb and cows' milk; and detectable IgG antibodies to beef, pork, lamb, cows' milk, chicken and turkey. Of 19 dogs with complete data sets, 14 dogs showed clear improvement during diet and in 7 dogs AFR could be diagnosed by deterioration on rechallenge and subsequent improvement on refeeding the diet. Serum was obtained before and 6-8 weeks after beginning such a diet. There was no significant difference in pre- and post-diet levels for any of the individual allergens nor for the total IgE and IgG concentrations of all antigens (P= 0.55 and P= 0.53 respectively). In these 19 dogs in which an elimination diet was used for the diagnosis of food allergy and in which 14 were probably food allergic and 7 were proven food allergic there were no significant differences in food-specific antibodies before and after an elimination diet of 6-8 weeks. © 2011 Elsevier B.V.


Mirkes E.M.,University of Leicester | Alexandrakis I.,Avacta Animal Health | Slater K.,PetScreen Ltd | Tuli R.,Avacta Animal Health | Gorban A.N.,University of Leicester
Journal of Physics: Conference Series | Year: 2014

One out of four dogs will develop cancer in their lifetime and 20% of those will be lymphoma cases. PetScreen developed a lymphoma blood test using serum samples collected from several veterinary practices. The samples were fractionated and analysed by mass spectrometry. Two protein peaks, with the highest diagnostic power, were selected and further identified as acute phase proteins, C-Reactive Protein and Haptoglobin. Data mining methods were then applied to the collected data for the development of an online computer-assisted veterinary diagnostic tool. The generated software can be used as a diagnostic, monitoring and screening tool. Initially, the diagnosis of lymphoma was formulated as a classification problem and then later refined as a lymphoma risk estimation. Three methods, decision trees, kNN and probability density evaluation, were used for classification and risk estimation and several preprocessing approaches were implemented to create the diagnostic system. For the differential diagnosis the best solution gave a sensitivity and specificity of 83.5% and 77%, respectively (using three input features, CRP, Haptoglobin and standard clinical symptom). For the screening task, the decision tree method provided the best result, with sensitivity and specificity of 81.4% and >99%, respectively (using the same input features). Furthermore, the development and application of new techniques for the generation of risk maps allowed their user-friendly visualization. © Published under licence by IOP Publishing Ltd.


Bethlehem S.,Ludwig Maximilians University of Munich | Bexley J.,Avacta Animal Health | Mueller R.S.,Ludwig Maximilians University of Munich
Veterinary Immunology and Immunopathology | Year: 2012

Adverse food reaction (AFR) is a common differential diagnosis for pruritic dogs. The only way to diagnose AFR is an elimination diet of 6-8 weeks with a protein and a carbohydrate source not previously fed. In humans, patch testing has been shown to be a useful tool to diagnose food allergies. In veterinary medicine, serum food allergen-specific antibody testing is widely offered to identify suitable ingredients for such diets. The aim of this study was to determine sensitivity, specificity, negative and positive predictability of patch testing with and serum antibody testing for a variety of common food stuffs. Twenty-five allergic dogs underwent an elimination diet and individual rechallenge with selected food stuffs, food patch testing and serum testing for food-antigen specific IgE and IgG. Eleven clinically normal control dogs only were subjected to patch and serum testing. The sensitivity and specificity of the patch test were 96.7 and 89.0% respectively, negative and positive predictability were 99.3 and 63.0%. For IgE and IgG the sensitivity was 6.7 and 26.7%, specificity were 91.4 and 88.3%, the negative predictive values 80.7 and 83.7% and the positive predictive values were 15.4 and 34.8%. Based on these results, a positive reaction of a dog on these tests is not very helpful, but a negative result indicates that this antigen is tolerated well. We conclude that patch testing (and to a lesser degree serum testing) can be helpful in choosing ingredients for an elimination diet in a dog with suspected AFR. © 2012.


Mirkes E.M.,University of Leicester | Alexandrakis I.,Avacta Animal Health | Slater K.,Avacta Animal Health | Tuli R.,Avacta Animal Health | Gorban A.N.,University of Leicester
Computers in Biology and Medicine | Year: 2014

The canine lymphoma blood test detects the levels of two biomarkers, the acute phase proteins (C-Reactive Protein and Haptoglobin). This test can be used for diagnostics, for screening, and for remission monitoring as well. We analyze clinical data, test various machine learning methods and select the best approach to these oblems. Three families of methods, decision trees, kNN (including advanced and adaptive kNN) and probability density evaluation with radial basis functions, are used for classification and risk estimation. Several pre-processing approaches were implemented and compared. The best of them are used to create the diagnostic system. For the differential diagnosis the best solution gives the sensitivity and specificity of 83.5% and 77%, respectively (using three input features, CRP, Haptoglobin and standard clinical symptom). For the screening task, the decision tree method provides the best result, with sensitivity and specificity of 81.4% and >99%, respectively (using the same input features). If the clinical symptoms (Lymphadenopathy) are considered as unknown then a decision tree with CRP and Hapt only provides sensitivity 69% and specificity 83.5%. The lymphoma risk evaluation problem is formulated and solved. The best models are selected as the system for computational lymphoma diagnosis and evaluation of the risk of lymphoma as well. These methods are implemented into a special web-accessed software and are applied to the problem of monitoring dogs with lymphoma after treatment. It detects recurrence of lymphoma up to two months prior to the appearance of clinical signs. The risk map visualization provides a friendly tool for exploratory data analysis. © 2014 Elsevier Ltd.


PubMed | University of Leicester and Avacta Animal Health
Type: | Journal: Computers in biology and medicine | Year: 2014

The canine lymphoma blood test detects the levels of two biomarkers, the acute phase proteins (C-Reactive Protein and Haptoglobin). This test can be used for diagnostics, for screening, and for remission monitoring as well. We analyze clinical data, test various machine learning methods and select the best approach to these oblems. Three families of methods, decision trees, kNN (including advanced and adaptive kNN) and probability density evaluation with radial basis functions, are used for classification and risk estimation. Several pre-processing approaches were implemented and compared. The best of them are used to create the diagnostic system. For the differential diagnosis the best solution gives the sensitivity and specificity of 83.5% and 77%, respectively (using three input features, CRP, Haptoglobin and standard clinical symptom). For the screening task, the decision tree method provides the best result, with sensitivity and specificity of 81.4% and >99%, respectively (using the same input features). If the clinical symptoms (Lymphadenopathy) are considered as unknown then a decision tree with CRP and Hapt only provides sensitivity 69% and specificity 83.5%. The lymphoma risk evaluation problem is formulated and solved. The best models are selected as the system for computational lymphoma diagnosis and evaluation of the risk of lymphoma as well. These methods are implemented into a special web-accessed software and are applied to the problem of monitoring dogs with lymphoma after treatment. It detects recurrence of lymphoma up to two months prior to the appearance of clinical signs. The risk map visualization provides a friendly tool for exploratory data analysis.


PubMed | Avacta Animal Health, University of Edinburgh and North Carolina State University
Type: Journal Article | Journal: Veterinary dermatology | Year: 2016

Knowledge of cross-reactivity between foods is useful so that potentially cross-reactive allergens can be avoided in diet trials.To evaluate allergenic cross-reactivity in related foods.Sera from 469 dogs with suspected adverse food reactions.An IgE-based serological assay using 19 food allergens was performed in 469 dogs. Pairwise comparisons were used to calculate the odds ratios (ORs) for each food pair, with significance at P < 0.0002 by Holm-Bonferroni correction, both in all 469 dogs and in the 261 of 469 dogs with at least one positive reaction. One-way ANOVA with Tukeys post hoc tests (significance at P < 0.05) were used to test for differences between mean logE ORs in different food groups. Inhibition enzyme-linked immunosorbent assays (ELISAs) were performed to assess allergenic cross-reactivity between beef, lamb and cows milk.Significant associations were observed between both related and unrelated food pairs. Associations were, however, more frequent and stronger among related than unrelated foods. In all 469 dogs, 38 of 43 related food pairs were significantly associated [mean (SD) logE OR 3.4 (0.9)] compared with 79 of 128 unrelated pairs [2.7 (1.0)], P < 0.0002. In positive dogs, 32 of 43 related pairs were significantly associated [2.7 [1.0)] compared with 49 of 128 unrelated pairs [1.8 (1.0)], P < 0.0002. Inhibition ELISAs confirmed the presence of cross-reactive IgE-binding epitopes in beef, lamb and cows milk.The results suggest that related and potentially cross-reactive foods should be avoided in elimination diets.

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