Study Links Dog Breed, Environment To Canine Obesity
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Study Links Dog Breed, Environment To Canine Obesity

A groundbreaking study led by Texas A&M University and the Dog Aging Project (DAP) has revealed that canine obesity stems from a complex interplay of breed predisposition, environmental factors, and food motivation. The research, which analyzed data from over 50,000 dogs enrolled in the DAP, provides critical insights for veterinarians and pet owners striving to address this growing health concern affecting half of all U.S. dogs.f

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Scientists make breakthrough in developing Nipah virus vaccine for pigs
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Scientists make breakthrough in developing Nipah virus vaccine for pigs

Scientists at The Pirbright Institute have developed three experimental Nipah virus vaccines for pigs, successfully preventing infection in field trials. This breakthrough could reduce zoonotic transmission to humans, protect livestock economies, and enhance global pandemic preparedness. The study, published in npj Vaccines, highlights a One Health approach to combating this deadly pathogen.

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Perception of health problems in French bulldogs and attitudes toward BOAS grading among Danish owners
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Perception of health problems in French bulldogs and attitudes toward BOAS grading among Danish owners

A new Danish study published in [Journal Name] sheds light on French bulldog owners’ perceptions of their pets’ health—particularly regarding brachycephalic obstructive airway syndrome (BOAS)—and their attitudes toward BOAS grading as a potential solution. While most owners acknowledged the breed’s health challenges, many still viewed their own dogs as exceptions, highlighting a persistent disconnect between general breed concerns and individual pet experiences.

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Sonographic machine-assisted recognition and tracking of B-lines in dogs
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Sonographic machine-assisted recognition and tracking of B-lines in dogs

The SMARTDOG study evaluates an AI-based ultrasound algorithm for detecting B-lines in dogs with cardiogenic pulmonary edema (CPE). Results show strong agreement (ICC = 0.88) between AI and manual operator counts, with 84-86% accuracy in classifying pathological lung patterns. While AI failed in 14.2% of cases (more often in CPE dogs), it shows promise as a decision-support tool in veterinary critical care.

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