American journal of veterinary research最新文献

Objective: Dexamethasone is used to experimentally induce insulin resistance; however, its impact on insulin secretion is unclear. This study aimed to assess the responses to oral carbohydrate challenges in dexamethasone-treated horses.

Methods: 8 healthy Standardbreds received 0.08 mg/kg of dexamethasone IM every 48 hours for 14 days in June 2022 (winter in the Southern hemisphere). Oral glucose tests (OGT) were conducted before treatment (day 1) and on days 8 and 15. Glucose, insulin, triglycerides, total and active glucagon-like peptide-1 (tGLP-1 and aGLP-1) and glucose-dependent insulinotropic polypeptide (GIP) were measured at baseline and at intervals up to 240 minutes after OGT. The results were analyzed using a mixed-effects linear regression model.

Results: After 8 days of dexamethasone, significant increases in areas under the curve (AUC) of glucose (effect size, +139.1 [95% CI, 124.0 to 154.1] mg/dL·min), insulin (+297.6 [95% CI, 214.6 to 380.8] µIU/mL·min), triglycerides (+4,854.3 [95% CI, 2,181.3 to 7,527.3] mg/dL·min), tGLP-1 (+2.58 [95% CI, 0.23 to 4.93] pmol/L·min), and GIP (+65.56 [95% CI, 40.98 to 90.16] pg/mL·min) were detected post-OGT. These effects were blunted by day 15, with glucose, insulin, and active glucagon-like peptide-1 AUC significantly lower than on day 8 and tGLP-1, triglycerides, and GIP AUC not different from day 1. No horse developed clinical laminitis.

Conclusions: Dexamethasone increased insulin secretion after an OGT with higher lipid mobilization and stimulation of the enteroinsular axis, but the effect was partially reversed by day 15.

Clinical relevance: While dexamethasone induces insulin resistance consistently over prolonged periods, its effect on insulin secretion seems transient.

Objective: Lyme disease is a vector-borne emerging zoonosis in Ontario driven by human population growth and climate change. Lyme disease is also a prime example of the One Health concept. While little can be done to immediately reverse climate change and population growth, public health must resort to health communication as its best option for disease control until an effective vaccine becomes available. Disease surveillance enabling precision public health has an important role in this respect: one of the goals of disease surveillance is to forecast the future burden of disease to inform those who need to know. The goal of this study was to forecast the burden of Lyme disease using automated machine learning and statistical learning approaches.

Methods: Lyme disease reports were retrieved from Ontario's integrated Public Health Information System surveillance system from January 2005 to December 2023. The reports from January 2005 to December 2021 were used as training data, and reports from January 2022 to December 2023 served as validation data. Forecasts from a seasonal autoregressive integrated moving-average model were used as a benchmark for forecasts from a feed-forward single-layer neural network machine learning algorithm.

Results: The Lyme disease burden in Ontario is predicted to increase dramatically. Neither the neural network nor the seasonal autoregressive integrated moving-average model proved to be generally more accurate.

Conclusions: The increasing burden of human Lyme disease is concerning to public health, further indicating ecosystem changes and challenges for canine health.

Clinical relevance: Human Lyme disease surveillance provides useful information to veterinarians.

Objective: To capture veterinary professionals' perspectives and applications of AI in veterinary care. This study assesses the perceived benefits, challenges, and potential areas where AI could enhance veterinary medicine and practice workflows.

Methods: An online survey was distributed to members of the American Animal Hospital Association and Digitail's network of veterinary professionals. The questionnaire included 18 close-ended and 7 open-ended questions exploring awareness, perceptions, usage, expectations, and concerns about AI in veterinary medicine. The survey was open from December 19, 2023, through January 8, 2024.

Results: The survey gathered 3,968 responses from professionals in various veterinary roles. Most respondents were veterinarians and veterinary technicians, with an average age of 35.

Conclusions: Respondents demonstrated varying familiarity with AI, with an overall positive outlook toward its adoption in veterinary medicine. Those who actively use AI tools in their professional tasks reported higher levels of optimism about its integration. Key concerns included the reliability and accuracy of AI in diagnosis and treatment. The top benefits identified by respondents included improving efficiencies, streamlining administrative tasks, and potential contributions to revenue growth, employee satisfaction, and client retention.

Clinical relevance: The findings underscore the influence of practical exposure and experience with AI tools on attitudes toward AI adoption. The positive correlation suggests that familiarity with AI technologies fosters trust and confidence, consequently driving greater acceptance and adoption within the veterinary community.

Objective: This study aims to quantify the frequency and resistance patterns of 3 methicillin-resistant staphylococci (MRS), Staphylococcus aureus (MRSA), Staphylococcus pseudintermedius (MRSP), and Staphylococcus schleiferi (MRSS), in companion animals, using historical culture and susceptibility data from a national diagnostic laboratory.

Methods: Samples from cats and dogs across the US, between 2019 and 2022, were analyzed. Methicillin-resistant isolates identified according to Clinical and Laboratory Standards Institute VET01S (5th ed) were included. Data included location, patient species, sampling site, year, and susceptibility results for various panels of antimicrobials.

Results: There were 110,423 MRSP, 5,618 MRSA, and 20,934 MRSS isolates identified. Methicillin-resistant S pseudintermedius was predominantly found in dogs (96.2%), with skin and soft tissue being the most common sites. Methicillin-resistant S aureus and MRSS were also primarily isolated from dogs, with significant yearly, regional, and species-specific differences in antimicrobial susceptibility observed. This study highlights high resistance levels in MRSP isolates, while MRSA and MRSS showed relatively higher susceptibility to several antimicrobials.

Conclusions: This study provides insight into the distribution and antimicrobial resistance patterns of MRSA, MRSP, and MRSS in companion animals in the US. Resistance rates for enrofloxacin, marbofloxacin, and chloramphenicol may be higher than reported in this analysis due to recent changes in MIC breakpoints in the Clinical and Laboratory Standards Institute VET01S (7th ed). The findings underscore significant geographical and temporal variations in resistance, emphasizing the need for tailored antimicrobial stewardship programs.

Clinical relevance: The prevalence of MRS in companion animals poses treatment challenges and potential zoonotic risks. This study provides nationwide insight that was not previously available.

Objective: To develop models for prediction of the onset of specific diseases in cats using pet insurance data and to evaluate their predictive performance.

Methods: Agria Pet Insurance data from almost 550,000 cats (2011 to 2016) were analyzed and used to train predictive models for periodontal disease and skin tumors using breed, sex, and insurance claim history. Random downsampling and 1:1 matching by age, insurance duration, and time at risk balanced the dataset. Variables were then further processed, with random forest and conditional logistic regression used for analysis. Model accuracy was assessed through leave-one-out cross-validation, while variable importance plots, partial dependence plots, and coefficients were used for model interpretation.

Results: Model accuracy ranged from 81.9% to 88.2% (P < .01, baseline 50%). Key predictors included prior insurance claims for "digestive," "whole body symptom," "skin," and "injury conditions," which may be nonspecific and predictive of various diseases. Maine Coon, Siamese, and Burmese cats were associated with periodontal disease-positive predictions, while domestic cats were linked with negative predictions. For skin tumors, Norwegian Forest Cats, Devon Rex and Sphynx cats, and Maine Coon cats were associated with positive predictions, whereas Birman and domestic cats were linked with negative predictions.

Conclusions: This study presents a method of machine learning predictive analysis on pet insurance data, although more comprehensive medical information and approaches accounting for data characteristics may be necessary to develop clearer predictors.

Clinical relevance: To prevent or detect these conditions early, veterinarians can use the breed risk results to guide clients, especially those with high-risk breeds, by offering early advice on lifestyle and monitoring.

Objective: To determine if ACTH, cortisol, arginine vasopressin (AVP), ghrelin, 5-hydroxyindoleacetic acid (5-HIAA), and substance P (SP) blood biomarkers associated with nausea in humans have similar associations in dogs.

Methods: 7 healthy, mixed hound dogs were nausea scored using videotaped observations, and concentrations of ACTH, cortisol, AVP, ghrelin, 5-HIAA, and SP were measured in blood at baseline, after 0.5 mg/kg, IM, morphine administration, and following administration of the treatment drug. Data collection occurred from October 20 through November 24, 2023. Treatments were saline 0.1 mL/kg (S) and propofol 0.5 mg/kg (P1), 1.0 mg/kg (P2), and 1.5 mg/kg (P3) administered IV 20 minutes after morphine administration using a randomized, crossover design with a 7-day washout between treatments.

Results: Nausea scores increased at 5 minutes and over time in all treatments. Adrenocorticotropic hormone concentrations were lower in P2 versus P1, P2 versus S, and P3 versus S at the 50-minute time point. At 50 minutes, cortisol concentrations were lower in P3 versus S, P2 versus S, and P3 versus P1. There were no statistically significant differences in AVP, ghrelin, 5-HIAA, or SP concentrations between treatments or over time.

Conclusions: AVP, ghrelin, 5-HIAA, and SP did not correlate with nausea signs in dogs. Additionally, propofol, at the subhypnotic doses administered, did not significantly decrease signs of nausea.

Clinical relevance: ACTH and cortisol, but not AVP, ghrelin, 5-HIAA, and SP, concentrations appeared to be associated with signs of nausea in dogs. Propofol was not effective at decreasing signs of nausea at the administered dosages.

Bovine respiratory disease (BRD) is the leading infectious disease in cattle, resulting in significant economic losses and welfare concerns in beef and dairy production systems. Traditional diagnostic methods for BRD typically rely on clinical observations and diagnostic laboratory tests, which can be time consuming with moderate diagnostic sensitivity. In recent years, machine learning (ML) and AI have emerged as powerful tools in animal health research, offering opportunities for improving BRD diagnostics and management. This review explores the current landscape of published literature on the use of ML and AI in BRD prevention, diagnostics, and classification. First, disease classification and pathogen identification models leveraging supervised models and metagenomic sequencing have identified specific community structure information in classifying specific BRD cases. From epidemiological datasets tracking disease outbreaks and risk factors, user-friendly platforms for producers and veterinarians are capable of being generated and deployed, providing customized scenarios, potential economic impacts, and pathogenic effects as a decision-support tool. Veterinarian-operated technologies, such as computer-aided lung auscultation stethoscopes, can automatically calculate lung scores and associated BRD severity likelihoods. Prediction and detection models used to leverage physical characteristics and feed consumption data provide novel methods of categorizing BRD risk. Finally, sensor technology monitoring behavioral or motion-based information provides continuous data on animal health and can enable early automated detection of BRD symptoms. Through synthesizing research in these key areas, this narrative review highlights the transformative potential of AI and ML in improving the accuracy, speed, and efficiency of BRD diagnostics, enhancing disease control and cattle welfare.

Objective: To achieve clinical recovery in canine atopic dermatitis affected pet dogs via alteration of the gut microbiome, following a meat and egg exclusion diet for 60 days.

Methods: 24 atopic dermatitis-affected pet dogs, all fed poultry meat and egg, and another 48 apparently healthy controls fed both poultry meat and egg (n = 24) or vegetable diet (24) were included in the study. The study was undertaken in the Bhubaneswar Smart City, Odisha, India, from July to December 2023. Fecal samples were collected at 2 points for DNA analysis, ie, on day 0 and day 60 of the change from a meat/egg-based diet to a vegetable-based diet. Extracted DNA samples were pooled category-wise and subjected to the gut microbiome analysis in the Nanopore sequencer targeting the 16S rRNA gene. Burrows-Wheeler Transform, Ferragina-Manzini index, and Krona charts were used for taxonomical classification and visualization of relative abundances of bacterial species within the metagenome. Alpha- and beta-diversity analyses were performed.

Results: Atopic pets at day 0 showed elevation in the gut microbiome population with an adequate concentration of pathogens like Escherichia coli and Clostridiodes difficile with lower amounts of the beneficial bacteria like Lactobacillus sp, while the pets at 60 days after dietary intervention showed a significant decline in bacterial species like E coli and C difficile with higher amount of Lactobacillus sp. Both control groups showed variations of microbiome between them as well as from the atopic pets.

Conclusions: We found a close association of poultry meat/egg diet with gut microbiome population and atopic symptoms as well in dogs, and elimination of such diet could be helpful in clinical recovery.

Clinical relevance: Dietary intervention with the exclusion of potential allergens from poultry meat and egg sources can be an effective approach for the management of canine atopic dermatitis.

Objective: To investigate indicators of mobility, inflammation, and cartilage remodeling in Dunkin-Hartley guinea pigs (Cavia porcellus) treated with manual acupuncture compared to 2 different comparator acupuncture groups.

Methods: 12-month-old male Hartleys were randomly assigned to 1 of 3 in vivo experimental groups that received manual acupuncture, needle sheath taps on corresponding acupoints, or off-point acupuncture. Treatments were performed under isoflurane once weekly for 3 weeks, and open-field enclosure monitoring was performed at the same frequency. After final treatments, all animals were euthanized, blood was collected for inflammatory marker analysis, and tissues were collected for histology, immunohistochemistry, and transcript expression analysis.

Results: 18 animals were involved: 6 per experimental group. Serum concentrations of complement component 3 and prostaglandin E2 were significantly decreased in the acupuncture group (P < .05). Muscle from acupoint stomach-36 had 6 gene transcripts with altered expressions in the manual acupuncture group compared to comparators. From cartilage/menisci, manual acupuncture resulted in the downregulation of 13 gene transcripts. Nerve growth factor (NGF) immunostaining in all 3 layers of articular cartilage of the medial tibial plateau was greater in the manual acupuncture group relative to the comparator groups. There were no differences in enclosure monitoring parameters or histologic grading.

Conclusions: Appreciable changes in voluntary mobility, behavioral or serum biochemical parameters, or stifle histological structure were not seen. Differences in serum inflammatory proteins, the gene expression of cartilage-remodeling transcripts, and NGF protein concentrations in cartilage were elucidated.

Clinical relevance: The short duration of manual acupuncture showed the initiation of beneficial regenerative and remodeling processes.

Objective: To evaluate the utility of routine preanesthetic screening thoracic radiographs in dogs without a specific clinical indication for this test.

Methods: All patients presented for elective tibial plateau leveling osteotomy between January 1, 2022, and December 31, 2022, were enrolled if there were no clinical signs or history of neoplasia or cardiopulmonary or thoracic disease. Three-view thoracic radiographic studies were performed and evaluated by the attending surgeon and a board-certified veterinary radiologist. The incidence of radiographic abnormalities and agreement between the attending clinician and the radiologist were analyzed.

Results: Of the 281 cases evaluated in this study, 10 (3.6%) were found to have radiographic abnormalities that were likely to affect the clinician's decision to proceed with elective surgery. There was no association between patient age and the probability of diagnosing a significant radiographic abnormality. There was poor agreement between the findings of the clinician and radiologist for cardiovascular and pulmonary abnormalities. There was slight agreement between the findings of the clinician and the radiologist for extrathoracic abnormalities.

Conclusions: Our data suggest that the utility of preoperative screening thoracic radiographs in dogs with no specific clinical indications for this test appears to be low. Given the poor agreement between clinician and radiologist findings, clinicians should consider routine evaluation of thoracic radiographs by a radiologist.

Clinical relevance: These findings should be considered by a clinician when deciding whether to recommend thoracic radiographs as a screening tool for a patient without history or physical examination findings suggestive of intrathoracic disease.