Letters In Animal Biology

Comparison of analgesic effects of medetomidine and meloxicam in pain control after ovariectomy in cats

2024-09-04T17:45:37+00:00

In small animal practice, various medications are used for postoperative pain management, with NSAIDs and alpha-2 adrenergic drugs being commonly employed. This study aimed to compare the efficacy of these medications in relieving postoperative pain following ovariectomy in cats. In this study, eleven healthy adult female cats were anesthetized for traditional midline ovariectomy and randomly administered either 0.2 mg/kg of IV Meloxicam (MLX) or 20 μg/kg of IV medetomidine (MED). Parameters including serum cortisol and glucose levels, pain scores using the Unesp-Botucatu Multidimensional Pain Scale (UMPS) method, anesthesia duration, blood pressure, and hemoglobin oxygen saturation (SpO2) were measured before the surgery and at 1, 2, 4, 6, and 24 hours post-surgery. All cats experienced pain, with the highest pain score recorded 3 hours post-surgery. Although the median pain score at this time point was higher in the MLX group than in the MED group, the difference was insignificant. The median serum glucose level peaked at two hour-post-surgery, significantly correlating with UMPS pain scores. Anesthesia duration was significantly lower in the MLX group, and the serum cortisol level in the MED group was significantly higher than in the MLX group at the 2-hour mark post-surgery. No significant difference in SpO2 changes was observed between the two groups. In conclusion, both Meloxicam and medetomidine are equally effective in alleviating post-ovariectomy pain in cats. However, due to their shorter anesthesia duration, Meloxicam may be the preferable choice for pain management in ovariectomy surgery. Furthermore, blood glucose levels can serve as a reliable pain indicator in cats, along with other biochemical markers.

The effects of Crocin from red saffron flower on the innate and humoral immune systems of domestic short hair cats

2024-09-11T15:05:18+00:00

Crocin, the primary active component of the red saffron flower (Crocus sativus), possesses a variety of biological and antioxidant properties. This study aimed to evaluate its effects on the immune system of domestic short hair (DSH) cats compared to the immunosuppressive drug cyclosporine. A total of 32 cats were divided into four groups: G1) received crocin at a dosage of 10 mg/kg body weight, G2) received cyclosporine at 7 mg/kg body weight for two weeks, followed by crocin for an additional two weeks, G3) received only cyclosporine for 30 days, and G4) served as the control group. Blood samples were collected every ten days to monitor changes in immune parameters. Statistical analysis revealed significant differences (p<0.05) in the concentrations of immunoglobulin A (IgA), IgG, IgM, and neutrophil counts among the treatment and control groups. However, there were no significant changes observed in lymphocyte and monocyte counts, or the percentage of phagocytes. In the group receiving crocin, a significant increase in immunoglobulin M was observed between days 0 to 10, and from days 20 to 30, indicating a continued enhancement of the immune response. Immunoglobulin G levels remained stable until day 20, after which a significant increasing trend was observed, alongside notable differences between the groups throughout the study period. Furthermore, immunoglobulin M levels in all groups showed significant changes with the saffron group starting from day 20 onward, indicating a consistent upward trend. In conclusion, the findings suggest that the incorporation of saffron significantly enhances the humoral immune response in cats, specifically through increased levels of immunoglobulin A, G, and M. However, saffron did not demonstrate a notable effect on the innate immune system, as indicated by unchanged lymphocyte and monocyte counts. Based on these results, the use of saffron in veterinary medicine and the food industry is recommended for its potential immunomodulatory effects.

Application of artificial intelligence and machine learning in poultry disease detection and diagnosis: A review

2024-09-14T17:07:03+00:00

The poultry population has increased exponentially from 13.9 billion in the early 21st century to 26.56 billion by 2022 worldwide, emphasizing the vital nutritional and economic part of this section. Simultaneously, the poultry sector faces a considerable amount of tests from diseases such as avian influenza, coccidiosis, mycoplasmosis, etc. that cost the industry multibillion-dollar losses each year. The groundbreaking and revolutionary possibilities of artificial intelligence and machine learning in poultry disease detection and diagnosis are discussed in this review. By capitalizing on data from physiological and behavioral traits like movement, vocalization, body temperature, and excreta, AI algorithms can detect indications of illness and pathological conditions, which means strengthening disease management and bringing down economic losses. High-precision image and video processing, non-invasive monitoring, the use of thermal imaging, and accurate tracking of poultry to spot health issues are some of the crucial developments that have also aided in analyzing stress and other abnormalities. Incorporating new-age technologies into feasible, applicable, and economical diagnostic tools that have the potential to transform poultry well-being, enhance the welfare of poultry, and upgrade production as well as handling processes is discussed here. The upcoming prospects include global partnerships, better data analytics, and extended research or studies for the management of diseases and behavioral anomalies in all poultry species. The collaboration of AI, machine learning, and biotechnology holds colossal promise for the poultry sector, guaranteeing food safety and ensuring public health.