فهرست مطالب مهسا دانشمند

Early diagnosis of diseases is one of the main goals of health and wellness centers. Timely diagnosis can reduce the potential damage of diseases. The importance of this issue in veterinary medicine multiplies due to its combination with economic goals. Therefore, a predictive approach is necessary for early diagnosis of diseases. This approach should be evidence-based and highly accurate. It should also be economically efficient. Artificial intelligence is the simulation of human intelligence and judgment by a computer or a robot that is programmed or trained to perform tasks that normally need human abilities. The emergence of artificial intelligence and machine learning techniques in today's world has improved the existing functions in health care systems. So that with the application of this technology, a significant progress has been made in the procedures of event prediction and disease diagnosis, management and health at the macro level, etc. Furthermore, the scope of diagnosable diseases is extensive, encompassing any ailment for which relevant data can be processed by artificial intelligence algorithms. The trained model has the capability to diagnose a wide range of diseases, with accuracy contingent upon factors such as disease indicators, collected data, and other pertinent variables. In this review article, the most important applications of artificial intelligence in veterinary medicine will be mentioned, and in general, these applications will be examined in various fields such as diagnosis of common diseases, differential diagnosis, prediction of disease occurrence, veterinary diagnostic imaging techniques, veterinary clinical pathology, etc. In addition, the challenges in this field will also be mentioned. This article is a review of recent studies in this fiel.

 Cotton seed is one of the main sources of protein in animal feeds, containing gossypol, which has been shown to have toxic effects. Results reported by various studies also indicate the anti-cancer effects of gossypol on various cell types. However, its toxic effects on human and animal cells have not been fully established. This study was planned to investigate, for the first time, the cytotoxic effects and oxidative stress induced by gossypol on normal bovine kidney (BK) and HeLa cell lines, representing typical healthy and cancer cells, respectively.

The BK and HeLa cell lines were treated for 24, 48 or 72 hours with 5, 10 or 20 ppm of gossypol (+/-). The cellular bio-availability and cytotoxicity were measured by MTT assay. The catalase and malondialdehyde (MDA) levels were also measured to represent the oxidative stress parameters.

The percentages of cytotoxicity in BK and HeLa cell lines were calculated at a gossypol concentration of 5, 10 and 20 ppm over 24, 48 or 72 hours of incubation, respectively. The IC50 values were also determined for the two cell lines. No changes in the catalase and lipid peroxidase activities were observed in either cell line.

The percentage of the gossypol cytotoxicity was concentration-dependent. By comparing the IC50 in both cell lines using ANOVA analysis, a significant difference was observed, suggesting that Hela cells were less sensitive to gossypol than the BK cells. Lack of changes in the oxidative stress, as tested by catalase and MDA assays, demonstrated that gossypol did not induce oxidative stress in either cell line.