Doxorubicin (DOX) possesses strong anti-tumor effects but is limited by its irreversible cardiac toxicity. The relationship between exercise, a known enhancer of cardiovascular health, and DOX-induced cardiotoxicity has been a focus of recent research. Exercise has been suggested to mitigate DOX's cardiac harm by modulating the Yes-associated protein (YAP) and Signal transducer and activator of transcription 3 (STAT3) pathways, which are crucial in regulating cardiac cell functions and responses to damage. This study aimed to assess the protective role of exercise preconditioning against DOX-induced cardiac injury. We used Sprague-Dawley rats, divided into five groups (control, DOX, exercise preconditioning (EP), EP-DOX, and verteporfin + EP + DOX), to investigate the potential mechanisms. Our findings, including echocardiography, histological staining, Western blot, and q-PCR analysis, demonstrated that exercise preconditioning could alleviate DOX-induced cardiac dysfunction and structural damage. Notably, exercise preconditioning enhanced the nuclear localization and co-localization of YAP and STAT3. Our study suggests that exercise preconditioning may counteract DOX-induced cardiotoxicity by activating the YAP/STAT3 pathway, highlighting a potential therapeutic approach for reducing DOX's cardiac side effects.
PURPOSE: Exercise training is associated with improving the prognosis of breast cancer survivors, but no studies have evaluated the optimal exercise intervention. We aimed to investigate the most effective exercise intervention to improve obesity-related outcomes in breast cancer survivors. METHODS: A comprehensive search strategy was conducted in Medline, Embase, Web of Science, Cochrane Library, and Chinese biomedical literature databases from the time of library construction to April 2, 2023. We included randomized controlled trials reporting the effects of four types of exercise interventions (aerobic exercise; aerobic combined with resitance exercise, resitstance exercise and mind-body exercise ) on obesity-related outcomes in breast cancer survivors. A Bayesian network meta-analysis was used to analyze and rank the effectiveness of four exercise types. RESULTS: A total of 76 randomized controlled trials that contained 5610 breast cancer survivors were included. The treatment effect of combined aerobic and resistance exercise (mean difference = -0.59; 95% credible interval: 1.15, -0.08) was significantly better than that of the control groups in terms of body mass index. For percentage of body fat, combined aerobic and resistance exercise (mean difference = -1.74; 95% credible interval: 0.87, -0.90) and aerobic exercise (mean difference = -1.16; 95% credible interval: 2.15, -0.16) were significantly better than controls. Subgroup analysis suggested that combined aerobic and resistance exercise significantly affected body mass index at an intervention duration >12 weeks or weekly time on exercise >150 min. CONCLUSION: Our network meta-analysis found combined aerobic and resistance exercise may be the most effective intervention to improve obesity-related outcomes in breast cancer survivors. In addition, intervention duration and participant adherence are important factors that influence the effectiveness of exercise interventions.
In recent years, a new method of fault diagnosis, named variational mode decomposition (VMD), has been widely used in industrial production, but the decomposition accuracy of VMD is determined by two parameters, which are respectively the decomposition layer number k and the penalty factor α, if the parameters are not properly selected, there will be over-decomposition or under-decomposition. In order to find an approach to determine the parameters adaptively, a method to optimize VMD by using the immune fruit fly optimization algorithm (IFOA) is proposed in this paper. In this method, permutation entropy is used as the fitness function, firstly, the immune fruit fly optimization algorithm is used to search the combined parameters of k and α in VMD, searching for the best combination parameters of k and α by iteration, and then uses the combined parameters to perform VMD, finally, the center frequency is determined through frequency spectrum analysis. The method mentioned is applied to the fault extraction of a simulated signal and a measured signal of a wind turbine gearbox, and the fault frequency is successfully extracted. Using ensemble empirical mode decomposition (EEMD) and singular spectrum decomposition (SSD) to compare with the proposed method, which validated feasibility of the proposed method.
