Dexmedetomidine ameliorates x-ray-induced myocardial injury via alleviating cardiomyocyte apoptosis and autophagy.

BACKGROUND: Radiotherapy is a primary local treatment for tumors, yet it may lead to complications such as radiation-induced heart disease (RIHD). Currently, there is no standardized approach for preventing RIHD. Dexmedetomidine (Dex) is reported to have cardio-protection effects, while its role in radiation-induced myocardial injury is unknown. In the current study, we aimed to evaluate the radioprotective effect of dexmedetomidine in X-ray radiation-treated mice. METHODS: 18 male mice were randomized into 3 groups: control, 16 Gy, and 16 Gy + Dex. The 16 Gy group received a single dose of 16 Gy X-ray radiation. The 16 Gy + Dex group was pretreated with dexmedetomidine (30 µg/kg, intraperitoneal injection) 30 min before X-ray radiation. The control group was treated with saline and did not receive X-ray radiation. Myocardial tissues were collected 16 weeks after X-ray radiation. Hematoxylin-eosin staining was performed for histopathological examination. Terminal deoxynucleotidyl transferase dUTP nick-end labeling staining was performed to assess the state of apoptotic cells. Immunohistochemistry staining was performed to examine the expression of CD34 molecule and von Willebrand factor. Besides, western blot assay was employed for the detection of apoptosis-related proteins (BCL2 apoptosis regulator and BCL2-associated X) as well as autophagy-related proteins (microtubule-associated protein 1 light chain 3, beclin 1, and sequestosome 1). RESULTS: The findings demonstrated that 16 Gy X-ray radiation resulted in significant changes in myocardial tissues, increased myocardial apoptosis, and activated autophagy. Pretreatment with dexmedetomidine significantly protects mice against 16 Gy X-ray radiation-induced myocardial injury by inhibiting apoptosis and autophagy. CONCLUSION: In summary, our study confirmed the radioprotective effect of dexmedetomidine in mitigating cardiomyocyte apoptosis and autophagy induced by 16 Gy X-ray radiation.

Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers.

DNA microarray technology can measure the activities of tens of thousands of genes simultaneously, which provides an efficient way to diagnose cancer at the molecular level. Although this strategy has attracted significant research attention, most studies neglect an important problem, namely, that most DNA microarray datasets are skewed, which causes traditional learning algorithms to produce inaccurate results. Some studies have considered this problem, yet they merely focus on binary-class problem. In this paper, we dealt with multiclass imbalanced classification problem, as encountered in cancer DNA microarray, by using ensemble learning. We utilized one-against-all coding strategy to transform multiclass to multiple binary classes, each of them carrying out feature subspace, which is an evolving version of random subspace that generates multiple diverse training subsets. Next, we introduced one of two different correction technologies, namely, decision threshold adjustment or random undersampling, into each training subset to alleviate the damage of class imbalance. Specifically, support vector machine was used as base classifier, and a novel voting rule called counter voting was presented for making a final decision. Experimental results on eight skewed multiclass cancer microarray datasets indicate that unlike many traditional classification approaches, our methods are insensitive to class imbalance.