The present research envisaged the analysis of the dissolved oxygen fault of the water quality monitoring system using the genetic algorithm-support vector machine (GA-SVM). The real-time data collected by the dissolved oxygen sensor was classified into the fault types. The fault types were divided into complete failure fault, impact fault, and constant output fault. Based on the fault classification of the dissolved oxygen parameters, SVM fault diagnosis experiments were conducted.  https://www.selleckchem.com/products/pomhex.html  Experimental results show that the accuracy of dissolved oxygen was 98.53%. On comparison with the experimental results of the back propagation (BP) neural network, it was found that the diagnosis results of the dissolved oxygen parameters using SVM were better than those of the BP neural network. The genetic algorithm (GA) was used to optimize the parameters. After iteration, the optimal parameters such as C and g were selected (C is the penalty coefficient, which adjusts the weight of the two index preferences in the optimization direction, i.e., the tolerance for errors, and g is a parameter that comes with the function that implicitly determines the distribution of the data after mapping to the new feature space.). By using GA, after iteration, the optimized values of C and g was found to be 2.1649 and 5.3312, respectively. The experimental results showed that the method exhibited a good accuracy.Mathematical models of tumor-immune interactions provide an analytic framework for studying tumor-immune dynamics. In this paper, we present a mathematical model to describe tumor-immune cell interactions, focusing on the role of the natural killer (NK) cells and CD8+ cytotoxic T lymphocytes (CTLs) in immune surveillance. According to the experimental and clinical results, we determine part of the model parameters to reduce the model parameter space. Then we analyze the local geometric properties of the equilibria of model and carry out numerical simulations to verify the conditions for the stability properties of equilibrium points. Numerical results suggest that the host immune system alone is not fully effective against progression of tumor cells, and CTLs play a crucial role in immune surveillance.Vaccination is an effective method to prevent individuals from contracting diseases like measles and the flu. Its success is clearly demonstrated by the large declines in the incidence of many diseases (e.g., childhood diseases like measles) after the start of mass vaccination programs. However, what happens after this drop in incidence can be complicated. It is known that some diseases exhibit "honeymoon periods" (long periods of temporary low disease incidence after start of mass vaccination). These periods end with a natural resurgence of the disease, which is not due to any change in the system. To study honeymoon periods, we used the compartmental model analyzed in [1] that can exhibit different types of vaccine failures failure in degree (leakiness), in take (all-or-nothing) and in duration (waning of vaccine-derived immunity). We showed that traditional measures of transient dynamics in ecology may not distinguish between models with different honeymoon periods. We also provide a proof of global stability of the endemic equilibrium when the reproduction number (accounting for vaccination) is greater than one, and introduce a technical definition of the honeymoon period.Targeted therapy is one of the promising strategies for the treatment of cancer. However, resistance to anticancer drug strongly limits the long-term effectiveness of treatment, which is a major obstacle for successfully treating cancer. In this paper, we analyze a linear system of ordinary differential equations for cancer multi-drug resistance induced mainly by random genetic point mutation. We investigate that the resistance generated before the beginning of the treatment is greater than that developed during-treatment. This result depends on the concentration of the drug, which holds only when the concentration of the drug reaches a lower limit. Moreover, no matter how many drugs are used in the treatment, the amount of resistance (generated at the beginning of the treatment and within a certain period of time after the treatment) always depends on the turnover rate. Using numerical simulations, we also evaluate the response of the mutant cancer cell population as a function of time under different treatment strategies. At appropriate dosages, combination therapy produces significant effects for the treatment with low-turnover rate cancer. For cancer with very high-turnover rate (close to 1), combination therapy can not significantly reduce the amount of resistant mutants compared to monotherapy, so in this case, combination therapy would not have advantage over monotherapy.Retinoblastoma (RB) is one of the most common cancer in children. However, the specific mechanism about RB tumorigenesis has not been fully understood. In this study, to comprehensively characterize the splicing alterations in the tumorigenesis of RB, we analyzed the differential alternative splicing events in RB. Specifically, the isoforms of RB1 were downregulated in the RB samples, and a large proportion of differentially expressed genes had multiple differentially expressed transcripts (64%). We identified 1453 genes with differential alternative splicing, among which, SE accounted for the majority, followed by MXE, RI, A3SS, and A5SS. Furthermore, the biological function related to the normal function of eyes, and E2F family TFs were significantly enriched by the genes with differential alternative splicing. Among the genes associated with visual sense, ABCA4 was found to have two mutually exclusive exons, resulting in two isoforms with different functionalities. Notably, DAZAP1 was identified as one of the critical splicing factors in RB, which was potentially involved in E2F and RB pathways. Functionally, differential binding sites in DAZAP1 protein were significantly observed between RB and normal samples. Based on the comprehensive analysis of the differential alternative splicing events and splicing factors, we identified some driver genes with differential alternative splicing and critical splicing factors involved in RB, which would greatly improve our understanding of the alternative splicing process in the tumorigenesis of RB.