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Nature-inspired metaheuristic algorithms are important components of artificial intelligence, and are increasingly used across disciplines to tackle various types of challenging optimization problems. This paper demonstrates the usefulness of such algorithms for solving a variety of challenging optimization problems in statistics using a nature-inspired metaheuristic algorithm called competitive swarm optimizer with mutated agents (CSO-MA). This algorithm was proposed by one of the authors and its superior performance relative to many of its competitors had been demonstrated in earlier work and again in this paper. The main goal of this paper is to show a typical nature-inspired metaheuristic algorithmi, like CSO-MA, is efficient for tackling many different types of optimization problems in statistics. Our applications are new and include finding maximum likelihood estimates of parameters in a single cell generalized trend model to study pseudotime in bioinformatics, estimating parameters in the commonly used Rasch model in education research, finding M-estimates for a Cox regression in a Markov renewal model, performing matrix completion tasks to impute missing data for a two compartment model, and selecting variables optimally in an ecology problem in China. To further demonstrate the flexibility of metaheuristics, we also find an optimal design for a car refueling experiment in the auto industry using a logistic model with multiple interacting factors. In addition, we show that metaheuristics can sometimes outperform optimization algorithms commonly used in statistics., (© 2024. The Author(s).)

Aim: To investigate the expression profile of microRNAs in inoperable advanced non-small cell lung cancer (NSCLC) patients receiving chemotherapy and the potential relevance of microRNAs to clinicopathological characteristics and prognosis., Methods: Serum samples were taken from 260 inoperable advanced NSCLC patients and 260 healthy individuals. All the patients received cisplatin-based chemotherapy, including NP/NC regimens, GP/GC regimens, and TP/TC regimens. The serum levels of microRNAs (miR-125b, miR-10b, miR-34a and miR-155) were determined by quantitative real-time PCR., Results: Serum levels of the 4 microRNAs examined in NSCLC patients were significantly increased as compared with healthy individuals. The levels of miR-125b and miR-155 were changed in a similar pattern: the patients with stage IV disease had the highest one, while the patients with stage III A and stage III B disease showed similar increased levels. The levels of miR-10b and miR-34a in the patients with different stages were increased to similar extent. The level of miR-125b in poorly differentiated cancer was significantly higher than those in well and moderately differentiated cancers, while the levels of miR-10b, miR-34a, and miR-155 did not significantly differ with cancer differentiation. Among the 4 microRNAs examined, only miR-125b was significantly associated with therapeutic response, exhibiting higher expression levels in non-responsive patients. Furthermore, the high level of miR-125b was significantly correlated with poor patient survival. A multivariate Cox regression analysis showed that the expression level of miR-125b was an independent prognostic marker in NSCLC patients., Conclusion: Our results suggest that miR-125b is a potential diagnostic or prognostic biomarker for NSCLC. This finding has important implications for development of targeted therapeutics to overcome chemotherapeutic resistance in NSCLC.