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Background: Although many epidemiological studies and meta-analyses have reported an association between autoimmune disorders and prostate cancer, none has reported a clear correlation or the direction of the association. The purpose of our study was to explore the potential relationship between autoimmunity-related disorders and prostate cancer using Mendelian randomization (MR). Methods: We retrieved literature from PubMed using the keywords “autoimmune disorder” AND “prostate cancer” to find more clues on the correlation between prostate cancer and autoimmunity-related disorder. Based on this literature search, we selected 16 autoimmunity-related disorders that had genome-wide association study (GWAS) data and may be associated with prostate cancer. The inverse variance weighting (IVW) method was applied as our primary analysis for two-sample MR and multivariate MR analysis to estimate the odds ratio (OR) and 95% confidence interval (CI). We further verified the robustness of our conclusions using a series of sensitivity analyses. Results: The autoimmunity-related diseases selected include rheumatoid arthritis, ankylosing spondylitis, coxarthrosis, gonarthrosis, Crohn's disease, ulcerative colitis, irritable bowel syndrome, celiac disease, primary sclerosing cholangitis, asthma, type 1 diabetes, systemic lupus erythematosus, multiple sclerosis, autoimmune hyperthyroidism, psoriatic arthropathies, and polymyalgia rheumatica. The results of inverse variance weighting (IVW suggested that six diseases were associated with the development of prostate cancer. The three diseases that may increase the risk of prostate cancer are rheumatoid arthritis (P = 0.001), coxarthrosis (P

Largemouth bass (Micropterus salmoides, LB) is an important aquaculture and fishing species in the world. LB has been introduced into China since 1983, and its aquaculture production has increased year by year. The total yield of LB in China reached 802,486 tons in 2022, ranking seventh in China's freshwater fish aquaculture. However, the LB is facing threats such as degradation of germplasm resources and disease susceptibility due to limitations in the scale of introduction, coupled with the effects of high-density aquaculture, inbreeding, and species hybridization. This paper summarizes the current status of LB germplasm resources, variety genetic improvement, nutrition and fodder, aquaculture mode and diseases, and circulation and processing. This paper also provides recommendations on how to fully explore and utilize the existing germplasm resources of LB; culture new LB germplasm that combines excellent resistance and growth characteristics through innovations in breeding techniques; reduce the morbidity rate and improve the efficiency of cultured LB through the optimization of fodder formulations and innovation of aquaculture modes; and shift the processing of LB toward standardization, efficient nutrition and safety through the integration of high-tech and large-scale production. This paper provides a reference for the sustainable and healthy development of the LB industry.

Summary: Prostate cancer (PCa) is one of the most prevalent urogenital malignancies. Bone metastasis from PCa reduces patient survival rates significantly. There currently exists no effective treatment for bone metastatic PCa, and the underlying mechanisms remain unclear. This study performed transcriptomic screening on PCa bone metastasis specimens and intersection analysis in public databases and identified SERPINH1 as a potential target for treatment. SERPINH1 was found to be upregulated in PCa bone metastases and with poor prognosis, high Gleason score, and advanced metastatic status. SERPINH1 induced PCa cells’ bone metastasis in vivo, promoted their proliferation, and mitigated apoptosis. Mechanistically, SERPINH1 bound to P62, reducing TRIM21-mediated K63-linked ubiquitination degradation of P62 and promoting proliferation and resistance to apoptosis of PCa. This study suggests the regulation of ubiquitination degradation of P62 by SERPINH1 that promotes PCa bone metastasis and can be considered as a potential target for treatment of bone metastatic PCa.

Multi-objective optimization problems (MOPs) constitute a vital component in the field of mathematical optimization and operations research. The multi-objective evolutionary algorithm based on decomposition (MOEA/D) decomposes a MOP into a set of single-objective subproblems and approximates the true Pareto front (PF) by optimizing these subproblems in a collaborative manner. However, most existing MOEA/Ds maintain population diversity by limiting the replacement region or scale, which come at the cost of decreasing convergence. To better balance convergence and diversity, we introduce auction theory into algorithm design and propose an auction-based matching (ABM) mechanism to coordinate the replacement procedure in MOEA/D. In the ABM mechanism, each subproblem can be associated with its preferred individual in a competitive manner by simulating the auction process in economic activities. The integration of ABM into MOEA/D forms the proposed MOEA/D-ABM. Furthermore, to make the appropriate distribution of weight vectors, a modified adjustment strategy is utilized to adaptively adjust the weight vectors during the evolution process, where the trigger timing is determined by the convergence activity of the population. Finally, MOEA/D-ABM is compared with six state-of-the-art multi-objective evolutionary algorithms (MOEAs) on some benchmark problems with two to ten objectives. The experimental results show the competitiveness of MOEA/D-ABM in the performance of diversity and convergence. They also demonstrate that the use of the ABM mechanism can greatly improve the convergence rate of the algorithm.

Fluoride is widely present in the environment. Excessive fluoride exposure leads to fluorosis, which has become a global public health problem and will cause damage to various organs and tissues. Only a few studies focus on serum metabolomics, and there is still a lack of systematic metabolomics associated with fluorosis within the main organs. Therefore, in the current study, a non-targeted metabolomics method using gas chromatography-mass spectrometry (GC-MS) was used to research the effects of fluoride exposure on metabolites in different organs, to uncover potential biomarkers and study whether the affected metabolic pathways are related to the mechanism of fluorosis. Male Sprague-Dawley rats were randomly divided into two groups: a control group and a fluoride exposure group. GC-MS technology was used to identify metabolites. Multivariate statistical analysis identified 16, 24, 20, 20, 24, 13, 7, and 13 differential metabolites in the serum, liver, kidney, heart, hippocampus, cortex, kidney fat, and brown fat, respectively, in the two groups of rats. Fifteen metabolic pathways were affected, involving toxic mechanisms such as oxidative stress, mitochondrial damage, inflammation, and fatty acid, amino acid and energy metabolism disorders. This study provides a new perspective on the understanding of the mechanism of toxicity associated with sodium fluoride, contributing to the prevention and treatment of fluorosis.

Fisheries is a social production sector that captures and farms fish and other aquatic animals and plants for aquatic products. In a broad sense, fisheries also include upstream departments (e.g., manufacturing, maintenance and supply of fishing gear, fishing boats, fishery machinery, fishery instruments and other means of production), downstream departments (e.g., storage, processing, comprehensive utilization, transportation and sales of aquatic products), and auxiliary departments (e.g., the construction of fishing ports). As an important constituent part of the national economy in China, fisheries not only provide a large amount of food sources for humans but also provide many industrial raw materials for national construction. In this paper, the development of fisheries in China is reviewed, including the development history of fisheries, the current situations of the aquatic seed industry, aquaculture industry, capture industry, aquatic product processing industry, aquatic animal nutrition and feed industry, and leisure fishery; additionally, the contribution of Chinese fisheries in the global fisheries is assessed, as are the current fisheries development problems and development strategies in China. This paper has important guiding significance for the development of fisheries in China.

Since there are often few or no samples and asymmetry information in the problems, uncertainty theory is introduced to study uncertain multi-objective programming (UMP), which cannot be solved by probability theory. Generally speaking, there are two types of methods for solving the UMP problem: in deterministic method, using the numerical characteristics of an uncertain variable, the UMP problem is transformed into a deterministic multiobjective programming, and then solved by the weighting method and ideal point method; in the uncertain method, the UMP problem is transformed into an uncertain single-objective programming, and then is solved by the evaluation criteria of the uncertain variables. The theoretical analysis and the data results for numerical examples solved by the AC algorithm designed in the paper show that the two types of methods are obviously different. Further, using this comparison, the essential difference between the two methods is whether the uncertainty relation between objective functions sholud be considered. Therefore, when the uncertainty relation is closely related, the uncertain method is more appropriate; otherwise, the deterministic method should be chosen.

UAV trajectory planning is one of the research focuses in artificial intelligence and UAV technology. The asymmetric information, however, will lead to the uncertainty of the UAV trajectory planning; the probability theory as the most commonly used method to solve the trajectory planning problem in uncertain environment will lead to unrealistic conclusions under the condition of lacking samples, while the uncertainty theory based on uncertain measures is an efficient method to solve such problems. Firstly, the uncertainties in trajectory planning are sufficiently considered in this paper; the fuel consumption, concealment and threat degree with uncertain variables are taken as the objective functions; the constraints are analyzed according to the maneuverability; and the uncertain multi-objective trajectory planning (UMOTP) model is established. After that, this paper takes both the long-term benefits and its stability into account, and then, the expected-value and standard-deviation efficient trajectory model is established. What is more, this paper solves the Pareto front of the trajectory planning, satisfying various preferences, which avoids the defects of the trajectory obtained by traditional model only applicable to a certain specific situation. In order to obtain a better solution set, this paper proposes an improved backbones particle swarm optimization algorithm based on PSO and NSGA-II, which overcomes the shortcomings of the traditional algorithm such as premature convergence and poor robustness, and the efficiency of the algorithm is tested. Finally, the algorithm is applied to the UMOTP problem; then, the optimal trajectory set is obtained, and the effectiveness and reliability of the model is verified.