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Reinforcement learning, a cornerstone in the expansive landscape of artificial intelligence, has asserted its dominance as the prevailing methodology in contemporary multiagent system decision-making because of its formidable efficacy. However, the path to the zenith of algorithmic excellence is fraught with challenges intrinsic to traditional multiagent reinforcement learning algorithms, such as dimensionality explosion, scarcity of training samples, and the labyrinthine nature of migration processes. In a concerted effort to surmount these formidable challenges and propel the evolution of algorithmic prowess, this paper unfurls its inquiry from the perspective of learning mechanisms and undertakes an exhaustive exploration of the symbiotic integration of learning mechanisms and reinforcement learning. At the inception of this scholarly expedition, we meticulously delineate the rudimentary principles underpinning multiagent algorithms, present a historical trajectory tracing their developmental evolution, and cast a discerning eye upon the salient challenges that have been formidable impediments in their trajectory. The ensuing narrative charts a course into the avant-garde realm of multiagent reinforcement learning methods anchored in learning mechanisms, a paradigmatic shift that emerges as an innovative frontier in the field. Among these learning mechanisms, meta-learning and transfer learning are empirically validated as useful instruments in hastening the learning trajectory of multiagent systems and simultaneously mitigating the intricate challenges posed by dimensionality explosion. This paper assumes the role of a sagacious guide through the labyrinthine landscape of multiagent reinforcement learning, focusing on the manifold applications of learning mechanisms across diverse domains. A comprehensive review delineates the impact of learning mechanisms in curriculum learning, evolutionary games, meta-learning, hierarchical learning, and transfer learning. The research outcomes within these thematic realms are methodically cataloged, with a discerning eye cast upon the limitations inherent in each methodology and erudite propositions for the trajectory of future improvements. The discourse pivots toward synthesizing advancements and accomplishments wrought by fusion algorithms in practical milieus. This paper meticulously examines the transformative impact of fusion algorithms in real-world applications, with a detailed exposition of their deployment in domains as diverse as traffic control and gaming. Simultaneously, an incisive analysis charting the future trajectory of fusion algorithms is conducted. This prediction encompasses exploring nascent theories, refining algorithmic efficacy, and expanding dissemination and application across a broader spectrum of domains. Through this scholarly odyssey, this paper provides an invaluable compass for navigating the uncharted waters of future research endeavors and the judicious deployment of multiagent reinforcement learning algorithms in pragmatic scenarios.

Objective To investigate asymptomatic infection of hepatitis B virus(HBV) among hepatitis B vaccinated donors in Shenzhen, and analyze its serological and molecular characteristics. Methods The HBsAg ELISA positive blood samples of blood donors born after 1992 were collected. HBsAg, anti-HBs, HBeAg, anti-HBe and anti-HBc were further detected by Roche electrochemiluminescence immunoassay (ECL). BCP/PC and S regions were amplified by Nested-PCRs, HBV DNA quantification were adopted by qPCR simultaneously, and the sequences were also analyzed. Results A total of 46 632 blood samples of donors(31 612 males and 15 020 females) from December 2020 to January 2022 collected, and 99 samples with HBsAg ELISA positive were screened out. After tested by ECL, Nested-PCRs, and real-time fluorescence PCR, 61 were confirmed HBsAg positive, with the positive rate at 0.13% (61/46 632), including 49 males (0.16%, 49/31 612) and 12 females (0.08%, 12/15 020). The HBsAg positive rate of males was higher than that of females (P

Background and purpose: Golgi membrane protein 1 (GOLM1) plays the role of an oncogene in lung adenocarcinoma (LUAD), however, the effects of GOLM1 on the proliferation, invasion and migration of LUAD cells and its mechanism are not clear yet. This study investigated the effects of GOLM1 on the proliferation, invasion and migration of LUAD cells and its mechanism of action. Methods: We selected cancer tissues and corresponding paracancerous tissue specimens from 90 LUAD patients who underwent surgical resection in Karamay Central Hospital from April 2019 to April 2021. The expression of GOLM1 protein in LUAD tissues and paracancerous tissues was detected by immunohistochemistry, and the relationship between GOLM1 protein expression and clinicopathological characteristics of LUAD tissues was analyzed. Western blot was used to detect the expression of GOLM1 protein in human lung epithelial cells BEAS-2B and human lung adenocarcinoma H460, A549, PG49 and H1299 cells. Lung adenocarcinoma A549 cells in logarithmic growth stage were randomly divided into blank group (cells not transfected), GOLM1 small interfering RNA negative control (si-NC) group (cells transfected with si-NC), GOLM1 small interfering RNA (si-GOLM1) group (cells transfected with si-GOLM1), insulin-like growth factor-1 (IGF-1) group [10 μmol/L phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway activator IGF-1 for 30 min] and si-GOLM1+IGF-1 group (after treatment with 10 μmol/L IGF-1 for 30 min, si-GOLM1 was transfected). Cell counting kit-8 method was used to detect cell proliferation in each group of lung adenocarcinoma A549 cells. Scratch test was used to detect cell migration in each group of lung adenocarcinoma A549 cells. Transwell experiment was used to detect cell invasion in each group of lung adenocarcinoma A549 cells. Western blot was used to detect the expressions of GOLM1 and PI3K/AKT/mTOR signaling pathway related proteins in each group of lung adenocarcinoma A549 cells. Xenograft model was constructed by subcutaneously injecting A549 cells on the right side of BALB/c nude mice, which were divided into: nude mice blank group, nude mice si-NC group, nude mice si-GOLM1 group, nude mice IGF-1 group, nude mice si-GOLM1+IGF-1 group, with 6 mice in each group. The nude mice were sacrificed six weeks after injection, the tumor was collected, and the weight and volume of the tumor were measured. Results: The results of immunohistochemistry showed that the positive expression rate of GOLM1 protein was significantly higher in LUAD tissues than in adjacent tissues (P0.05). Compared with BEAS-2B cells, the relative expression level of GOLM1 protein in human lung adenocarcinoma H460, A549, PG49 and H1299 cells was significantly increased (P0.05). Compared with the nude mice blank group and nude mice si-NC group, the mass and volume of transplanted tumors in the nude mice si-GOLM1 group were significantly reduced, while the mass and volume of transplanted tumors in the nude mice IGF-1 group were significantly increased (P

Lactate dehydrogenase (LDH) is one of the important enzymes for anaerobic glycolysis and gluconeogenesis. It could catalyze pyruvate to form lactic acid, which had high application value in food fermentation industry. However, LDH was easily affected by high temperature, which leaded to the decline of lactic acid production. To study the effects of different temperature on the conformation and activity of LDH, molecular dynamics simulations at four different temperatures (37, 55, 70 and 85 °C) were performed for 80 ns, respectively. The overall conformational changed and the differences of enzyme active centers were analyzed. The results showed that LDH was relatively stable at 37 and 55 °C, and the root mean square error, root mean square fluctuation, radius gyration and solvent accessible surface area of LDH increased significantly at 70 and 85 °C. Moreover, the secondary structure of protein had changed greatly at 85 °C, which indicated that high temperature would lead to protein conformational instability. Comparing the binding ability of pyruvate at 37 and 85 °C, which was the substrate of the enzyme, we found that high temperature would increase the distance between the residues of pyruvate binding sites, and then destroy the microenvironment of substrate molecular binding. Therefore, the denaturation of LDH occurred when the temperature exceeded 70 °C, and the denaturation degree was positively correlated with the increase of temperature. This would lead to the loss of its enzyme activity, which was not conducive to the application value in food industry. In this study, the effects of four different temperatures on LDH were analyzed at atomic level, and the key information of enzyme activity and conformation changes were revealed, which provided theoretical support for the selection of appropriate temperature in the fermentation process of lactic acid products.