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The rapid development of Internet of vehicles (IoV) depends on the safe and reliable infrastructure for storing and sharing large amounts of data. Blockchain, a kind of distributed data storage technology that cannot be forged and tampered with, can solve the security and privacy issues of IoV. However, the low throughput of blockchain hinders its wide application in IoV. The current research on blockchain throughput optimization has poor scalability because of its action space explosion. Aiming at the above problems, a blockchain throughput optimi-zation method in IoV based on deep reinforcement learning (DRL) is proposed to maximize the transaction throughput, and optimize the throughput of the blockchain by choosing block producers and consensus algorithms, adjusting block size and block interval while ensuring the decentralization, low delay and high security of the underlying blockchain system. This method introduces the branching dueling Q-network (BDQ) framework in DRL, carries out fine-grained division for action space, and solves the problem of action space explosion of traditional deep reinforcement learning methods. Simulation results show that the proposed method can improve the throughput of blockchain in IoV effectively.

Background Many medical postgraduate students exhibit a lack of clarity in their understanding of relevant statistical concepts during the conduct of diagnostic studies. Methods This article, grounded in research practice, delves into the role of understanding statistical concepts in diagnostic research. It includes an exploration of sensitivity, specificity, types of statistical errors, and their interrelationships, as well as a discussion on statistical power—an often-overlooked but crucial concept in research. Results The article elucidates these important concepts with specific examples and illustrations, and addresses an issue of inconsistency related to the receiver operating characteristic curve in research practice. Conclusion By drawing analogies between basic concepts in diagnostic tests and concepts in statistics, this article helps to enhance researchers' abilities in designing and interpreting clinical diagnostic studies, thereby improving the quality of clinical diagnostic research. [ABSTRACT FROM AUTHOR]

This study aimed to assess the impact of alcalase, trypsin, flavourzyme, and neutrase on the characteristics, antioxidant activity stability, and anti-fatigue activity of hydrolysates derived from Cucumaria frondosa tentacles (CFTHs). The results demonstrate that favourzyme hydrolysates exhibited the highest degree of hydrolysis (DH). Zeta potential and particle size measurements indicated that hydrolyzed peptides treated with favourzyme appeared aggregated and exhibited larger particle sizes. The antioxidant properties of CFTHs demonstrated good thermal stability, pH stability, and enhanced simulated gastrointestinal digestive stability. The anti-fatigue activity of CFTHs was examined using an acute exercise fatigue model. The results indicate that CFTHs extended the exhaustive swimming time of mice to 17.81 min. Additionally, CFTHs significantly elevated (p < 0.01) blood glucose (Glu) and liver glycogen (LG) levels, while also decreasing (p < 0.05) the concentrations of metabolites such as lactic acid (LA), urea nitrogen (BUN), creatine kinase (CK), lactate dehydrogenase (LDH), and ammonia (NH3). This reduction contributed to the alleviation of fatigue in the body. Furthermore, the levels of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) were significantly increased (p < 0.05), which aided in mitigating oxidative damage induced by strenuous exercise. These findings strongly support the potential utilization of CFTHs in food products as natural antioxidant and anti-fatigue alternatives. [ABSTRACT FROM AUTHOR]

Background Many medical graduate students lack a thorough understanding of decision curve analysis (DCA), a valuable tool in clinical research for evaluating diagnostic models. Methods This article elucidates the concept and process of DCA through the lens of clinical research practices, exemplified by its application in diagnosing liver cancer using serum alpha-fetoprotein levels and radiomics indices. It covers the calculation of probability thresholds, computation of net benefits for each threshold, construction of decision curves, and comparison of decision curves from different models to identify the one offering the highest net benefit. Results The paper provides a detailed explanation of DCA, including the creation and comparison of decision curves, and discusses the relationship and differences between decision curves and receiver operating characteristic curves. It highlights the superiority of decision curves in supporting clinical decision-making processes. Conclusion By clarifying the concept of DCA and highlighting its benefits in clinical decisionmaking, this article has improved researchers' comprehension of how DCA is applied and interpreted, thereby enhancing the quality of research in the medical field. [ABSTRACT FROM AUTHOR]

Parvalbumins have long been identifified as major allergens in fish, but our research has found that parvalbumins are not the main cause of allergic reactions to tilapia. After homogenization, proteins were extracted from freshwater tilapia to react with a pooled sera sample taken from patients ( n == 20) tested to be allergic to tilapia. Enzyme-linked immunosorbent assay revealed immunoglobulin E antibody activity, followed by sodium dodecyl sulphate polyacrylamide gel electrophoresis, Western blot, 2D electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to carry out protein separation and analysis. Protein identification against different databases yielded three known high molecular weight proteins as tilapia allergens: chromosome undetermined SCAF7145, fructose-bisphosphate aldolase A and enolase 3 (beta muscle). A fourth, new, unidentified protein with two T-cell receptors was discovered. [ABSTRACT FROM AUTHOR]

We wished to screen the cell line that stably expresses the HPV18E5 protein, and to ascertain the influence of HPV18E5 protein on cell proliferation and the cell cycle. The HPV18E5 gene was amplified by the polymerase chain reaction. Then, the His-tag pSecTag-HPV18E5 eukaryotic expression vector was constructed by digestion ligation and connection. The recombinant plasmid was transfected into Balb/c3T3 cells with lipofectamine, and positive cell lines were screened by a culture medium containing bleomycin. HPV18E5 expression in cells was confirmed by western blotting and immuno-enzymatic methods. The influence of HPV18E5 on cell proliferation and the cell cycle were detected by Cell Counting Kit-8 and flow cytometry, respectively. The pSecTag-HPV18E5 eukaryotic expression vector was constructed. After 21-day selection in a culture medium containing 400 μg/mL bleomycin, stably expressing HPV18E5 protein cells were harvested. Compared with control groups, cell proliferation in HPV18E5 stably expressed cells was obviously increased, as was the S phase in the cell cycle. Our results suggested that HPV18E5 influences cell proliferation and the cell cycle. Our study has laid the foundation of the biologic properties of HPV18E5 protein, which will aid further studies on the mechanism of action of carcinogenesis.

Fish are an important source of dietary protein for humans throughout the world. However, they are recognized as one of the most common food allergens and pose a serious health problem in countries where fish consumption is high. Many marine fish allergens have been extensively studied, but relatively little is known about freshwater fish allergens. This study identified two main allergens from blunt snout bream (Megalobrama amblycephala), a freshwater fish widely consumed in China. Sera from 11 patients with convincing clinical history of blunt snout bream allergy were utilized in IgE immunoblot analysis to identify prominent allergens. Several blunt snout bream proteins revealed specific binding to serum IgE, with the 47 and 41 kDa proteins being the most immunodominant among them. Two-dimensional gel electrophoresis (2D SDS-PAGE) enabled resolution of the 47 and 41 kDa proteins into several protein spots with distinct isoelectric points. 2D SDS-PAGE along with IgE immunoblot analysis further confirmed the strong reactivity of these protein spots with the pooled sera from blunt snout bream-sensitive patients. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis of the peptides generated by trypsin digestion of the different spots corresponding to the 47 and 41 kDa proteins indicated that these spots were isoforms of enolase and muscle creatine kinase, respectively. The potential allergenicity of these proteins was further verified by an bioinformatics approach using the full-length and 80 amino acid sliding window FASTA searches, which revealed a significant amino acid sequence homology between blunt snout bream allergens and several known inhaled and crustacean allergens.