Quality control prediction of electrolytic copper using novel hybrid nonlinear analysis algorithm.

Traditional linear regression and neural network models demonstrate suboptimal fit and lower predictive accuracy while the quality of electrolytic copper is estimated. A more dependable and accurate model is essential for these challenges. Notably, the maximum information coefficient was employed initially to discern the non-linear correlation between the nineteen factors influencing electrolytic copper quality and the five quality control indicators. Additionally, the random forest algorithm elucidated the primary factors governing electrolytic copper quality. A hybrid model, integrating particle swarm optimization with least square support vector machine, was devised to predict electrolytic copper quality based on the nineteen factors. Concurrently, a hybrid model combining random forest and relevance vector machine was developed, focusing on primary control factors. The outcomes indicate that the random forest algorithm identified five principal factors governing electrolytic copper quality, corroborated by the non-linear correlation analysis via the maximum information coefficient. The predictive accuracy of the relevance vector machine model, when accounting for all nineteen factors, was comparable to the particle swarm optimization-least square support vector machine model, and surpassed both the conventional linear regression and neural network models. The predictive error for the random forest-relevance vector machine hybrid model was notably less than the sole relevance vector machine model, with the error index being under 5%. The intricate non-linear variation pattern of electrolytic copper quality, influenced by numerous factors, was unveiled. The advanced random forest-relevance vector machine hybrid model circumvents the deficiencies seen in conventional models. The findings furnish valuable insights for electrolytic copper quality management.

Volatile Profiling and Transcriptome Sequencing Provide Insights into the Biosynthesis of α-Pinene and ß-Pinene in Liquidambar formosana Hance Leaves.

Liquidambar formosana Hance is a pinene-rich deciduous plant species in the Altingiaceae family that is used as a medicinal plant in China. However, the regulatory mechanisms underlying α-pinene and ß-pinene biosynthesis in L. formosana leaves remain unknown. Here, a joint analysis of the volatile compounds and transcriptomes of L. formosana leaves was performed to comprehensively explore the terpene synthase (TPS) that may participate in α-pinene and ß-pinene biosynthesis. Headspace solid-phase microextraction (HS-SPME) and gas chromatography-mass spectrometry (GC-MS) jointly detected volatile L. formosana leaves. Trees with high and low levels of both α-pinene and ß-pinene were defined as the H group and L group, respectively. RNA sequencing data revealed that DXR (1-deoxy-D-xylulose-5-phosphate reductoisomerase), HDS [(E)-4-hydroxy-3-methylbut-2-eny-l-diphosphate synthase], and TPS may be the major regulators of monoterpenoid biosynthesis. We identified three TPSs (LfTPS1, LfTPS2, and LfTPS3), which are highly homologous to α-pinene and ß-pinene synthases of other species in phylogenetic analysis. Four TPS genes (LfTPS1, LfTPS2, LfTPS4, LfTPS5) may be critically involved in the biosynthesis and regulation of α-pinene and ß-pinene in L. formosana. Bioinformatic and transcriptomic results were verified using quantitative real-time PCR. We identified LfTPS1, LfTPS2 as candidate genes for α-pinene and ß-pinene biosynthesis that significantly improve the yield of beneficial terpenoids.

The Novel Nuclear Targeting and BFRF1-Interacting Domains of BFLF2 Are Essential for Efficient Epstein-Barr Virus Virion Release.

Epstein-Barr virus (EBV) genomic DNA is replicated and packaged into procapsids in the nucleus to form nucleocapsids, which are then transported into the cytoplasm for tegumentation and final maturation. The process is facilitated by the coordination of the viral nuclear egress complex (NEC), which consists of BFLF2 and BFRF1. By expression alone, BFLF2 is distributed mainly in the nucleus. However, it colocalizes with BFRF1 at the nuclear rim and in cytoplasmic nuclear envelope-derived vesicles in coexpressing cells, suggesting temporal control of the interaction between BFLF2 and BFRF1 is critical for their proper function. The N-terminal sequence of BFLF2 is less conserved than that of alpha- and betaherpesvirus homologs. Here, we found that BFLF2 amino acids (aa) 2 to 102 are required for both nuclear targeting and its interaction with BFRF1. Coimmunoprecipitation and confocal analysis indicated that aa 82 to 106 of BFLF2 are important for its interaction with BFRF1. Three crucial amino acids (R47, K50, and R52) and several noncontinuous arginine and histidine residues within aa 59 to 80 function together as a noncanonical nuclear localization signal (NLS), which can be transferred onto yellow fluorescent protein (YFP)-LacZ for nuclear targeting in an importin ß-dependent manner. Virion secretion is defective in 293 cells harboring a BFLF2 knockout EBV bacmid upon lytic induction and is restored by trans-complementation of wild-type BFLF2, but not NLS or BFRF1-interacting defective mutants. In addition, multiple domains of BFRF1 were found to bind BFLF2, suggesting multiple contact regions within BFRF1 and BFLF2 are required for proper nuclear egress of EBV nucleocapsids.IMPORTANCE Although Epstein-Barr virus (EBV) BFRF1 and BFLF2 are homologs of conserved viral nuclear egress complex (NEC) in all human herpesviruses, unique amino acid sequences and functions were identified in both proteins. In this study, the nuclear targeting and BFRF1-interacting domains were found within the N terminus of BFLF2. We showed that amino acids (aa) 82 to 106 are the major region required for BFLF2 to interact with BFRF1. However, the coimmunoprecipitation (Co-IP) data and glutathione transferase (GST) pulldown experiments revealed that multiple regions of both proteins contribute to reciprocal interactions. Different from the canonical nuclear localization signal (NLS) in other herpes viral homologs, BFLF2 contains a novel importin-dependent nuclear localization signal, including R47, K50, and R52 and several neighboring discontinuous arginine and histidine residues. Using a bacmid complementation system, we show that both the nuclear targeting and the novel nuclear localization signal within aa 82 to 106 of BFLF2 are required for virion secretion.

[Optimization method of MOS sensor array for identification of traditional Chinese medicine based on electronic nose].

Optimization of sensor array is a significant topic in the application of electronic nose (EN). Stepwise discriminant analysis and cluster analysis combining with screening of typical index were employed to optimize the original array in the classification of 100 samples from 10 kinds of traditional Chinese medicine based on alpha-FOX3000 EN. And the identification ability was evaluated by three algorithm including principle component analysis, Fisher discriminant analysis and random forest. The results showed that the identification ability of EN was improved since not only the effective information was maintained but also the redundant one was eliminated by the optimized array. The optimized method was eventually established, it was accurate and efficient. And the optimized array was built up, that is, S1, S2, S5, S6, S8, S12.