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Very-long-chain fatty acids (VLCFAs) are essential precursors for plant membrane lipids, cuticular waxes, suberin, and storage oils. Integral to the fatty acid elongase (FAE) complex, 3-ketoacyl-CoA synthases (KCSs) function as crucial enzymes in the VLCFA pathway, determining the chain length of VLCFA. This study explores the in-planta role of the KCS19 gene. KCS19 is predominantly expressed in leaves and stem epidermis, sepals, styles, early silique walls, beaks, pedicels, and mature embryos. Localized in the endoplasmic reticulum, KCS19 interacts with other FAE proteins. kcs19 knockout mutants displayed reduced total wax and wax crystals, particularly alkanes, while KCS19 overexpression increased these components and wax crystals. Moreover, the cuticle permeability was higher for the kcs19 mutants compared to the wild type, rendering them more susceptible to drought and salt stress, whereas KCS19 overexpression enhanced drought and salt tolerance. Disrupting KCS19 increased C18 species and decreased C20 and longer species in seed fatty acids, indicating its role in elongating C18 to C20 VLCFAs, potentially up to C24 for seed storage lipids. Collectively, KCS19-mediated VLCFA synthesis is required for cuticular wax biosynthesis and seed storage lipids, impacting plant responses to abiotic stress.

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This paper introduces BiLSTM-MLAM, a novel multi-scale time series prediction model. Initially, the approach utilizes bidirectional long short-term memory to capture information from both forward and backward directions in time series data. Subsequently, a multi-scale patch segmentation module generates various long sequences composed of equal-length segments, enabling the model to capture data patterns across multiple time scales by adjusting segment lengths. Finally, the local attention mechanism enhances feature extraction by accurately identifying and weighting important time segments, thereby strengthening the model's understanding of the local features of the time series, followed by feature fusion. The model demonstrates outstanding performance in time series prediction tasks by effectively capturing sequence information across various time scales. Experimental validation illustrates the superior performance of BiLSTM-MLAM compared to six baseline methods across multiple datasets. When predicting the remaining life of aircraft engines, BiLSTM-MLAM outperforms the best baseline model by 6.66% in RMSE and 11.50% in MAE. In the LTE dataset, it achieves RMSE improvements of 12.77% and MAE enhancements of 3.06%, while in the load dataset, it demonstrates RMSE enhancements of 17.96% and MAE improvements of 30.39%. Additionally, ablation experiments confirm the positive impact of each module on prediction accuracy. Through segment length parameter tuning experiments, combining different segment lengths has resulted in lower prediction errors, affirming the effectiveness of the multi-scale fusion strategy in enhancing prediction accuracy by integrating information from multiple time scales.

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The evaluation of tumor biomarkers in blood specimens is vital for patients with cervical lesions. Herein, an ultrasensitive surface enhanced Raman scattering (SERS) platform was proposed for simultaneous detection of cervical-lesion-related serum biomarkers. Raman reporter labeled Au-Ag nanoshells (Au-AgNSs) acted as SERS tags and an Au-Ag nanobox (Au-AgNB) array substrate prepared by the oil-water interface self-assembly method was used as a capture substrate. This single-layer Au-AgNB array substrate was proved to have exceptional uniformity by atomic force microscopy and SERS mapping. Numerous "hot spots" and specific adsorption surfaces offered by the Au-AgNB array substrate were confirmed by the finite difference time domain method, which could generate a SERS signal in electromagnetic enhancement. Binding of antigens between antibodies on Au-AgNSs and the Au-AgNB array substrate led to the formation of a sandwich-structure by the two metal nanostructures. Consequently, an ultralow detection limit of 6 pg mL-1 for squamous cell carcinoma antigen (SCCA) and 5 pg mL-1 for survivin in a wide linear logarithmic range of 10 pg mL-1 to 10 µg mL-1 was acquired. High selectivity and reproducibility with relative standard deviations of 7.701% and 6.943% were detected. Furthermore, the simultaneous detection of the two biomarkers in practical specimens was conducted, and the results were consistent with those of the enzyme-linked immunosorbent assay. This platform exhibited good robustness in the rapid and sensitive detection of SCCA and survivin, which could be a promising tool in early clinical diagnosis for different grades of cervical lesions.

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A novel gene (designated as cen219) encoding endoglucanase was isolated from a Bursaphelenchus xylophilus metagenomic library by functional screening. Sequence analysis revealed that cen219 encoded a protein of 367 amino acids. SDS-PAGE analysis of purified endoglucanase suggested that Cen219 was a monomeric enzyme with a molecular mass of 40 kDa. The optimum temperature and pH for endoglucanase activity of Cen219 was separately 50 °C and 6.0. It was stable from 30 to 50 °C, and from pH 4.0 to 7.0. The activity was significantly enhanced by Mn(2+) and dramatically reduced by detergent SDS and metals Fe(3+), Cu(2+) or Hg(2+). The enzyme hydrolyzed a wide range of ß-1, 3-, and ß-1, 4-linked polysaccharides, with varying activities. Activities towards microcrystalline cellulose and filter paper were relatively high, while the highest activity was towards oat gum. The Km and Vmax of Cen219 towards CMC was 17.37 mg/ml and 333.33 U/mg, respectively. The findings have an insight into understanding the molecular basis of host-parasite interactions in B. xylophilus species. The properties also make Cen219 an interesting enzyme for biotechnological application.

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OBJECTIVE: To screen, identify bacterial strains with high capability to degrade cellulose from bacteria associated with Bursaphelenchus xylophilus and to clone related genes. METHODS: First, we collected B. xylophilus samples from pine wood nematode disease areas in Nanyang, Henan province, China. Then, we obtained the bacterial strains with high cellulase activities by primarily screening according to Congo red plate methods. The bacterial strain was classified by phenotypic and genotypic characteristics. We designed degenerate primes according to the known endoglucanase gene sequences in GenBank to carry out PCR, and analyzed the cloned sequence. RESULTS: We obtained seven bacterial strains with high cellulase activities. Among them, the bacterial strain numbered C8 showed the highest cellulase activities. The bacterium was classified to be Enterobacter genus. The full length of a cellulase gene cDNA (1104 bp) (GenBank JQ845065) coding region was successfully cloned. The homogeneous analysis demonstrated that the deduced nucleotide and amino acid of the gene separately shared 97% and 92% with the cellulase from E. aerogenes KCTC 2190, and 82% with the endo-1,4-D-glucanase gene from Klebsiella pneumoniae, and 82% with the a cellulase gene from unculturable bacteria. CONCLUSION: It was a novel cellulose gene cloned from B. xylophilus associated bacteria.

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