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PLCPs (papain-like cysteine proteases) are one of the most abundant groups of cysteine proteases and play vital roles in multiple processes. The pepper (Capsicum annuum) is an important Solanaceae vegetable crop; its commercial hybrid seeds are widely used in production. Male sterility is a valuable trait for hybrid seed production. However, the function of PLCPs and the underlying mechanisms of male sterility in peppers remain unclear. In this study, we comprehensively identified the PLCP gene family in peppers, identifying 31 CaPLCPs. A phylogenetic analysis classified 31 members into eight clades. These CaPLCPs were unevenly distributed across eight chromosomes, and five segmental duplicated pairs were observed. The promoter cis-acting element analysis indicated that CaPLCP promoters contained abundant hormone-responsive and stress-responsive cis-elements, suggesting that CaPLCPs may play important roles in responding to abiotic stress, such as drought and low temperatures, as well as in plant immunity. The qRT-PCR analysis demonstrated that the expression levels of CaPLCP1, CaPLCP5, CaPLCP11, CaPLCP12, CaPLCP13, CaPLCP17, CaPLCP19, and CaPLCP21 were significantly reduced in the flowers of MS (male sterile pepper) at least at one stage, indicating their potential roles as regulatory factors in pepper male sterility. These findings provide important insights into the functional analysis of the PLCP gene family in peppers and other species, laying a crucial foundation for understanding the mechanisms of male sterility in peppers. [ABSTRACT FROM AUTHOR]

In the in-situ quality detection of yarn production, image deblurring plays a critical role in the vision-based detection systems to restore a sharp image and provide more accurate input for inspection. However, image deblurring is still challenging since the current methods are mainly based on the pre-defined blur degree. In dynamic yarn production, the relationship between the defocus blur degrees and the poses of the yarn body is highly associated, which can be excavated to prior knowledge in image deblurring to achieve more effective restoration. Thus, a knowledge augmented deep learning model is proposed to adaptively deblur yarn images with variable defocus blur degrees. A pose classification module designed by prior knowledge is embedded into the deep neural network, which classifies the yarn poses and feeds them into multi-scale deblurring channels. In each channel, we incorporate the image gradient prior into the specially designed loss function to attract the attention of the deblurring network on the edge details of the yarn. The experimental results from actual spinning processes demonstrate that the proposed method performs a better effect not only in the variable-scale deblurring of the global image but also in the restoration of the edge details. [ABSTRACT FROM AUTHOR]

A formal [4+2] annulation reaction of phthalaldehydes and 3‐ylideneoxindoles through a tandem process of a Stetter–aldol reaction was accomplished by the application N‐heterocyclic carbenes as effective catalysts. Under mild conditions, this unprecedented cascade reaction readily occurs in good yield, enabling straightforward access to functionalized tetrahydronaphthalene‐fused spirooxindoles. For the first time, the feasibility of an asymmetric Stetter–aldol reaction has also been briefly explored by employing chiral organic bases to promote the asymmetric transformation. [ABSTRACT FROM AUTHOR]

Foodborne pathogens are important factors that contribute to foodborne illnesses, posing significant threats to food safety and human health, and presenting a major challenge for global healthcare systems. Contaminated food matrices are complex and often have low concentrations of early-stage pathogens, which hinder the sensitivity of existing detection methods. Traditional microbial culture methods are typically used to increase the concentration of pathogens for detection purposes, but these methods are time-consuming and labor-intensive, making them inadequate for the rapid testing needs of regulatory authorities. Therefore, there is an urgent need for effective methods of isolating and enriching foodborne pathogens to accurately detect early-stage contamination in food and ensure food safety. In recent years, magnetic nanoparticles have been extensively studied. By modifying their surfaces with recognition elements that can specifically bind to pathogens, they can effectively isolate and enrich foodborne pathogens in complex food matrices. When combined with existing highly sensitive detection methods, these magnetic nanoparticles enable rapid early-stage detection of foodborne pathogens. This article provides an overview of Magnetic nanoseparation technology, the coupling methods of magnetic nanoparticles with recognition elements, the types of recognition elements, and the application of combined detection methods. The aim is to provide reference for the development of rapid detection methods for foodborne pathogens. [ABSTRACT FROM AUTHOR]