Molluscs form their shells out of CaCO 3 and a matrix of biomacromolecules. Understanding the role of matrices may shed some light on the mechanism of biomineralization. Here, a 1401-bp full-length cDNA sequence encoding a novel matrix protein was cloned from the mantle of the bivalve oyster, Pinctada fucata. The deduced protein (Prisilkin-39), which has a molecular mass of 39.3 kDa and an isoelectric point of 8.83, was fully characterized, and its role in biomineralization was demonstrated using both in vivo and in vitro crystal growth assays. Prisilkin-39 is a highly repetitive protein with an unusual composition of Gly, Tyr, and Ser residues. Expression of Prisilkin-39 was localized to columnar epithelial cells of the mantle edge, corresponding to the calcitic prismatic layer formation. Immunostaining in situ and immunodetection in vitro revealed the presence of a characteristic pattern of Prisilkin-39 in the organic sheet and in sheaths around the prisms. Prisilkin-39 binds tightly with chitin, an insoluble polysaccharide that forms the highly structured framework of the shell. Antibody injection in vivo resulted in dramatic morphological deformities in the inner shell surface structure, where large amounts of CaCO 3 were deposited in an uncontrolled manner. Moreover, Prisilkin-39 strictly prohibited the precipitation of aragonite in vitro. Taken together, Prisilkin-39 is the first protein shown to have dual function, involved both in the chitinous framework building and in crystal growth regulation during the prismatic layer mineralization. These observations may extend our view on the rare group of basic matrices and their functions during elaboration of the molluscan shell.

Smart windows control indoor solar radiation by regulating the transmittance of light, which is a promising way to reduce building energy consumption. The advent of photonic crystals (PCs) has accelerated the industrialization of smart windows. The combination of static and dynamic regulation can be realized based on the photon control function of photonic band gaps, which is expected to achieve the ideal effect of light transmission and heat control. This paper reviews recent advances of electrochromic and thermochromic smart windows based on PCs. Firstly, theory, materials, performance and development of electrochromic and thermochromic smart windows based on PCs are briefly outlined. Typical structures of electrochromic and thermochromic PCs are introduced in detail, from preparation process, morphology characterization and performance analysis, which provides directions for the future development and construction of smart windows based on PCs. Finally, challenges and opportunities facing next-generation smart windows are summarized.

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Edible gelatin has been widely used as a food additive in the food industry, and illegal adulteration with industrial gelatin will cause serious harm to human health. The present work used laser-induced breakdown spectroscopy (LIBS) coupled with the partial least square–support vector machine (PLS-SVM) method for the fast and accurate estimation of edible gelatin adulteration. Gelatin samples with 11 different adulteration ratios were prepared by mixing pure edible gelatin with industrial gelatin, and the LIBS spectra were recorded to analyze their elemental composition differences. The PLS, SVM, and PLS-SVM models were separately built for the prediction of gelatin adulteration ratios, and the hybrid PLS-SVM model yielded a better performance than only the PLS and SVM models. Besides, four different variable selection methods, including competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MC-UVE), random frog (RF), and principal component analysis (PCA), were adopted to combine with the SVM model for comparative study; the results further demonstrated that the PLS-SVM model was superior to the other SVM models. This study reveals that the hybrid PLS-SVM model, with the advantages of low computational time and high prediction accuracy, can be employed as a preferred method for the accurate estimation of edible gelatin adulteration.

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In recent years, there has been growing concern among consumers about pesticide contamination in fruits. Therefore, rapid, reliable, and consistent detection methods for OPPs, especially dimethoate, are crucially needed. The existing quantitative methods for detecting dimethoate are not suitable for rapid measuring system such as the dimethoate samples from two channels. Hence this paper examines the utilization of a dual-channel system for utilize the absorption variations of the Localized Surface Plasmon Resonance (LSPR) bands of gold nanoparticles (AuNPs) were investigate for detection of dimethoate. Under optimized conditions, the relationship between concentrations of dimethoate and absorbance ratios (A(520)/A(640)) was linearly found in the concentration range of 10-100 nM. Result from the experiment shows that both channels exhibit a linear correlation coefficient as high as 0.97 and a limit of detection (LOD) as low as 5.5 nM. This LSPR detection system was characterized by testing the dimethoate in apple samples and the recovery rates were found to be in the range of 85.90% to 107.37%. The proposed dual-channel LSPR system for detecting dimethoate creating a new approach for detecting organophosphate insecticide in agricultural fields. It could lay the foundation for designing a high-throughput analysis of the insecticides using a wavelength division multiplexing switch (WDMS).