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BACKGROUND: The Colorado potato beetle (CPB), Leptinotarsa decemlineata, is a major potato (Solanum tuberosum) pest, infesting over 16 million km2 and causing substantial economic losses. The insect cuticle forms an apical extracellular matrix (ECM) envelope covering exposed organs to direct morphogenesis and confer structural protection. While select chitinase (Cht) genes have proven essential for larval development, their potential activities directing ECM remodeling underlying adult wing maturation remain undefined. RESULTS: We investigated the expression patterns and performed an oral RNA interference (RNAi) screen targeting 19 LdChts in late-instar L. decemlineata larvae. Subsequently, we assessed their effects on adult eclosion and wing characteristics. Knockdown of LdCht5, LdCht7, LdCht10, LdIDGF2, and LdIDGF4, as well as others from Group IV (LdCht15, LdCht12, LdCht17, and LdCht13) and Groups VII-X (LdCht2, LdCht11, LdCht1, and LdCht3), resulting in shrunken, misshapen elytra with reduced areal density, as well as transverse wrinkling and impaired wing-tip folding in hindwings. Scanning electron micrographs revealed eroded elytral ridges alongside thinned, ruptured hindwing veins, indicative of mechanical fragility post-LdCht suppression. Spectroscopic analysis uncovered biomolecular alterations underlying the elytral anomalies, including decreases in peaks representing chitin, proteins, and lipids. This loss of essential ECM components provides evidence for the fragility, wrinkling, and shrinkage observed in the RNAi groups. CONCLUSION: Our findings elucidate the crucial role of chitinases in the turnover of chitinous cuticles on beetle wings, offering insights into RNAi-based control strategies against this invasive pest. © 2024 Society of Chemical Industry.
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BACKGROUND: Olfactory dysfunction is among the earliest non-motor symptoms of Parkinson's disease (PD). As the foremost pathological hallmark, α-synuclein initiates the pathology in the olfactory pathway at the early stage of PD, particularly in the olfactory epithelium (OE) and olfactory bulb (OB). However, the local neural microcircuit mechanisms underlying olfactory dysfunction between OE and OB in early PD remain unknown. RESULTS: We observed that odor detection and discrimination were impaired in 6-month-old SNCA-A53T mice, while their motor ability remained unaffected. It was confirmed that α-synuclein increased and accumulated in OB but not in OE. Notably, the hyperactivity of mitral/tufted cells and the excitation/inhibition imbalance in OB were found in 6-month-old SNCA-A53T mice, which was attributed to the impaired GABAergic transmission and aberrant expression of GABA transporter 1 and vesicular GABA transporter in OB. We further showed that tiagabine, a potent and selective GABA reuptake inhibitor, could reverse the impaired olfactory function and GABAergic signaling in OB of SNCA-A53T mice. CONCLUSIONS: Taken together, our findings demonstrate potential synaptic mechanisms of local neural microcircuit underlying olfactory dysfunction at the early stage of PD. These results highlight the critical role of aberrant GABAergic signaling of OB in early diagnosis and provide a potential therapeutic strategy for early-stage PD.
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The present paper,on the basis of analyzing the terrain scattering characteristics, proposed a novel supervised classification method combined with complex Wishart classifier ideology. This method used coherent matrix which almost contains all the polarization information to make subsequent adjustments for the supervised classification result to achieve higher accuracy division categories. For the first beginning, supervised classification was carried out on the Cloude & Pottier polarimetric characteristics combination to get the initial classification result. Then, in order to achieve the purpose to correct the mistakes resulting from just using the spatial distribution of feature vectors in supervised classification, we did some analysis as follow. The accuracy analysis of the classification results and the analysis of study area feature scattering similarity play an important role in our study to help us make the determination that the pixels need to be adjusted. Furthermore, taking the mean value of each category coherence matrix as the initial cluster centers of subsequent iterations, and using Kernel Fuzzy C-Means algorithm to adjust the fixed pixel set categories by subsequent category iterative correction, the fine and high-accuracy classification results were obtained, combined with complex Wishart distribution of coherence matrix. The domestic X-band full polarization SAR data of Lingshui area in Hainan province was applied in this classification experiment. The experiment results demonstrate that the proposed method can obtain a favorable classification accuracy polarization SAR image classification results, and better meet the scattering characteristics of the surface objects compared to the original method.
