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The molting process of the lepidopteran insects is observed for many species. However, the detailed description of the morphological transformation and behavioral sequence during molting are rarely provided and visualized. Here, we described the molting process of the diamondback moth Plutella xylostella by providing the duration and photographic details of staging criteria of each stage using stereo microscopy and a digital video camera. We divided the morphological transformation of egg development and hatching into five stages, the larval–larval ecdysis and the larval–pupal metamorphosis into five stages, the pupal development and eclosion into three stages, and the post-eclosion behavior into four stages. Several new characters in the molting process that were not previously described in other lepidopteran insects were found, i.e., the larvae contracted anterior-posteriorly then dorsal-ventrally during pre-ecdysis, and the antennae waved backward then forward in the post-eclosion behavior. Our findings will deepen the knowledge of the molting biology of lepidopteran insects and facilitate the study of the underlying mechanisms.

Abstract Parasitoids introduce various virulence factors when parasitism occurs, and some taxa generate teratocytes to manipulate the host immune system and metabolic homeostasis for the survival and development of their progeny. Host-parasitoid interactions are extremely diverse and complex, yet the evolutionary dynamics are still poorly understood. A category of serpin genes, named CvT-serpins, was discovered to be specifically expressed and secreted by the teratocytes of Cotesia vestalis, an endoparasitoid of the diamondback moth Plutella xylostella. Genomic and phylogenetic analysis indicated that the C. vestalis serpin genes are duplicated and most of them are clustered into 1 monophyletic clade. Intense positive selection was detected at the residues around the P1–P1′ cleavage sites of the Cv-serpin reactive center loop domain. Functional analyses revealed that, in addition to the conserved function of melanization inhibition (CvT-serpins 1, 16, 18, and 21), CvT-serpins exhibited novel functions, i.e. bacteriostasis (CvT-serpins 3 and 5) and nutrient metabolism regulation (CvT-serpins 8 and 10). When the host-parasitoid system is challenged with foreign bacteria, CvT-serpins act as an immune regulator to reprogram the host immune system through sustained inhibition of host melanization while simultaneously functioning as immune effectors to compensate for this suppression. In addition, we provided evidence that CvT-serpin8 and 10 participate in the regulation of host trehalose and lipid levels by affecting genes involved in these metabolic pathways. These findings illustrate an exquisite tactic by which parasitoids win out in the parasite–host evolutionary arms race by manipulating host immune and nutrition homeostasis via adaptive gene evolution and neofunctionalization.

Parasitoids modulate host development for the survival of their offspring, but the mechanisms underlying this phenomenon remain largely unknown. Here, we found that the endoparasitoid Cotesia vestalis disrupted the larval-larval ecdysis in its host Plutella xylostella by the 20-hydroxyecdysone (20E) synthesis pathway. After parasitization by C. vestalis , the 20E peak of host larvae disappeared before the onset of ecdysis and the expression of ecdysone synthesis genes was significantly downregulated. We further found that a Cotesia vestalis bracovirus (CvBV) gene CvBV_28 − 5 was transiently high-level expressed prior to the host’s 20E peak, enabling the precise suppression of this critical developmental signal. Consistently, the knockdown of CvBV_28 − 5 affected the expression of 20E response transcription factors in the cuticle and several ecdysis-related genes. Furthermore, we found that CvBV_28 − 5 bound directly to the Raf, a MAP3K member of the MAPK pathwaythat functions as a critical regulator of ecdysone synthesis genes in hosts. Collectively, our results provide the first evidence that parasitoids modulate host ecdysis by affecting MAPK-20E signaling during a defined developmental window and provide novel insights into the mechanism of parasitoid regulation of host development.

Enzymatic catalysis in living cells enables the in-situ detection of cellular metabolites in single cells, which could contribute to early diagnosis of diseases. In this study, enzyme is packaged in amorphous metal-organic frameworks (MOFs) via a one-pot co-precipitation process under ambient conditions, exhibiting 5–20 times higher apparent activity than when the enzyme is encapsulated in corresponding crystalline MOFs. Molecular simulation and cryo-electron tomography (Cryo-ET) combined with other techniques demonstrate that the mesopores generated in this disordered and fuzzy structure endow the packaged enzyme with high enzyme activity. The highly active glucose oxidase delivered by the amorphous MOF nanoparticles allows the noninvasive and facile measurement of glucose in single living cells, which can be used to distinguish between cancerous and normal cells. For packaging enzymes into metal–organic frameworks (MOFs), crystalline MOFs are usually used. Here, the authors encapsulated enzymes in amorphous MOFs a via one-pot co-precipitation process under ambient condition, which led to higher enzymatic activity than in a corresponding crystalline MOF composite.

To enhance the generalization of networks and avoid redundant training efforts, cross-image hyperspectral anomaly detection (HAD) based on deep learning has been gradually studied in recent years. Cross-image HAD aims to perform anomaly detection on unknown hyperspectral images after a single training process on the network, thereby improving detection efficiency in practical applications. However, the existing approaches may require additional supervised information or stacking of networks to improve model performance, which may impose high demands on data or hardware in practical applications. In this paper, a simple and lightweight unsupervised cross-image HAD method called Variational Joint Discrimination Network (VJDNet) is proposed. We leverage the reconstruction and distribution representation ability of the variational autoencoder (VAE), learning the global and local discriminability of anomalies jointly. To integrate these representations from the VAE, a probability distribution joint discrimination (PDJD) module is proposed. Through the PDJD module, the VJDNet can directly output the anomaly score mask of pixels. To further facilitate the unsupervised paradigm, a sample pair generation module is proposed, which is able to generate anomaly samples and background representation samples tailored for the cross-image HAD task. The experimental results show that the proposed method is able to maintain the detection accuracy with only a small number of parameters.

Atherosclerotic plaque instability contributes to ischaemic stroke and myocardial infarction. This study is to compare the abundance and difference of immune cell subtypes within unstable atherosclerotic tissues. CIBERSORT was used to speculate the proportions of 22 immune cell types based on a microarray of atherosclerotic carotid artery samples. R software was utilized to illustrate the bar plot, heat map and vioplot. The immune cell landscape in atherosclerosis was diverse, dominated by M2 macrophages, M0 macrophages, resting CD4 memory T cells and CD8 T cells. There was a significant difference in resting CD4 memory T cells (p = 0.032), T cells follicular helper (p = 0.033), M0 (p = 0.047) and M2 macrophages (p = 0.012) between stable and unstable atherosclerotic plaques. Compared with stable atherosclerotic plaques, unstable atherosclerotic plaques had a higher percentage of M2 macrophages. Moreover, correlation analysis indicated that the percentage of naïve CD4 T cells was strongly correlated with that of gamma delta T cells (r = 0.93, p < 0.001), while memory B cells were correlated with plasma cells (r = 0.85, p < 0.001). In summary, our study explored the abundance and difference of specific immune cell subgroups at unstable plaques, which would aid new immunotherapies for atherosclerosis.

Social anxiety has been associated with abnormalities in cognitive processing in the literature, manifesting as various cognitive biases. To what extent these biases interrupt social interactions remains largely unclear. This study used the Social Judgment Paradigm that could separate the expectation and experience stages of social feedback processing. Event-related potentials (ERPs) in these two stages were recorded to detect the effect of social anxiety that might not be reflected by behavioral data. Participants were divided into two groups according to their social anxiety level. Participants in the high social anxiety (HSA) group were more likely to predict that they would be socially rejected by peers than did their low social anxiety (LSA) counterparts (i.e. the control group). Compared to the ERP data of the LSA group, the HSA group showed: (a) a larger P1 component to social cues (peer faces) prior to social feedback presentation, possibly indicating an attention bias; (b) a difference in feedback-related negativity amplitude between unexpected social acceptance and unexpected social rejection, possibly indicating an expectancy bias; and (c) a diminished sensitivity of the P3 amplitude to social feedback valence (be accepted/be rejected), possibly indicating an experience bias. These results could help understand the cognitive mechanisms that comprise and maintain social anxiety.

Angiogenesis and osteogenesis are coupled. However, the cellular and molecular regulation of these processes remains to be further investigated. Both tissues have recently been recognized as endocrine organs, which has stimulated research interest in the screening and functional identification of novel paracrine factors from both tissues. This review aims to elaborate on the novelty and significance of endocrine regulatory loops between bone and the vasculature. In addition, research progress related to the bone vasculature, vessel-related skeletal diseases, pathological conditions, and angiogenesis-targeted therapeutic strategies are also summarized. With respect to future perspectives, new techniques such as single-cell sequencing, which can be used to show the cellular diversity and plasticity of both tissues, are facilitating progress in this field. Moreover, extracellular vesicle-mediated nuclear acid communication deserves further investigation. In conclusion, a deeper understanding of the cellular and molecular regulation of angiogenesis and osteogenesis coupling may offer an opportunity to identify new therapeutic targets.

This research investigated the linkages between tropical cyclones (TCs) and extreme precipitation, and their associations with El Niño-Southern Oscillation (ENSO) over China. The contribution of TC-induced to total extreme precipitation events along the southeast coast of China was higher than 50%, and the values gradually decreased as TCs moved inland. However, the precipitation extremes (magnitude and frequency) related to TCs did not show statistically significant changes over the most recent 57 years. The impacts of TCs on precipitation extremes are evidently modulated by the ENSO phases. We found less extreme precipitation linked with TCs in southeastern China during El Niño phase, because of the fewer TC tracks over this region and less TC genesis in the western North Pacific (WNP). The small TC track density over southeastern China is due to the prevalent westerly steering flow and abnormal integrated vapor transport from northern to southern China during El Niño years. Additionally, warmer sea surface temperature, more vigorous westerlies, larger vorticity in 250 hPa, and higher divergence in 850 hPa in an El Niño phase jointly displaced the mean genesis of the WNP TCs eastward and this led to fewer TCs passing through southeastern China.

Background As one of the fundamental problems in bioinformatics, the double digest problem (DDP) focuses on reordering genetic fragments in a proper sequence. Although many algorithms for dealing with the DDP problem were proposed during the past decades, it is believed that solving DDP is still very time-consuming work due to the strongly NP-completeness of DDP. However, none of these algorithms consider the privacy issue of the DDP data that contains critical business interests and is collected with days or even months of gel-electrophoresis experiments. Thus, the DDP data owners are reluctant to deploy the task of solving DDP over cloud. Results Our main motivation in this paper is to design a secure outsourcing computation framework for solving the DDP problem. We at first propose a privacy-preserving outsourcing framework for handling the DDP problem by using a cloud server; Then, to enable the cloud server to solve the DDP instances over ciphertexts, an order-preserving homomorphic index scheme (OPHI) is tailored from an order-preserving encryption scheme published at CCS 2012; And finally, our previous work on solving DDP problem, a quantum inspired genetic algorithm (QIGA), is merged into our outsourcing framework, with the supporting of the proposed OPHI scheme. Moreover, after the execution of QIGA at the cloud server side, the optimal solution, i.e. two mapping sequences, would be transferred publicly to the data owner. Security analysis shows that from these sequences, none can learn any information about the original DDP data. Performance analysis shows that the communication cost and the computational workload for both the client side and the server side are reasonable. In particular, our experiments show that PP-DDP can find optional solutions with a high success rate towards typical test DDP instances and random DDP instances, and PP-DDP takes less running time than DDmap, SK05 and GM12, while keeping the privacy of the original DDP data. Conclusion The proposed outsourcing framework, PP-DDP, is secure and effective for solving the DDP problem.