Orientation selectivity mapping in the visual cortex.

The orientation map is one of the most well-studied functional maps of the visual cortex. However, results from the literature are of different qualities. Clear boundaries among different orientation domains and blurred uncertain distinctions were shown in different studies. These unclear imaging results will lead to an inaccuracy in depicting cortical structures, and the lack of consideration in experimental design will also lead to biased depictions of the cortical features. How we accurately define orientation domains will impact the entire field of research. In this study, we test how spatial frequency (SF), stimulus size, location, chromatic, and data processing methods affect the orientation functional maps (including a large area of dorsal V4, and parts of dorsal V1) acquired by intrinsic signal optical imaging. Our results indicate that, for large imaging fields, large grating stimuli with mixed SF components should be considered to acquire the orientation map. A diffusion model image enhancement based on the difference map could further improve the map quality. In addition, the similar outcomes of achromatic and chromatic gratings indicate two alternative types of afferents from LGN, pooling in V1 to generate cue-invariant orientation selectivity.

Effects of imidacloprid combined with validamycin on the population fitness and symbiotic of Nilaparvata lugens (Hemiptera: Delphacidae).

Using a high-efficiency insecticide in combination with fungicides that have different mechanisms of action is a conventional method in the current management of brown planthopper (BPH) resistance. In this study, we investigate the separate and combined effects of the low-toxicity fungicide validamycin and the non-cross-resistant insecticide imidacloprid on the fitness and symbiosis of BPH. These research results indicate that when the proportion of active ingredients in validamycin is combined with imidacloprid at a ratio of 1:30, the toxicity ratio and co-toxicity coefficient are 1.34 and 691.73, respectively, suggesting that the combination has a synergistic effect on the control of BPH. The number of yeast-like symbiotic (YLS) and dominant symbiotic (Noda) in the imidacloprid + validamycin groups were significantly lower than the other three treatment groups (validamycin, imidacloprid, and water). The results of the study on population fitness show that the lifespan of the BPH population in validamycin, imidacloprid, and imidacloprid + validamycin was shortened. Notably, the BPH populations in the imidacloprid + validamycin groups were significantly lower than other groups in terms of average generation cycle, intrinsic growth rate, net reproduction rate, finite rate of increase, and fitness. The Real-time quantitative PCR showed that validamycin and imidacloprid + validamycin can significantly inhibit the expression of the farnesyl diphosphate farnesyl transferase gene (EC2.5.1.21) and uricase gene (EC1.7.3.3), with imidacloprid + validamycin demonstrating the most pronounced inhibitory effect. Our research results can provide insights and approaches for delaying resistance and integrated management of BPH.

A Comprehensive Review of Image Line Segment Detection and Description: Taxonomies, Comparisons, and Challenges.

An image line segment is a fundamental low-level visual feature that delineates straight, slender, and uninterrupted portionsof objects and scenarios within images. Detection and description of line segments lay the basis for numerous vision tasks. Althoughmany studies have aimed to detect and describe line segments, a comprehensive review is lacking, obstructing their progress. This studyfills the gap by comprehensively reviewing related studies on detecting and describing two-dimensional image line segments to provideresearchers with an overall picture and deep understanding. Based on their mechanisms, two taxonomies for line segment detectionand description are presented to introduce, analyze, and summarize these studies, facilitating researchers to learn about them quicklyand extensively. The key issues, core ideas, advantages and disadvantages of existing methods, and their potential applications for eachcategory are analyzed and summarized, including previously unknown findings. The challenges in existing methods and correspondinginsights for potentially solving them are also provided to inspire researchers. In addition, some state-of-the-art line segment detectionand description algorithms are evaluated without bias, and the evaluation code will be publicly available. The theoretical analysis, coupledwith the experimental results, can guide researchers in selecting the best method for their intended vision applications. Finally, this studyprovides insights for potentially interesting future research directions to attract more attention from researchers to this field.

CS2DIPs: Unsupervised HSI Super-Resolution Using Coupled Spatial and Spectral DIPs.

In recent years, fusing high spatial resolution multispectral images (HR-MSIs) and low spatial resolution hyperspectral images (LR-HSIs) has become a widely used approach for hyperspectral image super-resolution (HSI-SR). Various unsupervised HSI-SR methods based on deep image prior (DIP) have gained wide popularity thanks to no pre-training requirement. However, DIP-based methods often demonstrate mediocre performance in extracting latent information from the data. To resolve this performance deficiency, we propose a coupled spatial and spectral deep image priors (CS2DIPs) method for the fusion of an HR-MSI and an LR-HSI into an HR-HSI. Specifically, we integrate the nonnegative matrix-vector tensor factorization (NMVTF) into the DIP framework to jointly learn the abundance tensor and spectral feature matrix. The two coupled DIPs are designed to capture essential spatial and spectral features in parallel from the observed HR-MSI and LR-HSI, respectively, which are then used to guide the generation of the abundance tensor and spectral signature matrix for the fusion of the HSI-SR by mode-3 tensor product, meanwhile taking some inherent physical constraints into account. Free from any training data, the proposed CS2DIPs can effectively capture rich spatial and spectral information. As a result, it exhibits much superior performance and convergence speed over most existing DIP-based methods. Extensive experiments are provided to demonstrate its state-of-the-art overall performance including comparison with benchmark peer methods.

Odorant binding protein 18 increases the pathogen resistance of the imported willow leaf beetle, Plagiodera versicolora.

Background: Insect odorant-binding proteins (OBPs) are a class of small molecular weight soluble proteins. In the past few years, OBPs had been found to work as carriers of ligands and play a crucial role in olfaction and various other physiological processes, like immunity. A subset of insect OBPs had been found to be expressed differently and play a function in immunity of fungal infection. However, there are few studies on the role of OBPs in immunity of bacterial infection. Methods: To identify the immune-related OBPs of Plagiodera versicolora after infected by Pseudomonas aeruginosa, we determined the mortality of P. versicolora to P. aeruginosa and selected the time point of 50% mortality of larvae to collect samples for RNA-seq. RNAi technology was used to investigate the function of immune-related OBPs after P. aeruginosa infection. Results: RNA-seq data shows that PverOBP18 gene significantly up-regulated by 1.8-fold and further RT-qPCR affirmed its expression. Developmental expression profile showed that the expression of PverOBP18 was highest in the pupae, followed by the female adults, and lower in the 1st-3rd larvae and male adults with lowest in eggs. Tissue expression profiling showed that PverOBP18 was dominantly expressed in the epidermis. RNAi knockdown of PverOBP18 significantly reduced the expression of bacterial recognition receptor gene PGRP and antibacterial peptide gene Attacin and reduced the resistance of P. versicolora to P. aeruginosa infection. Conclusion: Our results indicated that PverOBP18 gene increased the pathogen resistance of P. versicolora by cooperating with the immune genes and provided valuable insights into using OBPs as targets to design novel strategies for management of P. versicolora.

An odorant receptor mediates the avoidance of Plutella xylostella against parasitoid.

BACKGROUND: Ecosystems are brimming with myriad compounds, including some at very low concentrations that are indispensable for insect survival and reproduction. Screening strategies for identifying active compounds are typically based on bioassay-guided approaches. RESULTS: Here, we selected two candidate odorant receptors from a major pest of cruciferous plants-the diamondback moth Plutella xylostella-as targets to screen for active semiochemicals. One of these ORs, PxylOR16, exhibited a specific, sensitive response to heptanal, with both larvae and adult P. xylostella displaying heptanal avoidance behavior. Gene knockout studies based on CRISPR/Cas9 experimentally confirmed that PxylOR16 mediates this avoidance. Intriguingly, rather than being involved in P. xylostella-host plant interaction, we discovered that P. xylostella recognizes heptanal from the cuticular volatiles of the parasitoid wasp Cotesia vestalis, possibly to avoid parasitization. CONCLUSIONS: Our study thus showcases how the deorphanization of odorant receptors can drive discoveries about their complex functions in mediating insect survival. We also demonstrate that the use of odorant receptors as a screening platform could be efficient in identifying new behavioral regulators for application in pest management.

Relish involved in immunity and larval survival in the willow leaf beetle Plagiodera versicolora.

BACKGROUND: Insects mainly rely on innate immunity against pathogen infection. Plagiodera versicolora (Coleoptera: Chrysomelidae), is a worldwide leaf-eating forest pest in salicaceous trees. However, the mechanisms behind the immunodeficiency pathway (IMD) remain poorly understood. RESULTS: In this study, we obtained a Relish gene from transcriptome analysis. Tissue and instar expression profiles were subsequently obtained using quantitative real-time polymerase chain reaction analysis. The results showed that Relish has high expression levels in eggs, larvae and adults, and especially in fat bodies. Transcripts of the tested antimicrobial peptides (AMPs), defensin1, defensin2 and attacin2 were downregulated by dsRelish. Knockdown of Relish led to greater mortality in larvae after Staphylococcus aureus infection. In addition, we performed bacterial 16S ribosomal RNA-based high-throughput sequencing. The results showed that the relative abundance of some gut bacteria was significantly altered after dsRelish ingestion. CONCLUSION: This study provides a greater understanding of the IMD signaling pathway, facilitating functional studies of Relish in P. versicolora. Moreover, a genetic pest management technique might be developed using Relish as a lethal gene to control the pest P. versicolora. © 2024 Society of Chemical Industry.

Tensor Completion for Alzheimer's Disease Prediction From Diffusion Tensor Imaging.

OBJECTIVE: Alzheimer's disease (AD) is a slowly progressive neurodegenerative disorder with insidious onset. Accurate prediction of the disease progression has received increasing attention. Cognitive scores that reflect patients' cognitive status have become important criteria for predicting AD. Most existing methods consider the relationship between neuroimages and cognitive scores to improve prediction results. However, the inherent structure information in interrelated cognitive scores is rarely considered. METHOD: In this article, we propose a relation-aware tensor completion multitask learning method (RATC-MTL), in which the cognitive scores are represented as a third-order tensor to preserve the global structure information in clinical scores. We combine both tensor completion and linear regression into a unified framework, which allows us to capture both inter and intra modes correlations in cognitive tensor with a low-rank constraint, as well as incorporate the relationship between biological features and cognitive status by imposing a regression model on multiple cognitive scores. RESULT: Compared to the single-task and state-of-the-art multi-task algorithms, our proposed method obtains the best results for predicting cognitive scores in terms of four commonly used metrics. Furthermore, the overall performance of our method in classifying AD progress is also the best. CONCLUSION: Our results demonstrate the effectiveness of the proposed framework in fully exploring the global structure information in cognitive scores. SIGNIFICANCE: This study introduces a novel concept of leveraging tensor completion to assist in disease diagnoses, potentially offering a solution to the issue of data scarcity encountered in prolonged monitoring scenarios.

Research progress on extracellular vesicles in the renal tubular injury of diabetic kidney disease.

Diabetic kidney disease (DKD) is a severe microvascular complication of diabetes and is a chronic progressive condition. It is also a common cause of end-stage renal disease (ESRD), which is characterized by proteinuria or a progressive decline in the glomerular filtration rate. Due to their dependence on high-energy and aerobic metabolism, renal tubules are more susceptible to the metabolic disturbances associated with DKD, leading to inflammation and fibrosis. Consequently, tubular injury has become a recent research focus, and significant advancements have been made in studying the role of extracellular vesicles in DKD-associated tubular injury. This review aimed to elucidate the mechanisms and potential applications of different types of extracellular vesicles in tubular injury in DKD to provide new insights for the prevention and treatment of DKD.

Oviposition by Plagiodera versicolora on Salix matsudana cv. 'Zhuliu' alters the leaf transcriptome and impairs larval performance.

Insect egg deposition can induce plant defenses against their larvae. Previous studies have primarily focused on herbaceous plant defenses; however, little is known about how the Salicaceae respond to insect egg deposition and defend themselves against herbivores. By combining plant defense gene studies and bioassays, we investigated the effect of the coleoptera Plagiodera versicolora egg deposition on willow (Salix matsudana cv. 'Zhuliu') and examined the interactions at the plant resistance and transcriptome levels. RNA-seq data were utilized to analyze changes in the leaf transcriptome with and without oviposition, and also the changes in the leaf transcriptome of feeding-damaged leaves with and without prior oviposition. P. versicolora oviposition on willow leaves resulted in altered expression levels of transcripts associated with plant stress and metabolic responses. Compared with leaves with no oviposition, leaves with egg deposition showed a slight increase in phenylpropanoid biosynthesis and phytohormone signaling genes after larval feeding. The RNA-seq analysis revealed alterations in willow transcripts in response to leaf beetle infestations. Bioassays indicated that oviposition by P. versicolora on willows reduced subsequent larvae performance, suggesting that prior oviposition by P. versicolora could increase willows' resistance to larvae. This study advances our knowledge of how oviposition by coleoptera insects induces changes in the resistance of leaves to herbivory in the Salicaceae family.

Multiplex Transformed Tensor Decomposition for Multidimensional Image Recovery.

Low-rank tensor completion aims to recover the missing entries of multi-way data, which has become popular and vital in many fields such as signal processing and computer vision. It varies with different tensor decomposition frameworks. Compared with matrix SVD, recently emerging transform t-SVD can better characterize the low-rank structure of order-3 data. However, it suffers from rotation sensitivity, and dimensional limitation (i.e., only effective for order-3 tensors). To alleviate these deficiencies, we develop a novel multiplex transformed tensor decomposition (MTTD) framework, which can characterize the global low-rank structure along all modes for any order- N tensor. Based on MTTD, we propose a related multi-dimensional square model for low-rank tensor completion. Besides, a total variation term is also introduced to utilize the local piecewise smoothness of the tensor data. The classic alternating direction method of multipliers is used to solve the convex optimization problems. For performance testing, we choose three linear invertible transforms including FFT, DCT, and a group of unitary transform matrices for our proposed methods. The simulated and real-data experiments demonstrate the superior recovery accuracy and computational efficiency of our method compared with state-of-the-art ones.

Chromosome-level genomes of two armyworms, Mythimna separata and Mythimna loreyi, provide insights into the biosynthesis and reception of sex pheromones.

Mythimna separata and Mythimna loreyi are global pests of gramineous cereals, heavily controlled with synthetic insecticides. Here, we generated two high-quality chromosome-level genome assemblies for M. separata (688 Mb) and M. loreyi (683 Mb). Our analysis identified Z and W chromosomes, with few genes and abundant transposable elements (TEs) found on the W chromosome. We also observed a recent explosion of long interspersed nuclear elements (LINEs), which contributed to the larger genomes of Mythimna. The two armyworms diverged ~10.5 MYA, with only three chromosomes have intrachromosomal rearrangements. Additionally, we observed a tandem repeat expansion of α-amylase genes in Mythimna, which may promote the digestion of carbohydrates and exacerbate their damage to crops. Furthermore, we inferred the sex pheromone biosynthesis pathway for M. separata, M. loreyi and Spodoptera frugiperda. We discovered that M. loreyi and S. frugiperda synthesized the same major constituents of sex pheromones through different pathways. Specifically, the double bonds in the dominant sex pheromone components of S. frugiperda were generated by Δ9- and Δ11-desaturase, while they were generated by Δ11-desaturase and chain-shortening reactions in M. loreyi. We also identified pheromone receptor (PR) genes and inferred their corresponding components. These findings provide a better understanding of sex pheromone communication and promote the development of a new pest control strategy involving pheromone traps, which are more effective and environmentally friendly than current strategies.

Research progress on exosomes in podocyte injury associated with diabetic kidney disease.

Diabetic kidney disease (DKD), a common cause of end-stage renal disease, is a serious complication that develops with the progression of chronic diabetes. Its main clinical manifestations are persistent proteinuria and/or a progressive decline in the estimated glomerular filtration rate. Podocytes, terminally differentiated glomerular visceral epithelial cells, constitute the glomerular filtration barrier together with the basement membrane and endothelial cells, and the structural and functional barrier integrity is closely related to proteinuria. In recent years, an increasing number of studies have confirmed that podocyte injury is the central target of the occurrence and development of DKD, and research on exosomes in podocyte injury associated with DKD has also made great progress. The aim of this review is to comprehensively describe the potential diagnostic value of exosomes in podocyte injury associated with DKD, analyze the mechanism by which exosomes realize the communication between podocytes and other types of cells and discuss the possibility of exosomes as targeted therapy drug carriers to provide new targets for and insights into delaying the progression of and treating DKD.

Influence of load knowledge on lifting biomechanics.

Objectives. Findings from previous studies implied that appropriately controlling load knowledge might help improve the biomechanical performance during lifting tasks. However, only load weight knowledge was often discussed in previous studies. The current study aimed to complement the existing studies and provide improved knowledge about the influence of load knowledge on lifting biomechanics. Methods. Twenty-four healthy male participants were recruited and instructed to perform symmetric lifting tasks with different load weights under different load knowledge conditions. Load weights were set at three levels (40, 80 and 120%) of each participant's maximum acceptable lifting capacity. The examined load knowledge conditions included 'no knowledge' condition, 'weight known' condition, 'fragile material known' condition and 'weight and fragile material known' condition. Results. We found that when knowing fragility information about lifting materials, workers tended to be more cautious by adopting a less dynamic motion pattern during the landing phase, as evidenced by decreases of 6-8% in elbow joint acceleration. The 'cautious' lifting pattern when fragility load knowledge was presented could contribute to reduced risk of lower back disorder. Conclusion. This finding could help to develop lower back disorder prevention interventions to improve occupational safety and health.

Low Dimensional Trajectory Hypothesis is True: DNNs Can Be Trained in Tiny Subspaces.

Deep neural networks (DNNs) usually contain massive parameters, but there is redundancy such that it is guessed that they could be trained in low-dimensional subspaces. In this paper, we propose a Dynamic Linear Dimensionality Reduction (DLDR) based on the low-dimensional properties of the training trajectory. The reduction method is efficient, supported by comprehensive experiments: optimizing DNNs in 40-dimensional spaces can achieve comparable performance as regular training over thousands or even millions of parameters. Since there are only a few variables to optimize, we develop an efficient quasi-Newton-based algorithm, obtain robustness to label noise, and improve the performance of well-trained models, which are three follow-up experiments that can show the advantages of finding such low-dimensional subspaces. The code is released (Pytorch: https://github.com/nblt/DLDR and Mindspore: https://gitee.com/mindspore/docs/tree/r1.6/docs/sample_code/dimension_reduce_training).

LncRNA ATP1A1-AS1 inhibits cell proliferation and promotes cell apoptosis in thyroid carcinoma by regulating the miR-620/IRF2BP2 axis.

BACKGROUND: Thyroid carcinoma (THCA) is a common malignancy of the endocrine system. Further understanding of the molecular mechanism underlying THCA is crucial to develop effective diagnostic therapy and improve its treatments. In this study, we intended to provide novel direction for THCA targeted therapy from the aspect of lncRNA-miRNA-mRNA interaction. We aimed to investigate the function and molecular mechanism of lncRNA ATP1A1-AS1 in THCA. METHODS: Gene expression was assessed by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Cell growth was detected by CCK-8 and EdU assays. Flow cytometry was applied for analyzing cell apoptosis. The binding of ATP1A1-AS1 or IRF2BP2 to miR-620 was validated by RNA pulldown and luciferase reporter assays. The protein levels were examined by western blotting. RESULTS: ATP1A1-AS1 was decreased in THCA cells and tissues. ATP1A1-AS1 overexpression attenuated cell growth and promoted apoptosis. MiR-620, which was upregulated in THCA, was identified as a direct target of ATP1A1-AS1. Furthermore, IRF2BP2 was discovered to be a target of miR-620, which displayed low expression in THCA cells and tissues. Importantly, IRF2BP2 knockdown reversed the influence of ATP1A1-AS1 overexpression on THCA cell proliferation and apoptosis. CONCLUSIONS: LncRNA ATP1A1-AS1 inhibited cell growth and promotes apoptosis in THCA via the miR-620/IRF2BP2 axis.

IncRNA TYMSOS Promotes Epithelial-Mesenchymal Transition and Metastasis in Thyroid Carcinoma through Regulating MARCKSL1 and Activating the PI3K/Akt Signaling Pathway.

Thyroid carcinoma (THCA) has been increasing in incidence greater than other cancers. Long noncoding RNAs (lncRNAs) were reported to play crucial roles in THCA development. Our study aimed to explore the underlying mechanism of lncRNA thymidylate synthetase opposite strand RNA (TYMSOS) in THCA. TYMSOS and myristoylated alanine rich protein kinase C substrate like 1 (MARCKSL1) were upregulated whereas miR-130a-5p was downregulated in THCA cells and tissues. The results of loss-of-function assays showed that TYMSOS knockdown inhibited cell metastasis and epithelial-mesenchymal transition (EMT) in THCA. TYMSOS was primarily distributed in the cytoplasm of THCA cells, as shown by FISH assay. RNA pulldown and luciferase reporter assay further showed that TYMSOS binds with miR-130a-5p. Luciferase reporter assay also revealed that MARCKSL1 is targeted by miR-130a-5p. Rescue assay showed that the suppression of TYMSOS downregulation on THCA cell malignant behaviors was reversed by MARCKSL1 overexpression. Additionally, overexpressing MARCKSL1 offset the inhibition of TYMSOS downregu-lation on the PI3K/Akt signaling pathway. TYMSOS knockdown inhibits the growth of THCA tumors, as in vivo assays showed. Collectively, TYMSOS facilitates THCA progression by sponging miR-130a-5p and upregulating MARCKSL1 to activate the PI3K/Akt signaling pathway, providing new avenues for THCA treatment.

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In order to understand the interspecific and ecological relationships of Michelia odora (extremely small population) community and strengthen the protection of wild M. odora resources in Junzifeng Nature Reserve, we studied the niche characteristics and interspecific associations of dominant tree species. The results showed that M. odora, Machilus chekiangensis, Schima superba, and Alniphyllum fortunei had obvious niche breadth advantages, which were the constructive species of the community. Among the 190 groups of species pairs among the 20 dominant tree species, 50.5% of species pairs had niche overlap value greater than 0.5. The degree of ecological niche differentiation among species was general. M. odora had large niche overlap with other 19 species, indicating a competitive risk when resources were insufficient. The overall associations of dominant tree species were significantly positive, indicating the community was at the late stage of relatively stable succession. The results ofχ2 test, asso-ciation coefficient, and Pearson correlation coefficient showed that all the significance ratios of interspecific association were lower, and that the independence among species was relatively strong. There was a positive correlation between interspecific association and niche overlap. The M. odora community was relatively mature, with full utilization of resources and stable interspecific relationship. To promote the rejuvenation and create a good habitat of M. odora population, the population size with large overlap with M. odora niche and significant negative association could be appropriately limited, while that with positive interaction could be increased.

Optimization of the Laminate Structure of a Composite Cylinder Based on the Combination of Response Surface Methodology (RSM) and Finite Element Analysis (FEA).

This study optimized the laminate structure of a composite cylinder under the constraint of minimum layup thickness. Based on the progressive damage theory, a finite element model of the cylinder was established, and the NOL ring tensile test was used to verify the accuracy of the damage theory. The winding angle, the number of layers, and the helical/hoop ratio (the stacking sequence) were selected as the optimization factors, and the burst pressure value was used to evaluate the quality of the laminate structure. Then the orthogonal experiments were designed by RSM. Combined with FEA, the function model of the burst pressure of the gas cylinder and each optimization factor was established to obtain the optimal layering scheme, satisfying the minimum burst pressure. In addition, finite element analysis was used to verify the optimal scheme, demonstrating that the error of the burst pressure predicted by the quadratic model established by the response surface design was not more than 5%. This study provides a faster and more efficient optimization method for the optimization design of composite gas cylinder layers.

Multi-Phase Environmental Impact Assessment of Marine Ecological Restoration Project Based on DPSIR-Cloud Model.

In order to achieve a comprehensive evaluation of the environmental impact of ecological restoration projects (ERP) under the current destruction and restoration of coastal ecological areas, this paper takes into account the impact of positive and negative indicators on the environment; analyzes the positive and negative benefits of ERP; and establishes a comprehensive environmental impact index system for marine ERP from ecological, economic, and social perspectives through the DPSIR model. On this basis, the cloud model and Monte Carlo simulation are used to obtain the comprehensive assessment grade of the construction period, short-term operation, and long-term operation in the project life cycle. The results show that the benefits of ERP, considering the impact of negative factors, are significantly reduced, and the benefits of ERP will increase remarkably in the long-term operation period. In engineering practice, the environmental pressure factor caused by excessive human activities during construction and operation periods is a key negative factor affecting the overall benefits of ERP. For project decision makers and other stakeholders, the comprehensive assessment grade considering negative impacts is more practical. At the same time, decision makers should take active response measures in the framework of long-term sustainable development, set a tolerance threshold for negative pressure indicators, and strengthen the management of ERP.