Two distinct SNARE complexes mediate vesicle fusion with the plasma membrane to ensure effective development and pathogenesis of Fusarium oxysporum f. sp. cubense.

SNAREs (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) facilitate docking and fusion of vesicles with their target membranes, playing a crucial role in vesicle trafficking and exocytosis. However, the spatial assembly and roles of plasma membrane (PM)-associated SNAREs in phytopathogen development and pathogenicity are not clearly understood. In this study, we analysed the roles and molecular mechanisms of PM-associated SNARE complexes in the banana Fusarium wilt fungus Fusarium oxysporum f. sp. cubense tropical race 4 (FocTR4). Our findings demonstrate that FocSso1 is important for the fungal growth, conidiation, host penetration and colonization. Mechanistically, FocSso1 regulates protein secretion by mediating vesicle docking and fusion with the PM and hyphal apex. Interestingly, a FocSso1-FocSec9-FocSnc1 complex was observed to assemble not only at the fungal PM but also on the growing hyphal apex, facilitating exocytosis. FocSso2, a paralogue of FocSso1, was also found to form a ternary SNARE complex with FocSec9 and FocSnc1, but it mainly localizes to the PM in old hyphae. The functional analysis of this protein demonstrated that it is dispensable for the fungal growth but necessary for host penetration and colonization. The other subunits, FocSec9 and FocSnc1, are involved in the fungal development and facilitate host penetration. Furthermore, FocSso1 and FocSnc1 are functionally interdependent, as loss of FocSso1 leads to mis-sorting and degradation of FocSnc1 in the vacuole and vice versa. Overall, this study provides insight into the formation of two spatially and functionally distinct PM SNARE complexes and their involvement in vesicle exocytosis to regulate development and pathogenicity of FocTR4.

Tunable Optical Display of Multilayer Graphene through Lithium Intercalation.

The tunable optical display is vital for many application fields in telecommunications, sensors, and military devices. However, most optical materials have a strong wavelength dependence, which limits their spectral operation range. In this work, we develop an electrically reconfigurable optical medium based on graphene, demonstrating a cycle-controlled display covering the electromagnetic spectrum from the visible to the infrared wavelength. Through an electro-intercalation method, the graphene-based surface enables rich colors from gray to dark blue to dark red to yellow, and the response time is about 1 min from the start gray color to the final yellow color. Simultaneously, it exhibits a remarkable change in infrared emissivity (from 0.63 to 0.80 reduction to 0.20) with a response time of 1 s. This modification of optical properties of lithiated multilayer graphene (MLG) is the increase of Fermi energy (Ef) due to the charge transfer from lithium (Li) to graphene layers, which causes changes in interband and intraband electronic transitions. Our findings imply potential value in fabricating multispectral optical materials with high tunability.

A Review on Microstructural Formations of Discontinuous Fiber-Reinforced Polymer Composites Prepared via Material Extrusion Additive Manufacturing: Fiber Orientation, Fiber Attrition, and Micro-Voids Distribution.

A discontinuous fiber-reinforced polymer composite (DFRPC) provides superior mechanical performances in material extrusion additive manufacturing (MEAM) parts, and thus promotes their implementations in engineering applications. However, the process-induced structural defects of DFRPCs increase the probability of pre-mature failures as the manufactured parts experience complicated external loads. In light of this, the meso-structures of the MEAM parts have been discussed previously, while systematic analyses reviewing the studies of the micro-structural formations of the composites are limited. This paper summarizes the current state-of-the-art in exploring the correlations between the MEAM processes and the associated micro-structures of the produced composites. Experimental studies and numerical analyses including fiber orientation, fiber attrition, and micro-voids are collected and discussed. Based on the review and parametric study results, it is considered that the theories and numerical characterizations on fiber length attrition and micro-porosities within the MEAM-produced composites are in high demand, which is a potential topic for further explorations.

A Novel Multi-Stage Residual Feature Fusion Network for Detection of COVID-19 in Chest X-Ray Images.

To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial, chest screening with radiography imaging plays an important role in addition to the real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test. Due to the limited data, existing models suffer from incapable feature extraction and poor network convergence and optimization. Accordingly, a multi-stage residual network, MSRCovXNet, is proposed for effective detection of COVID-19 from chest x-ray (CXR) images. As a shallow yet effective classifier with the ResNet-18 as the feature extractor, MSRCovXNet is optimized by fusing two proposed feature enhancement modules (FEM), i.e., low-level and high-level feature maps (LLFMs and HLFMs), which contain respectively more local information and rich semantic information, respectively. For effective fusion of these two features, a single-stage FEM (MSFEM) and a multi-stage FEM (MSFEM) are proposed to enhance the semantic feature representation of the LLFMs and the local feature representation of the HLFMs, respectively. Without ensembling other deep learning models, our MSRCovXNet has a precision of 98.9% and a recall of 94% in detection of COVID-19, which outperforms several state-of-the-art models. When evaluated on the COVIDGR dataset, an average accuracy of 82.2% is achieved, leading other methods by at least 1.2%.

STIM2 promotes the invasion and metastasis of breast cancer cells through the NFAT1/TGF-ß1 pathway.

A large amount of evidence indicates that the abnormal activation of multiple signal transduction pathways in cells is closely related to the occurrence and development of tumors. TGF-ß and NFAT1 signaling pathways can inhibit cell proliferation and promote apoptosis in the early stage of breast cancer, but with the increase of tumor malignancy, the two appear to promote tumor progression and deterioration. Therefore, the study of the relationship between STIM2 and NFAT1/TGF-ß1 is helpful for the discovery and treatment of breast cancer, which is of great significance for improving the survival rate of breast cancer patients. This article focuses on the effect of STIM2 molecules on breast cancer cell migration through the NFAT1/ TGF-ß1 pathway and discusses the regulatory mechanism of STIM2 affecting breast cancer cell migration. Experimental data shows that the positive rate of breast cancer NFAT1 is 54%, which is significantly lower than that of benign breast Tissue 85%; the positive expression rate of TGF-ß1 in benign breast tissue is 85%, and the positive expression rate in breast cancer tissue is 49%. The results show that STIM2 protein can promote the invasion and metastasis of breast cancer cells through the NFAT1 / TGF-ß1 pathway.

The effect of miR-138 on the proliferation and apoptosis of breast cancer cells through the NF-κB/VEGF signaling pathway.

The analyze the effect of miR-138 on the proliferation and apoptosis of breast cancer cells through the NF-κB/VEGF signaling pathway is the Objective of this experiment. For this aim, the endometrial stem breast cancer cell line MCF-7 was cultured in vitro, and the overexpression mimic miR-138 mimics and the inhibitor anti-miR-138 were transfected into the endometrial stem breast cancer cell line MCF-7, which was set to overexpress miR-138 group and interfere with miR-138, and set up negative control of overexpression and negative control of inhibitor. Observe the cell proliferation and apoptosis ability of each group, and the changes in tumor necrosis factor-α (TNF-α), interleukin 1ß, 6, 18 (IL-1ß, IL-6, IL-18) levels, and compare the Bax of each group, NF-κB, VEGF protein expression level. Results showed that the proliferation ability of the miR-138 overexpression group was significantly lower than that of the miR-138 overexpression control group (P<0.05); the proliferation ability of the miR-138 interference group was significantly higher than that of the miR-138 interference control group (P<0.05). The apoptosis rate, caspase-3 and caspase-9 expression levels of the miR-138 overexpression group were significantly higher than those of the miR-138 overexpression control group (P<0.05);  the apoptosis rate, caspase-3 and caspase-9 expression levels of the miR-138 interference group were significantly lower than those of the miR-138 interference control group (P<0.05). The expression levels of IL-1 ß, IL-6, IL-18 and TNF - α in the miR-138 overexpression group were significantly lower than those in the miR-138 overexpression control group (P < 0.05). The protein expression levels of Bax, NF-κB and VEGF in the miR-138 overexpression group were significantly lower than those in the miR-138 overexpression control group (P < 0.05); the protein expression levels of Bax, NF-κB and VEGF in the miR-138 interference group were significantly higher than those in the miR-138 interference control group (P <0.05). The proliferation ability of the miR-138 overexpression group was significantly lower than that of the miR-138 overexpression control group (P < 0.05); the proliferation ability of the miR-138 + NF-κB overexpression group was significantly higher than that of the miR-138 overexpression group (P<0.05). The apoptosis rate of the miR-138 + NF-κB overexpression group was significantly lower than that of the miR-138 overexpression group (P < 0.05). Then MiR-138 can significantly inhibit the proliferation of breast cancer cells, promote apoptosis, and regulate the expression of inflammatory factors in the cells. It is speculated that the related mechanism may be related to the negative regulation of the NF-κB/VEGF signaling pathway.

SC2Net: A Novel Segmentation-Based Classification Network for Detection of COVID-19 in Chest X-Ray Images.

The pandemic of COVID-19 has become a global crisis in public health, which has led to a massive number of deaths and severe economic degradation. To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial. As the popularly used real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test can be lengthy and inaccurate, chest screening with radiography imaging is still preferred. However, due to limited image data and the difficulty of the early-stage diagnosis, existing models suffer from ineffective feature extraction and poor network convergence and optimisation. To tackle these issues, a segmentation-based COVID-19 classification network, namely SC2Net, is proposed for effective detection of the COVID-19 from chest x-ray (CXR) images. The SC2Net consists of two subnets: a COVID-19 lung segmentation network (CLSeg), and a spatial attention network (SANet). In order to supress the interference from the background, the CLSeg is first applied to segment the lung region from the CXR. The segmented lung region is then fed to the SANet for classification and diagnosis of the COVID-19. As a shallow yet effective classifier, SANet takes the ResNet-18 as the feature extractor and enhances high-level feature via the proposed spatial attention module. For performance evaluation, the COVIDGR 1.0 dataset is used, which is a high-quality dataset with various severity levels of the COVID-19. Experimental results have shown that, our SC2Net has an average accuracy of 84.23% and an average F1 score of 81.31% in detection of COVID-19, outperforming several state-of-the-art approaches.

Aspartate Transaminase AST2 Involved in Sporulation and Necrotrophic Pathogenesis in the Hemibiotrophs Magnaporthe oryzae and Colletotrichum graminicola.

Aspartate family includes five additional amino acids other than aspartate, among which most except aspartate have been reported for their action in pathogenesis by amino acid biosynthesis. However, how aspartate, the initial substrate of this family metabolic pathway, is involved in pathogenesis remains unknown. Here, we focused on aspartate transaminase (AST) that catalyzes transamination reaction between glutamate-aspartate in Magnaporthe oryzae. Three MoAST genes were bioinformatically analyzed, of which MoAST2 was uniquely upregulated when invasive hyphae switched to necrotrophic pathogenesis. MoAST2 deletion (ΔMoast2) caused a drastic reduction in conidiogenesis and appressorium formation. Particularly, ΔMoast2 was observed to be proliferated at the biotrophic phase but inhibited at the necrotrophic stage, and with invisible symptoms detected, suggesting a critical role in necrotrophic phase. Glutamate family restored the ΔMoast2 defects but aspartate family did not, inferring that transamination occurs from aspartate to glutamine. MoAST2 is cytosolic and possessed H2O2 stress tolerance. In parallel, Colletotrichum graminicola AST2, CgAST2 was proven to be a player in necrotrophic anthracnose development. Therefore, conserved AST2 is qualified to be a drug target for disease control.

Highly thermostable white-emitting Ca9ZnK(PO4)7:Ce3+,Dy3+ single-phase phosphor with tunable photoluminescence and energy transfer.

White light-emitting diodes (WLEDs) fabricated with single-phase white phosphor are currently widely used in lighting and displays. Herein, we describe the development of a single-component white-emitting micro-sized powder Ca9ZnK(PO4)7 (CZKP):Ce3+,Dy3+ with high thermal stability. Theoretical and experimental investigations confirmed that the phosphate CZKP with a whitlockite-like structure was suitable as a phosphor host. The photoluminescence of cerium/dysprosium single- and co-doped samples was comprehensively studied. Dipole-dipole interaction resulted in the Ce3+ → Dy3+ energy transfer, which contributed to the spectral regulation for acquiring the white-emitting performance. Moreover, the superior thermal stability of the representative CZKP:0.10Ce3+,0.15Dy3+ phosphor was revealed. Finally, we explored the working performance of single-phase white phosphor-converted WLEDs. The corresponding work shows a successful design for achieving a single-component white phosphor via the Ce3+ → Dy3+ energy transfer approach.

Adaptive Distance-Based Band Hierarchy (ADBH) for Effective Hyperspectral Band Selection.

Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) processing. Although many unsupervised band selection (UBS) approaches have been developed in the last decades, a flexible and robust method is still lacking. The lack of proper understanding of the HSI data structure has resulted in the inconsistency in the outcome of UBS. Besides, most of the UBS methods are either relying on complicated measurements or rather noise sensitive, which hinder the efficiency of the determined band subset. In this article, an adaptive distance-based band hierarchy (ADBH) clustering framework is proposed for UBS in HSI, which can help to avoid the noisy bands while reflecting the hierarchical data structure of HSI. With a tree hierarchy-based framework, we can acquire any number of band subset. By introducing a novel adaptive distance into the hierarchy, the similarity between bands and band groups can be computed straightforward while reducing the effect of noisy bands. Experiments on four datasets acquired from two HSI systems have fully validated the superiority of the proposed framework.

Research on elderly users' intentions to accept wearable devices based on the improved UTAUT model.

Introduction: As the proportion of the world's elderly population continues to increase, wearable devices can provide ideas for solving a series of problems caused by population aging. Therefore, it is of great significance for the development of intelligent elderly care and the improvement of the quality of elderly care services to explore the factors that influence the intention of elderly users to accept wearable devices. Methods: An improved unified theory of acceptance and use of technology (UTAUT) model is constructed from the perspective of elderly individuals, and new parameters are added, including four factors related to wearable devices, including performance expectancy, perceived cost, hedonic value and aesthetic appeal, and three factors related to elderly individuals, including personal physiological conditions, health anxiety and personal innovativeness in information technology. The data analysis was accomplished with the partial least square regression structural equation modeling. Results: The findings of this study revealed that performance expectancy, perceived cost, hedonic value and aesthetic appeal all have significant impact on elderly users' intention to use wearable devices. Furthermore, personal innovativeness in information technology, personal physiological condition, and intention to use all have significant impact on elderly users' actual usage behavior of wearable devices. However, there is no obvious relationship between health anxiety and actual usage behavior. Discussion: Elderly adults' attention to wearable devices plays an important role in the development of the wearable device-related industry chain, which provides management suggestions for stakeholders.

A Novel Prognostic Signature of Transcription Factors for the Prediction in Patients With GBM.

Background: Although the diagnosis and treatment of glioblastoma (GBM) is significantly improved with recent progresses, there is still a large heterogeneity in therapeutic effects and overall survival. The aim of this study is to analyze gene expressions of transcription factors (TFs) in GBM so as to discover new tumor markers. Methods: Differentially expressed TFs are identified by data mining using public databases. The GBM transcriptome profile is downloaded from The Cancer Genome Atlas (TCGA). The nonnegative matrix factorization (NMF) method is used to cluster the differentially expressed genes to discover hub genes and signal pathways. The TFs affecting the prognosis of GBM are screened by univariate and multivariate COX regression analysis, and the receiver operating characteristic (ROC) curve is determined. The GBM hazard model and nomogram map are constructed by integrating the clinical data. Finally, the TFs involving potential signaling pathways in GBM are screened by Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Results: There are 68 differentially expressed TFs in GBM, of which 43 genes are upregulated and 25 genes are downregulated. NMF clustering analysis suggested that GBM patients are divided into three groups: Clusters A, B, and C. LHX2, MEOX2, SNAI2, and ZNF22 are identified from the above differential genes by univariate/multivariate regression analysis. The risk score of those four genes are calculated based on the beta coefficient of each gene, and we found that the predictive ability of the risk score gradually increased with the prolonged predicted termination time by time-dependent ROC curve analysis. The nomogram results have showed that the integration of risk score, age, gender, chemotherapy, radiotherapy, and 1p/19q can further improve predictive ability towards the survival of GBM. The pathways in cancer, phosphoinositide 3-kinases (PI3K)-Akt signaling, Hippo signaling, and proteoglycans, are highly enriched in high-risk groups by GSEA. These genes are mainly involved in cell migration, cell adhesion, epithelial-mesenchymal transition (EMT), cell cycle, and other signaling pathways by GO and KEGG analysis. Conclusion: The four-factor combined scoring model of LHX2, MEOX2, SNAI2, and ZNF22 can precisely predict the prognosis of patients with GBM.

Lysophosphatidic Acid Up-Regulates Hexokinase II and Glycolysis to Promote Proliferation of Ovarian Cancer Cells.

Lysophosphatidic acid (LPA), a blood-borne lipid mediator, is present in elevated concentrations in ascites of ovarian cancer patients and other malignant effusions. LPA is a potent mitogen in cancer cells. The mechanism linking LPA signal to cancer cell proliferation is not well understood. Little is known about whether LPA affects glucose metabolism to accommodate rapid proliferation of cancer cells. Here we describe that in ovarian cancer cells, LPA enhances glycolytic rate and lactate efflux. A real time PCR-based miniarray showed that hexokinase II (HK2) was the most dramatically induced glycolytic gene to promote glycolysis in LPA-treated cells. Analysis of the human HK2 gene promoter identified the sterol regulatory element-binding protein as the primary mediator of LPA-induced HK2 transcription. The effects of LPA on HK2 and glycolysis rely on LPA2, an LPA receptor subtype overexpressed in ovarian cancer and many other malignancies. We further examined the general role of growth factor-induced glycolysis in cell proliferation. Like LPA, epidermal growth factor (EGF) elicited robust glycolytic and proliferative responses in ovarian cancer cells. Insulin-like growth factor 1 (IGF-1) and insulin, however, potently stimulated cell proliferation but only modestly induced glycolysis. Consistent with their differential effects on glycolysis, LPA and EGF-dependent cell proliferation was highly sensitive to glycolytic inhibition while the growth-promoting effect of IGF-1 or insulin was more resistant. These results indicate that LPA- and EGF-induced cell proliferation selectively involves up-regulation of HK2 and glycolytic metabolism. The work is the first to implicate LPA signaling in promotion of glucose metabolism in cancer cells.

TomoTherapy MLC verification using exit detector data.

PURPOSE: Treatment delivery verification (DV) is important in the field of intensity modulated radiation therapy (IMRT). While IMRT and image guided radiation therapy (IGRT), allow us to create more conformal plans and enables the use of tighter margins, an erroneously executed plan can have detrimental effects on the treatment outcome. The purpose of this study is to develop a DV technique to verify TomoTherapy's multileaf collimator (MLC) using the onboard mega-voltage CT detectors. METHODS: The proposed DV method uses temporal changes in the MVCT detector signal to predict actual leaf open times delivered on the treatment machine. Penumbra and scattered radiation effects may produce confounding results when determining leaf open times from the raw detector data. To reduce the impact of the effects, an iterative, Richardson-Lucy (R-L) deconvolution algorithm is applied. Optical sensors installed on each MLC leaf are used to verify the accuracy of the DV technique. The robustness of the DV technique is examined by introducing different attenuation materials in the beam. Additionally, the DV technique has been used to investigate several clinical plans which failed to pass delivery quality assurance (DQA) and was successful in identifying MLC timing discrepancies as the root cause. RESULTS: The leaf open time extracted from the exit detector showed good agreement with the optical sensors under a variety of conditions. Detector-measured leaf open times agreed with optical sensor data to within 0.2 ms, and 99% of the results agreed within 8.5 ms. These results changed little when attenuation was added in the beam. For the clinical plans failing DQA, the dose calculated from reconstructed leaf open times played an instrumental role in discovering the root-cause of the problem. Throughout the retrospective study, it is found that the reconstructed dose always agrees with measured doses to within 1%. CONCLUSIONS: The exit detectors in the TomoTherapy treatment systems can provide valuable information about MLC behavior during delivery. A technique to estimate the TomoTherapy binary MLC leaf open time from exit detector signals is described. This technique is shown to be both robust and accurate for delivery verification.