Controlling sap-sucking insect pests with recombinant endophytes expressing plant lectin

We developed a novel pest management strategy, which uses endophytes to express anti-pest plant lectins. Fungal endophyte of Chaetomium globosum YY-11 with anti-fungi activities was isolated from rape seedlings, and bacterial endophytes of SJ-10 (Enterobacter sp.) and WB (Bacillus subtilis) were isolated from rice seedlings. Pinellia ternate agglutinin gene was cloned into SJ-10 and WB for expression by a shuttle vector, and YY-11 was mediated by Agrobacterium tumefaciens. Positive transformants were evaluated using PCR and Western blot assay. Recombinant endophytes colonized most of crops, and resistance of rice seedlings, which were inoculated with the recombinant endophytic bacteria, to white backed planthoppers was dramatically enhanced by decreasing the survival and fecundity of white backed planthoppers. Rape inoculated with recombinant endophytic fungi significantly inhibited the growth and reproduction of aphids. Recombinant endophytes expressing PTA may endow hosts with resistance against sap-sucking pests

Molecular dynamics simulation of graphene sinking during chemical vapor deposition growth on semi-molten Cu substrate

Copper foil is the most promising catalyst for the synthesis of large-area, high-quality monolayer graphene. Experimentally, it has been found that the Cu substrate is semi-molten at graphene growth temperatures. In this study, based on a self-developed C-Cu empirical potential and density functional theory (DFT) methods, we performed systematic molecular dynamics simulations to explore the stability of graphene nanostructures, i.e., carbon nanoclusters and graphene nanoribbons, on semi-molten Cu substrates. Many atomic details observed in the classical MD simulations agree well with those seen in DFT-MD simulations, confirming the high accuracy of the C-Cu potential. Depending on the size of the graphene island, two different sunken-modes are observed: (i) graphene island sinks into the first layer of the metal substrate and (ii) many metal atoms surround the graphene island. Further study reveals that the sinking graphene leads to the unidirectional alignment and seamless stitching of the graphene islands, which explains the growth of large single-crystal graphene on Cu foil. This study deepens our physical insights into the CVD growth of graphene on semi-molten Cu substrate with multiple experimental mysteries well explained and provides theoretic references for the controlled synthesis of large-area single-crystalline monolayer graphene

Acoustic Analysis of Multi-Frequency Problems Using the Boundary Element Method Based on Taylor Expansion

This work proposes a refreshing technique that utilizes the Taylor expansion to improve the computational efficiency of the multi-frequency acoustic scattering problem. The Helmholtz equation in acoustic problems is solved using the boundary element method (BEM). In this work, the Taylor expansion is utilized to separate frequency-dependent terms from the integrand function in the boundary integral equation so that the wave number is independent of the equation system, thereby avoiding the time-consuming frequency sweep analysis. To conquer the non-uniqueness of the solution for the external acoustic field problem, the Burton-Miller method is used to linearly combine the conventional boundary integral equation and the hypersingular boundary integral equation. Moreover, to eliminate the computational difficulties caused by the Burton-Miller method, the Cauchy principal value and the Hadamard finite part integral method are used to solve singular integrals. Two-dimensional numerical examples are exploited to verify the effectiveness and compatibility of the algorithm for the multi-frequency analysis

Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation

The annotation scarcity of medical image segmentation poses challenges in collecting sufficient training data for deep learning models. Specifically, models trained on limited data may not generalize well to other unseen data domains, resulting in a domain shift issue. Consequently, domain generalization (DG) is developed to boost the performance of segmentation models on unseen domains. However, the DG setup requires multiple source domains, which impedes the efficient deployment of segmentation algorithms in clinical scenarios. To address this challenge and improve the segmentation model's generalizability, we propose a novel approach called the Frequency-mixed Single-source Domain Generalization method (FreeSDG). By analyzing the frequency's effect on domain discrepancy, FreeSDG leverages a mixed frequency spectrum to augment the single-source domain. Additionally, self-supervision is constructed in the domain augmentation to learn robust context-aware representations for the segmentation task. Experimental results on five datasets of three modalities demonstrate the effectiveness of the proposed algorithm. FreeSDG outperforms state-of-the-art methods and significantly improves the segmentation model's generalizability. Therefore, FreeSDG provides a promising solution for enhancing the generalization of medical image segmentation models, especially when annotated data is scarce. The code is available at https://github.com/liamheng/Non-IID_Medical_Image_Segmentation

The MBD7 complex promotes expression of methylated transgenes without significantly altering their methylation status.

DNA methylation is associated with gene silencing in eukaryotic organisms. Although pathways controlling the establishment, maintenance and removal of DNA methylation are known, relatively little is understood about how DNA methylation influences gene expression. Here we identified a METHYL-CpG-BINDING DOMAIN 7 (MBD7) complex in Arabidopsis thaliana that suppresses the transcriptional silencing of two LUCIFERASE (LUC) reporters via a mechanism that is largely downstream of DNA methylation. Although mutations in components of the MBD7 complex resulted in modest increases in DNA methylation concomitant with decreased LUC expression, we found that these hyper-methylation and gene expression phenotypes can be genetically uncoupled. This finding, along with genome-wide profiling experiments showing minimal changes in DNA methylation upon disruption of the MBD7 complex, places the MBD7 complex amongst a small number of factors acting downstream of DNA methylation. This complex, however, is unique as it functions to suppress, rather than enforce, DNA methylation-mediated gene silencing

BrLAS, a GRAS Transcription Factor From Brassica rapa, Is Involved in Drought Stress Tolerance in Transgenic Arabidopsis

GRAS proteins belong to a plant-specific transcription factor family and play roles in diverse physiological processes and environmental signals. In this study, we identified and characterized a GRAS transcription factor gene in Brassica rapa, BrLAS, an ortholog of Arabidopsis AtLAS. BrLAS was primarily expressed in the roots and axillary meristems, and localized exclusively in the nucleus of B. rapa protoplast cells. qRT-PCR analysis indicated that BrLAS was upregulated by exogenous abscisic acid (ABA) and abiotic stress treatment [polyethylene glycol (PEG), NaCl, and H2O2]. BrLAS-overexpressing Arabidopsis plants exhibited pleiotropic characteristics, including morphological changes, delayed bolting and flowering time, reduced fertility and delayed senescence. Transgenic plants also displayed significantly enhanced drought resistance with decreased accumulation of ROS and increased antioxidant enzyme activity under drought treatment compared with the wild-type. Increased sensitivity to exogenous ABA was also observed in the transgenic plants. qRT-PCR analysis further showed that expression of several genes involved in stress responses and associated with leaf senescence were also modified. These findings suggest that BrLAS encodes a stress-responsive GRASs transcription factor that positively regulates drought stress tolerance, suggesting a role in breeding programs aimed at improving drought tolerance in plants

BrRLP48, Encoding a Receptor-Like Protein, Involved in Downy Mildew Resistance in Brassica rapa

Downy mildew, caused by Hyaloperonospora parasitica, is a major disease of Brassica rapa that causes large economic losses in many B. rapa-growing regions of the world. The genotype used in this study was based on a double haploid population derived from a cross between the Chinese cabbage line BY and a European turnip line MM, susceptible and resistant to downy mildew, respectively. We initially located a locus Br-DM04 for downy mildew resistance in a region about 2.7 Mb on chromosome A04, which accounts for 22.3% of the phenotypic variation. Using a large F2 mapping population (1156 individuals) we further mapped Br-DM04 within a 160 kb region, containing 17 genes encoding proteins. Based on sequence annotations for these genes, four candidate genes related to disease resistance, BrLRR1, BrLRR2, BrRLP47, and BrRLP48 were identified. Overexpression of both BrRLP47 and BrRLP48 using a transient expression system significantly enhanced the downy mildew resistance of the susceptible line BY. But only the leaves infiltrated with RNAi construct of BrRLP48 could significantly reduce the disease resistance in resistant line MM. Furthermore, promoter sequence analysis showed that one salicylic acid (SA) and two jasmonic acid-responsive transcript elements were found in BrRLP48 from the resistant line, but not in the susceptible one. Real-time PCR analysis showed that the expression level of BrRLP48 was significantly induced by inoculation with downy mildew or SA treatment in the resistant line MM. Based on these findings, we concluded that BrRLP48 was involved in disease resistant response and the disease-inducible expression of BrRLP48 contributed to the downy mildew resistance. These findings led to a new understanding of the mechanisms of resistance and lay the foundation for marker-assisted selection to improve downy mildew resistance in Brassica rapa

Identification and characterization of bone/cartilage-associated signatures in common fibrotic skin diseases

Background: Fibrotic skin diseases are characterized by excessive accumulation of the extracellular matrix (ECM) and activation of fibroblasts, leading to a global healthcare burden. However, effective treatments of fibrotic skin diseases remain limited, and their pathological mechanisms require further investigation. This study aims to investigate the common biomarkers and therapeutic targets in two major fibrotic skin diseases, namely, keloid and systemic sclerosis (SSc), by bioinformatics analysis.Methods: The keloid (GSE92566) and SSc (GSE95065) datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, followed by functional enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We then constructed a protein–protein interaction (PPI) network for the identification of hub genes. We explored the possibility of further functional enrichment analysis of hub genes on the Metascape, GeneMANIA, and TissueNexus platforms. Transcription factor (TF)–hub gene and miRNA–hub gene networks were established using NetworkAnalyst. We fixed GSE90051 and GSE76855 as the external validation datasets. Student’s t-test and receiver operating characteristic (ROC) curve were used for candidate hub gene validation. Hub gene expression was assessed in vitro by quantitative real-time PCR.Results: A total of 157 overlapping DEGs (ODEGs) were retrieved from the GSE92566 and GSE95065 datasets, and five hub genes (COL11A1, COL5A2, ASPN, COL10A1, and COMP) were identified and validated. Functional studies revealed that hub genes were predominantly enriched in bone/cartilage-related and collagen-related processes. FOXC1 and miR-335-5p were predicted to be master regulators at both transcriptional and post‐transcriptional levels.Conclusion: COL11A1, COL5A2, ASPN, COL10A1, and COMP may help understand the pathological mechanism of the major fibrotic skin diseases; moreover, FOXC1 and miR-355-5p could build a regulatory network in keloid and SSc

Apolipoprotein E Overexpression Is Associated With Tumor Progression and Poor Survival in Colorectal Cancer

Apolipoprotein E (ApoE) plays a key role in tumorigenesis and progression, such as cell proliferation, angiogenesis and metastasis. ApoE overexpression was associated with aggressive biological behaviors and poor prognosis in a variety of tumor according to previous studies. This study aimed to assess the prognostic value and explore the potential relationship with tumor progression in colorectal cancer (CRC). We collected the expression profiling microarray data from the Gene Expression Omnibus (GEO), investigated the ApoE expression pattern between the primary CRC and liver metastasis of CRC, and then explored the gene with prognostic significance based on the TCGA database. ApoE high expression was associated with poor overall survival (OS, p = 0.015) and progression-free survival (PFS, p = 0.004) based on the public databases. Next, ApoE expression was evaluated in two CRC cohorts by immunohistochemistry, of whom 306 cases were stage II and 201 cases were metastatic liver CRC. In the cohort of the liver metastasis, the ApoE expression was increasing in normal mucosa tissue, primary colorectal cancer (PC), and colorectal liver metastases (CLM) in order. Meanwhile, the level of ApoE expression in stage II tumor sample which had no progression evidence in 5 years was lower than that in PC of synchronous liver metastases. The high ApoE expression in PC was an independent risk factor in both stage II (HR = 2.023, [95% CI 1.297–3.154], p = 0.002; HR = 1.883, [95% CI 1.295-2.737], p = 0.001; OS and PFS respectively) and simultaneous liver metastasis (HR = 1.559, [95% CI 1.096–2.216], p = 0.013; HR = 1.541, [95% CI 1.129–2.104], p = 0.006; OS and PFS respectively). However, the overexpression of ApoE could not predict the benefit from the chemotherapy in stage II. The study revealed that the relevance of the ApoE overexpression in CRC progression, conferring a poor prognosis in CRC patients especially for stage II and simultaneous liver metastasis. These finding may improve the prognostic stratification of patients for clinical strategy selection and promote CRC clinic outcomes