DNA Methylation can lead to abnormal gene expression. In the present study, we investigated whether the expression of methylated MFSD4A (major facilitator superfamily domain containing 4 A) was ...downregulated in nasopharyngeal carcinoma (NPC) and whether it is associated with malignant progression and poor prognosis of NPC. Bioinformatic analysis, bisulfite pyrosequencing, quantitative real-time reverse transcription PCR, and western blotting assays were performed to explore the relationship between hypermethylation of MFSD4A and its expression in NPC. The role of MFSD4A in NPC was verified by Cell Cycle Kit 8, transwell assays and flow cytometry in vitro and by animal experiments in vivo. Mass spectrometry, co-immunoprecipitation, and immunofluorescence assays were applied to explore the mechanism by which MFSD4A inhibits NPC. The prognostic significance of MFSD4A or EPHA2 was investigated by immunohistochemical analysis of clinical specimens. Hypermethylation of the promoter region of MFSD4A led to decreased expression of MFSD4A. When MFSD4A expression was upregulated or downregulated, the proliferation, apoptosis, migration, and invasion abilities of NPC cells were altered accordingly. Mechanistically, MFSD4A could specifically bind to and degrade EPH receptor A2 (EPHA2) by recruiting ring finger protein 149 (RNF149), which led to alterations in the EPHA2-mediated PI3K-AKT-ERK1/2 pathway and epithelial-mesenchymal transition (EMT), thereby affecting NPC progression. Clinically, high MFSD4A expression or low-EPHA2 expression was associated with better prognosis for patients with NPC. In all, reduced MFSD4A expression in NPC is caused by promoter hypermethylation. MFSD4A or EPHA2 expression is associated with the malignant biological behavior and prognosis of NPC. MFSD4A is a promising potential therapeutic target for NPC.
Environments in both biotic and abiotic ecosystems have been affected by the colonization of non-native flora. In this study, we examined the effect of Bidens alba invasion on different land-use ...types along a coastline in southern China. Bacterial communities in each site were determined using 16S rDNA sequencing, and soil physicochemical properties were analyzed using standard methods. Although our results indicated that B. alba invasion did not have a significant effect on the alpha diversity of bacteria, it caused significant differences in soil bacterial community composition between invaded and uninvaded soil across different land-use types. Beta diversity and several physicochemical properties in forest, orchard and waterfront environments were recorded to be more susceptible to B. alba invasion. A high proportion of the variation of bacterial communities can be explained by a combination of environmental variables, indicating that environmental selection rather than plant invasion is a more effective process in coastal microbial assemblages. By comparing topological roles of shared OTUs among invaded and uninvaded soil, keystone taxa in invaded soil were identified. Acidobacteria was the major phyla involved in the invasive process which could be driven by environmental selection. How key phyla react in our experiment should be verified by further studies.
Identifying patterns and drivers of plant community assembly has long been a central issue in ecology. Many studies have explored the above questions using a trait‐based approach; however, there are ...still unknowns around how patterns of plant functional traits vary with environmental gradients. In this study, the responses of individual and multivariate trait dispersions of 134 species to soil resource availability were examined based on correlational analysis and torus‐translation tests across four spatial scales in a subtropical forest, China. Results indicated that different degrees of soil resource availability had different effects on trait dispersions. Specifically, limited resource (available phosphorus) showed negative relationships with trait dispersions, non‐limited resource (available potassium) showed positive relationships with trait dispersions, and saturated resource (available nitrogen) had no effect on trait dispersions. Moreover, compared with the stem (wood density) and architectural trait (maximum height), we found that leaf functional traits can well reflect the response of plants to nutrient gradients. Lastly, the spatial scale only affected the magnitude but not the direction of the correlations between trait dispersions and environmental gradients. Overall, the results highlight the importance of soil resource availability and spatial scale in understanding how plant functional traits respond to environmental gradients.
In this study, the responses of individual and multivariate trait dispersions of 134 species in Dinghushan plot, China, to soil resource availability were examined. Results showed that different degrees of soil resource availability had different effects on trait dispersions. Specifically, limited resource mainly showed negative relationships with trait dispersions, non‐limited resource mainly showed positive relationships with trait dispersions, and saturated resource had no effect on trait dispersions.
Tree species diversity is vital for maintaining ecosystem functions, yet our ability to map the distribution of tree diversity is limited due to difficulties in traditional field-based approaches. ...Recent developments in spaceborne remote sensing provide unprecedented opportunities to map and monitor tree diversity more efficiently. Here we built partial least squares regression models using the multispectral surface reflectance acquired by Sentinel-2 satellites and the inventory data from 74 subtropical forest plots to predict canopy tree diversity in a national natural reserve in eastern China. In particular, we evaluated the underappreciated roles of the practical definition of forest canopy and phenological variation in predicting tree diversity by testing three different definitions of canopy trees and comparing models built using satellite imagery of different seasons. Our best models explained 42%–63% variations in observed diversities in cross-validation tests, with higher explanation power for diversity indices that are more sensitive to abundant species. The models built using imageries from early spring and late autumn showed consistently better fits than those built using data from other seasons, highlighting the significant role of transitional phenology in remotely sensing plant diversity. Our results suggested that the cumulative diameter (60%–80%) of the biggest trees is a better way to define the canopy layer than using the subjective fixed-diameter-threshold (5–12 cm) or the cumulative basal area (90%–95%) of the biggest trees. Remarkably, these approaches resulted in contrasting diversity maps that call attention to canopy structure in remote sensing of tree diversity. This study demonstrates the potential of mapping and monitoring tree diversity using the Sentinal-2 data in species-rich forests.
Community assembly in natural communities is commonly explained by stochastic and niche-based processes such as environmental filtering and biotic interactions. Many studies have inferred the ...importance of these processes using a trait-based approach, however, there are still unknowns around what factors affect the importance of different assembly processes in natural communities. In this study, the trait dispersion patterns of 134 species were examined across different functional traits, habitat types, ontogenetic stages and spatial scales from a 20-ha Dinghushan Forest Dynamic Plot in China. The results showed that (1) functional traits related to productivity such as specific leaf area and leaf area mainly showed functional clustering, indicating these two functional traits were more affected by environmental filtering. However, trait dispersion patterns depended on more than the ecological significances of functional traits. For example, trait dispersions of leaf dry matter content, leaf thickness and maximum height did not show consistent patterns across habitat types and ontogenetic stages, suggesting more complex mechanisms may operate on these traits; (2) the trait dispersion varied with the habitat types and ontogenetic stages. Specifically, we found that habitat types only affected the strength of trait dispersions for all the five traits, but ontogenetic stages influenced both the strength and direction of trait dispersions, which depended on the traits selected; (3) the relative importance of soil, topography and space to trait dispersion varied with ontogenetic stages. Topography and space were more important for trait dispersion of saplings but soil was more important for trait dispersion of adults; (4) biotic interactions dominated community assembly at smaller spatial scales but environmental filtering dominated community assembly at larger spatial scales. Overall, the results highlight the importance of functional traits, habitat types, ontogenetic stages and spatial scales to community assembly in natural communities.
The aldolization of formaldehyde and acetone to form 4-hydroxy-2-butanone over anion exchange resins with and without modifications is investigated in this work. Attempts such as surfactants addition ...and Soxhlet extraction are taken aiming to improve the aldolization selectivity thus the product yield. Subsequently, resins grafted long alkyl chains intrigue us for its steric hindrance effect and the synergic effect of weak and strong basic sites. Two types of modifications are carried out (1) one long alkyl chain on the copolymer tertiary amine via Menshutkin N-alkylation reaction; (2) two long alkyl chains: one on polystyrene aromatic ring through FriedelaCrafts alkylation under the circumstances of tertiary amine and the other on the copolymer tertiary amine using the Menshutkin N-alkylation reaction. The reaction results indicate that the yield for 4-hydroxy-2-butanone can be increased from 44.3% to around 50% for the resin with one long alkyl chain (the first case), while this can achieve up to 71.3% for the resin with two long alkyl chains.
Security monitoring and analysis can help users to timely perceive threats faced by the host, thereby protecting and backup data and improving the host's security status. In the research domain of ...host security analysis, many feasible solutions have been proposed. However, real‐time performance and accuracy still need improvement. This paper proposes a host security analysis method based on Dempster–Shafer (D‐S) evidence theory. It adopts three models of support vector regression, logistic regression, and K‐nearest neighbor regression, as sensors for multisource information fusion. Multiple sensors perform security analysis on the host, respectively, and use the analysis results as evidence of D‐S evidence theory. Experiments show that the proposed method provides effective security protection for the host in terms of absolute error, root mean square error, and the average absolute percentage error.
Intrusion Detection Systems (IDS) are crucial in cybersecurity for monitoring network traffic and identifying potential attacks. Existing IDS research largely focuses on known attack detection, ...leaving a significant gap in research regarding unknown attack detection, where achieving a balance between false alarm rate (identifying normal traffic as attack traffic) and recall rate of unknown attack detection remains challenging. To address these gaps, we propose a novel IDS based on Sigmoid Kernel Transformation and Encoder-Decoder architecture, namely SKT-IDS, where SKT stands for Sigmoid Kernel Transformation. We start with pre-training an attention-based encoder for coarse-grained intrusion detection. Then, we use this encoder to build an encoder–decoder model specifically for 0-day attack detection, training it solely on known traffic using the cosine similarity loss function. To enhance detection, we introduce a Sigmoid Kernel Transformation for feature engineering, improving the discriminative ability between normal traffic and 0-day attacks. Finally, we conducted a series of ablation and comparative experiments on the NSL-KDD and CSE-CIC-IDS2018 datasets, confirming the effectiveness of our proposed method. With a false alarm rate of 1%, we achieved recall rates for unknown attack detection of 65% and 69% on the two datasets, respectively, demonstrating significant performance improvements compared to existing state-of-the-art models.
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