HSV-1 miR-H6 Inhibits HSV-1 Replication and IL-6 Expression in Human Corneal Epithelial Cells In Vitro

HSV-1 infection in the cornea could lead to blindness. The infected cell polypeptide 4 (ICP4) of herpes simplex virus 1 (HSV-1) is a regulator of viral transcription that is required for productive infection. It has been previously demonstrated that miR-H6 encoded from HSV-1 genome targets ICP4 to help maintain latency. In this study, synthesized miR-H6 mimics were transfected into HSV-1-infected human cornea epithelial (HCE) cells. The inhibition of HSV-1 replication and viral ICP4 expression in miR-H6-transfected HCE was confirmed by plaque assay, immunofluorescence, and Western blot. Compared to nontransfection or mock, miR-H6 produced a low-titer HSV-1 and weak ICP4 expression. In addition, miR-H6 can decrease the interleukin 6 released into the medium, which was determined by ELISA. Taken together, the data suggests that miR-H6 targeting of ICP4 inhibits HSV-1 productive infection and decreases interleukin 6 production in HCE, and this may provide an approach to prevent HSV-1 lytic infection and inhibit corneal inflammation

Energy-Based Controller Design of Stochastic Magnetic Levitation System

This paper investigates the control problem of magnetic levitation system, in which velocity feedback signal is influenced by stochastic disturbance. Firstly, single-degree-freedom magnetic levitation is regarded as an energy-transform action device. From the view of energy-balance relation, the magnetic levitation system is transformed into port-controlled Hamiltonian system model. Next, based on the Hamiltonian structure, the control law of magnetic levitation system is designed by applying Lyapunov theory. Finally, the simulation verifies the correctness of the proposed results

Seven Glycolysis-Related Genes Predict the Prognosis of Patients With Pancreatic Cancer

ObjectivesTo identify the key glycolysis-related genes (GRGs) in the occurrence and development of pancreatic ductal carcinoma (PDAC), and to construct a glycolysis-related gene model for predicting the prognosis of PDAC patients.MethodologyPancreatic ductal carcinoma (PDAC) data and that of normal individuals were downloaded from the TCGA database and Genotype-Tissue Expression database, respectively. GSEA analysis of glycolysis-related pathways was then performed on PDAC data to identify significantly enriched GRGs. The genes were combined with other patient’s clinical information and used to construct a glycolysis-related gene model using cox regression analysis. The model was further evaluated using data from the validation group. Mutations in the model genes were subsequently identified using the cBioPortal. In the same line, the expression levels of glycolysis related model genes in PDAC were analyzed and verified using immunohistochemical images. Model prediction for PDAC patients with different clinical characteristics was then done and the relationship between gene expression level, clinical stage and prognosis further discussed. Finally, a nomogram map of the predictive model was constructed to evaluate the prognosis of patients with PDAC.ResultsGSEA results of the training set revealed that genes in the training set were significantly related to glycolysis pathway and iconic glycolysis pathway. There were 108 differentially expressed GRGs. Among them, 29 GRGs were closely related to prognosis based on clinical survival time. Risk regression analysis further revealed that there were seven significantly expressed glycolysis related genes. The genes were subsequently used to construct a predictive model. The model had an AUC value of more than 0.85. It was also significantly correlated with survival time. Further expression analysis revealed that CDK1, DSC2, ERO1A, MET, PYGL, and SLC35A3 were highly expressed in PDAC and CHST12 was highly expressed in normal pancreatic tissues. These results were confirmed using immunohistochemistry images of normal and diseases cells. The model could effectively evaluate the prognosis of PDAC patients with different clinical characteristics.ConclusionThe constructed glycolysis-related gene model effectively predicts the occurrence and development of PDAC. As such, it can be used as a prognostic marker to diagnose patients with PDAC

A Quantum Mechanism Study of the C-C Bond Cleavage to Predict the Bio-Catalytic Polyethylene Degradation

The growing amount of plastic solid waste (PSW) is a global concern. Despite increasing efforts to reduce the residual amounts of PSW to be disposed off through segregated collection and recycling, a considerable amount of PSW is still landfilled and the extent of PSW ocean pollution has become a worldwide issue. Particularly, polyethylene (PE) and polystyrene (PS) are considered as notably recalcitrant to biodegradation due to the carbon-carbon backbone that is highly resistant to enzymatic degradation via oxidative reactions. The present research investigated the catalytic mechanism of P450 monooxygenases by quantum mechanics to determine the bio-catalytic degradation of PE or PS. The findings indicated that the oxygenase-induced free radical transition caused the carbon-carbon backbone cleavage of aliphatic compounds. This work provides a fundamental knowledge of the biodegradation process of PE or PS at the atomic level and facilitates predicting the pathway of plastics’ biodegradation by microbial enzymes

Multiplexed five-color molecular imaging of cancer cells and tumor tissues with carbon nanotube Raman tags in the near-infrared

Single-walled carbon nanotubes (SWNTs) with five different C13/C12 isotope compositions and well-separated Raman peaks have been synthesized and conjugated to five targeting ligands in order to impart molecular specificity. Multiplexed Raman imaging of live cells has been carried out by highly specific staining of cells with a five-color mixture of SWNTs. Ex vivo multiplexed Raman imaging of tumor samples uncovers a surprising up-regulation of epidermal growth factor receptor (EGFR) on LS174T colon cancer cells from cell culture to in vivo tumor growth. This is the first time five-color multiplexed molecular imaging has been performed in the near-infrared (NIR) region under a single laser excitation. Near zero interfering background of imaging is achieved due to the sharp Raman peaks unique to nanotubes over the low, smooth autofluorescence background of biological species.Comment: Published in Nano Researc

β-Alanine Metabolism Leads to Increased Extracellular pH during the Heterotrophic Ammonia Oxidation of Pseudomonas putida Y-9

The mechanisms underlying the increase in external pH caused by heterotrophic nitrification and aerobic denitrification microorganisms during ammonia oxidation were unclear. This work demonstrated that after culturing Pseudomonas putida Y-9 for 60 h in a medium with ammonium nitrogen as the sole nitrogen source at an initial pH of 7.20, the pH value increased to 9.21. GC-TOF-MS analysis was used to compare the significantly regulated metabolites and related metabolic pathways between different time points. The results showed that the consumption of H+ in the conversion of malonic acid to 3-hydroxypropionic acid in the β-alanine metabolic pathway was the main reason for the increase in pH. RT-qPCR confirmed that the functional gene ydfG dominated the consumption of H+. This study provides new research ideas for the change of external pH caused by bacterial metabolism and further expands the understanding of the interaction between bacteria and the environment

β-Alanine Metabolism Leads to Increased Extracellular pH during the Heterotrophic Ammonia Oxidation of <i>Pseudomonas putida</i> Y-9

The mechanisms underlying the increase in external pH caused by heterotrophic nitrification and aerobic denitrification microorganisms during ammonia oxidation were unclear. This work demonstrated that after culturing Pseudomonas putida Y-9 for 60 h in a medium with ammonium nitrogen as the sole nitrogen source at an initial pH of 7.20, the pH value increased to 9.21. GC-TOF-MS analysis was used to compare the significantly regulated metabolites and related metabolic pathways between different time points. The results showed that the consumption of H+ in the conversion of malonic acid to 3-hydroxypropionic acid in the β-alanine metabolic pathway was the main reason for the increase in pH. RT-qPCR confirmed that the functional gene ydfG dominated the consumption of H+. This study provides new research ideas for the change of external pH caused by bacterial metabolism and further expands the understanding of the interaction between bacteria and the environment

Catalytic Reduction of Organic Dyes by Multilayered Graphene Platelets and Silver Nanoparticles in Polyacrylic Acid Hydrogel

Graphene oxide has been widely used in the oxidative degradation of environmental pollutants. However, its catalytic role can be questioned as graphene oxide with oxygen-containing functional groups may also act as reactant in oxidative reactions. Herein, hydrogel composites loaded with multilayered graphene platelets showed excellent catalytic performance for the reduction of a wastewater organic pollutant (methylene blue) under NaBH4, which proved the catalytic role of multilayered graphene platelets. The liquid-based direct exfoliation method was used to prepare two-dimensional materials, which is compatible with other liquid phase methods to prepare nanomaterials. Hydrogel composites composed of multilayered graphene platelets, silver nanoparticles, and polyacrylic acid hydrogels were synthesized in water solution under irradiation with ultraviolet light, demonstrating the advantages of synthesizing nanocomposites using the liquid-based direct exfoliation method

Molecular Mechanism Study on Stereo-Selectivity of α or β Hydroxysteroid Dehydrogenases

Hydroxysteroid dehydrogenases (HSDHs) are from two superfamilies of short-chain dehydrogenase (SDR) and aldo–keto reductase (AKR). The HSDHs were summarized and classified according to their structural and functional differences. A typical pair of enzymes, 7α–hydroxysteroid dehydrogenase (7α–HSDH) and 7β–hydroxysteroid dehydrogenase (7β–HSDH), have been reported before. Molecular docking of 7-keto–lithocholic acid(7–KLA) to the binary of 7β–HSDH and nicotinamide adenine dinucleotide phosphate (NADP+) was realized via YASARA, and a possible binding model of 7β–HSDH and 7–KLA was obtained. The α side of 7–KLA towards NADP+ in 7β–HSDH, while the β side of 7–KLA towards nicotinamide adenine dinucleotide (NAD+) in 7α–HSDH, made the orientations of C7–OH different in products. The interaction between Ser193 and pyrophosphate of NAD(P)+ [Ser193–OG⋯3.11Å⋯O1N–PN] caused the upturning of PN–phosphate group, which formed a barrier with the side chain of His95 to make 7–KLA only able to bind to 7β–HSDH with α side towards nicotinamide of NADP+. A possible interaction of Tyr253 and C24 of 7–KLA may contribute to the formation of substrate binding orientation in 7β–HSDH. The results of sequence alignment showed the conservation of His95, Ser193, and Tyr253 in 7β–HSDHs, exhibiting a significant difference to 7α–HSDHs. The molecular docking of other two enzymes, 17β–HSDH from the SDR superfamily and 3(17)α–HSDH from the AKR superfamily, has furtherly verified that the stereospecificity of HSDHs was related to the substrate binding orientation

Feasible Cluster Model Method for Simulating the Redox Potentials of Laccase CueO and Its Variant

Laccases are regarded as versatile green biocatalysts, and recent scientific research has focused on improving their redox potential for broader industrial and environmental applications. The density functional theory (DFT) quantum mechanics approach, sufficiently rigorous and efficient for the calculation of electronic structures, is conducted to better comprehend the connection between the redox potential and the atomic structural feature of laccases. According to the crystal structure of wild type laccase CueO and its variant, a truncated miniature cluster model method was established in this research. On the basic of thermodynamic cycle, the overall Gibbs free energy variations before and after the one-electron reduction were calculated. It turned out that the trends of redox potentials to increase after variant predicted by the theoretical calculations correlated well with those obtained by experiments, thereby validating the feasibility of this cluster model method for simulating the redox potentials of laccases