GOLPH3 Regulates EGFR in T98G Glioblastoma Cells by Modulating Its Glycosylation and Ubiquitylation

Protein trafficking is altered when normal cells acquire a tumor phenotype. A key subcellular compartment in regulating protein trafficking is the Golgi apparatus, but its role in carcinogenesis is still not well defined. Golgi phosphoprotein 3 (GOLPH3), a peripheral membrane protein mostly localized at the trans-Golgi network, is overexpressed in several tumor types including glioblastoma multiforme (GBM), the most lethal primary brain tumor. Moreover, GOLPH3 is currently considered an oncoprotein, however its precise function in GBM is not fully understood. Here, we analyzed in T98G cells of GBM, which express high levels of epidermal growth factor receptor (EGFR), the effect of stable RNAi-mediated knockdown of GOLPH3. We found that silencing GOLPH3 caused a significant reduction in the proliferation of T98G cells and an unexpected increase in total EGFR levels, even at the cell surface, which was however less prone to ligand-induced autophosphorylation. Furthermore, silencing GOLPH3 decreased EGFR sialylation and fucosylation, which correlated with delayed ligand-induced EGFR downregulation and its accumulation at endo-lysosomal compartments. Finally, we found that EGF failed at promoting EGFR ubiquitylation when the levels of GOLPH3 were reduced. Altogether, our results show that GOLPH3 in T98G cells regulates the endocytic trafficking and activation of EGFR likely by affecting its extent of glycosylation and ubiquitylation.     

Modeling the Motion of a Saw Ginning Machine

The dynamic characteristics of a saw gin as a subsystem with lumped and distributed parameters are considered in the paper. On the basis of investigation of the machine assembly, graphs are drawn that allow establishing the maximum values of the angle of relative rotation and the angle of rotation of the saw cylinder shaft under torsion.     

The Role of Excitation Photons Energy in the Photoinduced Carrier Dynamics in InGaAs/InAlAs Superlattice Heterostructures

Technical Physics Letters - The influence of excitation photons energy on the relaxation times of photoexcited carriers is studied. The involved relaxation mechanisms are evaluated and the...     

Methyltransferase Contingencies in the Pathway of Everninomicin D Antibiotics and Analogues

Everninomicins are orthoester oligosaccharide antibiotics with potent activity against multidrug-resistant bacterial pathogens. Everninomicins act by disrupting ribosomal assembly in a distinct region in comparison to clinically prescribed drugs. We employed microporous intergeneric conjugation with Escherichia coli to manipulate Micromonospora for targeted gene-replacement studies of multiple putative methyltransferases across the octasaccharide scaffold of everninomicin effecting the A₁, C, F, and H rings. Analyses of gene-replacement and genetic complementation mutants established the mutability of the everninomicin scaffold through the generation of 12 previously unreported analogues and, together with previous results, permitted assignment of the ten methyltransferases required for everninomicin biosynthesis. The in vitro activity of A₁- and H-ring-modifying methyltransferases demonstrated the ability to catalyze late-stage modification of the scaffold on an A₁-ring phenol and H-ring C-4’ hydroxy moiety. Together these results establish the potential of the everninomicin scaffold for modification through mutagenesis and in vitro modification of advanced biosynthetic intermediates.     

A simple model for the semicontinuous heterophase polymerization: Ethyl methacrylate as a case example

A simple but comprehensive model considering homogeneous and micellar nucleation, coagulation, entry of radicals to particles and to micelles and radicals' exit from particles, is presented. The model is validated, in a starved semicontinuous heterophase polymerization of ethyl methacrylate, at three monomer addition rates. The model accurately describes the overall and instantaneous conversion, the average particle density and diameter, and the number and weight average molar masses evolutions over time. It is found that even though the average number of radicals is much smaller than 0.5, the system is not 0-1. An empirical function was used to describe the gel effect. The homogeneous nucleation was the prevailing mechanism for particle formation and large exit rates of radicals were observed. POLYM. ENG. SCI., 60: 223–232, 2019. © 2019 Society of Plastics Engineers     

Study of the Density of Interface States at the Insulator/In0.52Al0.48As Interface

Technical Physics Letters - The C–V characteristics of Au/Al2O3/In0.52Al0.48As and Au/SiO2/In0.52Al0.48As metal–insulator–semiconductor structures have been studied. It has been...     

Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods.