Adhesion study of tetra methyl cyclo tetra siloxanes (TMCTS) and tri methyl silane (3MS)-based low-k films

Chemical vapor deposited (CVD) low-k films using tri methyl silane (3MS) precursors and tetra methyl cyclo tetra siloxanes (TMCTS) precursors were studied. Films were deposited by means of four processes, namely, O₂, O₂ + He process and CO₂, CO₂ + O₂ process for 3MS and TMCTS precursors, respectively. Interfacial adhesion energy (G_c), of low-k/Si samples, as measured by a 4-point bending test displayed a linear relationship with film hardness and modulus. Fractography studies indicated two possible failure modes with the primary interface of delamination being either at low-k/Si or Si/epoxy interface. In the former, once delamination initiated at the low-k/Si interface, secondary delamination at the Si/epoxy and epoxy/low-k interfaces was also observed. Films with low hardness (<5 GPa) displayed a low G_c (<10 J/m²) with an adhesive separation of Si/epoxy, epoxy/low-k, and low-k/Si interfaces. Whereas, films of high hardness (>5 GPa) displayed interfacial energies in excess of 10 J/m² with separation of Si/epoxy and epoxy/low-k interfaces, thus indicating excellent adhesion between the Si and low-k films. Films with high hardness have less carbon in the system causing it to be more “silicon dioxide” like and exhibiting better adhesion with the Si substrate.     

Neuro-levelset system based segmentation in dynamic susceptibility contrast enhanced and diffusion weighted magnetic resonance images

In this study, neuro-levelset method is proposed and evaluated for segmentation and grading of brain tumors on reconstructed images of dynamic susceptibility contrast (DSC) and diffusion weighted (DW) magnetic resonance images. The proposed neuro-levelset method comprises of two independent phases of processing. At first, reconstructed images have been independently processed by three different artificial neural network systems such as multilayer perceptron (MLP), self-organizing map (SOM), and radial basis function (RBF). The images used for these tasks were the cerebral blood volume (CBV), time to peak (TTP), percentage of base at peak (PBP) and apparent diffusion coefficient (ADC) images. This processing step ensued in formation of segmentation images of brain tumors. Further, in the second phase, these coarse segmented images of each artificial neural network system have been independently subjected as speed images to levelset method in order to optimize the segmentation performance. This has resulted in construction of three distinct neuro-levelset methods such as MLP-levelset, SOM-levelset and RBF-levelset method. Proposed neuro-levelset methods performed better in segmenting tumor, edema, necrosis, CSF and normal tissues as compared to independent artificial neural network systems. Among three neuro-levelset methods, RBF-levelset system has performed well with average sensitivity and specificity values of 91.43±2.94% and 94.43±1.90%, respectively.     

Bioinspired glycosaminoglycan hydrogels via click chemistry for 3D dynamic cell encapsulation

Cell encapsulation within 3D hydrogels is an attractive approach to develop effective cell-based therapies. However, little is known about how cells respond to the dynamic microenvironment resulting from hydrogel gelation-based cell encapsulation. Here, a tunable biomimetic hydrogel system that possesses alterable gelation kinetics and biologically relevant matrix stiffness is developed to study 3D dynamic cellular responses during encapsulation. Hydrogels are synthesized by crosslinking thiolated hyaluronic acid and thiolated chondroitin sulfate with poly(ethylene glycol) diacrylate under cell-compatible conditions. Hydrogel properties are tailored by altering thiol substitution degrees of glycosaminoglycans or molecular weights of crosslinkers. Encapsulation of human mesenchymal stem cells through hydrogel gelation reveals high cell viability as well as a three-stage gelation-dependent cellular response in real-time focal adhesion kinase (FAK) phosphorylation in live single cells. Furthermore, stiffer hydrogels result in higher equilibrium FAK activity and enhanced actin protrusions. Our results demonstrate the promise of hydrogel-mediated cellular responses during cell encapsulation. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47212.     

Effects of ternary alloying on mechano-synthesis and nano-crystal stability of an iron-silicon alloy

This paper reports the effects of ternary alloying additions Al, Cu and Nb to Fe₇₅Si₂₅ in high energy ball milling to produce nano-crystalline alloy powder, and its microstructural stability during subsequent high temperature annealing. It is shown that all additions generally retard grain growth up to some temperature. Nb appears to amorphise the alloy. The binary base alloy and Al containing alloy forms the DO₃ ordered structure at high temperatures accompanied by rapid grain growth. The Cu and Nb containing alloys precipitate Cu and Nb₂Fe at high temperatures but do not become ordered.     

A Search for Cyclin-Dependent Kinase 4/6 Inhibitors by Pharmacophore-Based Virtual Screening,Molecular Docking,and Molecular Dynamic Simulations

The G1 phase of cell cycle progression is regulated by Cyclin-Dependent Kinase 4 (CDK4) as well as Cyclin-Dependent Kinase 6 (CDK6), and the acivities of these enzymes are regulated by the catalytic subunit, cyclin D. Cell cycle control through selective pharmacological inhibition of CDK4/6 has proven to be beneficial in the treatment of estrogen receptor-positive (ER-positive) breast cancer, particularly improving the progression-free survival of patients. Thus, targeting specific inhibition on CDK4/6 is bound to increase therapeutic efficiency. This study aimed to obtain CDK4/6 inhibitors through a pharmacophore-based virtual screening of the ZINC15 purchasable compound database using the in silico method. The pharmacophore model was designed based on the FDA-approved cdk4/6 inhibitor structures, and molecular docking was performed to further screen the hit compounds obtained. A total of eight compounds were selected based on docking results and interactions with CDK4 and CDK6, using palbociclib as the reference drug. According to the results, the compounds of ZINC585292724 and ZINC585291674 were the best compounds based on free binding energy, as well as hydrogen bond stability, and, therefore, exhibit potential as starting points in the development of CDK4/6 inhibitors.