Comparative analysis of spatial and transform domain methods for meningioma subtype classification

Pattern recognition in histopathological image analysis requires new techniques and methods. Various techniques have been presented and some state of the art techniques have been applied to complex textural data in histological images. In this paper, we compare the novel Adaptive Discriminant Wavelet Packet Transform (ADWPT) with a few prominent techniques in texture analysis namely Local Binary Patterns (LBP), Grey Level Co-occurrence Matrices (GLCMs) and Gabor Transforms. We show that ADWPT is a better technique for Meningioma subtype classification and produces classification accuracies of as high as 90%

Effect of Salvadora persica Linn root aqueous extract on oral epithelial dysplasia and oral cancer cell lines

Purpose: To evaluate the potential chemo-preventive and anti-oral cancer effects of Salvadora persica (S. persica) on oral epithelial dysplasia and oral squamous cell carcinoma cell lines. Methods: Aqueous S. persica root extracts were prepared at concentrations up to 15.75 mg/mL and applied to oral epithelial dysplasia (DOK), oral squamous cell carcinoma (PE/CA-PJ15), and periodontal ligament fibroblast (PDL) cell lines. The effect of the extract on cell survival and proliferation was determined using MTT assay, while its effect on apoptosis in DOK and PE/CA-PJ15 lines were investigated by measuring apoptotic index using Hoechst stain. Results: In DOK and PE/CA-PJ15 cell lines, cytotoxicity was significant at extract concentrations of 11.25, 13.50 and 15.75 mg/mL, while extract concentration of 13.50 mg/mL produced significant cytotoxic effects on PDL cell line (p < 0.05). The percentage of apoptotic cells significantly increased at extract concentration of 11.25 mg/mL for both DOK and PE/CA-PJ15 cell lines (p < 0.05). Conclusion: Significant cytotoxic effects of aqueous root extract of S. persica appeared at a lower concentration in oral epithelial dysplasia and oral cancer cell lines than in normal PDL cell line. These results suggest the potential of S. persica for preventing oral cancer

A robust adaptive wavelet-based method for classification of meningioma histology images

Intra-class variability in the texture of samples is an important problem in the domain of histological image classification. This issue is inherent to the field due to the high complexity of histology image data. A technique that provides good results in one trial may fail in another when the test and training data are changed and therefore, the technique needs to be adapted for intra-class texture variation. In this paper, we present a novel wavelet based multiresolution analysis approach to meningioma subtype classification in response to the challenge of data variation.We analyze the stability of Adaptive Discriminant Wavelet Packet Transform (ADWPT) and present a solution to the issue of variation in the ADWPT decomposition when texture in data changes. A feature selection approach is proposed that provides high classification accuracy

Characterizing Visual Programming Approaches for End-User Developers: A Systematic Review

Recently many researches have explored the potential of visual programming in robotics, the Internet of Things (IoT), and education. However, there is a lack of studies that analyze the recent evidence-based visual programming approaches that are applied in several domains. This study presents a systematic review to understand, compare, and reflect on recent visual programming approaches using twelve dimensions: visual programming classification, interaction style, target users, domain, platform, empirical evaluation type, test participants’ type, number of test participants, test participants’ programming skills, evaluation methods, evaluation measures, and accessibility of visual programming tools. The results show that most of the selected articles discussed tools that target IoT and education, while other fields such as data science, robotics are emerging. Further, most tools use abstractions to hide implementation details and use similar interaction styles. The predominant platforms for the tools are web and mobile, while desktop-based tools are on the decline. Only a few tools were evaluated with a formal experiment, whilst the remaining ones were evaluated with evaluation studies or informal feedback. Most tools were evaluated with students with little to no programming skills. There is a lack of emphasis on usability principles in the design stage of the tools. Additionally, only one of the tools was evaluated for expressiveness. Other areas for exploration include supporting end users throughout the life cycle of applications created with the tools, studying the impact of tutorials on improving learnability, and exploring the potential of machine learning to improve debugging solutions developed with visual programming

Viscosity of fluid membranes measured from vesicle deformation

Viscosity is a key mechanical property of cell membranes that controls time-dependent processes such as membrane deformation and diffusion of embedded inclusions. Despite its importance, membrane viscosity remains poorly characterized because existing methods rely on complex experimental designs and/or analyses. Here, we describe a facile method to determine the viscosity of bilayer membranes from the transient deformation of giant unilamellar vesicles induced by a uniform electric field. The method is non-invasive, easy to implement, probe-independent, high-throughput, and sensitive enough to discern membrane viscosity of different lipid types, lipid phases, and polymers in a wide range, from 10$^{-8}$ to 10$^{-4}$ Pa.s.m. It enables fast and consistent collection of data that will advance understanding of biomembrane dynamics

Hypoxia-induced gene expression pattern in doxorubicin resistant MCF7 cells

Purpose: To investigate hypoxia-induced gene expression pattern in doxorubicin-resistant human breast cancer cells (MCF7). Methods: Human breast cancer cells (MCF7) were exposed to 60 episodes of 8 h hypoxia thrice a week for three months. Chemo-resistance to doxorubicin was assessed using 3-(4,5-dimethylthiazol-2- yl)-2, 5-diphenyl tetrazolium bromide (MTT) cell proliferation assay. Real-time quantitative polymerase chain reaction (qRT-PCR) assay was performed to assess gene expression pattern in doxorubicinresistant cells on exposure to hypoxia. Results: Hypoxia significantly increased the resistance of MCF7 cells to doxorubicin, with a maximum of 16.42-fold enhancement after 25 episodes of 8-h hypoxia, while the resistance thereafter significantly decreased with prolonged episodes of hypoxia (p < 0.05). Gene expression analysis revealed significant changes in 42 genes. The expressions of 10 of these genes were significantly upregulated, while those of 32 genes were significantly down-regulated (p < 0.05). Cytochrome P450 family 1, subfamily A, member1 (CYP1A1) was the most conspicuous upregulated gene (13.32-fold), while breast cancer gene 1 (BRCA1) was the most down-regulated (8.23-fold). Gene expression analysis after 60 episodes of 8-h hypoxia revealed the upregulation of CYP1A1 (5.77-fold). Similarly, 27 genes were significantly down-regulated, with BRCA2 as the most down-regulated gene (8.11-fold). Topoisomerase (DNA) II alpha (TOP2A) was the most down-regulated among genes involved in drug metabolism and resistance (6.37-fold), while cyclin-dependent kinase 2 (CDK2) was the most profoundly downregulated among genes involved in cell cycle regulation (3.56-fold). Conclusion: These results indicate that development of resistance to doxorubicin by MCF7 cells after short-term hypoxia results from the upregulation of genes responsible for the metabolism of doxorubicin and for shifting the cells to alternative pathway driven principally by EGF and ESR2. The observed down-regulation is an adaptation of the MCF7 cells to survive under long-term hypoxia