Automated Assessment of Facial Wrinkling: a case study on the effect of smoking

Facial wrinkle is one of the most prominent biological changes that accompanying the natural aging process. However, there are some external factors contributing to premature wrinkles development, such as sun exposure and smoking. Clinical studies have shown that heavy smoking causes premature wrinkles development. However, there is no computerised system that can automatically assess the facial wrinkles on the whole face. This study investigates the effect of smoking on facial wrinkling using a social habit face dataset and an automated computerised computer vision algorithm. The wrinkles pattern represented in the intensity of 0-255 was first extracted using a modified Hybrid Hessian Filter. The face was divided into ten predefined regions, where the wrinkles in each region was extracted. Then the statistical analysis was performed to analyse which region is effected mainly by smoking. The result showed that the density of wrinkles for smokers in two regions around the mouth was significantly higher than the non-smokers, at p-value of 0.05. Other regions are inconclusive due to lack of large scale dataset. Finally, the wrinkle was visually compared between smoker and non-smoker faces by generating a generic 3D face model.Comment: 6 pages, 8 figures, Accepted in 2017 IEEE SMC International Conferenc

Evaluating Pharmacy Health Literacy and Its Barriers among Patients with Cardiovascular Diseases in Qatar

Background: Patients’ health literacy, which is their capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions, is a critical determinant of whether they are able to actively participate in their healthcare. The objective of this study was to measure the level of health literacy among patients with acute coronary syndrome (ACS) and/or heart failure (HF) and to explore barriers and facilitators to health literacy among this population. Methods: The Abbreviated version of the Test of Functional Health Literacy in Adults (S TOFHLA) and the Three-item Brief Health Literacy Screen (3-item BHLS) were used to assess health literacy levels among patients with ACS and/or HF. A qualitative approach was used to identify facilitators and barriers to health literacy with the use of one-to-one interviews for patients’ perspective and focus group discussions for healthcare providers’ perspective. Results: The prevalence of inadequate to marginal health literacy was found to be 36% using S TOFHLA and 54% using 3-item BHLS. The most prominent factors were found to contribute to health literacy including patient attitudes and attributes, healthcare provider skills and attitudes, healthcare facility attributes, communication-related aspects, care process, and resources. Conclusions: Limited health literacy is common among patients with ACS and/or HF in Qatar. Many aspects were found to play a role in the patient’s health literacy; therefore, combination of interventions may be necessary to yield the most improvement in patient understanding, health literacy, and health outcomes

A Novel Therapeutic Strategy for the Treatment of Glioma, Combining Chemical and Molecular Targeting of Hsp90a

Hsp90α's vital role in tumour survival and progression, together with its highly inducible expression profile in gliomas and its absence in normal tissue and cell lines validates it as a therapeutic target for glioma. Hsp90α was downregulated using the post-transcriptional RNAi strategy (sihsp90α) and a post-translational inhibitor, the benzoquinone antibiotic 17-AAG. Glioblastoma U87-MG and normal human astrocyte SVGp12 were treated with sihsp90α, 17-AAG and concurrent sihsp90α/17-AAG (combined treatment). Both Hsp90α gene silencing and the protein inhibitor approaches resulted in a dramatic reduction in cell viability. Results showed that sihsp90α, 17-AAG and a combination of sihsp90α/17-AAG, reduced cell viability by 27%, 75% and 88% (p < 0.001), respectively, after 72 h. hsp90α mRNA copy numbers were downregulated by 65%, 90% and 99% after 72 h treatment with sihsp90α, 17-AAG and sihsp90α/17-AAG, respectively. The relationship between Hsp90α protein expression and its client Akt kinase activity levels were monitored following treatment with sihsp90α, 17-AAG and sihsp90α/17-AAG. Akt kinase activity was downregulated as a direct consequence of Hsp90α inhibition. Both Hsp90α and Akt kinase levels were significantly downregulated after 72 h. Although, 17-AAG when used as a single agent reduces the Hsp90α protein and the Akt kinase levels, the efficacy demonstrated by combinatorial treatment was found to be far more effective. Combination treatment reduced the Hsp90α protein and Akt kinase levels to 4.3% and 43%, respectively, after 72 h. hsp90α mRNA expression detected in SVGp12 was negligible compared to U87-MG, also, the combination treatment did not compromise the normal cell viability. Taking into account the role of Hsp90α in tumour progression and the involvement of Akt kinase in cell signalling and the anti-apoptotic pathways in tumours, this double targets treatment infers a novel therapeutic strategy

Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments

Multi-Analytical Approach for Characterization of Archaeological Meroatic Potsherds

In this paper, the results obtained using a multi-analytical approach for characterization of six potsherds originally attributed to the 4th century BC excavated from Meroatic sites, Sudan were reported. Sort of the minerals and their structural deformation during the production forming process from the raw material used by artisan to ware were performed, in the particular, the maximum heating temperature obtained during burial and operative condition (open or close condition) of the kiln were performed by Fourier Transform Infrared Spectroscopy (FT-IR), X-Ray Diffraction (XRD) and thermogravimetric analysis (TGA) was the completing analysis to estimate the firing temperature from typical thermal reactions in potsherds. Further X-ray Ray Fluorescence, Scanning Electron Microscope (SEM) coupled with Energy Dispersive X-ray spectrometer (EDX) were used to analyze the morphology, chemical composition and find subsequent progress of vitrification levels. The XRD results give supportive information obtained from the FT-IR spectra. X-ray diffractometry results have shown the existence of quartz, albite (MER-02, MER-04, MER-06) anatase (MER-03) and manganite (MER-05) minerals. Thus, the mineralogical structure of a potsherds samples has a quite dissimilar composition that could suggest that different source of the raw material utilized for the potsherds production. Clay minerals can be used for re-establishment of previous production conditions. In the present paper TGA, FT-IR and XRD results potsherds are examined and information derived on potsherds technologies regarding raw materials and production conditions is confirmed by SEM observations relating to the extent of vitrification. The temperature at which potsherds were fired differs over range (700-900 ℃) depending on the sort of clay used and the kiln existing. The obtained data point out that the investigated potsherds were made from different raw materials and workshops

Identification and function of human cytomegalovirus microRNAs

microRNAs are an extensive class of non-coding genes that regulate gene expression through post-transcriptional repression. These small RNAs are evolutionarily conserved and are likely to be a basic mechanism of gene regulation present within most eukaryotic organisms. Over 100 viral miRNAs have been identified to date through a combination of bioinformatics and cloning studies. In this review we discuss the use of bioinformatics for the identification of HCMV miRNAs and also for the discovery of potential target transcripts. Such studies will enable us to define the functional role of viral miRNAs and gain a better understanding of viral gene regulation

Ametryn removal by Metarhizium brunneum: Biodegradation pathway proposal and metabolic background revealed

Ametryn is a representative of a class of s-triazine herbicides absorbed by plant roots and leaves and characterized as a photosynthesis inhibitor. It is still in use in some countries in the farming of pineapples, soybean, corn, cotton, sugar cane or bananas; however, due to the adverse effects of s-triazine herbicides on living organisms use of these pesticides in the European Union has been banned. In the current study, we characterized the biodegradation of ametryn (100 mg L-1) by entomopathogenic fungal cosmopolite Metarhizium brunneum. Ametryn significantly inhibited the growth and glucose uptake in fungal cultures. The concentration of the xenobiotic drops to 87.75 mg L-1 at the end of culturing and the biodegradation process leads to formation of four metabolites: 2-hydroxy atrazine, ethyl hydroxylated ametryn, S-demethylated ametryn and deethylametryn. Inhibited growth is reflected in the metabolomics data, where significant differences in concentrations of L-proline, gamma-aminobutyric acid, L-glutamine, 4-hydroxyproline, L-glutamic acid, ornithine and L-arginine were observed in the presence of the xenobiotic when compared to control cultures. The metabolomics data demonstrated that the presence of ametryn in the fungal culture induced oxidative stress and serious disruptions of the carbon and nitrogen metabolism. Our results provide deeper insights into the microorganism strategy for xenobiotic biodegradation which may result in future enhancements to ametryn removal by the tested strain.National Science Center, Poland (Project No. 2015/19/B/NZ9/00167

A Comparative Study between Fixed-size Kernel Logistic Regression and Support Vector Machines Methods for beta-turns Prediction in Protein

Beta-turn is an important element of protein structure; it plays a significant role in protein configuration and function. There are several methods developed for prediction of beta-turns from protein sequences. The best methods are based on Neural Networks (NNs) or Support Vector Machines (SVMs). Although Kernel Logistic Regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems, however it is often not found in beta-turns classification, mainly because it is computationally expensive. Fixed-Size Kernel Logistic Regression (FS-KLR) is a fast and accurate approximate implementation of KLR for large-scale data sets. It uses trust-region Newton’s method for large-scale Logistic Regression (LR) as a basis, to solve the approximate problem, and Nystrom method to approximate the features' matrix. In this paper we used FS-KLR for beta-turns prediction and the results obtained are compared to those obtained with SVM. Secondary structure information and Position Specific Scoring Matrices (PSSMs) are utilized as input features. The performance achieved using FS-KLR is found to be comparable to that of SVM method. FS-KLR has an advantage of yielding probabilistic outputs directly and its extension to the multi-class case is well-defined. In addition its evaluation time is less than that of SVM method. Beta-turn is an important element of protein structure; it plays a significant role in protein configuration and function. There are several methods developed for prediction of beta-turns from protein sequences. The best methods are based on Neural Networks (NNs) or Support Vector Machines (SVMs). Although Kernel Logistic Regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems, however it is often not found in beta-turns classification, mainly because it is computationally expensive. Fixed-Size Kernel Logistic Regression (FS-KLR) is a fast and accurate approximate implementation of KLR for large-scale data sets. It uses trust-region Newton’s method for large-scale Logistic Regression (LR) as a basis, to solve the approximate problem, and Nystrom method to approximate the features' matrix. In this paper we used FS-KLR for beta-turns prediction and the results obtained are compared to those obtained with SVM. Secondary structure information and Position Specific Scoring Matrices (PSSMs) are utilized as input features. The performance achieved using FS-KLR is found to be comparable to that of SVM method. FS-KLR has an advantage of yielding probabilistic outputs directly and its extension to the multi-class case is well-defined. In addition its evaluation time is less than that of SVM method

A cache framework for nomadic clients of web services

This research explores the problems associated with caching of SOAP Web Service request/response pairs, and presents a domain independent framework enabling transparent caching of Web Service requests for mobile clients. The framework intercepts method calls intended for the web service and proceeds by buffering and caching of the outgoing method call and the inbound responses. This enables a mobile application to seamlessly use Web Services by masking fluctuations in network conditions. This framework addresses two main issues, firstly how to enrich the WS standards to enable caching and secondly how to maintain consistency for state dependent Web Service request/response pairs