Sarinder K. Dhillon

Coffee component hydroxyl hydroquinone (HHQ) as a putative ligand for PPAR gamma and implications in breast cancer

BackgroundCoffee contains several compounds that have the potential to influence breast cancer risk and survival. However, epidemiologic data on the relation between coffee compounds and breast cancer survival are sparse and inconsistent.ResultsWe show that coffee component HHQ has significant apoptotic effect on MDA-MB-231 and MCF-7 cells in vitro, and that ROS generation, change in mitochondrial membrane permeability, upregulation of Bax and Caspase-8 as well as down regulation of PGK1 and PKM2 expression may be important apoptosis-inducing mechanisms. The results suggest that PPARγ ligands may serve as potential therapeutic agents for breast cancer therapy. HHQ was also validated as a ligand for PPARγ by docking procedure.ConclusionThis is the first report on the anti-breast cancer (in vitro) activity of HHQ.

Therapeutic implications of targeting energy metabolism in breast cancer.

PPARs are ligand activated transcription factors. PPARγ agonists have been reported as a new and potentially efficacious treatment of inflammation, diabetes, obesity, cancer, AD, and schizophrenia. Since cancer cells show dysregulation of glycolysis they are potentially manageable through changes in metabolic environment. Interestingly, several of the genes involved in maintaining the metabolic environment and the central energy generation pathway are regulated or predicted to be regulated by PPARγ. The use of synthetic PPARγ ligands as drugs and their recent withdrawal/restricted usage highlight the lack of understanding of the molecular basis of these drugs, their off-target effects, and their network. These data further underscores the complexity of nuclear receptor signalling mechanisms. This paper will discuss the function and role of PPARγ in energy metabolism and cancer biology in general and its emergence as a promising therapeutic target in breast cancer.

Biodiversity image retrieval framework for monogeneans

In this paper, we propose a framework for Biodiversity Image Retrieval using Content Based Image Retrieval (CBIR) and structured vocabulary. The monogenean images used in this paper belong to the order Dactylogyridea Bychowsky, 1937. We use illustrations of monogenean haptoral bar diagnostic hard part to demonstrate how textual and content-based information can be integrated in building a better retrieval system. In this approach, an ontology-based image annotation and retrieval is developed to support the CBIR. Using ontology in combination with CBIR reduces the number of images needed in the training set, utilizing the provided user parameters. Efficiency of retrieval of the proposed approach is calculated using the relevance ranking and classification error rate of the retrieved images; and the efficiency of overall retrieval performance.

Novel phytochemical–antibiotic conjugates as multitarget inhibitors of Pseudomononas aeruginosa GyrB/ParE and DHFR

Background There is a dearth of treatment options for community-acquired and nosocomial Pseudomonas infections due to several rapidly emerging multidrug resistant phenotypes, which show resistance even to combination therapy. As an alternative, developing selective promiscuous hybrid compounds for simultaneous modulation of multiple targets is highly appreciated because it is difficult for the pathogen to develop resistance when an inhibitor has activity against multiple targets. Methods In line with our previous work on phytochemical–antibiotic combination assays and knowledge-based methods, using a fragment combination approach we here report a novel drug design strategy of conjugating synergistic phytochemical–antibiotic combinations into a single hybrid entity for multi-inhibition of P. aeruginosa DNA gyrase subunit B (GyrB)/topoisomerase IV subunit B (ParE) and dihydrofolate reductase (DHFR) enzymes. The designed conjugates were evaluated for their multitarget specificity using various computational methods including docking and dynamic simulations, drug-likeness using molecular properties calculations, and pharmacophoric features by stereoelectronic property predictions. Results Evaluation of the designed hybrid compounds based on their physicochemical properties has indicated that they are promising drug candidates with drug-like pharmacotherapeutic profiles. In addition, the stereoelectronic properties such as HOMO (highest occupied molecular orbital), LUMO (lowest unoccupied molecular orbital), and MEP (molecular electrostatic potential) maps calculated by quantum chemical methods gave a good correlation with the common pharmacophoric features required for multitarget inhibition. Furthermore, docking and dynamics simulations revealed that the designed compounds have favorable binding affinity and stability in both the ATP-binding sites of GyrB/ParE and the folate-binding site of DHFR, by forming strong hydrogen bonds and hydrophobic interactions with key active site residues. Conclusion This new design concept of hybrid “phyto-drug” scaffolds, and their simultaneous perturbation of well-established antibacterial targets from two unrelated pathways, appears to be very promising and could serve as a prospective lead in multitarget drug discovery.

Semantic representation of monogenean haptoral Bar image annotation

BackgroundDigitised monogenean images are usually stored in file system directories in an unstructured manner. In this paper we propose a semantic representation of these images in the form of a Monogenean Haptoral Bar Image (MHBI) ontology, which are annotated with taxonomic classification, diagnostic hard part and image properties. The data we used are basically of the monogenean species found in fish, thus we built a simple Fish ontology to demonstrate how the host (fish) ontology can be linked to the MHBI ontology. This will enable linking of information from the monogenean ontology to the host species found in the fish ontology without changing the underlying schema for either of the ontologies.ResultsIn this paper, we utilized the Taxonomic Data Working Group Life Sciences Identifier (TDWG LSID) vocabulary to represent our data and defined a new vocabulary which is specific for annotating monogenean haptoral bar images to develop the MHBI ontology and a merged MHBI-Fish ontologies. These ontologies are successfully evaluated using five criteria which are clarity, coherence, extendibility, ontology commitment and encoding bias.ConclusionsIn this paper, we show that unstructured data can be represented in a structured form using semantics. In the process, we have come up with a new vocabulary for annotating the monogenean images with textual information. The proposed monogenean image ontology will form the basis of a monogenean knowledge base to assist researchers in retrieving information for their analysis.

Fully-automated identification of fish species based on otolith contour: using short-time Fourier transform and discriminant analysis (STFT-DA)

Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.

Automated otolith image classification with multiple views: an evaluation on Sciaenidae

Combined multiple 2D views (proximal, anterior and ventral aspects) of the sagittal otolith are proposed here as a method to capture shape information for fish classification. Classification performance of single view compared with combined 2D views show improved classification accuracy of the latter, for nine species of Sciaenidae. The effects of shape description methods (shape indices, Procrustes analysis and elliptical Fourier analysis) on classification performance were evaluated. Procrustes analysis and elliptical Fourier analysis perform better than shape indices when single view is considered, but all perform equally well with combined views. A generic content-based image retrieval (CBIR) system that ranks dissimilarity (Procrustes distance) of otolith images was built to search query images without the need for detailed information of side (left or right), aspect (proximal or distal) and direction (positive or negative) of the otolith. Methods for the development of this automated classification system are discussed.

HPC+Azure environment for bioinformatics applications

In the past 20 years, huge flow of data, produced by the nonstop rise of computational power has led to a paradigm shift in large scale data processing mechanisms and computing architecture. As a result, human and computational resources are needed to aid data-intensive operations which will cause the high degree of storage and management expenses. An organized and standard approach is important to manage these issues with an architecture that able to scale into the predictable future. Instead of the fastest and largest single computer solution, economical clusters of computers can better manage and process all data. Most of the high-performance computing (HPC) systems need a huge amount of processing power and Windows Azure is capable of providing a huge quantity of processing power on demand. As the Windows HPC server and Windows Azure combine, the cloud and on-premises world are now able to function together. In this paper we explore a HPC+Azure implementation model and demonstrate by running a genome sequence assembly application.

Advances in Biomedical Infrastructure 2013

Current Biomedical Databases are independently administered in geographically distinct locations, lending them almost ideally to adoption of intelligent data management approaches. This book focuses on research issues, problems and opportunities in Biomedical Data Infrastructure identifying new issues and directions for future research in Biomedical Data and Information Retrieval, Semantics in Biomedicine, and Biomedical Data Modeling and Analysis. The book will be a useful guide for researchers, practitioners, and graduate-level students interested in learning state-of-the-art development in biomedical data management.

Benchmarking Large Scale Cloud Computing in Asia Pacific

Cloud services allows organizations to run their applications faster, under better manageability and less maintenance so that they can focus on their core business. In this paper we are benchmarking various public clouds (Microsoft Azure, Amazon EC2 and the Australian National eResearch Collaboration Tools and Resources Cloud (NeCTAR)) that are commonly used by academic organizations in Asia Pacific to gauge their performances using variety of tests.