Quantum Dot Based Nano-Biosensors for Detection of Circulating Cell Free miRNAs in Lung Carcinogenesis: From Biology to Clinical Translation

Lung cancer is the most frequently occurring malignancy and the leading cause of cancer-related death for men in our country. The only recommended screening method is clinic based low-dose computed tomography (also called a low-dose CT scan, or LDCT). However, the effect of LDCT on overall mortality observed in lung cancer patients is not statistically significant. Over-diagnosis, excessive cost, risks associated with radiation exposure, false positive results and delay in the commencement of the treatment procedure questions the use of LDCT as a reliable technique for population-based screening. Therefore, identification of minimal-invasive biomarkers able to detect malignancies at an early stage might be useful to reduce the disease burden. Circulating nucleic acids are emerging as important source of information for several chronic pathologies including lung cancer. Of these, circulating cell free miRNAs are reported to be closely associated with the clinical outcome of lung cancer patients. Smaller size, sequence homology between species, low concentration and stability are some of the major challenges involved in characterization and specific detection of miRNAs. To circumvent these problems, synthesis of a quantum dot based nano-biosensor might assist in sensitive, specific and cost-effective detection of differentially regulated miRNAs. The wide excitation and narrow emission spectra of these nanoparticles result in excellent fluorescent quantum yields with a broader color spectrum which make them ideal bio-entities for fluorescence resonance energy transfer (FRET) based detection for sequential or simultaneous study of multiple targets. In addition, photo-resistance and higher stability of these nanoparticles allows extensive exposure and offer state-of-the art sensitivity for miRNA targeting. A major obstacle for integrating QDs into clinical application is the QD-associated toxicity. However, the use of non-toxic shells along with surface modification not only overcomes the toxicity issues, but also increases the ability of QDs to quickly detect circulating cell free miRNAs in a non-invasive mode. The present review illustrates the importance of circulating miRNAs in lung cancer diagnosis and highlights the translational prospects of developing QD-based nano-biosensor for rapid early disease detection

Energy Consumption in Data Analysis for On-board and Distributed Applications

Energy consumption is an important issue in the growing number of data mining and machine learning applications for battery-powered embedded and mobile devices. It plays a critical role in determining the capabilities of a broad range of applications such as space probes with onboard scientific missions, PDA-based monitoring of remote data streams, event detection in sensor networks comprised of battery-powered data sensors and light-weight data processing nodes

Distributed Data Mining and Agents

Abstract. Multi-Agent Systems (MAS) offer an architecture for distributed problem solving. Distributed Data Mining (DDM) algorithms focus on one class of such distributed problem solving tasks—analysis and modeling of distributed data. This paper offers a perspective on DDM algorithms in the context of multiagents systems. It discusses broadly the connection between DDM and MAS. It provides a high-level survey of DDM, then focuses on distributed clustering algorithms and some potential applications in multi-agent-based problem solving scenarios. It reviews algorithms for distributed clustering, including privacypreserving ones. It describes challenges for clustering in sensor-network environments, potential shortcomings of the current algorithms, and future work accordingly. It also discusses confidentiality (privacy preservation) and presents a new algorithm for privacy-preserving density-based clustering

An overview of Indian research in schizophrenia

The Indian Journal of Psychiatry published three articles in its first issue way back in 1958. Since then, it has steadily published more than 200 papers on one or the other aspect of schizophrenia. From rudimentary research methodology and descriptive approach, schizophrenia research, as published in the Journal, seems to have come of age with more and more sophisticated research designs and methodologies. Our ardent researchers have made significant contributions in the understanding of this riddle called schizophrenia. Notable contributions have been made in the field of epidemiology, course and outcomes and phenomenology of this disorder. However, research in psycho-social rehabilitation of schizophrenia and related areas is sparse and sporadic. The need to conduct research that impacts health policies and planning of services for this disorder is evident and our researchers would do well to provide impetus in these areas