A clinical study on the effect of Bilvapatra Ghana in the management of Madhumeha with respect to Type II Diabetes Mellitus

In the course of evolution of human life, man has struggled a lot to obtain the best of living standards. Among all necessities, health care is given the best attention because, only healthy individual can enjoy the benefits of beauties of the nature. Positive health doesn’t mean only physical but physiological, mental, social and spiritual wellbeing also. If the principles of Ayurveda are studied in modern scientific way, both in respect of its approach to disease and therapy, especially in relation to Madhumeha. Diabetes results when the body makes too little insulin or does not use insulin properly, allowing sugar levels to build up in the blood stream. The free radicals are one of the important etiological factors for the development of diabetes and its complications. Antioxidants capable of protecting against the damage induced by free radicals and it also have a role in reducing the effects of diabetes. There are many herbal medicinal plants like Babul, Bilva, Davana, Neem, Jambu etc. with proven antidiabetic and related beneficial effects. Bilvapatra is effective in the treatment for diabetes by reducing blood glucose level. So in present study Bilvapatra Ghana is used in the management of Madhumeha

Lepa Kalpana - A Review

Ayurveda the science of life is the most ancient medical knowledge in the world. Metals and minerals are in frequent use in Indian system of medicine since long back without any untowards effect. In Bhaishjya Kalpana application of herbal drug externally known as Lepa. Lepa preparation are the topical medicaments meant for external application to the skin or mucosal membrane. The topical preparation include Lepa, Upanaha, Malhara etc. out of many Bahya Kalpana, Lepa Kalpana has due importance in Ayurvedic system of medicine. Lepa Kalpana are used in different conditions like inflammation, wound healing, wound cleaning and many more uses

Design and Development of Network Monitoring and Controlling Tool for Department of Computer Studies CSIBER

In most of the organizations it is highly desirable to perform different tasks on different machines based on their configuration and permissions assigned to the machines for execution of different tasks. This can be achieved by performing a user-machine mapping by stating clearing the list of tasks that can be performed by a particular user on a particular machine. This kind of discipline further enables traffic control, prevents internal DOS (Denial Of Service) attacks for legitimate users and helps in fair resource sharing. The intent of this research is to enable the end user performing only the tasks permissible to him/her. In this paper we have developed a network monitor and control tool for monitoring the tasks on a medium sized local area network. To facilitate this, task permissions are assigned to different machines which is stored in XML configuration file which is then parsed using JDOM (Java Document Object Model) Parser. The configuration file contains the details such as machine name, and the list of tasks not permitted on that machine. The list of machines and the list of tasks denied on that machine is configurable by an end user. A background thread will continuously monitor the execution of illegal task on a machine and will abort and report the same in a database. This also facilitates the control of network traffic thereby improving the network performance by aborting illegal tasks. Network monitoring tool is tested for local area network of department of computer studies at SIBER by setting up specific monitors to check status and to carry out specific operations. The tool developed by us requires a small amount of system resources, and it is an open source tool. Presently, the tool generates a report comprising of a list of illegal tasks in a specified time period, which enables network administrator to take corrective measures for the smooth operation of the network. DOI: 10.17762/ijritcc2321-8169.15037

Sonification and Music as Support to the Communication of Alcohol-Related Health Risks to Young People : Study design and results

Excessive consumption of alcohol has been recognised as a significant risk factor impacting the health of young people. Effective communication of such risk is considered to be one key step to improve behaviour. We evaluated an innovative multimedia intervention that utilised audio (sonification—using sound to display data—and music) and interactivity to support the visual communication of alcohol health risk data. A 3-arm pilot experiment was undertaken. The trial measures included health knowledge, alcohol risk perception and user experience of the intervention. Ninety-six subjects participated in the experiment. At 1 month follow-up, alcohol knowledge and alcohol risk perception improved significantly in the whole sample. However, there was no difference between the intervention groups that experienced (1) visual presentation with interactivity (VI-Exp group) and, (2) visual presentation with audio (sonification and music) and interactivity (VAI-Exp group), when compared to the control group which experienced a (3) visual only presentation (V-Cont group). Participants reported enjoying the presentations and found them educational. The majority of participants indicated that the audio, music and sonification helped to convey the information well, and, although a larger sample size is needed to fully establish the effectiveness of the different interventions, this study provides a useful model for future similar studies

Semaphorin 3A Suppresses Tumor Growth and Metastasis in Mice Melanoma Model

<div><h3>Background</h3><p>Recent understanding on cancer therapy indicated that targeting metastatic signature or angiogenic switch could be a promising and rational approach to combat cancer. Advancement in cancer research has demonstrated the potential role of various tumor suppressor proteins in inhibition of cancer progression. Current studies have shown that axonal sprouting inhibitor, semaphorin 3A (Sema 3A) acts as a potent suppressor of tumor angiogenesis in various cancer models. However, the function of Sema 3A in regulation of melanoma progression is not well studied, and yet to be the subject of intense investigation.</p> <h3>Methodology/Principal Findings</h3><p>In this study, using multiple <em>in vitro</em> and <em>in vivo</em> approaches we have demonstrated that Sema 3A acts as a potent tumor suppressor <em>in vitro</em> and <em>in vivo</em> mice (C57BL/6) models. Mouse melanoma (B16F10) cells overexpressed with Sema 3A resulted in significant inhibition of cell motility, invasiveness and proliferation as well as suppression of <em>in vivo</em> tumor growth, angiogenesis and metastasis in mice models. Moreover, we have observed that Sema 3A overexpressed melanoma clone showed increased sensitivity towards curcumin and Dacarbazine, anti-cancer agents.</p> <h3>Conclusions</h3><p>Our results demonstrate, at least in part, the functional approach underlying Sema 3A mediated inhibition of tumorigenesis and angiogenesis and a clear understanding of such a process may facilitate the development of novel therapeutic strategy for the treatment of cancer.</p> </div

An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology

<p>Abstract</p> <p>Background</p> <p>Semantic similarity measures are useful to assess the physiological relevance of protein-protein interactions (PPIs). They quantify similarity between proteins based on their function using annotation systems like the Gene Ontology (GO). Proteins that interact in the cell are likely to be in similar locations or involved in similar biological processes compared to proteins that do not interact. Thus the more semantically similar the gene function annotations are among the interacting proteins, more likely the interaction is physiologically relevant. However, most semantic similarity measures used for PPI confidence assessment do not consider the unequal depth of term hierarchies in different classes of cellular location, molecular function, and biological process ontologies of GO and thus may over-or under-estimate similarity.</p> <p>Results</p> <p>We describe an improved algorithm, Topological Clustering Semantic Similarity (TCSS), to compute semantic similarity between GO terms annotated to proteins in interaction datasets. Our algorithm, considers unequal depth of biological knowledge representation in different branches of the GO graph. The central idea is to divide the GO graph into sub-graphs and score PPIs higher if participating proteins belong to the same sub-graph as compared to if they belong to different sub-graphs.</p> <p>Conclusions</p> <p>The TCSS algorithm performs better than other semantic similarity measurement techniques that we evaluated in terms of their performance on distinguishing true from false protein interactions, and correlation with gene expression and protein families. We show an average improvement of 4.6 times the <it>F</it>₁score over Resnik, the next best method, on our <it>Saccharomyces cerevisiae </it>PPI dataset and 2 times on our <it>Homo sapiens </it>PPI dataset using cellular component, biological process and molecular function GO annotations.</p

Continuous low-dose cyclophosphamide and methotrexate combined with celecoxib for patients with advanced cancer

BACKGROUND: Combined therapy of metronomic cyclophosphamide, methotrexate and high-dose celecoxib targeting angiogenesis was used in a phase II trial. METHODS: Patients with advanced cancer received oral cyclophosphamide 50 mg o.d., celecoxib 400 mg b.d. and methotrexate 2.5 mg b.d. for two consecutive days each week. Response was determined every 8 weeks; toxicity was evaluated according to CTC version 2.0. Plasma markers of inflammation, coagulation and angiogenesis were measured. RESULTS: Sixty-seven of 69 patients were evaluable for response. Twenty-three patients had stable disease (SD) after 8 weeks, but there were no objective responses to therapy. Median time to progression was 57 days. There was a low incidence of toxicities. Among plasma markers, levels of tissue factor were higher in the SD group of patients at baseline, and levels of both angiopoietin-1 and matrix metalloproteinase-9 increased in the progressive disease group only. There were no changes in other plasma markers. CONCLUSION: This metronomic approach has negligible activity in advanced cancer albeit with minimal toxicity. Analysis of plasma markers indicates minimal effects on endothelium in this trial. These data for this particular regimen do not support basic tenets of metronomic chemotherapy, such as the ability to overcome resistant tumours by targeting the endothelium

Bayesian statistical modelling of human protein interaction network incorporating protein disorder information

<p>Abstract</p> <p>Background</p> <p>We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive approaches. The model is capable to capture generic and structural properties of a network as emergent from local interdependencies and uses a limited number of parameters. Here, we consider one global parameter capturing the density of edges in the network, and local parameters representing each node's contribution to the formation of edges in the network. The modelling suggests a novel definition of important nodes in the network, namely <it>social</it>, as revealed based on the local <it>sociality </it>parameters of the model. Moreover, the sociality parameters help to reveal organizational principles of the network. An inherent advantage of our approach is the possibility of hypotheses testing: <it>a priori </it>knowledge about biological properties of the nodes can be incorporated into the statistical model to investigate its influence on the structure of the network.</p> <p>Results</p> <p>We applied the statistical modelling to the human protein interaction network obtained with Y2H experiments. Bayesian approach for the estimation of the parameters was employed. We deduced <it>social </it>proteins, essential for the formation of the network, while incorporating into the model information on protein disorder. <it>Intrinsically disordered </it>are proteins which lack a well-defined three-dimensional structure under physiological conditions. We predicted the fold group (ordered or disordered) of proteins in the network from their primary sequences. The network analysis indicated that protein disorder has a positive effect on the connectivity of proteins in the network, but do not fully explains the interactivity.</p> <p>Conclusions</p> <p>The approach opens a perspective to study effects of biological properties of individual entities on the structure of biological networks.</p

Modified cantilever arrays improve sensitivity and reproducibility of nanomechanical sensing in living cells

Mechanical signaling involved in molecular interactions lies at the heart of materials science and biological systems, but the mechanisms involved are poorly understood. Here we use nanomechanical sensors and intact human cells to provide unique insights into the signaling pathways of connectivity networks, which deliver the ability to probe cells to produce biologically relevant, quantifiable and reproducible signals. We quantify the mechanical signals from malignant cancer cells, with 10 cells per ml in 1000-fold excess of non-neoplastic human epithelial cells. Moreover, we demonstrate that a direct link between cells and molecules creates a continuous connectivity which acts like a percolating network to propagate mechanical forces over both short and long length-scales. The findings provide mechanistic insights into how cancer cells interact with one another and with their microenvironments, enabling them to invade the surrounding tissues. Further, with this system it is possible to understand how cancer clusters are able to co-ordinate their migration through narrow blood capillaries