Drug utilisation pattern in dermatology outpatient department at a tertiary care hospital

Background: Skin is the part of integumentary system that constitutes the largest organ of human body and thus it is exposed to injury by various extrinsic and intrinsic factors. The skin disorders have serious detrimental effect on quality of life of the general population. The present study was planned to define the prescription pattern in terms of rationality, drug interactions and financial burden of disease to the individual. Also, in the identification of problems related to drug use such as poly-pharmacy and drug-drug interaction.Methods: The present study was conducted in the male and female out-patient Department of Dermatology at a Tertiary Care Hospital in Hyderabad, Telangana over a period of two months. Prescriptions of 400 patients were analyzed i.e. 200 each were taken from the male and female OPD patients. An observational and cross-sectional study design was adopted for this study.Results: Prescriptions of 400 patients were analyzed. The average number of drugs per prescription was 3.73 in male OPD and 3.59 in female OPD. The percentage of generic drugs prescribed was 84.13% in male OPD and 77.3% in female OPD, drugs prescribed by brand name was 15.82% in male OPD and 22.7% in female OPD. Antihistamines were the most commonly prescribed drugs followed by antibacterial in female OPD and antifungals in male OPD.Conclusions: Prescription of maximum drugs was by their generic name and was dispensed free of cost to the patients from the hospital pharmacy. Almost all the drugs prescribed as oral formulation were present in the NLEM, India 2011. Whereas some topical formulations prescribed are not present in the NLEM. Therefore, were prescribed by trade name. Regular educational interventions like sensitization on pharmacovigilance may further promote rational prescribing

A Neural Network Simulator for the Connnection Machine

In this paper we describe the design, development, and performance of a neural network simulator for the Connection Machine (CM)3. The design of the simulator is based on the Rochester Connectionist Simulator(RCS). RCS is a simulator for connectionist networks developed at the University of Rochester. The CM simulator can be used as a stand-alone system or as a high-performance parallel back-end to RCS. In the latter case, once the network has been built by RCS, the high-performance parallel back-end system constructs an equivalent network on the CM processor array and executes it. The CM simulator facilitates the exploitation of the massive parallelism inherent in connectionist networks. It can also enable substantial reduction in the training times of connectionist networks

A Novel System for the Efficient Generation of Antibodies Following Immunization of Unique Knockout Mouse Strains

International audienceBACKGROUND: We wished to develop alternate production strategies to generate antibodies against traditionally problematic antigens. As a model we chose butyrylcholinesterase (BChE), involved in termination of cholinergic signaling, and widely considered as a poor immunogen. METHODOLOGY/PRINCIPAL FINDINGS: Jettisoning traditional laborious in silico searching methods to define putative epitopes, we simply immunized available BChE knock-out mice with full-length recombinant BChE protein (having been produced for crystallographic analysis). Immunization with BChE, in practically any form (recombinant human or mouse BChE, BChE purified from human serum, native or denatured), resulted in strong immune responses. Native BChE produced antibodies that favored ELISA and immunostaining detection. Denatured and reduced BChE were more selective for antibodies specific in Western blots. Two especially sensitive monoclonal antibodies were found capable of detecting 0.25 ng of BChE within one min by ELISA. One is specific for human BChE; the other cross-reacts with mouse and rat BChE. Immunization of wild-type mice served as negative controls. CONCLUSIONS/SIGNIFICANCE: We examined a simple, fast, and highly efficient strategy to produce antibodies by mining two expanding databases: namely those of knock-out mice and 3D crystallographic protein-structure analysis. We conclude that the immunization of knock-out mice should be a strategy of choice for antibody production

The CAP cancer protocols – a case study of caCORE based data standards implementation to integrate with the Cancer Biomedical Informatics Grid

BACKGROUND: The Cancer Biomedical Informatics Grid (caBIG™) is a network of individuals and institutions, creating a world wide web of cancer research. An important aspect of this informatics effort is the development of consistent practices for data standards development, using a multi-tier approach that facilitates semantic interoperability of systems. The semantic tiers include (1) information models, (2) common data elements, and (3) controlled terminologies and ontologies. The College of American Pathologists (CAP) cancer protocols and checklists are an important reporting standard in pathology, for which no complete electronic data standard is currently available. METHODS: In this manuscript, we provide a case study of Cancer Common Ontologic Representation Environment (caCORE) data standard implementation of the CAP cancer protocols and checklists model – an existing and complex paper based standard. We illustrate the basic principles, goals and methodology for developing caBIG™ models. RESULTS: Using this example, we describe the process required to develop the model, the technologies and data standards on which the process and models are based, and the results of the modeling effort. We address difficulties we encountered and modifications to caCORE that will address these problems. In addition, we describe four ongoing development projects that will use the emerging CAP data standards to achieve integration of tissue banking and laboratory information systems. CONCLUSION: The CAP cancer checklists can be used as the basis for an electronic data standard in pathology using the caBIG™ semantic modeling methodology

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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withdrawn 2017 hrs ehra ecas aphrs solaece expert consensus statement on catheter and surgical ablation of atrial fibrillation

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Locality-Conscious Load Balancing: Connectionist Architectural Support

Traditionally, in distributed memory architectures, locality maintenance and load balancing are seen as user level activities involving compiler and runtime system support in software. Such software solutions require an explicit phase of execution, requiring the application to suspend its activities. This paper presents the first (to our knowledge) architecture-level scheme for extracting locality concurrent with the application execution. An artificial neural network coprocessor is used for dynamically monitoring processor reference streams to learn temporally emergent utilities of data elements in ongoing local computations. This facilitates use of kernel-level load balancing schemes thus, easing the user programming burden. The kernel-level scheme migrates data to processor memories evincing higher utilities during load-balancing. The performance of an execution-driven simulation evaluating the proposed coprocessor is presented for three applications. The applications chosen represent the range of load and locality fluxes encounted in parallel programs, with (a) static locality and load characteristics, (b) slowly varying localities for fixed datasetsizes and (c) rapidly fluctuating localities among slowly varying datasetsizes. The performance results indicate the viability and success of the coprocessor in concurrently extracting locality for use in load balancing activities