885 research outputs found

    SN algorithm: analysis of temporal clinical data for mining periodic patterns and impending augury

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    EHR (Electronic Health Record) system has led to development of specialized form of clinical databases which enable storage of information in temporal prospective. It has been a big challenge for mining this form of clinical data considering varied temporal points. This study proposes a conjoined solution to analyze the clinical parameters akin to a disease. We have used “association rule mining algorithm” to discover association rules among clinical parameters that can be augmented with the disease. Furthermore, we have proposed a new algorithm, SN algorithm, to map clinical parameters along with a disease state at various temporal points

    Design of dimensional model for clinical data storage and analysis

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    Current research in the field of Life and Medical Sciences is generating chunk of data on daily basis. It has thus become a necessity to find solutions for efficient storage of this data, trying to correlate and extract knowledge from it. Clinical data generated in Hospitals, Clinics & Diagnostics centers is falling under a similar paradigm. Patient’s records in various hospitals are increasing at an exponential rate, thus adding to the problem of data management and storage. Major problem being faced corresponding to storage, is the varied dimensionality of the data, ranging from images to numerical form. Therefore there is a need for development of efficient data model which can handle this multi-dimensionality data issue and store the data with historical aspect. For the stated problem lying in façade of clinical informatics we propose a clinical dimensional model design which can be used for development of a clinical data mart. The model has been designed keeping in consideration temporal storage of patient's data with respect to all possible clinical parameters which can include both textual and image based data. Availability of said data for each patient can be then used for application of data mining techniques for finding the correlation of all the parameters at the level of individual and population

    Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor

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    Healthcare sector is generating a large amount of information corresponding to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for the diagnosis & treatment of disease from the clinical dataset is therefore increasingly becoming necessary. Aim of this study was to assess the applicability of knowledge discovery in brain tumor data warehouse, applying data mining techniques for investigation of clinical parameters that can be associated with occurrence of brain tumor. In this study, a brain tumor warehouse was developed comprising of clinical data for 550 patients. Apriori association rule algorithm was applied to discover associative rules among the clinical parameters. The rules discovered in the study suggests - high values of Creatinine, Blood Urea Nitrogen (BUN), SGOT & SGPT to be directly associated with tumor occurrence for patients in the primary stage with atleast 85% confidence and more than 50% support. A normalized regression model is proposed based on these parameters along with Haemoglobin content, Alkaline Phosphatase and Serum Bilirubin for prediction of occurrence of STATE (brain tumor) as 0 (absent) or 1 (present). The results indicate that the methodology followed will be of good value for the diagnostic procedure of brain tumor, especially when large data volumes are involved and screening based on discovered parameters would allow clinicians to detect tumors at an early stage of development

    Mode of interaction of calcium oxalate crystal with human phosphate cytidylyltransferase 1: a novel inhibitor purified from human renal stone matrix

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    Nephrolithiasis is a common clinical disorder, and calcium oxalate (CaOx) is the principal crystalline component in approximately 75% of all renal stones. It is widely believed that proteins act as inhibitors of crystal growth and aggregation. Acidic amino acids present in these proteins play a significant role in the inhibition process. In this study, interaction of cal-cium oxalate with human phosphate cytidylyltrans-ferase 1(CCT), a novel calcium oxalate crystal growth inhibitor purified from human renal stone matrix has been elucidated in silico and involvement of acidic amino acids in the same. As only sequence of CCT is available, henceforth its 3-D structure was modeled via Homology modeling using Prime module of Schrodinger package. Molecular dynamic simulation of modeled protein with solvation was done by mac-romodel (Schrodinger). The quality of modeled pro-tein was validated by JCSG protein structure valida-tion (PROCHECK & ERRAT) server. To analyze the interaction of modeled protein CCT with calcium oxalate along with role played by acidic amino acids, ‘Docking simulation’ was done using MOE–Dock. Interaction between calcium oxalate and CCT was also studied by substituting acidic amino acid in the active sites of the protein with neutral and positively charged amino acids. The in silico analysis showed the bond formation between the acidic amino acids and calcium atom, which was further substantiated when substitution of these acidic amino acids with alanine, glycine, lysine, arginine and histidine com-pletely diminished the interaction with calcium ox-alate

    Plasmacytoma of Bronchus Treated by Radical Radiotherapy-A Rare Case with Four and a Half Years Follow up

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    AbstractPlasmacytoma of the bronchus is a very rare plasma cell neoplasm affecting the bronchus. Here we report a case of plasmacytoma of the bronchus treated by radical radiotherapy in July 2002. The tumor responded very well to treatment and showed a slow but sustained regression in the size over two years. Presently, he has completed four and a half years of follow-up and is free of disease

    Chemical composition and larvicidal activities of the essential oil of Zanthoxylum armatum DC (Rutaceae) against three mosquito vectors

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    Background & objectives: In view of the recently increased interest in developing plant origininsecticides as an alternative to chemical insecticide, this study was undertaken to assess the larvicidalpotential of the essential oil from the seeds of Zanthoxylum armatum DC [syn. Z. alatum Roxb](Rutaceae) against three medically important species of mosquito vectors, Aedes aegypti, Anophelesstephensi and Culex quinquefasciatus.Methods: Essential oil was hydro distilled in the laboratory from the seeds obtained from the marketand the chemical constituents of the oil were determined using GC/GC-MS. Bioefficacy of theessential oil was evaluated under laboratory conditions using III instar mosquito larvae.Results: Among the three mosquito species tested, Cx. quinquefasciatus was the most sensitive(LC50 = 49 ppm) followed by Ae. aegypti (LC50 = 54 ppm) and An. stephensi (LC50 = 58 ppm). GCMSanalysis of the oil revealed at least 28 compounds, consisting mainly of oxygenated monoterpenes(75%) and monoterpenes (22%). Linalool though constituted a major part (57%), failed to produceany appreciable mortality when tested alone.Interpretation & conclusion: From the results it can be concluded that the larvae of the three mosquitospecies were susceptible to the essential oil composition. Such findings would be useful in promotingresearch aiming at the development of new agent for mosquito control based on bioactive chemicalcompounds from indigenous plant sources as an alternative to chemical larvicides

    Tomographic Quantum Cryptography

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    We present a protocol for quantum cryptography in which the data obtained for mismatched bases are used in full for the purpose of quantum state tomography. Eavesdropping on the quantum channel is seriously impeded by requiring that the outcome of the tomography is consistent with unbiased noise in the channel. We study the incoherent eavesdropping attacks that are still permissible and establish under which conditions a secure cryptographic key can be generated. The whole analysis is carried out for channels that transmit quantum systems of any finite dimension.Comment: REVTeX4, 9 pages, 3 figures, 1 tabl

    Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

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    Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations.Peer reviewe

    ϒ production in p–Pb collisions at √sNN=8.16 TeV

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    ϒ production in p–Pb interactions is studied at the centre-of-mass energy per nucleon–nucleon collision √sNN = 8.16 TeV with the ALICE detector at the CERN LHC. The measurement is performed reconstructing bottomonium resonances via their dimuon decay channel, in the centre-of-mass rapidity intervals 2.03 < ycms < 3.53 and −4.46 < ycms < −2.96, down to zero transverse momentum. In this work, results on the ϒ(1S) production cross section as a function of rapidity and transverse momentum are presented. The corresponding nuclear modification factor shows a suppression of the ϒ(1S) yields with respect to pp collisions, both at forward and backward rapidity. This suppression is stronger in the low transverse momentum region and shows no significant dependence on the centrality of the interactions. Furthermore, the ϒ(2S) nuclear modification factor is evaluated, suggesting a suppression similar to that of the ϒ(1S). A first measurement of the ϒ(3S) has also been performed. Finally, results are compared with previous ALICE measurements in p–Pb collisions at √sNN = 5.02 TeV and with theoretical calculations.publishedVersio

    (Anti-)deuteron production in pp collisions at 1as=13TeV

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    The study of (anti-)deuteron production in pp collisions has proven to be a powerful tool to investigate the formation mechanism of loosely bound states in high-energy hadronic collisions. In this paper the production of (anti-)deuterons is studied as a function of the charged particle multiplicity in inelastic pp collisions at s=13 TeV using the ALICE experiment. Thanks to the large number of accumulated minimum bias events, it has been possible to measure (anti-)deuteron production in pp collisions up to the same charged particle multiplicity (d Nch/ d \u3b7 3c 26) as measured in p\u2013Pb collisions at similar centre-of-mass energies. Within the uncertainties, the deuteron yield in pp collisions resembles the one in p\u2013Pb interactions, suggesting a common formation mechanism behind the production of light nuclei in hadronic interactions. In this context the measurements are compared with the expectations of coalescence and statistical hadronisation models (SHM)
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