46 research outputs found

    Databases and Algorithms in Allergen Informatics

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    Allergic diseases are considered as one of the major health problems worldwide due to their increasing prevalence. Advancements in genomic, proteomic, and analytical techniques have resulted in considerable progress in the field of allergology, which has led to accumulation of huge amount of data. Allergen bioinformatics comprises allergen-related data resources and computational methods/tools, which deal with an efficient archival, management, and analysis of allergological data. Significant work has been done in the area of allergen bioinformatics that has proven pivotal for the development and progress of this field. In this chapter, we describe the current status of databases and algorithms, encompassing the field of allergen bioinformatics by examining work carried out thus far with respect to features such as allergens and allergenicity, allergen databases, algorithms/tools for allergen/allergenicity prediction, allergen epitope prediction, and allergenic cross-reactivity assessment. This chapter illustrates concepts and algorithms in allergen bioinformatics, as well as it outlines the key areas for potential development in allergology field

    LIPOPREDICT: Bacterial lipoprotein prediction server

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    Bacterial lipoproteins have many important functions owing to their essential nature and roles in pathogenesis and represent a class of possible vaccine candidates. The prediction of bacterial lipoproteins from sequence is thus an important task for computational vaccinology. A Support Vector Machines (SVM) based module for predicting bacterial lipoproteins, LIPOPREDICT, has been developed. The best performing sequence model were generated using selected dipeptide composition, which gave 97% accuracy of prediction. The results obtained were compared very well with those of previously developed methods

    Synthesis of quinazolinones derivatives an antiproliferative agent against human lung carcinoma cells

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    2,3‐Dihydroquinazolin‐4(1H)‐one derivatives (3a-p) were synthesized in excellent yields. These compounds were screened for antiproliferative activity against A549 cells and were found as potent cytotoxicity. Compounds A4, A8, A10 found to be more promising antiproliferative against the lung carcinoma A549 cells. IC50 values for compounds A4, A8 and A10 were found to be 8.6, 8.9 and 8.1 ÎŒg/L against A549 cells, respectively

    Object Detection for Image Captioning

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    Generation of description of pictures victimization tongue sentences is gaining a lot of quality of late. It's a difficult task, because it needs not solely understanding a picture, however to translate that visual data into sentence description. So as to caption a picture, we tend to 1st have to be compelled to discover the objects within the image. Object detection has become one amongst the international widespread analysis fields. 1st the paper introduced the distinction between deep learning and machine learning for object detection. Second the techniques for object detection are surveyed. Third it mentioned techniques for object classification

    Designing a TiO2-MoO3-BMIMBr nanocomposite by a solvohydrothermal method using an ionic liquid aqueous mixture: an ultra high sensitive acetaminophen sensor

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    This study shows a simplistic, efficient procedure to synthesize TiO2-MoO3-BMIMBr nanocomposites. Powder X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy have all been used to completely analyse the materials. The detection of acetaminophen (AC) has been examined at a modified glassy carbon electrode with TiO2-MoO3-BMIMBr nanocomposites. Moreover, the electrochemical behavior of the nanocomposite modified electrode has been studied by cyclic voltammetry (CV), differential pulse voltammetry (DPV), chronoamperometry and electrochemical impedance spectroscopy (EIS). The linear response of AC was observed in the range 8.26–124.03 nM. The sensitivity and detection limits (S/N = 3) were found to be 1.16 ÎŒA L mol−1 cm−2 and 11.54 nM by CV and 24 ÎŒA L mol−1 cm−2 and 8.16 nM by DPV respectively

    Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

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    IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

    Kiran L. Kadam

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    This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Available electronically at http://www.doe.gov/bridge Available for a processing fee to U.S. Department of Energy and its contractors, in paper, from: U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, TN 37831-0062 phone: 865.576.8401 fax: 865.576.5728 email: [email protected] Available for sale to the public, in paper, from: U.S. Department of Commerce National Technical Information Service 5285 Port Royal Road Springfield, VA 22161 phone: 800.553.6847 fax: 703.605.6900 email: [email protected] online ordering: http://www.ntis.gov/ordering.htm Printed on paper containing at least 50% wastepaper, including 20% postconsumer waste ii TABLE OF CONTENTS Acknowledgments____________________________________________________________ vii Executive Summary _________________________________________________..
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