204 research outputs found

    Ultra-large alignments using Phylogeny-aware Profiles

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    Many biological questions, including the estimation of deep evolutionary histories and the detection of remote homology between protein sequences, rely upon multiple sequence alignments (MSAs) and phylogenetic trees of large datasets. However, accurate large-scale multiple sequence alignment is very difficult, especially when the dataset contains fragmentary sequences. We present UPP, an MSA method that uses a new machine learning technique - the Ensemble of Hidden Markov Models - that we propose here. UPP produces highly accurate alignments for both nucleotide and amino acid sequences, even on ultra-large datasets or datasets containing fragmentary sequences. UPP is available at https://github.com/smirarab/sepp.Comment: Online supplemental materials and data are available at http://www.cs.utexas.edu/users/phylo/software/upp

    A 12 week prospective clinical evidence of empagliflozin efficacy in uncontrolled type 2 diabetes mellitus treated with metformin and a sulfonylurea

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    Background: The main aim of the study is to evaluate the efficacy of empagliflozin 10 mg once daily over 12 weeks as add-on therapy to metformin plus sulfonylurea in patients with type 2 diabetes mellitus with inadequate glycemic control.Methods: It is a prospective, observational, study conducted in patients of Sri Badhrakali Diabetic Center located in Warangal, Telangana, India. The efficacy of empagliflozin 10 mg was assessed by measuring the change in the glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), body mass index (BMI) at the baseline and 12 weeks, systolic blood pressure (SBP) and diastolic blood pressure (DBP) at the baseline and after 24 hours of treatment.Results: In the present study, the addition of empagliflozin to metformin and Sulfonylurea therapy for 12 weeks provided 0.87 % reduction in HbA1c. The mean changes of FPG from baseline to 12-week is -26 mg/dl. At 24 hours empagliflozin significantly reduced blood pressure with mean changes of SBP and DBP -4.147 and -1.526 mmHg respectively. The mean changes in BMI from baseline to week 12 is -0.638 kg/m2.Conclusions: Empagliflozin 10 mg provided ancillary reduction in HbA1c outside of metformin and sulfonylurea. Controlled body weight, HbA1c, blood pressure decreases diabetes progression, decreased risk of diabetic complications and reduced risk for cardiovascular disorders

    Histomorphometric and sympathetic innervation of the human internal thoracic artery

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    INTRODUCTION: Internal thoracic artery (ITA) is an established arterial graft for the coronary artery by-pass surgery. Special micro-anatomical features of the ITA wall may protect it from age related pathological changes. One of the complications seen after coronary artery bypass grafting is vasospasm. Sympathetic nerves may be involved in vasospasm. OBJECTIVE: To ascertain the sympathetic innervation of the internal thoracic artery and to assess the effect of aging on this artery by histomorphometry. METHOD: Fifty-four human internal thoracic artery samples were collected from 27 cadavers (19 male and 8 female) with ages of 19 to 83 years. Samples were divided into three age groups: G1, 19-40 years; G2, 41-60 years; G3, >61 years. Sections (thickness 5 mm) of each sample were taken and stained with hematoxylin-eosin and Verhoeff-Van Gieson stains. Five of fifty-four samples were processed for tyrosine hydroxylase immunostaining. RESULTS: The thickness of the tunica intima was found to be constant in all age groups, whereas the thickness of the tunica media decreased in proportion to age. Verhoeff-Van Gieson staining showed numerous elastic laminae in the tunica media. Significant differences (p<0.0001) in the number of elastic laminae were found between G1 with G2 cadavers, between G2 and G3 cadavers and between G3 and G1 cadavers. Tyrosine hydroxylase immunostaining demonstrated sympathetic fibers, located mainly in the tunica adventitia and the adventitia-media border. The sympathetic nerve fiber area and sympathetic index were found to be 0.0016 mm² and 0.012, respectively. DISCUSSION: Histology of the ITA showed features of the elastic artery. This may be associated with lower incidence of Atherosclerosis or intimal hyperplasia in ITA samples even in elderly cases. Low sympathetic index (0.012) of ITA may be associated with fewer incidences of sympathetic nervous systems problems (vasospasm) of the ITA. CONCLUSION: Sympathetic nerve fibers are present in the adventitia of the internal thoracic artery. This is an elastic artery, although anatomically it is considered to be medium-sized. The sympathetic index may be used for analysis of sympathetic nerve fiber-related problems of the internal thoracic arter

    Expression of Autoreactive B Cell (B-1a) in Periodontal Health and Disease: An Immunohistochemical Study.

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    BACKGROUND: Autoreactive B cell (B-1a) may play a role in the pathogenesis of periodontal disease and this study was undertaken to elicit the autoimmune nature of B-1a cell in periodontal health and disease. MATERIALS AND METHODS: Thirty gingival tissue samples were collected from two groups of patients (periodontal health-Group A and periodontal disease- Group B). The tissue sections were paraffanised and processed. B-1a cell expression in connective tissue was determined using CD5+ as a marker by immunohistochemical analysis. Intensity of staining was assessed and interexaminer error was calculated by kappa analysis. The mean labeling index was statistically analysed using independent ‘t’ test. RESULTS: A good interexaminer agreement was observed between two examiners while assessing intensity. Comparison of mean labeling index between the two study groups was not statistically significant since p value was >0.01 (p value = 0.276). CONCLUSION: An increase in the number of autoreactive B-1a cells (CD5+) has been found in periodontitis as compared to healthy gingival specimens, which was found to be statistically insignificant

    MEDICINAL VALUES OF PUTRANJIVA ROXBURGHII-A REVIEW

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    The evolving economic concerns and the depletion of natural sources motivate the researchers to look for various alternatives. We started utilizing the bio resources like bio-diesel that is substituted over Petro-diesel. As the needs increasing day by day, it is our responsibility to not to deplete all the resources available now and hence not making the future generation in a great risk. So the idea is to find new sources that we can utilize and to also try to utilize the natural resources around us in a useful manner. In a recent trend, there are more technologies available for utilizing bio-resources in an effective manner. One such kind of bio-resource we can utilize is Putranjiva roxburghii. The ultimate aim of this review paper is to create a limelight on the medicinal values of Putranjiva plant. This current study explains the research works done so far with Putranjiva plant in a detailed manner and also to create awareness on growing Putranjiva plant all over the world. The plant material can be utilized as Anti-oxidant, febrifuge and for anti-inflammatory activities, as biofuel, as an herbal preservative, as an Antioxidant agent and as Trypsin inhibitor. The commercial, as well as medicinal values of Putranjiva, are so attractive, that encourages the authors to write a review over this excellent plant material

    Role of artificial intelligence in drug development

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    In the last decade, artificial intelligence (AI) has revolutionised the field of drug research. Staff abilities (55 percent), data structure (52 percent), and resources were all factors in AI deployment (49 percent ). Nearly 60% of respondents said they expected to hire more people in the next two years to assist AI usage or adoption in drug development. AI in areas like as drug research and development, drug repurposing, boosting pharmaceutical productivity, and clinical trials, among others, minimises human effort and allows for the achievement of objectives in a short amount of time. On the one hand, AI techniques used in drug development bring the drug development process and the use of various models closer to medicinal chemists, while on the other hand, AI methods used in drug development bring the drug development process and the use of various models closer to mathematicians

    FORMULATION AND EVALUATION OF BILAYERED FELODIPINE TRANSDERMAL PATCHES: IN VITRO AND EX VIVO CHARACTERIZATION

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    Objective: Felodipine (FD) is an effective Biopharmaceutics Classification System Class II calcium channel blocker mainly used in the management of hypertension and angina pectoris. It has poor solubility and low oral bioavailability (15%). To overcome these disadvantages and to maintain constant plasma concentration for maximum therapeutic activity, there is a need to design an alternative route, that is, transdermal route. The pharmacokinetic parameters make FD a suitable candidate for transdermal delivery. The present investigation consists of the study of in vitro and ex vivo skin flux of FD from bilayered transdermal patches. Methods: The patches were fabricated by solvent casting method using hydrophilic and hydrophobic polymer with different composition. Tween 80 incorporated as solubilizer, polyethylene glycol 600 as plasticizer, menthol, eucalyptus oil, and lemongrass oil used as permeation enhancers, respectively. The prepared transdermal drug delivery system was extensively evaluated for in vitro release, ex vivo permeation through pig ear skin, moisture content, moisture absorption, water vapor transmission, and mechanical properties. The physicochemical interaction between FD and polymers was investigated by Fourier-transform infrared (FTIR) spectroscopy. Results: All the formulations exhibited satisfactory physicochemical and mechanical characteristics. A flux of 35.2 μg/cm2 h, 27.9 μg/cm2 h, and 25.25 μg/cm2 h was achieved for optimized formulations containing lemongrass oil, eucalyptus oil, and menthol, respectively, permeation enhances. Values of tensile strength (0.0652±0.034 kg/mm²) and elongation at break (0.8749±0.0.0029% mm²) revealed that formulation F9 was strong but not brittle. Drug and excipients compatibility studies showed no evidence of interaction between the active ingredient and polymers. Conclusion: Bilayered FD transdermal patches could be prepared with required flux and suitable mechanical properties

    Design and development of an instrument for non- destructive fabric weight measurement

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    In this study, an image processing approach for fabric weight measurement has been proposed and tested. The system involves digital capturing of image using a microscope and then its processing in simple steps using image processing software (MATLAB). The study is conducted using a range of woven fabric samples. The fabrics have been conventionally weighed using an electronic weighing balance, and digital images of the sample fabrics are obtained and processed. The process involves application of suitable filters to obtain weft count, warp count, EPI, PPI and yarn crimp. The values are then substituted in standard formula to obtain the fabric weight. The study shows that the results of the proposed method of image processing, based on fabric weight measurement, are well correlated with the results of conventional method of measurement

    Skin Cancer Classification using Deep Learning

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    According to world health organization skin cancer is the one of the most common cancer types in the world. The abnormal growth of skin cells most often develops on the skin when exposed to the sun and occurs when there is a mutation in the DNA of skin cells, it begins at the top of the skin. More than five million people are affected by skin cancer each year. The proposed method aim at analyzing and detecting the significant class of skin cancer variant such as Melanoma, Basal cell Carcinoma, Nevus. Melanoma is the most dangerous form of skin cancer when compared to the other types. In this paper we have developed a webapp that could differentiate skin cancer. The data set has been taken from ISIC and the model is trained using Gcollab. The proposed work has used convolution neural network (CNN) as algorithm for deep learning as it has higher accuracy and flask is used to develop the web app and the class of cancer is classified based on historical data of dermoscopic images

    ORAL PEMPHIGUS - A CASE REPORT

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    PEMPHIGUS is a serious chronic skin disease characterized by the appearance of vesicles &amp; bullae, small or large fluid filled blisters that develop in cycles. The term pemphigus refers to a group of autoimmune blistering diseases of skin and mucous membranes that are characterized histologically by intraepidermal blisters due to acantholysis and immunopathologically by an in vivo bound &amp; circulating IgG directed against the cell surface of keratinocytes. Pemphigus vulgaris is the most common form and frequently affects oral cavity. Main antigen is Dsg 3 (desmoglein) but 50% of patients also have autoantibodies to Dsg 1. Dsg 3: Dsg 1 is directly proportional to severity. We present a case of pemphigus occurring in the oral cavity of a 45-year-old male. Treatment with oral prednisolone and topical steroid resulted in remission of the disease. Clinical features, histological features and treatment of pemphigus vulgaris will be discussed. KEYWORDS:&nbsp;Pemphigus; Blisters; Acantholysis; Autoantibodies
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