20 research outputs found
Coding Genome Sequence and Protein Sequence Analysis of Dengue Strains: In Silico Correlation
Background: DENV-1, DENV-2, DENV-3, and DENV-4 are the four serotypes of dengue viruses (DENV) that are transferred from person to person through the bite of Aedes mosquitoes. Dengue fever has surged 30-fold in occurrence over the last 50 years, making it one of the world's most serious arboviral diseases. The aim of this study is to bioinformatically correlate the coding sequences of four DENV strains to check their genetic & functional diversity on the basis of the similarity of the sequences.Methods: The coding sequences (CDs) and protein sequences of newly reported dengue strains (DENV 1, DENV 2, DENV 3, and DENV 4) were obtained from the National center for Biotechnology Information (NCBI) nucleotide and protein databases. We compare the genetic and functional compatibility of selected gene sequences from four dengue strains by using various bioinformatics tools and software such as BLAST, MEGA 11.0, ProtParam, GOR4 and SWISS Model.Results: The total number of amino acids in dengue strains DENV1, 2, 3, and 4 is 3392, 3391, 3390, and 3387, according to physiochemical analysis. The phylogenetic analysis reveals that DENV-1 and DENV-2 have more genetic similarity than DENV-2 and DENV-3, with bootstrap values greater than 90%. While different percentages of alpha helices were predicted in secondary structure, such as 33.23 %, 36.51 %, 31.21%, and 32.27% of DENV1, 2, 3, and 4 show little variation. The non-structural proteins NS1 and NS5 of all four DENV strains show more than 65 percent similarity index in 3D structure analysis.Conclusion: This study first presented a bioinformatics comparison of all four DENV strains. The 3D and 2D structures of DENV strains (1-4) show some similarity and dissimilarity index, however the four DENV strains differ in their 2D structure's alpha helix (H), random coil, and number of amino acids.Keywords: Bioinformatics; Dengue strains; Non-structural protein; Coding sequence; viral pathogenesis
EVALUATION OF ROOT AND LEAF OF ABUTILON THEOPHRASTI MEDIK FOR ANTIFUNGAL ACTIVITY
ABSTRACTThe investigation was aimed to carry out the antifungal activities of the methanol and aqueous extracts of Abutilon theophrasti against four fungalstrains (Microsporum gypseum, Penicillium spp., Fusarium spp., Aspergillus spp.). Antifungal activity of the extracts was determined by the discdiffusion method against various fungi with soubred dextrose agar as media. Methanolic extracts of A. theophrasti showed promising antifungalactivity compared to aqueous extracts against selected fungal species. Methanolic extract of leaf displayed the highest activity with zone of inhibition14 mm against Penicillium spp. which were totally concentration dependent; however, a poor activity was seen in aqueous extracts. Methanolicextracts of root displayed good antifungal activity, while as no activity was seen in aqueous extracts of root. The results obtained in the study showthat methanolic leaf extracts possess phytoconstituents with potent antifungal activity.Keywords: Abutilon, Methanol, Rhizopus, Penicillium
IN VITRO ANTHELMINTIC ACTIVITY OF ABUTILON THEOPHRASTI MEDIK. (MALVACEAE) AGAINST EGGS AND L3 LARVAE OF HAEMONCHUS CONTORTUS
Objective: The present study was carried out to assess the in vitro anthelmintic activity of Abutilon theophrasti stem extracts.
Methods: Simple maceration was employed for extraction. Solvents such as methanol, water, and hexane were used. Egg hatch test (EHT) and larval motility test were employed to check the anthelmintic activity of crude extracts. Concentrations of 500, 250, 125, 62.5, and 31.25 mg/ml were made. Levamisole and distilled water served as control, respectively.
Results: All selected extracts displayed concentration-dependent inhibition except aqueous extracts. At higher concentration (500 mg/ml), stem extracts (methanol, aqueous, and ethanol) showed 74.39%, 72.5 and 70.03% of efficacy in EHT, respectively (p≤0.05). Meanwhile, inhibition of larval motility was seen higher with inhibition percentage of 79.79, 75.65, and 71.28 by methanolic, aqueous, and hexane extracts, respectively (p≤ 0.05).
Conclusion: The presents study suggests active principles having anthelmintic efficacy in Abutilon theopharsti stem
Effect of early tranexamic acid administration on mortality, hysterectomy, and other morbidities in women with post-partum haemorrhage (WOMAN): an international, randomised, double-blind, placebo-controlled trial
Background
Post-partum haemorrhage is the leading cause of maternal death worldwide. Early administration of tranexamic acid reduces deaths due to bleeding in trauma patients. We aimed to assess the effects of early administration of tranexamic acid on death, hysterectomy, and other relevant outcomes in women with post-partum haemorrhage.
Methods
In this randomised, double-blind, placebo-controlled trial, we recruited women aged 16 years and older with a clinical diagnosis of post-partum haemorrhage after a vaginal birth or caesarean section from 193 hospitals in 21 countries. We randomly assigned women to receive either 1 g intravenous tranexamic acid or matching placebo in addition to usual care. If bleeding continued after 30 min, or stopped and restarted within 24 h of the first dose, a second dose of 1 g of tranexamic acid or placebo could be given. Patients were assigned by selection of a numbered treatment pack from a box containing eight numbered packs that were identical apart from the pack number. Participants, care givers, and those assessing outcomes were masked to allocation. We originally planned to enrol 15 000 women with a composite primary endpoint of death from all-causes or hysterectomy within 42 days of giving birth. However, during the trial it became apparent that the decision to conduct a hysterectomy was often made at the same time as randomisation. Although tranexamic acid could influence the risk of death in these cases, it could not affect the risk of hysterectomy. We therefore increased the sample size from 15 000 to 20 000 women in order to estimate the effect of tranexamic acid on the risk of death from post-partum haemorrhage. All analyses were done on an intention-to-treat basis. This trial is registered with ISRCTN76912190 (Dec 8, 2008); ClinicalTrials.gov, number NCT00872469; and PACTR201007000192283.
Findings
Between March, 2010, and April, 2016, 20 060 women were enrolled and randomly assigned to receive tranexamic acid (n=10 051) or placebo (n=10 009), of whom 10 036 and 9985, respectively, were included in the analysis. Death due to bleeding was significantly reduced in women given tranexamic acid (155 [1·5%] of 10 036 patients vs 191 [1·9%] of 9985 in the placebo group, risk ratio [RR] 0·81, 95% CI 0·65–1·00; p=0·045), especially in women given treatment within 3 h of giving birth (89 [1·2%] in the tranexamic acid group vs 127 [1·7%] in the placebo group, RR 0·69, 95% CI 0·52–0·91; p=0·008). All other causes of death did not differ significantly by group. Hysterectomy was not reduced with tranexamic acid (358 [3·6%] patients in the tranexamic acid group vs 351 [3·5%] in the placebo group, RR 1·02, 95% CI 0·88–1·07; p=0·84). The composite primary endpoint of death from all causes or hysterectomy was not reduced with tranexamic acid (534 [5·3%] deaths or hysterectomies in the tranexamic acid group vs 546 [5·5%] in the placebo group, RR 0·97, 95% CI 0·87-1·09; p=0·65). Adverse events (including thromboembolic events) did not differ significantly in the tranexamic acid versus placebo group.
Interpretation
Tranexamic acid reduces death due to bleeding in women with post-partum haemorrhage with no adverse effects. When used as a treatment for postpartum haemorrhage, tranexamic acid should be given as soon as possible after bleeding onset.
Funding
London School of Hygiene & Tropical Medicine, Pfizer, UK Department of Health, Wellcome Trust, and Bill & Melinda Gates Foundation
SpeakerNet for Cross-lingual Text-Independent Speaker Verification
Biometrics provide an alternative to passwords and pins for authentication. The emergence of machine learning algorithms provides an easy and economical solution to authentication problems. The phases of speaker verification protocol are training, enrollment of speakers and evaluation of unknown voice. In this paper, we addressed text independent speaker verification using Siamese convolutional network. Siamese networks are twin networks with shared weights. Feature space can be learnt easily by training these networks even if similar observations are placed in proximity. Extracted features from Siamese then can be classified using difference or correlation measures. We have implemented a customized scoring scheme that utilizes Siamese’ capability of applying distance measures with the convolutional learning. Experiments made on cross language audios of multi-lingual speakers confirm the capability of our architecture to handle gender, age and language independent speaker verification. Moreover, our designed Siamese network, SpeakerNet, provided better results than the existing speaker verification approaches by decreasing the equal error rate to 0.02
Development of Cefotaxime Impregnated Chitosan as Nano-antibiotics: De Novo Strategy to Combat Biofilm Forming Multi-drug Resistant Pathogens
Frequent incidents of antibiotic-resistant biofilm forming pathogens in community-associated and hospital-acquired infections have become a global concern owing to failure of conventional therapies. Nano-antibiotics (NABs) are de novo tools to overcome the multi-drug resistant mechanisms employed by the superbugs. Inhibition of biofilm formation is one of those strategies to curb multi drug resistance phenomenon. In the current study, the anti-biofilm and antibacterial potential of newly synthesized cefotaxime loaded chitosan based Nano-antibiotics (NABs) have been investigated. Both bare and cefotaxime loaded NABs were prepared by ionotropic gelation method. They were found carrying positive zeta potential of more than +50 mV, indicating highly stable nano-dispersion. Moreover, microscopic studies revealed their size as less than 100nm. Nano-antibiotics (NABs) were tested against clinical isolates of multi drug resistant Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli and methicillin resistant Staphylococcus aureus (MRSA) and wherein they demonstrated broad-spectrum anti-biofilm and anti-pathogenic activity. Thus, in vitro synergistic action of cephalosporin drugs and chitosan polymer at nano-scale in contrast to free antibiotics can be an improved broad-spectrum strategy to thwart resistance mechanisms in both Gram positive and Gram negative resistant pathogens
Secoisolariciresinol diglucoside and anethole ameliorate lipid abnormalities, oxidative injury, hypercholesterolemia, heart, and liver conditions
Abstract Fennel seeds and flaxseed have been traditionally used against many medical ailments due to their medicinal characteristics. The aim of the study was to investigate the health properties of secoisolariciresinol diglucoside (SDG) and anethole from flaxseed and fennel seeds in rats fed with high‐fat diet. Histopathological changes in the heart and liver were also examined. Sixty rats were divided into two main groups. Group I (10 rats) was used as a negative control group and fed on the basal diet only. Group II (50 rats) was fed a hypercholesterolemic diet but not given any drugs during the trial for 2 weeks. This group was further divided into five subgroups (10 rats each). One of them was fed on the basal diet and used as a positive control group. However, the other four subgroups were fed on basal diets and anethole (20 mg/kg/day, orally), SDG (20 mg/kg/day, orally), a mixture of anethole + SDG (10 + 10 mg/kg/day, orally), and atorvastatin (10 mg/kg/day, orally) for 6 weeks. Compared to control, treatment with a combination of anethole + SDG showed a significant (p ≤ .05) improvement in serum levels of triglyceride (TG) (137.88 ± 1.61 mg/dL), total cholesterol‐(TC) (180.12 ± 8.99 mg/dL), LDL‐C (46.40 ± 6.67 mg/dL), VLDL‐C (11.81 ± 1.07 mg/dL), aspartate aminotransferase (AST) (75.97 ± 6.92 U/L), alanine aminotransferase (ALT) (34.83 ± 2.17 U/L), alkaline phosphatase (ALP) (130.65 ± 1.05 U/L), and malondialdehyde (MDA) (30.12 ± 1.89 mmol/g), and improved activities of catalase (70.99 ± 3.29 U/g) and superoxide dismutase (SOD) (35.13 ± 2.53 U/dL) enzymes while SDG and anethole group had relatively less impact. Atorvastatin also improved serum levels of triglyceride, total cholesterol, LDL‐C, and VLDL‐C significantly and rose serum high‐density lipoprotein cholesterol (HDL‐C) levels considerably meanwhile it had a minor but negative impact on AST, ALT, and ALP, and negligible impact on activities of MDA, CAT, and SOD enzymes compared to the positive control group. The study revealed that combining anethole and SDG may improve dyslipidemia, improve lipid profile, decrease risks of chronic heart diseases, increase HDL‐C, and enhance antioxidant enzymes' activities
Isolation of natural herbicidal compound from Lantana camara
A flavone glucoside 'vitexin' (C21H20O10) was isolated from the leaves of Lantana camara through bioassay-guided isolation. Kupchan method of solvent-solvent partitioning of crude methanol extract from leaves of L. camara gave ethyl acetate, chloroform, hexane and aqueous fraction. Bio-assay with four fractions at 500 ppm, 1000 ppm and 10,000 ppm indicated chloroform fraction to be most potent phytotoxic against weeds (monocot: Phalaris minor, Avena fatua; Dicot: Chenopodium album, Rumex dentatus). Column chromatography of chloroform fraction with hexane: ethyl acetate (60:40) based on TLC profiling with vanillin visualisation stain and subsequent bioassays indicated sub-fraction (iii) of fraction 23 as most growth inhibitory. The chemical structure of the isolated compound was identified by gas chromatography-mass spectrometry (Shimadzu GC-MS-QP2010 ultra). The natural herbicidal activity of the isolated compound against various weeds in laboratory and field conditions is suggested
A Hybrid Deep Learning-Based Approach for Brain Tumor Classification
Brain tumors (BTs) are spreading very rapidly across the world. Every year, thousands of people die due to deadly brain tumors. Therefore, accurate detection and classification are essential in the treatment of brain tumors. Numerous research techniques have been introduced for BT detection as well as classification based on traditional machine learning (ML) and deep learning (DL). The traditional ML classifiers require hand-crafted features, which is very time-consuming. On the contrary, DL is very robust in feature extraction and has recently been widely used for classification and detection purposes. Therefore, in this work, we propose a hybrid deep learning model called DeepTumorNet for three types of brain tumors (BTs)—glioma, meningioma, and pituitary tumor classification—by adopting a basic convolutional neural network (CNN) architecture. The GoogLeNet architecture of the CNN model was used as a base. While developing the hybrid DeepTumorNet approach, the last 5 layers of GoogLeNet were removed, and 15 new layers were added instead of these 5 layers. Furthermore, we also utilized a leaky ReLU activation function in the feature map to increase the expressiveness of the model. The proposed model was tested on a publicly available research dataset for evaluation purposes, and it obtained 99.67% accuracy, 99.6% precision, 100% recall, and a 99.66% F1-score. The proposed methodology obtained the highest accuracy compared with the state-of-the-art classification results obtained with Alex net, Resnet50, darknet53, Shufflenet, GoogLeNet, SqueezeNet, ResNet101, Exception Net, and MobileNetv2. The proposed model showed its superiority over the existing models for BT classification from the MRI images