25 research outputs found

    Investigation for Bioactive Compounds of Berberis Lyceum Royle and Justicia Adhatoda L.

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    In order to explore the medicinal values of plant species like Berberis lyceum and Justicia adhatoda, a study was conducted to analyze roots, leaves and fruits of both plant species for identification of various organic compounds. Chemical analysis as well as identification of organic compounds by chromatographic techniques were carried out. Results indicates that both plant species contained Proteins, Sugars, Lipids, Vitamin C, Sodium, Calcium, Sulphur, Iron, and Zinc.Whereas the alkaloids like Palmatine, Berberine, Vasicine and Vasicinone were also found in leaves and roots of these plant species. However, it was observed that roots of both plant species contained higher concentrations of these chemical compounds as compared to fruits and leaves except sugar and vitamin C those were high in fruits. Furthermore presence of such bioactive compounds in Berberis lyceum and Justicia adhatoda indicated their importance in the form of local medicines. This experiment will help to increase the importance of new raw material found in these plant species and their demand in the market will be increased in the future. The extract of roots and fruits of these plant species are being used against various infections and diseases in rural population of subcontinent since many centuries

    An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation

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    In project management, effective cost estimation is one of the most crucial activities to efficiently manage resources by predicting the required cost to fulfill a given task. However, finding the best estimation results in software development is challenging. Thus, accurate estimation of software development efforts is always a concern for many companies. In this paper, we proposed a novel software development effort estimation model based both on constructive cost model II (COCOMO II) and the artificial neural network (ANN). An artificial neural network enhances the COCOMO model, and the value of the baseline effort constant A is calibrated to use it in the proposed model equation. Three state-of-the-art publicly available datasets are used for experiments. The backpropagation feedforward procedure used a training set by iteratively processing and training a neural network. The proposed model is tested on the test set. The estimated effort is compared with the actual effort value. Experimental results show that the effort estimated by the proposed model is very close to the real effort, thus enhanced the reliability and improving the software effort estimation accuracy

    3D-Bioprinting: A stepping stone towards enhanced medical approaches

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    In the past few decades, tissue engineering has been seen unprecedented escalation driving the field of artificial tissue and organ construct and brought metamorphosis in regenerative medicine. Prime advancement has been attained through the expansion of novel biomanufacturing approaches to devise and convene cells in three dimensions to fabricate tissue contrive. Accompaniment manufacturing differently known as 3D bioprinting is leading prime innovation in a number of applications in life sciences such as tissue and organ construct, personalized drug dosing, cancer model and heart tissue engineering. Overall, this review summarizes most prevalent bioprinting technologies; including laser-based bioprinting, extrusion bioprinting, injection bioprinting, stereolithography as well as biomaterial such as bioink. It also explores 3D industries, approaches such as Biomimicry, autonomous self-assembly, mini tissues and biomedical applications. Existing challenges that impede clinical mileage of bioprinting are also discussed along with future prospective.Keywords: Bioprinting, tissue engineering, tissue and organ construct, medicinal approac

    Clinical signs predictive of severe illness in young Pakistani infants

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    Objective: Early detection of specific signs and symptoms to predict severe illness is essential to prevent infant mortality. As a continuation of the results from the multicenter Young Infants Clinical Signs and Symptoms (YICSS) study, we present here the performance of the seven-sign algorithm in 3 age categories (0-6 days, 7-27 days and 28-59 days) in Pakistani infants aged 0-59 days.Results: From September 2003 to November 2004, 2950 infants were enrolled (age group 0-6 days = 1633, 7-27 days = 817, 28-59 days = 500). The common reason for seeking care was umbilical redness or discharge (29.2%) in the 0-6 days group. Older age groups presented with cough (16.9%) in the 7-27 age group and (26.9%) infants in the 28-59 days group. Severe infection/sepsis was the most common primary diagnoses in infants requiring hospitalization across all age groups. The algorithm performed well in every age group, with a sensitivity of 85.9% and specificity of 71.6% in the 0-6 days age group and a sensitivity of 80.5% and specificity of 80.2% in the 28-59 days group; the sensitivity was slightly lower in the 7-27 age group (72.4%) but the specificity remained high (83.1%)

    Synthesis, Characterization, Biological Activities and Ab-initio Study of Transition Metal Complexes of [Methyl 2-((4-chlorophenyl)(hydroxy)methyle) Acrylate]

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    Taking cognizance of the medicinal significance and diverse functions of synthetic Morita-Baylis-Hillman adducts (MBHA), the title ligand was synthesized and purified through column chromatography. Cr+3, Mn+2, Co+3, Ni+2, Cu+2 complexes of the ligand were synthesized under basic conditions, subjected to characterization through spectral analyses and verified with the IR spectrum that was generated computationally by the DFT B3LYP method, with 6-311++ G (d,p) basis set and Hartree Fock (HF) B3LYP method in conjunction with 3-21G(d,p) basis set. Powder XRD helped to testify crystals of the complexes. Moreover, the antibacterial, and antioxidant characteristics of MBHA and its complexes were also established. All of them were found to be active antioxidants. The antibacterial activities, examined against S. aureus, E. coli, B. pumilis and S. typhi have revealed that its Cobalt complex has an excellent potential to act against all of them. Hence, these compounds maybe having potentialities for the discovery of new, cheaper and efficient drugs against various infectious diseases. The study also uncovers the first example of utilization of MBHA towards metal complex formation

    Nasopharyngeal carriage of Streptococcus pneumoniae in children under 5 years of age before introduction of pneumococcal vaccine (PCV10) in urban and rural districts in Pakistan

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    Background: Benefits of pneumococcal conjugate vaccine programs have been linked to the vaccine’s ability to disrupt nasopharyngeal carriage and transmission. The 10-valent pneumococcal vaccine (PCV10) was included in the Expanded Program on Immunization (EPI) in Sindh, Pakistan in February 2013. This study was carried out immediately before PCV10 introduction to establish baseline pneumococcal carriage and prevalent serotypes in young children and to determine if carriage differed in urban and rural communities.Methods: Nasopharyngeal specimens were collected from a random sample of children 3-11 and 12-59 months of age in an urban community (Karachi) and children 3-11 months of age in a rural community (Matiari). Samples were processed in a research laboratory in Karachi. Samples were transported in STGG media, enriched in Todd Hewitt broth, rabbit serum and yeast extract, cultured on 5% sheep blood agar, and serotyped using the CDC standardized sequential multiplex PCR assay. Serotypes were categorized into PCV10-type and non-vaccine types.Results: We enrolled 670 children. Pneumococci were detected in 73.6% and 79.5 % of children in the infant group in Karachi and Matiari, respectively, and 78.2% of children 12 to 59 months of age in Karachi. In infants, 38. 9% and 33.5% of those carrying pneumococci in Karachi and Matiari, respectively, had PCV10 types. In the older age group in Karachi, the proportion was 30.7%, not significantly different from infants. The most common serotypes were 6A, 23F, 19A, 6B and 19F.Conclusion: We found that about 3 of 4 children carried pneumococci, and this figure did not vary with age group or urban or rural residence. Planned annual surveys in the same communities will inform change in carriage of PCV10 serotype pneumococci after the introduction and uptake of PCV10 in these communitie

    Burden of waterpipe smoking and chewing tobacco use among women of reproductive age group using data from the 2012-13 Pakistan Demographic and Health Survey

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    Background: Despite the general decline in cigarette smoking, use of alternative forms of tobacco has increased particularly in developing countries. Waterpipe (WP) and Chewing Tobacco (CT) are two such alternative forms, finding their way into many populations. However, the burden of these alternative forms of tobacco and their socio demographic determinants are still unclear. We assessed the prevalence of WP and CT use among women of reproductive age group in Pakistan. Methods: Data from the most recent Pakistan Demographic and Health Survey 2012–13 (n = 13,558) was used for this analysis. Information obtained from ever married women, aged between 15 and 49 years were analyzed using two separate data subgroups; exclusive WP smokers (total n = 12,995) and exclusive CT users (total n = 12,771). Univariate and Multivariate logistic regression analyses were conducted and results were reported as crude and adjusted Odds Ratio with 95 % confidence intervals. Results: Prevalence of WP smoking and CT were 4 % and 2 %, respectively. After multivariate adjustments, ever married women who were: older than 35 years (OR; 4.68 95 % CI, 2.62–8.37), were poorest (OR = 4.03, 95 % CI 2.08–7.81), and had no education (OR = 9.19, 95 % CI 5.10–16.54), were more likely to be WP smokers. Similarly, ever married women who were: older than 35 years (OR = 3.19, 95 % CI 1.69–6.00), had no education (OR = 4.94, 95 % CI 2.62–9.33), were poor (OR = 1.64, 95 % CI 1.07–2.48) and had visited health facility in last 12 months (OR = 1.81, 95 % CI 1.22–2.70) were more likely to be CT users as well. Conclusion: Older women with lower socio-economic profile were more likely to use WP and CT. Focused policies aiming towards reducing the burden of alternate forms of tobacco use among women is urgently needed to control the tobacco epidemic in the country

    Does Organization Learning Capacity influence the Organization Effectiveness? Moderating Role of Absorptive Capacity

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    International audienceOrganizational learning capacity play significant role to boost up the organizational effectiveness. The purpose of this study is to explore the association between organizational learning capacity and organizational effectiveness by considering the moderating role of absorptive capacity. Study is descriptive in nature. Questionnaire survey method was used for data collection by applying simple random sampling technique. CFA and SEM were used for the statistical analysis. Results of study indicated that organizational learning capacity positively and significantly correlated with organizational effectiveness. Moreover, absorptive capacity also significantly moderates the relationship between organizational learning capacity and organizational effectiveness. The implications and limitation of research are discussed along with direction and suggestion for further research

    Feature Selection for Lung and Breast Cancer Disease Prediction Using Machine Learning Techniques

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    Early detection of cancer is essential for a favorable prognosis because it is the biggest cause of death globally. After lung cancer, breast cancer ranks as the second most prevalent cause of death. With the fast expansion of the populace, the risk of mortality from lung and breast cancer is increasing rapidly. Early cancer prediction is challenging because there are few signs of this disease at an early stage. An automated sickness identification system provide accurate, efficient and quick response while assisting medical workers in identifying disorders and decreases death rates. In this research, we proposed PSO-FS (particle swarm optimization-based feature selection) method to select the features for several machine learning techniques to categorize accessible lung and breast cancer data. The best classifier approach for predicting both cancer diseases is considered to be the forest (RF) and deep learning (DL) classifier, which has high accuracy of 99.7% and 97%, respectively. Hence feature selection approach can increase performance by selecting only significant features
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