172 research outputs found

    ANTIMUTAGENIC POTENTIAL OF POLLEN GRAINS OF SOME MEDICINAL PLANT SPECIES

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    Objective: The present study was planned to explore the antimutagenic response of ethanolic extracts of pollen grains of four plant species viz., Bauhinia variegata, Cassia biflora, Cassia glauca and Cassia siamea belonging to Fabaceae family.Methods: Ames assay was used to evaluate the antimuatagenic activity of the ethanolic extracts of pollen grains of four plant species. Both TA 98 and TA 100 strains of Salmonella typhimurium were used in presence and absence of S9 mix during the present study.Results: Among four species studied, pollen extracts of Bauhinia variegata and Cassia biflora had shown maximum percentage inhibition of revertant colonies during presence and absence of S9 mix, respectively.Conclusion: The present study reveals that pollen extract of four plant species viz., Bauhinia variegata, Cassia glauca, Cassia biflora and Cassia siamea exhibited antimutagenic potential against two direct acting mutagens viz., (4 nitro-o-phenylenediamine; NPD for TA 98 and sodium azide for TA 100) and one indirect acting mutagen (2 amino-flourine; 2AF) which indicates that pollen grains of these species can act as potential source of anticancer drugs.Keywords: Ames assay, Bauhinia variegata, Pharmaceutical, Cance

    Polyphenolic characterization of pollen grains of some medicinal plant species using Ultra High Performance Liquid Chromatography (UHPLC)

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    Polyphenols, the secondary metabolites distributed in different parts of a plant, have major role in protecting the plants from deleterious effects of ultraviolet radiations and various diseases caused by pathogens. Considering the fact that these metabolites possess tremendous medicinal properties, extensive research has been carried out during the past few decades to explore their potential health benefits. Further, polyphenols are documented to possess different activities such as antioxidant, anticarcinogenic, anti-inflammatory, antimicrobial and antiulcer. The present study pertained to analyze different polyphenolic compounds in pollen grains of 9 medicinally important plant species viz., Bauhinia variegata, B.purpurea, Cassia biflora, C. fistula, C. glauca, C. saimea and Delonix regia belonging to Fabaceae family, Hibiscus rosa-sinensis belonging to Malvaceae family and Melia azadirach belonging toMeliaceaefamily using Ultra high-performance liquid chromatography (UHPLC). Various polyphenolic compounds likecaffeic acid, catechin, chlorogenic acid, coumaric acid, ellagic acid, epicatechin, gallic acid, kaempferol, quercetin, rutin, tert-butyl hydroquinone andumbelliferonewere found to be present in the pollen grains of these plant species. The order of plant species in terms of maximum number of polyphenolic compounds was observed as Cassia saimea (10) > B. purpurea (9) = C. fistula (9) = Hibiscus rosa-sinensis (9) > Delonix regia (8) > B. variegata (6) > C. glauca (4) = Melia Azadirach (4) > C. biflora (3). The plants such as C. saimea, B. purpurea, C. fistula and H. rosa-sinensis with different polyphenolic compounds indicated their potential forthe treatment of ailments

    Effect of copper, nickel and lead on callus growth dynamics of Solanum lycopersicum

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    Solanum lycopersicum cv. (Punjab Kesar Cherry) (Tomato) belonging to family Solanaceae has been priced for the presence of lycopene, low sugar content and curative properties. However, the productivity of tomatoes has been observed to be low due to both biotic as well as abiotic stress. Considering the toxicity of copper (Cu), lead (Pb) and nickel (Ni) as environmental contamination and the economic importance of S. lycopersicum, the present study was undertaken to investigate the effects of these heavy metals on various growth parameters of callus cultures and plantlet regeneration. Callus induced through nodal segments was inoculated on Murashige and Skoog medium containing different concentrations (0 µM, 50 µM, 100 µM, 200 µM, 300 µM, 400 µM and 500 µM) of copper, lead and nickel. Decrease in different growth parameters was observed as 91.66-16.66 %, 76.38-11.11 %, 81.94-13.88 % for percent callus survival,  90.90-25 %, 72.72-37.50 %, 79.66-20 % for percent callus multiplication, 79.54-0 %, 82.75-33 %, 63.8-50 %  for percent root regeneration and 73.33-33 %, 72.50-33 %, 79.6- 20 % for percent shoot generation with increasing concentrations of Cu, Pb and Ni, respectively. Decrease in the average fresh and dry weight of callus was observed for all the metals. The order of toxicity was observed as Pb > Ni > Cu at the highest concentrations used for treating S. lycopersicum. The present study revealed that all three metals induced stress in the studied plant and need attention to developing methods to mitigate the consequences of metal toxicity in crop plants.

    Preterm premature rupture of membranes: maternal and perinatal outcome

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    Background: This is an observational analytical study carried out in department of obstetrics and Gynecology, in a tertiary care center to determine the factors influencing fetal and maternal outcome, prognosis and complications in preterm premature rupture of membrane cases.Methods: The present study is a prospective observational study of perinatal and maternal outcome in 100 cases of preterm premature rupture of membranes in between 2837 weeks gestation with singleton pregnancy, from 1st March 2013 to 28th February 2014. Patients with medical complications like anemia, preexisting hypertension, diabetes, vascular or renal disease, multiple gestations, uterine or fetal anomalies etc. are excluded from the study. Detailed history, physical examinations were carried out and appropriate management instituted as per individual patients need.Results: In this study maternal morbidity was 16%. Perinatal morbidity was 33% and most common causes were hyperbilirubinemia (23%), RDS (21%).  Perinatal mortality was seen in 15% and mainly due to RDS (53%). Twenty-five (25%) neonates were delivered by cesarean. The main indications for cesarean being malpresentation (36%) followed by fetal distress (24%).Conclusions: PPROM is one of the important causes of preterm birth that can result in high perinatal morbidity and mortality along with maternal morbidity. Looking after a premature infant puts immense burden on the family, economy and health care resources of the country. An understanding of gestational age dependent neonatal morbidity and mortality is important in determining the potential benefits of conservative management of preterm PROM at any gestation

    Exploring Post-Adoption Behavior of the UPI users with Cognitive and Affective Factors

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    The National Payments Corporation of India (NPCI) has invested a sizable amount of money in the country's massive payment infrastructure in an effort to enhance the user experience. However, in order for investments to be profitable, NPCI must guarantee the ongoing use of technological solutions and post-adoptive behaviors like continuance and recommendation intention. The impact of cognitive factors (i.e. Performance expectancy, effort expectancy, social influences, facilitating conditions; personal innovativeness) and affective factors (such as satisfaction) on conative factors (such as continuation and recommendation intention) in the perspective of UPI applications (apps) was investigated using the UTAUT model. Partial Least Square Structural Equation Modeling when applied on 651 users (PLS-SEM) showed that satisfaction had a direct impact on continuation intentions, which in turn had an impact on recommendations intentions. It was discovered that all cognitive factors, including performance expectations, effort expectations, and facilitating conditions, have an impact on satisfaction. According to the study, adding a significant individual difference variable—personal innovativeness with regard to information technology—would aid in our understanding of the role that these factors play in the development of continuous intention. It further examines the influence of trust and security, and the pace of innovation on continued intentions. Through the mediating function  of user satisfaction, it also looked at the impact of performance expectancy, effort expectancy, social influence, facilitating variable, and personal innovativeness on the continuance intentions of the UPI system. All factors have been shown to be significant. Future researchers will find it extremely helpful that the study used a validated instrument to better understand user adherence and referral intentions. Therefore, this study adds to the limited body of knowledge in the payment industry literature by examining how users perceive UPI apps and post-adoption behaviors

    Point Prevalence of Indwelling Catheterized Patients Admitted in a Tertiary Care Hospital and Related Nursing Care Practices

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    Urinary catheterization facilitates the drainage of urinary bladder. The current study was carried out to assess the point prevalence of indwelling catheterized patients admitted in a tertiary care hospital and to assess the related practices of nurses. A descriptive cross-sectional design was employed. Sampling technique was purposive. Survey of all the admitted patients was carried out in a single day to assess the point prevalence of catheterized patients. Tools for data collection comprised of sociodemographic profile and clinical profile of the catheterized patients. A checklist was used to assess the self-expressed practices of nurses regarding insertion, care and removal of catheter. The total number of admitted patients on the day of survey was 1718. 317 (18.5%) patients were found to be catheterized. Majority of the patients were in Intensive Care Unit followed by Emergency areas and were suffering from neurological disorders. Most of the self-expressed practices of nurses regarding catheterization were adequate other than documentation of the procedure; providing perineal care at the time of catheterization, catheter care and removing the catheter; and clamping the catheter before its removal.

    DaaS: Dew Computing as a Service for Intelligent Intrusion Detection in Edge-of-Things Ecosystem

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    Edge of Things (EoT) enables the seamless transfer of services, storage, and data processing from the cloud layer to edge devices in a large-scale distributed Internet of Things (IoT) ecosystems (e.g., Industrial systems). This transition raises the privacy and security concerns in the EoT paradigm distributed at different layers. Intrusion detection systems (IDSs) are implemented in EoT ecosystems to protect the underlying resources from attackers. However, the current IDSs are not intelligent enough to control the false alarms, which significantly lower the reliability and add to the analysis burden on the IDSs. In this article, we present a Dew Computing as a Service (DaaS) for intelligent intrusion detection in EoT ecosystems. In DaaS, a deep learning-based classifier is used to design an intelligent alarm filtration mechanism. In this mechanism, the filtration accuracy is improved (or sustained) by using deep belief networks. In the past, the cloud-based techniques have been applied for offloading the EoT tasks, which increases the middle layer burden and raises the communication delay. Here, we introduce the dew computing features that are used to design the smart false alarm reduction system. DaaS, when experimented in a simulated environment, reflects lower response time to process the data in the EoT ecosystem. The revamped DBN model achieved the classification accuracy up to 95%. Moreover, it depicts a 60% improvement in the latency and 35% workload reduction of the cloud servers as compared to edge IDS

    Service vs Protection: A Bayesian Learning Approach for Trust Provisioning in Edge of Things Environment

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    Edge of Things (EoT) technology enables end-users participation with smart-sensors and mobile devices (such as smartphones, wearable devices) to the smart devices across the smart city. Trust management is the main challenge in EoT infrastructure to consider the trusted participants. The Quality of Service (QoS) is highly affected by malicious users with fake or altered data. In this paper, a Robust Trust Management (RTM) scheme is designed based on Bayesian learning and collaboration filtering. The proposed RTM model is regularly updated after a specific interval with the significant decay value to the current calculated scores to update the behavior changes quickly. The dynamic characteristics of edge nodes are analyzed with the new probability score mechanism from recent services’ behavior. The performance of the proposed trust management scheme is evaluated in a simulated environment. The percentage of collaboration devices are tuned as 10%, 50% and 100%. The maximum accuracy of 99.8% is achieved from the proposed RTM scheme. The experimental results demonstrate that the RTM scheme shows better performance than the existing techniques in filtering malicious behavior and accuracy
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