miniDVMS v1.8 : A user manual(The data visualization and modeling system)

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. miniDVMS v1.8 provides a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualisation domain. The advantage of this interface is that the user is directly involved in the data mining process. Principled projection methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), are integrated with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, and user interaction facilities, to provide this integrated visual data mining framework. The software also supports conventional visualisation techniques such as principal component analysis (PCA), Neuroscale, and PhiVis. This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install and use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software

FORMULATION DEVELOPMENT AND EVALUATION OF NIOSOMAL GEL OF COLLECTIVE ANTI-FUNGAL AGENTS

Objectives: Tea tree oil (TTO) and Eucalyptus oil (EO) are essential oils derived from the leaves and terminal branches of Melaleuca alternifolia and Eucalyptus globulus. Both oils have narrative topical antifungal agents. Niosomal vesicles were chosen for Tea tree and EO dispersion in this investigation because of their ability to protect enclosed drugs, reduce drug dose amount, target drug delivery, increase residence time and penetration. Methods: TTO and EO containing niosomes were made using a modified thin-film hydration process and Carbopol 934 as a gelling agent to produce a smooth antifungal niosomal gel. Results: TTO and EO entrapment efficiency was found to be 84.89±0.19% and 86.86±0.57%, respectively, and percent cumulative drug diffusion of TTO and EO was found to be 84.21% and 85.22% in the prepared optimized batch [N9]. Transmission electron microscopy revealed vesicular, spherical particles in the nano range with a smooth surface. The optimum batch [N9] of niosomal gel was made with 1% w/w carbopol 934. TTO 84.9% and EO 86.89%, respectively, were found to have prolonged drug release in an in vitro release investigation utilizing the dialysis bag method. The G9 batch niosomal gel was found to be stable by performing an accelerated stability study for 3 months. Conclusion: It was concluded that the best formulation batch G9 shows better-sustained release, enhanced residence time, and stability

PERSONALIZED VIRTUAL SCHOOL ENVIRONMENT USING CLASSIFIER ALGORITHM AND SEMANTIC ADVISOR-ASSISTING FRAMEWORK

As we knew that every individual is different than each other and their brain levels are also different, some students are very bright and some arenot, so there is a need to develop such system which will teach them as per their thought process and learning habits. This research aims to developa personalized virtual school environment for students which help them to learn the things same as they learn in school physically, but the thinghere is each student will be treated differently as per his/her ability. Hence, this system would be a virtual school for any student, which resemblesthe CBSE school system in India. In this virtual school, all things are present such as teachers, homework, games, and exams which present in actualschool except one which is the physical classroom because in virtual environment the course and things are personalized for each student as perhis/her thoughts and brain level, so here the student can seat in his/her home and can learn at any time with help of computer. The system is a webbasedenvironment and machine learning would be used for doing personalization on family and knowledge context of student. This web system contains four components: (1) Classification based on family context, (2) classification based on knowledge context, (3) learning material selection algorithm, (4) web-based learning system on top of above three, are discussed in this paper.Â

EFFECTIVENESS OF SPIRULINA MOUTHWASH ON REDUCTION OF DENTAL PLAQUE AND GINGIVITIS: A CLINICAL STUDY

Objective: The present study evaluated the effectiveness of Spirulina mouthwash on the reduction of dental plaque and gingivitis.Methods: A single-blind clinical trial was conducted among thirty patient's aged 18-40 y visiting dental college and hospital in Bangalore city. Mouthwash was prepared using 0.5% Spirulina. Intervention protocol consisted of instructing the patients to rinse with 10 ml of mouthwash for 1 minute twice daily for 7 d. Plaque index and Gingival index were used to assess the variables at the baseline and after the intervention. The perception of the individual subjects with regard to the use of mouthwash was assessed using 10 cm long visual analog scale (VAS). Statistical analysis was carried out using Wilcoxon signed rank test for mean pre and post plaque and gingival scores respectively. Descriptive statistics was performed for VAS questionnaireResults: The results showed a highly significant difference (p<0.001) between the mean plaque scores at the baseline (2.16±0.34) and at the follow up (1.27±0.46). The mean gingival scores at the baseline (1.86±0.38) and at the follow-up (1.05±0.43) also showed a highly significant difference (p<0.001). Regarding the Visual Analog Scale, the mean values of 5 or greater than suggested the responses to be favourable as the values were reflectedConclusion: The study showed that Spirulina mouthwash resulted in significant reduction in dental plaque and gingivitis. Also, the mouthwash was convenient to use without any adverse effects. Hence, the use of herbal mouth rinses such as Spirulina should be supported

Evaluation of peripheral and central analgesic activity of ethanolic extract of Clerodendrum infortunatum Linn. in experimental animals

Background: Clerodendrum infortunatum Linn. (Verbenaceae) is an important and widely used medicinal plant. Though variously used in Ayurveda, Unani, and Homeopathy system of medicine in the case of ailments such as diarrhoea, skin disorders, venereal and scrofulous complaints, wounds, post-natal complications, as anti-helminthic, and external applications on tumors, the plant needs thorough investigation for its specific medicinal activity. This study evaluates both the central and peripheral analgesic effect of the ethanolic extract of the leaves of C. infortunatum Linn. (EECI) in the experimental animals.Methods: Acute toxicity test was done following the Organization of Economic Co-operation and Development guidelines. EECI (100 mg/kg, 200 mg/kg, and 400 mg/kg body weight [b.w.] p.o) was evaluated for central analgesic activity by the tail flick method and peripheral analgesic activity by the acetic acid (0.7%) induced writhing test, respectively. Using aspirin (300 mg/kg b.w. and 100 mg/kg b.w.) as the standard drug.Results: EECI significantly decreased the number of writhing in writhing test at all the doses (p<0.01) and increased the reaction time in tail-flick method (p<0.01) at all the doses. EECI in the dosage of 400 mg/kg b.w. produced effects which was comparable with that of the standard drug aspirin (p<0.001) in writhing test (p<0.001) and tail flick method (p<0.001).Conclusion: The study showed significant central and peripheral analgesic activity of EECI which may be attributed to the inhibition of prostaglandin synthesis, phospholipase A2, and tumor necrosis factor alpha. C. infortunatum Linn. as a commercial source of analgesic drug should be subjected to further research

Peripheral and central analgesic activity evaluation of ethanolic extract of Vitex Negundo flowers in experimental animals

Background: Vitex negundo Linn (Family: Verbenaceae), locally known as ‘Nirgundi’ an important medicinal plant is a woody, aromatic shrub growing to a small tree. It commonly bears tri- or penta-foliate leaves on quadrangular branches, which give rise to bluish-purple coloured flowers in branched tomentose cymes. It has been claimed to possess analgesic activity apart from many medicinal properties. The aim of the present study was to evaluate both the peripheral and central analgesic activity of ethanolic extract of Vitex negundo flowers (EEVNF) in experimental animals.Methods: Acute toxicity test was done following the Organization of Economic Cooperation and Development guidelines. EEVNF (100mg/kg, 200mg/kg, and 400 mg/kg body weight [b.w.] p.o) was evaluated for peripheral analgesic activity by the acetic acid (0.7%) induced writhing test and central analgesic activity by the tail flick method respectively using aspirin (100mg/kg b.w. and 300mg/kg b.w.) as the standard drug.Results: EEVNF significantly decreased the number of writhing in writhing test at all the doses (p<0.001) and increased the reaction time in tail-flick method (p<0.001) at all the doses when compared to control. EEVNF in the dosage of 400mg/kg b.w. produced analgesic effects which was comparable with that of the standard drug aspirin at dose 100mg/kg b.w in writhing test and produced greater analgesic activity than that of standard drug aspirin at dose 300mg/kg b.w in tail flick method.Conclusions: EEVNF has significant peripheral and central analgesic activity

Ethanol Enhances Estrogen Mediated Angiogenesis in Breast Cancer

Angiogenesis, a highly regulated process, is exploited by tumors like breast cancer to ensure a constant supply of oxygen and nutrients and is key for tumor survival and progression. Estrogen and alcohol independently have been observed to contribute to angiogenesis in breast cancer but their combinatorial effects have never been evaluated. The exact mechanism by which estrogen and alcohol contribute to breast cancer angiogenesis remains to be elucidated. In this study, we defined the in vitro effects of the combination of estrogen and alcohol in breast cancer angiogenesis using the tubulogenesis and scratch wound assays. Conditioned media, generated by culturing the murine mammary cancer cell line, TG1-1, in estrogen and ethanol, enhanced tubule formation and migration as well as modulated the MAP Kinase pathway in the murine endothelial cell line, SVEC4-10. Additionally, estrogen and ethanol in combination enhanced the expression of the pro-angiogenic factors VEGF, MMP-9, and eNOS, and modulated Akt activation. These observations suggest that TG1-1 cells secrete pro-angiogenic molecules in response to the combination of estrogen and ethanol that modulate the morphological and migratory properties of endothelial cells. The data presented in this study, is the first in attempting to link the cooperative activity between estrogen and ethanol in breast cancer progression, underscoring correlations first made by epidemiological observations linking the two

Visual data mining: integrating machine learning with information visualization

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. Most existing systems concentrate either on mining algorithms or on visualization techniques. Though visual methods developed in information visualization have been helpful, for improved understanding of a complex large high-dimensional dataset, there is a need for an effective projection of such a dataset onto a lower-dimension (2D or 3D) manifold. This paper introduces a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualization domain. The framework follows Shneiderman’s mantra to provide an effective user interface. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection methods, such as Generative Topographic Mapping (GTM) and Hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, billboarding, and user interaction facilities, to provide an integrated visual data mining framework. Results on a real life high-dimensional dataset from the chemoinformatics domain are also reported and discussed. Projection results of GTM are analytically compared with the projection results from other traditional projection methods, and it is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework

DVMS 1.5: A user manual (the data visualization and modeling system)

The data available during the drug discovery process is vast in amount and diverse in nature. To gain useful information from such data, an effective visualisation tool is required. To provide better visualisation facilities to the domain experts (screening scientist, biologist, chemist, etc.),we developed a software which is based on recently developed principled visualisation algorithms such as Generative Topographic Mapping (GTM) and Hierarchical Generative Topographic Mapping (HGTM). The software also supports conventional visualisation techniques such as Principal Component Analysis, NeuroScale, PhiVis, and Locally Linear Embedding (LLE). The software also provides global and local regression facilities . It supports regression algorithms such as Multilayer Perceptron (MLP), Radial Basis Functions network (RBF), Generalised Linear Models (GLM), Mixture of Experts (MoE), and newly developed Guided Mixture of Experts (GME). This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install &amp; use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software

Evaluation of anticonvulsant activity of ethanolic extract of Momordica tuberosa leaves in experimental animals

Background: The aim of the present study was to evaluate the anticonvulsant activity of ethanolic extract of Momordica tuberosa leaves (EEMTL) in a maximal electric shock induced seizure (MES) model in experimental animals.Methods: A total of 30 albino rats of either sex weighing 150-200 g were randomly divided into five groups of six animals each. Group I received normal saline (0.5 ml), Group II received phenytoin sodium (25 mg/kg body weight) intraperitoneal, Group III, IV, V received different doses (100, 200, 400 mg/kg, respectively) of M. tuberosa leaves extract orally. Convulsions were produced in all groups by giving maximal electric shock of 150 mA for 0.2 sec after 1 hr of giving test and standard drugs. Tonic-clonic seizures were produced after giving an electric shock. Recovery time was noted. The period of tonus, clonus, and stupor were measured and compared between the control, standard and test.Results: In MES model, EEMTLsignificantly (p<0.0001) decreased the duration of tonic-clonic seizures and recovery time.Conclusion: M. tuberosa leaveswere shown anticonvulsant property in MES animal models