RESEARCH ARTICLE ARTICALTICLE International Journal of Pharma and Bio Sciences GENETICS CYTOGENETIC ANALYSIS OF MICRONUCLEI, SISTER CHROMATID EXCHANGE AND CHROMOSOMAL ABERRATIONS IN PAN MASALA CHEWERS

Pan Masala (PM) chewing is very dangerous for health but it is becoming very popular day by day. PM is a dried powdered mixture containing ingredients like areca nut, catechu, lime, cardamom and flavouring agents. It is consumed abundantly by Indians and is also exported to Western countries. A cytogenetic study to assess the micronucleus (MN), sister chromatid exchange (SCE) levels and chromosomal aberrations among (CA) 60 pan chewers and 60 non-chewers was conducted in Chennai, Tamil Nadu. In the present cytogenetic monitoring study, analysis of MN was significantly higher (15.82 ± 1.31) in chewers than controls (4.82 ± 1.47) (P < 0.001) and SCE also was significantly higher in chewers (9.23 ± 2.12) than controls (4.80±1.11) (P < 0.001). In exfoliated buccal mucosa and chromosome analysis (CA), frequency of chromatid type aberrations is lower in controls than chewers such as gaps (0.90 % v. 1.83%) breaks (0.47 % v. 1.77%), exchanges (0.02 % v. 0.18) and acentric fragments (0.20 % v. 0.90%). The increased percentage of aberrations found among pan chewers is significantly higher when compared to that of the controls. Isochromatid aberrations also increased significantly such as gaps (0.12 % v. 0.97%) breaks (0.07 % v. 0.80%), acentric fragments (0.05 % v. 0.23%), dicentrics (0.02 % v. 0.63%), and these were estimated in th

An Additive Order And Privacy Preserving Function Family (AOPPF)

The plentiful benefits of cloud computing, for privacy concerns, individuals and enterprise users are disinclined to outsource their susceptible data, including emails, personal health records and government confidential files, to the cloud. This is as once sensitive data are outsourced to a inaccessible cloud, the analogous data owners lose direct control of these data. We identify a multi-owner model for privacy preserving keyword search over encrypted cloud data. We recommend an capable data user , which not only prevents attackers from eavesdropping secret keys and imaginary to be illegal data users performing searches, but also facilitate data user certification and revocation.

An Additive Order and Privacy Preserving Function Family (AOPPF)

The abundant advantages of cloud computing, for protection concerns, people and venture clients are reluctant to outsource their  susceptible data, including E- mail, individual health records and government private documents, to the cloud. This is as once touchy information are outsourced to a blocked off cloud, the practically equivalent to information proprietors lose coordinate control of these information. We recognize a multi-proprietor show for protection saving watchword look over encoded cloud information. We suggest a fit information client , which not just keeps aggressors from listening in mystery keys and nonexistent to be unlawful information clients performing seeks, additionally encourage information client confirmation and disavowal.

Bio Characterization via FTIR and GCMS Analysis of Cucurbita variety (Yellow and White Pumpkin)

The current study aimed to conduct phytochemical screening, FTIR, and GCMS analysis in squash (Cucurbita pepo L.,) also known as a yellow and white selected pumpkin. It’s one of the dicotyledonous vegetables consumed in daily diets that imparts high inhibitor properties of inflammation, cancer, and diabetes. Traditionally it is used as an anti-helminthic remedy. The phytochemical characterization can facilitate seeking out the substance with a therapeutic property. The peel, flesh, and seed sample of each pumpkin variety were used as sources and extracted consecutively with ethyl acetate and acetonitrile using the maceration method. Phytochemical screening and quantification were carried out by standard analytical methods. The functional groups of the sample extracts were analyzed using FT-IR methods. Further, phytochemical profiling was carried out utilizing the GCMS technique to identify the therapeutically important chemicals contained in the sample. Phytochemical analysis of ethyl acetate and acetonitrile extracts showed the presence of major components like alkaloids, phenol, carbohydrate, and proteins. The farthest alkaloid, phenol, carbohydrate, and protein varied consequently for different parts like peel, flesh, and seed. The FT-IR analysis of each extract in the peel, flesh, and seed revealed that the ethyl acetate extract had the most functional groups. The major peak was characterized at wavelength 3004.24 to 3421.05 nm which indicates O-H functional group. Further quantification and GC-MS analysis were performed in ethyl acetate extract. Remarkably, GC-MS analysis of yellow and white pumpkin ethyl acetate extracts showed the utmost 6 - 8 compounds within the flesh part. Further, employing these compounds for anti-inflammatory and anti-microbial assays may aid in the discovery of new drugs for therapeutic applications

Free vibration analysis of a discretized aircraft with an integrated biodynamic pilot model – modal approach

This work deals with the formulation of mathematical model for a discretized aircraft with combined seated biodynamic pilot model. The developed model provides scope for exploring the dynamic characteristics of the aircraft system and pilot under various runway operations and landing impacts. Modal analysis approach is used to obtain the free vibration characteristics of multi degrees-of-freedom system. The obtained results like natural frequencies, mode shapes and undamped response curves are reported

Effect of gas flow on electronic transport in a DNA-decorated carbon nanotube

We calculate the two-time current correlation function using the experimental data of the current-time characteristics of the Gas-DNA-decorated carbon nanotube field effect transistor. The pattern of the correlation function is a measure of the sensitivity and selectivity of the sensors and suggest that these gas flow sensors may also be used as DNA sequence detectors. The system is modelled by a one-dimensional tight-binding Hamiltonian and we present analytical calculations of quantum electronic transport for the system using the time-dependent nonequilibrium Green's function formalism and the adiabatic expansion. The zeroth and first order contributions to the current $I^{(0)}(\bar{t})$ and $I^{(1)}(\bar{t})$ are calculated, where $I^{(0)} (\bar{t})$ is the Landauer formula. The formula for the time-dependent current is then used to compare the theoretical results with the experiment.Comment: 14 pages, 5 figures and 2 table

Detection of Residues of Cardenolides of Nerium oleander by High-Performance Thin-Layer Chromatography in Autopsy Samples

Background: Nerium oleander is an evergreen shrub of Apocynaceae family cultivated worldwide as an ornamental plant. All parts of the plant are toxic and contain a mixture of very toxic cardiac glycosides of cardenolides. A number of techniques were used to determine the cardenolides of N.oleander in various biological matrices. A survey of literature has revealed that the use of high-performance thin-layer chromatography (HPTLC) for the detection of oleander glycosides is very scanty. Method: A simple and rapid HPTLC method for separation and identification of cardenolides of N.oleander is reported. The cardenolides present in the aerial parts of the plant and residues available in the autopsy samples sent in cases of poisoning; were extracted with chloroform by using accelerated solvent extractor (ASE). Results: Separation of cardenolides was achieved on precoated silica gel 60F254 HPTLC plates with chloroform-acetone-acetic acid 8.5:1:0.5 (v/v) as mobile phase and densitometric analysis was carried out at 275 nm. A comprehensive study for the separation and detection of cardenolides in general and oleandrin in particular were studied by new mobile phases and spray reagents. The 1H-NMR spectra were recorded for the separated components and the component corresponding to oleandrin was identified. Conclusion: The method has specific advantages that it is simple, rapid and has higher resolution of separation achieved so as to be free from interferences from the plant and forensic matrices

Towards Learning and Explaining Indirect Causal Effects in Neural Networks

Recently, there has been a growing interest in learning and explaining causal effects within Neural Network (NN) models. By virtue of NN architectures, previous approaches consider only direct and total causal effects assuming independence among input variables. We view an NN as a structural causal model (SCM) and extend our focus to include indirect causal effects by introducing feedforward connections among input neurons. We propose an ante-hoc method that captures and maintains direct, indirect, and total causal effects during NN model training. We also propose an algorithm for quantifying learned causal effects in an NN model and efficient approximation strategies for quantifying causal effects in high-dimensional data. Extensive experiments conducted on synthetic and real-world datasets demonstrate that the causal effects learned by our ante-hoc method better approximate the ground truth effects compared to existing methods