Assessment of DNA Damage in Peripheral Blood of Tobacco Users

The smokeless tobacco has a physical powerful association with the risk of oral leukoplakia, oral submucous fibrosis, Oral squamous cell carcinoma and Squamous cell carcinoma of the head and neck. ST components exhibit genotoxicity and may alter the structure of DNA, proteins and lipids, resulting in the production of antigenicity. Present study was carried out to investigate the effects of chewing tobacco (CT) with smoking on lymphocyte DNA damage. After signing a consent form, volunteers provided blood samples (76 samples from including experimental and control subjects) to establish SCGE (comet).  Statistically significant results were obtained in experimental subjects when compared to controls. However association found with smoking had significant effect, and it can induce maximum amount of DNA damage. The genotoxic effect of chewing tobacco (CT) should be considered in addition to other known hazards for assessing health risks

DWT Feature Extraction Based Face Recognition using Intensity Mapped Unsharp Masking and Laplacian of Gaussian Filtering with Scalar Multiplier

AbstractFace recognition under varying illumination and poses at certain angles is challenging, and hence improved edge prominence and contrast enhancement techniques are an effective approach to solve this problem. This paper proposes two novel techniques, namely, Intensity Mapped Unsharp Masking (IMUM) which provides a much finer outline of the face image by reducing the background intensity, and Laplacian of Gaussian based filtering with Scalar Multiplier (LOGSM) which provides an improved edge detection. Individual stages of the FR System are examined and an attempt is made to improve each stage. A Binary Particle Swarm Optimization (BPSO) based feature selection algorithm is used to search the feature vector space for the optimal feature subset. Experimental results, obtained by applying the proposed algorithm on ORL, UMIST, Extended YaleB, ColorFERET face databases, show that the proposed system outperforms other FR systems. A significant increase in the overall recognition rate and a substantial reduction in the selected features are observed

Incorporation of coconut milk residue in pasta: Influence on cooking quality, sensory and physical properties

A study was conducted to explore the potentiality of coconut milk residue (CMR) for cold extrusion (pasta preparation). Proximate analysis revealed that coconut milk residue is a rich source of crude fibre (24.03%) in addition to crude fat (41.55%), crude protein (5%), total carbohydrates (26.24%) and ash content (0.97%) at 2.23 per cent moisture. The effect of coconut milk residue upon replacing durum wheat semolina on cooking qualities, colour parameters, textural property and overall sensory acceptability of pasta samples were evaluated. Incorporation of coconut milk residue significantly influenced the observed parameters (P<0.01). Cooking time was unaffected by incorporating milk residue up to 10 per cent (P<0.05). Though the addition of residue increased the gruel loss (0.84 to 1.34%), the per cent loss was below the technologically acceptable limit (<8%). A similar effect was visualized in water absorption. Conversely, the firmness gets reduced with an increased concentration of coconut milk residue beyond 10 per cent. Pasta with 5 per cent and 10 per cent coconut milk residue were accepted as that of control by the sensory panel. Free fatty acid content was not affected by the period of storage (P>0.05). Thus, the study recommends incorporating 10 per cent coconut milk residue in durum wheat semolina for pasta preparation. Moreover, the entrepreneurs engaged in the coconut milk/milk powder and virgin coconut oil industry would be benefitted by adopting this venture, wherein they would be able to fetch huge additional income by placing their residue product on an upgraded fast-moving consumer good (FMCG) value chain

Parameter Identification in Nonlinear Mechanical Systems with Noisy Partial State Measurement Using PID-Controller Penalty Functions

Dynamic models of physical systems often contain parameters that must be estimated from experimental data. In this work, we consider the identification of parameters in nonlinear mechanical systems given noisy measurements of only some states. The resulting nonlinear optimization problem can be solved efficiently with a gradient-based optimizer, but convergence to a local optimum rather than the global optimum is common. We augment the dynamic equations with a morphing parameter and a proportional-integral-derivative (PID) controller to transform the objective function into a convex function; the global optimum can then be found using a gradient-based optimizer. The morphing parameter is used to gradually remove the PID controller in a sequence of steps, ultimately returning the model to its original form. An optimization problem is solved at each step, using the solution from the previous step as the initial guess. This strategy enables use of a gradient-based optimizer while avoiding convergence to a local optimum. The efficacy of the proposed approach is demonstrated by identifying parameters in the van der Pol-Duffing oscillator, a hydraulic engine mount system, and a magnetorheological damper system. Our method outperforms genetic algorithm and particle swarm optimization strategies, and demonstrates robustness to measurement noise

Impact of mannitol and poly ethylene glycol 6000 induced water deficit on plant biomass and major secondary metabolites in Centella asiatica (L.) Urb. in vitro

184-191Low water potential related stresses are regulated by modifying water uptake and loss to avoid low water potential, accumulating solutes which in turn enhance active principles and its gene expressions. Present study examined effect of in vitro induced absorption of mannitol and PEG (poly ethelene glycol) 6000 in Indian pennywort, Centella asiatica (L.) Urb., neutraceutical plant, evidenced by phenotypic, molecular and phytochemical analyses. Both mannitol and PEG 6000 induce water deficit conditions in plants and retarded normal plant biomass in terms of fresh and dry weights. These effects were significantly less severe in plants subjected to mannitol, compared to PEG. PEG and mannitol imposed water deficit, resulted in decline in major active compound, asiaticoside evidenced by HPTLC of asiaticoside content. Differential expression of some selected key genes in the asiaticoside pathway including squalene synthase and β amyrin synthase by qPCR, confirmed decrease in transcript level expression of asiaticoside, whereas upregulated transcript level expression was observed in cycloartenol synthase for synthesis of phytosterols. Estimation of total flavonoids and phenolics under different water deficit conditions were found declined. In conclusion, water deficit by mannitol and PEG 6000 can significantly affects processes associated with biomass growth and ability to synthesize secondary metabolites in C. asiatica

Phytochemicals as weapons against drug resistance

Phytochemicals are plant-based products with high medicinal value. These metabolites effectively target disease-causing microbes. Drug-resistant pathogens have developed mechanisms to sustain themselves even with inhibitors. Drug resistance has emerged as a global giant, causing all available treatment options to fail. The solution to this problem is in the phytochemicals of plants with antibacterial and drug resistance modulation properties. Phytochemicals might be able to get rid of efflux pumps, drug-modulating enzymes, resistance genes, quorum sensing, and biofilm, all of which cause pathogens to be resistant to drugs. Moreover, anti-obesogenic and cardioprotective properties are also observed in phytochemicals. Additionally, studies show the success of phytochemical-based nanoparticles in drug resistance regulation. This review emphasizes phytochemicals' different mechanisms of action and their derivatives in curbing drug-resistant pathogens and cancer cells

Physical properties of tender coconut

Not AvailableThe physical properties such as tender coconut size, weight, husk thickness, and husk moisture tender content play a vital role in the development of an efficient and ergonomic trimming machine. The important physical properties of tender coconuts of cultivars namely Kulasekaran Green Dwarf (KGD), Andaman Giant Tall (AGT), Ganga Bondam (GB), Malayan Orange Dwarf (MOD), and Chowghat Orange Dwarf (COD) were determined. The important properties including weight, diameter, height, husk thickness, husk moisture content, shell diameter, shell height, and shell thickness were high for nuts of AGT and low for COD nuts. The average bulk density, true density, and porosity of AGT were 332.47 kg m−3, 1,196.67 kg m−3, and 72.21%, respectively. The husk weight and volume of water of AGT were 87.77% and 12.39% high, respectively, compared with COD. In the correlation study, the coconut weight correlated positively (r = 0.791) with the diameter and vertical distance between the shell and the fruit base (r = 0.813). The principal component analysis suggested that the cultivars GB, KGD, and MOD have similar physical properties to COD and AGT. Thus, the present investigation documents crucial basic information to design an efficient and superior tender coconut trimming machine.ICA