Influence of Aerobic Training and Selected Asanas Modulates Serum Lipds and Lipoproteins in Young Obese Males

Abstract The aim of the study was to analyze the effect of aerobic training and selected asanas on serum lipids and lipoproteins in young obese men.  To achieve the purpose, sixty obese male students were selected randomly from different faculties of Annamalai University, and their age ranges between 18 to 25 years. Selected subjects were classified into three groups with twenty members of each. Group 1 served as control, Group 2 act as aerobic training and Group 3 as asanas training group. Exercise training such as aerobic exercise and selected asanas were given to the experimental training groups for a period of three months (4 days/ week) whereas the control group was given no special training other than regular activities.  Blood samples were collected before and after the completion of full training course. Biochemical analyses were done on serum lipids (total cholesterol, triglycerides, free fatty acids and total phospholipids) and plasma lipoproteins (VLDL, LDL and HDL) to find out the significant effect of training on obese men. The data were collected and statistically analyzed using ANOVA and DMRT and they are significant at

Occurrence of Uranium in Groundwater from Cuddalore District Tamil Nadu Aided by Geospatial and Statistical Techniques

An attempt has been made to examine uranium distribution in groundwater from Cuddalore district, Tamil Nadu, India. Groundwater occurs under porous sedimentary, fractured, and weathered hard rock formations ranging in age from recent sediments to the oldest Archean formations. A total of 186 groundwater samples were collected during Pre- Monsoon (May) and Post-monsoon (January) and analyzed for major cations, anions, and uranium using standard procedures. Major anions and cations follow the order Cl- >H4SiO4>HCO3- >NO3- > Na+> Ca2+> Mg2+>K+>SO42- > F-> PO43- irrespective of seasons. Uranium in groundwater ranges from 0.1 micro gram per liter (µg/l ) to 24.67 µg/l with average 1.82 µg/l. The spatial representation maps isolated areas of higher and lower uranium and statistical analysis inferred uranium sources to the groundwater environment

Review of Hybrid Wind-Solar PV Technology in the Generation of Electricity

Achieving sustainability by utilizing alternative energy sources viable technological possibilities for creating sustainable energy, the sun, biomass, wind, geothermal resources, hydropower, and ocean resources are considered. Despite the fact that the total amount of energy produced by PV cells and wind turbines is still far less than that of fossil fuels, their ability to generate electricity has significantly expanded in recent years. This article provides an overview of the Solar-Wind hybrid power system, which generates electricity by combining the Sun and Wind, two renewable energy sources. Microcontrollers are widely used in the field of system management. We can maximize the utilization of those resources by employing this strategy, which takes into account the distinct production processes of each resource. Furthermore, it increases dependability and decreases reliance on any single input. This hybrid solar-wind power generation system is suitable for both industrial and residential applications

A glossy mutant in onion (Allium cepa L.) shows decreased expression of wax biosynthesis genes

Cuticular wax is a characteristic feature of land plants that provides protection against both biotic and abiotic stresses. In this study, a glossy mutant lacking an epicuticular wax layer was identified in the γ-irradiated M2 mutant population of the onion cultivar Bhima Super. The inheritance of the mutant’s glossy phenotype was determined to be recessive and single locus. Scanning electron microscopy analysis showed poor accumulation of wax crystals in the glossy mutant, concentrated near the stomata. The plant height, number of leaves per plant, and stomatal parameters of the mutant were similar to the wild-type. RNA-seq was used to comprehend the expression variations of waxy cuticle-related genes in the glossy mutant and its wild-type waxy cultivars. Differential gene expression analysis of the RNA-seq data revealed that the genes involved in wax biosynthesis, such as AcCER1, AcCER26, AcMAH1, and AcWSD1, were downregulated by 2.72, 1.74, 2.59 and 2.12-fold, respectively, in the glossy mutant respectively. The expression patterns of these four unigenes were validated using semi-quantitative RT-PCR. The glossy mutant displayed a substantial 3.5-fold reduction in cuticular wax load compared to the wild-type due to the significant downregulation of these wax biosynthesis genes. These findings represent early advancements in understanding the molecular mechanisms of wax biosynthesis in onions. Furthermore, they provide a foundation for utilizing the glossy mutant trait in breeding programmes to enhance stress and pest resilience

Nonlinear saturation of electrostatic waves: mobile ions modify trapping scaling

The amplitude equation for an unstable electrostatic wave in a multi-species Vlasov plasma has been derived. The dynamics of the mode amplitude $\rho(t)$ is studied using an expansion in $\rho$; in particular, in the limit $\gamma\rightarrow0^+$, the singularities in the expansion coefficients are analyzed to predict the asymptotic dependence of the electric field on the linear growth rate $\gamma$. Generically $|E_k|\sim \gamma^{5/2}$, as $\gamma\rightarrow0^+$, but in the limit of infinite ion mass or for instabilities in reflection-symmetric systems due to real eigenvalues the more familiar trapping scaling $|E_k|\sim \gamma^{2}$ is predicted.Comment: 13 pages (Latex/RevTex), 4 postscript encapsulated figures which are included using the utility "uufiles". They should be automatically included with the text when it is downloaded. Figures also available in hard copy from the authors ([email protected]

CyclinPred: A SVM-Based Method for Predicting Cyclin Protein Sequences

Functional annotation of protein sequences with low similarity to well characterized protein sequences is a major challenge of computational biology in the post genomic era. The cyclin protein family is once such important family of proteins which consists of sequences with low sequence similarity making discovery of novel cyclins and establishing orthologous relationships amongst the cyclins, a difficult task. The currently identified cyclin motifs and cyclin associated domains do not represent all of the identified and characterized cyclin sequences. We describe a Support Vector Machine (SVM) based classifier, CyclinPred, which can predict cyclin sequences with high efficiency. The SVM classifier was trained with features of selected cyclin and non cyclin protein sequences. The training features of the protein sequences include amino acid composition, dipeptide composition, secondary structure composition and PSI-BLAST generated Position Specific Scoring Matrix (PSSM) profiles. Results obtained from Leave-One-Out cross validation or jackknife test, self consistency and holdout tests prove that the SVM classifier trained with features of PSSM profile was more accurate than the classifiers based on either of the other features alone or hybrids of these features. A cyclin prediction server- CyclinPred has been setup based on SVM model trained with PSSM profiles. CyclinPred prediction results prove that the method may be used as a cyclin prediction tool, complementing conventional cyclin prediction methods

Inhibition of protein ubiquitination by paraquat and 1-methyl-4-phenylpyridinium impairs ubiquitin-dependent protein degradation pathways

Intracytoplasmic inclusions of protein aggregates in dopaminergic cells (Lewy bodies) are the pathological hallmark of Parkinson’s disease (PD). Ubiquitin (Ub), alpha [α]-synuclein, p62/sequestosome 1 and oxidized proteins are major components of Lewy bodies. However, the mechanisms involved in the impairment of misfolded/oxidized protein degradation pathways in PD are still unclear. PD is linked to mitochondrial dysfunction and environmental pesticide exposure. In this work, we evaluated the effect of the pesticide paraquat (PQ) and the mitochondrial toxin 1-methyl-4-phenylpyridinium (MPP+) on Ub-dependent protein degradation pathways. No increase in the accumulation of Ub-bound proteins or aggregates was observed in dopaminergic cells (SK-N-SH) treated with PQ or MPP+, or in mice chronically exposed to PQ. PQ decreased Ub protein content, but not its mRNA transcription. Protein synthesis inhibition with cycloheximide depleted Ub levels and potentiated PQ–induced cell death. Inhibition of proteasomal activity by PQ was found to be a late event in cell death progression, and had no effect on either the toxicity of MPP+ or PQ, or the accumulation of oxidized sulfenylated, sulfonylated (DJ-1/PARK7 and peroxiredoxins) and carbonylated proteins induced by PQ. PQ- and MPP+-induced Ub protein depletion prompted the dimerization/inactivation of the Ub-binding protein p62 that regulates the clearance of ubiquitinated proteins by autophagic. We confirmed that PQ and MPP+ impaired autophagy flux, and that the blockage of autophagy by the overexpression of a dominant-negative form of the autophagy protein 5 (dnAtg5) stimulated their toxicity, but there was no additional effect upon inhibition of the proteasome. PQ induced an increase in the accumulation of α-synuclein in dopaminergic cells and membrane associated foci in yeast cells. Our results demonstrate that inhibition of protein ubiquitination by PQ and MPP+ is involved in the dysfunction of Ub-dependent protein degradation pathways

Prediction of Surface Roughness Using Artificial Neural Network in Single Point Diamond Turning

In manufacturing industries, manufacturers focused on the quality and productivity of the product. To increase the productivity of the product, computer numerically machine tools have been implemented during the past decades. Surface roughness is one of the most important parameters to determine the quality of product. The mechanism behind the formation of surface roughness is very dynamic, complicated, and process dependent. Several factors will influence the final surface roughness in a Diamond turning operations such as controllable factors (spindle speed, feed rate and depth of cut) and uncontrollable factors (tool geometry and material properties of both tool and work piece). Some of the machine operator using trial and error method to set-up machine cutting conditions. This method is not much effective and efficient and the achievement of a desirable value is a repetitive and empirical process that can be very time consuming. In order to solve the problem, a surface prediction technique based on artificial neural network prediction models is developed to predict the machining response for different input machining parameters. Thus, manufacturers can improve the quality and productivity of the product with minimum cost and time

Correlation for oil yield in sunflower (Helianthus annus.L)

Fifty five hybrids of sunflower were selected for the character association study to assess the relationship among yield and itscomponents. Observations were recorded on nine traits viz., 50% flowering, days to maturity, plant height, head diameter, 100-seed weight, volume weight, oil content, oil yield per plant and seed yield per plant. Character association analysis revealed strongpositive association of oil yield per plant with days to maturity, 100_seed weight, volume weight, oil content and seed yield perplant. Hence simultaneous selection of these characters would contribute for the improvement of the oil yield per plant