Manipal University

About: Manipal University is a education organization based out in Manipal, Karnataka, India. It is known for research contribution in the topics: Population & Health care. The organization has 9525 authors who have published 11207 publications receiving 110687 citations.

Sesamol Treatment Reduces Plasma Cholesterol and Triacylglycerol Levels in Mouse Models of Acute and Chronic Hyperlipidemia

Abstract: The active constituents of Sesamum indicum, sesamin and sesamolin, have already been explored for hypolipidemic action. In this study we have explored the anti-dyslipidemic activity of another active component and metabolite of sesamolin (sesamol), by using acute models of hyperlipidemia viz., a fat tolerance test, a tyloxapol-induced hyperlipidemia model and a chronic model of hyperlipidemia viz., a high-fat diet-induced hyperlipidemia model in Swiss albino mice. Sesamol (100 and 200 mg/kg) significantly (P < 0.05) decreased triacylglycerol absorption in the fat tolerance test by showing a dose-dependent decrease in triacylglycerol levels. The hypolipidemic effect of sesamol at 200 mg/kg was equivalent to 10 mg/kg of orlistat. In the tyloxapol-induced hyperlipidemia model, Sesamol at 200 mg/kg reversed the elevated levels of cholesterol and triacylglycerol compared with the tyloxapol group at 12 and 24 h, which indicates its probable effect on cholesterol synthesis. Chronic hyperlipidemia in mice was produced by feeding a high-diet, a mixture of cholesterol (2 % w/w), cholic acid (1 % w/w) and coconut oil 30 % (v/w) with standard powdered standard animal chow (up to 100 g). Niacin (100 mg/kg) and sesamol (100 mg/kg) significantly (P < 0.05) reduced the elevated body weight compared with the high fat diet control group. Elevated levels of cholesterol and triacylglycerol were significantly (P < 0.05) reversed by the sesamol (50 and 100 mg/kg), implying that it might reduce the absorption and increase the excretion of cholesterol as well.

Quantitative temporal proteomic analysis of human embryonic stem cell differentiation into oligodendrocyte progenitor cells.

Abstract: Oligodendrocytes (OLs) are glial cells of the central nervous system, which produce myelin. Cultured OLs provide immense therapeutic opportunities for treating a variety of neurological conditions. One of the most promising sources for such therapies is human embryonic stem cells (ESCs) as well as providing a model to study human OL development. For these purposes, an investigation of proteome level changes is critical for understanding the process of OL differentiation. In this report, an iTRAQ-based quantitative proteomic approach was used to study multiple steps during OL differentiation including neural progenitor cells, glial progenitor cells and oligodendrocyte progenitor cells (OPCs) compared to undifferentiated ESCs. Using a 1% false discovery rate cutoff, ∼3145 proteins were quantitated and several demonstrated progressive stage-specific expression. Proteins such as transferrin, neural cell adhesion molecule 1, apolipoprotein E and wingless-related MMTV integration site 5A showed increased expression from the neural progenitor cell to the OPC stage. Several proteins that have demonstrated evidence or been suspected in OL maturation were also found upregulated in OPCs including fatty acid-binding protein 4, THBS1, bone morphogenetic protein 1, CRYAB, transferrin, tenascin C, COL3A1, TGFBI and EPB41L3. Thus, by providing the first extensive proteomic profiling of human ESC differentiation into OPCs, this study provides many novel proteins that are potentially involved in OL development.

Multi-Modal Medical Image Fusion With Adaptive Weighted Combination of NSST Bands Using Chaotic Grey Wolf Optimization

Abstract: Recently, medical image fusion has emerged as an impressive technique in merging the medical images of different modalities. Certainly, the fused image assists the physician in disease diagnosis for effective treatment planning. The fusion process combines multi-modal images to incur a single image with excellent quality, retaining the information of original images. This paper proposes a multi-modal medical image fusion through a weighted blending of high-frequency subbands of nonsubsampled shearlet transform (NSST) domain via chaotic grey wolf optimization algorithm. As an initial step, the NSST is applied on source images to decompose into the multi-scale and multi-directional components. The low-frequency bands are fused based on a simple max rule to sustain the energy of an individual. The texture details of input images are preserved by an adaptively weighted combination of high-frequency images using a recent chaotic grey wolf optimization algorithm to minimize the distance between the fused image and source images. The entire process emphasizes on retaining the energy of the low-frequency band and the transferring of texture features from source images to the fused image. Finally, the fused image is formed using inverse NSST of merged low and high-frequency bands. The experiments are carried out on eight different disease datasets obtained from Brain Atlas, which consists of MR-T1 and MR-T2, MR and SPECT, MR and PET, and MR and CT. The effectiveness of the proposed method is validated using more than 100 pairs of images based on the subjective and objective quality assessment. The experimental results confirm that the proposed method performs better in contrast with the current state-of-the-art image fusion techniques in terms of entropy, VIFF, and FMI. Hence, the proposed method will be helpful for disease diagnosis, medical treatment planning, and surgical procedure.