Defective protein folding and accumulation of misfolded proteins is associated with neurodegenerative, cardiovascular, secretory, and metabolic disorders. Efforts are being made to identify small-molecule modulators or structural-correctors for conformationally destabilized proteins implicated in various protein aggregation diseases. Using a metastable-reporter-based primary screen, we evaluated pharmacological chaperone activity of a diverse class of natural products. We found that a flavonoid glycoside ( C-10 , chrysoeriol-7-O-β-D-glucopyranoside) stabilizes metastable proteins, prevents its aggregation, and remodels the oligomers into protease-sensitive species. Data was corroborated with additional secondary screen with disease-specific pathogenic protein. In vitro and cell-based experiments showed that C-10 inhibits α-synuclein aggregation which is implicated in synucleinopathies-related neurodegeneration. C-10 interferes in its structural transition into β-sheeted fibrils and mitigates α-synuclein aggregation-associated cytotoxic effects. Computational modeling suggests that C-10 binds to unique sites in α-synuclein which may interfere in its aggregation amplification. These findings open an avenue for comprehensive SAR development for flavonoid glycosides as pharmacological chaperones for metastable and aggregation-prone proteins implicated in protein conformational diseases. 相似文献
Present paper reports the synthesis of nanostructured (Sn–Ti)O2 via physicochemical method, its characterization and performance as liquefied petroleum gas (LPG) sensor. The synthesized material was characterized using XRD that confirmed the formation of (Sn–Ti)O2 nanocomposite. Minimum crystallite size was found as 7 nm. The material was also investigated through SEM, DSC, FTIR, PL and UV–Vis spectrophotometer. Further, the pellet, thick and thin films were fabricated for the sensing analysis. Pellets (9 mm diameter, 4 mm thickness) of (Sn–Ti)O2 nanocomposite were made by hydraulic pressing machine by applying uniaxial pressure of 616 MPa, thick films (thickness ~2 µm) were made by screen printing technique and thin films were prepared using a Photo resist spinner unit. Further at room temperature, the pellet and films were exposed to LPG in a gas chamber under controlled conditions at room temperature and variations in resistance with the concentrations of LPG were observed. The maximum value of sensitivity of solid state pellet, thick and thin films based sensors were found 7, 9 and 39 for 5 vol% of LPG, respectively. Sensing characteristics were found to be reproducible, after 6 months of their fabrication, indicating the stability of the sensors. 相似文献
Multimedia Tools and Applications - This paper presents an efficient hybrid DWT-DCT based illumination normalization technique for face recognition. In a face image, illumination usually changes... 相似文献
The aim of this research was to exploit the chemical properties of natural products to control the incidence and extent of mould growth in houses. The screening of antimould activities of seven essential oil extracts showed that most of the extracts completely inhibited the growth of all three test mould at the concentration of 1% w/v on nutrient medium, whereas, different fractions of manuka oil showed varied activity. Subsequently, using both mycological and scanning electron microscopy, the testing of selected extracts on two different types of gypsum board finished with either paint or wall-paper, confirmed the antimould activity of eugenol, thymol and cinnamaldehyde against Penicillium corylophilum. This study identified certain essential oil extract as a potential mould inhibitor for panel products which is one of the most common mould habitats in the building environment. Mould growth in residential houses is a major concern and chemical fungicides commonly used to control the growth of mould are not often appropriate for indoor applications. Natural alternatives such as essential oils are desirable for this application. Knowledge gained through this research should lead to new niche panel product development to create healthier housing. 相似文献
Three drying technologies [i.e., vacuum belt drying (VBD), hot air drying (HAD), and freeze drying (FD)] were evaluated for the processing of muscadine pomace in terms of their impact on drying time requirement, moisture content (MC), water activity (aw), total phenolics content (TPC), and antioxidant activity (AA). Muscadine pomace discs of two thicknesses (2 and 4 mm) were dried using 16 different time-temperature combinations for VBD, 12 different time-temperature and air velocity combinations for HAD, and one treatment for FD. The TPC and AA in lyophilised samples were 583 ± 8 and 608 ± 16 μmol GAE/g d.w. and 2.21 ± 0.15 and 2.30 ± 0.17 mmol Fe2+ E/g d.w. for the 2 and 4 mm thick discs, respectively. The VBD treatment of 60-80-100-100 °C for 60 min (i.e., TV2) for 2 mm thick discs showed the highest TPC value, and no significant (P > 0.05) differences were observed in AA of 2 mm thick discs dried by VDB and FD. The TPC and AA for the VBD treatment of 60-80-100-100 °C for 90 min and HAD treatment of 70 °C at 0.6 m/s for 3 h for the 2 mm thick discs were not significantly (P > 0.05) different compared to freeze dried samples. For 4 mm thick samples, the TPC and AA for the VBD treatments of 60-80-100-100 °C, 60-90-120-120 °C, 70-90-110-110 °C, 80-90-100-100 °C, and 90-105-120-120 °C for 90 min as well as 70-90-110-110 °C for 60 min were not significantly (P > 0.05) different compared to those for freeze dried discs. VBD is a promising drying technology, as the resultant products possessed high TPCs and were dried in less than ¼ of the time compared with that of FD. 相似文献
In recent times, the images and videos have emerged as one of the most important information source depicting the real time scenarios. Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane. The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition. One of the application fields pertains to detection of diseases occurring in the plants, which are destroying the widespread fields. Traditionally the disease detection process was done by a domain expert using manual examination and laboratory tests. This is a tedious and time consuming process and does not suffice the accuracy levels. This creates a room for the research in developing automation based methods where the images captured through sensors and cameras will be used for detection of disease and control its spreading. The digital images captured from the field's forms the dataset which trains the machine learning models to predict the nature of the disease. The accuracy of these models is greatly affected by the amount of noise and ailments present in the input images, appropriate segmentation methodology, feature vector development and the choice of machine learning algorithm. To ensure the high rated performance of the designed system the research is moving in a direction to fine tune each and every stage separately considering their dependencies on subsequent stages. Therefore the most optimum solution can be obtained by considering the image processing methodologies for improving the quality of image and then applying statistical methods for feature extraction and selection. The training vector thus developed is capable of presenting the relationship between the feature values and the target class. In this article, a highly accurate system model for detecting the diseases occurring in citrus fruits using a hybrid feature development approach is proposed. The overall improvement in terms of accuracy is measured and depicted. 相似文献
Pristine ZnO, Al-doped ZnO, and TiO2 coated ZnO nanoparticles (NPs) were synthesized by the wet chemical precipitation technique. All the synthesized NPs were characterized using X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), Transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy. XRD analysis of pristine ZnO and Al-doped ZnO NPs revealed the hexagonal wurtzite structure with P63mc space group with no secondary phases and impurities. FESEM micrographs also depicted hexagonal grains with well-defined grain boundaries. TEM images showed hexagonal polyhedral shape for pure ZnO NPs and spherical shape dominating polyhedral particle for Al-doped ZnO NPs, and pseudospherical particles for TiO2 coated ZnO NPs. Energy-dispersive X-ray spectroscopy of Al-doped ZnO indicates the eminent exchange of dopant in the lattice site of Zn. Dielectric Studies reveal the highest value of the dielectric constant and lowest value of dielectric loss for Al-doped ZnO as compared to pure and TiO2-coated ZnO NPs. Suggesting Al-doped ZnO to be used as a dielectric material that can serve as a basic building block of the energy storage devices such as dielectric capacitor. TiO2-coated ZnO NPs demonstrated higher AC conductivity in comparison to pure ZnO and Al-doped ZnO NPs suggesting their use as a conductive nanofiller materials in a polymer-based nanocomposite to achieve higher energy density.
This review describes recent progress made in the rapidly developing field of C H bond activation, in particular for syntheses of biaryls. The catalysts presented here provide convenient strategies for the direct arylation of arenes, via single or double C H bond activation, leading to inter‐, and intramolecular carbon‐carbon bond formation. The literature from mid‐2009 to December 2013 has been discussed.
Benzene, toluene, ethylbenzene and xylene (BTEX) form an important group of aromatic Volatile Organic Compounds (VOCs) because of their role in the tropospheric chemistry and the risk posed by them to human health. Concentrations of BTEX were determined at different sampling points in the ambient air of Delhi in order to investigate their temporal and spatial distributions. Significant positive correlation coefficient (p<0.01) was found between inter-species concentrations at all the sampling locations. Inter-species ratio and Pearson's correlations indicate that gasoline vehicular exhaust could be the major source of BTEX in Delhi. The inter-species ratios exhibit clear seasonal variations indicating differential reactivity of the VOC species in different seasons. Xylenes were found the largest contributor to the ozone formation followed by toluene. 相似文献