Mutation in Archain 1, a Subunit of COPI Coatomer Complex, Causes Diluted Coat Color and Purkinje Cell Degeneration

Intracellular trafficking is critical for delivering molecules and organelles to their proper destinations to carry out normal cellular functions. Disruption of intracellular trafficking has been implicated in the pathogenesis of various neurodegenerative disorders. In addition, a number of genes involved in vesicle/organelle trafficking are also essential for pigmentation, and loss of those genes is often associated with mouse coat-color dilution and human hypopigmentary disorders. Hence, we postulated that screening for mouse mutants with both neurological defects and coat-color dilution will help identify additional factors associated with intracellular trafficking in neuronal cells. In this study, we characterized a mouse mutant with a unique N-ethyl-N-nitrosourea (ENU)–induced mutation, named nur17. nur17 mutant mice exhibit both coat-color dilution and ataxia due to Purkinje cell degeneration in the cerebellum. By positional cloning, we identified that the nur17 mouse carries a T-to-C missense mutation in archain 1 (Arcn1) gene which encodes the δ subunit of the coat protein I (COPI) complex required for intracellular trafficking. Consistent with this function, we found that intracellular trafficking is disrupted in nur17 melanocytes. Moreover, the nur17 mutation leads to common characteristics of neurodegenerative disorders such as abnormal protein accumulation, ER stress, and neurofibrillary tangles. Our study documents for the first time the physiological consequences of the impairment of the ARCN1 function in the whole animal and demonstrates a direct association between ARCN1 and neurodegeneration

The role of platelets in the recruitment of leukocytes during vascular disease

Besides their role in the formation of thrombus during haemostasis, it is becoming clear that platelets contribute to a number of other processes within the vasculature. Indeed, the integrated function of the thrombotic and inflammatory systems, which results in platelet-mediated recruitment of leukocytes, is now considered to be of great importance in the propagation, progression and pathogenesis of atherosclerotic disease of the arteries. There are three scenarios by which platelets can interact with leukocytes: (1) during haemostasis, when platelets adhere to and are activated on sub-endothelial matrix proteins exposed by vascular damage and then recruit leukocytes to a growing thrombus. (2) Platelets adhere to and are activated on stimulated endothelial cells and then bridge blood borne leukocytes to the vessel wall and. (3) Adhesion between platelets and leukocytes occurs in the blood leading to formation of heterotypic aggregates prior to contact with endothelial cells. In the following review we will not discuss leukocyte recruitment during haemostasis, as this represents a physiological response to tissue trauma that can progress, at least in its early stages, in the absence of inflammation. Rather we will deal with scenarios 2 and 3, as these pathways of platelet–leukocyte interactions are important during inflammation and in chronic inflammatory diseases such as atherosclerosis. Indeed, these interactions mean that leukocytes possess means of adhesion to the vessel wall under conditions that may not normally be permissive of leukocyte–endothelial cell adhesion, meaning that the disease process may be able to bypass the regulatory pathways which would ordinarily moderate the inflammatory response

Improving the Classification Accuracy of Fragmented Cropland by using an Advanced Classification Algorithm

&amp;lt;p&amp;gt;Fragmented crop land and marginal landholdings play an important role to classify the landuse and adopt different cropping and management practices. Here the implementation crop classification algorithms are very much difficult and produce results with lower accuracy. Static imagery captured in the optical bands are often contaminated with cloud cover and fail to detect the phenological as well as the structural changes happening during the crop growth. This is very common and most typical in Indian climatic condition. Here, during monsoon period capturing temporal satellite images of the crop periods is a very challenging task. Therefore, the present study aims at application of a novel crop classification algorithm that utilizes the temporal patterns of synthetic aperture radar (SAR) datasets from Sentinel-1 in mapping of landuse of an agriculture system, that is fragmented, small and heterogeneous in nature. Here we used different polarization of Sentinel-1 datasets and developed the temporal crop patterns of different crops grown in semi-arid region of India. Further, an advanced classification algorithm such as time weighted dynamic time wrapping (TWDTW) is employed to classify the cropland with a higher accuracy. Pixel based image analysis was carried out and tested their applicability for cropland mapping. In-situ data sets are collected from the study site to validate the exhibited results from classification outputs. The overall accuracy of the pixel based TWDTW method performed very good results with accuracy of 63 %. The Kappa coefficient is found to be 0.58. The findings confirmed that the pixel based TWDTW algorithm has the potential to delineate the croplands, which were subjected to varying irrigation treatments and management practices, using sentinel-1 datasets.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;Keywords:&amp;lt;/strong&amp;gt; crop classification, landuse, image analysis, Sentinel-1, TWDTW&amp;lt;/p&amp;gt;</jats:p

Technological Relationship Between Banknifty and Other Selected Sectorial Indices of NSE

Financial market of a country signifies the monetary strength of its economy. Smart monetary health of a rustic helps in enhancing the money flows and creates capital, that contributes to the event of the country. Post economic process innovate India he monetary market has entered into a replacement phase of worldwide integration and alleviation with variety of recent and innovative monetary instruments. The objective of the is to find the nature and extent of technical relationship between Nifty Bank on other selected sectorial indices of National Stock Exchange and to examine the risk and return factors of the sectorial indices. The major use of stock market indices are as a forecasting tool. Studying the historical performance of the stock market indices, you can forecast trends in the market. All the sectors of NSE are not considered in this study. Only five sectors other than bank nifty are considered. Six different sectors are compared individually with the Nifty Bank by the tools called correlation and Regression. Correlation and regression between the indices has been used to identify the relationship and extent of impact between Nifty Bank and other selected sectorial indices. From the results and findings of this study, one can understand that there is a significant relationship between Bank Nifty and other selected sectors (Energy, FMCG, IT, Media, Pharma) except Infrastructure. It is showing a poor relationship with Bank Nifty.</jats:p