ATP dependent assembly of the human origin recognition complex

The Origin Recognition Complex (ORC) was initially discovered in budding yeast extracts as a protein complex that binds with high affinity to Autonomously Replicating Sequences (ARS) in an ATP dependent manner. We have cloned and expressed the human homologs of the ORC subunits as recombinant proteins. In contrast to other eukaryotic initiators examined thus far, assembly of human ORC in vitro is dependent on ATP binding. Mutations in the ATP binding sites of Orc4 or Orc5 impair complex assembly, whereas Orc1 ATP binding is not required. Immunofluorescence staining of human cells with anti-Orc3 antibodies demonstrate cell cycle-dependent association with a nuclear structure. Immunoprecipitation experiments show that ORC disassembles as cells progress through S phase. The Orc6 protein binds directly to the Orc3 subunit and interacts as part of ORC in vivo. These data suggest that the assembly and disassembly of ORC in human cells is uniquely regulated and may contribute to restricting DNA replication to once in every cell division cycle

Rural Credit and Rural Development: Some Issues

Credit plays an important role in acquiring command over the use of working capital, fixed capital, and consumption goods that leads to growth and development of a country. The paper investigates that the role of non-institutional sources is quite clearly borne out. The price paid for institutional credit in Pakistan Kept low by the government. Institutional credit reforms implemented has not been effective. There is a great need to have the land reforms prior to credit reforms. The importance of social and economic infrastructure needs to be addressed. Appropriate use of new credit should be assured. Proper credit policy be designed and implemented.

Seroprevalence Of Hepatitis-b Virus In Mid And Far Western Region In Nepal

Hepatitis B is significant health problems that might involve the late sequel of liver cirrhosis and hepatocellular carcinoma. The present study aimed to know the seroprevalence of hepatitis B virus (HBV) in mid and far western region in Nepal with various clinical conditions.This was a retrospective study conducted in mid and far western region in Nepal, which was performed in the Central Laboratory of Microbiology at Nepalgunj Medical College and Teaching Hospital, Banke, Nepal during the period of September 2010 to April 2012. The serum samples were tested for Hepatitis B surface Antigen (HBsAg) by Sandwich immunoassay. Total 7010 patients including 43.72% male and 56.28% female were tested for HBsAg. Of them, 135 were positive and 6875 were negative.In 135 positive cases 84 (62.22%) were male and 51 (37.77% )were female. In 6875 negative cases 2981 were male and 3894 were female. The seroprevalence rate of HBV was 1.93% in mid and far western region in Nepal. Seroprevalence of HBV seems to be higher in male then the female; it was 2.75% in male and 1.29% in female.The study revealed that the seroprevalence of HBV was alarmingly higher in such a population, which probably reflects a high background prevalence of HBV infections should be taken into consideration and Implementation of community-based preventive measures and improved strategies for safe blood supply might prove useful to decrease the seroprevalence

An Efficient Image Segmentation Approach through Enhanced Watershed Algorithm

Image segmentation is a significant task for image analysis which is at the middle layer of image engineering. The purpose of segmentation is to decompose the image into parts that are meaningful with respect to a particular application. The proposed system is to boost the morphological watershed method for degraded images. Proposed algorithm is based on merging morphological watershed result with enhanced edge detection result obtain on pre processing of degraded images. As a post processing step, to each of the segmented regions obtained, color histogram algorithm is applied, enhancing the overall performance of the watershed algorithm. Keywords – Segmentation, watershed, color histogra

Posttransplant Metabolic Syndrome

Metabolic syndrome (MS) is a cluster of metabolic derangements associated with insulin resistance and an increased risk of cardiovascular mortality. MS has become a major health concern worldwide and is considered to be the etiology of the current epidemic of diabetes and cardiovascular disease. In addition to cardiovascular disease, the presence of MS is also closely associated with other comorbidities including nonalcoholic fatty liver disease (NAFLD). The prevalence of MS in patients with cirrhosis and end-stage liver disease is not well established and difficult to ascertain. Following liver transplant, the prevalence of MS is estimated to be 44–58%. The main factors associated with posttransplant MS are posttransplant diabetes, obesity, dyslipidemia, and hypertension. In addition to developing NAFLD, posttransplant MS is associated with increased cardiovascular mortality that is 2.5 times that of the age- and sex-matched individuals. Additionally, the presence of posttransplant MS has been associated with rapid progression to fibrosis in individuals transplanted for HCV cirrhosis. There is an urgent need for well-designed prospective studies to fully delineate the natural history and risk factors associated with posttransplant MS. Until then, early recognition, prevention, and treatment of its components are vital in improving outcomes in liver transplant recipients

Accumulation and Effects of Dissolved and Nanoparticle Silver and Copper in Two Marine Seaweed Species

This study investigated the accumulation and effects of metal nanoparticles in two seaweed species, Ulva lactuca and Agardhiella subulata. Both seaweeds were exposed to silver nitrate (AgNO3), silver nanoparticles, and copper oxide (CuO) nanoparticles for 48 h. Metal accumulation occurred in both seaweed species in a concentration-dependent manner after 48 h exposure to each form of metal. In several cases, seaweeds exposed to AgNO3 (the dissolved form) accumulated comparatively higher tissue Ag concentration than seaweed exposed to Ag nanoparticles; and A. subulata had higher tissue Ag concentrations than U. lactuca after exposure to AgNO3 for 48 h. Additionally, clear differences were observed in the regulation of Ag between the two seaweed species. Photosynthetic toxicity (primarily due to decreased maximum electron transport rate) was observed in U. lactuca after exposure to AgNO3, Ag nanoparticles, and CuO nanoparticles. These results increase current knowledge about the differences in dissolved metal versus nanoparticle exposure in marine seaweeds and have implications in marine food webs

An investigation of a deep learning based malware detection system

We investigate a Deep Learning based system for malware detection. In the investigation, we experiment with different combination of Deep Learning architectures including Auto-Encoders, and Deep Neural Networks with varying layers over Malicia malware dataset on which earlier studies have obtained an accuracy of (98%) with an acceptable False Positive Rates (1.07%). But these results were done using extensive man-made custom domain features and investing corresponding feature engineering and design efforts. In our proposed approach, besides improving the previous best results (99.21% accuracy and a False Positive Rate of 0.19%) indicates that Deep Learning based systems could deliver an effective defense against malware. Since it is good in automatically extracting higher conceptual features from the data, Deep Learning based systems could provide an effective, general and scalable mechanism for detection of existing and unknown malware.Comment: 13 Pages, 4 figure