Spectrophotometric Determination of Amines by Cu(II)

544-54

Synthesis & Ion-exchange Properties of Niobium Selenite: Separation of La-Th, Th-Cu, Pb-Cd, Zn-Pb & La-Ce

754-75

Study of etiology, clinical profile and predictive factors of spontaneous bacterial peritonitis in cirrhosis of liver

Background: Spontaneous bacterial peritonitis (SBP) is one of the potentially lethal complication of liver cirrhosis and is defined as infected ascites in the absence of any recognizable secondary cause of infection. Majority of the SBP cases are caused by organism from the gastrointestinal tract mainly aerobic gram-negative organisms- Escherichia coli being the most common etiological agent.Methods: It was a prospective observational study done over a period of 1 year in a tertiary care hospital. 50 patients from medical and gastroenterology wards were included in the study. Patients above 12 year of age with diagnosed cirrhosis of liver and documented evidence of SBP were included. Pregnant females, patients who refused to give consent, patients with a documented evidence of intra-abdominal source of infection or patients with ascitis due to non-hepatic causes were excluded.Results: The high serum bilirubin and creatinine levels were associated with higher mortality rate. Hepatic encephalopathy is associated with worse outcome. The outcome of the patient in relation to the grades of ascitis, liver enzymes, prothrombin time, international normalised ratio (INR), Child pugh grades, ascitic fluid polymorphonuclear leucocyte count, ascitic fluid culture and blood culture were not statistically significant.Conclusions: A high index of suspicion should exist for SBP in patients with cirrhosis and ascitis. Serum creatinine and bilirubin levels are strong predictors of mortality. Hepatic encephalopathy has a strong association with mortality in patients with spontaneous bacterial peritonitis

RASSF4: Regulator of plasma membrane PI(4,5)P2.

Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) is a negatively charged phospholipid that plays a major role in recruiting and regulating proteins at the plasma membrane-cytosol interface. In this issue, Chen et al. (2017. J. Cell Biol. https://doi.org/10.1083/jcb.201606047) demonstrate that RAS association domain family 4 (RASSF4) positively influences PI(4,5)P2 synthesis through ARF6-dependent regulation of PIP5K

Field induced magnetic transition and metastability in Co substituted Mn2SbMn_{2}Sb

A detailed investigation of first order ferrimagnetic (FRI) to antiferromagnetic (AFM) transition in Co (15%) doped $Mn_2Sb$ is carried out. These measurements demonstrate anomalous thermomagnetic irreversibility and glass-like frozen FRI phase at low temperatures. The irreversibility arising between the supercooling and superheating spinodals is distinguised in an ingenious way from the irreversibility arising due to kinetic arrest. Field annealing measurements shows reentrant FRI-AFM-FRI transition with increasing temperature. These measurements also show that kinetic arrest band and supercooling band are anitcorrelated i.e regions which are kinetically arrested at higher temperature have lower supercooling temperature and vice versa.Comment: 10 pages, 8 figure

Novel Implementation of Conditional Co-Regulation by Graph Theory to Derive Co-Expressed Genes from Microarray Data

BackgroundMost existing transcriptional databases like Comprehensive Systems-Biology Database (CSB.DB) and Arabidopsis Microarray Database and Analysis Toolbox (GENEVESTIGATOR) help to seek a shared biological role (similar pathways and biosynthetic cycles) based on correlation. These utilize conventional methods like Pearson correlation and Spearman rank correlation to calculate correlation among genes. However, not all are genes expressed in all the conditions and this leads to their exclusion in these transcriptional databases that consist of experiments performed in varied conditions. This leads to incomplete studies of co-regulation among groups of genes that might be linked to the same or related biosynthetic pathway. ResultsWe have implemented an alternate method based on graph theory that takes into consideration the biological assumption – conditional co-regulation is needed to mine a large transcriptional data bank and properties of microarray data. The algorithm calculates relationships among genes by converting discretized signals from the time series microarray data (AtGenExpress) to output strings. A \u27score\u27 is generated by using a similarity index against all the other genes by matching stored strings for any gene queried against our database. Taking carbohydrate metabolism as a test case, we observed that those genes known to be involved in similar functions and pathways generate a high \u27score\u27 with the queried gene. We were also able to recognize most of the randomly selected correlated pairs from Pearson correlation in CSB.DB and generate a higher number of relationships that might be biologically important. One advantage of our method over previously described approaches is that it includes all genes regardless of its expression values thereby highlighting important relationships absent in other contemporary databases. ConclusionBased on promising results, we understand that incorporating conditional co-regulation to study large expression data helps us identify novel relationships among genes. The other advantage of our approach is that mining expression data from various experiments, the genes that do not express in all the conditions or have low expression values are not excluded, thereby giving a better overall picture. This results in addressing known limitations of clustering methods in which genes that are expressed in only a subset of conditions are omitted. Based on further scope to extract information, ASIDB implementing above described approach has been initiated as a model database. ASIDB is available at http://www.asidb.co