Effect of amino acids on inhibition of lactate dehydrogenase-X by gossypol

Gossypol acetic acid (GAA) has been shown to have male antifertility effects, but there are pronounced differences among animal species. In the search of endogenous effector molecules, which interfere with the functions of GAA, we have studied the in vitro effect of various amino acids on the inhibition of the purified LDH-X by GAA. Histidine, cysteine and glycine were shown to block the effect of GAA. The effects of these amino acids were concentration dependent. Histidine and glycine protection was found to be complex type in which both the Km and Vmax were decreased compared to control. Arginine, glutamic acid, phenylalanine and valine were found to be ineffective against the inhibitory action of GAA

Virtual To Reality: Teaching Mathematics And Aerospace Concepts To Undergraduates Using Unmanned Aerial Systems And Flight Simulation Software

Student engagement is an essential element for learning. Active learning has been consistently shown to increase student engagement and hence learning. Hands-on activities are one of the many active learning approaches. These activities vary from structured laboratory experiments on one end of the spectrum to virtual gaming environments and to for example building a solar car on the other end. Active learning has also been credited for developing critical thinking skills that promote metacognition. We have used virtual and real environments to promote student engagement and provide opportunities for developing a deeper understanding of science, technology, engineering, and mathematics (STEM) concepts. Several learning modules have been developed utilizing Unmanned Aerial Systems (UAS) with autonomous flight capabilities and a flight simulation environment . In this paper we explain three modules. Based on a survey, students reported positve impact of these modules and of the opportunity to assemble the UAS

A Short Review on the Development of Salt Tolerant Cultivars in Rice

Rice is staple food for half of the world. With a population of almost 9.6 billion by the year 2050, there is a dire need of developing techniques to improve the crop plants, not only in terms of better yield but also to withstand harsh environmental conditions and stresses like drought, temperature, flood and salinity. Salinity is second to drought stress and hence it is very important to develop crops tolerant to salinity stress. This review discusses the mechanisms of salt tolerance and the recent developments in understanding the complex tolerance phenomena. One way to address the salinity issue is to develop tolerant rice varieties using conventional and modern breeding techniques for which screening the rice germplasm for the varieties with desired traits is critical. Conventional methods to develop tolerant rice varieties are discussed along with modern biotechnology techniques are also discussed. Quantitative Trait Loci (QTL) and Marker Assisted Selection (MAS) are promising techniques. In addition to these modern techniques, some recent developments in the fields of transgenic plants, haploid breeding and Somaclonal variations have also been discussed. The limited knowledge about molecular and genetic mechanisms to tolerate abiotic stresses, however is a barrier to efficiently develop tolerant cultivars. A combination of conventional and modern biotechnology techniques could possibly open up the new ways

A Hybrid Gold’s Returns Prediction Model Based on Empirical Mode Decomposition

Consumers have produced extraordinary levels of demand of Gold since the beginning of the financial crisis in 2008 and investment in small coins and bars striking a record high. Since the previous decade, the prices have reached the sky, but the demand for gold remains firm. With such an enormous need for gold coming from whole over the globe, forecast gold prices are of great interest. The main aim of this study is to forecast the price of gold returns, making use of Autoregressive (AR), Empirical Mode Decomposition Autoregressive (EMDAR) and hybrid Empirical Mode Decomposition Autoregressive Neural Network (EMDARNN). The daily data consists of 4837 observations starting from Jan 1995 to June 2013, has been used in this research. After assessing the accuracy of these models by mean absolute error and mean square error, it turns out that hybrid Empirical Mode Decomposition Autoregressive Neural Network excels all the other methods and produces better forecasting with high precision. Keywords: Gold Price, Autoregressive, Empirical Mode decomposition, Artificial Neural Networ

Correlation of CALL score with disease progression in COVID-19 patients

Background: Many prognostic models have been introduced to predict the disease progression in an individual with COVID-19, CALL score is one among them. The objective of the study was to evaluate the role of comorbidity, high age, low lymphocyte count, high lactate dehydrogenase (CALL) score in predicting disease progression and mortality in COVID 19 patients.Methods: Total 105 patients were divided into - stable group (CALL≤6) and progressive group (CALL>6), Chi- square test and ROC analysis is applied to predict the outcomes like oxygen requirement, ICU requirement (high flow nasal oxygen), invasive ventilation requirement, increase in respiratory rate ≥30 Cpm and death/recovery with CALL score in both the groups.Results: ROC analysis was done to predict outcome based on CALL score in both groups which showed sensitivity 100% (91.6% to 100%), specificity of 8.2% (2.7 to 18.1%), PPV – 44% (42.16 to 45.86%) and NPV – 100%.Conclusions: Using the CALL score model with cut off of 6 points, clinicians can predict the progression risk in terms of higher respiratory rate ≥30 cpm, oxygen requirement, requiring ICU, death/ recovery.

Magnetostratigraphy of Oligocene to Pleistocene Sediments, Sites 558 and 563

Integrated magnetostratigraphic and biostratigraphic studies of DSDP Sites 563 and 558 (western North Atlantic) show that, except for a short (~2 Ma) early Miocene hiatus, deposition was continuous from time of seafloor formation (Site 563, between Anomalies 12 and 13; Site 558, between Anomalies 13 and 15) through the Miocene at both sites. Several biostratigraphic datum levels, which have been correlated firmly with magnetic polarity chrons elsewhere, allow correlation of the magnetostratigraphy with the geomagnetic polarity time scale. Based upon that calibration, sediment accumulation rates were low to moderate ( 10 m/ Ma) in the middle-late Miocene after a short hiatus (Chron C5E is missing at both sites). The established magnetochronology is used to make direct magnetobiostratigraphic correlations. For the Oligocenelower Miocene samples, these correlations agree well with previously published first-order correlations. However, our correlations differ from the earlier indirect middle to upper Miocene correlations. In particular, indirect methods were previously used to correlate magnetostratigraphic Chron 11 ( = Zone NN9) with marine Anomaly 5A (Chron C5AN). However, Zone NN9 ( = Chron 11) and associated Zone N16 occur in a long normal interval at Sites 563 and 558 that best correlates with marine magnetic Anomaly 5. This reassignment (Chron 11 = Anomaly 5 = Chron C5N) requires an approximately 1.5 2 Ma upward shift in nannofossil zonal boundaries NN7/NN8 through NN10/NN11. The stratotype lower upper Miocene (Tortonian) is biostratigraphically linked with Zones NN9-NN11. Because Zone NN9 occurs in magnetic Anomaly 5 correlative (Chron C5N), the middle-upper Miocene boundary (basal Tortonian) is probably near the base of Chron C5N, with an estimated magnetochronologic age of 10.4 Ma