Investigations of separated flow over backward facing steps in IISc hypersonic shock tunnel

Two backward facing step (2 mm and 3 mm step height) models are selected for surface heat transfer measurements. The platinum thin film gauges are deposited on the Macor inserts using both hand paint and vacuum sputtering technique. Using the Eckert reference temperature method the heating rates has been theoretically calculated along the flat plate portion of the model and the theoretical estimates are compared with experimentally determined surface heat transfer rate. Theoretical analysis of heat flux distribution down stream of the backward facing step model has been carried out using Gai’s non-dimensional analysis. Based on the measured surface heating rates on the backward facing step, the reattachment distance is estimated for 2 and 3 mm step height at nominal Mach number of 7.6. It has been found from the present study that for 2 and 3 mm step height, it approximately takes about 10 and 8 step heights downstream of the model respectively for the flow to re-attach.

Measurement of Heat Transfer Rate on Backward-Facing Steps at Hypersonic Mach Number

Two backward-facing models with step heights of 2 and 3 mm are used to measure the convective surface heat transfer rates by using platinum thin-film gauges, deposited on Macor inserts. Heat transfer rates have been theoretically calculated along the flat plate portion of a model using the Eckert reference temperature method. The experimentally determined surface heat transfer rate distributions are compared with theoretical and numerical estimations. Experimental heat flux distribution over a flat plate model showed good agreement with the reference temperature method at stagnation enthalpy range of 0.8-2 MJ/kg. Theoretical analysis has been used for downstream of a backward-facing step using Gai's nondimensional analysis. It has been found from the present study that approximately 10 and 8 step heights are required for the flow to reattach for 2 and 3 mm step height backward-facing step models, respectively, at a nominal Mach number of 7.6.

Network approaches to drug discovery

Introduction: Advances in genomics technologies are providing a very large amount of data on genome-wide gene expression profiles, protein molecules and their interactions with other macromolecules and metabolites. Molecular interaction networks provide a useful way to capture this complex data and comprehend it. Networks are beginning to be used in drug discovery, in many steps of the modern discovery pipeline, with large-scale molecular networks being particularly useful for the understanding of the molecular basis of the disease. Areas covered: The authors discuss network approaches used for drug target discovery and lead identification in the drug discovery pipeline. By reconstructing networks of targets, drugs and drug candidates as well as gene expression profiles under normal and disease conditions, the paper illustrates how it is possible to find relationships between different diseases, find biomarkers, explore drug repurposing and study emergence of drug resistance. Furthermore, the authors also look at networks which address particular important aspects such as off-target effects, combination-targets, mechanism of drug action and drug safety. Expert opinion: The network approach represents another paradigm shift in drug discovery science. A network approach provides a fresh perspective of understanding important proteins in the context of their cellular environments, providing a rational basis for deriving useful strategies in drug design. Besides drug target identification and inferring mechanism of action, networks enable us to address new ideas that could prove to be extremely useful for new drug discovery, such as drug repositioning, drug synergy, polypharmacology and personalized medicine.

Corticosterone targets distinct steps of synaptic transmission via concentration specific activation of mineralocorticoid and glucocorticoid receptors

Hippocampal neurons are affected by chronic stress and have a high density of cytoplasmic mineralocorticoid and glucocorticoid receptors (MR and GR). Detailed studies on the genomic effects of the stress hormone corticosterone at physiologically relevant concentrations on different steps in synaptic transmission are limited. In this study, we tried to delineate how activation of MR and GR by different concentrations of corticosterone affects synaptic transmission at various levels. The effect of 3-h corticosterone (25, 50, and 100nM) treatment on depolarization-mediated calcium influx, vesicular release and properties of miniature excitatory post-synaptic currents (mEPSCs) were studied in cultured hippocampal neurons. Activation of MR with 25nM corticosterone treatment resulted in enhanced depolarization-mediated calcium influx via a transcription-dependent process and increased frequency of mEPSCs with larger amplitude. On the other hand, activation of GR upon 100nM corticosterone treatment resulted in increase in the rate of vesicular release via the genomic actions of GR. Furthermore, GR activation led to significant increase in the frequency of mEPSCs with larger amplitude and faster decay. Our studies indicate that differential activation of the dual receptor system of MR and GR by corticosterone targets the steps in synaptic transmission differently.

Magnetization-steps in Y2CoMnO6 double perovskite: The role of antisite disorder

Antisite disorder is observed to have significant impact on the magnetic properties of the double perovskite Y2CoMnO6 which has been recently identified as a multiferroic. A paramagnetic-ferromagnetic phase transition occurs in this material at T-c approximate to 75 K. At 2K, it displays a strong ferromagnetic hysteresis with a significant coercive field of H-c approximate to 15 kOe. Sharp steps are observed in the hysteresis curves recorded below 8K. In the temperature range 2K <= T <= 5K, the hysteresis loops are anomalous as the virgin curve lies outside the main loop. The field-cooling conditions as well as the rate of field-sweep are found to influence the steps. Quantitative analysis of the neutron diffraction data shows that at room temperature, Y2CoMnO6 consists of 62% of monoclinic P2(1)/n with nearly 70% antisite disorder and 38% Pnma. The bond valence sums indicate the presence of other valence states for Co and Mn which arise from disorder. We explain the origin of steps by using a model for pinning of magnetization at the antiphase boundaries created by antisite disorder. The steps in magnetization closely resemble the martensitic transformations found in intermetallics and display first-order characteristics as revealed in the Arrott's plots. (C) 2014 AIP Publishing LLC.

Stacking Interactions in RNA and DNA: Roll-Slide Energy Hyperspace for Ten Unique Dinucleotide Steps

Understanding dinucleotide sequence directed structures of nuleic acids and their variability from experimental observation remained ineffective due to unavailability of statistically meaningful data. We have attempted to understand this from energy scan along twist, roll, and slide degrees of freedom which are mostly dependent on dinucleotide sequence using ab initio density functional theory. We have carried out stacking energy analysis in these dinucleotide parameter phase space for all ten unique dinucleotide steps in DNA and RNA using DFT-D by B97X-D/6-31G(2d,2p), which appears to satisfactorily explain conformational preferences for AU/AU step in our recent study. We show that values of roll, slide, and twist of most of the dinucleotide sequences in crystal structures fall in the low energy region. The minimum energy regions with large twist values are associated with the roll and slide values of B-DNA, whereas, smaller twist values correspond to higher stability to RNA and A-DNA like conformations. Incorporation of solvent effect by CPCM method could explain the preference shown by some sequences to occur in B-DNA or A-DNA conformations. Conformational preference of BII sub-state in B-DNA is preferentially displayed mainly by pyrimidine-purine steps and partly by purine-purine steps. The purine-pyrimidine steps show largest effect of 5-methyl group of thymine in stacking energy and the introduction of solvent reduces this effect significantly. These predicted structures and variabilities can explain the effect of sequence on DNA and RNA functionality. (c) 2014 Wiley Periodicals, Inc. Biopolymers 103: 134-147, 2015.

On the Two-Step Mechanism for Synthesis of Transition-Metal Nanoparticles

The two-step particle synthesis mechanism, also known as the Finke-Watzky (1997) mechanism, has emerged as a significant development in the field of nanoparticle synthesis. It explains a characteristic feature of the synthesis of transition metal nanoparticles, an induction period in precursor concentration followed by its rapid sigmoidal decrease. The classical LaMer theory (1950) of particle formation fails to capture this behavior. The two-step mechanism considers slow continuous nucleation and autocatalytic growth of particles directly from precursor as its two kinetic steps. In the present work, we test the two-step mechanism rigorously using population balance models. We find that it explains precursor consumption very well, but fails to explain particle synthesis. The effect of continued nucleation on particle synthesis is not suppressed sufficiently by the rapid autocatalytic growth of particles. The nucleation continues to increase breadth of size distributions to unexpectedly large values as compared to those observed experimentally. A number of variations of the original mechanism with additional reaction steps are investigated next. The simulations show that continued nucleation from the beginning of the synthesis leads to formation of highly polydisperse particles in all of the tested cases. A short nucleation window, realized with delayed onset of nucleation and its suppression soon after in one of the variations, appears as one way to explain all of the known experimental observations. The present investigations clearly establish the need to revisit the two-step particle synthesis mechanism.

Evolution of Aromatic beta-Glucoside Utilization by Successive Mutational Steps in Escherichia coli

The bglA gene of Escherichia coli encodes phospho-beta-glucosidase A capable of hydrolyzing the plant-derived aromatic beta-glucoside arbutin. We report that the sequential accumulation of mutations in bglA can confer the ability to hydrolyze the related aromatic beta-glucosides esculin and salicin in two steps. In the first step, esculin hydrolysis is achieved through the acquisition of a four-nucleotide insertion within the promoter of the bglA gene, resulting in enhanced steady-state levels of the bglA transcript. In the second step, hydrolysis of salicin is achieved through the acquisition of a point mutation within the bglA structural gene close to the active site without the loss of the original catabolic activity against arbutin. These studies underscore the ability of microorganisms to evolve additional metabolic capabilities by mutational modification of preexisting genetic systems under selection pressure, thereby expanding their repertoire of utilizable substrates.

Framework for morphometric classification of cells in imaging flow cytometry

Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.