The Tracking Tapered Gridded Estimator (TTGE) for the power spectrum from drift scan observations

Intensity mapping with the redshifted 21-cm line is an emerging tool in cosmology. Drift scan observations, where the antennas are fixed to the ground and the telescope's pointing center (PC) changes continuously on the sky due to earth's rotation, provide broad sky coverage and sustained instrumental stability needed for 21-cm intensity mapping. Here we present the Tracking Tapered Grided Estimator (TTGE) to quantify the power spectrum of the sky signal estimated directly from the visibilities measured in drift scan radio interferometric observations. The TTGE uses the data from the different PC to estimate the power spectrum of the signal from a small angular region located around a fixed tracking center (TC). The size of this angular region is decided by a suitably chosen tapering window function which serves to reduce the foreground contamination from bright sources located at large angles from the TC. It is possible to cover the angular footprint of the drift scan observations using multiple TC, and combine the estimated power spectra to increase the signal to noise ratio. Here we have validated the TTGE using simulations of $154 \, {\rm MHz}$ MWA drift scan observations. We show that the TTGE can recover the input model angular power spectrum $C_{\ell}$ within $20 \%$ accuracy over the $\ell$ range $40 < \ell < 700$.Comment: Accepted for publication in MNRA

New Trends in Artificial Intelligence: Applications of Particle Swarm Optimization in Biomedical Problems

Optimization is a process to discover the most effective element or solution from a set of all possible resources or solutions. Currently, there are various biological problems such as extending from biomolecule structure prediction to drug discovery that can be elevated by opting standard protocol for optimization. Particle swarm optimization (PSO) process, purposed by Dr. Eberhart and Dr. Kennedy in 1995, is solely based on population stochastic optimization technique. This method was designed by the researchers after inspired by social behavior of flocking bird or schooling fishes. This method shares numerous resemblances with the evolutionary computation procedures such as genetic algorithms (GA). Since, PSO algorithms is easy process to subject with minor adjustment of a few restrictions, it has gained more attention or advantages over other population based algorithms. Hence, PSO algorithms is widely used in various research fields like ranging from artificial neural network training to other areas where GA can be used in the system

HI Fluctuations at Large Redshifts: I--Visibility correlation

We investigate the possibility of probing the large scale structure in the universe at large redshifts by studying fluctuations in the redshifted 1420 MHz emission from the neutral hydrogen (HI) at early epochs. The neutral hydrogen content of the universe is known from absorption studies for z<4.5. The HI distribution is expected to be inhomogeneous in the gravitational instability picture and this inhomogeneity leads to anisotropy in the redshifted HI emission. The best hope of detecting this anisotropy is by using a large low-frequency interferometric instrument like the Giant Meter-Wave Radio Telescope (GMRT). We calculate the visibility correlation function <V_nu(u) V_nu'(u)> at two frequencies nu and nu' of the redshifted HI emission for an interferometric observation. In particular we give numerical results for the two GMRT channels centered around nu =325 and 610 MHz from density inhomogeneity and peculiar velocity of the HI distribution. The visibility correlation is ~10^-9 to 10^-10 Jy^2. We calculate the signal-to-noise for detecting the correlation signal in the presence of system noise and show that the GMRT might detect the signal for integration times ~ 100 hrs. We argue that the measurement of visibility correlation allows optimal use of the uncorrelated nature of the system noise across baselines and frequency channels.Comment: 17 pages, 2 figures, Submitted to JA

Using HI to probe large scale structures at z ~ 3

The redshifted 1420 MHz emission from the HI in unresolved damped Lyman-\alpha clouds at high z will appear as a background radiation in low frequency radio observations. This holds the possibility of a new tool for studying the universe at high-z, using the mean brightness temperature to probe the HI content and its fluctuations to probe the power spectrum. Existing estimates of the HI density at z~3 imply a mean brightness temperature of 1 mK at 320 Mhz. The cross-correlation between the temperature fluctuations across different frequencies and sight lines is predicted to vary from 10^{-7} K^2 to 10^{-8} K^2 over intervals corresponding to spatial scales from 10 Mpc to 40 Mpc for some of the currently favoured cosmological models. Comparing this with the expected sensitivity of the GMRT, we find that this can be detected with \~10 hrs of integration, provided we can distinguish it from the galactic and extragalactic foregrounds which will swamp this signal. We discuss a strategy based on the very distinct spectral properties of the foregrounds as against the HI emission, possibly allowing the removal of the foregrounds from the observed maps.Comment: 16 pages, includes 6 figures, accepted in JAA (minor revisions, references added

Inhibitory insights of strawberry (Fragaria × ananassa var. Seolhyang) root extract on tyrosinase activity using computational and in vitro analysis

The strawberry (Fragaria × ananassa var. seolhyang) is commonly used as fruit but medicinal importance for the non-edible roots which contained a pool of bioactive compounds are not yet studied against tyrosinase inhibition. This study demonstrates the potential of bioactive compounds in root and rhizome of strawberry against tyrosinase inhibition using in silico and in vitro approaches. ADMET profiling and molecular docking analysis show druglikeness for the major bioactive compounds in strawberry root extract (SRE), i.e. procyanidin, procyanidin trimer, kaempferol 3-O-(4-O-p-coumaroyl)-glucoside, neochlorogenic acid, procyanidin tetramer, and quercetin-3-O-pentoside, and docking score between −7.8 to −6.3 kcal/mol with tyrosinase, respectively. Also, these docked complexes exhibit substantial stability contributed by strong hydrogen bonding, hydrophobic interactions, and polar interactions in 100 ns molecular dynamics simulation; further supported by essential dynamics and dynamic cross-correlation matrix analysis. Also, in vitro functional assays support in silico predicted results in terms of substantial cytoprotective and cellular antioxidant potential in Raw 264.7 macrophages challenged by H2O2 as well as non-significant toxicity in zebrafish. SRE exhibits the lowest (5.8%) and highest (42.8%) inhibition of tyrosinase at 100 and 500 μg/ml concentrations, respectively. These results advocated functional properties and tyrosinase inhibition potential of SRE; and hence, SRE can be used in medicinal or cosmetic applications

Nano-particle mediated inhibition of Parkinson's disease using computational biology approach

Parkinson's disease (PD) arises as neurodegenerative disorder and characterized by progressive deterioration of motor functions due to forfeiture of dopamine-releasing neurons. During PD, neurons at stake loss their functionality that results into cognition impairment and forgetfulness, commonly called as dementia. Recently, nanoparticles (NPs) have been reported for easy drug delivery through blood-brain barrier (BBB) into the central nervous system (CNS) against the conventional drug delivery systems. However, present study attempted to elucidate the α-synuclein activity, a major factor casing PD, in presence of its inhibitor cerium oxide (CeO2) nanoparticle via computational biology approach. A computational analysis was also conducted for the α-synuclein activity with biocompatible metal NPs such as GOLD NPs and SPIONs to scrutinize the efficacy and degree of inhibition induced by the CeO2 NP. The obtained results concluded that CeO2 NP fit best in the active site of α-synuclein with good contacts and interaction, and potentially inhibited the PD against L-DOPA drug selected as positive control in the designed PD biochemical pathway. Hence, CeO2 NP has been purposed as potential inhibitor of α-synuclein and can be employed as nano-drug against the PD

Receptor thermodynamics of ligand–receptor or ligand–enzyme association

Experimental techniques that directly assess the thermodynamics of ligand–receptor or ligand–enzyme association, such as isothermal titration calorimetry, have been improved in recent years and can provide thermodynamic details of the binding process. Parallel to the continuous increase in computational power, several classes of computational methods have been developed that can be used to get a more detail insight into the mode and affinity of compounds (drug) to their target (off). Such methods are affiliated with a qualitative and/or quantitative assessment of binding free energies, and differently trade off speed versus physical accuracy. With the current wealth of available three-dimensional structures of proteins and their complexes with ligands, structure-based drug design studies can be used to identify the key ligand interactions and free energy calculations, and can quantify the thermodynamics of binding between ligand and the target of interest

Thermodynamic cycles and their application in protein targets

A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions. Comprehensive thermodynamic evaluation is vital in the drug development process to speed drug development towards an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now been developed to provide proven utility in design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design

Structure-based screening and validation of bioactive compounds as Zika virus methyltransferase (MTase) inhibitors through first-principle density functional theory, classical molecular simulation and QM/MM affinity estimation

Recent Zika virus (ZIKV) outbreak and association with human diseases such as neurological disorders have raised global health concerns. However, in the absence of an approved anti-ZIKV drug has generated urgency for the drug development against ZIKV infection. Here, structure-based virtual screening of 8589 bioactive compounds, screened at the substrate-binding site of ZIKV nonstructural 5 (NS5)-based structure N-terminal methyltransferase (MTase) domain followed by ADMET (absorption, distribution, metabolism, excretion and toxicity) profiling concluded the four potential lead inhibitors, i.e. (4-acetylamino-benzenesulfonylamino)-acetic acid (F3342-0450), 3-(5-methylfuran-2-yl)-N-(4-sulfamoylphenyl)propanamide (F1736-0142), 8-(2-hydroxy-ethylamino)-1,3-dimethyl-7-(3-methyl-benzyl)-3,7-dihydro-purine-2,6-dione (F0886-0080) and N-[4-(aminosulfonyl)phenyl]-2,3-dihydro-1,4-benzodioxine-2-carboxamide (F0451-2187). Collectively, extra precision docking and Density Functional Theory(DFT) calculations studies identified the F3342-0450 molecule, having strong interactions on the active site of MTase, further supported by molecular dynamics simulation, binding affinity and hybrid QM/MM calculations, suggest a new drug molecule for the antiviral drug development against ZIKV infection. Communicated by Ramaswamy H. Sarma