Showing papers by "Indian Institute of Technology Indore published in 2018"

Nanoparticle Vaccines Against Infectious Diseases

Abstract: Due to emergence of new variants of pathogenic micro-organisms the treatment and immunization of infectious diseases have become a great challenge in the past few years. In the context of vaccine development remarkable efforts have been made to develop new vaccines and also to improve the efficacy of existing vaccines against specific diseases. To date, some vaccines are developed from protein subunits or killed pathogens, whilst several vaccines are based on live-attenuated organisms, which carry the risk of regaining their pathogenicity under certain immunocompromised conditions. To avoid this, the development of risk-free effective vaccines in conjunction with adequate delivery systems are considered as an imperative need to obtain desired humoral and cell-mediated immunity against infectious diseases. In the last several years, the use of nanoparticle-based vaccines has received a great attention to improve vaccine efficacy, immunization strategies, and targeted delivery to achieve desired immune responses at the cellular level. To improve vaccine efficacy, these nanocarriers should protect the antigens from premature proteolytic degradation, facilitate antigen uptake and processing by antigen presenting cells, control release, and should be safe for human use. Nanocarriers composed of lipids, proteins, metals or polymers have already been used to attain some of these attributes. In this context, several physico-chemical properties of nanoparticles play an important role in the determination of vaccine efficacy. This review article focuses on the applications of nanocarrier-based vaccine formulations and the strategies used for the functionalization of nanoparticles to accomplish efficient delivery of vaccines in order to induce desired host immunity against infectious diseases.

The Role of Histamine and Histamine Receptors in Mast Cell-Mediated Allergy and Inflammation: The Hunt for New Therapeutic Targets.

Abstract: Histamine and its receptors (H1R-H4R) play a crucial and significant role in the development of various allergic diseases. Mast cells are multifunctional bone marrow-derived tissue-dwelling cells that are the major producer of histamine in the body. H1R are expressed in many cells, including mast cells, and are involved in Type 1 hypersensitivity reactions. H2R are involved in Th1 lymphocyte cytokine production. H3R are mainly involved in blood-brain barrier function. H4R are highly expressed on mast cells where their stimulation exacerbates histamine and cytokine generation. Both H1R and H4R have important roles in the progression and modulation of histamine-mediated allergic diseases. Antihistamines that target H1R alone are not entirely effective in the treatment of acute pruritus, atopic dermatitis, allergic asthma, and other allergic diseases. However, antagonists that target H4R have shown promising effects in preclinical and clinical studies in the treatment of several allergic diseases. In the present review, we examine the accumulating evidence suggesting novel therapeutic approaches that explore both H1R and H4R as therapeutic targets for histamine-mediated allergic diseases.

Aptamers in the Therapeutics and Diagnostics Pipelines.

Abstract: Aptamers are short single-stranded DNA or RNA oligonucleotides that can selectively bind to small molecular ligands or protein targets with high affinity and specificity, by acquiring unique three-dimensional structures. Aptamers have the advantage of being highly specific, relatively small in size, non-immunogenic and can be easily stabilized by chemical modifications, thus allowing expansion of their diagnostic and therapeutic potential. Since the invention of aptamers in the early 1990s, great efforts have been made to make them clinically relevant for diseases like macular degeneration, cancer, thrombosis and inflammatory diseases. Furthermore, owing to the aforementioned advantages and unique adaptability of aptamers to point-of-care platforms, aptamer technology has created a stable niche in the field of in vitro diagnostics by enhancing the speed and accuracy of diagnoses. The aim of this review is to give an overview on aptamers, highlight the inherent therapeutic and diagnostic opportunities and challenges associated with them and present various aptamers that have reached therapeutic clinical trials, diagnostic markets or that have immediate translational potential for therapeutics and diagnostics applications.

A Multi-class EEG-based BCI classification using Multivariate Empirical Mode Decomposition Based Filtering and Riemannian Geometry

Abstract: A brain-computer interface (BCI) facilitates a medium to translate the human motion intentions using electrical brain activity signals such as electroencephalogram (EEG) into control signals. EEG signals are non-stationary and subject specific. A major challenge in BCI research is to classify human motion intentions from non-stationary EEG signals. We propose a novel subject specific multivariate empirical mode decomposition (MEMD) based filtering method, namely, SS-MEMDBF to classify the motor imagery (MI) based EEG signals into multiple classes. The MEMD method simultaneously decomposes the multichannel EEG signals into a group of multivariate intrinsic mode functions (MIMFs). This decomposition enables us to extract the cross-channel information and also localize the specific frequency information. The MIMFs are considered as narrow-band, amplitude and frequency modulated (AFM) signals. The statistical measure, mean frequency has been used to automatically filter the MIMFs to obtain enhanced EEG signals which better represent motor imagery related brainwave modulations over μ and β rhythms. The sample covariance matrix has been computed and used as a feature set. The feature set has been classified into multiple MI tasks using Riemannian geometry. The proposed method has helped achieve mean Kappa value of 0.60 across nine subjects of the BCI competition IV dataset 2A which is superior to all the reported methods.

EEG signal classification using universum support vector machine

Abstract: Support vector machine (SVM) has been used widely for classification of electroencephalogram (EEG) signals for the diagnosis of neurological disorders such as epilepsy and sleep disorders. SVM shows good generalization performance for high dimensional data due to its convex optimization problem. The incorporation of prior knowledge about the data leads to a better optimized classifier. Different types of EEG signals provide information about the distribution of EEG data. To include prior information in the classification of EEG signals, we propose a novel machine learning approach based on universum support vector machine (USVM) for classification. In our approach, the universum data points are generated by selecting universum from the EEG dataset itself which are the interictal EEG signals. This removes the effect of outliers on the generation of universum data. Further, to reduce the computation time, we use our approach of universum selection with universum twin support vector machine (UTSVM) which has less computational cost in comparison to traditional SVM. For checking the validity of our proposed methods, we use various feature extraction techniques for different datasets consisting of healthy and seizure signals. Several numerical experiments are performed on the generated datasets and the results of our proposed approach are compared with other baseline methods. Our proposed USVM and proposed UTSVM show better generalization performance compared to SVM, USVM, Twin SVM (TWSVM) and UTSVM. The proposed UTSVM has achieved highest classification accuracy of 99% for the healthy and seizure EEG signals.

A novel approach for automated detection of focal EEG signals using empirical wavelet transform

Abstract: The determination of epileptogenic area is a prime task in presurgical evaluation. The seizure activity can be prevented by operating the affected areas by clinical surgery. In this paper, an automatic approach has been presented to detect electroencephalogram (EEG) signals of non-focal and focal groups. The proposed approach can be used to determine the area linked to the focal epilepsy. In our method, the EEG signal is decomposed into rhythms using empirical wavelet transform technique. The two-dimensional (2D) projections of the reconstructed phase space (RPS) have been obtained for the rhythms. Area measures for various RPS plots are estimated using central tendency measure (CTM) parameter. The area parameters are used with least-squares support vector machine (LS-SVM) classifier to classify the focal and non-focal classes of EEG signals. In this work, we have achieved a maximum classification accuracy of 90%, sensitivity and specificity of 88 and 92%, respectively, using 50 pairs of focal and non-focal EEG signals. The same method has achieved maximum classification accuracy, sensitivity and specificity of 82.53, 81.60 and 83.46%, respectively, with 750 pairs of signals. The developed prototype can be used for the epileptic patients and aid the clinicians to confirm diagnosis.

Metal Catalysts for the Efficient Transformation of Biomass‐derived HMF and Furfural to Value Added Chemicals

Abstract: Catalytic transformation of biomass‐derived compounds to different platform chemicals and liquid fuel is a prominent way to reduce the global dependence on fossil resources. In past few decades, biomass‐derived furans such as 2‐furfuraldehyde (furfural) and 5‐hydroxymethyl‐2‐furfural (HMF) have received outstanding attention because of their wide applications in the production of various industrially important value‐added chemicals and fuel components. Various catalytic systems and methodologies have been extensively explored for the transformation of these furans to a wide range of products including open ring diketones, ketoacids, alcohols and long chain alkanes. This Review is aimed to provide an extensive overview of the recent developments of several high‐performing heterogeneous catalysts for the catalytic upgradation of the key biomass‐derived furans (furfural and HMF) to value‐added chemicals. Moreover, the role of these catalysts in the catalytic transformations including hydrogenation, decarbonylation, oxidation, hydrogenolysis and ring opening reactions, and the mechanistic pathways are also highlighted in this Review.

Tunable-Q Wavelet Transform and Dual Multiclass SVM for Online Automatic Detection of Power Quality Disturbances

Abstract: A new automated recognition approach based on tunable-Q wavelet transform (TQWT) and a dual multiclass support vector machines (MSVM) has been proposed for detection of power quality disturbances. The proposed approach first investigates the presence of low-frequency interharmonics and then tunes the wavelet for decomposition of signal into fundamental and harmonic components. The tuning of Q-factor and redundancy makes the filter design to accurately extract the fundamental frequency component from a distorted input signal. Then, a unique set of features, which clearly reveal the characteristics of disturbances, are extracted. The power quality disturbances are broadly categorized into two groups based on the pre-obtained information of low-frequency interharmonics. Therefore, multiple disturbances are recognized by employing a dual MSVM, one for each group. Results demonstrate the applicability, strength, and accuracy of the proposed approach for classification of single and combined disturbances under different noisy conditions. Moreover, to illustrate the prominence of the features extracted from TQWT, two more classifiers based on decision tree and feedforward neural network have been employed for classification of power quality disturbances.

Human Activity Classification in Smartphones Using Accelerometer and Gyroscope Sensors

Abstract: Activity classification in smartphones helps us to monitor and analyze the physical activities of the user in daily life and has potential applications in healthcare systems. This paper proposes a descriptor-based approach for activity classification using built-in sensors of smartphones. Accelerometer and gyroscope sensor signals are acquired to identify the activities performed by the user. In addition, time and frequency domain signals are derived using the collected signals. In the proposed approach, two descriptors, namely, histogram of gradient and centroid signature-based Fourier descriptor, are employed to extract feature sets from these signals. Feature and score level fusion are explored for information fusion. For classification, we have studied the performance of multiclass support vector machine and $k$ -nearest neighbor classifiers. The proposed approach is evaluated on two publicly available data sets, namely, UCI HAR data set and physical activity sensor data. Our experimental results show that the feature level fusion provides better performance than the score level fusion. In addition, our approach provides considerable improvement in classifying different activities as compared with the existing works. The average activity classification accuracy achieved using the proposed method is 97.12% as against the existing work, which provided 96.33% on UCI HAR data set. On the second data set, the proposed approach attained 96.83% classification accuracy, whereas the existing work achieved 90.2%.

The effect of stoichiometry on the structural, thermal and electronic properties of thermally decomposed nickel oxide

Abstract: A thermal decomposition route with different sintering temperatures was employed to prepare non-stoichiometric nickel oxide (Ni1−δO) from Ni(NO3)2·6H2O as a precursor. The non-stoichiometry of samples was then studied chemically by iodometric titration, wherein the concentration of Ni3+ determined by chemical analysis, which is increasing with increasing excess of oxygen or reducing the sintering temperature from the stoichiometric NiO; it decreases as sintering temperature increases. These results were corroborated by the excess oxygen obtained from the thermo-gravimetric analysis (TGA). X-ray diffraction (XRD) and Fourier transformed infrared (FTIR) techniques indicate the crystalline nature, Ni–O bond vibrations and cubic structural phase of Ni1−δO. The change in oxidation state of nickel from Ni3+ to Ni2+ were seen in the X-ray photoelectron spectroscopy (XPS) analysis and found to be completely saturated in Ni2+ as the sintering temperature reaches 700 °C. This analysis accounts for the implication of non-stoichiometric on the magnetization data, which indicate a shift in antiferromagnetic ordering temperature (TN) due to associated increased magnetic disorder. A sharp transition in the specific heat capacity at TN and a shift towards lower temperature are also evidenced with respect to the non-stoichiometry of the system.

Thermal resistance of fly ash based rubberized geopolymer concrete

Abstract: This research paper presents the first scientific attempt at a comparative study of thermal resistance of fly ash based geopolymer concrete and rubberized geopolymer concrete. In this study, rubberized fly ash based geopolymer concrete has been prepared using waste rubber tire fibres as a partial substitute for natural river sand, providing an efficient solution to the disposal problems of both fly ash and waste rubber. Changes in the weight, compressive strength , density, and microstructure of control and rubberized fly ash based geopolymer concrete at room temperature, and after thermal treatment at 200 °C, 400 °C, 600 °C and 800 °C for two hours, have been investigated using X-ray diffraction (XRD), Fourier transform spectrometry (FTIR) and thermogravimetric analysis (TGA-DTA). Results indicate that the loss in strength for rubberized geopolymer concrete at elevated temperatures is only slightly higher than that of the control geopolymer concrete because of the probable mismatch between the coefficients of thermal expansion of the integral materials.

Energy dependence and fluctuations of anisotropic flow in Pb-Pb collisions at √sNN = 5.02 and 2.76 TeV

Abstract: Measurements of anisotropic flow coefficients with two- and multi-particle cumulants for inclusive charged particles in Pb-Pb collisions at $ \sqrt{s_{\mathrm{NN}}}=5.02 $ and 2.76 TeV are reported in the pseudorapidity range |η| < 0.8 and transverse momentum 0.2 < p$_{T}$ < 50 GeV/c. The full data sample collected by the ALICE detector in 2015 (2010), corresponding to an integrated luminosity of 12.7 (2.0) μb$^{−1}$ in the centrality range 0-80%, is analysed. Flow coefficients up to the sixth flow harmonic (v$_{6}$) are reported and a detailed comparison among results at the two energies is carried out. The p$_{T}$ dependence of anisotropic flow coefficients and its evolution with respect to centrality and harmonic number n are investigated. An approximate power-law scaling of the form v$_{n}$(p$_{T}$) ∼ p$_{T}^{n}^{/3}$ is observed for all flow harmonics at low p$_{T}$ (0.2 < p$_{T}$ < 3 GeV/c). At the same time, the ratios v$_{n}$/v$_{m}^{n}^{/ }^{m}$ are observed to be essentially independent of p$_{T}$ for most centralities up to about p$_{T}$ = 10 GeV/c. Analysing the differences among higher-order cumulants of elliptic flow (v$_{2}$), which have different sensitivities to flow fluctuations, a measurement of the standardised skewness of the event-by-event v$_{2}$ distribution P(v$_{2}$) is reported and constraints on its higher moments are provided. The Elliptic Power distribution is used to parametrise P(v$_{2}$), extracting its parameters from fits to cumulants. The measurements are compared to different model predictions in order to discriminate among initial-state models and to constrain the temperature dependence of the shear viscosity to entropy-density ratio.

Core–Shell Zeolitic Imidazolate Frameworks for Enhanced Hydrogen Storage

Abstract: Core–shell ZIF-8@ZIF-67- and ZIF-67@ZIF-8-based zeolitic imidazolate frameworks (ZIFs) were synthesized solvothermally using a seed-mediated methodology. Transmission electron microscopy–energy-dispersive X-ray spectrometry, line scan, elemental mapping, X-ray photoelectron spectroscopy, and inductively coupled plasma-atomic emission spectroscopy analyses were performed to confirm the formation of a core–shell structure with the controlled Co/Zn elemental composition of ∼0.50 for both the core–shell ZIFs. The synthesized core–shell ZIF-8@ZIF-67 and ZIF-67@ZIF-8 frameworks conferred enhanced H2 (2.03 and 1.69 wt %) storage properties at 77 K and 1 bar, which are ca. 41 and 18%, respectively, higher than that of the parent ZIF-8. Notably, the distinctly remarkable H2 storage properties shown by both the core–shell ZIFs over the bimetallic Co/Zn-ZIF and the physical mixture of ZIF-8 and ZIF-67 clearly evidenced their unique structural properties (confinement of porosity) and elemental heterogeneity due to th...

TiO2–Co3O4 Core–Shell Nanorods: Bifunctional Role in Better Energy Storage and Electrochromism

Abstract: A suitably designed heterostructured TiO2–Co3O4 core–shell nanorod array has been found to exhibit improved supercapacitive as well as electrochromic properties as compared to the nanowires of either of the oxides when used individually The core–shell nanostructures have been grown on an FTO coated glass substrate by preparing TiO2 nanorods through hydrothermal reaction followed by growing a Co3O4 shell layer by electrodeposition The core–shell electrode shows high specific and areal capacitance of ∼342 F/g and ∼140 mF/cm2 (at scan rate of 100 mV/s), respectively Such an improvement in supercapacitive behavior, as compared to the behavior of the existing ones, is likely due to increased surface area and modified charge dynamics within the core–shell heterojunction Additionally, these core–shells also exhibit stable and power efficient bias induced color change between transparent (sky blue) and opaque (dark brown) states with coloration efficiency of ∼91 cm2/C Porous morphology and strong adhesion to

Stimuli responsive AIE active positional isomers of phenanthroimidazole as non-doped emitters in OLEDs

Abstract: The development of mechanochromic materials by incorporating aggregation induced emission (AIE) luminogens has gained momentum owing to their wide range of applications in optoelectronics In this work, the authors contribute to the development of AIE active mechanochromic phenanthroimidazole derivatives The positional isomers of phenanthroimidazoles 1 and 2 were designed to study the effect of the position of triphenylamine (TPA) and tetraphenylethylene (TPE) units on their AIE and mechanochromism Phenanthroimidazoles 1 and 2 were synthesized using the Suzuki cross-coupling reaction of TPE boronate ester with iodo-phenanthroimidazole of TPA and bromo-phenanthroimidazole of TPA, respectively The single crystal X-ray analysis of 1 reveals a propeller orientation of multiple phenyl rings of the TPA and TPE units, confirming strong AIE characteristics of 1 and 2 Phenanthroimidazoles 1 and 2 exhibit reversible mechanochromism between blue and green colours, which was studied using powder X-ray diffraction (PXRD) The PXRD studies suggest that a phase transition from a crystalline state to an amorphous state is associated with the colour change Moreover, phenanthroimidazoles 1 and 2 worked efficiently as non-doped emitters based on the AIE character and provided a high external quantum efficiency of 28 and 40%, respectively

D-meson azimuthal anisotropy in midcentral Pb-Pb collisions at √sNN=5.02 TeV

Abstract: A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences and Nationalstiftung fur Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), Universidade Federal do Rio Grande do Sul (UFRGS), Financiadora de Estudos e Projetos (Finep), and Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Brazil; Ministry of Science and Technology of China (MSTC), National Natural Science Foundation of China (NSFC) and Ministry of Education of China (MOEC), China; Ministry of Science, Education and Sport and Croatian Science Foundation, Croatia; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research–Natural Sciences, the Carlsberg Foundation, and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat a l’Energie Atomique (CEA) and Institut National de Physique Nucleaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS), France; Bundesministerium fur Bildung, Wissenschaft, Forschung und Technologie (BMBF) and GSI Helmholtzzentrum fur Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece; National Research, Development and Innovation Office, Hungary; Department of Atomic Energy Government of India (DAE) and Council of Scientific and Industrial Research (CSIR), New Delhi, India; Indonesian Institute of Science, Indonesia; Centro Fermi—Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi and Istituto Nazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science and Technology, Nagasaki Institute of Applied Science (IIST), Japan Society for the Promotion of Science (JSPS) KAKENHI, and Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnologia, through Fondo de Cooperacion Internacional en Ciencia y Tecnologia (FONCICYT) and Direccion General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Catolica del Peru, Peru; Ministry of Science and Higher Education and National Science Centre, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics, and Romanian National Agency for Science, Technology and Innovation, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation, and National Research Centre Kurchatov Institute, Russia; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Centro de Aplicaciones Tecnologicas y Desarrollo Nuclear (CEADEN), Cubaenergia, Cuba, Ministerio de Ciencia e Innovacion and Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT), Spain; Swedish Research Council (VR) and Knut and Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; National Science and Technology Development Agency (NSDTA), Suranaree University of Technology (SUT), and Office of the Higher Education Commission under NRU project of Thailand, Thailand; Turkish Atomic Energy Agency (TAEK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America.

Spiro-linked organic small molecules as hole transport materials for perovskite solar cells

Abstract: Organic–inorganic halide perovskite solar cells (PSCs) have attracted great attention as an alternative renewable photovoltaic technology with a power conversion efficiency (PCE) > 22%, which is on par with established technologies. The state-of-the-art spiro-OMeTAD (2,2′,7,7′-tetrakis-(N,N-di-p-methoxyphenyl-amine)-9,9′-spirobifluorene) is the most successful hole-transport material (HTM) employed in PSCs. Recently, various types of spiro-linked organic small molecules have been reported to overcome the reported disadvantages of spiro-OMeTAD, such as a complex synthetic route, high synthetic cost, and requirement for hygroscopic dopants to improve the charge-carrier mobility and device performance, which significantly limits spiro-OMeTAD for large-scale application in the future. Herein, we provide an overview of recent developments in the design, synthesis, and characterization of spiro-linked organic small molecules as hole-transport materials (HTM) in perovskite solar cells (PSCs).

Automated System for Epileptic EEG Detection Using Iterative Filtering

Abstract: The nonstationary characteristics present in electroencephalogram (EEG) signal require a crucial analysis that can reveal a method for diagnosis of neurological abnormalities, especially epilepsy. This article presents a new technique for automated classification of epileptic EEG signals based on iterative filtering (IF) of EEG signals. The superiority of IF over empirical mode decomposition for the classification of seizure EEG signals is presented. In this article, EEG epochs are decomposed into their intrinsic mode functions (IMFs) using IF. Amplitude envelope (AE) function is extracted from these modes, using the discrete separation energy algorithm. The features are extracted from these IMFs and AE functions. The feature set includes K-nearest neighbor entropy estimator, log energy entropy, Shannon entropy, and Poincar $\acute{\text{e}}$ plot parameters. These features are tested for their discriminative strength, on the basis of their $p$ -values, for classification of EEG signals into seizure, seizure-free, and normal classes. This proposed methodology has obtained a high classification accuracy using random forest classifier and takes far less time, which can be suitable for real-time implementation.

Oncotargeting by Vesicular Stomatitis Virus (VSV): Advances in cancer therapy

Abstract: Modern oncotherapy approaches are based on inducing controlled apoptosis in tumor cells. Although a number of apoptosis-induction approaches are available, site-specific delivery of therapeutic agents still remain the biggest hurdle in achieving the desired cancer treatment benefit. Additionally, systemic treatment-induced toxicity remains a major limiting factor in chemotherapy. To specifically address drug-accessibility and chemotherapy side effects, oncolytic virotherapy (OV) has emerged as a novel cancer treatment alternative. In OV, recombinant viruses with higher replication capacity and stronger lytic properties are being considered for tumor cell-targeting and subsequent cell lysing. Successful application of OVs lies in achieving strict tumor-specific tropism called oncotropism, which is contingent upon the biophysical interactions of tumor cell surface receptors with viral receptors and subsequent replication of oncolytic viruses in cancer cells. In this direction, few viral vector platforms have been developed and some of these have entered pre-clinical/clinical trials. Among these, the Vesicular stomatitis virus (VSV)-based platform shows high promise, as it is not pathogenic to humans. Further, modern molecular biology techniques such as reverse genetics tools have favorably advanced this field by creating efficient recombinant VSVs for OV; some have entered into clinical trials. In this review, we discuss the current status of VSV based oncotherapy, challenges, and future perspectives regarding its therapeutic applications in the cancer treatment.

Structure–property relationship in multi-stimuli responsive D–A–A′ benzothiazole functionalized isomers

Abstract: Multichromophoric D–A–A′ molecules comprising of benzothiazole (BT) as A′, benzothiadiazole (BTD) as A and tetraphenylethylene (TPE) as D were designed and synthesized as positional isomers p-BT, m-BT and o-BT by attaching the BTD–TPE moiety ortho, meta and para to the phenyl BT unit The positional change exploited in these isomers can influence the acceptor strength and molecular packing Hence, a comparative study of the photophysical and electronic properties has been carried out to study the effect of position The p-BT and m-BT isomers were synthesized by the Suzuki cross-coupling reaction of BTD–TPE with boronate esters of BT The Stille cross-coupling reaction was employed for o-BT The structural features of the isomers endowed them with solvatochromism, mechanochromism, acidochromism and aggregation induced emission properties which were studied using emission and absorption spectroscopy The reversible mechanochromic behaviour was associated with the phase transition from crystalline to amorphous and was used to develop rewritable ink free paper The single crystal X-ray analysis of p-BT and o-BT establishes that mechanochromism synergistically depends on the flexibility and twisting in the donor and acceptor moieties The isomers can sense trifluoroacetic acid in solution as well as the solid state The chosen strategy allows modulation of fluorescence properties making them potential stimuli responsive materials with applications in mechano-sensors, security inks and optoelectronic-devices

Mesoporous Nickel Oxide (NiO) Nanopetals for Ultrasensitive Glucose Sensing

Abstract: Glucose sensing properties of mesoporous well-aligned, dense nickel oxide (NiO) nanostructures (NSs) in nanopetals (NPs) shape grown hydrothermally on the FTO-coated glass substrate has been demonstrated. The structural study based investigations of NiO-NPs has been carried out by X-ray diffraction (XRD), electron and atomic force microscopies, energy dispersive X-ray (EDX), and X-ray photospectroscopy (XPS). Brunauer–Emmett–Teller (BET) measurements, employed for surface analysis, suggest NiO’s suitability for surface activity based glucose sensing applications. The glucose sensor, which immobilized glucose on NiO-NPs@FTO electrode, shows detection of wide range of glucose concentrations with good linearity and high sensitivity of 3.9 μA/μM/cm2 at 0.5 V operating potential. Detection limit of as low as 1 μΜ and a fast response time of less than 1 s was observed. The glucose sensor electrode possesses good anti-interference ability, stability, repeatability & reproducibility and shows inert behavior toward ascorbic acid (AA), uric acid (UA) and dopamine acid (DA) making it a perfect non-enzymatic glucose sensor.