654 research outputs found
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Synthesis and characterization of ZIF-8 nanoparticles for controlled release of 6-mercaptopurine drug
No full textZeolitic imidazolate framework (ZIF-8) has been synthesized at room temperature in aqueous medium. Their suitability as potential drug carrier for delivery of an anti-leukemia drug, 6-mercaptopurine (6-MP) is examined. 6-MP was loaded in situ into the ZIF-8 nanoparticles during synthesis. Both ZIF-8 and 6-MP@ZIF-8 have been characterized using various characterization tools. The structural integrity and phase purity of 6-MP@ZIF-8 nanoparticles was obtained through X-ray diffraction pattern and was comparable to that of sodalite type ZIF-8. FESEM micrographs of pure ZIF-8 showed hexagonal nanocrystals with well-developed facets and uniform particle size distribution of around 80–100 nm. Encapsulation of 6-MP into ZIF-8 resulted into a nearly two fold increase of size while preserving the well-developed facets and hexagonal morphology. The encapsulation of 6-MP was confirmed by UV-Visible and FTIR spectroscopy studies. Furthermore, the release kinetics of 6-MP drug from 6-MP@ZIF-8 has been investigated in phosphate buffer saline 37 °C at two different pH values 7.4 and 5.0. The 6-MP@ZIF-8 exhibited much faster release of drug in acidic pH as compared with release in pH 7.4 owing to the decomposition of ZIF-8 structure, thus, indicating the potential of ZIF-8 to be used as a carrier for controlled delivery of 6-MP against cancerous cells
Electrochemical sensing and remediation of 4-nitrophenol using bio-synthesized copper oxide nanoparticles
No full textThe present work reports impedance based electrochemical sensing and remediation of 4-nitro phenol (4-NP) using biosynthesized (CuO) copper oxide nanoparticles. The synthesis of CuO nanoparticles is achieved using fruit extract of plant Fortunella japonica as reducing and stabilizing agent. The CuO nanoparticles were characterized using various analytical techniques like UV–Visible spectroscopy, Atomic force microscopy (AFM), High resolution transmission electron microscopy (HR-TEM), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, and X-ray diffraction (XRD). For electrochemical sensing of 4-NP, the CuO nanoparticles were drop casted on screen printed electrode (SPE) and electrode is referred at SPE/CuONPs sensor. The mechanism of 4-NP redox reactions was examined using cyclic voltammetry (CV). The electrochemical sensing of 4-NP has been done using square wave voltammetry (SWV) and impedance spectroscopy. In SWV, the oxidation peak current increased with increase in the concentration of 4-NP from 10 nM to 10 mM having regression coefficient of 0.996. In impedometric sensing, change in charge transfer resistance (Rct) with change in 4-NP concentration was used as a signal. The Rct decreased with increase in 4-NP concentration which is in accordance with SWV results. The effect of solution pH on impedometric response of SPE/CuONPs sensor was also evaluated. The SPE/CuONPs sensor exhibited good reproducibility and selectivity towards the analyte and is able to perform real sample analysis. The CuO nanoparticles act as a catalyst and showed good degradation percentage of 4-NP pollutant
Characterization of Chickpea Flour by Near Infrared Spectroscopy and Chemometrics
No full textNear infrared (NIR) spectrometry was used for the rapid characterization of quality parameters in desi chickpea flour (besan). Partial least square regression, principal component regression (PCR), interval partial least squares (iPLS), and synergy interval partial least squares (siPLS) were used to determine the protein, carbohydrate, fat, and moisture concentrations of besan. Spectra were collected in reflectance mode using a lab-built predispersive filter-based instrument from 700 to 2500 nm. The quality parameters were also determined by standard methods. The root mean square error (RMSE) for the calibration and validation sets was used to evaluate the performance of the models. The correlation coefficients for moisture, fat, protein, and carbohydrates in chickpea flour exceeded 0.96 using PLS and PCR models using the full spectral range. Wavelengths from 2100 to 2345 nm had the lowest RMSE for quality parameters by iPLS. The error was further decreased by 0.41, 0.1, and 1.1% for carbohydrates, fats, and proteins by siPLS. The NIR spectral regions yielding the lowest RMSE of prediction were 1620–2345 nm for carbohydrates, 1180–1590 nm and 1860–2094 nm for fat, and 1700–2345 nm for proteins. The study shows that chickpea flour quality parameters were accurately determined using the optimized wavelengths
Computer assisted classification framework for prediction of acute lymphoblastic and acute myeloblastic leukemia
No full textHematological malignancies i.e. acute lymphoid leukemia and acute myeloid leukemia are the types of blood cancer that can affect blood, bone marrow, lymphatic system and are the major contributors to cancer deaths. In present work, an attempt has been made to design a CAC (computer aided classification system) for diagnosis of myeloid and lymphoid cells and their FAB (French, American, and British) characterization. The proposed technique improves the AML and ALL diagnostic accuracy by analyzing color, morphological and textural features from the blood image using image processing and to assist in the development of a computer-aided screening of AML and ALL. This paper endeavors at proposing a quantitative microscopic approach toward the discrimination of malignant from normal in stained blood smear. The proposed technique firstly segments the nucleus from the leukocyte cell background and then computes features for each segmented nucleus. A total of 331 geometrical, chromatic and texture features are computed. A genetic algorithm using support vector machine (SVM) classifier is used to optimize the feature space. Based on optimized feature space, an SVM classifier with various kernel functions is used to eradicate noisy objects like overlapped cells, stain fragments, and other kinds of background noises. The significance of the proposed method is tested using 331 features on 420 microscopic blood images acquired from the online repository provided by the American society of hematology. The results confirmed the viability or potential of using a computer aided classification method to reinstate the monotonous and the reader-dependent diagnostic methods
Experimental and theoretical investigation of relative optical band gaps in graphene generations
No full textSize and chemical functionalization dependant optical band gaps in graphene family nanomaterials were investigated by experimental and theoretical study using Tauc plot and density functional theory (DFT). We have synthesized graphene oxide through a modified Hummer's method using graphene nanoplatelets and sequentially graphene quantum dots through hydrothermal reduction. The experimental results indicate that the optical band gap in graphene generations was altered by reducing the size of graphene sheets and attachment of chemical functionalities like epoxy, hydroxyl and carboxyl groups plays a crucial role in varying optical band gaps. It is further confirmed by DFT calculations that the π orbitals were more dominatingly participating in transitions shown by projected density of states and the molecular energy spectrum represented the effect of attached functional groups along with discreteness in energy levels. Theoretical results were found to be in good agreement with experimental results. All of the above different variants of graphene can be used in native or modified form for sensor design and optoelectronic applications
Accelerating Growth of Technology Transfers from CSIR-CSIO
Get PDFA premier national laboratory dedicated to research, design and development of scientific and industrial instruments, CSIR-CSIO has contributed substantially towards the growth of the scientific instruments industry in the country, generating revenue from the commercialisation of the technologies. A few technologies recently commercialised by it are discussed here
Thermal stability and electrochemical properties of PVP-protected Ru nanoparticles synthesized at room temperature
No full textStable ruthenium nanoparticles (RuNPs) have been synthesized by the chemical reduction of ruthenium trichloride trihydrate (RuCl3 centerdot 3H2O) using sodium borohydride (NaBH4) as a reductant and polyvinylpyrrolidone (PVP) as a protecting agent in the aqueous medium at room temperature. The nanoparticles thus prepared were characterized by their morphology and structural analysis from transmission electron microscopy (TEM), X-ray powder diffraction (XRD), UV–vis spectroscopy, Fourier transformation infrared and thermogravimetric analysis (TGA) techniques. The TEM image suggested a homogeneous distribution of PVP-protected RuNPs having a small average diameter of 2–4 nm with a chain-like network structure. The XRD pattern also confirmed that a crystallite size is around 2 nm of PVP-protected RuNPs having a single broad peak. The thermal stability studied using TGA, indicated good stability and the electrochemical properties of these nanoparticles revealed that saturation current increases for PVP-protected RuNPs/GC
Fluorescent nanobiosensors for the targeted detection of foodborne bacteria
No full textFoodborne diseases caused by bacterial pathogens are severe threats to human health. Conventional culture based microbiologic methods for the analysis of bacterial contamination in food products are laborious, time consuming and require specific skills. Immunologic and polymerase chain reaction (PCR)-based molecular methods are also costly, lack specificity, and may yield false results. As outlined in this review, fluorescent nanobiosensors have now become effective alternative tools for rapid and routine detection of foodborne bacteria. We provide an overview of the use of different fluorescent nanomaterials in the development of nanobiosensors with special emphasis on underlying detection principles, sensitivity, specificity, and their capability of multiplexed analysis. In summary, the diverse nanomaterials used for bacterial detection are critically analyzed with respect to their advantages and limitations for future applications in the diagnosis of foodborne bacteria
Prediction of properties of wheat dough using intelligent deep belief networks
No full textIn this paper, the rheological and chemical properties of wheat dough are predicted using deep belief networks. Wheat grains are stored at controlled environmental conditions. The internal parameters of grains viz., protein, fat, carbohydrates, moisture, ash are determined using standard chemical analysis and viscosity of the dough is measured using Rheometer. Here, fat, carbohydrates, moisture, ash and temperature are considered as inputs whereas protein and viscosity are chosen as outputs. The prediction algorithm is developed using deep neural network where each layer is trained greedily using restricted Boltzmann machine (RBM) networks. The overall network is finally fine-tuned using standard neural network technique. In most literature, it has been found that fine-tuning is done using back-propagation technique. In this paper, a new algorithm is proposed in which each layer is tuned using RBM and the final network is fine-tuned using deep neural network (DNN). It has been observed that with the proposed algorithm, errors between the actual and predicted outputs are less compared to the conventional algorithm. Hence, the given network can be considered as beneficial as it predicts the outputs more accurately. Numerical results along with discussions are presented
The reliability of different methods of manual volumetric segmentation of pharyngeal and sinonasal subregions
No full textObjectives
The purpose of the study was to test the intra and interobserver reliability of manual volumetric segmentation of pharyngeal and sinonasal airway subregions.
Study Design
Cone beam computed tomography data of 15 patients were collected from an orthodontic clinical database. Two experienced orthodontists independently performed manual segmentation of the airway subregions. Four performance measures were considered to test intra and interobserver reliability of manual segmentation: (1) volume correlation, (2) mean slice correlation, (3) percentage of volume difference, and (4) percentage of nonoverlapping voxels.
Results
Intra and interobserver reliability was observed to be greater than 0.96 for the entire pharyngeal and sinonasal airway sinus subregions by both observers using the volume correlation method. Mean slice correlation was found to be greater than 0.84, showing the existence of nonoverlapping voxels. Therefore, the percentage of nonoverlapping voxels was used as a reliability measure and was found to be less than 20% for both intra and interobserver markings.
Conclusions
The mean slice correlation and percentage of nonoverlapping voxels were the most reliable performance measures of segmentation correctness. Volume correlation and the percentage of volume difference were observed to be the most reliable performance measures for volume correctness