Purpose: The present work aimed to synthesize organic and inorganic quantum dots (QDs) and discuss their bioconjugation strategies. Design/methodology/approach: We have prepared 3 different QDs, organic (Carbon [CQDs]) and inorganic (Cadmium Sulphide [CdS] and Zinc Mercury Selenide [ZnHgSe]) quantum dots (QDs) and bioconjugation through in-situ and ex-situ route. These QDs have been characterized through UV-Vis spectroscopy and photoluminescence (PL) emission spectra. Their surface functional groups have been identified through Fourier-transform infrared (FTIR) spectroscopy. The bioconjugated quantum dots were tested through PL emission shift, Agarose electrophoresis, and Bradford assay technique. Findings: Successful synthesized QDs, and their bioconjugation has been confirmed through the previously listed characterization techniques. There are distinct differences in their emission peak, FTIR spectroscopy, and Bradford assay, which confirms their successful bioconjugation. Research limitations/implications: These bioconjugated QDs are difficult to filter from their unconjugated counterpart. Bioconjugation steps are extremely crucial. Practical implications: These QDs could be utilized for highly effective biolabelling and bioimaging in-vivo as well as in-vitro applications. Originality/value: The synthesis has been majorly modified, and the bioconjugation has been prepared in a novel method. There is limited reported work with this much description of the differences in conjugated and unconjugated QDs.
Purpose: Nucleolin is a multifactorial protein, having a significant role in chromatin remodelling, mRNA stability, ribosome biogenesis, stemness, angiogenesis, etc., thus, it is potential therapeutic target in cancer. The purpose of this paper is to study porous silicon (pSi) nanocarrier-based natural drug delivery system targeting dysregulated nucleolin expression for cancer therapeutics. Design/methodology/approach: Quercetin was loaded in pre-synthesized and characterized pSi nanoparticles, and release kinetics was studied. The study compared the inhibitory concentration (IC50) of quercetin, synthetic drug doxorubicin, and quercetin-loaded pSi nanoparticles. Further, mRNA expression of a target gene, nucleolin, was tested with a quercetin treated breast cancer cell line (MCF-7). Findings: Quercetin-loaded pSi nanoparticles followed first-order release kinetics. IC50 was determined at concentrations of 312 nM, 160 μM, and 50 μM against doxorubicin, quercetin, and quercetin-loaded pSi nanoparticles, respectively. The results further indicated 16-fold downregulation of nucleolin mRNA expression after 48h of quercetin treatment of exponentially growing MCF-7 cells. Research limitations/implications: Whether pSi nanoparticle loaded quercetin can significantly downregulate nucleolin protein expression and its impact on apoptosis, cell proliferation, and angiogenic pathways need further investigation. Practical implications: The practical application of the proposed nanocarrier-based drug delivery system potentially lays out a path for developing targeted therapy against nucleolin-dysregulated cancer using natural products to minimize the side effects of conventional chemotherapeutic drugs. Originality/value: Inhibition of nucleolin and nucleolin regulated pathways using natural compounds and its targeted delivery with nanocarrier is not yet done.
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Dye sensitized solar cells are photoelectrochemical cells mimicking photosynthesis. They represent a new generation of solar cells which is intensively studied nowadays. This cell was fabricated using TiO2 nanoparticles coated on FTO glass, organic dyes as photosensitizer, PEDOT:PSS as counter electrode and iodide-triiodide as electrolyte. The present work aims at the use of low cost new organic dyes viz. biebrich scarlet, alizarine cyanine green and evans blue for DSSC as an alternative to metallic dyes. In the present work, I-V characteristics, energy or power conversion efficiencies of the dyes have been studied in different solvents. The photoelectrochemical properties of the dyes were observed under 1.5 AM condition.
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This study is devoted to quantify the near-bed turbulence parameters in mobile-bed flows with bed-load transport. A reduction in near-bed velocity fluctuations due to the decrease of flow velocity relative to particle velocity of the transporting particles results in an excessive near-bed damping in Reynolds shear stress (RSS) distributions. The bed particles are associated with the momentum provided from the flow to maintain their motion overcoming the bed resistance. It leads to a reduction in RSS magnitude over the entire flow depth. In the logarithmic law, the von Karman coefficient decreases in presence of bed-load transport. The turbulent kinetic energy budget reveals that for the bed-load transport, the pressure energy diffusion rate near the bed changes sharply to a negative magnitude, implying a gain in turbulence production. According to the quadrant analysis, sweep events in mobile-bed flows are the principal mechanism of bed-load transport. The universal probability density functions for turbulence parameters given by Bose and Dey have been successfully applied in mobile-bed flows.
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Purpose: The purpose of the paper is to characterize of syndiotactic polystyrene/carbon nanofiber composites through X-ray diffraction using adaptive neuro-fuzzy interference system and artificial neural network. Owing to their interesting mechanical, electrical and thermal properties, syndiotactic polystyrene (s-PS)/carbon nanofiber (CNF) composites have gained adequate importance in the scientific and industrial communities and as a result, characterization of s-PS/CNF is an issue of major interest to the researchers. Design/methodology/approach: In the present paper, two quantitative models, based on adaptive neuro-fuzzy interference system (ANFIS) and artificial neural network (ANN), are developed and compared with a goal of accurately predicting the intensity values from the scattering angle values in X-ray Diffraction (XRD) of syndiotactic polystyrene (s-PS)/carbon nanofiber (CNF) composites. Findings: Results demonstrate that both the proposed models are highly effective in estimating intensity from scattering angle. However, more accurate results are obtained with the ANFIS model as compared to the ANN model. Research limitations/implications: The results of the investigations carried out in this study is suggestive of the fact that both ANFIS and ANN can be used quite effectively for prediction of intensity from scattering angle values in XRD of s-PS/CNF composites. Originality/value: The proposed ANFIS and ANN model-predicted intensity values are in very good agreement with the experimental intensity values. However, it is seen that, irrespective of the type of composite sample, the proposed ANFIS models outperform the proposed ANN models in terms of prediction accuracy.
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