A study of vegetable oil modified QCM sensor to detect ß-pinene in Indian cardamom.

A quartz crystal microbalance (QCM) sensor was developed in this study with the vegetable oil from olive (OLV-QCM) to detect an important volatile organic compound, ß-pinene in Indian cardamom. Hydrophobic vegetable oil from olive, which contains oleic acid and omega-9, a monounsaturated fatty acid was found to be suitable for binding ß-pinene through non-covalent bonds. The fabricated QCM sensor coating was examined with the field emission scanning electron microscope (FESEM) and Fourier-transform infrared spectroscopy (FTIR) to determine its surface morphology and chemical compositions. The sensitivity, reproducibility, repeatability, and reusability were studied for the developed sensor. Notably, the sensor was observed to be highly selective towards ß-pinene as compared to the other volatile components present in cardamom. The limit of detection (LOD) and limit of quantitation (LOQ) parameters were determined as 5.57 mg L-1 and 18.57 mg L-1, respectively. Moreover, the adsorption isotherm models of the sensor were studied to validate the physical adsorption affinity towards ß-pinene applying Langmuir, Freundlich, and Langmuir-Freundlich isotherm models. The sensor showed a correlation factor of 0.99 with the peak area percentage of gas chromatography-mass spectrometry (GC-MS) analysis for ß-pinene in cardamom samples. The sensor was prepared with natural vegetable oil, unlike health hazard chemicals. In addition to this, the low-cost, easy fabrication process ensured the suitability of the sensor for practical deployment.

A brief review on solid lipid nanoparticles: part and parcel of contemporary drug delivery systems.

Drug delivery technology has a wide spectrum, which is continuously being upgraded at a stupendous speed. Different fabricated nanoparticles and drugs possessing low solubility and poor pharmacokinetic profiles are the two major substances extensively delivered to target sites. Among the colloidal carriers, nanolipid dispersions (liposomes, deformable liposomes, virosomes, ethosomes, and solid lipid nanoparticles) are ideal delivery systems with the advantages of biodegradation and nontoxicity. Among them, nano-structured lipid carriers and solid lipid nanoparticles (SLNs) are dominant, which can be modified to exhibit various advantages, compared to liposomes and polymeric nanoparticles. Nano-structured lipid carriers and SLNs are non-biotoxic since they are biodegradable. Besides, they are highly stable. Their (nano-structured lipid carriers and SLNs) morphology, structural characteristics, ingredients used for preparation, techniques for their production, and characterization using various methods are discussed in this review. Also, although nano-structured lipid carriers and SLNs are based on lipids and surfactants, the effect of these two matrixes to build excipients is also discussed together with their pharmacological significance with novel theranostic approaches, stability and storage.

A Composite Mode Differential Gene Regulatory Architecture based on Temporal Expression Profiles.

Exploring the complex interactive mechanism in a Gene Regulatory Network (GRN) developed using transcriptome data obtained from standard microarray and/or RNA-seq experiments helps us to understand the triggering factors in cancer research. The Transcription Factor (TF) genes generate protein complexes which affect the transcription of various target genes. However, considering the mode of regulation in a time frame such transcriptional activities are dependent on some specific activation time points only. It is also crucial to check whether the regulating capabilities are uniform across varied stages, especially when periodicity is a big issue. In this context, we propose an algorithm called RIFT which helps to monitor the temporal differential regulatory pattern of a Differentially Expressed (DE) target gene either by a TF gene or a group of TF genes from a large time series (TS) data. We have tested our algorithm on HeLa cell cycle data and compared the result with its most advanced state of the art counterpart proposed so far. As our algorithm yields up stringent mode and target specific significant valid TF genes for a DE gene, we can expect to have new forms of genetic interactions.