DNA interaction,anti-proliferative effect of copper oxide nanocolloids prepared from metallosurfactant based microemulsions acting as precursor,template and reducing agent

In the present study, we have synthesized mixed cuprous/copper oxide nanosuspensions by metallosurfactant based microemulsion technique. Three metallosurfactants were synthesized which includes two non-ionic double chained metallosurfactants with C₁₂, C₁₆ chains with coordinated copper i.e. Cudda and Cuhexa, respectively. Another cationic double chained metallosurfactant with loosely bound metal (Cuctac) was also prepared. The prepared metallocomplexes were characterized using FTIR, elemental analysis, and NMR. The effect of the position of metallosurfactant in microemulsion on the fabrication and properties of nanosuspensions was elucidated. In this method, no external reducing agent and capping agent were added and tween 80 acted both as reducing and stabilizing agent for the nanoparticles. The synthesized nanoparticles were characterized and it was observed that mixed copper and cuprous oxide particles are present in colloidal suspension for all the three studied metallosurfactants. The kinetics of formation of mixed copper/cuprous oxide nanosuspensions (Ns) and their stability was estimated using Uv-visible spectroscopy. Further, the binding and interactions of copper nanosuspensions with calf Thymus DNA (CT-DNA) were assessed using Uv–vis spectroscopy, circular dichroism and gel electrophoresis. Additionally, the antioxidant activity of the Cu Ns was checked using DPPH assay. The role of positive charge on nanoparticles as evaluated from Zeta potential was responsible for DNA affinity. The DNA conformational changes in the presence of nanosuspensions and relevant scavengers were investigated. Further, the anti-proliferative activity of copper Ns was assessed using HeLa cells and Cuhexa derived Ns were proved to be active with highest activity at a low concentration and were nontoxic towards normal cell lines. In summary, this work demonstrates a softer approach for the synthesis of copper nanosuspensions with a size range of 2–5?nm and evaluated the role of type and structure of metallosurfactant on size, stability of particles and anti-proliferative activity.     

Synthesis,structure, antioxidant activity,and water solubility of trolox ion conjugates

The interaction of trolox with ammonia, alkylamines of different classes, and amino derivatives of heterocyclic compounds, including nitroxyl radicals and alkaloids, led to the production of ammonium salts called ion conjugates (ICs). Five ICs were characterised by X-ray diffraction. This is the first time a wide range of ICs were made from trolox with amines, and ESI-MS data demonstrated they have the potential to generate pseudomolecular [(A^?B⁺)?+?H]⁺ ions. For all obtained trolox ICs, a significant increase (1–3 orders of magnitude) in water solubility was achieved while retaining high antioxidant activity. ICs synthesised from two biologically active fragments may be used to create polyfunctional agents with varying solubility and bioavailability.     

Singular value based characterization and analysis of thermal patches for early breast abnormality detection

The purpose of this study is to develop a novel breast abnormality detection system by utilizing the potential of infrared breast thermography (IBT) in early breast abnormality detection. Since the temperature distributions are different in normal and abnormal thermograms and hot thermal patches are visible in abnormal thermograms, the abnormal thermograms possess more complex information than the normal thermograms. Here, the proposed method exploits the presence of hot thermal patches and vascular changes by using the power law transformation for pre-processing and singular value decomposition to characterize the thermal patches. The extracted singular values are found to be statistically significant (p?<?0.001) in breast abnormality detection. The discriminability of the singular values is evaluated by using seven different classifiers incorporating tenfold cross-validations, where the thermograms of the Department of Biotechnology-Tripura University-Jadavpur University (DBT-TU-JU) and Database of Mastology Research (DMR) databases are used. In DMR database, the highest classification accuracy of 98.00% with the area under the ROC curve (AUC) of 0.9862 is achieved with the support vector machine using polynomial kernel. The same for the DBT-TU-JU database is 92.50% with AUC of 0.9680 using the same classifier. The comparison of the proposed method with the other reported methods concludes that the proposed method outperforms the other existing methods as well as other traditional feature sets used in IBT based breast abnormality detection. Moreover, by using Rank1 and Rank2 singular values, a breast abnormality grading (BAG) index has also been developed for grading the thermograms based on their degree of abnormality.