PSG College of Arts & Science

A urea-based fluorescent chemosensor, ITCQ, was developed for the selective detection of Cu²⁺ ions in a DMSO/H₂O (1:1, v/v) medium buffered with 50 mM HEPES at pH 7.4. Upon excitation at 350 nm, Cu²⁺ induced a marked fluorescence quenching via an intramolecular charge transfer (ICT) mechanism. Probe ITCQ demonstrated high selectivity for Cu²⁺ over other metal ions, as confirmed by competitive binding studies. Stern-Volmer analysis yielded a quenching constant of 3 × 10⁴ M^-1, with a low detection limit of 2.23 nM and a quantification limit of 7.45 nM. Job's plot, along with HRMS, IR, and ¹H NMR titration, confirmed a 1:1 binding stoichiometry. The sensor exhibited excellent reversibility and reusability, supporting its practical utility. Real sample analyses, including water and food matrices, validated its effectiveness. Additionally, swab and paper strip assays demonstrated strong potential for portable, on-site Cu²⁺ monitoring. With a good sensitivity, selectivity, and field applicability, probe ITCQ marks a meaningful advancement in metal ion sensing.

Background: The utilization of solar radiation for generating thermal energy has garnered a significant amount of attention, especially with the rising demand for sustainable power and heating sources.Nanofluids appeared as promising options for enhancing the efficiency of solar-thermal systems owing to their superior heat transmission properties.In this aspect, the present research deals with Ree-Eyring hybrid nanofluid $ ({\rm SWCNT-MWCNT/H}_2{\rm O}) $ (SWCNT-MWCNT/H2O) flow in the presence of thermal radiation effect and shape factor to examine the thermal behavior in solar panels.Addnl., the innovation lies in the field of artificial neural networks and fluid flow anal. as an integrated approach.Methodol.: The considered phys. interpretation is stated in the form of nonlinear partial differential equations.To facilitate the computation process, the governing equations turned into nondimensional ordinary differential equations with the help of invariant transformations.The converted equations are treated scientifically using the NDSolve methodol., which automatically adjusts the step size.In further, an artificial neural network-based multi-layer perceptron deploying the Levenberg-Marquardt model is employed to forecast the measurements of phys. quantities.Core Findings: The markable outcomes from this advanced work imply that the stretching surface has an important role in analyzing the thickness of the boundary layer.The improving Weissenberg number enhances the boundary layer thickness, leading to a magnification in the momentum field of the non-Newtonian fluid.In addition, thermal radiation is captured as a second significant influence on temperature distribution.It follows that enhancing the Radiation parameter upsurges the thermal layer.The variation of the volume fraction of nanoparticles resulted in higher temperatures due to the Hamilton-Crosser model, which involves the cylindrical shape of the nanoparticles.Validation: The validation of the current work is explored by comparing it with the existing literature in certain instances.The incorporation of multi-layer perceptron for hybrid nanofluid delivers the performance capacity of high prediction with the error 4.83E-06, 1.11E-10 and 2.4E-08.Applications: The existing optimization approach provides a new perspective on solar-powered offshore, solar vehicles, solar-powered charging stations, solar power greenhouse and solar water pump implementation.

Triple-negative breast cancer (TNBC) is a significant global health issue, with high mortality rates. The chemotherapeutic drugs currently used for TNBC have significant side effects, impacting both normal and cancer cells. In this study, we investigated a potential use of fruit peel extract of Psidium guajava (PGP) encapsulated with chitosan nanoparticles (CSNPs) to combat TNBC. The synthesized PGP-CSNPs were characterized using UV-vis spectroscopy, Fourier transform infra-red (FTIR) spectroscopy, TEM and GC-MS. The maximum loading capacity and encapsulation efficacy of PGP-CSNPs were found to be 72.5 ± 0.49% and 92.9 ± 0.10%, respectively. Furthermore, in vitro cytotoxicity was assessed, and the IC₅₀ value for PGP-CSNPs was 50.13 µg/mL. It was observed that PGP-CSNPs could induce apoptosis in MDA-MB-231 cells in dose-dependent manner. Furthermore, molecular docking was performed for bioactive compounds retrieved from PGP-CSNPs against human tumour suppressor proteins Bcl2, and results showed that the PGP-CSNPs had lower binding energy than cisplatin. This suggests that, the synthesized PGP-CSNPs have the potential to serve as a therapeutic agent for tackling TNBC. However, to validate its efficacy in human therapy, furthermore pre-clinical and clinical procedures should be examined, as this is an ongoing and significant step towards developing an effective and safe anticancer drug.