Mangalayatan University

We construct a new class of exact solutions for shear-free, spherically symmetric radiating stars undergoing gravitational collapse in the presence of pressure anisotropy. Starting with the static metric potentials, we specialise the parametric family to the inhomogeneous anisotropic subclass n=- 2 and carry out a complete dynamical and thermodynamic analysis of this configuration. The interior solution, obtained in closed form, satisfies the standard regularity and energy conditions (null, weak, strong, and dominant), and is matched across the stellar boundary to an exterior Vaidya spacetime through the appropriate junction conditions. The configuration admits an initially static perfect-fluid limit and evolves smoothly into a dissipative collapse driven by radiative heat transport. A numerical study is also performed, wherein the effect of the anisotropy parameter on radial profiles and temporal evolutions of the density, pressures, heat flux, collapse rate, redshift, luminosity, and interior temperature is studied. The energy conditions are verified. The results demonstrate that increasing pressure anisotropy strengthens the matter variables, accelerates the contraction rate and enhances thermal dissipation throughout the radiating phase.

Drug-resistant epilepsy (DRE) remains a major therapeutic challenge, affecting millions of patients globally who do not respond to conventional antiepileptic medications. Recent evidence highlights GABA transporter 3 (GAT3), a glial subtype responsible for regulating extracellular GABA levels, as a promising molecular target for seizure control. Despite its therapeutic potential, selective and potent GAT3 inhibitors remain largely unexplored. This study aims to identify novel GAT3 inhibitors through an integrative computational strategy combining quantum chemical, molecular dynamics, and machine learning approaches to accelerate antiepileptic drug discovery. The cryo-EM-resolved human GAT3-SNAP-5114 complex structure was used for virtual screening, leading to the identification of three highest-ranking compounds, viz. Comp_1, Comp_2, and Comp_3, from the diverse chemically optimized screening library. Analysis of their quantum chemistry profiles indicated HOMO-LUMO energy gap values of 4.14 eV, 4.21 eV, and 3.26 eV, respectively, suggesting them to be maximally reactive with favorable electronic properties for interacting with biological molecules. Molecular dynamics simulations were performed in a fully hydrated POPC lipid bilayer using the AMBER force field, providing a physiologically relevant environment for assessing ligand binding and transporter dynamic, revealed stable binding modes, with the highest structural integrity or least deviations in the structure with Comp_2, having RMSD values ranging from 2.5 to 3.0 Å, with strong hydrogen bonding, while the binding mode was more flexible with strong anchorage for Comp_3, with its mode involving diverse interactions in the complex. Principal component and free energy landscape analyses identified energetically favorable, ligand-induced conformational states. Machine learning–based pIC₅₀ predictions using the AdaBoost regressor yielded values of 7.95 (Comp_1), 7.98 (Comp_2), and 7.63 (Comp_3), all comparable or superior to the reference inhibitor (7.89). A novel approach for network pharmacology integrating detailed drug-gene interaction profiling was additionally used to improve systems-level understanding of the discovered compound. These findings validate the potential of Comp_1–3 as lead GAT3-targeting antiepileptic agents. A docking-based virtual screening of a structurally diverse compound library was performed against the cryo-EM structure of human GAT3 in complex with the reference inhibitor SNAP-5114. The top-scoring ligands were subjected to density functional theory (DFT) analysis to assess electronic properties such as HOMO-LUMO energy gaps, reflecting potential binding reactivity. Lead candidates were refined, docked, and evaluated through 500 ns molecular dynamics (MD) simulations, analyzing structural stability via RMSD, RMSF, hydrogen bonding, and interaction network profiles. Principal component analysis and free energy landscape evaluations were used to explore ligand-induced conformational dynamics. Furthermore, machine learning (ML) models—particularly the AdaBoost algorithm—were employed to predict pIC₅₀ values, confirming bioactivity trends. Finally, network pharmacology analysis was conducted to elucidate gene targets and pathway interconnections, revealing the multi-pathway involvement of top candidates in seizure regulation. This integrative computational framework underscores the potential of GAT3-focused modelling and ML-guided screening for rational antiepileptic drug design.

Polymer-ceramic hybrid composites are emerging as attractive candidates for lightweight, corrosion-resistant absorber components in solar thermal collectors; however, their adoption is constrained by the intrinsically low thermal conductivity of polymers, processing-induced anisotropic heat transport, interfacial thermal resistance at tube/laminate joints, and durability challenges under outdoor exposure. This review provides a collector-centered synthesis of polymer-ceramic hybrid materials, emphasizing the translation of composite properties into collector-level outcomes rather than conductivity enhancement alone. A structure-property-performance mapping approach is presented to connect directional thermal conductivity ((k_in-plane), (k_perp)), thermal diffusivity, heat capacity, coefficient of thermal expansion, and service temperature with collector performance parameters such as heat removal effectiveness, overall heat losses, and stagnation behavior. Ceramic fillers (e.g., boron nitride, aluminum nitride, silicon carbide, alumina) are examined for stable conduction-network formation, coating compatibility, and long-term reliability, while carbon fillers (graphite, graphene nanoplatelets, carbon nanotubes) are evaluated for combined heat spreading and solar absorption benefits, with attention to emissivity penalties. Hybrid ceramic-carbon architectures and multilayer absorber designs are identified as the most promising routes to balance thermal transport, optical selectivity (high solar absorptance and low thermal emittance), manufacturability, and durability under UV, humidity, and thermal cycling.

Cancer remains a leading global health challenge, driving an urgent need for novel therapeutic agents that offer greater efficacy and safety. The pyrimidine nucleus, a foundational component of DNA, RNA, and key cofactors, stands as a privileged scaffold in anticancer drug discovery. This systematic review comprehensively analyzes the design, synthesis, and biological evaluation of new pyrimidine-based derivatives reported over the past decade. We detail modern design strategies, including molecular hybridization with heterocycles and natural products, scaffold morphing via ring fusion, and rational targeting of critical pathways such as kinase signaling (EGFR, VEGFR, CDKs) and nucleotide metabolism (TS, DHFR). The synthesis of these libraries leverages both classical cyclocondensation reactions and advanced, efficient methodologies. A critical analysis of In vitro data across diverse cancer cell lineages reveals potent, often nanomolar, cytotoxicity and elucidates established mechanisms of action, including apoptosis induction, cell cycle arrest, and enzyme inhibition. A comprehensive Structure-Activity Relationship discussion identifies key pharmacophoric features and substituent effects governing potency and selectivity. Despite promising results, significant challenges remain, particularly the frequent lack of in vivo validation and detailed mechanistic studies. Future progress hinges on integrating computational chemistry for rational design and ADMET prediction, exploring emerging targets, and rigorously pursuing the translational pathway to clinically viable, multi-targeted anticancer agents.

Objective: The present study focused on the design, characterization, and in vitro evaluation of a berberrubineembedded pH-responsive polymeric hydrogel system for colon-specific delivery aimed at targeted intervention in Crohn's disease. The hydrogel was synthesized using free radical polymerization of methacrylic acid and acrylamide with controlled crosslinking density to achieve pH-triggered swelling behaviour. Characterization: Drug–polymer compatibility was confirmed through FTIR analysis, demonstrating structural integrity without significant chemical interaction. The optimized formulation (F3) exhibited high encapsulation efficiency (84.6%) and an optimal gel fraction (90.5%), indicating a stable and well-formed polymeric network. Swelling studies revealed minimal expansion in acidic conditions (pH 1.2) and significant swelling at colonic pH (7.4), confirming strong pH responsiveness. In vitro pH-shift dissolution studies demonstrated negligible drug release in gastric conditions followed by enhanced release under simulated colonic conditions. Kinetic and Safety Analysis: Kinetic modeling indicated that the drug release followed the Korsmeyer–Peppas model with super case-II transport behavior, suggesting polymer relaxation-driven release. Surface morphology analysis showed a porous network architecture supporting diffusion-controlled release. Cytocompatibility assessment confirmed high cell viability, indicating formulation safety. Conclusion: Overall, the developed hydrogel system represents a promising colon-targeted delivery platform for localized therapy in inflammatory bowel disorders.