Sanatana Dharma College

Rationale: Due to a broad spectrum of anticancer potential, quercetin (Qu) has attracted substantial attention. However, its biological application is hindered by poor water solubility and low bioavailability. Amorphous solid dispersion (ASD) technology has emerged as an effective formulation strategy to overcome these limitations by converting crystalline drugs into a high-energy amorphous state and improving molecular dispersion within suitable polymeric carriers. Aim: To develop and characterise ASDs of Qu for enhanced anticancer properties. Methods: ASDs of Qu were developed using PVP K30 at varying weight ratios, (Qu:PVP): ASD1 (1:9), ASD2 (1:4), and ASD3 (1:2.3). The amorphous nature, molecular interactions, thermal stability, and relaxation dynamics of ASDs were characterised using scanning electron microscope (SEM), differential scanning calorimetry (DSC), Xray diffraction (XRD), fourier transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA), and broadband dielectric spectroscopy (BDS). The biological efficacy of the optimized formulation is assessed through antiproliferative studies using breast cancer cell lines, MDA-MB-231 and MCF-7. Results: SEM images showed the transformation of crystalline Qu into amorphous structures in the prepared ASDs, while Qu remained visible in the physical mixture. XRD showed amorphization of Qu in ASD1 and ASD2, identifying 1:9 and 1:4 ratios as optimal. However, ASD2 exhibited a mild tendency toward recrystallization. Pure Qu showed poor solubility (0.53 mu M in water, 17.32 mu M in ethanol), whereas ASDs significantly improved it (22.81-25.83 mu M in water, 50.13-99.24 mu M in ethanol). TGA showed Qu degradation at 375 K with major decomposition at 620 K (52% residue), whereas ASD1 degraded at 526.5 K and 820 K with 38.41% residue, indicating enhanced stability. DSC showed ASD1's glass transition at 395 K. BDS revealed a primary relaxation following VFT behaviour (Tg approximate to 438 K, fragility index 116) and a secondary Arrhenius-type relaxation (activation energy 49.5 kJ/mol). ASD1 demonstrated significantly enhanced antioxidant and anti-inflammatory activities compared to pure quercetin in water. In the DPPH assay (2-10 & micro;M), ASD1 in water showed 24% inhibition at 10 & micro;M, compared with 3% for Qu in water, whereas Qu in DMSO reached 65%. In the superoxide scavenging assay (20-100 & micro;M), ASD1 achieved 37% inhibition at 100 & micro;M compared to 10% for Qu in water (58% in DMSO). Similarly, in the nitric oxide scavenging assay, ASD1 exhibited 28% inhibition at 100 & micro;M, whereas Qu in water showed only 1.2% (51% in DMSO), confirming markedly improved bioactivity due to enhanced solubility and molecular dispersion. Cytotoxicity studies demonstrated that ASD1 exhibited lower IC50 values in ethanol against MDA-MB-231 (40.54 f 0.55 mu M vs 75.45 f 3.4 mu M for Qu) and MCF-7 (39.08 f 0.55 mu M vs 35.9 f 1.28 mu M for Qu), confirming its enhanced efficacy over pure quercetin. Discussion: The results suggest that PVP K30-based ASDs enhance the physicochemical and biological properties of Qu. The increased solubility and thermal stability of ASD1 contributed to its superior antiproliferative activity against TNBC cells. The intermediate fragility index observed by BDS supports its physical stability. Overall, ASD1, with the optimum drug-to-polymer ratio (1:9), shows strong potential as a formulation strategy to overcome Qu's biopharmaceutical limitations in cancer therapy. Conclusion: The development of ASDs of Qu with PVP K30 significantly enhanced its solubility, thermal stability, and antiproliferative activity. These results support the potential of amorphous dispersion as a viable strategy to improve the therapeutic utility of poorly soluble anticancer compounds like Qu in breast cancer management.

Hematologic malignancies, including leukemia, lymphoma, and multiple myeloma, are characterized by high relapse rates and therapeutic resistance, largely driven by stem cell–mediated mechanisms. Hematopoietic stem cells and leukemic stem cells play a dual role in maintaining normal hematopoiesis and promoting tumor initiation, progression, and resistance to treatment. This review provides a comprehensive analysis of the biological and molecular mechanisms underlying stem cell–driven oncogenic resistance, including genetic and epigenetic alterations, microenvironmental interactions, drug efflux, and cellular dormancy. Advances in bioanalytical technologies, such as multi-omics profiling and single-cell analysis, have significantly enhanced the understanding of tumor heterogeneity and resistance pathways. Furthermore, emerging drug delivery strategies, including nanocarrier-based systems and targeted therapeutics, offer promising approaches to overcome biological barriers and selectively eliminate resistant stem cell populations. Despite these advances, challenges remain in clinical translation, particularly in achieving effective targeting within the bone marrow niche and addressing inter-patient variability. Future perspectives emphasize the integration of artificial intelligence, precision medicine, and next-generation delivery platforms to improve therapeutic outcomes. Overall, targeting stem cell–driven resistance represents a critical strategy for advancing toward durable remission and potential cure in hematologic malignancies.

Tin monosulfide (SnS) is an excellent candidate for thin‐film solar cell absorbers due to its earth abundance, environmental friendliness, and suitable optoelectronic properties for efficient solar energy conversion. In this study, SnO 2 /SnS/CuSCN device structure, where SnO 2 serves as an electron transport and window layer simultaneously, while CuSCN acts as a hole transport layer, has been simulated using SCAPS‐1D. It is found that increasing the shallow acceptor density up to 10 17 cm −3 improves collection, while lowering the bulk and interface defect density in SnS is crucial for reducing the recombination. Losses are further reduced by managing resistance levels judiciously. The simulated structure after multiparameter optimization produces a theoretical highest conversion efficiency of 29.06%, with associated photovoltaic parameters of open‐circuit voltage () = 1.01 V, short‐circuit current density () = 33.62 mA/cm 2 , and fill factor = 85.89%. The observed parameters are typical of limits reported in literature on SnS absorbers. The main performance boost is due to favourable band alignment offered by SnO 2 and CuSCN that results in the reduced interface‐associated recombination losses. Overall, this study shows that the SnO 2 /SnS/CuSCN design has the potential for being an efficient and stable thin‐film solar cell architecture.

The rapid integration of generative artificial intelligence (GenAI) is transforming personal financial advisory services. While Large Language Models (LLMs) have demonstrated unprecedented strength in complex knowledge synthesis and macroeconomic sentiment analysis, their application is often constrained by high computational costs, latency, and significant data privacy issues. This paper investigates the new potential of small language models (SLMs) as an efficient, domain-specific alternative in the financial industry. While there is growth in GenAI adoption in India, there is a research gap in terms of the practical efficacy of different model architectures in nuanced financial scenarios (e.g., mitigating look-ahead bias and managing sensitive client data). This study employs a conceptual and comparative framework to distinguish the functional roles of LLMs and SLMs. It measures the performance of ten key financial advisory dimensions using industry data and current academic research. The results show that LLMs are better at macro-level tasks such as estate planning and insurance analysis. SLMs perform better for micro-level operations like cash management and debt management. The study concludes by suggesting a hybrid design that combines the cognitive power of LLMs and the localised precision of SLMs. This dual-model approach will be recognised as the best way to deliver scalable, secure, personalized digital wealth management in emerging economies.

Sulfur-doped graphene oxide (S-GO) nanocomposites were synthesized with varying sulfur concentrations (5 %, 10 %, and 25 %) to assess impact of sulfur incorporation on their structural, electrical, dielectric properties. Graphene oxide (GO) has been first prepared using a modified Hummers method and used to prepare the S-GO nanocomposites. The nanocomposites were studied for their morphological, structural, dielectric, and charge transport properties. Scanning electron microscopy paired with Energy Dispersive Spectroscopy (SEM-EDS) provides information on surface morphology and elemental compositional profile of the nanocomposites, confirming successful doping. Structural features were investigated using X-ray diffraction (XRD), which confirms formation of sulfur-doped GO. The produced nanocomposites were found to have a grain size <10 nm. Electrochemical impedance spectroscopy (EIS), frequency-dependent dielectric studies, and Jonscher’s power law examination of AC conductivity were employed to examine the materials' dielectric properties and charge transport characteristics. The non-Debye relaxation model (1 > α > 0 and β = 1) and various variable range hopping (VRH) conduction models were applied to obtain dielectric and hopping parameters. DC electrical conductivity measurements indicated that the Mott VRH conduction mechanism predominates in the S-GO nanocomposites.