Gokul Global University

A novel ionic liquid-functionalized graphitic carbon nitride/graphene oxide (g-C3N4-IL@GO) nanocomposite was successfully synthesized through a facile multi step strategy. Graphitic carbon nitride (g-C3N4) was prepared by thermal polymerization and then functionalized with a DABCO-based ionic liquid via the substitution of surface active sites with 1,4-dibromobutane and functionalized DABCO to afford g-C3N4-IL. The functionalized material was then combined with graphene oxide sheets by interfacial assembly. This approach facilitated the development of a hybrid layered nanostructure with enhanced physicochemical properties for energy storage applications. The successful functionalization and nanocomposite formation were verified by complementary structural and surface analysis methods such as (XRD), (FTIR), (SEM), (EDS), (XPS), (BET), and (TGA). The electrochemical behavior of the g-C3N4-IL@GO electrode material was comprehensively analyzed using CV, GCD, and EIS in a three electrode system. The CV curves exhibited redox features and a total charge-storage mechanism comprising of Faradaic and electric double-layer capacitance. The GCD curves showed a high specific capacitance value of 425F/g at 2 A/g with a high current processing ability and good utilization of electroactive sites with a favorable ion-accessibility in the electrode. The excellent cycling stability of the electrode with 93% of initial capacitance retained after 10,000 successive cycles demonstrated that the electrode possessed robust structural integrity and long-term electrochemical durability. The energy and power densities were calculated from the GCD curves of the three-electrode system and found to be as high as 35 Wh/kg and 549 W/kg, respectively. To sum up, these results demonstrate the synergistic effect of the g-C3N4 framework, ionic liquid group and graphene oxide layer structure, which leads to fast charge transport, high reversibility, and better electrochemical performance. Thus the composite could be considered a potential candidate for supercapacitor electrodes.

The dynamic interplay between tumor cells and immune components within the tumor microenvironment (TME) is a critical determinant of cancer progression. At the tissue and cellular levels, immune surveillance mechanisms mediated by cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells are responsible for recognizing and eliminating transformed cells. However, tumor cells remodel their microenvironment to establish an immunosuppressive niche that supports immune evasion. Increasing evidence identifies long non-coding RNAs (lncRNAs), particularly members of the small nucleolar RNA host gene (SNHG) family, as key regulators of tumor-immune cell interactions. This review focuses on the cellular and tissue-specific mechanisms by which SNHG lncRNAs (including SNHG1, SNHG3, SNHG4, SNHG9, SNHG10, SNHG12, SNHG14, SNHG15, SNHG17 and SNHG20) modulate the immune landscape across diverse malignancies. Mechanistically, SNHGs function through competitive endogenous RNA (ceRNA) networks, signaling pathway modulation, and epigenetic regulation to influence immune cell differentiation and activity within the TME. They promote regulatory T cell (Treg) expansion, drive macrophage polarization toward the M2 phenotype, suppress NK cell cytotoxicity, impair CTL responses, and enhance expression of immunosuppressive mediators such as PD-L1 and IL-6R. By reshaping immune cell composition and function at the tissue level, SNHG lncRNAs contribute to the establishment of an immunologically permissive tumor niche. Understanding these cellular regulatory circuits highlights SNHG family members as potential modulators of tumor-immune crosstalk and as promising targets for microenvironment-directed therapeutic strategies.

This study introduces an AI-driven integrated framework for predicting and optimizing the performance of turbo air classifiers, addressing the limited application of advanced intelligence techniques in fine-particle processing. A turbo air classifier was examined using three operational inputs, rotor speed (561-1739 rpm), primary air flow (98.87-351.13 m(3)/h), and secondary air flow (6-74 m(3)/h), to predict two key performance indicators: cut size (CS) and classification accuracy index (CAI). Multilayer perceptron neural networks (MLPNNs) were optimized using modified particle swarm optimization (MPSO), marine predators algorithm (MPA), and gray wolf optimizer (GWO). MPSO-MLPNN yielded the best CS predictions (R > 0.999), while GWO-MLPNN achieved the most accurate CAI predictions (R > 0.99). Pareto-based multi-objective bat algorithm (MOBA) was then applied to minimize CAI while constraining CS within 15-18 mu m and 18-21 mu m. The Pareto results revealed a clear trade-off: CAI decreased from similar to 2.30 to similar to 1.65 as CS increased slightly in the fine separation regime and stabilized at similar to 1.58-1.60 for coarser separation. Optimal conditions showed that fine separation requires high rotor speed with moderate-high airflow, whereas coarser, energy-efficient operation is achievable with lower rotor speeds and high airflow.

The persistent global burden of tuberculosis (TB) and the context-dependent efficacy of the Bacillus Calmette–Guérin (BCG) vaccine necessitate the development of innovative prophylactic strategies. mRNA vaccine platforms have emerged as a transformative toolkit, offering unprecedented versatility in antigen design and manufacturing scalability. This inclusive innovation review synthesizes the molecular engineering and immunological mechanisms of mRNA TB vaccines, evaluating their capacity to address the unique challenges posed by the intracellular lifestyle of Mycobacterium tuberculosis (Mtb). mRNA platforms realistically offer superior endogenous antigen production for CD8⁺ T-cell activation and the flexibility to encode multi-stage fusion antigens targeting both active and latent bacilli. However, significant constraints remain; mRNA technology alone cannot resolve the spatial sequestration of Mtb within necrotic granulomas or the "recruitment lag" of systemic immunity to the lung parenchyma. Achieving sterile protection requires a transition toward mucosal delivery systems capable of inducing lung TRM cells. Furthermore, translational success must be measured beyond classical interferon-gamma (IFN-γ) readouts, prioritizing correlates of protection that reflect site-specific immunity, safety in latently infected populations, and the deployment of thermostable formulations in endemic regions. By integrating mRNA constructs into heterologous prime-boost regimens and host-directed therapies, the field moves toward a precision vaccinology framework capable of curtailing the TB epidemic.

Microsphere-based technologies have increasingly gained attention as adaptable and multifunctional tools in breast cancer research and clinical care. Traditional approaches, including two‑dimensional cell cultures, systemic drug delivery, and broad diagnostic methods, often fail to accurately mimic tumor behavior or deliver therapeutics efficiently. Microspheres, with their customizable size, composition, mechanical characteristics, and surface chemistry, offer a platform that can overcome many of these limitations. Their ability to modulate cell–material interactions and control local drug release positions them as valuable components in modern cancer modeling, diagnosis, and therapy. The primary aim of this review is to synthesize current advancements in microsphere technologies as they apply to breast cancer. The review seeks to evaluate how microsphere-based systems contribute to improved tumor modeling, enhanced diagnostic accuracy, and more effective therapeutic strategies. Additionally, it identifies existing challenges and defines future directions needed to translate these technologies into routine clinical use. This review explores microsphere technologies in breast cancer research and clinical applications. It highlights their roles in three‑dimensional tumor modeling, advanced diagnostic platforms integrating imaging, electrochemical sensors, and microfluidics, and controlled drug delivery systems for chemotherapeutic and endocrine therapies. The review also discusses stimuli‑responsive microspheres enabling targeted release and clinical uses such as transarterial chemoembolization and yttrium‑90 radioembolization. Evidence from experimental, preclinical, and clinical studies is synthesized to evaluate current progress and future potential. Findings indicate that microsphere-enabled three‑dimensional tumor culture systems better replicate key hallmarks of breast cancer biology compared to traditional two‑dimensional platforms. These 3D systems capture tumor architecture, mechanobiology, metabolic diversity, and drug resistance behavior more accurately, improving the predictive value of drug screening. Diagnostic innovations demonstrate that functionalized microspheres significantly enhance analytical sensitivity, allow dynamic monitoring of tumor biomarkers, and improve cell tracking capabilities across imaging and sensor-based platforms. Therapeutic applications show that microspheres provide sustained and localized drug delivery, reducing systemic toxicity and enhancing treatment efficacy. Stimuli-responsive microspheres allow precisely targeted and temporally coordinated release, enabling more personalized and adaptive treatment strategies. Microsphere-based technologies represent a powerful and multifaceted toolkit for advancing breast cancer research, diagnosis, and therapy. Their versatility enables improved disease modeling, more sensitive and real-time diagnostics, and effective localized treatment strategies. Despite substantial progress, persistent challenges, such as standardization, biological complexity, reproducibility, scalability, and integration into routine clinical workflows, continue to hinder widespread adoption.