This study presents a comprehensive density functional theory (DFT) investigation into the stepwise reduction of nitrobenzene to aniline via nitroso and hydroxylamine intermediates. Two mechanistic pathways were explored: a non-catalyzed route in both gas and ethanol phases and a surface-catalyzed route facilitated by a palladium (Pd) catalyst. Geometry optimizations, thermodynamic parameters, frontier molecular orbital (FMO) analysis, and vibrational frequency (IR) simulations were carried out for all key species involved: nitrobenzene (Ph-NO₂), nitrosobenzene (Ph-NO), phenylhydroxylamine (Ph-NHOH), and aniline (Ph-NH₂). A comparison of gas-phase and solvent-phase geometries revealed solvent-induced elongation of N–O and N–H bonds, particularly in polar intermediates, consistent with ethanol’s stabilizing effect. FMO analysis showed a notable decrease in HOMO–LUMO energy gaps in the solvent phase, indicating enhanced reactivity. IR spectra further supported these findings, with observable shifts in characteristic stretching frequencies upon solvation. In the Pd-catalyzed pathway, adsorption of reactants and intermediates on the Pd surface significantly altered molecular geometries and lowered reaction energy barriers. Calculated adsorption energies and bond elongations suggest strong Pd–O and Pd–N interactions that facilitate bond activation. The overall energy profile indicates a smoother and more favorable reduction pathway on the Pd surface compared to the noncatalyzed routes. These results provide mechanistic insight into the catalytic role of Pd in hydrogenation reactions and highlight the importance of solvent effects in modulating electronic and structural properties. This comparative approach enhances our understanding of nitroarene reductions and offers valuable guidance for catalyst design and process optimization.
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 m3/h), and secondary air flow (6–74 m3/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 μm and 18–21 μm. The Pareto results revealed a clear trade-off: CAI decreased from ∼2.30 to ∼1.65 as CS increased slightly in the fine separation regime and stabilized at ∼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 tumor microenvironment (TME) is a central regulator and driver of lung cancer progression. Within this TME, cancer-associated fibroblasts (CAFs) serve as key mediators of crosstalk between tumor cells and the surrounding stroma. CAFs promote immunosuppression, remodel the extracellular matrix (ECM), induce abnormal hypoxia and altered metabolism, and contribute to therapeutic resistance. These effects arise through dynamic interactions with cancer cells, cancer stem cells, and other stromal and immune components in the TME. Recent studies have revealed substantial heterogeneity among lung CAFs, with distinct subsets identified by specific marker proteins. This heterogeneity is associated with distinct secretory profiles that support tumor growth. The present review summarizes current understanding of the roles of CAFs in lung cancer progression and therapy resistance. We outline emerging strategies for targeting lung CAFs, including disrupting their signaling pathways, inhibiting ECM remodeling, and blocking CAF-derived secreted factors. In addition, we address the conflicting roles of CAFs in responses to immunotherapy, chemotherapy, and radiotherapy. Finally, we discuss the therapeutic potential of novel approaches, including nanoparticle-based delivery systems, small-molecule inhibitors, natural compounds, and repurposed drugs.
Hepatocellular carcinoma (HCC) driven by chronic hepatitis B virus (HBV) infection remains a global health challenge, with late diagnosis and limited therapeutic options underscoring the need for novel biomarkers and mechanistic insights. Once considered guardians of the germline, PIWI-interacting RNAs (piRNAs) are now emerging as key somatic regulators of chromatin, transcription, and signaling in cancer. This review considers HBV a plausible perturbant of the hepatic piRNA ecosystem, through viral integration, epigenetic remodeling, and altered intercellular communication. Unlike prior reviews that mainly catalog PIWI/piRNA findings in HCC or summarize broader liver-cancer multi-omics, this article advances a testable HBV–piRNAome disruptor model with three falsifiable predictions: HBV integration and 3D genome rewiring alter piRNA-cluster output, HBx/HBsAg-driven chromatin remodeling shifts PIWI/piRNA stoichiometry, and spatially restricted tumor, stromal, and immune niches generate distinct piRNA signatures that can be mapped in matched tissue and plasma. This framework is intended to help move from association to testable mechanism and, where supported, to clinically anchored validation. This is a conceptual narrative review rather than a systematic review or meta-analysis; therefore, no PRISMA flow diagram is provided, and the cited literature was selected for conceptual and mechanistic relevance. We argue that decoding HBV-driven hepatocarcinogenesis requires linking piRNA dysregulation to the biological consequences of HBV integration, HBx-driven epigenetic remodeling, and niche-specific fibrogenic and immune reprogramming; spatial multi-omics should be used to localize these mechanisms to the relevant cell types and tissue compartments. Such systems-level profiling can help nominate candidate biomarkers and therapeutic vulnerabilities for future validation, but clinical translation will still require prospective cohorts, standardized EV/small-RNA workflows, rigorous functional confirmation, and formal safety/regulatory review before use in patients.
Heavy-metal-oxide (HMO) glass-ceramics that retain optical transparency while offering superior gamma- and X-ray attenuation are sought for next-generation radiation shields. In this work, a quinary tellurite-borate-zinc framework, 20TeO(2)-25B(2)O(3)-10ZnO-(20-x)BaO-25Bi(2)O(3)-xPbO (x = 2.5, 5, 7.5, 10 mol% %), was synthesized by conventional melt-quenching followed by controlled heat treatment to induce partial crystallization. The X-ray diffraction demonstrates that progressive replacement of B2O3 with PbO (x = 2.5-10 mol% %) drives nanocrystallization and densification. Systematic substitution of BaO with PbO increased the glass density from 5.77 to 6.06 g cm(-)(3). The PbO-doped glasses showed outstanding gamma-ray shielding effectiveness from 0.015-15 MeV, with the increased PbO level providing increased attenuation due to the contribution of higher density and higher atomic number. For example, at 0.015 MeV, the Pb10 glass had the highest maximum linear attenuation coefficient (LAC) of similar to 492.4 cm(-1) and the lowest half-value layer (HVL) of 0.001 cm, and at 15 MeV maintained superior performance, over Pb2.5, with a similar to 35% higher LAC than the other PbO-doped glasses. This supports recent findings that nano-PbO significantly enhances photon-matter interactions due to its higher surface-to-volume ratio and more uniform spatial distribution. These results indicate that tellurite-borate glass ceramics incorporating nano-PbO may produce clear, lightweight shields that are comparable to traditional lead-based ones but with reduced toxicity and processing issues.
