Soil salinity poses a significant challenge to agricultural productivity, threatening global food security. Although conventional approaches such as selective breeding and genetic modification have sought to enhance plant resilience, they often face limitations in adaptability, scalability, and cost. In contrast to conventional methods, emerging research underscores the promising role of plant-associated halotolerant bacteria and metagenomic approaches in addressing salt stress. Halotolerant bacteria contribute to salinity mitigation through multiple mechanisms, including phytohormone synthesis, activation of antioxidant enzymes, mineral and nutrient acquisition, osmolyte accumulation, ion homeostasis, and exopolysaccharide production. Additionally, they restrict excessive Na⁺ uptake and induce salt stress-responsive genes, collectively alleviating the physiological impact of salinity and supporting sustainable agricultural practices. Metagenomics enables the identification of key bacterial taxa and functional gene elements associated with salinity resilience, facilitating the development of targeted bioinoculants and optimizing plant-microbe interactions. This review integrates multi-omics pipelines, synthetic microbe design strategies, and critical evaluation of field-level limitations, while outlining future directions for translating PGPR-mediated salt tolerance into sustainable agriculture.
This study reports the biological synthesis of environmentally friendly zinc oxide nanoparticles (ZnO-NPs) using the marine red alga Gracilaria corticata. The algal extract served as a natural reducing and stabilizing agent in the formation of ZnO nanoparticles (GC-ZnONPs). The synthesized nanoparticles were comprehensively characterized using UV–Vis spectroscopy, FTIR, XRD, SEM, EDX, HRTEM, DLS, zeta potential analysis, VSM, NMR and TGA/DTA. Characterization results confirmed that GC-ZnONPs possess a crystalline structure with predominantly spherical and hexagonal morphologies and a relatively uniform size distribution. The GC-ZnONPs exhibited significant antioxidant activity through inhibiting DPPH and H2O2 free radicals. Anti-inflammatory activity, evaluated using a bovine serum albumin (BSA) denaturation assay, demonstrated concentration-dependent inhibition of protein denaturation. In addition, GC-ZnONPs showed pronounced antibacterial activity against several pathogenic bacterial strains. Cytotoxicity assessment using the MTT assay revealed strong anticancer activity against AGS gastric cancer cells, with an IC₅₀ value of 53.16 µg/mL. Furthermore, molecular docking analysis demonstrated strong binding interactions between 2,4-di-tert-butylphenol, a bioactive compound isolated from G. corticata and key gastric cancer-associated proteins, including KRAS, PIK3CA, SMAD4, TP53 and CDH1, suggesting a potential multi-target therapeutic mechanism. Collectively, these findings indicate that GC-ZnONPs exhibit multifunctional biological activities, including antioxidant, anti-inflammatory, antibacterial and anticancer properties. Overall, the results highlight the promise of green nanomedicine for the development of environmentally sustainable, marine-derived nanotherapeutics for gastric cancer treatment.
In this study, we investigate the one-dimensional Chafee–Infante model, where heat diffusion serves as the primary mechanism of energy transfer. The Shehu transform is employed to derive solutions for three distinct forms of the Chafee–Infante equation, incorporating the time derivative in the Caputo fractional sense, and the resulting transformed systems are solved with the nonlinear terms using the Adomian decomposition method. The Chafee–Infante equation is widely used to model nonlinear phenomena in population dynamics, chemical reactions, heat transfer and neural activity. This study provides a new contribution by applying the Shehu decomposition method (SDM) to the time-fractional CI equation. The key advantage of the Shehu decomposition method (SDM) over transform-based hybrid methods such as Laplace–ADM, Sumudu–ADM and Elzaki–ADM lies in its direct handling of nonlinear problems without requiring inverse transforms, which significantly simplifies both analysis and computation. The present method also demonstrates accurate and convergent solutions, supported by error norms and rate of convergence analysis. A detailed comparison between the approximate and exact solutions demonstrates that the proposed hybrid approach is both highly accurate and computationally efficient for a broad class of nonlinear Chafee–Infante problems. For each case, the L_2 and L_∞ norms error norms are evaluated to assess accuracy. Numerical simulations, convergence investigations and comprehensive error and stability analyses consistently confirm excellent agreement between the analytical approximations and the exact solutions. The behavior of the solutions is further illustrated through three-dimensional surface plots and two-dimensional line graphs. Additionally, the numerical results obtained in this work are compared with existing findings in the literature, showing strong consistency and improved performance in terms of computational efficiency cost (CPU time).
Background VEXAS syndrome is a recently recognized, acquired monogenic adult onset hemato-inflammatory syndrome characterized by somatic mutations within the UBA1 gene. The acronym VEXAS stands for vacuoles, E1 enzyme, X-linked inheritance, autoinflammatory tendencies, and somatic mutations. It presents as a severe progressive disease displaying varied characteristics that bridge hematologic and rheumatologic domains. Herein, we describe a series with a detailed evaluation of 11 cases of VEXAS syndrome. Materials and methods A comprehensive retrospective analysis of patients diagnosed with VEXAS syndrome over the last 5 years (2020-2025) was conducted. Data on clinical presentation, histopathological findings, genetic characteristics, and outcomes were recorded for systematic characterization. Results A total of 11 cases of VEXAS syndrome were identified. All the patients were males with an age range from 42 to 77 years. Prominent clinical characteristics included history of fever (11), arthritis/arthralgia (10), inflammatory skin lesions (7), vasculitis (6), ocular inflammatory conditions (6), relapsing polychondritis (6), unprovoked venous thrombosis (5), and auricular chondritis (4). Persistent unexplained cytopenia was present in all the patients, manifesting as anemia (10, 8 of which were macrocytic), thrombocytopenia (4), and neutropenia (2). Bone marrow examination was performed in nine cases, five showed morphologic dysplasia. Furthermore, all nine cases characteristically showed cytoplasmic vacuolations in hematopoietic precursors. UBA1 somatic mutations included p.Met41Thr (c.122 T>C Exon 3) (55%), p.Met41Val (c.121 A>G Exon 3) (27%), p.Met41Leu (c.121 A>C Exon 3) (9%), and a variant in the acceptor splice site of Exon 3 (c.118 G>C) (9%). p.Met41Val is associated with inferior overall survival (OS). Conclusion This study characterizes the clinical, morphologic, and laboratory features of VEXAS syndrome and presents the first comprehensive patient cohort from India. With a complex and heterogeneous clinical profile, awareness of the disease is particularly essential among hematologists, rheumatologists, and dermatologists for accurate diagnosis and management.
This study examines whether firm-level pricing power influences innovation investment among Indian listed non-financial firms. The study is motivated by India’s relatively low and uneven private-sector R D participation, despite increasing policy emphasis on innovation-led industrial growth. Drawing on Schumpeterian innovation theory and the internal finance hypothesis, the study argues that firms with stronger pricing power can generate higher operating margins and internal financial slack, which may help them finance long-term and uncertain R D activities. Pricing power is measured using the Lerner Index, while innovation investment is captured through R D intensity. The analysis uses BSE 500 non-financial firms over the period 2012–2024, forming a balanced panel of 4,550 firm-year observations. Fixed Effects panel regression is employed as the baseline estimation method to control for unobserved firm-specific heterogeneity, while System GMM is used to address endogeneity. The findings show that pricing power has a positive and significant effect on R D intensity. The results remain consistent after applying System GMM, suggesting that the relationship is not driven merely by firm heterogeneity or simultaneity bias. These findings contribute to the market power–innovation debate by showing that pricing power can operate as an internal finance mechanism for innovation in an emerging economy. The study offers implications for managers, policymakers, and investors seeking to strengthen private-sector innovation in India.
