Amjad Ali

Authors Shaista Khan, Sanam Nusrat, Amjad Ali, Shumaila Khero, Asadullah, Muhammad Imran Farid, Asma Nadeem, Author DOI:

This study reports the development of a microcontroller-based, portable fluorometric sensing device for the rapid and highly sensitive detection of picric acid (PA), a hazardous nitroaromatic explosive. The sensor utilizes biomass-derived carbon dots synthesized from watermelon extract (Citrullus lanatus) vi

Accurate geospatial inventories of fruit orchards are essential for precision horticulture and food security, yet Pakistan lacks consistent spatial datasets at district and tehsil levels. This study presents the first national-scale, object-based Random Forest (RF) framework for orchard delineation and yield estimation by integrating multi-temporal Sentinel-2 imagery on Google Earth Engine (GEE) with high-resolution Pakistan Remote Sensing Satellite-1 (PRSS-1) data. Among the tested classifiers, RF achieved the highest performance on Sentinel-2 data (Overall Accuracy (OA) = 79.0%, kappa (κ) = 0.78), outperforming Support Vector Machines (OA = 74.5%, κ = 0.74) and Gradient Boosting Decision Trees (OA = 73.8%, κ = 0.73), with statistical significance confirmed (McNemar’s χ2, p 560 kg tree−1). The resulting multisensory geospatial inventory of citrus and mango orchards establishes a scalable, transferable, and operationally viable framework for orchard mapping yield forecasting, and resource planning, demonstrating the strategic value of national satellite assets for food security monitoring in data-scarce regions.

This study presents a dynamic hydrogen-bonding switching strategy to control crystal transformation, enabling multi-stimuli-responsive fluorescence. By exploiting the conformational adaptability of V-shaped donors and their interactions with solvents, the system achieves wide-range (>140 nm) reversible emission switching or quenching. These properties are further demonstrated in thermal sensing, selective nitroaromatic detection, and multi-level anti-counterfeiting applications.

Hesperidin, a flavonoid abundantly found in citrus fruits, has demonstrated a substantial role in the management of various pathogeneses. Furthermore, the wide range of health-promoting properties of hesperidin, including antioxidant, anti-inflammatory, anti-cancerous, hepatoprotective, neuroprotective, nephroprotective, and cardioprotective effects, has been well documented. Additionally, persuasive evidence from both in vivo and in vitro studies highlights its substantial roles in combating obesity, protecting the kidneys, liver, and lung tissue architecture, promoting wound healing, and modulating immune responses. This flavonoid acts as an effective antimicrobial agent against a wide range of microorganisms by inhibiting biofilm formation and disrupting the cell membrane. This review aims to deliver comprehensive insights into the therapeutic potential of hesperidin across different pathogenesis through distinct mechanisms. Moreover, it provides up-to-date evidence on the synergistic properties of this compound with other drugs as well as compounds, and emerging plans to enhance its efficiency in health management through various nanoformulation approaches. Despite its considerable therapeutic potential, the clinical application of hesperidin remains constrained by poor bioavailability, rapid degradation, and dosage-related limitations. Addressing these challenges will require extensive further research to clarify its mechanisms of action, safety profile, and therapeutic efficacy in managing underlying pathogenic conditions.

In the original publication [...]

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, underscoring the need for robust molecular biomarkers to improve prognosis and therapeutic strategies. Although advances have been made in imaging, surgery, as well as systemic therapies, the prognosis of HCC remains poor due to late detection, high recurrence, and molecular heterogeneity, underscoring the significance of identifying robust prognostic biomarkers and therapeutic targets. mRNA-sequencing data from the TCGA-HCC cohort were examined to recognize differentially expressed genes (DEGs) between tumor and normal tissues. Weighted gene co-expression network analysis (WGCNA) was applied to uncover key gene modules and hub genes. Protein–protein interaction network (PPIN) construction and modular analysis further refined candidate genes. Univariate overall survival (OS) analysis identified five genes (TTK, CENPA, NUF2, KIF2C, and CDCA8) whose elevated expression significantly correlated with poor patient survival. Pathway enrichment analysis exhibited a strong association with mitotic checkpoint and kinetochore signaling pathways. Mutational profiling demonstrated frequent genomic alterations, particularly in NUF2, whereas immune infiltration analysis demonstrated significant correlations between NUF2 expression and multiple immune cell populations. In this study, we employed an integrative transcriptomic and systems biology approach to recognize prognostically relevant hub genes in HCC. Collectively, this finding highlights the critical genes that may serve as prognostic biomarkers and potential therapeutic targets in HCC.

PLOS ONE , May 2026 This is a preview of a remote PDF: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0349094&type=printable

Abstract Aims Polymer-free drug-eluting stents were developed to enhance vascular biocompatibility and safety while maintaining antirestenotic efficacy.