Browse Articles
Discover research articles across all indexed journals
Bipolar resistive switching in amorphous calcium zirconate memristors
Therapeutic potential of photoimmunotherapy in solid tumors expressing CD98 heavy chain
Abstract Near-infrared photoimmunotherapy (NIR-PIT) is an emerging targeted cancer therapy that uses an antibody–photoabsorber conjugate. In this study, we evaluated the therapeutic potential of NIR-PIT targeting CD98 heavy chain (CD98hc), a transmembrane glycoprotein that is highly expressed in various solid tumors and is associated with poor prognosis. We prepared a conjugate of the clinically tested anti-CD98hc antibody IGN523 and photoabsorber IRDye700DX (IGN523-IR700). The therapeutic efficacy was assessed in vitro using four CD98hc-expressing cancer cell lines and in an in vivo tumor xenograft mouse model. In vitro, IGN523-IR700 binds to cancer cells and induces rapid and light dose-dependent cell death upon near-infrared light exposure. In the in vivo model, intravenous administration of IGN523-IR700 followed by tumor-directed light irradiation resulted in significant tumor growth inhibition compared with that in the control groups. These results demonstrate that CD98hc is a viable and effective target for NIR-PIT. Given its widespread expression, targeting CD98hc may significantly broaden the applicability of NIR-PIT to diverse cancer types.
Bacterial community shifts in response to arsenic and cadmium contamination in aquatic ecosystems: a microcosm study
Abstract Industrialization and urbanization have led to increased levels of heavy metal pollution in aquatic ecosystems. Heavy metals exhibit toxicity even at low concentrations, posing risks to aquatic organisms, human health, and overall ecosystem health. To investigate bacterial community responses to arsenic (As) and cadmium (Cd) contamination, a microcosm experiment was conducted, followed by 16S rRNA gene amplicon sequencing, and indicator species were identified for each metal. Two concentrations (1 mg L − 1 and 10 mg L − 1 ) of As and Cd were applied separately, and their effects were examined. Bacterial communities in water without sediment changed more rapidly than those with sediment. In contrast, the bacterial communities in sediment and in water containing sediment remained relatively stable. Additionally, bacterial communities responded more sensitively to Cd exposure than to As at equivalent concentrations. A total of two ( Rhizorhapis and Methylotenera ) and six ( Polynucleobacter , Aquabacterium , Curvibacter , Ramlibacter , Methylophilus , and Undibacterium ) genera were identified as indicator species for As and Cd contamination, respectively, suggesting that shifts in bacterial communities can reflect contamination by specific heavy metals. These findings highlight the potential of microbial community profiling as an effective tool for the early detection and monitoring of heavy metal pollution in aquatic environments.
Entomopathogenic activity of Purpureocillium takamizusanense against diverse agricultural pests
Ischemic preconditioning modulates the acute post-exercise inflammatory, angiogenic, and neurotrophic response in endurance runners
Research on a multi-strategy enhanced parrot optimization algorithm STPO for Complex optimization problems and its applications
Abstract Metaheuristic optimization algorithms are widely used to tackle complex, high-dimensional, and nonlinear problems by mimicking natural or social behaviors, showing great potential for future development. Among them, the Parrot Optimization (PO) algorithm, inspired by the green-cheeked conure, exhibits strong adaptability. However, in high-dimensional scenarios, it often converges slowly and is prone to getting trapped in local optima. To address these limitations, this study proposes a multi-strategy enhanced parrot optimizer, termed STPO. STPO integrates an alert protection mechanism inspired by the Sparrow Search Algorithm, an experience exchange strategy, and a worst-guided differential scale perturbation operator to improve population guidance, strengthen perturbation-based search, facilitate the transition from exploration to exploitation, and enhance convergence stability. Comprehensive experiments on the CEC2017 and CEC2022 benchmark suites demonstrate that STPO achieves highly competitive average rankings. Specifically, on CEC2017, STPO obtains average ranks of 1.76, 1.21, 1.21, and 1.46 under 10-, 30-, 50-, and 100-dimensional settings, respectively. On CEC2022, STPO achieves average ranks of 2.15 and 1.74 under 10- and 20-dimensional settings, respectively. These quantitative results indicate that STPO provides stable and accurate optimization performance compared with the twelve competing algorithms. Furthermore, statistical tests, ablation experiments, population diversity analysis, and exploration–exploitation analysis are conducted to further examine the effectiveness and dynamic search behavior of STPO. When applied to five classical engineering design problems and mobile robot path planning tasks, STPO also achieves competitive solution accuracy and convergence behavior, further confirming its applicability to constrained engineering optimization and practical path planning scenarios. The Source code for this work is openly available at https://github.com/MingXuanJian/STPO.git .
Multi-wavelength architecture of the tensional stress field of peninsular Italy
Correction: Heat shock factor-1 alleviates ER-stress in Caenorhabditis elegans
Behavioral and temporal dynamics of child pedestrian crash injury patterns: evidence from random parameter modeling
A feature-centric decision-making framework for diagnosing and enhancing system efficiency in intelligent multi-agent manufacturing
Abstract This research offers a feature-centric hybrid predictive framework to forecast the efficiency of the system in intelligent multi-agent manufacturing environments. By combining operational, learning-based, and cyber-physical indicators, the suggested approach caters to the growing demand for interpretable, resilient, and high-performance analytics in Industry 4.0/5.0 contexts. The paper presents a structured pipeline that involves recursive feature elimination for a principled feature selection, ANOVA-based sensitivity assessment for statistical variance attribution, and SHAP-based global explainability for model-embedded interpretability. To boost the predictive accuracy, three tree-based baseline learners—decision trees, random forests, CatBoost, and extra trees—are combined with two recent meta-heuristic optimizers: prairie dog optimization (PDO) and electric eel foraging optimization. The experimental results indicate that the hybrids, especially the PDO-enhanced random forest and extra trees models, lead to a significant increase in accuracy, stability, and error reduction across all the test stages. Sensitivity analyses continuously point out production efficiency, machine usage, Q-value, and security event as the main predictors, which confirms the multi-modal nature of industrial performance dynamics. The results emphasize the viability of feature-driven modeling and biologically inspired optimization in producing robust and interpretable outcomes that are suitable for practical smart manufacturing applications. This research adds a novel, explainable, and deployable predictive intelligence paradigm for modern multi-agent industrial systems as its contribution.
Development and characterization of dibenzalacetone-loaded oleogels as a potential photoprotective agents for sunscreen formulations
Abstract Prolonged exposure to ultraviolet radiation induces erythema, accelerates photoaging, and increases the risk of skin cancer. Sunscreens are the primary strategy for preventing UV-induced skin damage; however, the effective topical delivery of photoprotective agents is often limited by formulation challenges. Dibenzalacetone (DBA), a chalcone derivative with broad UVA and UVB absorption, exhibits strong photoprotective potential but is restricted by poor aqueous solubility. This study aimed to develop and optimize DBA-loaded silicon dioxide (SD) oleogels as topical photoprotective systems. Oleogels were prepared using argan oil (AO) or jojoba oil and optimized through a 2³ factorial design. DBA solubility, critical gelation concentration, rheological behavior, drug content, and in vitro sun protection factor (SPF) were evaluated. Further characterization included spreadability, photostability, skin permeation, differential scanning calorimetry, Fourier transform infrared spectroscopy, stability studies, and cytotoxicity assessment on human keratinocytes. DBA demonstrated high solubility in both oils, enabling the formation of stable, translucent oleogels at a structuring agent concentration of 10%. All formulations exhibited non-Newtonian, pseudoplastic, and thixotropic behavior, acceptable drug content, and broad-spectrum UV protection (λc > 370 nm). AO-based oleogels showed superior SPF values. Formulation F8 (AO, 15% SD, 8% DBA) achieved the highest SPF, excellent spreadability, enhanced photostability, low skin permeation, and no cytotoxicity up to 400 µg/mg.
Association of diet and physical activity with overweight and obesity in people living with HIV: a cross-sectional study in Brescia, Italy
TB vaccine from the 1920s shows promise in diabetes trial
Joint optimization of HBS 3D trajectory and power allocation transmission for energy- efficient NOMA downlink in 6G networks
Ancient ground squirrels feasted on carcasses like ‘zombies of the Pleistocene’
Socioeconomic determinants of practical adaptive capacity and food security under climate stress in Western Iran
Genetic polymorphisms associated with therapeutic response and adverse effects to methotrexate in Taiwanese patients with rheumatoid arthritis: a real-world, hospital-based study
Applying LIBS, SEM/EDX, and FTIR spectroscopic analysis for the conservation of cairene architectural heritage
Abstract This study investigates the wall paintings of Al-Qazdughli Palace, an early twentieth-century landmark in Cairo’s historic Garden City district near Simon Bolivar Square, using a multi-analytical spectrochemical approach. As an important example of Cairo’s architectural heritage, the palace has experienced extended neglect and significant deterioration. Laser-Induced Breakdown Spectroscopy (LIBS) using an Nd: YAG laser at 1064 nm was used to examine six pigment colors: gold, brown, light green, blue, bright red, and dark red. The gold pigment showed strong signals for Zn, Ag, Ba, Au, Cu, and Pb; Zn was dominant in the brown pigment; and the blue pigment contained Ti, Cu, and Zn. The light green pigment revealed Ca, Cu, Zn, and Pb; the bright red pigment showed Ca, Fe, Cr, Zn, Hg, and Pb; and the dark red pigment contained Ti, Mn, Fe, and Zn. The LIBS findings were confirmed through SEM/EDX analysis, which produced consistent elemental results. Optical microscopy enabled non-invasive examination of paint-layer surface morphology and microstratigraphy. FTIR analysis of selected pigments also identified carbonyl ester bands (1750–1740 cm⁻ 1 ), indicating oil-based binding media. Together, these results highlight LIBS, supported by complementary techniques, as an effective quasi-non-destructive tool for the in situ analysis of wall paintings and for informing conservation and restoration strategies.