Browse Articles

Phenothiazine Sulfoxides as Active Photocatalysts for the Synthesis of γ-Lactones

Metal-Based Approaches for the Fight against Antimicrobial Resistance: Mechanisms, Opportunities, and Challenges

AJUBA promotes the proliferation, invasion and migration of NSCLC cells by activating the ERK/β-catenin pathway

Abstract Accumulating evidence indicates that AJUBA acts as a potential target for new therapeutics to treat cancers. Nevertheless, the role of AJUBA in non-small cell lung cancer (NSCLC) remains unclear. In the current study, immunohistochemistry (IHC) showed that expression of AJUBA was upregulated in 67.55% of NSCLC tumor samples and was associated with tumor size, lymph node metastasis, advanced tumor stage, poor differentiation and poor prognosis. Loss-of-function assays of AJUBA produced by silencing RNA (siAJUBA) significantly inhibited the proliferation, invasion and migration of H1299 and A549 cell lines. Mechanistically, inhibition of extracellular signal-regulated kinases (ERKs) blocked the AJUBA-induced proliferation, invasion and migration of NSCLC cells, and decreased the expression of proteins related to the endothelial-mesenchymal transition (EMT). Silencing of AJUBA repressed tumor growth and led to a decrease in p-ERK, β-catenin and N-cadherin in vivo. In conclusion,, overexpression of AJUBA facilitates the proliferation and motility of NSCLC cells via the ERK and Wnt/β-catenin pathways. AJUBA may be useful as a prognostic marker which may provide a promising approach for the treatment of NSCLC.

Unraveling the Roles of Amines in Atom Transfer Radical Polymerization in the Dark

Enhanced aquila optimizer for global optimization and data clustering

Abstract The Aquila Optimizer (AO) is a newly proposed, highly capable metaheuristic algorithm based on the hunting and search behavior of the Aquila bird. However, the AO faces some challenges when dealing with high-dimensional optimization problems due to its narrow exploration capabilities and a tendency to converge prematurely to local optima, which can decrease its performance in complex scenarios. This paper presents a modified form of the previously proposed AO, the Locality Opposition-Based Learning Aquila Optimizer (LOBLAO), aimed at resolving such issues and improving the performance of tasks related to global optimization and data clustering in particular. The proposed LOBLAO incorporates two key advancements: the Opposition-Based Learning (OBL) strategy, which enhances solution diversity and balances exploration and exploitation, and the Mutation Search Strategy (MSS), which mitigates the risk of local optima and ensures robust exploration of the search space. Comprehensive experiments on benchmark test functions and data clustering problems demonstrate the efficacy of LOBLAO. The results reveal that LOBLAO outperforms the original AO and several state-of-the-art optimization algorithms, showcasing superior performance in tackling high-dimensional datasets. In particular, LOBLAO achieved the best average ranking of 1.625 across multiple clustering problems, underscoring its robustness and versatility. These findings highlight the significant potential of LOBLAO to solve diverse and challenging optimization problems, establishing it as a valuable tool for researchers and practitioners.

AI-driven energy management system based on hesitant bipolar complex fuzzy Hamacher power aggregation operators and their applications in MADM

In Situ Neutron Reflectometry Reveals the Interfacial Microenvironment Driving Electrochemical Ammonia Synthesis

MC4-R variant confirms its association with obesity during progression from childhood to adolescence

Excess Cations Alter *CO Intermediate Configuration and Product Selectivity of Cu in Acidic Electrochemical CO₂ Reduction Reaction

Defining the genetics of the widely used G3 strain of the mosquito, Anopheles gambiae

Abstract Mosquito species in the Anopheles gambiae complex have been referred to as “the deadliest animals in the world” due to their role as vectors of malaria throughout sub-Saharan Africa. Consequently, An. gambiae was among the first species to have its whole genome sequenced in 2002 and it continues to be the subject of intense study. An. gambiae is one member of a nine member species complex and, along with its sister species, An. coluzzii, is among the most important vectors of human malaria. Laboratory research on malaria vectors across a broad range of disciplines utilizes a strain known as G3, which was established in 1975 from mosquitoes collected from McCarthy Island, The Gambia. This strain is well known to be a mongrel strain, nonetheless it is often referred to as An. gambiae, which it is not. The issue with G3 goes far beyond the typical inbreeding associated with long-standing laboratory colonies. G3 is an An. gambiae/An. coluzzii interspecific hybrid. Although these two species are known to hybridize in nature, the pattern of interspecific introgression in G3 we describe in this paper is unlike any observed in natural populations. In this report we provide an in-depth analysis of the genetics of the G3 strain and compare it with natural populations of its two parental species. We discuss potential concerns that results obtained from research using the G3 strain may not apply to populations of these mosquito species as they occur in nature.

Chiral Lewis Acid-Catalyzed Intramolecular [2 + 2] Photocycloaddition: Enantioselective Synthesis of Azaarene-Functionalized Azabicyclo[2.1.1]hexanes and Bicyclo[1.1.1]pentanes

Introducing novel arc cosine-$$\Psi$$ class of distribution with theory and data evaluation related to coronavirus

Patient handover practice of nurses and associated factors in South Wollo Zone Public Hospitals, Ethiopia

Activating the Gate-Opening of a Metal–Organic Framework and Maximizing Its Adsorption Capacity

A contrast enhanced representation normalization approach to knowledge distillation

Visualizing the Sliding Motion of Dynamic Rotaxanes by Surface Wrinkles

A fine-grained course session recommendation method based on knowledge point pruning

Engineered Artificial Nanochannels with Cell Membrane Nanointerface for Ultrasensitive Detection and Discrimination of Multiple Bacterial Infections

RHOB regulates megakaryocytic and erythroid differentiation by altering the cell cycle and cytoskeleton

Adsorptive removal of lead, copper, and nickel using natural and activated Egyptian calcium bentonite clay

Abstract This study evaluates the efficiency of alkali-activated Egyptian calcium bentonite, obtained from the El Alamein region in northern Egypt, for the removal of copper (Cu2⁺), lead (Pb2⁺), and nickel (Ni2⁺) from synthetic wastewater. The bentonite samples underwent a series of preparation steps, including crushing, ball milling, magnetic separation, acid treatment with 0.1N acetic acid, and alkali activation using 5% sodium carbonate (Na2CO3). Various analytical techniques, such as X-ray fluorescence (XRF), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), cation exchange capacity (CEC) measurements, scanning electron microscopy (SEM), and free swelling analysis, were employed to characterize the materials. Absorption experiments were performed to examine the effects of pH, temperature, starting metal concentration, bentonite dose, and contact duration on heavy metal removal. The characterization results confirmed that montmorillonite was the predominant mineral in both the natural and activated bentonite samples. Adsorption studies indicated a significant improvement in heavy metal removal efficiency after activation. Under optimal conditions (pH 7, 1 g/L adsorbent dose, 120 min contact time, 20 mg/L initial metal concentration, and 20 °C), the maximum adsorption capacities of the activated bentonite were determined as 14 ± 0.03 mg/g for Cu2+, 13 ± 0.04 mg/g for Pb2+, and 12.2 ± 0.05 mg/g for Ni2+, exceeding those of the natural bentonite, which recorded capacities of 9.2 ± 0.04 mg/g, 9 ± 0.03 mg/g, and 8 ± 0.02 mg/g, respectively. Adsorption equilibrium data according to the Langmuir isotherm model, exhibiting high correlation values (R2 = 0.9979 for Cu2+, 0.9972 for Pb2+, and 0.9973 for Ni2+). Moreover, kinetic modeling demonstrated that the adsorption followed a pseudo-second-order mechanism, suggesting an intense chemisorption process. The thermodynamic analysis indicated that the adsorption process was spontaneous and endothermic, demonstrating enhanced adsorption at higher temperatures.