Browse Articles

Measuring Knowledge, Attitude, and Response (A-KAR) regarding chemotherapy among cancer patients: a cross-sectional study

Abstract Chemotherapeutic agents serve as a fundamental treatment approach for numerous cancer types. Providing patients with comprehensive information about chemotherapy’s purposes, advantages, disadvantages, and management strategies is crucial for decreasing anxiety, boosting treatment compliance, and improving general well-being. This study aims to measure the knowledge, attitude, and response ( KAR) scores among cancer patients, in addition to identifying the potential associated factors for high scores. This observational cross-sectional study was conducted at the Oncology Center, Mansoura University, a tertiary care center, between September 2025 and October 2025. The study enrolled 669 cancer patients aged 18 years and above. Data were collected via a structured, Arabic-translated questionnaire developed from previous literature to assess KAR toward chemotherapy. Content validity was confirmed by three oncologists. Reliability and construct validity were evaluated using Cronbach’s alpha and exploratory factor analysis. Associated factors of total A-KAR scores were identified using univariate and multiple linear regression. A total of 669 patients participated with a mean age of 51.5 ± 13.2 years, predominantly female (68.2%). The mean knowledge score was 5.4 ± 2.3 out of 10, the mean attitude score was 10.8 ± 2.1 out of 15, and the mean response score was 2.7 ± 0.6 out of 3, with an overall total A-KAR score of 18.9 ± 3.9 (range: 5–28). Females exhibited significantly higher knowledge, attitude, and total A-KAR scores than males ( p  < 0.001). In the multiple regression model, higher A-KAR scores were independently predicted by female gender (β = − 0.329, p  < 0.001), urban residency (β = 0.175, p  = 0.037), absence of a family history of malignancy (β = − 0.164, p  = 0.027), and receiving chemotherapy (β = − 0.478, p  = 0.012). Duration since chemotherapy initiation was a strong independent associated factor, with significantly lower scores among those treated for less than one year compared with those treated for one to three years (all p  < 0.001). Cancer patients demonstrated moderate overall knowledge and attitudes toward chemotherapy, with generally positive response behaviors. Several sociodemographic and clinical factors were significant independent associated factors of A-KAR scores. These findings highlight the need for targeted educational interventions that address knowledge gaps and support patients throughout their treatment journey.

Geometry‐Programmable Living Immunomaterials for Spatial Control of Innate Immune Signaling

ABSTRACT Spatial organization of immune ligands critically regulates cGAS–STING signaling by controling the nanoscale geometry that drives cooperative cGAS assembly and catalytic activity. Here we engineer geometry‐programmable DNA origami that precisely encodes double‐stranded DNA (dsDNA) valency and spacing to promote cooperative cGAS clustering and STING activation. Systematic architectural modulation identifies an optimal configuration within tested ranges, in which 60‐bp dsDNA ligands arranged with ∼16.3 nm periodicity induce approximately twofold stronger STING signaling than free dsDNA counterparts. We further integrate these origamis with the probiotic Escherichia coli Nissle 1917 via transporter‐mediated surface anchoring, forming a living immunomaterial interface for localized ligand presentation in colorectal tumors. In microsatellite‐stable colorectal cancer models, this biohybrid system drives robust intratumoral STING activation, promotes T‐cell‐inflamed immune remodeling, and suppresses tumor growth by ∼83.5% relative to controls. This work establishes a geometry‐programmable living immunomaterial translating nanoscale architectural design into spatially confined innate immune signaling.

A precision-constrained framework for evaluating noninvasive biomarkers in MASLD and beyond

Comparative analysis of cefoperazone-sulbactam and piperacillin-tazobactam in empirical treatment of acute biliary tract infections: a multicenter, retrospective, real-world study

Multispectral Synergistic Electrochromic Regulator With Triple Atmospheric Windows Selectivity for Global Building Energy Saving

ABSTRACT As a growing contributor to global energy demand, building energy consumption is strongly constrained by the passive nature of conventional opaque building envelopes. Here, we design a tunable multispectral regulator based on an ITO/WO 3 /LiNbO 3 /NiO/ITO electrochromic all‐thin‐film stack. Through the ingenious device architecture of an asymmetric Fabry–Pérot cavity (F–P cavity), the regulator achieves multispectral positive synergistic modulation: in the cooling mode, it simultaneously reflects sunlight and exhibits selective high emissivity within the atmospheric windows; in the heating mode, it absorbs sunlight while maintaining low infrared emissivity. This design also extends effective modulation to the third atmospheric window (16–25 µm). Consequently, the device delivers synergistic and wide modulation with values of 0.52 and 0.64 in the solar (0.3–2.5 µm) and mid‑far infrared (2.5–25 µm) bands, respectively, enabling both summer cooling and winter heating. Outdoor testing in an arid desert climate validates effective thermal regulation, achieving a diurnal temperature difference of ∼5.5°C. With its adaptive regulation capability, the device is well‐suited for year‑round building energy saving. EnergyPlus simulations further reveal substantial annual energy savings, particularly for heating in cold regions (22.2 MJ/m 2 ). This work provides a monolithic tunable platform for synchronized multispectra regulation, paving the way for next‑generation intelligent thermal management systems.

Enhanced energy storage in tungsten bronze-based ferroelectrics and MLCCs via a multi-coating engineering

Spatial information reconstruction framework for power grid datasets without geographic coordinates

Adaptive Redox Resistive Memory Programming for Efficient and Robust Class‐Incremental Learning

ABSTRACT Resistive memory (RM)‐based computing‐in‐memory (CiM) accelerators provide a promising platform for low‐power edge intelligence. However, practical edge AI requires not only efficient inference but also repeated model updates through class‐incremental learning (CiL). Implementing CiL on RM substrates exposes a critical material‐algorithm mismatch: the write‐intensive updates required by CiL are strongly affected by the stochastic programming of filamentary RM devices. Conventional fully programming (FP) mitigates this stochasticity by repeatedly programming and verifying each cell to a precise target conductance, but this exhaustive procedure incurs substantial energy consumption, latency, and device wear across successive CiL stages. Herein, we propose a hardware‐aware adaptive programming (AP) strategy that aligns CiL deployment with RM device physics. Microstructural and electrical analyzes reveal that the random spatial distribution of oxygen vacancies gives rise to unavoidable programming variability. Guided by this insight, AP does not attempt to eliminate intrinsic stochasticity through costly compensation. Instead, it updates only the most impactful weights to suppress accuracy loss caused by overall mapping errors, while leaving low‐impact weights unchanged. This converts large‐scale write‐verify operations into targeted updates of a minimal subset of cells, reducing programming overhead without requiring device or material optimization. Validated on a hybrid analog‐digital system with a 40 nm, 256 k RM‐based CiM core, AP reduces programming energy by 93.0% and programming cycles by more than 90% relative to FP during five‐stage CIFAR100 CiL, while achieving a final accuracy of 0.80, close to the 0.81 software baseline. For the more complex ShapeNet 3D point‐cloud recognition task across eight stages, AP achieves 92.3% energy savings with only a 0.03 accuracy loss. Moreover, AP improves robustness by reducing programming‐error‐induced accuracy degradation by 87.7% and 88.4% for the two tasks, respectively. This work bridges algorithmic update requirements and physical programming constraints, enabling robust and energy‐efficient lifelong learning on RM‐based CiM platforms.

Evolutionary trajectory of microbial sulfur oxidation pathways recapitulates Earth’s oxygenation history

Integrated DC resistivity and seismic refraction imaging for bedrock discontinuity mapping in New Minia city, Egypt

Abstract This study addresses geotechnical challenges in fractured limestone environments by integrating electrical resistivity tomography (ERT), seismic refraction, and direct current (DC) resistivity soundings with borehole data in New Minia city, Upper Egypt. The objective was to delineate shallow subsurface heterogeneity and structural discontinuities and to establish correlations between geophysical and geotechnical parameters. A genetic algorithm (GA) optimization was applied to DC resistivity inversion, reducing non-uniqueness and improving model convergence. Seventeen boreholes (10 m depth) provided constraints for calibration and validation. Results reveal three principal subsurface sequences: (1) sandy–silty soil with clay intercalations, (2) heterogeneous intermediate deposits, and (3) fractured limestone bedrock. Major structural features, including north–south trending faults, were clearly identified. The integrated approach enhances subsurface characterization, reduces interpretational uncertainty, and provides a robust framework for hazard assessment and urban planning in complex carbonate terrains.

<i>π</i> ‐Conjugated Aligned Polar [CO ₃ ] Triangulars Synergizing Hydroxylation Enables Stress‐Enhanced Geometric–Electronic Asymmetries for Hydrogen Piezoevolution

ABSTRACT Piezocatalytic water splitting offers a sustainable route for hydrogen evolution, yet is challenged by weak polarity and slow charge separation kinetics under stress. Herein, we report strong polar hydroxylated Bi 2 O 2 CO 3 (BOC) synthesized scalably, characterized by noncentrosymmetric (NCS) planar triangular [CO 3 ] groups and surface hydroxyls, which applies as a robust piezocatalyst for hydrogen evolution. The aligned NCS planar [CO 3 ] triangulars in BOC enable oriented accumulation of dipole moments to produce strong spontaneous polarization, and the intrinsic delocalized π ‐electrons within these structural units construct a conjugation freeway that minimizes charge migration resistance. Further external mechanical stress triggers a highly anisotropic lattice response; specifically, compression along the b ‐axis induces extreme geometric and electronic asymmetries that amplify the interlayer internal electric field (IEF) for charge separation. When synergistically coupled with surface hydroxylation, this stress‐induced structural distortion significantly lowers the work function and interfacial kinetic barrier for electron escape. Consequently, the hydroxylated BOC catalyst achieves an ultrahigh piezocatalytic H 2 evolution rate of 3055 µmol·g −1 ·h −1 and a record mechanical‐to‐hydrogen (MTH) energy conversion efficiency of 0.31% in pure water. It also maintains robust H 2 evolution from real‐world aquatic matrices, including rainwater, seawater, and antibiotic wastewater. This work establishes a polar group design‐oriented paradigm for exploiting advanced piezocatalysts.

Transversal fault tolerant distributed quantum computing operations

The location of a reported movement strategy influences visuomotor adaptation

Neural dynamics of temporal interference stimulation monitoring by soft liquid metal interfaces across neural systems

Energy–exergy optimization of steam methane reforming for hydrogen production using Lévy-flight-enhanced ant colony optimization

DNA-programmed galvanic Ostwald ripening in nanoparticle assemblies

Identification of a novel glutamate receptor 2 mutation in mice presenting progressive cerebellar ataxia

Delineating the risk factors, sources of acquisition and clinical outcomes in neonates colonised with multidrug-resistant bacteria: the NeoCol study

Isolation and characterization of midgut microbiota in Anopheles mosquitoes from areas under varying insecticide pressure and malaria transmission settings of Ethiopia

Vibrating membrane bioreactors enhance nutrient removal and energy efficiency in municipal wastewater treatment

Abstract Membrane bioreactors (MBRs) are widely applied in municipal wastewater treatment, yet their broader adoption has been constrained by energy-intensive aeration and membrane fouling. Here, we report approximately 800 consecutive days of full-scale (7500 m 3 d −1 ) parallel operation of the vibrating MBR (VMBR) and the conventional aerated MBR (AMBR) systems, systematically comparing their pollutant removal performance, long-term filtration stability, membrane fouling mechanisms, and full life cycle environmental impacts. Results showed that the VMBR demonstrated enhanced nutrient removal, lowering effluent total nitrogen by 22% and reducing the chemical dosage for phosphorus removal by 40% compared with the AMBR. It also exhibited enhanced fouling resistance, with a 20% higher average specific flux than that of the AMBR throughout the operation. Mechanism analysis revealed that the VMBR generated effective, uniform shear at the membrane surface while preserving the sludge floc structure, thereby mitigating membrane fouling. Consequently, the VMBR reduced specific energy consumption for fouling control by 75% and the overall carbon footprint by 30%. We validate that VMBRs represent a scalable, energy-efficient and sustainable technology for future wastewater treatment.