Search Results (76)

The manipulation of vector beams (VBs) with longitudinally variant polarization states is an important research topic and has potential applications in classical and quantum fields. In this study, we propose a half-wave plate dielectric metasurface composed of two interleaved sub-metasurfaces to generate longitudinally separated dual-channel vectorial structured light fields. The propagation and Pancharatnam–Berry phases are employed to construct hyperbolic, helical, and opposite gradient phases for focusing wavefronts, generating circularly polarized (CP) vortices, and deflecting CP vortices with the same chirality in opposite directions. Consequently, dual-channel higher-order or hybrid-order Poincaré (HOP or HyOP) beams are generated along the optical axis under elliptically polarized illumination, and their polarization states evolve along an arbitrary pair of antipodal meridians on the HOP or HyOP sphere by varying the ellipticity of the incident light, the propagation-phase topological charge, and the rotation order of the meta-atom. The consistency between the theoretical and simulated results demonstrates the feasibility and practicability of the proposed method. This study is significant for compact, integrated, and multifunctional optical devices, and provides an innovative strategy to extend optical field manipulation from two-dimensional to three-dimensional space. Full article

Stormwater runoff represents a significant vector for the transport of organic pollutants and pathogens into aquatic ecosystems, posing serious environmental and public health risks. Although extensively employed for bank stabilization, traditional gabion structures demonstrate constrained efficacy in pollutant removal. In this study, an enhanced ecological gabion (EG) system was developed by integrating a stratified configuration of functional fillers (ceramsite, maifanite, and biochar) with vegetation (Iris germanica). This design leverages synergistic effects to enhance the concurrent removal of dissolved organic matter (DOM), particulate organic matter (POM), and fecal indicator bacteria (FIB) from simulated stormwater. The system was evaluated in continuous flow experiments through comparison with a traditional gravel gabion (TG). Results showed that, compared with the TG, the EG exhibited markedly enhanced removal performance, with chemical oxygen demand (COD), NH₄⁺–N, and TN removal efficiencies being approximately 2.48, 3.68, and 3.56 times those of the TG, respectively. In addition, the EG exhibited significantly higher removal efficiencies for both particulate organic carbon (POC) and dissolved organic carbon (DOC) than the TG, with increases of 329% and 137%, respectively. Fluorescence spectroscopy and particle size distribution analyses revealed that the EG effectively transformed and removed diverse DOM components and fine particulates. The stratified filler media synergistically enhanced pollutant retention, with biochar serving as the primary agent for nutrient and pathogen adsorption. These findings demonstrate the viability of the EG as an integrated, eco-friendly solution for enhanced stormwater purification in riparian zones, providing a compact and multifunctional alternative to conventional end-of-pipe systems. Full article

Vector bending sensing is an important research direction in the field of bionic robot design. A vector bending sensor with temperature compensation based on Mach–Zehnder interferometer (MZI) is proposed and experimentally investigated. The MZI is implemented using an off-axis splice between a single-mode fiber (SMF) and a double-cladding fiber (DCF). The proposed sensor is analyzed comprehensively from the perspective of theoretical analysis and experimentally demonstrated. It reaches a high curvature sensitivity as high as −8.311 nm/m⁻¹ and a compact size as small as 3 mm, while keeping the capability of direction sensing and temperature compensation. The proposed vector bending sensor has a good potential for accurate curvature measurement due to its high accuracy, multifunction, low cost and, compact size. Full article

The K-means clustering algorithm is widely applied in various clustering tasks due to its high computational efficiency and simple implementation. However, its performance significantly deteriorates when dealing with non-convex structures, fuzzy boundaries, or noisy data, as it relies on the assumption that clusters are spherical or linearly separable. To address these limitations, this paper proposes a Gaussian membership-driven fuzzy granular K-means clustering method. In this approach, multi-function Gaussian membership functions are used for fuzzy granulation at the single-feature level to generate fuzzy granules, while fuzzy granule vectors are constructed in the multi-feature space. A novel distance metric for fuzzy granules is defined along with operational rules, for which axiomatic proof is provided. This Gaussian-based granulation enables effective modeling of nonlinear separability in complex data structures, leading to the development of a new fuzzy granular K-means clustering framework. Experimental results on multiple public UCI datasets demonstrate that the proposed method significantly outperforms traditional K-means and other baseline methods in clustering tasks involving complex geometric data (e.g., circular and spiral structures), showing improved robustness and adaptability. This offers an effective solution for clustering data with intricate distributions. Full article

Protein embedding is a protein representation that carries along the information derived from filtering large volumes of sequences stored in large archives. Routinely, the protein is represented by a matrix in which each residue is a context-specific vector whose dimensions reflect the size of the large architectures of neural networks (transformers) trained with deep learning algorithms on large volumes of sequences. A recently introduced method (Embedding-Based Alignment, EBA) is particularly suited for pairwise embedding comparisons and, as we report here, allows for remote homolog detection under specific constraints, including protein sequence length similarity. Multifunctional proteins are present in different species. However, particularly in humans, the problem of their structural and functional annotation is urgent since, according to recent statistics, they comprise up to 50% of the human reference proteome. In this paper we show that when EBA is applied to a set of randomly selected multifunctional human proteins, it retrieves, after a clustering procedure and rigorous validation on the reference Swiss-Prot database, proteins that are remote homologs to each other and carry similar structural and functional features as the query protein. Full article

A multifunctional diagnosis and treatment carrier, ZIF-8@CDs, based on carbon quantum dots (CDs) and the zeolitic imidazolate framework-8 (ZIF-8) metal–organic framework which serves as a core structure for constructing the responsive delivery platform, is developed in this paper. The anticancer drug doxorubicin (DOX) and Survivin oligo (siRNA) are loaded to form a ZIF-8@CDs/DOX@siRNA dual loading platform. CDs of 5–10 nm are synthesized by the solvent method and combined with ZIF-8. Electron microscopy shows that the composites are nearly spherical particles of approximately 200 nm, and the surface potential decreases from +36 mV before loading CDs to +25.7 mV after loading. The composite system shows unique advantages: (1) It has Fenton-like catalytic activity, catalyzes H₂O₂ to generate hydroxyl radicals, and consumes glutathione in the tumor microenvironment. The level of reactive oxygen species (ROS) in the ZIF-8@CDs group is significantly higher than that in the control group. (2) To achieve visual diagnosis and treatment, its fluorescence intensity is superior to that of the traditional Fluorescein isothiocyanate (FITC)-labeled vector; (3) It has a high loading capacity, with the loading amount of small nucleic acids reaching 36.25 μg/mg, and the uptake rate of siRNA by liver cancer cells is relatively ideal. The ZIF-8@CDs/DOX@siRNA dual-loading system is further constructed. Flow cytometry shows that the apoptosis rate of HepG2 cells induced by the ZIF-8@CDs/DOX@siRNA dual-loading system is 49%, which is significantly higher than that of the single-loading system (ZIF-8@CDs/DOX: 34.3%, ZIF-8@CDs@siRNA: 24.2%) and the blank vector (ZIF-8@CDs: 12.6%). The platform provides a new strategy for the integration of tumor diagnosis and treatment through the multi-mechanism synergy of chemical kinetic therapy, gene silencing and chemotherapy. Full article

This study suggests the concept of multifunctional social spaces (MSSs) as intergenerational communication platforms, contributing to SDG achievement and environment awareness in local communities. Retirees could perform socially significant practices via local MSS premises supported by municipalities and initiative groups. The basic social vector of an MSS is supposed to produce a synergy effect with the educational and environmental impetus of the Sustainable Environmental Education (SEE) approach. Lifelong education underlies the process of adapting various age groups to different local spaces, namely metropolis, suburb, or rural areas. Test qualitative interviews were conducted with pensioners and young people to discover attitudes towards MSS-prescribed functions within different reference groups. These interviews helped to define the preferred communication instruments for MSS operation. General types of MSSs were classified based on mini case studies. MSS introduction is supposed to influence basic social indices such as population health, life expectancy, and fertility levels in the long term, and support several environmental awareness markers. Future studies could examine such influences in detail and discuss more national and regional specifics. Municipal and regional authorities, as well as local community leaders, could use the results of this study to consider local development, SDG strategies, and roadmaps. Full article

As the global food industry expands and consumers demand higher food safety and quality standards, high-throughput detection technology utilizing digital intelligent optical sensors has emerged as a research hotspot in food testing due to its advantages of speed, precision, and non-destructive operation. Integrating cutting-edge achievements in optics, electronics, and computer science with machine learning algorithms, this technology efficiently processes massive datasets. This paper systematically summarizes the construction principles of intelligent optical sensors and their applications in food inspection. Sensors convert light signals into electrical signals using nanomaterials such as quantum dots, metal nanoparticles, and upconversion nanoparticles, and then employ machine learning algorithms including support vector machines, random forests, and convolutional neural networks for data analysis and model optimization. This enables efficient detection of target substances like pesticide residues, heavy metals, microorganisms, and food freshness. Furthermore, the integration of multiple detection mechanisms—including spectral analysis, fluorescence imaging, and hyperspectral imaging—has significantly broadened the sensors’ application scenarios. Looking ahead, optical sensors will evolve toward multifunctional integration, miniaturization, and intelligent operation. By leveraging cloud computing and IoT technologies, they will deliver innovative solutions for comprehensive monitoring of food quality and safety across the entire supply chain. Full article

Background/Objectives: Cell-mediated and peptide-assisted delivery systems have emerged as powerful platforms at the intersection of chemistry, nanotechnology, and molecular medicine. By leveraging the intrinsic targeting, transport, and signaling capacities of living cells and bioinspired peptides, these systems facilitate the delivery of therapeutic agents across otherwise restrictive biological barriers such as the blood–brain barrier (BBB) and the tumor microenvironment. This review aims to summarize recent advances in engineered cell carriers, peptide vectors, and hybrid nanostructures designed for enhanced intracellular and tissue-specific delivery. Methods: We surveyed recent literature covering molecular design principles, mechanistic studies, and in vitro/in vivo evaluations of cell-mediated and peptide-enabled delivery platforms. Emphasis was placed on neuro-oncology, immunotherapy, and regenerative medicine, with particular focus on uptake pathways, endosomal escape mechanisms, and structure–function relationships. Results: Analysis of current strategies reveals significant progress in optimizing cell-based transport systems, peptide conjugates, and multifunctional nanostructures for the targeted delivery of drugs, nucleic acids, and immunomodulatory agents. Key innovations include improved BBB penetration, enhanced tumor homing, and more efficient cytosolic delivery enabled by advanced peptide designs and engineered cellular carriers. Several platforms have progressed toward clinical translation, underscoring their therapeutic potential. Conclusions: Cell-mediated and peptide-assisted delivery technologies represent a rapidly evolving frontier with broad relevance to next-generation therapeutics. Despite notable advances, challenges remain in scalability, manufacturing, safety, and regulatory approval. Continued integration of chemical design, molecular engineering, and translational research will be essential to fully realize the clinical impact of these delivery systems. Full article

The problem of multi-function computation over a directed acyclic network is investigated in this paper. In such a network, a sink node is required to compute with zero error multiple vector-linear functions, where each vector-linear function has distinct inputs generated by multiple source nodes. The computing rate tuple of an admissible code is defined as a tuple consisting of the average number of zero-error computations for each vector-linear function when the network is used once jointly. From the information theoretic point of view, we are interested in characterizing the rate region, which is defined as the closed set of all achievable computing rate tuples. In particular, when the sink node is required to compute a single vector-linear function, the network multi-function computation problem degenerates to the network function computation problem. We prove an outer bound on the rate region by developing the approach of the cut-set strong partition. We also illustrate that the obtained outer bound is tight for a typical model of computing two vector-linear functions over the diamond network. Furthermore, we establish the relationship between the network multi-function computation rate region and the network function computation rate region. Also, we show that the best known outer bound on the rate region for computing an arbitrary vector-linear function over an arbitrary network is a straightforward consequence of our outer bound. Full article

Chimeric antigen receptor (CAR) T cell therapy for B cell malignancies is often limited by T cell exhaustion, which is frequently driven by the PD-1/PD-L1 immune checkpoint axis. To overcome this, we developed an “armored” CAR-T cell strategy using a novel bidirectional promoter system. We engineered a single vector to co-express a CD19-specific CAR alongside a secreted anti-PD1 molecule, in either a full-length antibody or a single-chain variable fragment (scFv) format, using the Sleeping Beauty (SB) transposon system. The sequences for the anti-PD1 modules were derived from the clinical antibody nivolumab. Both armored constructs demonstrated robust CAR expression, comparable to or higher than conventional CAR-T cells, and proliferated significantly more than untransfected controls. The engineered cells successfully secreted their anti-PD1 payloads, with the full-length antibody showing more sustained secretion than the scFv. This autocrine blockade resulted in significantly reduced surface PD1 expression on the armored CAR-T cells. Functionally, the anti-PD1-secreting cells exhibited superior cytotoxicity against PD-L1-positive Raji target cells, particularly at low effector-to-target ratios. Critically, in a serial rechallenge assay designed to simulate chronic antigen exposure, both armored CAR-T cell groups showed markedly enhanced proliferation and persistence compared to conventional CAR-T cells, which failed to expand after repeated stimulation. Our findings validate the bidirectional EF1 promoter as an efficient system for generating multi-functional T cells and demonstrate that armoring CAR-T cells with secreted anti-PD1 antibodies is a potent strategy to enhance their persistence and anti-tumor efficacy. Full article

In ancient civilisations, bitumen was widely used for its multifunctional applications in construction, sealing, and adhesion, evidencing early expertise in material engineering and resource optimisation. Here, Sumerian bitumen-based artefacts were studied through Fourier transform infrared spectroscopy (FTIR) and machine learning to investigate ancient practices for the repair, reuse, and recycling of everyday materials. The materials are dated back to the 3rd millennium BC and come from the archaeological site of Abu Tbeirah (Iraq). Four primary classes were identified based on their molecular composition, which revealed a specific gradient determined by the varying proportions of bitumen and other fillers. These composition-based classes were then applied to predict the classification of the undetermined samples, which constitute 50% of the entire dataset, via a kernel-based support vector machine (SVM). The new findings are consistent with philological sources that reference distinct formulations of use in everyday life. The findings offer a new perspective on the social and historical importance of the circular economy. Full article

Background/Objectives: This study systematically investigated the expression characteristics of the ALDOA gene in skeletal muscle cells and its effects on cell proliferation, apoptosis, and differentiation. Methods: We constructed an ALDOA overexpression vector and transfected it into C2C12 cells and porcine skeletal muscle satellite cells. Results: We found that ALDOA exhibited the highest expression in the longissimus dorsi muscle and was primarily localized in the cell nucleus. Overexpression of ALDOA significantly inhibited cell proliferation, induced G0/G1 phase arrest, and downregulated the expression of proliferation-related genes such as CDK2 and Cyclin D1. Concurrently, ALDOA overexpression markedly promoted apoptosis. Regarding differentiation, although ALDOA expression was upregulated during differentiation, its overexpression significantly suppressed the expression of myogenic differentiation-related genes (such as MYOD, MYOG, MEF2C), suggesting a negative regulatory role in differentiation control. Conclusions: This study reveals the multifaceted regulatory functions of ALDOA in skeletal muscle cells, providing experimental evidence for deepening the understanding of its mechanisms in muscle development and regeneration. This study provides the first functional evidence that ALDOA acts as a multifunctional regulator in skeletal muscle cells, negatively governing cell growth and fate decisions by inhibiting proliferation, promoting apoptosis, and impeding myogenic differentiation, thereby extending its role beyond glycolysis to direct governance of cellular processes. This study reveals for the first time that ALDOA possesses dual functions in muscle cells, regulating both metabolism and transcription. Full article

Background: The Tibetan Plateau, which is known for its high elevation and low oxygen levels, presents a challenging environment for its inhabitants. To adapt to these hypoxic conditions, species of Schizothoracine, a subfamily of Cyprinidae, have developed unique physiological mechanisms and functions. Transforming growth factor-β (TGF-β) is a multifunctional cytokine involved in the regulation of cell growth, differentiation, apoptosis, and the cellular immune response. However, its specific role in adaptation to hypoxia remains poorly understood. Methods: In this study, we aimed to characterize the TGF-β1 gene in Gymnocypris dobula (Gd) and Schizothorax prenanti (Sp) and to test whether TGF-β1 contributes to hypoxia adaptation in plateau Schizothoracine fish. The predicted protein for Gd-TGF-β1 contains several primary domains, including cwf21 (cdc5 protein 21), GYF (Glycine-Tyrosine-Phenylalanine), FN1 (Fibronectin 1), a conservative domain, and a signal peptide. Results: The results of tissue distribution revealed that the mRNA level of TGF-β1 in brain, heart, muscle, skin, gills, and spleen—which are key tissues involved in oxygen sensing, transport, and physiological adaptation to hypoxic environments—was significantly lower in G. dobula than that in S. prenanti. Western blotting analysis revealed that the expression of activated TGF-β1 in G. dobula was significantly higher than that in S. prenanti. To investigate whether TGF-β1 in G. dobula possesses hypoxic adaptive features, Gd-TGF-β1 and Sp-TGF-β1 were cloned into an expression vector and transfected into 293-T cells, which are widely used due to their ease of culture, high transfectability, and well-characterized properties. We found that the survival rate of cells transfected with Gd-TGF-β1 was significantly higher than that of cells transfected with Sp-TGF-β1 after hypoxia treatment. Conclusions: These findings suggest that G. dobula may promote hypoxic adaptation through the activation and increased expression of TGF-β1. Changes in TGF-β1 expression may play a role in the adaptation of G. dobula to hypoxic conditions. Full article