The rapid expansion of wearable electronics and distributed sensing is sharpening the demand for sustainable, maintenance free power sources that can operate quietly over long periods. Thermoelectric conversion is attractive here because it can harvest low grade heat, especially body heat, and translate small temperature differences into usable electrical power. Organic thermoelectric materials have therefore drawn sustained interest. They combine mechanical flexibility, low density, solution processability, and generally favorable biocompatibility, which aligns naturally with soft, skin interfaced devices. Their intrinsically low thermal conductivity, together with charge transport tunability enabled by molecular design and doping control, supports efficient operation under modest temperature gradients and conformal integration with compliant substrates. Recent progress in molecular engineering, secondary doping, microstructural regulation, and flexible device architectures has pushed performance forward, with reported power factors exceeding 1,000 μW m^-1 K^-2 and figure of merit values approaching unity at room temperature in selected systems. However, turning these advances into practical wearable generators remains nontrivial. Key bottlenecks include incomplete decoupling of electrical and thermal transport, limited long term stability under mechanical deformation and environmental exposure, and the persistent gap between laboratory scale demonstrations and scalable fabrication. This review summarizes recent developments in organic thermoelectric materials and wearable devices, and distills design principles aimed at enabling robust, manufacturable, and truly self-powered wearable systems.

Antibody-targeted lipid nanoparticles (Ab-LNPs) represent a highly promising delivery platform for precision therapy, enabling efficient in vivo targeted delivery of nucleic acid drugs such as mRNA, DNA and siRNA. Currently, the two primary strategies for antibody functionalization of LNPs are the post-insertion method and direct surface conjugation. This review outlines the key chemistry, manufacturing, and controls challenges associated with scaling up of Ab-LNP production, with a focus on antibody modification strategies, process scale-up challenges, and quality control considerations. It aims to provide practical guidance for translating Ab-LNP technology from laboratory research to scalable manufacturing.

Aims: The right to play is a basic human right. However, sport participation is often limited for children with complex motor disabilities. We developed a brain-computer interface (BCI)-enabled Boccia system that allows children with severe motor disabilities and communication difficulties to play independently. The purpose of this study was to partner with persons with lived experience (PWLE) to improve the BCI-Boccia system.

Methods: Following the Strategy for Patient-Oriented Research framework, we engaged seven PWLE. In the first session, we gathered comments from the PWLE, which were translated into a list of required features. The software was developed using an Agile approach. The second session involved a demonstration to collect additional feedback. In the third session, two PWLE tested the system in person. Engagement was evaluated using the Public and Patient Engagement Evaluation Tool (PPEET).

Results: Comments from the PWLE focused on improving the software controller and the mechanical stability of the ramp. New software controllers for coarse and fine movements were designed, and a new base was developed to enhance stability while allowing faster assembly and disassembly. The PPEET confirmed that PWLE felt their suggestions were considered and that sufficient resources were provided to support their participation.

Conclusion: We demonstrate that a patient engagement strategy can inform and facilitate improvements to a BCI-enabled Boccia system. Involving diverse PWLE throughout the design cycle may improve accessibility and user adoption in disability sports. Inclusive participation likely helps ensure that improvement efforts directly address the needs of end users.

Non-diffracting beams are typically confined to a limited set of specific profiles. Existing methods for diversifying these beams face challenges in achieving arbitrarily complex intensity distributions. In this paper, we present a phase engineering approach based on local spatial frequency mapping to construct novel non-diffracting beams. The proposed method facilitates the creation of customized intensity profiles by tailoring and splicing phase modulations in the Fourier domain, enabling the generation of intricate non-diffracting beams, such as those with a Tai Chi shape. We experimentally demonstrate the robust propagation invariance and self-healing capabilities of these novel non-diffracting beams. This approach provides a versatile means for designing structured non-diffracting fields, with potential applications in areas such as precision laser machining, optical trapping, free-space communication, and structured-light imaging.

Affective Computing aims to build systems that can sense, interpret, and influence human emotions. In parallel, virtual reality (VR) has matured into a powerful solution for immersion, presence, and interaction. When combined, these two technologies enable a new generation of emotionally adaptive systems that can recognize users’ inner states and react in real time. In this article, we explore the opportunities and challenges of emotion recognition and emotion elicitation in VR, focusing on the Virtual Emotion, Elicitation and Recognition Loop, a closed-loop framework where virtual environments adapt based on recognized and targeted emotions. We discuss applications in manufacturing, product design, and education, and highlight key ethical and privacy concerns, especially in light of recent regulations such as the European Commission released the proposed Regulation on Artificial Intelligence (EU AI Act). Finally, we outline open research directions toward responsible, privacy-aware, and scalable affective VR systems, suggesting that the convergence between VR and Affective Computing can become a crucial foundation for the next generation of human-centric interactive technologies.

Metabolic reprogramming fundamentally drives cancer progression, with aberrant amino acid metabolism serving as a critical nexus for maintaining redox homeostasis and dictating cell fate. Ferroptosis, an iron-dependent form of cell death driven by lipid peroxidation, is closely related to intracellular amino acid metabolic networks. Here, we systematically delineate how key amino acids function as multi-dimensional regulatory nodes that orchestrate tumor cell susceptibility to ferroptosis. We provide a focused analysis of the context-dependent mechanisms through which these metabolic pathways rewire cellular redox capacity, modulate central anti-ferroptotic defense nodes (e.g., GPX4), and reshape the tumor microenvironment. Finally, we highlight the profound metabolic plasticity and spatiotemporal heterogeneity of these networks, exposing the intrinsic vulnerabilities within the amino acid-ferroptosis axis that drive drug resistance and tumor evolution.

Autophagy is a fundamental catabolic process that is critical for maintaining cellular homeostasis and protein quality control in the central nervous system (CNS). While neuronal autophagy has been extensively characterized, growing evidence highlights the indispensable roles of glial autophagy, specifically in astrocytes, oligodendrocytes and microglia, in CNS physiology and pathology. These glial populations employ the autophagic machinery to regulate distinct but interconnected functions: astrocytes manage metabolic support and glutamate homeostasis; oligodendrocytes rely on autophagic flux for differentiation and myelin maintenance; and microglia employ specific pathways, such as LC3-associated phagocytosis, to orchestrate immune surveillance and inflammasome regulation. Impairment of glial autophagy has been implicated in non-cell-autonomous neurodegeneration, leading to excitotoxicity, myelin damage, the emergence of senescence-associated secretory phenotypes, and persistent neuroinflammation. Dysregulation of autophagic pathways during ageing has also been implicated in the pathogenesis of multiple neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis. In this review we summarize the cell-type-specific molecular mechanisms of autophagy in glia, and delineate their role in the clearance of pathogenic aggregates such as β-amyloid, α-synuclein, and mutant huntingtin. A deeper understanding of the spatiotemporal dynamics of glial autophagy and associated intercellular crosstalk is essential to fully elucidate the complex etiology of age-associated neurodegenerative conditions.

Iron is essential for cellular metabolism, redox balance, and proliferation, yet its redox activity generates reactive oxygen species (ROS) that can damage DNA, proteins, and lipids. Cancer cells exploit iron homeostasis mechanisms, including iron regulatory proteins, ferritinophagy, and hypoxia-inducible factors to maintain high intracellular iron, supporting metabolic reprogramming, antioxidant defenses, and therapy resistance. Iron-dependent lipid peroxidation drives ferroptosis, a regulated form of cell death uniquely dependent on iron. Ferroptosis is tightly controlled by metabolic and antioxidant pathways and mitochondrial ROS, as well as by lipid composition and polyunsaturated fatty acid availability. Ferroptosis also intersects with apoptosis and necroptosis, highlighting the central role of iron in cell fate and survival. Dysregulation of these pathways in cancer can sensitize cells to ferroptosis, creating a therapeutic vulnerability. Exploiting ferroptosis through modulation of iron availability, redox defenses, or lipid metabolism offers a promising anticancer strategy. However, tissue-specific iron dynamics, tumor heterogeneity, and interactions within the tumor microenvironment complicate clinical translation. Integrative approaches combining metabolic profiling, genetic analysis, and ferroptosis-targeted interventions will be critical to harness iron-dependent cell death while minimizing systemic toxicity. In this review, we explore the mechanisms through which cancer cells sustain high iron, evading associated toxicities and possible implications for integrating ferroptosis based therapies in clinical oncology.

Lipoprotein(a) [Lp(a)] is a genetically determined cardiovascular risk factor that has traditionally been considered stable throughout life, leading major scientific societies to recommend a single lifetime measurement in most individuals. However, emerging evidence challenges this long-standing assumption, suggesting the presence of clinically relevant intra-individual variability. While many individuals remain within the same risk category over time, a non-negligible proportion, particularly those with intermediate or borderline levels, may experience changes sufficient to alter cardiovascular risk classification or potential eligibility for emerging Lp(a)-lowering therapies. Variability appears more pronounced at lower baseline concentrations and may be influenced by demographic, metabolic, and inflammatory factors. Importantly, although long-term studies confirm that a single Lp(a) measurement is predictive of cardiovascular risk, the growing recognition of biological variability raises questions regarding risk stratification in selected patients. Standardization of variability definitions and further longitudinal research are needed to clarify the clinical implications of repeat testing. These considerations are particularly relevant in the era of targeted Lp(a)-lowering therapies, where accurate classification may influence treatment decisions. In this review, we summarize current data on Lp(a) variability across diverse populations and clinical contexts.

The construction industry is undergoing a low-carbon and digital transformation. The application of recycled aggregates in 3D printed concrete has emerged accordingly, combining the advantages of solid waste recycling and automated manufacturing. However, the optimization of mix design and the prediction of mechanical properties for 3D printed recycled aggregate concrete (3DPRAC) face two main challenges, namely the micro defects inherent in recycled aggregates and the anisotropy caused by layered deposition. This study proposes a Gene Expression Programming (GEP)-based computational framework for the prediction of the splitting tensile strength (STS) of 3DPRAC. A dataset of 110 data points was generated, with layer height and loading direction as key printing parameters representing the anisotropic effect. GEP showed the best performance among models, with an R² of 0.914 on the testing set. Furthermore, the GEP model provides explicit mathematical equations that delineate the contributions of individual input variables and reveal the nonlinear effects of fiber content and printing parameters on STS.

The efficient activation of CO₂ molecules is imperative for the development of a high-performance catalyst for the oxidative dehydrogenation of propane with carbon dioxide (CO₂-ODP). To enhance the activation of CO₂ over ceria, in this work, rare earth doped ceria (RE-CeO₂, RE=La, Pr, Nd, and Sm) is comparatively studied as a support for PtSn for CO₂-ODP. Compared with PtSn/CeO₂, Ce_1-xRE_xO₂ solid solution is formed for the RE-doped PtSn/CeO₂ catalysts, which increases the oxygen defect content, promotes the dispersion of Pt, and strengthens the ability of CO₂ to supplement lattice oxygen in the catalyst, thereby enhancing the catalytic performance for CO₂-ODP. Among the investigated catalysts, PtSn/ Nd-CeO₂ shows the best CO₂-ODP performance, with an initial propane conversion and propylene selectivity of 52.7% and 86.1%, respectively. Moreover, the Pt electron density and oxygen-defect content over PtSn/RE-CeO₂ catalysts, which can be regulated to relatively large extents by doping ceria with different RE metals, are key factors in determining the activity of CO₂-ODP. These findings regarding the CeO₂-based binary RE solid solutions with adjustable oxygen defects and the derived impacts on supported Pt provide important references for advancing the design of oxygen-defect involved supported metal catalysts, including Pt-based catalysts, for the oxidative dehydrogenation of light alkanes with carbon dioxide.

Magnesium alloys are primarily composed of magnesium, with the additions of elements such as calcium, yttrium, and zinc. In the human physiological environment, they gradually degrade, and their degradation products can be absorbed, exhibiting excellent biocompatibility, mechanical properties comparable to bone tissue, and degradability; thus, they hold broad prospects in orthopedics. Nanotechnology involves the design and manufacture of materials, devices, and systems with unique physical, chemical, and biological properties by controlling the arrangement and interactions of atoms, molecules, or nanostructural units at the nanoscale (1-100 nm). The integration of these two technologies shows exceptional potential for orthopedic regenerative repair. Nanotechnology significantly enhances the mechanical performance, bioactivity, antibacterial properties, and controlled degradation of biodegradable magnesium alloys through various approaches, while biodegradable magnesium alloys provide an ideal biomaterial carrier for nanotechnology, enabling the better exertion of its advantages in bone tissue repair. This review summarizes the innovations arising from the fusion of magnesium alloys and nanotechnology in bone repair, aiming to advance the evolution of orthopedic medical devices, promote a shift in clinical treatment paradigms toward personalized and precise therapy, and ultimately deliver superior and more efficient therapeutic options for patients with orthopedic conditions, thereby improving human health and quality of life.

Rare-earth-doped upconversion nanocrystals (UCNCs), with unique anti-Stokes emission, have been extensively explored, while their performances are hindered by the restriction of parity-forbidden 4f-4f transitions, making their emission difficult to control and resulting in low quantum yields. Current research primarily relies on modifying dopant types and concentrations, matrix composition, particle size, core-shell structures, and surface functional groups, to tune the absorption and emission transitions of 4f electrons. While these methods can effectively adjust emission spectra, reduce defects, and enhance luminescence efficiency, they cannot fundamentally regulate the 4f electron transition process, especially with respect to studying the intrinsic luminescence kinetics of rare earth ions. Therefore, a fundamental understanding of the transition behavior of 4f electrons and the ability to intrinsically control their absorption and emission processes are crucial. By manipulating the local optical field around UCNCs, micro-nano structures offer a powerful means to control their upconversion luminescence, making them an important tool for developing efficient optoelectronic devices for display, lighting, and conversion applications. In this review, we comprehensively expound on the optical engineering for UC luminescence control through micro/nano-optical structures. By utilizing structures such as plasmonic antennas, dielectric superstructures, high Q microcavities, and programmable wavefront shapers, precise control over the interaction between light and matter is achieved at multiple spatial scales. Moreover, we systematically analyze how such structures enhance local excitation fields, amplify spontaneous emission, and direct photon extraction, thereby transcending the inherent limitations of rare-earth emitters. By bridging advances in materials chemistry with nanophotonics design principles, this approach unlocks unprecedented control over UC efficiency, spectral purity, and polarization properties.

This study addresses the interoperability of building information modeling (BIM) across different systems and platforms. Because the semantics of the industry foundation classes (IFC) standard are large and complex, traditional full semantic conversion methods are general-purpose, but they often lead to data expansion, which reduces system responsiveness and usability. In addition, the strong dependence of BIM models on specialized software further limits flexibility in practical use. Our novel framework combines a streamlined ontology with IFC, significantly improving memory efficiency and operational effectiveness compared to existing systems. Additionally, we integrate large language models for enhanced natural language processing in BIM data interactions. This harmonization of technologies not only simplifies system extension but also makes BIM data services more user-friendly and adaptable to various industry needs. By streamlining BIM data management and enriching data services, our approach broadens BIM’s applicability and improves data integration and extraction, establishing a more interactive and user-centric paradigm.

Ferroptosis has emerged over the past decade as a compelling therapeutic avenue for cancer, prompting intense interest in strategies that selectively induce or inhibit this form of cell death. Although substantial progress has been made in identifying genes that regulate ferroptosis sensitivity and in developing small-molecule modulators, it remains unclear which molecular targets offer the greatest therapeutic potential in specific tissues and contexts. Here, we highlight fundamental differences between in vitro and in vivo ferroptosis modulation, with emphasis on the integration of different techniques, mouse models, and how the tumor microenvironment shapes two major ferroptosis surveillance pathways: glutathione peroxidase 4 and ferroptosis suppressor protein 1. We propose that integrating in vivo biological constraints and microenvironmental complexity is essential for the rational design and successful translation of ferroptosis-targeted therapies.

Structured light fields are engineered through precise control of their amplitude, phase, polarization, and spatiotemporal properties, which are extensively studied for both scientific and applied purposes, and can offer novel pathways for information processing, quantum communication, and precision measurement. Although the linear manipulation of structured light is already very mature with the help of liquid crystal devices and planar optical elements, nonlinear manipulation remains nascent, despite demonstrating unique potential for critical functionalities such as optical field information exchange. Hence, critical challenges now lie in harnessing nonlinear interactions, between light fields themselves and between light and matter, to achieve on-demand multidimensional control of target optical fields, particularly for spatial modes of light. The advancing nonlinear optics theory, guided by structured light, reveals novel physical phenomena in various nonlinear interactions, and promotes the development of novel applications based on nonlinear light field control technologies. Accordingly, this review systematically summarizes recent advances across key areas, including the nonlinear manipulation of spatial structured light fields, optical information transfer, full-dimensional manipulation theory, field modulation and nonlinear topological frontiers, and three-dimensional (3D) light field manipulation theory, thereby providing a comprehensive perspective on the current state and the emerging trends in this rapidly evolving field.

The nucleolus, the largest membraneless organelle in the cell, is a biomolecular condensate that houses ribosomal DNA (rDNA), facilitates ribosomal subunit assembly, and serves as a dynamic reservoir for numerous unrelated proteins. Aging across eukaryotic species is accompanied by nucleolar expansion, raising the question of whether it is a correlate of aging or a driver of cellular aging. Recent studies suggest that nucleolar expansion may drive aging and this may result from age-associated changes in the biophysical properties of the nucleolus. Emerging evidence points to age-driven biophysical changes in the nucleolar condensate, including shifts in size, dynamics, and viscoelasticity, which may occur gradually or through transitions from a liquid-like state to denser gel-like, and in some contexts amyloid-like, assemblies. These transitions remodel two core condensate properties: compartmentalization and partitioning, with consequences for ribosome biogenesis and rDNA stability. Here, we review recent literature on age-driven changes in nucleolar condensation and discuss how these changes may influence nucleolar function and longevity.

Medical catheters constitute indispensable components of contemporary healthcare, yet they are confronted with persistent limitations in biocompatibility and functionality, such as thrombosis, infection, and tissue injury, which adversely affect patient safety and therapeutic outcomes. Surface coating technology has consequently arisen as a critical approach to reengineer the catheter-biological interface, thereby augmenting functional performance while preserving the intrinsic properties of the bulk materials. This review systematically outlines recent advances in coating technologies for medical catheters. It begins by analyzing mainstream coating methods, such as layer-by-layer self-assembly, surface grafting, and biomimetic adhesion, followed by the introduction of coatings with anticoagulant, antibacterial, lubricant, and multifunctional properties. The effectiveness and challenges of these coatings in clinical applications, such as cardiovascular intervention, long-term indwelling urinary catheters, and respiratory management are critically examined. Finally, the review discusses current translational bottlenecks and future trends toward intelligent, durable, and cost-effective coating solutions, providing a comprehensive reference for developing next-generation high-performance medical catheters.