Aims: Severe COVID-19 is characterized by marked heterogeneity in lung pathology, including diffuse alveolar damage, inflammation, and fibrosis. However, how spatially organized cellular interactions contribute to these divergent pathological outcomes remains incompletely understood. We aimed to define the spatial organization of cellular microenvironments in severe COVID-19 lungs and identify niche-specific cellular interactions associated with distinct histopathological states.

Methods: We applied imaging-based single-cell spatial transcriptomics to post-mortem lung tissues from patients with severe COVID-19 and control subjects, enabling high-resolution mapping of cellular composition, spatial neighborhoods, and predicted ligand-receptor interactions within intact tissue architecture.

Results: Analysis of 76,973 cells identified 20 distinct cell populations and revealed marked heterogeneity between COVID-19 samples, corresponding to different histopathological states. Spatial niche analysis identified discrete macrophage-associated microenvironments. Fibrotic niches were enriched in CHI3L1/MMP9^hi macrophages spatially associated with COL1A1⁺ fibroblasts and basal cells. Ligand-receptor inference predicted macrophage-derived TGF-β and galectin-3 signaling as drivers of pathogenic fibroblast activation and extracellular matrix remodeling. In contrast, alveolar niches contained SPP1^hi macrophages exposed to epithelial-derived cues, including WNT ligands and GM-CSF, consistent with differentiation toward an alveolar macrophage-like state.

Conclusion: Severe COVID-19 lungs are organized into distinct spatial niches associated with divergent immunopathological trajectories. Imaging-based spatial transcriptomics provides a framework to link histopathological states with localized cellular interactions and macrophage-driven tissue remodeling programs.

Electrochromic devices (ECDs), featuring passive optical modulation, backlight-free operation, and bistable low-power characteristics, are promising candidates for energy-efficient display applications. However, wide-gamut color modulation in electrochromic displays is hampered by both the narrow spectral tunability of conventional materials and the fabrication complexity of existing wide‑gamut devices. Herein, we develop an approach in achieving reversible wide-gamut color switching by depositing ellipsoidal metallic nanoparticles and an electrochromic WO₃ layer in series. Specifically, the dielectric environment surrounding the metallic nanoparticles is dynamically altered by electrochemically modulating the refractive index of the WO₃ layer, enabling precise tuning of the localized surface plasmon resonance absorption peak. As a result, a broad collective color gamut spanning the visible spectrum is achieved through Ag NP dimension engineering. In addition, the Ag NPs/WO₃ working electrode exhibits a low electrode-level average coloration power density of 4 W m^-2. We believe the results demonstrated in this work provide a new strategy for electrochromic display devices.

Zeolite materials, featuring well-defined pore architectures, tunable framework structures, ion-exchange capability, and favorable thermal stability, have been widely utilized in catalysis, adsorption, and separation processes. Recent advances in synthetic strategies and functional modification have further extended their utility into a diverse range of emerging interdisciplinary fields. This review systematically surveys recent progress in zeolite synthesis and application, with a particular emphasis on elucidating the relationship between synthetic strategies, structural modulation, and resultant performance. Representative synthetic approaches, including hydrothermal, sonochemical, microwave-assisted, mechanochemical, dry-gel conversion, and molten-salt synthesis, are discussed in terms of their effects on crystal size, morphology, pore hierarchy, and framework composition. The emerging applications of zeolite materials in biomedicine, energy storage and conversion, and intelligent sensing are subsequently examined. In biomedical contexts, zeolite materials have shown promise in drug delivery, bone regeneration, diagnostic imaging and wound hemostasis, attributable to their controllable loading behavior, favorable ion-release properties, and biocompatibility. As for energy-related applications, they have been employed in electrochemical energy storage, separator modification, hydrogen storage, and thermal energy storage, achieved through precise pore structure regulation and interface engineering. In the realm of intelligent sensing, zeolite materials have evolved from passive sieving media into active functional components with enhanced selectivity and signal responsiveness. This review provides a comprehensive overview of recent advances in the synthesis and functional applications of zeolites and discusses their prospects across a broad range of emerging interdisciplinary fields.

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine and metabolic disorder, in which the interaction between insulin resistance (IR) and hyperandrogenism (HA) is a major driver of reproductive and metabolic complications. Accumulating evidence suggests that chromatin remodeling may represent a regulatory layer linking metabolic stress, inflammation, steroidogenic gene expression, and androgen receptor activity. Research indicates that chromatin remodeling may be a key regulatory factor linking metabolic stress, inflammation, steroidogenic gene expression, and androgen receptor activity. This review systematically summarizes current evidence on chromatin remodeling in PCOS-related IR and HA, focusing on histone modifications, DNA methylation, ATP-dependent remodeling complexes, transcription factors, and non-coding RNA-mediated regulation. We distinguish between direct evidence from PCOS tissues and cells and indirect evidence from metabolic, endocrine, and hormone-responsive disease models, proposing a hierarchy of evidence. Available data suggest that chromatin remodeling may influence insulin signaling genes, adipogenesis, ovarian steroidogenic enzymes, and co-transcriptional networks involving Forkhead box protein O1 (FOXO1), Peroxisome Proliferator-Activated Receptor γ (PPARγ), nuclear factor-kappa B (NF-κB), androgen receptor (AR) signaling, and SWI/SNF-related complexes. However, PCOS-specific functional validation remains limited, particularly in theca cells, granulosa cells, adipose tissue, and cell-type-resolved chromatin. Integrating multi-omics, single-cell epigenomics, and CRISPR-based epigenome editing may help identify causal chromatin regulators and clinically relevant PCOS subtypes. We further discuss how computational biomedical approaches, including bioinformatics, Artificial Intelligence (AI), machine learning, and multi-omics integration, can enhance mechanistic inference, biomarker discovery, and PCOS subtype stratification. A chromatin-centric framework may deepen our understanding of the IR-HA cycle and support future biomarker discovery and precision interventions in PCOS.

Aims: Human leukocyte antigen (HLA) polymorphism influences immunity by balancing protection against pathogens with the preservation of self-tolerance. This balance has been proposed to affect longevity, as associations with HLA variants have been identified. However, studies in this field have reported inconsistent findings due to small sample sizes and low-resolution genotyping methods. We aimed to identify HLA alleles linked with longevity by overcoming these previous limitations.

Methods: We performed high-resolution HLA genotyping using targeted sequencing (HLA-seq) in 1,265 long-lived individuals (LLI; ≥94 years) from Germany and compared their HLA allele frequencies to a large control population of 3.4 million individuals from the German Bone Marrow Donor Registry (DKMS) using χ² (chi-square) tests.

Results: Six HLA alleles were significantly associated with longevity. Of those, two exhibited the most robust associations: A*01:01g (OR=0.87; 95% CI: 0.80-0.95; adj. P=0.02) and DRB1*13:02g (OR=1.24; 95% CI: 1.10-1.41; P=0.01). DRB1*13:02g was replicated in the UK Biobank after Bonferroni correction, whereas A*01:01g showed directionally concordant nominal support but did not remain significant after multiple-testing correction.

Conclusions: Both DRB1*13:02g and A*01:01g have previously been implicated in dementia-related phenotypes. These observations support the hypothesis that HLA variation may influence longevity partly through pathways linked to neurodegeneration. This study provides a high-resolution (2-field) HLA data of a longevity cohort, which would be valuable for future investigations.

Spatial transcriptomics (ST) maps gene expression within intact tissues, but its cost and technical complexity limit broad adoption. A growing body of deep-learning methods now seeks to infer ST directly from routine histology images, especially H&E-stained slides, with the aim of turning archived pathology into virtual molecular data. This review examines more than 40 ST prediction models, comparing their data requirements, modelling strategies, evaluation practices and translational potential. Recent advances in model architecture, histology foundation models and higher resolution in situ ST platforms have improved prediction performance and expanded the range of potential applications. However, most current methods still show limited robustness and generalisability, with performance constrained primarily by the quantity, quality and diversity of available ST training data. Comparisons between models also remain difficult due to inconsistent pre-processing pipelines, training datasets and evaluation strategies. The field is increasingly recognising that progress depends not only on more sophisticated models, but also on standardised benchmarks, improved data harmonisation and clearer evaluation frameworks. Despite these limitations, ST prediction is already showing utility in research settings, including biomarker discovery, tissue domain inference, molecular super-resolution and large-scale analysis of archived histology cohorts. Emerging applications also include patient stratification, virtual molecular profiling and multi-modal pathology systems that integrate histology, transcriptomics and language models. As datasets continue to expand and models become more reliable, ST prediction has the potential to become an important component of next-generation digital pathology workflows.

Organic anti-corrosion coatings are extensively used to protect metallic structures, but conventional coatings mainly serve as passive barriers and offer limited information on concealed interfacial degradation. Once corrosive media pass through pores, cracks, or local delamination, under-coating corrosion may begin before visible rusting or coating blistering becomes evident. Early, in situ, and real-time monitoring of coating degradation is therefore necessary for assessing coating performance, clarifying failure mechanisms, and supporting timely maintenance. This review presents recent advances in corrosion monitoring technologies for anti-corrosion coatings. Electrochemical sensing methods, including electrochemical impedance spectroscopy, electrochemical noise monitoring, and galvanic corrosion sensors, are examined with respect to their signal mechanisms, sensor configurations, and suitability for service-state assessment. Optical and electromagnetic sensing techniques are subsequently reviewed for nondestructive and spatially resolved detection of under-coating corrosion. Special attention is given to corrosion-sensing coatings that introduce responsive molecules or micro/nanocontainers into coating matrices to realize pH- or metal ion-triggered fluorescent and colorimetric warning. Finally, the major remaining challenges and future research directions are discussed, including high-sensitivity detection, long-term signal stability, multi-signal coupling, quantitative interpretation, and engineering implementation of intelligent coating systems.

Hormesis, the biphasic dose-response by which mild stressors trigger adaptive programs that leave cells better defended, has become the standard lens through which geroscience reads lifespan-extending interventions. However, the supporting evidence comes largely from young or middle-aged animals. This review argues that the hormetic window, i.e., the range of stimulus intensities an organism can convert into net benefit, is set not by chronological age but by integrated adaptive reserve, which is shaped jointly by aging biology, cumulative life-history exposures, and comorbidity burden. Because stress-response pathways across NRF2, HSF1, FOXO, AMPK, autophagy, and the telomere-associated DNA damage response are progressively attenuated, and because immune resilience governs the sensing, resolution, and repair phases of any adaptive response, the window both narrows and shifts toward lower doses. Doses clearly restorative in youth can therefore fall on the damaging side of the curve in old age, and two individuals of identical chronological age may respond very differently. We apply this framework to five paradigms: mitohormesis, caloric restriction, thermal stress, exercise, and genotoxic stress, and show that the stimulus generally retains its signal in old age while the downstream amplification machinery becomes rate-limiting. Interventions with explicitly age-dependent effects, including senolytics, NAD⁺ precursors, partial reprogramming, Bcl-xL overexpression, and stem-cell-derived extracellular vesicles, are examined as complementary probes of the same principle. The review closes with implications for geriatric trial design: comprehensive geriatric assessment combined with molecular biomarkers, longitudinal monitoring of a moving window, explicit safety thresholds, and sex-disaggregated analysis.

Ga-based liquid metal (LM), particularly gallium-based alloy, uniquely combines metallic conductivity with fluidic flexibility, offering attractive opportunities for biomedical technologies that are difficult to achieve with conventional solid-state metals. This review firstly summarizes the expanding applications of LM in microfluidics, flexible electronics, biosensing, drug delivery, and thermal therapy, highlighting the functional advantages arising from their fluidity, deformability, and electrical conductivity. However, the limitations that hinder broader biomedical implementation remain: though the native gallium oxide layer can stabilize LM structures, it also introduces challenges in oxidation control, wettability, interfacial adhesion, conductivity, and long-term reliability. Against this background, surface engineering is presented as a central strategy for addressing these limitations. We systematically review surface modification approaches based on small molecules, polymers, biological coatings, and related interfacial strategies for improving stability, biocompatibility, and functionality. We further discuss fabrication approaches for integrating surface engineered LM into wearable platforms, including 3D printing and hydrogel-based architectures. Finally, persistent challenges involving surface tension, adhesion, nanoparticle aggregation, conductivity loss, electrochemical corrosion, mechanical mismatch, biocompatibility, and sterilization are critically evaluated together with corresponding solutions. This application-surface engineering framework provides a roadmap for designing multifunctional, surface engineered LM-based systems, while outlining future directions for translating these materials from laboratory studies to clinical and practical biomedical applications.

Joint disorders, such as osteoarthritis (OA) and rheumatoid arthritis (RA), significantly impair patients’ quality of life and pose persistent challenges for current clinical management. The articular cavity presents a uniquely challenging therapeutic environment characterized by dense avascular cartilage, stringent synovial barriers, rapid synovial fluid clearance, and complex dynamic mechanical loading. Conventional therapeutic strategies, ranging from systemic pharmacological administration and intra-articular (IA) injections to invasive surgical approaches, are severely constrained by poor local bioavailability, rapid drug clearance, off-target toxicity, and the inherent passivity of static scaffold designs. Consequently, there is an urgent need for intelligent platforms capable of responsively adapting to pathological microenvironments to orchestrate concurrent biochemical regulation and tissue reconstruction. This review summarizes recent advances in smart devices for joint tissue intervention and repair. This review summarizes multi-scale therapeutic strategies specifically for the management of arthritis and related joint disorders, encompassing microneedle (MN)-based systems and 3D-printed structural scaffolds. Finally, the primary translational bottlenecks and future perspectives of these technologies are outlined to guide next-generation joint therapeutics.

The development of asymmetric catalytic methods using CO₂ as a C1 synthon is an important strategy for constructing chiral carboxylic acids and heterocyclic compounds. In recent years, through the design of innovative catalytic systems, efficient and highly selective syntheses of chiral carboxylic acids, spanning central to axial chirality, have been achieved from diverse substrates, including alkenes, alkynes, and organic electrophiles. Concurrently, significant progress has also been made in the synthesis of chiral heterocycles, particularly 2-oxazolidinones and cyclic carbonates. This review systematically summarizes key advances in this field from 2021 to mid-2026. Organized by target product structure, the discussion first addresses chiral carboxylic acids, categorized by substrate type (carbon-carbon unsaturated bonds and organic electrophiles). Key strategies, including carbo-carboxylation, boracarboxylation, hydrocarboxylation, dicarboxylation, and electroreductive carboxylation, are elaborated in detail, along with their stereoselectivity control mechanisms. The discussion then covers chiral heterocycles, summarizing the catalytic asymmetric construction of chiral 2-oxazolidinones and chiral cyclic carbonates. Finally, the major challenges and future directions in this field are discussed.

Adoptive cell therapy continues to encounter diverse hurdles in treating solid tumors, including poor infiltration, an immunosuppressive microenvironment, and tumor immune evasion, necessitating the endowment of effector cells with multiple functionalities. However, conventional cell-engineering techniques, including genetic editing and chemical modification, merely modulate a single functional axis to yield a monofunctional effector cell that can overcome only one physiological barrier, leading to insufficient solid tumor suppression. Recently, membrane-fusogenic liposomes have emerged as a multiplex engineering tool capable of straightforwardly producing multifunctional effector cells to synchronously surmount multiple challenges for effective antitumor efficacy. Through a fusion process, this liposome concurrently achieves immune cell surface functionalization and intracellular delivery of bioactive molecules, thereby endowing effector cells with multiple functionalities within a single step. This minireview summarizes recent advances in the use of fusogenic liposomes for immune cell engineering to boost their therapeutic efficiency on solid tumors. We discuss their design principles, representative applications, and analyze their technical advantages and current limitations. Looking forward, we propose that membrane-fusogenic liposomes hold potential to advance the development of multimodal engineered immune cells for next-generation cancer immunotherapies.

The rapid development of the digital economy has led to a significant increase in the scale and electricity load of 5G base stations in urban areas. It is therefore essential to study the load characteristics of 5G base stations to enhance urban grid stability and improve the energy efficiency of telecom operators. This paper investigates the load characteristics of 5G base stations using energy data from 37,525 5G base stations. The comprehensive analysis examines spatial distribution patterns, temporal load characteristics, and grid integration impacts using 15-minute resolution data. Results show that base station deployment is strongly correlated with population density (r = 0.92). Temporal load patterns show strong seasonal characteristics, with summer consumption about 1 kW higher than winter consumption, driven primarily by temperature-dependent cooling demand. The base stations maintain consistently low capacity utilization rates (26-41%), indicating substantial infrastructure redundancy. Strong synchronization exists between base station and grid loads during peak consumption periods, increasing peak stress but also revealing significant demand response potential. This study can help urban energy facilities identify new flexible sources and improve 5G station planning and operations.

The tumor immune microenvironment (TIME) is a central determinant of cancer progression and therapeutic response. Although organoid and organ-on-a-chip technologies have substantially advanced the modeling of tumor-immune interactions, most current platforms overlook a critical dimension of clinical reality: immunosenescence. This process profoundly reshapes immune cell composition, functional capacity, and tumor-immune crosstalk, yet it remains largely absent from existing in vitro systems. In this review, we provide a conceptual and methodological overview of organoid- and microfluidic-based models for reconstructing the TIME. We highlight their respective strengths in capturing tumor heterogeneity and dynamic immune processes, while critically evaluating their limitations in modeling long-term immune evolution and age-associated dysfunction. Importantly, we propose immunosenescence as a missing but essential modeling axis and argue that it should be treated as a controllable experimental variable rather than a background condition. By integrating aging-associated immune features into advanced 3D and microfluidic platforms, next-generation models are poised to better recapitulate patient heterogeneity and improve the prediction of immunotherapy outcomes. This perspective underscores a shift toward age-aware, physiologically relevant tumor models and provides a framework for advancing precision immuno-oncology in an aging population.

Cellular senescence is increasingly recognized as a key contributor to many age-related disorders and diseases, and senotherapeutics, therapies that target senescent cells (SCs), have indicated benefits in multiple preclinical models, including models of obesity, metabolic syndrome/diabetes, and their complications. Importantly, SCs are not a uniform population. They differ by originating cell type, stimuli by which senescence was induced, time since induction of senescence, and the tissue and microenvironment in which senescent cells are located, including the composition and magnitude of the senescence-associated secretory phenotype (SASP). Recent studies have indicated that senescent cell populations comprise cells that release inflammatory SASP factors and less inflammatory senescent cells that release growth factors. Senolytics, agents that eliminate senescent cells, preferentially remove the more inflammatory senescent cells while sparing the less inflammatory senescent cells that arise during processes such as acute wound healing. In another study, senescent cell heterogeneity was investigated in adipose tissue impacted by obesity, with a focus on senescence marker expression and cell-type specificity. p16⁺ senescent endothelial cells were a key source of SASP factors within adipose tissue, but p21⁺ senescent preadipocytes and immune cells also contributed substantially to the inflammatory milieu. Identifying and selectively targeting the more pathogenic, pro-inflammatory senescent cell populations may be facilitated by single-cell-level analyses to elucidate the extent of senescent cell heterogeneity and markers of different senescent cell subpopulations. Appreciating the diversity of senescent cells may be critical, since refining senotherapies based on specific SC subtypes may lead to the development of individualized and personalized therapies, potentially improving upon existing broader-spectrum strategies.

We are entering a historic demographic transition: within decades, one-third of our lives will unfold after age 60, and functional decline typically begins ten to twenty years before disease onset. Yet aging is increasingly malleable: today’s 68-year-olds show the functional profile 62-year-olds showed in earlier cohorts, a measured gain in intrinsic capacity. This gain has not yet translated into a matching compression of morbidity, and the gap between lifespan and healthspan continues to widen. Closing it through geroscience-based prevention is both a scientific opportunity and a public health necessity.This Call to Action synthesizes contributions from 60 experts convened at the Paris Healthy Longevity Summit (May 20, 2026, French National Academy of Medicine, Paris) under the High Patronage of President Emmanuel Macron, organized around one guiding question: how to make healthy longevity accessible to the greatest number of people. Contributions were synthesized into five priority pillars and fifteen actions.Five priority pillars emerged: embedding prevention across the life course; large-scale deployment of the WHO’s ICOPE program; adapting health care professional training; investing in geroscience research and biomarker validation; and changing the cultural image of aging while reorganizing care around healthy longevity. Key recommendations include a healthy longevity check-up from age 50, systematizing ICOPE assessment at every point of contact with the population, a geroscience biomarker-validation consortium, and territorial Healthy Aging Coalitions to reduce socioeconomic gaps in healthy life expectancy.It is addressed to public authorities, health care institutions, research funders, employers, insurers, and civil society: the evidence is converging, and stakeholders are ready to act.

The aorta is increasingly recognised as an immunologically active organ, with studies reporting both resident and recruited myeloid cells throughout its anatomical range. Substantial evidence from experimental and clinical studies suggests that both adaptive and innate immune cells contribute to the pathogenesis of major aortic diseases. This review aims to present the current understanding of myeloid cell biology in the aorta, structured along both anatomical and disease-specific dimensions. We recapitulate the anatomy of the aorta, with an emphasis on the regional immune heterogeneity that underlies segment-specific disease susceptibility. We discuss the role of myeloid cells in prenatal aortic development and their contributions to hematopoietic stem cell emergence within the aorta-gonad-mesonephros region and to cardiac valve morphogenesis, followed by an overview of myeloid populations found in the healthy adult aorta. Subsequent sections address myeloid involvement in congenital aortic disease, calcific aortic valve stenosis, aortic dissection, and aortic aneurysm. Across these pathological states, studies have reported on mechanisms involving myeloid cells. The review concludes with an evaluation of myeloid-targeted therapeutic strategies, discussing lessons from clinical trials and the rationale for emerging inflammasome inhibitors, cytokine blockade, macrophage-targeting approaches, and biomarker studies. In summary, the available evidence suggests that myeloid cells may be involved in aortic pathology across the full anatomical and clinical spectrum, and their convergent inflammatory mechanisms may represent a potential therapeutic opportunity in aortic disease.

Ferroptosis sensitivity in cancer cells is directly governed by cellular metabolism and nutritional inputs, including amino acid availability, lipid composition, and redox homeostasis. This suggests that dietary interventions might systemically shift the metabolic landscape of tumors toward ferroptotic susceptibility. Specifically, dietary restriction of methionine and cysteine, iron supplementation, selenium or lipid modulation, ketogenic diets, and fasting-mimicking regimens each target distinct aspects of the ferroptosis regulatory network and offer pharmacologic parallels that converge on complementary mechanisms. In glioblastoma (GBM), preclinical studies demonstrate that restriction of dietary methionine and cysteine sensitizes gliomas to ferroptosis and synergizes with glutathione peroxidase 4 (GPX4) inhibitors, while radiation itself triggers ferroptotic cell death. Emerging data extend these principles across multiple tumor types, including pancreatic, gastric, esophageal, and colorectal cancers, as well as leukemia, suggesting broad applicability. Here, we synthesize the rapidly growing literature that links these nutritional interventions to ferroptosis sensitization in cancer, with particular focus on GBM as a paradigmatic treatment-resistant malignancy.

The rising incidence of age-related brain pathologies, including brain malignancy, underscores an urgent need to understand the mechanistic interplay between aging and tumorigenesis. Historically viewed as distinct entities, brain tumors and neurodegenerative disorders are now recognized to share key biological processes, such as cellular senescence, chronic inflammation, and metabolic dysregulation. In this review, we deconstruct the existing knowledge at the intersection of cancer neuroscience and aging biology, and propose that age-related alterations in neuronal function, such as the accumulation of senescent cells, ion channel dysregulation, and neurotransmitter imbalance, are not inert background features but as active mediators of tumor progression and treatment resistance. We summarize the aged neural microenvironment, marked by a proinflammatory senescence-associated secretory phenotype (SASP) and blood-brain barrier dysfunction, underlies a permissive soil for malignancy. Moreover, we highlight the emerging concept that tumors can induce a pathological aging phenotype in surrounding neurons, which in turn potentiates the observed cognitive deterioration. By framing brain tumors as products of a dysfunctional aging ecosystem, we propose therapeutic strategies that target convergent aging mechanisms through senolysis, metabolic reprogramming, and neurotransmitter modulation may simultaneously achieve tumor control and preserve cognitive function. This integrated perspective opens new avenues for repurposing neuroactive drugs and designing interventions that address the sophisticated biology of the aging brain and malignancy.

Autologous nerve grafting remains the clinical benchmark for the repair of peripheral nerve injury (PNI), but its widespread application is limited by restricted donor availability, donor-site morbidity, and functional mismatch. Allogeneic nerve grafting introduces additional concerns, including immune rejection and potential disease transmission. Accordingly, tissue-engineered nerve guidance conduits (NGCs) have emerged as promising alternatives for peripheral nerve repair. This review systematically summarizes recent advances in the design and fabrication of high-performance NGCs. We first discuss material-selection principles related to biodegradability, mechanical performance, and cell-adhesive properties, with emphasis on synthetic polymers such as polycaprolactone and natural biomaterials such as silk fibroin and chitosan. We then compare major fabrication strategies, including mold casting, freeze-drying, 3D printing, and electrospinning, highlighting their respective capabilities and limitations in controlling conduit geometry, porosity, micro/nanotopography, and directional guidance. Finally, we summarize functionalization strategies for remodeling the local regenerative microenvironment, including electrical functionalization, anti-inflammatory and antioxidant modifications, and pro-vascularization approaches. Compared with conventional single-layer conduits, multistructured biomimetic NGCs offer greater potential to integrate mechanical support, topographical guidance, electrical regulation, immunomodulation, and vascular support within a single regenerative platform, thereby providing a promising framework for the development and clinical translation of next-generation multifunctional NGCs.

Aims: Conventional type 1 dendritic cells (cDC1) specialize in cross-presentation and interleukin-12 production and are critical for immunity against intracellular pathogens and tumors, but remain rare in vivo, limiting mechanistic and translational studies. Existing bone marrow-derived dendritic cell (BMDC) methods do not achieve selective enrichment of cDC1 or scalable production at high purity. We therefore aimed to establish a high-efficiency BMDC culture system for selective generation of CD103⁺ cDC1 from mouse bone marrow.

Methods: Mouse bone marrow cells were cultured in defined medium with recombinant fms-like tyrosine kinase 3 ligand (FLT3L), low-dose granulocyte-macrophage colony-stimulating factor (GM-CSF), and Kit ligand (KitL) to generate induced cDC1 (iDC1). Phenotypic, transcriptomic, proteomic, phospho-proteomic, and functional analyses were performed and compared with established BMDC methods and ex vivo immune cell populations.

Results: iDC1 cultures enabled scalable generation of an estimated 1.5 × 10⁹ CD103⁺ cDC1 at greater than 95% purity from a single mouse, representing at least a 75-fold increase relative to previous recombinant cytokine-based methods. iDC1 closely aligned with the cDC1 lineage while distinct from macrophages. Functionally, iDC1 responded robustly to innate stimulation, secreted interleukin 12 (IL-12)p40 and inflammatory chemokines, and efficiently cross-presented cell-associated antigen to CD8⁺ T cells. Mechanistically, KitL and GM-CSF cooperated during early cDC1 generation, whereas GM-CSF promoted proliferation and survival during later stages of culture. iDC1 generation depended on the +32 kb Irf8 enhancer, and signal transducer and activator of transcription 5 (STAT5)- and bromodomain-containing protein 4 (BRD4)-associated regulatory programs contributed to efficient iDC1 generation.

Conclusion: iDC1 cultures are a scalable platform for studying cDC1 biology and may facilitate development and preclinical evaluation of cDC1-based immunotherapeutic strategies.

Aims: Δ133p53α is a naturally occurring isoform of the human p53 protein that inhibits p53-mediated cellular senescence. We previously reported that transgenic expression of this senescence-inhibitory p53 isoform counteracts aging-associated pathological changes in progeria model mice (heterozygous Lmna^G609G/+). The anti-aging effect of Δ133p53α was attributed in part to reduced levels of the proinflammatory cytokine IL-6. This study aims to comprehensively profile Δ133p53α-induced changes in cytokines and chemokines.

Methods: A Luminex-based multiplex quantitative assay was performed using mouse serum samples from transgenic Δ133p53α-expressing Lmna^G609G/+ mice and non-expressing controls. Quantitative RT-PCR and RNA in situ hybridization assays were used to assess Cxcl10 expression in mouse tissues. In addition, gene expression datasets from human tissues were analyzed.

Results: In the Luminex assay, used as an exploratory screen, transgenic Δ133p53α expression was suggestively associated with reduced serum levels of not only IL-6 but also CXCL1, IL-1α, and CXCL10. We further characterized CXCL10, which has not previously been linked to progeria in mice or humans. Consistent with reduced serum CXCL10 levels, both young (15-week-old) and old (10-month-old) Δ133p53α-expressing Lmna^G609G/+ mice showed reduced Cxcl10 expression in the liver, spleen, and brain, major organs that produce CXCL10, compared with age-matched non-expressing controls. In naturally aged wild-type mice (2 years old), transgenic Δ133p53α expression also significantly repressed Cxcl10 expression in the spleen and brain. An inverse association between CXCL10 and Δ133p53α levels was observed in human spleen tissues.

Conclusion: CXCL10, a proinflammatory chemokine elevated in both accelerated and natural aging, is a potential target of the anti-inflammatory activity of Δ133p53α.

Aging remains the primary risk factor for malignancy, driven primarily by the progressive decline of the immune system known as immunosenescence. Natural killer (NK) cells serve as the critical effectors of tumor immunosurveillance, yet their anti-tumor efficacy is compromised during biological aging. This review delineates the multifaceted mechanisms of NK cell immunosenescence including phenotypic subset redistribution, receptor signaling dysregulation, and metabolic biogenesis failure driven by mitochondrial impairment alongside telomere attrition and p16 p21 mediated cell cycle arrest. These cell intrinsic defects interact with the suppressive aging microenvironment to create a self-reinforcing vicious cycle that facilitates tumor escape in the elderly population. Breaking this cycle necessitates a multi-dimensional therapeutic framework that integrates cellular rejuvenation via induced pluripotent stem cell (iPSC) derived chimeric antigen receptor (CAR) NK cells with niche remodeling using senolytics or bone marrow rejuvenation. Ultimately targeting the biological hallmarks of NK cell immunosenescence represents a significant frontier in geriatric oncology offering the potential to resuscitate anti-tumor immunity for the burgeoning elderly population.

We discover that a standard Fourier transformation intrinsically imparts a parity-dependent phase shift to optical vortices, yielding a phase difference of π between modes carrying odd and even topological charges. This phase shift, however, is not directly observable from the intensity profile of the transformed beam. To render it measurable, we develop a spin-selective Fourier transformer by co-designing propagation-induced dynamic phase and Pancharatnam-Berry geometric phase in a pair of hybrid-lenses. This device converts the parity-dependent phase shift into orthogonal polarization states via spin-orbit interaction, enabling non-destructive separation of both individual and superimposed orbital angular momentum (OAM) modes without the need for an interferometer. Our work establishes Fourier transformation as a new mechanism for parity-resolved vortex manipulation, offering an integrable platform for high-dimensional photonic applications.

Smart windows are expected to improve building energy efficiency and indoor environmental quality, yet material-level optical modulation alone does not directly predict room-level optical and thermal responses. This study investigates the scenario-dependent performance of commercial stimuli-responsive smart windows through controlled chamber tests, outdoor chamber tests, full-scale office measurements, and a large-area skylight field case. Thermochromic windows (TCWs), electrochromic windows (ECWs), and polymer-dispersed liquid crystal (PDLC) dimming films were evaluated in terms of spectral modulation, illuminance response, temperature variation, and spatial distribution. Controlled chamber tests showed that TCW transition depended jointly on transition temperature and radiation intensity, while ECW coloration was governed by driving voltage and radiation-induced surface heating. Outdoor chamber tests further revealed that side-window modulation and skylight transmittance jointly shaped indoor daylight and heat gain. In the two tested south-facing office rooms, the passively operated TCW room exhibited longer daylight availability and a more spatially distributed illuminance profile through diffuse transmission, together with higher indoor temperatures. The ECW room, maintained at the fixed T2 state, showed lower indoor temperatures but limited daylight during most occupied periods. The large-area skylight case showed that PDLC visual dimming reduced illuminance but provided limited thermal regulation because near-infrared transmittance remained high. These results show that the measured optical and temperature responses were jointly shaped by material response, building configuration, solar exposure, and operation strategy. Scenario-specific spectral design and adaptive control are important for aligning optical and thermal responses in building-envelope applications.

Compared with conventional intensity imaging, complex optical field imaging enables the recovery of both amplitude and phase information of the optical field, and has become an important tool in label-free microscopy, surface metrology, and crystal characterization. However, because conventional detectors can only measure intensity and cannot directly record phase, complex field reconstruction is an ill-posed inverse problem that heavily relies on physical constraints and computational priors. Optical field modulation offers an effective solution by imposing known, controllable modulations into the illumination, propagation, reference, or detection path, improving the observability and recoverability of phase information. Optical field modulation increases the measurement diversity and improves the solvability of the inverse problem, reducing reconstruction ambiguity and improving robustness to noise and missing data. This review establishes a unified framework that classifies optical-field modulation according to the measurement mechanism and modulation location, and compares different strategies in terms of information diversity, identifiability, acquisition efficiency, calibration burden, and dynamic adaptability.