Aims: Non-enzymatic autoxidation of polyunsaturated fatty acids (PUFAs), generating numerous toxic by-products implicated in neurodegeneration, aging, and other pathologies, is a key process in ferroptosis. Lipid peroxidation (LPO) can be inhibited by deuterated polyunsaturated fatty acids (D-PUFA), as the rate-limiting step of abstraction of bis-allylic hydrogen atoms is slowed down by replacing the bis-allylic hydrogens with deuteriums. Here, we aimed to assess the protective effect of monounsaturated fatty acids (MUFA), which do not undergo LPO, as compared to that of various D-PUFAs, in a liposomal model of LPO.

Methods: To detect LPO induced by ferrous ions in liposomes, we used the LPO fluorescent probe C11-Bodipy (581/591), in addition to measuring conjugated diene and malondialdehyde accumulation.

Results: By applying the C11-Bodipy (581/591) probe, we found that both 1-palmitoyl-2-oleoyl-phosphatidylcholine (POPC) and 1-stearoyl-2-(11,11-d₂-linoleoyl)-phosphatidylcholine (D2-Lin-PC) protect non-deuterated 1-stearoyl-2-linoleoyl-sn-glycero-3-phosphocholine (H-Lin-PC) liposomes from LPO. Similarly, both POPC and 1-stearoyl-2-(11,11,14,14-D4-linolenyl)-phosphatidylcholine (D4-Lnn-PC) protect 1-stearoyl-2-linolenyl-phosphatidylcholine (H-Lnn-PC), and so does 1-stearoyl-2-(6,6,9,9,12,12,15,15,18,18-d10-docosahexaenoyl)-sn-glycero-3-phosphatidylcholine (D10-DHA-PC). The conjugated diene and malondialdehyde probes also showed similar protective effects of POPC and D-PUFA on LPO in H-Lnn-PC.

Conclusion: Obviously, the presence of non-oxidizable lipids, such as POPC, similar to the deuterated lipids D2-Lin-PC, D4-Lnn-PC, and D10-DHA-PC, leads to a sharp decrease in the length of lateral propagation of chain reactions in lipid membranes, but they do not participate in LPO themselves.

Osteoarthritis (OA) is a common degenerative joint disease driven by synovial inflammation and immune dysregulation, especially in the knee joint. Macrophages play a key role in innate immunity and can differentiate into pro-inflammatory M1 or anti-inflammatory M2 phenotypes, which have a significant impact on the progression of OA. Electrospun nanofiber membranes, as a promising biomaterial, can regulate the polarization of macrophages towards the M2 phenotype, thereby reducing inflammation and promoting tissue repair. This article systematically reviews the immune microenvironment of OA, the mechanism of macrophage polarization, and the role of nanofiber membranes in the treatment of OA. In conclusion, the continuous development of nanofiber membrane technology will greatly change the future of OA treatment and provide more effective and efficient solutions for patients.

Artificial intelligence (AI) has become a central driver in healthy longevity medicine (HLM), offering new tools to characterize biological aging trajectories, identify preclinical physiological decline, and optimize interventions aimed at preserving function throughout the lifespan by targeting age-related processes. HLM is increasingly recognized as a specialty focusing on the multidimensional process of aging, encompassing molecular, physiological, cognitive, and behavioral components, all of which generate complex, high-dimensional datasets that exceed the analytical capacity of traditional clinical approaches. AI methodologies, including machine learning and deep learning models capable of integrating large, multimodal data streams, provide the computational infrastructure required to produce actionable insights. In the clinical practice of HLM, AI further facilitates integration of converging domains, including continuous digital phenotyping enabled by wearables and sensors, advanced biomarker modeling, predictive modeling capable of forecasting risk trajectories and personalized intervention optimization through life models and digital twins. These models support anticipatory clinical management, shifting care from reactive disease treatment toward continuous preservation of physiological resilience. Despite rapid progress, the integration of AI into routine healthy longevity care requires careful consideration of data quality, algorithmic transparency, regulatory frameworks, population diversity, and clinical interpretability. Nonetheless, AI-driven healthy longevity management is beginning to allow biological aging to be quantified, targeted, and longitudinally monitored in clinical practice.

Optical vortices, characterized by their central singularities and spiral phase wavefront, have gained widespread attention in light manipulation and diverse applications. With their topological order being extended from integer to fraction, more unique properties have sprung out, such as continuous topological charges, fractional spiral-phase, expanded orbital angular momentum spectrum, and slit openings. These features have facilitated applications in areas such as optical tweezers, direction-selective edge enhancement imaging, robust rotational Doppler metrology, free-space communication, displacement sensing, and high-dimensional quantum entanglement. In recent years, advances in metasurface-based optical control, spatiotemporal pulse shaping, holographic imaging, and deep learning have spurred rapid innovation in the modeling, generation, and measurement of fractional vortex beams. This review begins with the fundamental theory of fractional vortex beams and surveys the latest developments in this rapidly evolving field. The scope of research has also expanded beyond optical vortices to include acoustic vortices. The growing interest in fractional vortex beams, coupled with ongoing technological innovations, is expected to pave the way for further advancements in this promising area of research.

Seawater-sea sand concrete has emerged as an innovative construction material due to its effective utilization of marine resources. At the same time, geopolymer concrete has shown rapid hardening capabilities, low energy consumption, and eco-friendly properties, making it highly promising for structural reinforcement. This study evaluated the effects of alkali modulus, alkali concentration, and fly ash (FA) content on the performance of geopolymer FA-slag seawater-sea sand mortar (SWSSGM). Performance characteristics such as consistency, flowability, compressive strength, and flexural strength were tested. The findings indicate that FA enhances workability, whereas slag powder has the opposite effect. Increasing alkali concentration reduces consistency but increases slump. Optimal compressive and flexural strength is achieved when the alkali modulus is 1.2, alkali content is 15%, and FA content is 30%. Generally, higher alkali concentrations promote strength development, while increased FA content raises porosity and reduces strength. However, strength gains over time are more pronounced, and the effects of alkali modulus require further investigation. Multiple linear regression analysis of the three factors affecting SWSSGM properties demonstrates that a quadratic polynomial regression model yields high coefficients of determination (R² ≥ 0.92), enabling accurate predictions of SWSSGM performance parameters. From a lifecycle (cradle-to-gate) perspective, SWSSGM outperforms traditional cement-based materials in terms of carbon emissions, energy consumption, and resource efficiency, showcasing its significant low-carbon, energy-saving, and environmentally friendly attributes. Through systematic optimization of SWSSGM’s design parameters, performance prediction modeling, and preliminary environmental assessment, this study provides guidance for its sustainable application in coastal engineering projects.

The increasing digitalization of the construction industry is reshaping how professionals are trained and educated. As a key component of construction education, traditional site visits provide students with valuable first-hand exposure to real-world construction environments. However, despite their educational value, such visits present multiple challenges, including scheduling difficulties, limited site capacity, health and safety restrictions, induction requirements, and high logistical costs. In recent years, Virtual Reality (VR) has offered new opportunities to deliver remote, realistic, and interactive site experiences that replicate the authenticity of on-site learning without requiring physical presence. Previous studies have primarily focused on fully computer-generated VR environments developed using platforms such as Unity or Unreal Engine. While these models offer flexibility and interactivity, they often lack the contextual realism of actual construction sites. Addressing this gap, the present study designed and developed a VR immersive construction site experience tailored to the Australian construction industry, built from 111 high-resolution 360° panoramas captured at a real construction site. The system architecture was developed using an incremental development approach to manage complexity, refine functions, and ensure continuous feedback. Drawing on insights from a systematic literature review, the system architecture specifically targeted barriers to VR adoption in construction education. The resulting prototype was evaluated by 31 students, revealing positive perceptions across all key constructs, with mean scores of 4.31 for usefulness, 4.30 for ease of use, and 4.28 for learning impact (five-point Likert scale). This study represents a pioneer exploration in establishing a scalable and educationally aligned framework for VR-based construction learning. Future development stages will focus on expanding the system to cover diverse project types, integrating adaptive learning features, and linking it with learning management systems to enhance engagement and learning analytics.

Integrating Carbon Capture, Utilization, and Storage technology into concrete additive manufacturing represents an innovative pathway for achieving carbon emission reduction in the construction industry, while simultaneously offering effective solutions to critical challenges such as insufficient early-age strength and weak interlayer bonding in printed components. Bibliometric analysis reveals that this interdisciplinary field is experiencing a period of exponential growth, with research hotspots rapidly shifting from fundamental 3D printing process exploration to the synergistic optimization of material properties utilizing accelerated carbonation and carbon dioxide sequestration technologies. This review systematically elucidates the mechanisms of carbon mineralization curing, with a particular focus on analyzing three key process pathways: fresh state carbon mineralization, synchronous carbon sequestration during printing, and post-printing carbonation curing. Furthermore, the synergistic enhancement mechanisms of material strategies, including supplementary cementitious materials and carbonated recycled aggregates, are discussed. On this basis, the review identifies core challenges regarding curing uniformity, narrow process windows, and the absence of long-term durability research, and subsequently outlines future development directions such as intelligent closed-loop control and integrated structure-material-process design.

Aims: Users’ empathy towards artificial agents can be influenced by the agent’s expression of emotion. To date, most studies have used a Wizard of Oz design or manually programmed agents’ expressions. This study investigated whether autonomously animated emotional expression and neural voices could increase user empathy towards a Virtual Human.

Methods: 158 adults participated in an online experiment, where they watched videos of six emotional stories generated by ChatGPT. For each story, participants were randomly assigned to a virtual human (VH) called Carina, telling the story with either (1) autonomous expressive or non-expressive animation, and (2) a neural or standard text-to-speech (TTS) voice. After each story, participants rated how well the animation and voice matched the story, and their cognitive, affective, and subjective empathy towards Carina were evaluated. Qualitative data were collected on how well participants thought Carina expressed emotion.

Results: Autonomous emotional expression enhanced the alignment between the animation and voice, and improved subjective, cognitive, and affective empathy. The standard voice was rated as matching the fear and sad stories better, the sad animation was better, creating greater subjective and cognitive empathy for the sad story. Trait empathy and ratings of how well the animation and voice matched the story predicted subjective empathy. Qualitative analysis revealed that the animation conveyed emotions more effectively than the voice, and emotional expression was associated with increased empathy.

Conclusion: Autonomous emotional animation of VHs can improve empathy towards AI-generated stories. Further research is needed on voices that can dynamically change to express different emotions.

Against the backdrop of global climate anomalies and rapid urbanization, rainfall-induced urban flooding has become increasingly frequent. Wuxi, a city in southern Jiangsu Province, suffers annual casualties and economic losses due to flooding, leading to urban chaos. This study proposes a quantitative evaluation of the level of urban flood resilience using a system of resilience evaluation indicators. An evaluation indicator system for urban flood resilience encompassing infrastructure, environment, society, and economy was constructed with 26 indicators. A hybrid multi-criteria decision-making method integrating the Analytic Hierarchy Process, entropy weight method, and GIS technology was developed to assess flood resilience in Wuxi systematically. Additionally, emergy analysis was applied to evaluate urban sustainability. The results indicate that five administrative districts centered in Liangxi District and parts of Yixing City near water bodies exhibit low resilience due to gentle slopes, proximity to active river channels, and high population density. In contrast, most areas of Jiangyin City demonstrate higher resilience owing to elevated terrain, fewer social vulnerabilities, and advanced economic development. The model’s consistency was validated using the Area Under the Curve (AUC) method, yielding an AUC of 0.843. The Emergy Sustainability Index for Wuxi was 0.08 < 1, indicating an unsustainable state. This study provides actionable recommendations for enhancing urban flood management and regional resilience.

When focusing on enhancing specificity, selectivity, and reproducibility of a powerful transducer, such as graphene-based field effect transistors (gFETs), the surface architecture is nearly as important as the bioreceptor, and plays a pivotal role, especially for sensing in complex real-world media. Maximizing analyte-receptor binding efficiency and boosting signal transduction require careful consideration of the charge and size of the bioreceptor and the implementation of strategies for bioreceptor configuration optimization, and concepts to prevent non-specific binding. Antifouling strategies for gFETs commonly include the integration of polyethylene glycol or creating barriers against unwanted proteins and molecules via the formation of functional coatings on the device surface. Recently, specialized approaches have been proposed, such as coating graphene with co-polymers or hydrogels. This perspective article will discuss how the unique properties of these materials can be leveraged to improve gFET sensor sensitivity, selectivity, and performance towards protein biomarkers.

The family of Nectin and Nectin-like molecules (Necls) and their immunoreceptors are essential in the immune response against cancer. While primarily involved in cell adhesion, motility, and proliferation, some Nectin members also serve as ligands for both stimulatory and inhibitory immune receptors, influencing immune responses. The Nectin/Necls and their receptors form a complex regulatory axis crucial for natural killer (NK) and T cell activity. The most relevant ligands in this axis are the Nectin CD112 and the Nectin-like molecule CD155. Both are ligands for the activating receptor DNAX accessory molecule-1 (DNAM-1) and the inhibitory receptor T cell immunoreceptor with Ig and ITIM domains (TIGIT). Additionally, CD155 is a ligand for T cell activation induced late expression (TACTILE), and CD112 for poliovirus receptor related immunoglobulin domain containing (PVRIG), both inhibitory receptors. These ligands bind with higher affinity to their inhibitory receptors than to the activating receptor DNAM-1. Recent advances in cancer immunotherapy have focused on identifying new targets to overcome tumor resistance. Antibody-mediated blockade of inhibitory receptors such as TIGIT, TACTILE, and PVRIG on NK and T cells has shown promising results in animal models and clinical trials, helping to break immune tolerance. Aging significantly increases cancer risk and contributes to the deterioration of the immune response, impairing cancer immune surveillance. Aging is also associated with an altered tumor microenvironment, reducing immune cell infiltration and promoting tumor progression. In elderly cancer patients, both immunosenescence and cancer-related immunosuppression contribute to a defective immune response against tumor cells. Thus, cancer immunotherapy strategies should be personalized to overcome the dysfunctional immune responses in elderly cancer patients. Understanding these interactions, including ligand-receptor binding mechanisms, is vital for developing effective immunotherapies. Since cancer predominantly affects older adults, further research is needed to explore how aging impacts Nectin-receptor interactions and to tailor immunotherapy strategies for elderly patients.

Aims: Sharing a robot’s intentions is crucial for building human confidence and ensuring safety in robot co-located environments. Communicating planned motion or internal state of a robot in a clear and timely manner is challenging, especially when users are occupied with other tasks. Augmented reality (AR) offers an effective medium for delivering visual cues that convey such information. This study evaluates a smartphone-based AR interface designed to communicate a robot’s navigation intentions and enhance users’ situational awareness (SA) in shared human–robot settings.

Methods: We developed a mobile AR application using Unity3D and Google ARCore to display goal locations, planned trajectories, and the real-time motion of a Robot Operating System enabled mobile robot. The system provides three visualization modes: Goal Visible, Path Visible, and Robot Visible, with spatial alignment achieved via a reference image marker. Fifty-eight participants, with varying levels of experience in robotics and AR, took part in an online user study. SA was assessed using a query-based evaluation adapted from the Situational Awareness Global Assessment Technique (SAGAT), examining perception, comprehension, and projection levels. A post-assessment survey captured user opinions on usability and perceived benefits.

Results: Participants achieved an average SAGAT score of 86.5%, indicating improved awareness of the robot mission, spatial positioning, and safe zones. AR visualization was particularly effective for identifying obstacles and predicting unobstructed areas. In the post-assessment survey, over 96.6% of participants agreed that the interface enhanced their confidence and understanding of robot motion intentions.

Conclusion: A mobile AR interface can significantly enhance SA in shared human–robot environments by making robot intentions more transparent and comprehensible. Future work will include in-situ evaluations with physical robots, integration of richer robot-state information such as velocity and sensor data, and the exploration of additional visualization strategies that further strengthen safety, predictability, and trust in human–robot collaborative environments.

Ferroptosis is a regulated form of cell death driven by iron-dependent lipid peroxidation. Recent evidence indicates that ferroptosis is a critical player associated with cell death and inflammatory processes in neurodegenerative diseases, such as Alzheimer’s and Parkinson’s disease, as well as in chronic inflammation. In addition, during aging, the expression and activity of various proteins and cellular processes associated with the ferroptotic pathway, such as lipid peroxidation, have been shown to be altered. In this review, we introduce the concept of xenoferroptosis, a process in which ferroptotic signalling is amplified through the combined action of distinct challenges: one involving sub-threshold ferroptosis-related mechanisms, and another involving sub-toxic levels of exogenous or endogenous stressors. Exogenous challenges, such as air pollutants, pesticides, and micro- or nanoplastics, can disrupt redox balance through increased reactive oxygen species production, and impaired antioxidant defences. Endogenous triggers could include misfolded, aggregated proteins, such as amyloid-beta, hyperphosphorylated tau, and alpha-synuclein, which sensitize cells by promoting redox imbalance and mitochondrial dysfunction. While each individual stressor, either endogenous/exogenous or ferroptotic-associated process, may be sublethal, their convergence would initiate a synergistic cascade that accelerates cell death. We propose that xenoferroptosis represents a distinct pathogenic axis at the intersection of molecular pathology and environmental exposure, offering new perspectives for therapeutic interventions that target its dual-trigger mechanisms.

Ferroptosis, an iron-dependent form of regulated cell death (RCD) driven by lipid peroxidation, has been extensively studied since its conceptualization in 2012 and has been suggested as a therapeutic target in many cancers and degenerative diseases. However, three fundamental questions remain unanswered about ferroptosis. First, the mechanisms by which cells execute death during ferroptosis remain elusive: The key role of lipid peroxides in triggering ferroptosis is established, but how this results in the death of a cell remains unclear. Second, the physiological role of ferroptosis throughout the human life cycle is unclear; currently, there is evidence for ferroptosis in early development, immunity, aging, and tumor suppression, but not in many other aspects of physiology. Third, and finally, the intersection between ferroptosis and other RCD modalities, such as apoptosis, necroptosis, pyroptosis, and autophagic cell death, is necessary for understanding how ferroptosis integrates into networks controlling cellular fate. Addressing these gaps in knowledge is essential for building a comprehensive understanding of this mode of cell death, as well as translating ferroptosis knowledge into effective therapeutics.

Bacterial infections caused by biomaterials represent a significant challenge in the clinical management of implants. Implant infections not only lead to surgical failure, prolong patient hospital stays, and increase healthcare costs, but may also trigger severe complications and even pose a threat to the patient’s life. Research on antimicrobial materials for metal implant surfaces holds significant importance. By developing antimicrobial coatings for implant surfaces or utilizing inherently antimicrobial metallic materials, bacterial adhesion and growth on implant surfaces can be effectively suppressed, thereby reducing infection rates and improving the success rate of implant surgeries. Simultaneously, the development of antimicrobial materials also contributes to advancing medical materials science, offering new approaches and methodologies for antimicrobial design in other medical devices. This holds broad application prospects and significant socioeconomic benefits.

Aims: Atherosclerosis, affecting the aorta, cervical, or intracranial arteries, is a common cause of stroke. Previous studies have shown a strong link between high Lp(a) levels and atherosclerotic stroke due to intracranial atherosclerotic disease, implicating Lp(a) in disease development and progression. The precise role of Lp(a) in stroke subtypes remains unclear, although smaller isoform sizes and oxidized phospholipids on Lp(a) are associated with the disease presence. To clarify Lp(a)’s connection with ischemic stroke subtypes, we evaluated various plasma biomarkers previously linked to Lp(a) and disease.

Methods: We used stored plasma samples and data from 244 participants enrolled in an acute ischemic stroke registry at Columbia University Medical Center in New York. Plasma Lp(a) concentrations, apolipoprotein B100 (APOB), and oxidized phospholipids were measured via enzyme-linked immunosorbent assay. APO(a) isoform size was measured via gel electrophoresis. Stroke subtypes were classified based on etiologies using clinical and imaging data. Adjusted multivariate logistic regression models were built to assess associations between Lp(a)-related biomarkers and stroke subtype.

Results: In participants with acute ischemic stroke, high Lp(a) concentrations, percentage of APOB in Lp(a), and OxPL-APO(a) concentrations were significantly associated with the presence of atherosclerotic stroke compared to those with non-atherosclerotic strokes [OR = 1.30 (p = 5.7e - 3), 1.29 (p = 6.9e - 3), 1.27 (p = 1.7e - 2), respectively]. In participants with atherosclerotic stroke, these changes were significantly associated with extracranial atherosclerotic stroke (ECAD), with an OR = 0.69, p = 4e - 2.

Conclusion: In addition to Lp(a) concentrations, the percentage of APOB in Lp(a), and OxPL-APO(a) concentrations are positively associated with acute atherosclerotic ischemic stroke, specifically ECAD.

The decline in brown adipose tissue (BAT) activity is a hallmark of aging and is believed to contribute significantly to the loss of cold tolerance and the increased propensity for obesity with age. Paradoxically, unlike in many other tissues and organs, available evidence suggests that macroautophagy increases in BAT with aging. This aligns with observations of a negative correlation between thermogenic activity and macroautophagy in response to environmental factors such as ambient temperature, with evidence showing that macroautophagy is suppressed in thermogenically active BAT under cold conditions, and conversely, increased in warmer environments. Moreover, the activation of macroautophagy, particularly mitophagy, has been shown to be essential for the “whitening” process, whereby brown or beige adipose tissue loses its thermogenic phenotype and adopts characteristics of energy-storing white adipose tissue. In contrast, recent findings suggest that chaperone-mediated autophagy (CMA) is directly associated with BAT thermogenesis. In male mice, CMA tends to decline with age in BAT, and pharmacological activation of CMA can restore thermogenic activity. This may be due to a specific role of CMA in degrading thermogenesis-inhibiting factors that accumulate in aging BAT because of diminished CMA activity. Given the critical role of BAT in metabolic health, especially during aging, autophagic processes, and their potential druggability, emerge as a promising strategy to preserve thermogenic capacity and improve metabolic health in the elderly.

Solid waste generation from industrial production and construction activities has increased sharply in recent years. Improper disposal and abandonment of solid waste have led to significant resource loss and pose serious risks to soil, water, and air quality. As a result, incorporating solid waste into concrete production presents a promising strategy to reduce environmental pressure and promote sustainable development. This review investigates the feasibility and performance of various solid waste materials, such as fly ash, limestone powder, stone sludge, silica fume, waste glass, rubber particles, and recycled concrete sand, that are incorporated into 3D printed concrete (3DPC). These materials demonstrate the potential to enhance rheological behavior, mechanical strength, interfacial bonding, and dimensional stability of printable composites. Additionally, their incorporation reduces carbon emissions, diverts waste from landfills, and promotes resource circularity. The benefits and limitations of solid waste are critically evaluated, including printability challenges arising from particle morphology and water absorption. The review emphasizes the need for standardized cost-effectiveness analysis frameworks to quantify economic and environmental balance. Finally, this study highlights the importance of optimizing mix design, surface treatment techniques, and large-scale production strategies to enable widespread adoption of waste-based 3DPC in sustainable construction.

Age-related macular degeneration (AMD), primarily driven by dysfunction of the retinal pigment epithelium (RPE), is the leading cause of irreversible blindness in the elderly. As the central hub for photoreceptor support, nutrient transport, and waste clearance, the RPE is particularly vulnerable to age-related stressors that disrupt proteostasis and mitochondrial quality control. Autophagy and mitophagy are essential regulators of RPE and retinal longevity, ensuring the turnover of damaged proteins and organelles while maintaining energy homeostasis. In AMD, these pathways become compromised, contributing to lipofuscin accumulation, oxidative stress, inflammation, and progressive cell death. This review examines the physiological roles of autophagy and mitophagy in retinal homeostasis, their dysregulation in AMD, and emerging therapeutic approaches aimed at restoring these protective processes. Targeting autophagy and mitophagy is a promising strategy to preserve vision and delay the progression of AMD.

Aims: Drug-target affinity (DTA) prediction is crucial for drug discovery and repositioning. However, existing deep learning-based methods often overlook the synergy between the topological structure of DTA networks and the multimodal features of drugs and targets themselves.

Methods: This study proposes a new method, MIGDTA, a DTA prediction method based on multi-source information and graph convolutional network (GCN), which enhances prediction accuracy by integrating local features with global interaction information. MIGDTA first constructs a drug molecular graph, a target protein graph, and a DTA network, while computing molecular fingerprints and protein descriptors. Subsequently, it employs a graph isomorphism network to learn graph features, a GCN to capture network features, and a multilayer prceptron to encode biological features. Then, it refines heterogeneous network and graph features iteratively through the GCN, and finally concatenates the fused features with biological features for affinity prediction.

Results: Comparative experiments on benchmark datasets demonstrate that MIGDTA significantly outperforms existing methods. On the Davis dataset, compared to the best baseline method, MIGDTA reduces mean squared error (MSE) to 0.185, increases CI by 0.006, and improves $r_m^2$ by 5%. Similar enhancements were observed on the KIBA dataset, where MIGDTA achieves an MSE of 0.130, along with 0.002 and 1% gains in CI and $r_m^2$, respectively.

Conclusion: Feature ablation studies verify the core role of graph features in modeling local structures and network features in capturing global topology, along with the supplementary importance of biological features. Comparative analyses of feature integration approaches confirm the effectiveness of the feature refinement module in fusing multimodal features and enhancing model discriminability.

Aims: Recurrent and uncontrolled inflammation of the colon may cause inflammatory bowel diseases (IBD), which are strongly associated with the onset of colitis-associated cancer (CAC). However, the molecular mechanisms linking inflammation, dysregulated growth, and tumorigenesis remain unclear. This study aims to determine the role of the N⁶-methyladenosine (m⁶A) reader YTH m⁶A RNA binding protein 1 (Ythdf1) in regulating colitis severity and CAC development.

Methods: Ythdf1-deficient and wild-type mice were subjected to dextran sodium sulfate (DSS)-induced colitis to evaluate disease severity, epithelial survival, goblet cell and mucus preservation, and inflammatory signaling. m⁶A-dependent regulation of Jak1 mRNA and the Il6-Jak1-Stat3 pathway activation was assessed through molecular analyses. Additionally, an azoxymethane (AOM)/DSS model was used to determine the impact of Ythdf1 loss on CAC development.

Results: Ythdf1 deficiency significantly worsened DSS-induced colitis, with increased epithelial damage, loss of goblet cells and mucus, impaired epithelial survival, and reduced Stat3 activation. Mechanistically, Ythdf1 recognized m⁶A-modified Jak1 mRNA and enhanced Jak1 protein expression, thereby maintaining the Il6-Jak1-Stat3 signaling during inflammatory stress. Despite aggravating colitis, Ythdf1 loss markedly suppressed CAC progression and reduced tumor burden.

Conclusion: Ythdf1 is a key regulator of intestinal homeostasis, maintaining the Il6-Jak1-Stat3 signaling to protect against colitis while paradoxically promoting CAC progression. These findings identify Ythdf1 as a context-dependent modulator of intestinal inflammation and tumorigenesis, highlighting its therapeutic potential in IBD and CAC.

Aims: This study aims to investigate the relationship between eye movement behaviors and social competence, particularly focusing on listening patterns in multi-person conversations. The goal is to identify objective, quantifiable behavioral indicators of social competence to inform the development of assessment tools and training interventions.

Methods: A three-person setting was designed with two conversational partners and one primary listener, and immersive eye-tracking data were collected using Microsoft HoloLens 2 during conversations on naturalistic topics. Social competence was rated by a clinical psychiatrist using standardized behavioral criteria, while analysis targeted three pre-selected indicators: nodding frequency, selective attention allocation to speaker’s regions of interest (head versus shoulders), and vertical gaze stability during listening.

Results: The results revealed that nodding frequency showed a strong positive correlation with social competence scores, indicating its potential as a robust nonverbal biomarker. Participants with higher social competence demonstrated greater attention to the speaker’s head region while minimizing focus on less informative areas such as the shoulders. Furthermore, individuals with higher scores exhibited significantly lower vertical gaze dispersion, reflecting more focused and stable attentional control during social listening.

Conclusion: This study establishes reliable eye movement-based indicators of social competence, highlighting their potential for assessing and enhancing social skills in real-world interactions. By integrating multimodal behavioral analysis, the findings provide a theoretical and technical foundation for developing personalized, real-time feedback systems for social competence training.

Peripheral nerve injury remains a significant clinical challenge, particularly in cases of long-gap defects. While autologous nerve grafting serves as the current gold standard treatment, its limitations include donor site morbidity and limited donor nerve availability. As a promising alternative, nerve guidance conduits (NGCs) have emerged within the field of tissue engineering. Incorporating electrical stimulation into NGCs has been shown to facilitate peripheral nerve repair by promoting Schwann cell migration and neurite extension. A significant advancement in this area is the application of piezoelectric biomaterials, which generate endogenous electrical signals from physiological mechanical stimuli. This self-powered mechanism eliminates the need for external power sources or additional surgical interventions. This review systematically examines the material design, fabrication strategies, and electromechanical properties of piezoelectric NGCs, along with their recent applications for enhancing Schwann cell function, guiding axonal growth, and promoting functional nerve recovery. Furthermore, it discusses current challenges and future directions, aiming to provide novel insights for the development of next-generation intelligent neural repair materials.