Iron occupies a paradoxical position in biology: indispensable for life through enabling electron transport in metabolism, yet equally capable of driving cellular death. This is exemplified when ferroptosis was defined in 2012 by Dixon and Stockwell (built on parallel work by Marcus Conrad) as a distinct form of regulated cell death. Crucially, ferroptosis is not simply cell death caused by iron poisoning (i.e., iron overload); rather, the ‘dependency of iron’ is evidenced by specific iron chelators that inhibit the induction of death by agents that disrupt cellular redox control (e.g. erastin, which depletes cellular glutathione, and RSL3, which inhibits GPX4 activity, and others). Still, the etymological emphasis on iron does not fully capture the complexity of ferroptosis, which involves a network of potentially lethal metabolic processes encompassing lipids, thiols, and reactive oxygen species. Adding to this tension, recent negative clinical trials of iron chelators in degenerative diseases where ferroptosis has been implicated have tempered enthusiasm for iron-focused strategies and prompted a re-evaluation of iron’s true role in these diseases, and by extension, ferroptosis. In this perspective, we examine the evolving understanding of the ferrum in ferroptosis, its place within the broader metabolic landscape, and its role in neurodegenerative diseases.

Aims: The subcellular localization of viral proteins can give insight into virus replication, immune evasion, and the development of therapeutic targets. Traditional experimental methods for determining localization are time-consuming and costly to perform, which calls for robust computational approaches. In this paper, we propose designing a computational method for identifying the subcellular localization of viral proteins.

Methods: In the effort to improve feature extraction for viral protein subcellular localization, a novel hybrid deep learning architecture, SpanAttNet, was proposed by incorporating span-based convolution with spatial pyramid dilated convolution and a residual self-attention mechanism. Three commonly used sequence descriptors, AAC, PseAAC, and DDE, each combined with PCA for feature dimension reduction, were systematically used to benchmark SpanAttNet.

Results: Among the individual descriptors, the best performance was yielded by PseAAC (accuracy 93.95%, MCC 91.18% at ρ = 0.8 PCA reduction), while optimal performance from DDE was at minimum reduction (accuracy 87.00% at ρ = 0.2). Moreover, ensemble feature fusion across the various descriptors elevated SpanAttNet to its top performance, reaching an MCC of 93.79% and an F1-score of 92.91%, hence achieving the best balance between sensitivity and specificity. Compared to state-of-the-art models, SpanAttNet managed to consistently match or surpass predictive accuracy, demonstrating strong generalizability.

Conclusion: We establish SpanAttNet as a robust and biologically informed predictor for viral protein subcellular localization, with strong potential for extension to multi-label classification and broader proteomic applications.

Accurate measurement of cysteine and related thiol-containing metabolites is essential for understanding cellular redox regulation. However, the intrinsic reactivity and instability of cysteine present substantial analytical challenges. This review summarizes the biochemical context of cysteine and glutathione metabolism, emphasizing their dynamic redox equilibria and physiological relevance. We critically examine existing analytical approaches, including mass spectrometry-based, enzyme-coupled, and colorimetric methods, and discuss their respective strengths and limitations. Particular attention is given to sample preparation, derivatization strategies, and reagent selection, as these steps are crucial for preserving native thiol-disulfide status. Among various alkylating agents, N-ethylmaleimide is identified as the most reliable for thiol stabilization in liquid chromatography–mass spectrometry (LC-MS) workflows, while specific reagents such as monobromobimane or β-(4-hydroxyphenyl)ethyl iodoacetamide (HPE-IAM) are required for persulfide and polysulfide detection. The review also highlights the pitfalls of using indirect surrogates—such as glutathione or cystathionine levels—to infer cysteine availability, which can lead to significant misinterpretation of metabolic states. We conclude that direct LC-MS-based quantification of cysteine and glutathione, combined with careful derivatization and sample handling, remains the most reliable and accurate approach currently available for the assessment of thiol metabolism and redox homeostasis.

Aims: This study introduces and evaluates a virtual reality (VR) prototype designed for the Loving-Kindness Meditation (LKM) to support mental health rehabilitation and relaxation in clinical contexts. The aims include the co-creation of a VR-based mindfulness experience with clinical experts and the evaluation of its usability, user experience, and short-term effects on relaxation, affect, and self-compassion.

Methods: Following a design thinking and co-creation approach, the VR-based LKM experience was developed iteratively with input from clinicians and computer scientists. The final prototype was implemented for the Meta Quest 3 and included five immersive scenes representing phases of the LKM and transition moments guided by a professional voice recording. Eleven participants (M = 36.5 years, SD = 14.6) experienced the 12-minute session. Pre- and post-session measures included relaxation, positive and negative affect schedule, self-compassion, and usability, complemented by the Igroup Presence Questionnaire and a semi-structured qualitative interview.

Results: Participants reported significant decreases in negative affect (t(10) = -2.512, p = .0307, d = -1.037) and stress (t(10) = -3.318, p = .007, d = -1.328), as well as increases in relaxation (t(10) = 5.487, p < .0001, d = 2.471) and self-compassion (t(10) = 2.231, p = .0497, d = 0.283). Usability was rated as excellent (M = 92.5), and presence as good (M = 4.0, SD = 0.43). Qualitative feedback described the experience as calming, aesthetically pleasing, and easy to engage with, highlighting the falling leaves and pulsating orb as effective design elements.

Conclusion: The co-designed VR-LKM prototype was perceived as highly usable and beneficial for inducing relaxation and self-compassion, suggesting its potential as a supportive tool for clinical mindfulness interventions. The results indicate that immersive VR can effectively facilitate engagement and emotional regulation, providing a foundation for future clinical trials and broader implementation in therapeutic and wellness settings.

Ferroptosis, a regulated form of cell death driven by iron-dependent lipid peroxidation, has emerged as a crucial tumor suppressive mechanism and a promising therapeutic target in oncology. This review synthesizes the current understanding of its core molecular machinery, encompassing lipid metabolism, iron homeostasis, and multi-layered cellular defense systems. We highlight the unique metabolic and genetic vulnerabilities that render specific cancer cell types intrinsically susceptible to ferroptosis. Furthermore, we discuss the dynamic propagation of ferroptotic signals within the tumor microenvironment and their complex immunomodulatory effects. Central to this review is a strategic framework for targeting ferroptosis, synthesizing recent advances in the development of specific ferroptosis inducers and evaluating their synergistic potential when combined with chemotherapy, radiotherapy, targeted therapy, and immunotherapy. By integrating mechanistic insight with translational perspectives, this work provides a systematic guide for rationally exploiting ferroptosis in cancer treatment.

It has been extensively shown that Building Information Modelling (BIM) improves project performance, which is impacted by various critical performance factors of BIM project (CPFs-BP). However, it has become a difficult problem in theory and practice to determine the most important CPFs-BP impacting BIM project performance (BPP) at various life-cycle stages. In light of this information gap, the goal of this study is to identify the most important CPFs-BP and identify the stages at which BIM can be applied to enhance BPP through specific CPFs-BP. Using a review of the literature, this work first discovers and characterizes 17 CPFs-BP. Then, by constructing a two-dimensional, two-mode network of heterogeneous nodes, this study demonstrates the top seven CPFs-BP, the relationship between CPFs-BP and life-cycle stages, and the relative significance of various life-cycle stages in BIM projects using descriptive methods and complex network theory. BPP prediction models were then constructed and validated utilizing fitness parameters using MATLAB and data obtained from expert interviews and surveys. Lastly, five specific strategies are put forth to enhance BPP: increasing BIM accuracy during the construction phase, enhancing stakeholders’ capacity to coordinate the design of construction documents, enhancing BIM accuracy during the completion phase, fostering cooperation between conceptual design organizations, and utilizing the BIM system environment during the construction phase. Important BIM project stakeholders can apply the study’s conclusions. Finally, five specific approaches to improving BPP are proposed: improving BIM accuracy at the construction stage, stakeholders’ ability to organize construction document design, BIM accuracy at the completion stage, collaboration between conceptual design organizations, and the BIM system environment during the construction stage. The study is useful for key stakeholders in BIM projects who can put its findings into practice and help evaluate BPP throughout the project’s life cycle.

Drug-Drug Interaction (DDI) prediction plays a critical role in ensuring clinical medication safety and optimizing therapeutic regimens, while also representing a significant challenge in the drug development process. With the rapid advancement of artificial intelligence technologies, computational methods based on machine learning and deep learning have emerged as the mainstream paradigm in DDI research. In this survey, we systematically review the latest research progress and establish a clear methodological taxonomy that traces the evolution from classical feature engineering to modern deep learning architectures. Beyond detailing foundational molecular representations, we provide a comprehensive overview of DDI prediction techniques, encompassing sequence-based models, graph-based models, Transformers, and Graph Transformers. Our analysis culminates in a dedicated discussion of emerging advanced strategy paradigms, such as multimodal fusion and specialized pre-training and fine-tuning schemes. Furthermore, we synthesize current challenges with contemporary solutions and discuss their practical implications for clinical decision support, providing a forward-looking perspective for the continued development of DDI prediction models.

Lipoprotein(a) is an established risk factor for atherosclerotic cardiovascular disease (ASCVD), with strong evidence of causality from genetic and epidemiological studies. This recognition has led to the development of multiple potent lipoprotein(a)-lowering therapies, four of which are currently in phase 3 cardiovascular outcomes trials. Despite this progress, several critical knowledge gaps remain. Notably, the potential role of high lipoprotein(a) in non-coronary vascular diseases, specifically peripheral arterial disease, major adverse limb events, and abdominal aortic aneurysms, has not been adequately investigated, despite the considerable morbidity and mortality associated with these conditions. Furthermore, recent findings suggest that systemic low-grade inflammation, as measured by high-sensitivity C-reactive protein (hsCRP), may modify the ASCVD risk attributable to high lipoprotein(a). This raises the possibility that future lipoprotein(a)-lowering therapies may only benefit individuals with concomitantly elevated hsCRP. This review summarizes the current knowledge of lipoprotein(a) as a risk factor for cardiovascular disease and aortic valve stenosis, outlines the emerging evidence linking lipoprotein(a) with peripheral arterial disease, major adverse limb events, and abdominal aortic aneurysms, and examines whether high lipoprotein(a) independently predicts the risk of ASCVD and aortic valve stenosis regardless of the presence or absence of systemic low-grade inflammation. By placing recent studies within a broader scientific landscape, we will thus attempt to clarify the vascular relevance of high lipoprotein(a) beyond coronary disease and inform precision targeting of future lipoprotein(a)-lowering therapies.

Several EU policy and legislative initiatives aim to tackle the problem of major resource use and waste within the built environment, both energy and materials, including plans to decarbonise the sector and implement circularity principles. The use of modular systems in deep energy retrofit is argued to present an accelerated decarbonisation pathway with potential to implement advanced circularity. However, modular retrofit and the integration of circularity in the built environment and its assessment is an emerging area of research with the literature identifying need for comprehensive assessment methods demonstrated in practical case studies. This paper examines the development of a novel holistic design for disassembly assessment framework and method piloted in the prototype design of modular wall over-cladding systems in the deep energy retrofit of social housing in Ireland under the EU Drive 0 project. The findings indicate significant differences in design for disassembly performance between the modular circular solution and a conventional solution, with differences in performances at all construction levels. The method provides a holistic and detailed assessment but is critiqued in terms of complexity and user subjectivity relating to the assessment stage, data availability and professional knowledge and/or experience, with a revised adapted method proposed. The research contributes to knowledge in highlighting the potential and complexity of achieving advanced design for disassembly in practice, demonstrating that there are significant differences in the performances across construction types and hierarchy and that assessment methods need to be robust, holistic, sufficiently detailed but not overly complex for application in practice.

Immunosenescence is a biological process accompanying ageing, characterized by increased susceptibility to infections, reduced vaccine efficacy, and the development of chronic low-grade inflammation. Although immunosenescence is systemic, the relative contribution and compensability of each organ in the adaptive immune axis remain debated. We consolidate current evidence supporting a thymus-centric model of immune ageing. In this model, early and progressive thymic involution, marked by thymic epithelial cell attrition, FOXN1 decline, and architectural disruption, emerges as the principal constraint on de novo naive T‑cell production and T-cell receptor (TCR) repertoire renewal. In contrast, age‑related changes in bone marrow and spleen often exhibit partial compensability through peripheral redistribution and clinical interventions, sustaining counts but not restoring de novo diversity. We evaluate mechanisms of thymic involution, inter-organ communication, and cross-species parallels, identifying shared features across animal models. Quantitative readouts, including age-associated declines in sjTRECs and TCR-β repertoire diversity, further support the thymus-centricity. Clinically, constrained thymopoiesis may undercut vaccine responsiveness and reduce the efficacy of cancer immunotherapies (chimeric antigen receptor T-cell and immune checkpoint inhibitors) in older adults. We assess genetic, pharmacological, and bioengineering strategies to preserve or restore thymic function and outline translational paths and endpoints for future trials.

Adrenaline hydrochloride is an indispensable drug in clinical emergencies, effective at alleviating critical conditions such as weak pulse and respiratory distress. However, the catechol moiety in its molecular structure is prone to oxidation, leading to drug degradation, reduced efficacy, and a short half-life. These inherent limitations significantly restrict its broader clinical application. To address this challenge, this study constructed an intelligent microneedle patch designed to stabilize drugs. We first grafted 3-aminophenylboronic acid onto silk fibroin via 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide/N-hydroxysuccinimide coupling chemistry. This design enables the formation of reversible boronic ester bonds between phenylboronic acid and the catechol structure of adrenaline, effectively shielding the oxidation-sensitive sites and significantly enhancing the drug’s storage stability. Upon insertion into the skin, the microneedles encounter the physiological environment where glucose competitively binds to the phenylboronic acid, triggering the cleavage of the boronic ester bonds and resulting in the on-demand release of adrenaline. A cumulative drug release rate of approximately 60% was achieved over 24 hours. This study proposes a novel “protection-release” dual-functional design, offering a new strategy for the efficient delivery and stabilized storage of catechol-containing drugs. This approach holds significant promise for applications in emergency medicine and the long-term storage of pharmaceuticals.

Current Lp(a)-related scientific literature is mainly related to cardiovascular diseases, while less attention has been paid to the role of Lp(a) in both the severity of infections and the vascular disease events that follow them. In this perspective article, we highlight findings related to lipoprotein(a) [Lp(a)] in infectious diseases, including those caused by the severe acute respiratory syndrome coronavirus 2, human immunodeficiency virus, hepatitis C virus (HCV), Helicobacter pylori, Chlamydia pneumoniae, cytomegalovirus, or the Plasmodium and trypanosomal parasites. Based on the data from the above-mentioned infections and Lp(a), the role of Lp(a) in these common infectious diseases will be discussed. Of particular interest is that Lp(a) can inhibit HCV infection and is also important for protection against parasitic infections such as malaria and trypanosomiasis. New drugs, like muvalaplin, significantly lower Lp(a) levels, and it is therefore important to learn about the significance of low Lp(a) levels in terms of the potential course of an infection. It remains to be seen whether Lp(a) drugs with different mechanisms of action are relevant for infections.

The aggregation, distribution, spreading, elongation and shrinking, as well as other behaviors of liquids, along with mass transfer and thermal exchange, are ubiquitous in both natural creatures and human daily life. These phenomena greatly inspire the advancement of liquid manipulating interfaces in theoretical models, production processes, and performance optimization. After decades of development, regulating liquid movements through surface chemistry, micro/nano structures, and geometrical gradients is becoming increasingly prevalent but still faces challenges. This review discusses the design principles of liquid manipulating interfaces, bionic prototypes and its models behind, and introduces their specific role within these works. We summarize state-of-the-art works from different motion dimensions, as well as the most widely mentioned applications. We believe this can inspire the transfer of bioinspired structures into functional devices through continued innovative breakthroughs and multidisciplinary collaboration.

Background: DNA methylation patterns are established during development and are propagated in a cell type specific manner, but these patterns may become aberrant during aging and cancer. Regions of alternating high and moderate to low levels of DNA methylation exist along all chromosomes in human cells. It is unclear how these distinct DNA methylation blocks are established. Most of the prior work in this area has been performed with mouse embryonic stem cells.

Methods: Using whole genome bisulfite sequencing and chromatin-immunoprecipitation sequencing, we have profiled DNA methylation at single base resolution and various histone modifications in human bronchial epithelial cells.

Results: We found that many regions of lower DNA methylation (< 50%) are characterized by presence of the Polycomb repressive complex 2 (PRC2) mark, histone H3K27 trimethylation, but less so by the PRC1 mark histone H2AK119 monoubiquitylation. These same PRC2-marked regions also showed a depletion of histone H3K36 di- and tri-methylation.

Conclusion: Since H3K36me2 and H3K36me3 are recognized by the reader domains of the DNA methyltransferases DNMT3A and DNMT3B, and H3K36 methylation is a block to the PRC2 methyltransferases, these two types of crosstalk may explain the stable maintenance and antagonism between H3K27me3 and broad DNA methylation domains. However, methylated CpG islands are depleted of H3K36me2 and show a different relationship between DNA methylation and H3K36me2 deposition compared to non-CpG island regions. The data give insight into how DNA methylation patterns are established in human cells. We discuss these findings and their potential relevance for altered DNA methylation patterns seen in aging tissues and in cancer cells.

Skin diseases affect nearly one quarter of the global population, with prevalence rising sharply among older adults. By 2050, the number of individuals over 60 years will double, making age-related dermatological conditions an increasing public health concern. A central process underlying aging is cellular senescence, a stable form of growth arrest induced by diverse stressors, including DNA damage, telomere attrition, and oncogenic signaling. Senescent keratinocytes, fibroblasts, melanocytes, and immune cells accumulate in the skin with age and secrete a pro-inflammatory senescence-associated secretory phenotype (SASP) that actively shapes the cutaneous immune landscape. Although senescence can promote tissue repair and tumour suppression, the persistence of senescent cells drives inflammation, impairs immunity function, and contributes to pathology, a concept now termed senopathy. In this review, we first examine the crosstalk between senescent stromal and immune cells in human skin. Then we discuss how SASP from senescent fibroblasts inhibits the function of resident T cell, while senescent T cells adopt a paradoxical state, hyperfunctional yet non-proliferative, that can accelerate tissue damage. We further highlight the immune evasion strategies which enable senescent cells to persist and drive inflammaging. Insights from patients with Familial Melanoma Syndrome (germline CDKN2A mutations) illustrate how defective senescence pathways across multiple cell types impair cutaneous immunosurveillance and increase melanoma risk. Finally, we explore evidence for stromal- and immune-mediated cutaneous senopathies, including psoriasis, lupus, vitiligo, and leishmaniasis, where senescent cells actively drive the diseases’ progression. Based on the analysis, we propose that the skin represents a powerful and accessible model for investigating the interplay between senescent immune and non-immune cells across the lifespan, with therapeutic implications for aging and age-related pathologies.

Neurons exist at the intersection of two essential yet hazardous metabolic demands: iron-driven bioenergetics and lipid-dependent membrane remodeling. Their reliance on mitochondrial iron for adenosine triphosphate (ATP) generation, combined with the requirement for polyunsaturated fatty acids to sustain synaptic plasticity, creates a biochemical environment primed for ferroptosis. This Perspective examines how the interplay between iron and lipid metabolism defines neuronal vulnerability in neurodegenerative diseases, focusing on apolipoprotein E (ApoE) as a metabolic gatekeeper coordinating those pathways. Beyond its canonical function in lipid transport, ApoE acts as a potent anti-ferroptotic factor by inhibiting ferritinophagy and restraining the release of labile iron, thereby coupling lipid trafficking with iron homeostasis. Dysregulation of this axis in Alzheimer’s disease amplifies lipid peroxidation and compromises antioxidant defenses. Parallel mechanisms are observed in Neurodegeneration with Brain Iron Accumulation disorders, where mutations in lipid-metabolic genes paradoxically lead to brain iron accumulation, underscoring the genetic entanglement of these pathways. Collectively, these findings support a unifying model in which neuronal ferroptosis arises not from isolated iron overload or lipid imbalance, but from the breakdown of a coordinated iron-lipid defense network. We propose that restoring this equilibrium through modulation of ApoE function, preservation of mitochondrial iron utilization, and suppression of lipid peroxidation represents a promising avenue for therapeutic intervention in neurodegenerative disease.

Immobilized photocatalyst devices for overall water splitting (OWS) have emerged as a promising strategy for practical hydrogen production. Compared with traditional powder suspension systems, they offer great advantages, including scalability, facile recovery/replacement of photocatalysts, and the elimination of extra dispersion operations. Over the past decade, significant progress has been achieved in this field, especially in material screening, device construction, and system integration for scalable applications. However, up until now, there have been no related reviews focusing on this topic. This review aims to fill this gap by providing a comprehensive and structured overview of the immobilized photocatalyst devices for efficient OWS. Firstly, the basics of OWS process, including one-step and two-step photoexcitation mechanisms, are elaborated. Subsequently, recent advances in immobilized photocatalyst devices for scalable OWS via these two different approaches are summarized, based on which various solid-state electron mediators are classified and exemplified. The essential structure-performance relationship is also analyzed and revealed. Finally, the future prospects and challenges in this field are proposed and discussed.

3D-printed concrete (3DPC) represents a rapidly developing technology with numerous applications in construction. The properties of 3DPC under both static and dynamic loads can be enhanced by incorporating reinforcement. This study presents a novel reinforcement technique utilizing U-shaped steel wire mesh (U-shape SWM). This technique involves integrating both horizontal and vertical reinforcements during the concrete printing process. Additionally, a new fabrication process was developed using a dual-arm robotic system, with each arm equipped with shaping and welding tools, to autonomously create U-shape SWM structures. An experimental investigation was conducted on specimens reinforced with either flat or U-shape SWM reinforcements under flexural loading. Compared to the specimens reinforced with a single layer of 6-mm flat SWM under a shear-span ratio of 2, those incorporating one layer of U-shape SWM combined with two layers of 6-mm flat mesh exhibited a 200% increase in failure load and a 26.09% increase in cracking load, while the ultimate displacement decreased by approximately 6%. Under a reduced shear-span ratio of 0.5, this reinforcement configuration reached a failure load of 43.6 kN, a cracking load of 16.1 kN, and an ultimate displacement of 11.1 mm. Furthermore, an analytical model based on the strut-tie model was developed to predict the load-bearing capacity of the reinforced specimens. The model predictions showed good correspondence with the experimental results.

Background: The outcomes of older adults with cancer are usually worse than those of their younger counterparts. Several randomised trials have demonstrated benefits of a comprehensive geriatric assessment (CGA) in older patients undergoing systemic cancer therapy. Despite that, CGA is not implemented into routine care in Germany and data on its efficacy and feasibility within the German healthcare system are missing.

Methods: This prospective, bicentric cohort study will assess the feasibility of CGA implementation into routine care for older adults with cancer in Germany. Patients ≥ 65 years with a positive geriatric screening (G8) and newly diagnosed cancer or progressive disease prior to a new treatment line undergo a CGA as part of their routine care. Patients who consent to participate in the study receive a follow-up call after three months to assess functional measures, and their (routine) CGA data are analyzed thereafter. CGA results are presented during the multidisciplinary team meeting to inform treatment recommendations provided by primary healthcare providers (pHCP; e.g., oncologists, gynecologists, urologists). pHCP are further evaluated for their satisfaction with CGA implementation and whether its results have influenced their recommendations. The primary endpoint is to estimate the patients’ willingness to participate with an accuracy of ± 7.5%. Secondary endpoints focus on additional feasibility measures and patient preferences.

Conclusion: This study will assess the feasibility of CGA implementation into routine care for older cancer patients. Its results will provide the framework to design a larger subsequent trial to assess the efficacy and cost effectiveness of CGA implementation in Germany.

Clinical trial registration number: DRKS00035569

With increasing chronological age, the vascular system gradually loses its functional integrity, a process known as vascular aging. This decline is a major contributor to arterial and venous thromboembolic disorders, which represent one of the leading causes of mortality and morbidity among aged individuals. However, the precise biological mechanisms linking systemic aging to thrombotic susceptibility remain poorly understood, hindering the development of effective preventive and therapeutic strategies for age-related thrombotic diseases. Aging, as a fundamental determinant of vascular health, shifts the balance between prothrombotic and antithrombotic mechanisms through cumulative molecular and cellular alterations across vascular cells, red blood cells, platelets, and immune cells. These interconnected hallmarks collectively disrupt endothelial homeostasis, enhance platelet reactivity, and impair coagulation and fibrinolytic pathways. Emerging factors, including clonal hematopoiesis of indeterminate potential and environmental exposures, further exacerbate the thrombotic risk in older populations. Clinically, thrombosis management in the elderly requires careful calibration between protection against ischemia and bleeding risk, as age-associated changes are known to affect the safety and efficacy of antiplatelet and anticoagulant therapies. The development of geroscience-guided interventions, alongside optimized antithrombotic strategies, will be essential to reduce the thrombotic burden and improve outcomes in the aging population.