Objective: This investigation sought to elucidate the potential correlation between a recently characterized adiposity metric, termed the Weight-Adjusted-Waist Index (WWI) and hyperuricemia.Methods: A cross-sectional design was employed in this study, featuring both hyperuricemic and non-hyperuricemic subjects with complete WWI data, sourced from the National Health and Nutrition Examination Survey (NHANES) spanning 2017 to March 2020. WWI was calculated utilizing the formula which involves the division of waist circumference (WC) by the square root of the body weight. In order to determine the relationship between WWI and hyperuricemia, both univariate and multivariate logistic regression models, appropriately weighted, were employed in the analysis. The linearity of relationships was validated using smooth curve fitting. Additionally, subgroup evaluations and interaction assessments were conducted.Results: The study sample comprised 7437 subjects, yielding a hyperuricemia prevalence of 18.22%. Stratifying WWI into tertiles, a progressive rise in hyperuricemia prevalence was evident with increasing WWI (Tertile 1: 11.62%, Tertile 2: 17.91%, Tertile 3: 25.13%). The odds ratio (OR) demonstrated that individuals within the highest WWI tertile were significantly more prone to hyperuricemia than those in the lowest tertile (OR = 2.41, 95% CI: 1.88-3.08).Conclusion: This study provides evidence that an elevated WWI is correlated with an increased risk of hyperuricemia in the adult population of the United States. These results suggest that WWI may serve as a viable anthropometric indicator for predicting hyperuricemia.

The tumor microenvironment (TME) assumes a pivotal role in the treatment of oncological diseases, given its intricate interplay of diverse cellular components and extracellular matrices. This dynamic ecosystem poses a serious challenge to traditional research methods in many ways, such as high research costs, inefficient translation, poor reproducibility, and low modeling success rates. These challenges require the search for more suitable research methods to accurately model the TME, and the emergence of 3D bioprinting technology is transformative and an important complement to these traditional methods to precisely control the distribution of cells, biomolecules, and matrix scaffolds within the TME. Leveraging digital design, the technology enables personalized studies with high precision, providing essential experimental flexibility. Serving as a critical bridge between in vitro and in vivo studies, 3D bioprinting facilitates the realistic 3D culturing of cancer cells. This comprehensive article delves into cutting-edge developments in 3D bioprinting, encompassing diverse methodologies, biomaterial choices, and various 3D tumor models. Exploration of current challenges, including limited biomaterial options, printing accuracy constraints, low reproducibility, and ethical considerations, contributes to a nuanced understanding. Despite these challenges, the technology holds immense potential for simulating tumor tissues, propelling personalized medicine, and constructing high-resolution organ models, marking a transformative trajectory in oncological research.

Cardiac tissue engineering has emerged as a promising approach for restoring the functionality of damaged cardiac tissues following myocardial infarction. To effectively replicate the native anisotropic structure of cardiac tissues in vitro, this study focused on the fabrication of micropatterned gelatin methacryloyl hydrogels with varying geometric parameters. These substrates were evaluated for their ability to guide induced pluripotent stem cell-derived cardiomyocytes (CMs). The findings demonstrate that the mechanical properties of this hydrogel closely resemble those of native cardiac tissues, and it exhibits high fidelity in micropattern fabrication. Micropatterned hydrogel substrates lead to enhanced organization, maturation, and contraction of CMs. A microgroove with 20-μm-width and 20-μm-spacing was identified as the optimal configuration for maximizing the contact guidance effect, supported by analyses of nuclear orientation and F-actin organization. Furthermore, this specific micropattern design was found to promote CMs' maturation, as evidenced by increased expression of connexin 43 and vinculin, along with extended sarcomere length. It also enhanced CMs' contraction, resulting in larger contractile amplitudes and greater contractile motion anisotropy. In conclusion, these results underscore the significant benefits of optimizing micropatterned gelatin methacryloyl for improving CMs' organization, maturation, and contraction. This valuable insight paves the way for the development of highly organized and functionally mature cardiac tissues in vitro.

The field of cancer research is increasingly recognizing the complex interplay between biomechanics and tumor epigenetics. Biomechanics plays a significant role in the occurrence, development, and metastasis of cancer and may exert influence by impacting the epigenetic modifications of tumors. In this review, we investigate a spectrum of biomechanical tools, including computational models, measurement instruments, and in vitro simulations. These tools not only assist in deciphering the mechanisms behind these epigenetic changes but also provide novel methods for characterizing tumors, which are significant for diagnosis and treatment. Finally, we discuss the potential of new therapies that target the biomechanical properties of the tumor microenvironment. There is hope that by altering factors such as the stiffness of the extracellular matrix or interfering with mechano-sensing pathways, we can halt tumor progression through epigenetic mechanisms. We emphasize the necessity for multidisciplinary efforts to integrate biomechanics with tumor epigenetics more comprehensively. Such collaboration is anticipated to advance therapeutic strategies and enhance our understanding of cancer biology, signaling the dawn of a new era in cancer treatment and research.

Recent advances in medical diagnostics have highlighted the importance of wearable technologies for continuous and real-time physiological monitoring. In this study, we introduce a flexible, self-powered triboelectric nanogenerator (MB-TENG) engineered from commercially available medical elastic bandages for biomechanical sensing during rehabilitation and gait analysis. Leveraging the porous and skin-friendly properties of the bandage combined with a polytetrafluoroethylene film, the MB-TENG delivers robust electrical performance—achieving a peak open-circuit voltage (VOC) of 122 V, a short-circuit current (ISC) of 25 μA, and a transferred charge (QSC) of 110 nC—while maintaining long-term stability across 40 000 mechanical cycles. Its inherent self-adhesive property allows for multilayer assembly without the need for extra bonding agents, and mechanical stretching enhances output, enabling dual configurability. A stacked design further improves the power capacity, supporting applications in wearable medical electronics. The MB-TENG device seamlessly conforms to joint surfaces and foot regions, providing accurate detection of motion states and abnormal gait patterns. These features underscore the MB-TENG’s potential as a low-cost, scalable platform for personalized rehabilitation, injury monitoring, and early musculoskeletal diagnosis.

Three-dimensional printing technology is fundamentally reshaping the design and fabrication of health monitoring sensors. While it holds great promise for achieving miniaturization, multi-material integration, and personalized customization, the lack of a clear selection framework hinders the optimal matching of printing technologies to specific sensor requirements. This review presents a classification framework based on existing standards and specifically designed to address sensor-related requirements, categorizing 3D printing technologies into point-based, line-based, and area-based modalities according to their fundamental fabrication unit. This framework directly bridges the capabilities of each modality, such as nanoscale resolution, multi-material versatility, and high-throughput production, with the critical demands of modern health monitoring sensors. We systematically demonstrate how this approach guides technology selection: Point-based methods (e.g., stereolithography, inkjet) enable micron-scale features for ultra-sensitive detection; line-based techniques (e.g., Direct Ink Writing, Fused Filament Fabrication) excel in multi-material integration for creating complex functional devices such as sweat-sensing patches; and area-based approaches (e.g., Digital Light Processing) facilitate rapid production of sensor arrays and intricate structures for applications like continuous glucose monitoring. The point–line–area paradigm offers a powerful heuristic for designing and manufacturing next-generation health monitoring sensors. We also discuss strategies to overcome existing challenges, including material biocompatibility and cross-scale manufacturing, through the integration of AI-driven design and stimuli-responsive materials. This framework not only clarifies the current research landscape but also accelerates the development of intelligent, personalized, and sustainable health monitoring systems.