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By integrating 3D-inkjet bioprinting technology, differentiated human cells can be assembled into artificial lung tissue structure to achieve a rapid, efficient, and reproducible disease model construction process. Here, we developed a novel 3D-inkjet bioprinting-based method to construct artificial lung tissue structure (ALTs) for acute lung injury (ALI) disease modeling, research and application. It can also be used to study the role of relevant cells in the disease by adjusting the cell type and adapted to study the bio-functions of immune cells during the cell-cell interactions. Firstly, a series of process optimizations were done to mass-produce the alginate hydrogel microspheres (Alg) with a particle size of 262.63 ± 5 μm using a 3D bioprinter, then the type I collagen and polydopamine were deposited in turns to construct a cell adhesion layer on the surfaces of Alg (P-Alg) and the particle size was increased to 328.41 ± 3.81 μm. This platform exhibites good stability, timescale-dependent behavior, and long-term cell adhesion. Subsequently, several human cells including endothelial, epithelial, fibroblast, and even immune cells such as macrophages were adhered to P-Alg through rotational culture, leading to cell contractions and aggregation, subsequently formed ALTs or ALTs with macrophages (ALTs@M) with human alveolar-like structure. Finally, we successfully constructed an ALI model with lung barrier damage on ALTs using lipopolysaccharide stimulation in vitro, and comparison of secreted inflammatory factors between ALTs and ALTs@M. Results demonstrated that ALTs@M was more effective than ALTs in stimulating the inflammatory microenvironment of the lungs, providing a novel in vitro model for cellular interactions and human macrophage research. Altogether, this artificial lung tissue structure construction strategy using 3D-inkjet bioprinting technology allowed the flexible development of artificial lung tissue structures as potential disease models for preclinical studies.
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http://dx.doi.org/10.1177/20417314251328128 | DOI Listing |
Soft Robot
September 2025
Bioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Genoa, Italy.
Animal diaphragm-lung systems are soft organs that generate a controllable vacuum. Elephants, as rare land animals, can manipulate all three states of matter using their lung-generated vacuum. In soft robotics, however, current vacuum generation relies on rigid components, and no single soft device effectively handles all states of matter.
View Article and Find Full Text PDFAnn Acad Med Singap
August 2025
Division of Medical Oncology, National Cancer Centre Singapore, Singapore.
Introduction: The high prevalence and mortality rates of breast cancer and lung cancer in Singapore necessitate robust screening programmes to enable early detection and intervention for improved patient outcomes, yet 2024 uptake and coverage remain suboptimal. This narrative review synthesises expert perspectives from a recent roundtable discussion and proposes strategies to advance breast cancer and lung cancer screening programmes.
Method: A 2024 roundtable convened clinical practitioners, health policymakers, researchers and patient advocates discussed current challenges and opportunities for improving cancer screening in Singapore.
Crit Care Explor
September 2025
Division of Pulmonary, Allergy, Critical Care, and Sleep, University of Minnesota, Minneapolis, MN.
Mean airway pressure, a monitored variable continuously available on the modern ventilator, is the pressure measured at the airway opening averaged over the time needed to complete the entire respiratory cycle. Mean airway pressure is well recognized to connect three key physiologic processes in mechanical ventilation: physical stretch, cardiovascular dynamics, and pulmonary gas exchange. Although other parameters currently employed in adults to determine "safe" ventilation are undoubtedly valuable for daily practice, all have limitations for continuous monitoring of ventilation hazard.
View Article and Find Full Text PDFRev Cardiovasc Med
August 2025
Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, LE3 9QP Leicester, UK.
Adult congenital heart disease (ACHD) constitutes a heterogeneous and expanding patient cohort with distinctive diagnostic and management challenges. Conventional detection methods are ineffective at reflecting lesion heterogeneity and the variability in risk profiles. Artificial intelligence (AI), including machine learning (ML) and deep learning (DL) models, has revolutionized the potential for improving diagnosis, risk stratification, and personalized care across the ACHD spectrum.
View Article and Find Full Text PDFAllergy
September 2025
Department of Musculoskeletal and Dermatological Sciences, Faculty of Biology, Medicine and Health, Lydia Becker Institute of Immunology and Inflammation, The University of Manchester, Manchester, UK.
Mast cells (MCs) rapidly adapt to the microenvironment due to the plethora of cytokine receptors expressed. Understanding microenvironment-primed immune responses is essential to elucidate the phenotypic/functional changes MCs undergo, and thus understand their contribution to diseases and predict the most effective therapeutic strategies. We exposed primary human MCs to cytokines mimicking a T1/pro-inflammatory (IFNγ), T2/allergic (IL-4 + IL-13), alarmin-rich (IL-33) and pro-fibrotic/pro-tolerogenic (TGFβ) microenvironment.
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