Search Results (808)

Organoid culture represents a sophisticated biological model that surpasses traditional two-dimensional (2D) methods and animal models in physiological relevance and cost-effectiveness. Current organoid systems derive from adult, fetal, and induced pluripotent stem cells, providing innovative platforms for studying organ development, disease pathogenesis, and drug discovery. Recent technological advances now enable respiratory organoids to significantly contribute to respiratory disease research. This review comprehensively synthesizes the development of respiratory organoid models and their applications in studying major respiratory diseases, including pulmonary fibrosis, chronic obstructive pulmonary disease (COPD), and lung cancer. It further evaluates the transformative potential of these models in advancing respiratory disease research. Respiratory organoids uniquely model disease mechanisms and drug responses in human-specific microenvironments, enabling pathogenesis studies of respiratory diseases. They serve as functional platforms for drug screening and personalized therapy development. Future integration of multi-organoid systems with precision medicine promises to redefine respiratory disease research paradigms. Full article

Background/Objectives: Epithelial ovarian cancer (EOC) is often diagnosed at advanced stages, with metastasis driven by spheroid dissemination within the peritoneal cavity. We previously demonstrated that autophagy supports spheroid cell survival and suggest that it contributes to chemoresistance. Unc-51-like autophagy activating kinase 1 (ULK1), a key regulator of autophagy, has emerged as a promising therapeutic target. Here, we evaluated the effects of ULK1 inhibition via MRT68921, alone and in combination with afatinib—a tyrosine kinase inhibitor (TKI) known to induce pro-survival autophagy—in EOC. Methods: High-grade serous (HGSOC) and ovarian clear cell carcinoma (OCCC) cell lines were cultured under adherent and spheroid conditions. Immunoblotting confirmed on-target effects and modulation of autophagy. Autophagic flux was assessed using mCherry-eGFP-LC3 reporter assays. We assessed 96 dose combinations of MRT68921 and afatinib using drug combination matrices, with synergy evaluated via Synergy Finder. Promising combinations were evaluated across multiple EOC spheroid models and patient ascites-derived organoids. Results: MRT68921 inhibited ULK1 activity and reduced autophagic flux in a context-dependent manner while afatinib alone induced autophagy. Their combination produced synergistic effects at select concentrations, impairing spheroid reattachment and viability. However, MRT68921 alone significantly reduced viability across multiple EOC models, including patient ascites-derived organoids. Conclusions: This study is the first to evaluate the combined effects of MRT68921 and afatinib in epithelial ovarian cancer. Our findings demonstrate that ULK1 inhibition via MRT68921 consistently reduces cell viability across multiple ovarian cancer models, supporting ULK1 as a promising therapeutic target. In contrast, combination with afatinib produced limited and context-dependent effects, indicating that further investigation is needed to identify optimal combination strategies for ULK1-targeted therapies. Full article

Organoids are self-organizing multicellular structures generated in vitro that recapitulate the micro-architecture and function of an organ. They are commonly derived from stem cells but can also emerge from pieces of proliferative tissues. Organoid technology has opened novel ways to model development and disease, but it is not without challenges. Computational models of organoids have been established to elucidate organoid growth and facilitate the optimization of organoid cultures. This article is a systematic review of in silico organoid models constructed at single-cell or subcellular resolution. PubMed, Scopus, and Web of Science were searched for original papers published in peer-reviewed journals before 26 September 2025, yielding 439 records after deduplication. Two independent reviewers screened their titles and abstracts, retrieved 84 papers for full-text scrutiny, and identified 32 papers that met the inclusion criteria. They were grouped by organoid type: 12 intestinal, 1 airway, 2 pancreas, 3 neural, 1 kidney, 1 inner cell mass, 9 tumor, and 3 generic. The analysis of these works revealed that computer simulations guided experimental work. Parsimonious computational models provided insights into diverse organoid behaviors, such as the rotation of airway organoids, size oscillations of pancreatic organoids, epithelial patterning of neural tube organoids, or nephron segment formation in kidney organoids. Generally, a deep understanding was achieved through combined in silico and in vitro investigations (e.g., optic cup morphogenesis). Recent research trends suggest that next-generation computational models of organoids may emerge from a more detailed understanding of the complex regulatory circuits that govern stem cell fate, and machine-learning-based, high-throughput imaging of organoids. Full article

Long bone formation in vertebrates proceeds via endochondral ossification, a sequential process that begins with mesenchymal condensation, advances through cartilage anlage formation, and culminates in its replacement by mineralized bone. Recent advances in inducible lineage tracing and single-cell genomics have revealed that, rather than being a uniform event, mesenchymal condensation rapidly segregates into progenitor pools with distinct fates. Centrally located Sox9⁺/Fgfr3⁺ chondroprogenitors expand into the growth plate and metaphyseal stroma, peripheral Hes1⁺ boundary cells refine condensation via asymmetric division, and outer-layer Dlx5⁺ perichondrial cells generate the bone collar and cortical bone. Concurrently, dorsoventral polarity established by Wnt7a–Lmx1b and En1 ensures that dorsal progenitors retain positional identity throughout development. These lineage divergences integrate with signaling networks, including the Ihh–PTHrP, FGF, BMPs, and WNT/β-catenin networks, which impose temporal control over chondrocyte proliferation, hypertrophy, and vascular invasion. Perturbations in these programs, exemplified by mutations in Fgfr3, Sox9, and Dlx5, underlie region-specific skeletal dysplasias, such as achondroplasia, campomelic dysplasia, and split-hand/foot malformation, demonstrating the lasting impacts of embryonic patterning errors. Based on these insights, regenerative strategies are increasingly drawing upon developmental principles, with organoid cultures recapitulating ossification centers, biomimetic hydrogels engineered for spatiotemporal morphogen delivery, and stem cell- or exosome-based therapies harnessing developmental microRNA networks. By bridging developmental biology with biomaterials science, these approaches provide both a roadmap to unravel skeletal disorders and a blueprint for next-generation therapies to reconstruct functional bones with the precision of the embryonic blueprint. Full article

Neurodegenerative diseases (NDDs), including Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), are becoming more prevalent and still lack effective disease-modifying therapies (DMTs). However, translational efficiency remains critically low. For example, a ClinicalTrials.gov analysis of AD programs (2002–2012) estimated ~99.6% attrition, while PD programs (1999–2019) achieved an overall success rate of ~14.9%. In vitro platforms are assessed, ranging from immortalized neuronal lines and primary cultures to human-induced pluripotent stem cell (iPSC)-derived neurons/glia, neuron–glia co-cultures (including neuroinflammation paradigms), 3D spheroids, organoids, and blood–brain barrier (BBB)-on-chip systems. Complementary in vivo toxin, pharmacological, and genetic models are discussed for systems-level validation and central nervous system (CNS) exposure realism. The therapeutic synthesis focuses on AD, covering symptomatic drugs, anti-amyloid immunotherapies, tau-directed approaches, and repurposed drug classes that target metabolism, neuroinflammation, and network dysfunction. This review links experimental models to translational decision-making, focusing primarily on AD and providing a brief comparative context from other NDDs. It also covers emerging targeted protein degradation (PROTACs). Key priorities include neuroimmune/neurovascular human models, biomarker-anchored adaptive trials, mechanism-guided combination DMTs, and CNS PK/PD-driven development for brain-directed degraders. Full article

Hair loss disorders, particularly androgenetic alopecia (AGA), are common conditions that carry significant psychosocial impact. Current standard therapies, including minoxidil, finasteride, and hair transplantation, primarily slow progression or re-distribute existing follicles and do not regenerate lost follicular structures. In recent years, regenerative medicine has been associated with a gradual shift toward approaches that aim to restore follicular function and architecture. Stem cell-derived conditioned media and exosomes have shown the ability to activate Wnt/β-catenin signaling, enhance angiogenesis, modulate inflammation, and promote dermal papilla cell survival, resulting in improved hair density and shaft thickness with favorable safety profiles. Autologous cell-based therapies, including adipose-derived stem cells and dermal sheath cup cells, have demonstrated the potential to rescue miniaturized follicles, although durability and standardization remain challenges. Adjunctive interventions such as microneedling and platelet-rich plasma (PRP) further augment follicular regeneration by inducing controlled micro-injury and releasing growth and neurotrophic factors. In parallel, machine learning-based diagnostic tools and deep hair phenotyping offer improved severity scoring, treatment monitoring, and personalized therapeutic planning, while robotic Follicular Unit Excision (FUE) platforms enhance surgical precision and graft preservation. Advances in tissue engineering and 3D follicle organoid culture suggest progress toward producing transplantable follicle units, though large-scale clinical translation is still in early development. Collectively, these emerging biological and technological strategies indicate movement beyond symptomatic management toward more targeted, multimodal approaches. Future progress will depend on standardized protocols, regulatory clarity, and long-term clinical trials to define which regenerative approaches can reliably achieve sustainable follicle renewal in routine cosmetic dermatology practice. Full article

Patient-derived organoids (PDOs) have emerged as promising preclinical models for studying tumor biology and testing therapeutic strategies in oncology. These three-dimensional culture systems retain key histological, genetic, and functional characteristics of the original tumors, offering a unique opportunity to advance personalized medicine approaches in liver cancer. In this study, we present the methodological framework and preliminary findings of a prospective study aimed at generating and characterizing PDOs from patients with hepatocellular carcinoma (HCC) undergoing surgical resection. Tumor specimens were processed using an optimized protocol for organoid derivation, expansion, and cryopreservation. We evaluated the success rate of organoid establishment and the histo-molecular fidelity to the parental tumor. These early results demonstrate promising engraftment efficiency and maintenance of tumor-specific markers across passages. Our work highlights the potential of PDOs as a reliable and scalable platform for translational research in HCC, setting the stage for future applications in drug screening and biomarker discovery. Full article

The liver is the central organ in metabolism; however, modeling hepatic diseases remains limited by current experimental models. Animal models frequently fail to predict human liver physiology, while primary hepatocytes rapidly dedifferentiate in culture. We performed comprehensive transcriptomic profiling of induced pluripotent stem cells (iPSCs) differentiation into hepatocyte-like cells (HLCs) under two-dimensional (2D) and three-dimensional (3D) culture conditions. RNA sequencing analysis revealed the sequential activation of lineage-specific markers across major developmental stages: definitive endoderm (FOXA2, SOX17, CXCR4, CER1, GATA4), posterior foregut (PROX1, GATA6), and hepatoblasts (HNF4A, AFP). Comparative analysis demonstrated a markedly enhanced hepatic gene expression of 3D organoids, as demonstrated by a 33-fold increase in HNF4A expression and elevated levels of mature hepatocyte markers, including ALB, SERPINA1, and UGT2B15. However, the 3D cultures retained fetal characteristics (290-fold higher AFP expression) and exhibited significantly impaired metabolic function, with CYP3A4 expression levels reduced by 2000-fold compared to the adult human liver. This partial maturation was further supported by a moderate correlation with adult liver tissue (ρ = 0.57). We demonstrated high reproducibility across five biologically distinct iPSCs lines, including those derived from patients with rare monogenic disorders. The establishment of quantitative benchmarks provides a crucial tool for standardizing in vitro liver models. Furthermore, we delineate the specific limitations of the current model, highlighting the need for further protocol optimization to enhance metabolic maturation and P450 enzyme activity. Functional validation of metabolic activity (CYP enzyme assays, albumin secretion) was not performed; therefore, conclusions regarding hepatocyte functionality are based on transcriptomic evidence. Full article

The FDA plans to gradually replace animal testing with organoid and organ-on-a-chip technologies for drug safety assessment, driving surging demand for gut-on-a-chip in food and drug safety evaluation and highlighting the need for efficient, precise chip designs. Oxygen gradients are central to these devices because they shape epithelial metabolism, microbial co-culture, and overall gut homeostasis. We coupled machine learning with finite element analysis to build a parametric COMSOL Multiphysics model linking channel geometry, transport coefficients, and cellular oxygen uptake to the resulting oxygen field. For numerical prediction, three models—Random Forest (RF), XGBoost, and MLP—were employed, with XGBoost achieving the highest accuracy (RMSE = 1.68%). SHAP analysis revealed that medium flow rate (39.7%), external flux (26.9%), and cellular oxygen consumption rate (24.8%) contributed most importantly to the prediction. For oxygen distribution mapping, an innovative Boundary-Guided Generative Network (BG-Net) model was employed, yielding an average concentration error of 0.012 mol/m³ (~4.8%), PSNR of 33.71 dB, and SSIM of 0.9220, demonstrating excellent image quality. Ablation experiment verified the necessity of each architectural component of BG-Net. This pipeline offers quantitative, data-driven guidance for tuning oxygen gradients in gut-on-a-chip. Future work will explore extensions including real experimental data integration, real-time prediction, and multi-task scenarios. Full article

Background/Objectives: Interactions between colorectal tumours and their immune microenvironment critically influence disease progression and response to immunotherapy. However, most organoid systems fail to preserve the complex architecture and immune composition of the original tissue. Here, we applied the air–liquid interface (ALI) organoid model to paired tumour and perilesional colon tissues from colorectal cancer patients to evaluate its ability to retain immune and genetic features and to reproduce responses to chemotherapy and immune checkpoint blockade. Methods: Fresh human tumour and matched healthy colon tissues were processed to generate ALI organoids. Their histological organization, immune cell composition (including CD45⁺ subsets), and genomic profiles were compared with those of the parental tissues and with conventional Matrigel organoids, either alone or co-cultured with peripheral blood mononuclear cells (PBMCs). Organoids were exposed to 5-FU and nivolumab (anti–PD-1) to assess local immune modulation. Results: ALI organoids faithfully preserved the three-dimensional architecture, native immune infiltrates, and somatic mutational landscape of the source tissues. Importantly, upon PD-1 blockade with nivolumab, ALI organoids consistently exhibited a local expansion of regulatory T cells (Tregs), a phenomenon that could contribute to adaptive immune resistance. This response was not reproduced in PBMC–Matrigel co-culture systems, highlighting the importance of preserving endogenous tumour–immune interactions. Conclusions: Patient-derived ALI organoids represent a physiologically relevant platform that conserves key structural, immunological, and genomic hallmarks of colorectal cancer. By capturing clinically relevant immune remodeling events, such as Treg expansion following PD-1 blockade, this model provides a powerful tool for dissecting tumour–immune interactions. Full article

Microfluidic cell culture systems and organ-on-a-chip platforms provide powerful tools for modeling physiological processes, disease progression, and drug responses under controlled microenvironmental conditions. These technologies rely on diverse cell culture methodologies, including 2D and 3D culture formats, spheroids, scaffold-based systems, hydrogels, and organoid models, to recapitulate tissue-level functions and generate rich, multiparametric datasets through high-resolution imaging, integrated sensors, and biochemical assays. The heterogeneity and volume of these data introduce substantial challenges in pre-processing, feature extraction, multimodal integration, and biological interpretation. Artificial intelligence (AI), particularly machine learning and deep learning, offers solutions to these analytical bottlenecks by enabling automated phenotyping, predictive modeling, and real-time control of microfluidic environments. Recent advances also highlight the importance of technical frameworks such as dimensionality reduction, explainable feature selection, spectral pre-processing, lightweight on-chip inference models, and privacy-preserving approaches that support robust and deployable AI–microfluidic workflows. AI-enabled microfluidic and organ-on-a-chip systems now span a broad application spectrum, including cancer biology, drug screening, toxicity testing, microbial and environmental monitoring, pathogen detection, angiogenesis studies, nerve-on-a-chip models, and exosome-based diagnostics. These platforms also hold increasing potential for precision medicine, where AI can support individualized therapeutic prediction using patient-derived cells and organoids. As the field moves toward more interpretable and autonomous systems, explainable AI will be essential for ensuring transparency, regulatory acceptance, and biological insight. Recent AI-enabled applications in cancer modeling, drug screening, etc., highlight how deep learning can enable precise detection of phenotypic shifts, classify therapeutic responses with high accuracy, and support closed-loop regulation of microfluidic environments. These studies demonstrate that AI can transform microfluidic systems from static culture platforms into adaptive, data-driven experimental tools capable of enhancing assay reproducibility, accelerating drug discovery, and supporting personalized therapeutic decision-making. This narrative review synthesizes current progress, technical challenges, and future opportunities at the intersection of AI, microfluidic cell culture platforms, and advanced organ-on-a-chip systems, highlighting their emerging role in precision health and next-generation biomedical research. Full article

Human organoids are 3D cell culture models that precisely replicate the microenvironment of real organs. In organoid-based experiments, assessing whether the internal vasculature has formed normally is essential for ensuring the reliability of experimental results. However, conventional vasculature assessment relies on manual inspection by researchers, which is time-consuming and prone to variability caused by subjective judgment. This study proposes a lightweight deep learning model for automatic classification of normal and abnormal vasculature in vascular organoid images. The proposed model is based on EfficientNet by replacing the activation function SiLU with ReLU and removing the Squeeze-and-Excitation (SE) blocks to reduce computational complexity. The dataset consisted of vascular organoid images obtained from co-culture experiments. Data augmentation and noise addition were performed to alleviate class imbalance. Experimental results show that the proposed Modified 3 models (B0, B1, B2) achieved accuracy of 0.90, 0.99, and 1.00, respectively, with corresponding inference speed of 51.1, 36.0, and 32.4 FPS on the CPU, demonstrating real-time inference capability and an average speed improvement of 70% compared to the original models. This study presents an efficient automated analysis framework that enables quantitative and reproducible vasculature assessment by introducing a lightweight model that maintains high accuracy and supports real-time processing. Full article

The intestinal epithelium maintains tissue homeostasis through a dynamic balance of stem cell proliferation and differentiation. This process is spatially regulated along the crypt–villus axis, with intestinal stem cells in the crypt regions proliferating and progenitor cells differentiating as they migrate toward the villus tips. Because the lumen of the gut contains very low levels of oxygen (i.e., hypoxia), an oxygen gradient is established within the crypt–villus axis, placing the crypt regions under normoxic conditions while the villus tips reside under hypoxic conditions. Hence, intestinal epithelial cells encounter distinct oxygen microenvironments throughout their life span as they migrate along the crypt–villus structures during their proliferation and differentiation process. To investigate how oxygen availability influences intestinal stem cell proliferation and differentiation, we cultured patient-derived human ileum organoids (i.e., enteroids) under normoxic (20% oxygen) or hypoxic (1% oxygen) conditions. Under hypoxia, enteroid growth was reduced, and expression of several stem cell markers, such as OLFM4 and LGR5, was decreased. Bulk and single-cell RNA sequencing revealed that hypoxia suppressed Wnt signaling pathways and reduced stem cell activity. Importantly, pharmacological stabilization of HIF-1α under normoxic conditions recapitulated the hypoxia-induced loss of stemness, demonstrating that HIF-1α is a key mediator of oxygen-dependent stem cell regulation in enteroids. These findings establish that physiological hypoxia in the intestinal epithelium directly regulates stem cell fate through HIF-1α stabilization, providing mechanistic insight into how oxygen availability along the crypt–villus structures controls intestinal homeostasis. Full article

Temperature-responsive hydrogels are sophisticated stimuli-responsive biomaterials that undergo rapid, reversible sol–gel phase transitions in response to subtle thermal stimuli, most notably around physiological temperature. This inherent thermosensitivity enables non-invasive, precise spatiotemporal control of material properties and bioactive payload release, rendering them highly promising for advanced biomedical applications. This review critically surveys recent advances in the design, synthesis, and translational potential of thermo-responsive hydrogels, emphasizing nanoscale and hybrid architectures optimized for superior tunability and biological performance. Foundational systems remain dominated by poly(N-isopropylacrylamide) (PNIPAAm), which exhibits a sharp lower critical solution temperature near 32 °C, alongside Pluronic/Poloxamer triblock copolymers and thermosensitive cellulose derivatives. Contemporary developments increasingly exploit biohybrid and nanocomposite strategies that incorporate natural polymers such as chitosan, gelatin, or hyaluronic acid with synthetic thermo-responsive segments, yielding materials with markedly enhanced mechanical robustness, biocompatibility, and physiologically relevant transition behavior. Cross-linking methodologies—encompassing covalent chemical approaches, dynamic physical interactions, and radiation-induced polymerization are rigorously assessed for their effects on network topology, swelling/deswelling kinetics, pore structure, and degradation characteristics. Prominent applications include on-demand drug and gene delivery, injectable in situ gelling systems, three-dimensional matrices for cell encapsulation and organoid culture, tissue engineering scaffolds, self-healing wound dressings, and responsive biosensing platforms. The integration of multi-stimuli orthogonality, nanotechnology, and artificial intelligence-guided materials discovery is anticipated to deliver fully programmable, patient-specific hydrogels, establishing them as pivotal enabling technologies in precision and regenerative medicine. Full article

Extracellular vesicles (EVs) derived from stem cells have emerged as promising mediators of osteogenesis, suggesting cell-free alternatives for bone tissue engineering and regenerative medicine. This review provides a comprehensive analysis of the main stem cell sources used for EV production, including bone marrow mesenchymal stem cells (BM-MSCs), adipose-derived stem cells (ADSCs), umbilical cord MSCs (UC-MSCs), induced pluripotent stem cells (iPSCs), and alternative stromal populations. Particular attention is given to the ways in which different conditioning and differentiation strategies, such as osteogenic induction, hypoxia, and mechanical stimulation, modulate EV cargo composition and enhance their therapeutic potential. We further discuss the in vitro models employed to evaluate EV-mediated bone regeneration, ranging from 2D cultures to complex 3D spheroids, scaffold-based systems, and bone organoids. Overall, this review emphasizes the current challenges related to standardization, scalable production, and clinical translation. It also outlines future directions, including bioengineering approaches, advanced preclinical models, and the integration of multi-omics approaches and artificial intelligence to optimize EV-based therapies. By integrating current knowledge, this work aims to guide researchers toward more consistent and physiologically relevant strategies to harness EVs for effective bone regeneration. Finally, this work uniquely integrates a comparative analysis of EVs from multiple stem cell sources with engineering strategies and emerging clinical perspectives, thereby providing an updated and translational framework for their application in bone regeneration. Full article