Search Results (601)

Cystic fibrosis (CF) is caused by loss-of-function variants in the cystic fibrosis transmembrane conductance regulator (CFTR) chloride and bicarbonate channel and affects multiple organs, with pancreatic involvement showing very high penetrance. In pancreatic ducts, CFTR drives secretion of alkaline, bicarbonate-rich fluid that maintains intraductal patency, neutralises gastric acid and permits safe delivery of digestive enzymes. Selective impairment of CFTR-dependent bicarbonate transport, even in the presence of residual chloride conductance, is strongly associated with exocrine pancreatic insufficiency, recurrent pancreatitis and cystic-fibrosis-related diabetes. These clinical manifestations are captured by pharmacodynamic anchors such as faecal elastase-1, steatorrhoea, pancreatitis burden and glycaemic control, providing clinically meaningful benchmarks for CFTR-targeted therapies. In this review, we summarise the principal mechanisms underlying pancreatic pathophysiology and the current approaches to clinical management. We then examine in vitro pancreatic duct models that are used to evaluate small molecules and emerging therapeutics targeting CFTR. These experimental systems include native tissue, primary cultures, organoids, co-cultures and microfluidic devices, each of which has its own advantages and limitations. Intact micro-perfused ducts provide the physiological benchmark for studying luminal pH control and bicarbonate (HCO₃⁻) secretion. Primary pancreatic duct epithelial cells (PDECs) and pancreatic ductal organoids (PDO) preserve ductal identity, patient-specific genotype and key regulatory networks. Immortalised ductal cell lines grown on permeable supports enable scalable screening and structure activity analyses. Co-culture models and organ-on-chip devices incorporate inflammatory, stromal and endocrine components together with flow and shear and provide system-level readouts, including duct-islet communication. Across this complementary toolkit, we prioritise bicarbonate-relevant endpoints, including luminal and intracellular pH and direct measures of HCO₃⁻ flux, to improve alignment between in vitro pharmacology and clinical pancreatic outcomes. The systematic use of complementary models should facilitate the discovery of next-generation CFTR modulators and adjunctive strategies with the greatest potential to protect both exocrine and endocrine pancreatic function in people with CF. Full article

Amyotrophic lateral sclerosis (ALS) is the most common motor neuron disease, marked by progressive degeneration of upper and lower motor neurons. Clinically, genetically, and pathologically heterogeneous, ALS poses a major challenge for disease modeling and therapeutic translation. Over the past two decades, induced pluripotent stem cells (iPSCs) have reshaped our understanding of ALS pathogenesis and emerged as a promising translational platform for therapy development. ALS modeling has further expanded with the advent of three-dimensional systems, including ALS-on-chip platforms and organoid models, which better capture cell–cell interactions and tissue-level phenotypes. Despite these advances, effective disease-modifying therapies remain elusive. Recent clinical trial setbacks highlight the need for improved trial design alongside robust, translational iPSC models that can better predict therapeutic response. Nonetheless, the outlook is promising as large iPSC patient cohorts, quantitative phenotyping combined with genetically informed patient stratification, and reverse translational research are beginning to close the gap between in vitro discovery and clinical testing. In this review, we summarize the major advances in iPSC technology and highlight key iPSC-based studies of sporadic ALS. We further discuss emerging examples of iPSC-informed therapeutic strategies and outline the challenges associated with translating iPSC-derived mechanistic insights and pharmacological findings into successful clinical therapies. Full article

Regenerative medicine is increasingly leveraging the synergies between bioinspired conductive biomaterials and 3D/4D bioprinting to replicate the native electroactive and hierarchical microenvironments essential for functional tissue restoration. However, a critical gap remains in the intelligent integration of these technologies to achieve dynamic, responsive tissue regeneration. This review introduces a “bioinspired material–printing–function” triad framework to systematically synthesize recent advances in: (1) tunable conductive materials (polymers, carbon-based systems, metals, MXenes) designed to mimic the electrophysiological properties of native tissues; (2) advanced 3D/4D printing technologies (vat photopolymerization, extrusion, inkjet, and emerging modalities) enabling the fabrication of biomimetic architectures; and (3) functional applications in neural, cardiac, and musculoskeletal tissue engineering. We highlight how bioinspired conductive scaffolds enhance electrophysiological behaviors—emulating natural processes such as promoting axon regeneration cardiomyocyte synchronization, and osteogenic mineralization. Crucially, we identify multi-material 4D bioprinting as a transformative bioinspired approach to overcome conductivity–degradation trade-offs and enable shape-adaptive, smart scaffolds that dynamically respond to physiological cues, mirroring the adaptive nature of living tissues. This work provides the first roadmap toward intelligent electroactive regeneration, shifting the paradigm from static implants to dynamic, biomimetic bioelectronic microenvironments. Future translation will require leveraging AI-driven bioinspired design and organ-on-a-chip validation to address challenges in vascularization, biosafety, and clinical scalability. Full article

For more than a century, pathology has served as a cornerstone of modern medicine, relying primarily on static microscopic assessment of tissue morphology—such as H&E staining—which remains the “gold standard” for disease diagnosis. However, this conventional paradigm provides only a snapshot of disease states and often fails to capture their dynamic evolution and complex functional mechanisms. Moreover, animal models are constrained by marked interspecies differences, creating a persistent gap in translational research. To overcome these limitations, we propose the concept of New Pathophysiology, a research framework that transcends purely morphological descriptions and aims to resolve functional dynamics in real time. This approach integrates Organ-on-a-Chip (OOC) technology, multi-omics analyses, and artificial intelligence to reconstruct the entire course of disease initiation and to enable personalized medicine. In this review, we first outline the foundations and limitations of traditional pathology and animal models. We then systematically summarize more than one hundred existing OOC disease models across multiple organs—including the kidney, liver, and brain. Finally, we elaborate on how OOC technologies are reshaping the study of key pathological processes such as inflammation, metabolic dysregulation, and fibrosis by converting them into dynamic, mechanistic disease models, and we propose future perspectives in the field. This review adopts a relatively uncommon classification strategy based on pathological mechanisms (mechanism-based), rather than organ-based categorization, allowing readers to recognize shared principles underlying different diseases. Moreover, the focus of this work is not on emphasizing iteration or replacement of existing approaches, but on preserving past achievements from a historical perspective, with an emphasis on overcoming current limitations and enabling new advances. Full article

Many emerging and re-emerging infectious diseases have been observed over the last few decades around the globe due to population growth, international travel, environmental changes, and microbial adaptation and evolution, despite advances in the medical field. The spread of these diseases is related to complex interactions between pathogens and their hosts. Accordingly, this review summarises current knowledge on infection development and discusses methods used for detection and modeling. Recent studies have revealed the limitations of two-dimensional models and increasingly rely on 3D systems, including spheroids, organoids, and organ-on-a-chip systems, that offer more realistic tissue environments, allowing researchers to more effectively study host–pathogen interactions. Overall, the integration of complementary approaches and the development of 3D models are crucial for enhancing diagnosis, developing new therapeutic approaches, and strengthening control strategies of emerging outbreaks. Full article

Reliable models of the lung environment are important for research on inhalation products, drug delivery, and how aerosols interact with tissue. pH fluctuations frequently accompany real physiological processes in pulmonary environments, so monitoring pH changes in lung-on-a-chip devices is of considerable relevance. Presented here are flexible, miniaturized, inkjet-printed pH sensors that have been developed with the aim of integration into lung-on-a-chip systems. Different types of functional pH-sensitive materials were tested: hydrogen-selective plasticized PVC membranes and polyaniline (both electrodeposited and dropcast). Their deposition and performance were evaluated on different flexible conducting substrates, including screen-printed carbon electrodes (SPE) and inkjet-printed graphene electrodes (IJP-Gr). Finally, a biocompatible dropcast polyaniline-modified IJP was selected and paired with an inkjet-printed Ag/AgCl quasireference electrode. The printed potentiometric device showed Nernstian sensitivity (58.8 mV/pH) with good reproducibility, reversibility, and potential stability. The optimized system was integrated with a developed lung-on-a-chip model with an electrospun polycaprolactone membrane and alginate, simulating the alveolar barrier and the natural mucosal environment, respectively. The permeability of the system was studied by monitoring the pH changes upon the introduction of a 10 wt.% acetic acid aerosol. Overall, the presented approach shows that electrospun-hydrogel materials together with integrated microsensors can help create improved models for studying aerosol transport, diffusion, and chemically changing environments that are relevant for inhalation therapy and respiratory research. These results show that our system can combine mechanical behavior with chemical sensing in one platform, which may be useful for future development of lung-on-a-chip technologies. Full article

Microfluidics has emerged as a powerful enabling technology in plant science, offering unprecedented control over microscale environments for the cultivation, manipulation, and analysis of plant cells, tissues, and organs. This review provides a comprehensive overview of the development and application of microfluidic systems in plant physiology and development studies. We categorize the platforms based on their structural designs and biological targets—from single-cell trapping devices and droplet-based screening systems to organ-on-a-chip and root–microbe interaction modules. Key applications include live-cell imaging, real-time monitoring of stress responses, microenvironment simulation, and high-throughput phenotyping. Particular attention is given to microfluidic investigations of plant mechanobiology, chemotropism, and cell-to-cell communication, as well as their integration with biosensors, electrophysiological tools, and environmental control systems. We also examine current limitations related to material compatibility, device scalability, and biological complexity, and highlight emerging solutions such as modular design, interdisciplinary integration, and soil-on-a-chip systems. By addressing both fundamental research needs and practical agricultural challenges, microfluidic technologies offer a transformative path toward precision plant science and sustainable crop innovation. Full article

Microfluidic technologies have ushered in a new era in cardiac tissue engineering, providing more predictive in vitro models compared to two-dimensional culture studies. This review examines Organ-on-a-Chip (OoC) and Lab-on-a-Chip (LoC) platforms, with a specific focus on cardiovascular applications. OoCs, and particularly Heart-on-a-Chip systems, have advanced biomimicry to a higher level by recreating complex 3D cardiac microenvironments in vitro and dynamic fluid flow. These platforms employ induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), engineered extracellular matrices, and dynamic mechanical and electrical stimulation to reproduce the structural and functional features of myocardial tissue. LoCs have introduced miniaturization and integration of analytical functions into compact devices, enabling high-throughput screening, advanced diagnostics, and efficient pharmacological testing. They enable the investigation of pathophysiological mechanisms, the assessment of cardiotoxicity, and the development of precision medicine approaches. Furthermore, progress in multi-organ systems expands the potential of microfluidic technologies to simulate heart–liver, heart–kidney, and heart–tumor interactions, providing more comprehensive predictive models. However, challenges remain, including the immaturity of iPSC-derived cells, the lack of standardization, and scalability issues. In general, microfluidic platforms represent strategic tools for advancing cardiovascular research in translation and accelerating therapeutic innovation within precision medicine. Full article

Triple-negative breast cancer (TNBC) exhibits diverse histological and molecular characteristics. TNBC patients also have the poorest prognoses among those with various breast cancer subtypes, and no effective treatment strategy has been established for TNBC beyond non-specific chemotherapy. Recent studies have reported that the dysregulation of miRNAs is associated with tumor behavior, prognosis, and treatment responses in TNBC patients. Therefore, this study was conducted to identify miRNAs and key target proteins potentially associated with TNBC prognosis. Fresh-frozen tissue from relapsing and non-relapsing TNBC cases was examined for differentially expressed miRNAs using the Affymetrix GeneChip miRNA 4.0 array, while target genes and proteins were predicted using the miRwalk 2.0 database. The clinical significance of each differentially expressed miRNA was evaluated using the BreastMark database. Additional bioinformatics analyses were conducted to reveal associations with tumor-related signaling pathways; these analyses included protein–protein interaction network construction and Kyoto Encyclopedia of Genes and Genomes pathway annotation. Gene chip analysis identified three upregulated miRNAs (miR-500a, miR-501-3p, and miR-502-3p) and two downregulated miRNAs (miR-6798-5p and miR-7150) in patients with recurrence, and further bioinformatics analyses revealed that target proteins were significantly associated with cell cycle pathways. In addition, low expression of the miR-500a target protein UBE2Z was significantly associated with a poor prognosis. The expression levels of miR-500a and UBE2Z might be useful prognostic biomarkers in TNBC. Full article

Three-dimensional (3D) bioprinting is a rapidly evolving technology that uses complementary biomaterials to emulate native extracellular matrices, enabling the generation of finely patterned, multicellular tissue architectures. Autoimmune diseases (AD), which are characterized by chronic, often organ-specific, immune response, are ideally suited to these in vitro models. This review summarizes the current state of 3D bioprinting for modelling AD, focusing on rheumatoid arthritis (RA), type 1 diabetes (T1D) and inflammatory bowel disease (IBD), as well as applications to systemic lupus erythematosus (SLE), neuroinflammatory conditions such as multiple sclerosis (MS) and other AD. Bioprinting modalities, advances in immune competent bioinks, strategies for vascularization and approaches to the hybridization of printed tissues with organoids and organ-on-chip systems are reviewed. From a clinical perspective, this review focuses on applications with translational potential, including immune-competent models derived from patients for biomarker discovery, drug screening and treatment response prediction. The key challenges, notably the reconstitution of full immune complexity, stable and perfusable vasculature, and maintenance of long-term viability and function are highlighted. Finally, future directions are defined to enhance the clinical utility and impact of 3D bioprinting across preclinical development and precision medicine. Full article

Background/Objectives: Parkinson’s disease (PD) is an adult-onset neurodegenerative disorder whose pathogenesis is still not completely understood. Several lines of evidence suggest that alterations in epigenetic architecture may contribute to the development of this condition. Here, we present a pilot DNA methylation study from peripheral blood in a cohort of Sicilian PD patients and matched controls. Peripheral tissue analysis has previously been shown to reflect molecular and functional profiles relevant to neurological diseases, supporting their validity as a proxy for studying brain-related epigenetic mechanisms. Methods: We analyzed 20 PD patients and 20 healthy controls (19 males and 21 females overall), matched for sex, with an age range of 60–87 years (mean 72.3 years). Peripheral blood DNA was extracted and processed using the Illumina Infinium MethylationEPIC v2.0 BeadChip, which interrogates over 935,000 CpG sites across the genome, including promoters, enhancers, CpG islands, and other regulatory elements. The assay relies on sodium bisulfite conversion of DNA to detect methylation status at single-base resolution. Results: Epigenome-wide association study (EWAS) data allowed for multiple levels of analysis, including immune cell-type deconvolution, estimation of biological age (epigenetic clocks), quantification of stochastic epigenetic mutations (SEMs) as a measure of epigenomic stability, and differential methylation profiling. Immune cell-type inference revealed an increased but not significant proportion of monocytes in PD patients, consistent with previous reports. In contrast, epigenetic clock analysis did not reveal significant differences in biological age acceleration between cases and controls, partially at odds with earlier studies—likely due to the limited sample size. SEMs burden did not differ significantly between groups. Epivariations reveal genes involved in pathways known to be altered in dopaminergic neuron dysfunction and α-synuclein toxicity. Differential methylation analysis, however, yielded 167 CpG sites, of which 55 were located within genes, corresponding to 54 unique loci. Gene Ontology enrichment analysis highlighted significant overrepresentation of pathways with neurological relevance, including regulation of synapse structure and activity, axonogenesis, neuron migration, and synapse organization. Notably, alterations in KIAA0319, a gene involved in neuronal migration, synaptic formation, and cortical development, have previously been associated with Parkinson’s disease at the gene expression level, while methylation changes in FAM50B have been reported in neurotoxic and cognitive contexts; our data suggest, for the first time, a potential epigenetic involvement of both genes in Parkinson’s disease. Conclusions: This pilot study on a Sicilian population provides further evidence that DNA methylation profiling can yield valuable molecular insights into PD. Despite the small sample size, our results confirm previously reported findings and highlight biological pathways relevant to neuronal structure and function that may contribute to disease pathogenesis. These data support the potential of epigenetic profiling of peripheral blood as a tool to advance the understanding of PD and generate hypotheses for future large-scale studies. 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

Organ-on-a-chip (OoC) or tissue-on-a-chip (ToC) technologies represent a significant advancement in enabling modeling of human organ and tissue physiology for medical study, although further development is required for these technologies to reach widespread adoption. OoC/ToC are three-dimensional (3D) microfluidic platforms that overcome limitations of traditional two-dimensional (2D) cell culture or animal models, providing an alternative environment for disease study, drug interactions, and tissue regeneration. The design of these systems is complex, requiring advanced fabrication techniques and careful selection of biomaterials with consideration of material toxicity, optical clarity, stability, and flexibility. A key innovation in this field is the multi-organ-on-a-chip (MOC) technology, which links multiple organ systems on a single platform. This enables the study of systemic diseases and the complex communication between organs, which is not possible with single-organ models. Furthermore, OoC/ToC technology holds immense potential for personalized medicine. By using patient-specific cells, these devices can create disease models that reflect an individual’s unique genetic and phenotypic variations, paving the way for tailored therapeutic interventions. The integration of real-time sensors within these devices also facilitates high-throughput screening and accelerates drug discovery. While the development and optimization of these systems is still in its early stages, OoC/ToC technologies have already demonstrated promise in a number of translational research applications. Full article

Celiac disease (CeD) is a chronic, immune-mediated enteropathy triggered by dietary gluten in genetically susceptible individuals, with environmental and epigenetic factors also contributing to its pathogenesis. Once considered a rare pediatric malabsorptive disorder, CeD is now recognized as a systemic condition that can manifest with both gastrointestinal and extraintestinal symptoms across the lifespan. Although strict adherence to a gluten-free diet (GFD) remains the cornerstone of treatment, up to 30–40% of patients experience persistent symptoms and/or ongoing mucosal injury despite reported compliance. This therapeutic gap, combined with advances in molecular understanding of disease mechanisms, has driven the development of novel strategies targeting key pathogenic pathways. Intraluminal interventions include gluten-degrading enzymes and gluten-sequestering agents, while other approaches target tissue transglutaminase 2, induce antigen-specific immune tolerance, or modulate cytokine-driven inflammation, with particular emphasis on interleukin-15 (IL-15) signaling. Additional strategies aim to inhibit lymphocyte trafficking to the intestinal mucosa and enhance intestinal barrier function through zonulin modulation. Adjunctive therapies under investigation include nutraceuticals, microbiota-targeted interventions, and vaccine-based approaches. More recently, advanced experimental and computational platforms, such as human intestinal organoids, organ-on-chip systems, and machine learning–driven analytics, are being leveraged in efforts to accelerate translational research and support the rational design of precision medicine approaches. This narrative review synthesizes current evidence for therapies beyond the GFD, examines challenges in clinical implementation, and discusses how technological innovations may reshape the future therapeutic landscape of CeD. Full article

Candida biofilms play a critical role in clinical settings, contributing to persistent and device-associated infections and conferring resistance to antifungal agents, particularly in immunocompromised or hospitalized patients. Biofilm formation varies among Candida species, including C. albicans and non-albicans species, such as C. glabrata, C. tropicalis, C. parapsilosis, and C. auris, due to species-specific transcriptional networks that regulate modes of biofilm development, extracellular matrix composition, and metabolic reprogramming. These differences influence biofilm responses to treatment and the severity of infections, which can be further complicated in polymicrobial biofilms that modulate colonization and virulence. Understanding the mechanisms driving biofilm formation and interspecies interactions is essential for developing effective therapies and requires appropriate experimental models. Available models range from simplified in vitro systems to more complex ex vivo and in vivo approaches. Static in vitro models remain widely used due to their simplicity and reproducibility, but they poorly mimic physiological conditions and require careful standardization. Ex vivo tissue models offer a balance between practicality and biological relevance, enabling the study of biofilm physiology, host–microbe interactions and immune responses. In vivo models, primarily in mice, remain the gold standard for testing antifungal therapies, while alternative systems such as Galleria mellonella larvae provide simpler, cost-effective approaches. Advanced in vitro platforms, including organ-on-chip systems, bridge the gap between simplified tests and physiological relevance by simulating fluid dynamics, tissue architecture, and immune complexity. This review aims to examine Candida biofilms across species, highlighting differences in structural diversity and clinical implications, and to provide a guide to the most widely used experimental models supporting studies on Candida biofilm biology for the development of new therapeutic targets or drug testing. Full article