Search Results (60)

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

Background/Objectives: Cardiotoxicity remains a leading cause of drug withdrawal. Conventional preclinical models, such as two-dimensional (2D) cell cultures and animal studies, often fail to accurately predict human cardiac responses. While 2D cultures lack the complex architecture and dynamic functionality of native myocardium, interspecies differences limit the translational relevance of animal models. The objective of this study was to develop a human-relevant, in vitro platform that enables predictive and functional assessment of drug-induced cardiotoxicity. Methods: Here, we present a high-throughput in vitro platform for cardiotoxicity screening using three-dimensional (3D) cardiac tissues derived from human induced pluripotent stem cells (hiPSCs) within a thermoresponsive extracellular matrix-derived hydrogel. The hydrogel enables homogeneous encapsulation, differentiation in 3D, and long-term assembly into a functional cardiac tissue. Maturation was validated by immunostaining for cardiac-specific markers, and calcium imaging was employed to monitor electrical signal propagation. Contractile performance, defined by beat rate and contraction amplitude, was quantified using video-based motion analysis. The platform was applied to evaluate the dose-dependent effects of various cardioactive compounds, including β-adrenergic agonists ((-) epinephrine and dopamine), a cardiotoxic chemotherapeutic (doxorubicin), a sinus node inhibitor (ivabradine), a calcium channel blocker (verapamil), and a β-adrenergic antagonist (metoprolol). Results: The engineered cardiac tissues exhibited functional maturation and stable contractile behavior. Drug testing demonstrated compound-specific, dose-dependent functional responses. For each compound, the system faithfully reproduced the expected physiological responses. Conclusions: This human-relevant, scalable platform enables sensitive, multiparametric functional assessment of cardiac tissues, offering a cost-effective and predictive tool for preclinical drug safety testing. By bridging the gap between in vitro assays and human physiology, it holds promise to enhance translational accuracy while reducing reliance on animal models. Full article

Cytotoxicity testing remains a cornerstone of modern toxicology, providing critical insight into how chemicals and drugs affect cell viability and function. Classical colorimetric assays such as MTT, LDH release, and neutral red uptake established the methodological basis of in vitro toxicology and continue to serve as regulatory benchmarks. However, their limited mechanistic depth and physiological relevance have prompted the field to evolve towards more predictive and human-centred approaches. Recent advances in high-content imaging, flow cytometry, and real-time impedance analysis have transformed cytotoxicity testing into a multiparametric discipline capable of detecting adaptive and sub-lethal cellular responses. Parallel progress in computational toxicology has introduced in silico models—QSAR, machine learning, and physiologically based pharmacokinetic (PBPK) modelling—that enable quantitative in vitro–in vivo extrapolation (QIVIVE). The integration of these computational tools with 3D organoids, organ-on-chip systems, and stem cell-based models allows for cross-validation between predictive simulations and experimental evidence, enhancing mechanistic interpretation and translational accuracy. Together, these developments underpin New Approach Methodologies (NAMs) and Integrated Approaches to Testing and Assessment (IATA), marking the transition from descriptive assays to predictive, mechanism-anchored frameworks that bridge in silico prediction with in vitro and in vivo validation—advancing both biomedical research and regulatory toxicology. Full article

Background and Objectives: Surfactant protein-D (SP-D) enters the circulation when the alveolo-capillary barrier is injured. We synthesised evidence on the diagnostic and prognostic performance of circulating SP-D in children with acute infectious lung disease. Methods: We searched MEDLINE, Embase and Scopus (inception–1 June 2025) for human studies reporting serum/plasma SP-D in patients <18 years with community-acquired pneumonia (CAP), viral pneumonitis or paediatric ARDS (PARDS). Two reviewers independently screened, extracted data and assessed risk of bias (ROBINS-I). Primary outcomes were discrimination of severe versus non-severe disease and prediction of hard outcomes (mechanical ventilation, PARDS and mortality). Heterogeneity in assays and outcome definitions precluded meta-analysis; a narrative synthesis was undertaken. Results: Five studies (n = 723) from emergency and PICU settings met inclusion criteria. Admission SP-D was consistently higher in severe versus mild CAP; reported AUCs ranged 0.699–0.802. Thresholds of 110–180 ng/mL yielded sensitivities of 67–85% and specificities of 45–70%. In influenza-associated respiratory failure, SP-D correlated with ventilator days (r ≈ 0.45) and ICU length of stay (r ≈ 0.44). In multicentre PARDS cohorts, each 10 ng/mL increase in SP-D was associated with higher odds of severe PARDS and death (adjusted OR 1.02 per 10 ng/mL). Overall risk of bias across studies was low-to-moderate, with one study rated serious due to sampling and adjustment limitations. Conclusions: Across pathogens and care settings, elevated circulating SP-D correlates with radiographic consolidation, evolving PARDS and worse short-term outcomes. Although assay standardisation and external validation are needed, current evidence supports incorporating SP-D into multiparametric, age-aware risk-stratification algorithms for childhood pneumonia and viral lung injury. Full article

Human microglia are central regulators and actors in brain infections and neuro-inflammatory pathologies. However, access to such cells is limited, and studies systematically mapping the spectrum of their inflammatory states are scarce. Here, we generated microglia-like cells (MGLCs) from human induced pluripotent stem cells and characterized them as a robust, accessible model system for studying inflammatory activation. We validated lineage identity through transcriptome profiling, revealing selective upregulation of microglial signature genes and enrichment of microglia/macrophage-related gene sets. MGLCs displayed distinct morphologies and produced stimulus- and time-dependent cytokine secretion profiles upon exposure to diverse inflammatory stimuli, including pro-inflammatory cytokines (TNFα, interferon-γ) and agonists of the Toll-like receptors TLR2 (FSL-1), TLR3 (Poly(I:C)), TLR4 (lipopolysaccharide, LPS), and TLR7 (imiquimod). Transcriptome profiling and bioinformatics analysis revealed distinct activation signatures. Functional assays demonstrated stimulus-specific engagement of NFκB and JAK-STAT signaling pathways. The shared NFκB nuclear translocation response of TLR ligands and TNFα was reflected in overlapping transcriptome profiles: they shared modules (e.g., oxidative stress response and TNFα-related signaling) identified by weighted gene co-expression network analysis. Finally, the potential consequences of microglia activation for neighboring cells were studied on the example of microglia-astrocyte crosstalk. The capacity of MGLC supernatants to stimulate astrocytes was measured by quantifying astrocytic NFκB translocation. MGLCs stimulated with FSL-1, LPS, or Poly(I:C) indirectly activated astrocytes via a strictly TNFα-dependent mechanism, highlighting the role of soluble mediators in the signal propagation. Altogether, this platform enables a dissection of microglia activation states and multi-parametric characterization of subsequent neuroinflammation. Full article

Background/Objectives: Ovarian adnexal masses present diagnostic challenges due to their heterogeneous etiologies. Accurately differentiating these conditions is critical for timely and effective clinical intervention. This study evaluated circulating molecules and serum-induced apoptosis as complementary tools to conventional diagnostic methods (CA125, HE4, and the ROMA index) for distinguishing benign masses from malignant masses. Methods: A cohort of 136 participants (9 healthy controls, 87 women with benign ovarian adnexal masses and 40 with malignant ovarian adnexal masses) was analyzed. The induction of apoptosis in Jurkat cells by patient serum was assessed using flow cytometry. Serum concentrations of sFas/CD95, HE4, CA125, and additional molecules were measured by ELISA and LEGENDplex™. Clinical, ultrasonographic, and histopathological data were correlated with tumor malignancy. To improve diagnostic performance beyond individual biomarkers, we developed two multiparametric classifiers that integrate the dominant parameters identified through group divergence analysis and ROC evaluation across multiple clinical comparisons. Results: Malignant tumors were associated with older age (51.45 ± 8.35 years, p = 0.0002), postmenopausal status (61.1%, p = 0.0013), and larger tumor size (>10 cm). Ultrasonographic features of complexity were observed exclusively in malignant masses. Functional assays revealed reduced apoptosis in Jurkat cells exposed to malignant sera, suggesting tumor-mediated immune evasion. Although higher sFas levels were observed in tumors, no significant differences were identified between the groups. Among the circulating biomarkers, CA125, HE4, MRP8/14, OPN, and SAA levels were significantly higher in malignant tumors than in benign tumors and controls. Conclusions: The evaluation of CA125, HE4, MRP8/14, and apoptosis (Classifier 1) and, more prominently, the measurement of additional molecules: OPN, SAA, IL-6, IL-8, and IGFBP-4 (Classifier 2), systematically outperformed the ROMA. Both achieved superior specificity and balanced accuracy (Youden’s J index) across all clinical comparisons by capturing the biological diversity of malignancies. Full article

Triple-negative breast cancers (TNBC) lack estrogen, progesterone, and express little, if any, HER2 receptors on their surface. No targeted therapies exist for this aggressive form of breast cancer. A library of enriched fractions from marine organisms was screened in a multi-parametric cytotoxicity assay using MDA-MB-231 and MDA-MB-468 TNBC cells, grown as spheroids (3D cultures). Spheroids better resemble tumors and are considered more clinically predictive. The assay measures apoptosis via the cleavage of caspase 3/7, viability via DNA content, and loss of membrane integrity via 7AAD staining at 24 h of treatment. Fractions were also tested in a traditional 2D MTT assay at 72 h. A fraction from the sponge Aplysina was active in the 3D assay. Aplysinamisine I was identified as the compound responsible for the activity. Aplysinamisine I induces apoptosis in MDA-MB-268 spheroids with an IC₅₀ of 2.9 ± 0.28 µM at 24 h. This novel activity is the most potent for the compound to date. Its IC₅₀ in the MTT assay at 72 h is >80 µM. Striking synergy with Taxol™ is shown in both cell lines. Proteomic analysis led to a differential protein expression profile. Through bioinformatics, this profile led to the hypothesis that the inhibition of nucleophosmin is the potential mode of action of the compound. However, initial studies show only a modest decrease in nucleophosmin expression in spheroids treated with aplysinamisine I. Full article

Background: Hypoxia is a hallmark of solid tumors, including hepatocellular carcinoma (HCC), where it drives oxidative stress and extracellular matrix (ECM) remodeling, promoting tumor invasion and metastasis. Investigating these mechanisms in patients remains challenging due to the complexity of the tumor microenvironment. Methods: We developed a scaffold-free three-dimensional (3D) spheroid model of HCC using human hepatocellular carcinoma HepG2 cells (ATCC HB-8065). To characterize hypoxia-driven processes, a multiparametric approach combining MTT assays for metabolic activity, confocal microscopy for viability and ECM organization, flow cytometry for apoptosis and ROS detection, qRT-PCR for gene expression, and FTIR spectroscopy for biochemical profiling were performed. Results: The 3D model exhibited progressive ROS accumulation, stabilization of HIF-1α, and metabolic reprogramming toward aerobic glycolysis. In parallel, ECM remodeling was evident, with increased expression of SPARC and FN1 and collagen fiber alignment, reflecting an invasive tumor phenotype. Conclusions: This scaffold-free 3D HCC model recapitulates key physiopathological features of tumor progression, providing a robust and physiologically relevant platform to investigate the hypoxia–ROS–ECM relationship and to support preclinical evaluation of targeted therapeutic strategies. Full article

The development of bioactive glasses (BGs) and ceramics, such as β-Tricalcium phosphate (β-TCP), Hydroxyapatite (HAp), and apatite-wollastonite (A-W), has revolutionized regenerative medicine (RM), offering innovative solutions for bone and tissue repair, due to the ability of these materials to bond with living bone tissue. Despite significant advancements, evaluating the bioactivity and biological responsiveness of these biomaterials remains a critical challenge. This review provides a comprehensive synthesis of the available methodologies, critically analyzing their advantages, disadvantages, and the possible gap between in vitro and in vivo assessments, including false positives and false negatives. Classical immersion tests techniques for bioactivity evaluation in simulated physiological solutions, such as simulated body fluid (SBF), Tris-buffer (TRIS), or phosphate-buffered saline (PBS) solutions, are discussed, along with the more innovative Simulated Wound Fluid (SWF). Additionally, traditional standardized methods, such as MTT, BrdU, EdU, and XTT, as well as emerging methods like qPCR and immunocytochemistry, used to study cellular behavior, proliferation, adhesion, and differentiation, are compared. Staining assays, including crystal violet, neutral red, and alizarin red, have also been investigated for their effectiveness in evaluating cellular adhesion and quantification. Notably, while all techniques have shown promise in studies involving BGs and ceramics, a multi-parametric approach remains the most reliable strategy for assessing bioactivity and biological responsiveness, highlighting the need for comprehensive studies to validate the results. Finally, the choice between static and dynamic approaches represents a further critical issue, as it significantly affects assay outcomes. Full article

Cellular senescence is a fundamental hallmark of aging, contributing to tissue dysfunction and chronic disease through the senescence-associated secretory phenotype (SASP). The SASP encompasses a diverse and dynamic collection of secreted cytokines, chemokines, growth factors, and proteases that vary depending on cell type, senescence trigger, and microenvironmental context. Accurate quantification of SASP components is critical to understanding the mechanisms linking senescence to pathology and for advancing senotherapeutic strategies. However, measuring the SASP presents significant technical and biological challenges due to its complexity, heterogeneity, and context dependence. This review provides a comprehensive overview of the principal methodologies used to measure SASP components across different biological levels—transcriptional, translational, and functional—and sample types, including cell cultures, tissues, and systemic fluids. We discuss the advantages and limitations of widely used RNA-level techniques (e.g., qRT-PCR, RNA sequencing, in situ hybridization), protein-level assays (e.g., ELISA, Western blotting, mass spectrometry, Luminex, MSD), and spatial detection methods (e.g., immunohistochemistry, immunofluorescence). By organizing current SASP detection strategies by molecular level and sample source, this review highlights the importance of multiparametric approaches to capture the full spectrum of senescent cell activity. We also identify key methodological gaps and propose directions for refining SASP biomarker discovery in aging and disease research. Full article

Prostate-specific antigen (PSA) has been the primary biomarker used for the detection and monitoring of prostate cancer for decades. However, its limited specificity and prognostic accuracy have led to the development of novel molecular and imaging biomarkers aimed at improving the clinical characterization of localized disease. This review critically examines recent advances in urinary biomarkers (e.g., PCA3, SelectMDx), tissue-based genomic assays (Oncotype DX Prostate, Prolaris, Decipher), and imaging techniques such as multiparametric magnetic resonance imaging (mpMRI) and prostate-specific membrane antigen positron emission tomography (PET-PSMA). We evaluate their diagnostic performance, prognostic value, and clinical utility in risk stratification and individualized treatment decision-making. Methodological and clinical barriers to their routine implementation are also discussed. Current evidence supports the multidisciplinary integration of these biomarkers to overcome the limitations of PSA, improve biopsy decision-making, better distinguish indolent from aggressive tumors, and optimize therapeutic strategies. Finally, future research directions aimed at validating and incorporating emerging biomarkers into clinical practice are outlined, with the goal of improving outcomes in patients with localized prostate cancer. Full article

Human cytomegalovirus (HCMV) establishes lifelong latency in the host, with the bone marrow (BM) CD34+ cells serving as a key reservoir. To investigate tissue-specific immune responses to CMV, we analysed paired peripheral blood mononuclear cells (PBMCs) and bone marrow mononuclear cells (BMMNCs) from HCMV-seropositive donors using multiparametric flow cytometry and cytokine FluroSpot assays. We assessed immune cell composition, memory T cell subsets, cytokine production, cytotoxic potential, activation marker expression, and checkpoint inhibitory receptor (CIR) profiles, both ex vivo and following stimulation with lytic and latent HCMV antigens. BMMNCs were enriched in CD34+ progenitor cells and exhibited distinct T cell memory subset distributions. HCMV-specific responses were compartmentalised: IFN-γ responses predominated in PBMCs following lytic antigen stimulation, while IL-10 and TNF-α responses were more prominent in BMMNCs, particularly in response to latent antigens. US28-specific T cells in the BM showed elevated expression of CD39, PD-1, BTLA, CTLA-4, ICOS, and LAG-3 on CD4+ T cells and increased expression of PD-1, CD39, BTLA, TIGIT, LAG-3, and ICOS on CD8+ T cell populations, suggesting a more immunoregulatory phenotype. These findings highlight functional and phenotypic differences in HCMV-specific T cell responses between blood and bone marrow, underscoring the role of the BM niche in shaping antiviral immunity and maintaining viral latency. Full article

Flow cytometry use has significantly increased in clinical laboratories and has significantly helped improve the diagnosis of leukemias, lymphomas, and follow-up of minimal residual disease. Mastering this technique enables the performance of multiparametric single-cell analysis and increases the odds of identifying abnormal populations. As in many fields, there is a need to improve the quality of the data generated for accuracy, reproducibility, and trueness. The implementation of solutions reducing variability is achievable and needed, as the flow cytometry workflow involves many manual steps and items susceptible to operator bias and human error. Standardization of flow cytometry assays is sought and already implemented in many clinical hematology laboratories. However, the clinical community would highly benefit from further efforts in that direction to increase the comparability of findings across laboratories. This review covers the strengths and weaknesses of flow cytometry and focuses on the standardization approaches developed, including recent advances in the field. Full article

Background: Glioblastoma (GBM) resists current therapies due to its rapid proliferation, diffuse invasion, and heterogeneous cell populations. We previously showed that a single cold atmospheric plasma discharge tube (DT) reduces GBM viability via broad-spectrum electromagnetic (EM) emissions. Here, we tested whether two DTs arranged in a helmet configuration could generate overlapping EM fields to amplify the anti-tumor effects without thermal injury. Methods: The physical outputs of the single- and dual-DT setups were characterized by infrared thermography, broadband EM field probes, and oscilloscope analysis. Human U87-MG cells were exposed under the single or dual configurations. The viability was quantified with WST-8 assays mapped across 96-well plates; the intracellular reactive oxygen species (ROS), membrane integrity, apoptosis, and mitochondrial potential were assessed by multiparametric flow cytometry. Our additivity models compared the predicted versus observed dual-DT cytotoxicity. Results: The dual-DT operation produced constructive EM interference, elevating electric and magnetic field amplitudes over a broader area than either tube alone, while temperatures remained <39 °C. The single-DT exposure lowered the cell viability by ~40%; the dual-DT treatment reduced the viability by ~60%, exceeding the additive predictions. The regions of greatest cytotoxicity co-localized with the zones of highest EM field overlap. The dual-DT exposure doubled the intracellular ROS compared with single-DT and Annexin V positivity, confirming oxidative stress-driven cell death. The out-of-phase operation of the discharge tubes enabled the localized control of the treatment regions, which can guide future treatment planning. Conclusions: Two synchronously operated plasma discharge tubes synergistically enhanced GBM cell killing through non-thermal mechanisms that coupled intensified overlapping EM fields with elevated oxidative stress. This positions modular multi-DT arrays as a potential non-invasive adjunct or alternative to existing electric-field-based therapies for glioblastoma. Full article

Background/Objectives: This study aims to develop and evaluate neutrophil-membrane-coated nanoparticles (Siv@NMs) encapsulating sivelestat for the treatment of sepsis-induced endothelial injury. Leveraging the intrinsic chemotactic properties of neutrophil membranes, Siv@NMs are engineered to achieve site-specific delivery of sivelestat to damaged endothelia, thereby overcoming the limitations of conventional therapies in mitigating endothelial dysfunction and multiorgan failure associated with sepsis. Methods: Siv@NMs were synthesized through a combination of ultrasonication and extrusion techniques to encapsulate sivelestat within neutrophil-membrane-derived vesicles. Comprehensive physicochemical characterization included analysis of particle size distribution, zeta potential, and encapsulation efficiency. Stability profiles and controlled release kinetics were systematically evaluated under simulated conditions. In vitro investigations encompassed (1) endothelial cell biocompatibility assessment via cytotoxicity assays, (2) investigation of the targeting efficiency in suppressing endothelial neutrophil extracellular trap generation during inflammation, and (3) ROS-scavenging capacity quantification using flow cytometry with DCFH-DA fluorescent probes. In vivo therapeutic efficacy was validated using a cecal ligation and puncture (CLP) sepsis mouse model, with multiparametric monitoring of endothelial function, inflammatory markers, ROS levels, and survival outcomes. Results: The optimized Siv@NMs exhibited an average particle size of approximately 150 nm, and a zeta potential of −10 mV was achieved. Cellular studies revealed that (1) Siv@NMs selectively bound to inflammatory endothelial cells with minimal cytotoxicity, and (2) Siv@NMs significantly reduced ROS accumulation in endothelial cells subjected to septic stimuli. In vitro experiments demonstrated that Siv@NMs treatment markedly attenuated endothelial injury biomarkers’ expression (ICAM-1 and iNOS), suppressed formation of neutrophil extracellular traps, and improved survival rates compared to treatment with free sivelestat. Conclusions: The neutrophil-membrane-coated nanoparticles loaded with sivelestat present a breakthrough strategy for precision therapy of sepsis-associated endothelial injury. This bioengineered system synergistically combines targeted drug delivery with multimodal therapeutic effects, including ROS mitigation, anti-inflammatory action, and endothelial protection. These findings substantiate the clinical translation potential of Siv@NMs as a next-generation nanotherapeutic for sepsis management. Full article