Search Results (1,399)

In vitro neurovascular unit (NVU) models are essential for reproducing blood–brain barrier (BBB) transport and neurovascular cell interactions. However, the literature remains fragmented: biomaterial chemistry, fabrication parameters and organ-on-a-chip architecture are commonly evaluated in isolation, while inconsistent reporting of matrix properties, processing history, cell source, flow and barrier readouts prevents head-to-head comparison and the extraction of transferable design rules. To address this gap, this review integrates biomaterials, manufacturing technologies and organ-on-a-chip engineering within a unified material–process–structure–function framework. We translate endothelial junctions, basement-membrane components and perivascular cells into experimentally actionable material requirements; compare natural, synthetic, semisynthetic and decellularized extracellular-matrix hydrogels; and examine crosslinking, peptide functionalization, stimuli responsiveness, composite-network formation and preparation methods. Findings from Transwell, microfluidic, tubular, self-assembled and 3D-bioprinted BBB systems are used to relate matrix stiffness, degradability, ligand density, permeability, device-body material and fabrication route to barrier maturation, analytical access and reproducibility. By defining matched controls and minimum reporting requirements for chemistry, mechanics, transport and processing, this review provides a practical basis for next-generation BBB models that can improve permeability and efficacy screening in drug discovery, reproduce disease- and patient-specific barrier dysfunction, and support individualized response testing with iPSC- or patient-derived cells. Full article

Sulfathiazole (STH) pollution has been increasing, with a strong need for a sensitive and selective analysis method. In this paper, a three-component fluorescent sensing platform with Mn²⁺-doped ZnS quantum dots in a metal–organic framework coated with a surface molecularly imprinted polymer (Mn-ZnS-MOF-MIP) for selective sensing of sulfathiazole is proposed. This synergistic sensor platform combines Mn-ZnS-insensitive emission, MOF-assisted analyte enrichment, and imprinting-based molecular recognition. The sensing platform displays a characteristic turn-off fluorescence with a dominant static quenching mechanism. Under optimal conditions, a broad sensing range with a low detection limit of 13.75 nM can be obtained. Outstanding selectivity among similar sulfonamides, biomolecules, and metal ions were achieved with high reproducibility, stability, and reusability. This sensing platform was shown to analyze sulfathiazole accurately in aqueous samples and blood serum with high recoveries, within the range of 90.00–104.24%, compared to high-performance liquid chromatography methods. Full article

Background: Epstein–Barr virus (EBV) has long been linked to systemic lupus erythematosus (SLE), mainly through molecular mimicry, altered B-cell biology, defective antiviral immune surveillance and intermittent viral reactivation. However, the detection of EBV DNA in clinical samples does not necessarily indicate transcriptionally active infection or direct viral modulation of host pathways. Methods: Peripheral blood samples from 39 pediatric patients with SLE and 29 healthy controls were analyzed for host immune and apoptotic gene expression, including NFKB1, IL10, TLR3, BCL2, BAX and CASP3. EBV DNA was assessed in both patients and controls. In EBV DNA-positive SLE samples, the expression of EBV transcripts representative of latent, lytic and immunomodulatory programs, including LMP1, EBNA1, BZLF1, and viral IL-10, was also evaluated. Host gene expression was additionally compared between EBV DNA-positive and EBV DNA-negative patients with SLE. Results: EBV DNA was detected in 8 of 39 patients with SLE (20.5%) and in none of the 29 healthy controls (0%; Fisher’s exact test, p = 0.0171). None of the EBV DNA-positive samples showed detectable expression of LMP1, EBNA1, BZLF1 or viral IL-10. Compared with healthy controls, patients with SLE showed increased CASP3 expression that remained significant after FDR correction, whereas the reduction in IL10 expression was nominally significant only in the unadjusted analysis. NFKB1, TLR3, BCL2, and BAX did not differ significantly. In the exploratory comparison between EBV DNA-positive and EBV DNA-negative patients with SLE, no host gene remained significantly associated with EBV DNA status after false discovery rate correction. Conclusions: EBV DNA was detected more frequently in patients with SLE than in healthy controls, but this finding was not accompanied by detectable expression of the selected EBV transcripts under the analytical conditions used or by a consistent host transcriptional signature associated with EBV DNA positivity. These findings emphasize the importance of distinguishing EBV DNA detection from detectable viral transcript expression in SLE. Full article

Early detection of ovarian cancer remains challenging because of the lack of sensitive and reproducible blood-based biomarkers. A major challenge in plasma proteomics is the extremely wide dynamic range of protein concentrations, which prevents simultaneous detection of both high- and low abundance proteins and limits the identification of disease-associated signals. In this study, we applied a combined atomic force microscopy and mass spectrometry (AFM/MS) approach to investigate how sample dilution affects plasma proteome coverage and the detection of differences between healthy donors and patients with stage I and stage III ovarian cancer. Plasma samples were analyzed at two dilution levels (1:100 and 1:10,000). At 1:100 dilution, a total of 235 proteins were identified across all samples, representing the union of all replicates and groups. The reproducible CORE proteome comprised 169 proteins in the Healthy group, 183 in the Stage I group, and 193 in the Stage III group. Differential analysis revealed distinct, non-overlapping protein sets at each dilution level. At 1:100 dilution, most altered proteins were decreased in patients and corresponded to major plasma components, including complement proteins and protease inhibitors. At 1:10,000 dilution, most altered proteins were increased and were predominantly immunoglobulin-related proteins, along with complement regulatory components. These findings show that sample dilution determines which fraction of the plasma proteome is observable. Here, proteome depth refers to the total number of non-redundant proteins accessible within the analytical workflow. When CORE sets from all groups were combined, 216 proteins were identified at 1:100 and 149 at 1:10,000, with 133 shared between the two dilution conditions. The higher dilution contributed 16 additional CORE proteins not detected in the 1:100 CORE union, increasing the combined CORE set to 232 proteins. Thus, higher dilution alone did not increase proteome depth, but provided complementary protein identifications that increased cumulative proteome depth when both dilution conditions were considered together. This effect reflects dilution-dependent selectivity in the composition of the detectable protein subset. Full article

Microvascular invasion (MVI) is a critical prognostic indicator for recurrence and survival in hepatocellular carcinoma (HCC); however, its accurate preoperative assessment remains clinically challenging. Postoperative histopathology is subject to sampling bias and time delays, while traditional imaging techniques lack the molecular specificity required to predict MVI. Liquid biopsy, through the analysis of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), circulating tumor RNA (ctRNA), and extracellular vesicles (EVs), provides a minimally invasive approach for capturing tumor-derived molecular and cellular signals associated with vascular invasion. This narrative review comprehensively summarizes the current evidence linking these four liquid biopsy analyte categories to MVI in HCC, evaluates their integration into multi-omics predictive models, including multi-marker, clinicopathological-integrated, and imaging-integrated strategies, and proposes an evidence-level framework that categorizes blood biomarkers according to the strength of their support for MVI prediction, distinguishing direct histopathological validation from indirect associations with aggressive tumor biology. Key challenges are critically examined, including the variable specificity of individual biomarkers for MVI, the lack of head-to-head comparative studies, the absence of standardized pre-analytical and analytical protocols, and the methodological limitations of current prediction models. As a narrative review, this work does not employ systematic review methodology, and the evidence synthesis should be interpreted accordingly. The review provides a framework for understanding how liquid biopsy-based MVI risk stratification may inform surgical and perioperative decision-making following prospective validation. Full article

Liquid biopsy, the analysis of tumor-derived material in blood, saliva, and other body fluids, is increasingly explored for the diagnosis, surveillance, and molecular characterization of head and neck squamous cell carcinoma (HNSCC). Its performance, however, is not uniform across the disease, and the reason is fundamentally molecular. human papillomavirus (HPV)-positive oropharyngeal cancers carry viral oncogenes that are absent from the host genome and therefore provide a near ideal, tumor specific circulating marker, whereas HPV-negative tumors are driven by a heterogeneous somatic landscape that offers no single universal target. In this narrative review, we adopt a molecular perspective. We first examine the biological origin of circulating tumor DNA and of the other analytes that liquid biopsy can interrogate including circulating tumor HPV DNA, viral transcripts, microRNAs, extracellular vesicles, and methylation signatures. We then consider how analytical platforms, from droplet digital PCR to next generation and ultrasensitive whole-genome sequencing, translate these molecules into measurements. Only afterward do we discuss the clinical questions, organized by clinical objective rather than by individual study: diagnosis and early detection, prognosis and risk stratification, treatment response monitoring, minimal residual disease and surveillance, and biomarker guided de-escalation in HPV-positive disease. Twelve registered clinical trials, involving approximately 1183 patients, are presented as illustrations of these questions. We close on the biological and technical gaps that still separate promising signals from clinical practice, and on the multi analyte and dynamic strategies most likely to bridge them. At present, liquid biopsy should be regarded as a complementary tool rather than as a replacement for established clinicopathological assessment. Full article

A series of molecularly imprinted polymers (MIPs) based on hydroxypropyl-β-cyclodextrin (HPCD) crosslinked with 1,6-hexamethylene diisocyanate (HMD) or toluene diisocyanate (TDI), as well as hybrid chitosan–HPCD polymers crosslinked with genipin, were synthesized using levofloxacin and fluorescein as template molecules. The structure and spatial organization of the obtained materials were characterized by FTIR spectroscopy, FTIR microscopy mapping, and ζ-potential measurements. The influence of pH, crosslinker content, and template structure on sorption performance was investigated. All MIPs exhibited maximum sorption at pH 3.0. The highest sorption capacity toward levofloxacin was achieved for the LV–Chit–HPCD–Genipin_MIP (74.8 mg/g), whereas the fluorescein-imprinted FL–HPCD–TDI_MIP (1:1) demonstrated the highest sorption capacity (135.5 mg/g) and selectivity coefficient (84.1). Dynamic column experiments confirmed efficient analyte extraction, reducing the analyte concentration by more than 90% after ten loading cycles. All synthesized MIPs exhibited excellent regenerability, with less than 3% loss of sorption efficiency after ten consecutive sorption–desorption cycles. The applicability of the developed sorbents to real matrices was demonstrated using milk and blood plasma samples after minimal sample preparation. Fluorescein extraction efficiencies reached 97.6% and 93.6% for milk and plasma, respectively. The obtained results demonstrate that HPCD-based MIPs combine high sorption capacity, exceptional selectivity, operational stability, and applicability to complex biological matrices, making them promising materials for selective sample preparation, analyte preconcentration, and controlled drug delivery systems. Full article

Time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for noninvasive visualization of arterial anatomy, but extracting hemodynamics like blood velocity typically requires supplementary phase-contrast scans, tagging or multi-TE images. This study proposes a novel, physics-informed computational framework to extract variable fluid velocity directly from standard TOF-MRA signal profiles. We analytically expand the approach-to-steady-state Bloch equations to include convective flow, establishing a mathematical relationship between the spatial decay of longitudinal magnetization and fluid velocity. The velocity derivation was further extended to pointwise estimation over a 1-D centerline, overcoming the limitations of constant-velocity assumptions. To validate and solve this problem, a MATLAB (R2025b) simulation framework was developed to model fluid flow in two variable-geometry flowing tube cases, i.e., continuous narrowing and focal stenosis, under synthetic scanner noise. A global inverse optimization approach utilizing Dual-Tikhonov regularization was applied to stably invert the ill-posed transit time integral, actively penalizing high-frequency numerical ringing while preserving structural curves. The computational simulations successfully recovered ground-truth point-wise velocities, tracking gradual hemodynamic accelerations and sharp stenotic jets. This theoretical framework and the example centerline TOF-MRA signal intensity provide a robust mathematical proof-of-concept that quantitative, localized functional hemodynamic metrics can be extracted from standard structural MRA imaging, establishing a foundation for advanced flow quantification without requiring additional scan time. Full article

Background and Clinical significance: Potassium is one of the most frequently measured laboratory parameters used to assess a patient’s clinical status and is also one of the analytes most commonly affected by preanalytical errors. Case Presentation: A potassium test was ordered for a 63-year-old male patient. The result obtained was 6.4 mmol/L, indicating hyperkalemia, and a medical consultation was recommended in the laboratory report. As the potassium result was inconsistent with the patient’s clinical status, a new blood sample was analyzed the next day. This yielded a result that was 1.3 mmol/L (20%) lower. A detailed interview with the patient and the staff responsible for blood sample collection revealed that the spurious hyperkalemia was most likely caused by prolonged storage of the blood sample in a refrigerator implemented because of high ambient temperatures. Further analysis demonstrated that after storage of blood samples at low temperature, potassium concentration increased significantly on average by 5% and 20% at the 4 h and 8 h time points, respectively. Conclusions: Low temperature and prolonged blood sample storage before analysis significantly affect potassium results. Since even a slight alteration in potassium levels can have a severe impact on a patient’s health and may require immediate action, obtaining accurate potassium results requires ensuring appropriate conditions for sample storage and transport, and proper sample handling. This is particularly important in laboratories serving large geographical areas, where prolonged storage and transportation of blood samples can considerably extend the preanalytical phase. Full article

Background/Objectives: Modern automated hematology analyzers combine quantitative cell counting with proprietary algorithms for automated morphological interpretation. While analytical validation traditionally focuses on measurement agreement, less attention has been paid to the evaluation of algorithm-assisted morphological interpretation. This study compared the analytical performance and automated morphological flagging of the Sysmex XN-9100 and Mindray BC-7800/BC-7900 platforms under routine laboratory conditions. Methods: A total of 183 peripheral blood samples collected between October 2025 and February 2026 were analyzed in parallel using both platforms. The study population included healthy individuals and patients with hematological and non-hematological disorders. Analytical agreement for complete blood count (CBC) and leukocyte differential parameters was assessed using Passing–Bablok regression and Bland–Altman analyses. Automated morphological flagging was evaluated in 157 samples using expert optical microscopy as the reference standard. McNemar’s test, Cohen’s kappa coefficient, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy were calculated. Results: Excellent agreement was observed for the principal CBC parameters, including white blood cell count, red blood cell count, hemoglobin, hematocrit, mean corpuscular volume, and platelet count (correlation coefficients: 0.981–1.000), with minimal proportional bias. Greater variability was found for monocytes, eosinophils, and basophils, particularly at low cell concentrations. Although analytical performance was highly comparable, the two platforms showed different morphological flagging profiles. Both analyzers achieved high negative predictive values (>90%), while differences in sensitivity and specificity across individual flag categories reflected distinct algorithm-assisted classification strategies. Agreement with expert microscopy ranged from fair to moderate for most pathological flags. Conclusions: The Mindray BC-7800/BC-7900 and Sysmex XN-9100 demonstrated excellent analytical agreement for routine CBC testing. However, comparable analytical performance did not necessarily correspond to identical automated morphological interpretation. These results indicate that evaluation of modern hematology analyzers should include both analytical performance and agreement between automated flags and expert microscopy. Full article

Titanium-based implants remain among the most successful biomaterials in modern dentistry, but accumulating evidence demonstrates that titanium is not biologically inert under long-term physiological conditions. Mechanical loading, tribocorrosion, acidic and oxidative microenvironments, and biofilm-driven electrochemical processes contribute to progressive surface degradation and the release of titanium ions, microparticles, and nanoparticles into surrounding tissues and biological fluids. The present narrative review synthesizes current evidence regarding the mechanisms of titanium release from dental implant surfaces, the biodistribution of degradation-derived species across local and systemic biological compartments, and the analytical methodologies used to detect and characterize them. Mechanisms of electrochemical corrosion, tribocorrosion, and nanoparticle generation are critically discussed alongside biofilm-mediated acceleration of surface degradation. The biological matrices in which titanium has been measured—including peri-implant tissues, peri-implant crevicular fluid, saliva, blood, regional lymph nodes, and distant organs—are reviewed with attention to the methodologies employed (ICP-MS, SP-ICP-MS, LA-ICP-MS, SEM-EDS, TEM, XRF, and synchrotron-based approaches) and their respective strengths and limitations. Methodological heterogeneity in implant characterization, sample preparation, contamination control, and discrimination between ionic and particulate species is identified as a major source of inconsistency across the current literature. The biological consequences of titanium dissemination—including oxidative, immunological, microbiome-associated, and systemic responses—are addressed in detail in a companion review. Together, these analyses are intended to support the design of more rigorous, integrated, and clinically translatable investigations of implant-associated biomaterial degradation. Full article

Metastatic colorectal cancer remains associated with poor prognosis despite major therapeutic advances, highlighting the need for robust biomarkers to refine treatment selection and monitor disease dynamics. This review summarizes emerging predictive and prognostic biomarkers in metastatic colorectal cancer across molecular and cellular layers, encompassing both tissue and circulating biomarkers. At the tissue level, we discuss genomic alterations and mutational signatures, transcriptomic classification systems and immune-related gene expression tools, protein-level immune checkpoint markers, and cellular determinants including immune infiltrates, cancer-associated fibroblasts and microbiome features. At the circulating level, we review biomarkers derived from liquid biopsy and peripheral blood, including circulating tumor DNA kinetics, T-cell receptor repertoire diversity, soluble cytokines and proteins, immune cell phenotyping, and circulating tumor cells. We highlight major challenges limiting clinical translation, including tumor heterogeneity, methodological variability, and the absence of standardized analytical pipelines and thresholds. Finally, we discuss future perspectives, emphasizing the integration of multi-omics biomarkers and artificial intelligence-driven strategies to improve biomarker validation and enable more precise management of metastatic colorectal cancer, particularly for patients with microsatellite-stable tumors who derive limited benefit from immune checkpoint inhibition. Full article

Background/Objectives: Methylglyoxal-derived hydroimidazolone-1 (MG-H1), an advanced glycation end product, has implications in the pathogenesis of diabetic kidney disease (DKD). Although liquid chromatography–mass spectrometry is the current gold standard for quantifying MG-H1, its overall complexity limits its utility. We developed an ELISA to measure MG-H1 using a specific monoclonal antibody. Methods: Competitive ELISA was used to quantify total, high-molecular-weight (HMW), and low-molecular-weight (LMW) MG-H1 in serum. The assay’s specificity was validated against structurally related compounds. Spike-and-recovery experiments were conducted to assess accuracy and precision. Serum samples from healthy controls, diabetic patients without kidney disease, and patients with DKD were analyzed (n = 10, 23, and 19, respectively). MG-H1’s correlation with renal biomarkers and diagnostic performance was assessed using receiver operating characteristic analyses. Results: The ELISA exhibited preferential reactivity toward MG-H1 compared with structurally related compounds. Spike-and-recovery experiments resulted in recovery rates ranging 108–119%. MG-H1 levels were increased in patients with DKD, although the magnitude of the changes varied among the MG-H1 forms. All MG-H1 forms correlated positively with serum creatinine and blood urea nitrogen, and negatively with estimated glomerular filtration rate. No significant correlations were observed with glycoalbumin, and only a modest association was observed between LMW MG-H1 and HbA1c. Exploratory ROC analyses suggested that all MG-H1 forms could discriminate DKD from DM, with total and HMW MG-H1 showing performance comparable to that of conventional renal function markers. Conclusions: This competitive ELISA enables high-throughput quantification of MG-H1 in serum and demonstrates analytical feasibility; further multicenter validation is required before clinical implementation. Full article

Contemporary intensive care operates in an environment with high-complexity cases, large volumes of information, and vast physiological, biological, and therapeutic data, collected from laboratory results, investigations, and therapies for organ support, as well as from systems that operate in parallel. The lack of interoperability contributes to information overload, alarm fatigue, and delayed decision-making. The Smart ICU concept has been developed to address these limitations by integrating medical devices, information systems, and artificial intelligence into a unified system that allows interoperable data integration and predictive analytics. Aim: The purpose of this article is to provide a narrative review of the Smart ICU concept, with a specific focus on the cardiac intensive care unit. It summarizes Smart ICU architecture, data integration, clinical support, and applicability in monitoring perioperative inflammation in cardiac surgery. We describe the Smart ICU architecture, from data acquisition to storage and analytics, highlighting the differences between Smart ICU, artificial intelligence, and Tele-ICU, and we underline predictive analytics as a supportive tool, as well as its influence on clinical outcomes. Cardiac ICU application: Cardiac ICUs offer a data-dense, temporally well-defined model following cardiac surgery with cardiopulmonary bypass, where data concerning patients’ hemodynamics, perfusion data, and biological and inflammatory markers intertwine. Cardiac Smart ICU models could recognize early signs of hemodynamic compromise and low cardiac output states and identify early indicators of post-cardiac surgery complications. Neutrophil activation and complete blood count-derived indices may be used as dynamic biological data for Smart Cardiac ICU models. Conclusion: The Smart Cardiac ICU may support earlier risk stratification, and therefore earlier diagnostic and therapeutic interventions, but its clinical value requires prospective, multicenter validation. Cardiopulmonary bypass-induced inflammation may offer an ideal setting to integrate physiological, procedural, and immunological data into bedside predictive models. Full article

Micro- and nanoplastics (MNPs) are reported in blood, urine, and tissues, including the kidney, raising concern that the urinary system may be both a target and a route of elimination. This narrative review integrates analytical, toxicokinetic, experimental, epidemiological, and dialysis-related evidence on MNPs and renal health. Human studies report polymer-confirmed particles or polymer-associated signals in blood, urine, and kidney-related specimens, supporting systemic presence and compatibility with renal exposure; however, estimates are strongly method-dependent and do not establish anatomical localization, tissue dose, clearance, or a disease threshold. Cell, kidney-organoid, and animal studies consistently identify oxidative and mitochondrial stress, endoplasmic-reticulum dysfunction, inflammation, altered autophagy, regulated cell death, senescence, and fibrotic remodelling. Effects vary with polymer, size, shape, surface ageing, route, dose, and chemical co-exposures, and many experiments remain difficult to map to typical human exposure. Direct human outcome evidence is limited to cross-sectional or exploratory studies; plasticizer epidemiology is informative for chemical co-exposure but cannot establish particle-specific toxicity. Patients with chronic kidney disease may be more susceptible, while kidney dysfunction may also alter measured blood or urinary concentrations. Dialysis introduces an additional, incompletely quantified exposure system. MNP-related renal injury is biologically plausible, but causal contribution to human kidney disease and clinical actionability remain unproven. Standardized methods, paired-matrix kinetics, prospective cohorts, and complete dialysis mass-balance studies are priorities. Full article