Search Results (1,943)

YKL-40 is a glycoprotein that may be present at elevated levels in many cancers and neurodegenerative diseases. It has been investigated in numerous studies as a potential biomarker for several conditions, including Alzheimer’s Disease (AD). In this study, a biosensor with Surface Plasmon Resonance imaging (SPRi) detection, sensitive to YKL-40, was constructed for the detection of this analyte in the blood plasma of AD patients. Extensive validation of the biosensor was performed. This included the determination of analytical parameters such as the biosensor’s response characteristics, detection and quantification limits, precision, accuracy, repeatability, selectivity, stability, and performance in natural samples. Validation parameters were primarily tested using standard solutions, while natural samples were employed to evaluate repeatability, stability, and assay accuracy in three groups of samples from different patients. A YKL-40-specific antibody was used as the receptor layer, immobilized on a gold plate using the EDC/NHS protocol on thiol 11-MUA. The biosensor exhibited a wide operating range (1–200 ng/mL), a low detection limit (LOD) of 2 pg/mL, and a quantification limit (LOQ) of 7 pg/mL. High precision and accuracy were confirmed by the calculated standard deviations (SD) and coefficients of variation (CV), which ranged from 0.0009 to 7.02 ng/mL and from 0.12% to 9.24%, respectively. The sensor also demonstrated good repeatability (CV = 4.995%) and was capable of detecting the analyte of interest in complex biological matrices. Its applicability was confirmed in a study using plasma from AD patients and two selected control groups: plasma from smokers and patients with prostatitis. This allowed the assessment of YKL-40 levels across different groups. The results were consistent with literature values, and statistical analysis confirmed the significance of concentration differences between groups. Furthermore, ROC curve analysis confirmed the diagnostic usefulness of the constructed YKL-40 test in the context of Alzheimer’s disease. Full article

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by impaired social skills and communication. Forkhead box protein P1 (FOXP1) is involved in the development of the brain and the pathogenesis of ASD. However, the function of FOXP1 within the brain remains unclear. The aim of this case–control study was to evaluate whether FOXP1 could be used as a diagnostic biomarker for ASD. Method: Blood plasma was collected from children with ASD and age-matched controls. The enzyme-linked immunosorbent assay (ELISA) was used to determine the FOXP1 plasma levels in ASD and control groups. The behavioral and social impairments in children with ASD were assessed using the Childhood Autism Rating Scale (CARS) and the Social Responsiveness Scale (SRS). Spearman’s correlation coefficient (r) was used to determine the correlation between different variables. Results: The plasma FOXP1 protein level was significantly decreased in children with ASD compared to the controls (p < 0.001). CARS showed significant differences between the mild-to-moderate and severe subgroups, while the SRS showed no significant difference between the two subgroups. Moreover, both the mild-to-moderate and severe subgroups exhibited a substantial drop in plasma FOXP1 compared to the controls. ASD children older than six years old also showed a significantly decreased FOXP1 level, compared to those aged six years or less. Furthermore, no significant correlation between the FOXP1 level, CARS, and SRS was observed. However, a negative correlation was found between age and FOXP1 plasma level. Conclusions: We suggest that plasma FOXP1 may act as a potential biomarker for the prognosis of ASD severity and social communication impairment. Further research with a larger sample size is needed to clarify these associations and help diagnose or understand the underlying mechanism of ASD. Full article

Gliomas are aggressive brain tumours with diverse histological and molecular features, complicating accurate diagnosis and treatment. Dysregulated lipid metabolism contributes to glioma progression, and analysing lipid profiles in plasma and tissue may enhance diagnostic and prognostic accuracy. This study investigated lipid dysregulation to identify key lipid signatures that distinguish glioma from other brain diseases and examined the associations between lipid biomarkers in glioma tissue and plasma. Biospecimens from 11 controls and 72 glioma patients of varying grades underwent lipidomic profiling using liquid chromatography-mass spectrometry. Univariate and multivariate analyses identified differentially abundant lipids, and correlation analysis evaluated the associations between tissue and plasma biomarkers. Lipidomic analysis revealed distinct lipid profiles in the tissues and plasma of glioma patients compared to those of controls. Prominent lipid metabolites in glioma tissues included LPC 21:3 (AUC = 0.925), DG 43:11 (AUC = 0.906), and PC 33:1 (AUC = 0.892), which served as effective biomarkers. Conversely, in plasma, lipid metabolites such as phosphatidylethanolamine (PE 21:3, AUC = 0.862), ceramide-1-phosphate (CerP 26:1, AUC = 0.861), and sphingomyelin (SM 24:3, AUC = 0.858) were identified as the most promising lipid biomarkers. Significant positive and negative correlations were observed between the tissue and plasma lipid biomarkers of glioma patients. Lipidomic profiling revealed aberrant lipid classes and pathways in glioma tissues and plasma, enhancing understanding of glioma heterogeneity and potential clinical applications. Full article

Background: Intracranial aneurysm (IA) rupture is a life-threatening cerebrovascular event with a mortality rate of up to 40%, affecting approximately 500,000 people globally each year. Although environmental pollutants such as 2,2′,4,4′-tetrabromodiphenyl ether (PBDE-47) have been implicated in the pathogenesis of IA, the causal relationship and underlying mechanisms remain unclear. This study aims to systematically explore the potential causal role of PBDE-47 in the development of IA by integrating multi-omics approaches. Methods: We utilized the UK Biobank Drug Proteomics Project (UKB-PPP) genome-wide association study (GWAS) data, including 2940 plasma proteins and 1400 metabolites, along with IA genetic data from 456,348 individuals, to perform a two-sample Mendelian randomization (MR) analysis. Instrumental variables were selected based on genome-wide significance (p < 5 × 10⁻⁸) or suggestive thresholds (p < 5 × 10⁻⁵). Analytical methods included inverse variance weighting (IVW), MR-Egger, weighted median, MR-PRESSO, and Steiger filtering for sensitivity analysis. Molecular docking and 100-nanosecond molecular dynamics simulations were used to evaluate interactions between PBDE-47 and proteins. Mediation analysis assessed the roles of plasma metabolites and miRNAs, and SMR-HEIDI tests were used to verify causal relationships. Results: MR analysis identified 93 plasma proteins potentially causally associated with IA, including 53 protective factors and 40 risk factors. By integrating PBDE-47 targets, IA-related genes, and metabolite-related genes, we identified 15 hub genes. Molecular docking revealed potential binding between PBDE-47 and F2R (binding energy: −5.516 kcal/mol), and SMR-HEIDI testing supported F2R as a potential causal risk factor for IA. Molecular dynamics simulations indicated the stability of the complex structure. Mediation analysis suggested that F2R may influence IA risk through eight plasma metabolites, and miR-130b-3p may indirectly promote IA development by upregulating F2R. Conclusions: Our findings suggest that exposure to PBDE-47 may have a potential causal relationship with IA risk, potentially mediated through the “PBDE–47–F2R–metabolite–miRNA” regulatory axis. These results provide preliminary evidence for early diagnostic biomarkers and targeted interventions for IA. The multi-omics analytical framework established in this study offers new insights into environmental determinants of neurovascular diseases, although further validation is needed to address potential limitations. Full article

Multiple myeloma is a clonal plasma cell malignancy with a highly variable range of clinical manifestations. Over recent decades, substantial progress has been made in laboratory diagnostics, which has deepened our understanding of disease biology, improved risk stratification, and informed treatment strategies. In an era of transformation and innovation, conventional laboratory methods remain essential, as cutting-edge technologies might not be immediately accessible to all laboratories. Nonetheless, even widely used laboratory methodologies present many challenges, such as variability in assay performance, interpretative criteria, and standardization. This review by the Portuguese Multiple Myeloma Group of the Portuguese Society of Hematology provides a comprehensive overview and practical appraisal of current conventional laboratory methods employed for multiple myeloma diagnosis. Full article

SPCEs are crucial for electrochemical sensing because of their portability, low cost, disposability, and ease of mass production. This study details their manufacture, surface modifications, electrochemical characterization, and use in chemical and biosensing. SPCEs integrate working, reference, and counter electrodes on PVC or polyester substrates for compact sensor design. Surface modifications, such as plasma treatment (O₂, Ar), nanomaterial addition (AuNPs, GO, CNTs), polymer coatings, and MIPs, enhance performance. These changes improve sensitivity, selectivity, stability, and electron transport. Electrochemical methods such as CV, DPV, SWV, and EIS detect analytes, including biomolecules (glucose, dopamine, and pathogens) and heavy metals (Pb²⁺, As³⁺). Their applications include healthcare diagnostics, environmental monitoring, and food safety. Modified SPCEs enable rapid on-site analysis and offer strong potential to transform our understanding of the physical world. Full article

The paper presents experimental results for a modified pulsed plasma thruster (PPT) with solid propellant, using a coaxial anode–cathode design. Graphite from pencil leads served as propellant, and a tungsten trigger electrode was tested to reduce carbonization effects. Experiments were performed in a vacuum chamber at 0.001 Pa, employing diagnostics such as discharge current/voltage recording, power measurement, ballistic pendulum, time-of-flight (TOF) method, and a Faraday cup. Current and voltage waveforms matched an oscillatory RLC circuit with variable plasma channel resistance. Key discharge parameters were measured, including current pulse duration/amplitude and plasma channel formation/decay dynamics. Impulse bit values, obtained with a ballistic pendulum, reached up to 8.5 μN·s. Increasing trigger capacitor capacitance reduced thrust due to unstable “pre-plasma” formation and partial pre-discharge energy loss. Using TOF and Faraday cup diagnostics, plasma front velocity, ion current amplitude, current density, and ion concentration were determined. Tungsten electrodes produced lower charged particle concentrations than graphite but offered better adhesion resistance, minimal carbonization, and stable long-term performance. The findings support optimizing trigger electrode materials and PPT operating modes to extend lifetime and stabilize thrust output. Full article

The accurate classification of pancreatic cystic lesions remains clinically challenging due to overlapping imaging features and variable malignant potential. Mucinous cystic neoplasms, in particular, require early identification given their premalignant nature. RNA profiling presents a promising alternative to current diagnostic limitations—a molecular lens sharpened by AI-driven pattern recognition. This study aimed to evaluate the diagnostic potential of RNA signatures for differentiating pancreatic cyst subtypes and to clarify their roles in their pathophysiology. The study included 31 patients with pancreatic lesions who underwent endoscopic ultrasound-guided fine-needle aspiration. RNA was extracted from cyst fluid, tissue, and peripheral blood. Expression of 17 target genes was analyzed using qPCR. Gene expression patterns were compared across mucinous cystic neoplasms, serous cystic neoplasms, pseudocysts, adenocarcinoma, and chronic pancreatitis cohorts. Diagnostic accuracy was evaluated via ROC analysis. Mucinous cysts exhibited significant overexpression of MUC1, ITGA2, ELOVL6, and MUC5AC genes compared to serous cysts and pseudocysts. PKM gene expression correlated with increasing malignant potential. In blood plasma, only MUC1, MUC4, and PYGL were elevated in adenocarcinoma compared to mucinous neoplasms. We identified a distinct RNA signature that can distinguish mucinous cystic neoplasms from benign cystic lesions (serous cysts and pseudocysts), which could be useful for guiding patient management and improving clinical outcomes. Validation in broader cohorts is essential for clinical implementation. Full article

Background: Nowadays, there is a lack of reliable and minimally invasive diagnosis methods for the early detection of Alzheimer’s disease. The development and validation of such tools could significantly reduce the dependence on more invasive and costly confirmatory procedures, such as cerebrospinal fluid biomarkers analysis and neuroimaging techniques. Objectives: The main objective of this study is to validate the clinical performance of a previously developed diagnosis model based on plasma biomarkers from patients in a cognitive disorder unit. Methods: A new cohort of patients was recruited from the same cognitive disorder unit (n = 93). Specifically, demographic data (gender, age, and educational level), plasma biomarkers levels, and genotype (glial fibrillary acidic protein, phosphorylated Tau 181, amyloid-beta42/amyloid-beta40, apolipoprotein E) were collected to evaluate both approaches of the previous diagnosis model (one-cut-off, two-cut-off). Results: The one-cut-off approach showed a sensitivity of 74.3%, a specificity of 89.5%, and an area under the curve of 0.888, while the values for the two-cut-off approach were sensitivity of 66.7%, specificity of 99.9%, and area under the curve of 0.867. Conclusions: A multivariate diagnostic tool was temporally validated for implementation in a clinical unit. In fact, satisfactory results were obtained from both approaches (one-cut-off, two-cut-offs), but the two cut-offs approach was more consistent in correctly identifying non-Alzheimer’s disease cases, allowing us to identify a large number of cases with high specificity. Full article

Endometriosis is a chronic, estrogen-dependent inflammatory disease with heterogeneous clinical manifestations and uncertain systemic immune involvement. This study aimed to characterize peripheral immune profiles and circulating tumor markers in women with ovarian endometrioma (OE) and deep infiltrating endometriosis (DIE), and to explore their associations with disease severity, symptom burden, and physical health perception. Peripheral blood leukocyte subsets, plasma cytokines, and tumor markers (CA125, CA19-9, CEA, HE4) were analyzed in 146 patients and 50 healthy controls. OE was associated with increased monocyte counts and reduced neutrophil proportions, while DIE showed elevated levels of IL-8 and Galectin-1. IL-33 levels correlated negatively with the revised American Society for Reproductive Medicine (rASRM) scores and positively with neutrophil proportion, suggesting a role in systemic immune regulation. Tumor marker levels varied by subtype: CA19-9 was higher in OE, and CEA in DIE. CA125 correlated with disease severity, and CEA with monocyte levels. Exploratory heatmaps revealed consistent immune-tumor associations linked to anatomical severity and symptom profiles. Although exploratory, these findings highlight the presence of distinct systemic immune patterns in endometriosis and support the potential of integrative blood-based biomarkers for future diagnostic and stratification strategies. Full article

Multiple myeloma (MM) is one of the most common hematological malignancies and remains incurable. However, the survival of multiple myeloma patients has significantly increased due to the implementation of novel therapies along with autologous stem cell transplantation, changing the natural history of the disease. Consequently, there is an unmet need for more sensitive response assessment techniques capable of quantifying minimal tumor burden to identify patients at higher risk of early relapse. Multiparameter flow cytometry (MFC) is an essential tool for diagnosing and monitoring patients with various hematological conditions and has recently gained prominence in identifying, characterizing, and monitoring malignant plasma cells. The implementation of Next-Generation Flow (NGF) by EuroFlow aims to overcome the pitfalls of conventional MFC, including lack of standardization and lower sensitivity, by offering standardized and optimized protocols for evaluating response depth. Both MFC and NGF have wide-ranging applications in MM for diagnosis and measurable residual disease (MRD) monitoring. Plasma cell identification and clonality evaluation through MFC and NGF assist in diagnostic workup and are routinely used to assess therapeutic response through MRD analysis. Additionally, flow cytometry is applied for circulating tumor plasma cell (CTPC) enumeration, which has demonstrated significant prognostic value. Immune composition studies through MFC may provide better understanding of disease biology. Furthermore, MFC provides additional information about other bone marrow cell populations, assessing cellularity, immunophenotypic characteristics of plasma cells, and possible hemodilution. This review explores the applications of MFC and NGF in MM, highlighting their roles in diagnosis, response assessment, and prognosis. Beyond their established use in MRD monitoring, flow cytometry-derived immunophenotypic profiles show strong potential as cost-effective prognostic tools. We advocate for future studies to validate and integrate these markers into risk stratification models, complementing cytogenetic analyses and guiding individualized treatment strategies. Full article

We present three dimensional particle-in-cell simulations of current-voltage characteristics of the hemispherical Langmuir probe (LAP), onboard the China Seismo-Electromagnetic Satellite (CSES). Using realistic plasma parameters and background magnetic fields obtained from the International Reference Ionosphere (IRI) and International Geomagnetic Reference Field (IGRF) models, we simulate probe–plasma interactions at three locations: the equatorial region and two magnetically conjugate mid-latitude sites: Millstone Hill (Northern Hemisphere) and Rothera (Southern Hemisphere). The simulations, performed using the PTetra PIC code, incorporate realistic LAP geometry and spacecraft motion in the ionospheric plasma. Simulated current voltage characteristics or I–V curves are compared against in-situ LAP measurements from CSES Orbit-026610, with Pearson’s correlation coefficients used to assess agreement. Our findings indicate how plasma temperature, density, and magnetization affect sheath structure and probe floating potential. The study highlights the significance of kinetic modeling in enhancing diagnostic accuracy, particularly in variable sheath regimes where classic analytical models such as the Orbital-Motion-Limited (OML) theory may be inadequate. Full article

Iron overload-driven liver fibrosis is a major concern in β-thalassaemia patients, but non-invasive or minimally invasive biomarkers for fibrosis staging remain limited. This study evaluated five plasma microRNAs (let-7a, miR-21, miR-29a, miR-34a, and miR-122) as potential markers for distinguishing liver fibrosis stages in β-thalassaemia. Plasma samples from 40 patients with fibrosis stages F0–F1 to F4 were analysed using RT-qPCR, normalised against the arithmetic mean of reference miRNAs miR-16 and miR-221. Expression levels of candidate miRNAs showed no statistically significant variation across stages, and logistic regression and ROC analyses revealed fair discriminatory performance for individual miRNAs and their combinations in selected stage comparisons. Notably, while for the discrimination of different fibrosis stages all five candidate miRNAs tested showed fair area-under-the-curve values between 0.7 and 0.8 individually and up to 0.917 in combination, none of these findings reached statistical significance. These results suggest that while the selected set of miRNAs reflects liver injury, its performance for precise fibrosis staging in β-thalassaemia is limited. A key cause for the low discriminatory power of these miRNAs may be the overall change of the blood miRNA transcriptome in haemoglobinopathies. The results indicate the need for validation in larger cohorts based on larger miRNA panels or the use of alternative source materials to improve diagnostic performance. Full article

Intracranial aneurysms (IAs) are potentially devastating cerebrovascular lesions, and predicting rupture risk remains a major clinical challenge. Conventional radiological and clinical scores offer only partial risk stratification, highlighting the need for complementary approaches. Liquid biopsy represents a promising non-invasive strategy to identify circulating biomarkers that reflect aneurysm biology and instability. We conducted a systematic review according to PRISMA 2020 guidelines, screening PubMed, Scopus, and Web of Science up to August 2025. Forty-eight eligible studies, encompassing 3515 IA patients, evaluated circulating RNA species, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) in serum, plasma, blood, or cerebrospinal fluid. Multiple candidates emerged as consistently dysregulated: upregulation of miR-21, miR-126, and miR-200a-3p, and downregulation of miR-143 and let-7b-5p were recurrently observed across independent cohorts. LncRNAs, such as MALAT1 and MIAT, and circRNAs, including circ_0000690 and circ_0021001, demonstrated diagnostic and prognostic potential, with some correlating with rupture status and clinical severity indices. Despite encouraging findings, heterogeneity in study design, sample handling, and analytic methods limits reproducibility. Large-scale, multicenter validation studies are essential to translate these biomarkers into clinical practice. Full article

Alzheimer’s disease (AD) is the most common cause of cognitive decline; currently, anti-amyloid monoclonal antibodies are available for clinical use as disease-modifying treatments, while many other substances are being tested in clinical trials. Molecular biomarkers for AD have been studied for more than two decades, and various guidelines and diagnostic recommendations have been published. However, there are still questions and controversies about the biomarker profile needed to confirm AD and the eligibility for such established treatments and clinical trials. Is amyloid positivity sufficient for eligibility, or is a biomarker for tau biochemistry/pathology also needed? What is the role of hybrid ratios combining amyloid and tau? Should we rely on plasma biomarkers alone? This review aimed to describe and discuss such questions and controversies. Full article