Search Results (4,486)

Background: Biomarkers for HNSCC are still lacking. Biomolecules obtained via liquid biopsy are being investigated for diagnosis, prognosis, and therapy monitoring, including extracellular vesicles (EVs) and EV-cargo, e.g., proteins, RNA, and microRNA. This study aims to understand localization-dependent EV-microRNA expression in blood sera, their dynamics over time (12 months FU), and insights into their potential in diagnostics and therapy monitoring. Methods: Via liquid biopsy, blood serum was taken from 50 patients with HNSCC and 16 controls. Extracellular vesicles were isolated from serum by precipitation, and the contained microRNA-21, -1246, -200c, -let-7a, -181a, and -26a were amplified by reverse transcription and determined with real-time PCR. Expression ratios (HNSCC to healthy controls) were collated with the patients’ clinical parameters. A second liquid biopsy was carried out avg. 12 months later in the tumor aftercare. A sub-analysis with the Oropharynx subsite was implemented. Results: EV-mir-21, -let-7a, and -181a were 2.5–3-fold higher expressed in HPV/p16+ than in HPV/p16- HNSCC. Different expressions of EV-mir-181a and -26a could be demonstrated depending on the therapy modality. Conclusions: EV-microRNA could be a promising biomarker in the diagnosis and therapy monitoring of HNSCC. A systematic comparison of EV- and tissue microRNA expression in different HNSCC-subsites is needed. Full article

Background: Glial fibrillary acidic protein (GFAP) is an important biomarker for neuroinflammatory conditions. Recently, advancements in the treatment of neurological diseases have highlighted the increasing importance of biomarkers, creating a demand for accurate and simple measurement systems for GFAP levels, which are essential for both research and clinical applications. This study presents the development and validation of a novel fully automated immunoassay for the quantitative determination of GFAP levels in biological samples. Methods: We examined the analytical performance of the GFAP assay on the LUMIPULSE platform. The assay’s parameters, including antibody concentrations, incubation times, and detection methods, were optimized to enhance sensitivity and specificity. GFAP levels were measured in 396 serum or plasma samples, comprising both healthy controls and patients with neurodegenerative diseases. Results: In the analytical performance studies, intra- and inter-assay coefficients of variation (CV) were below 5%, indicating high reproducibility. Additionally, the assay demonstrated good linearity over the measurement range. The limit of quantification (LoQ) for this assay was 6.0 pg/mL, which is sufficient for measuring specimens from healthy controls. In clinical validation studies, GFAP levels were significantly elevated in patients with neurodegenerative diseases compared to healthy controls. Conclusions: This automated GFAP assay provides a robust and reliable tool for GFAP measurement, facilitating further research into GFAP’s role in neurological disorders and potentially aiding in the diagnosis and monitoring of these conditions. Full article

Objective: We aimed to compare the clinical utility and diagnostic accuracy of the ADNEX model, ROMA score, RMI I, and RMI IV, as well as two serum markers (CA125 and HE4) in preoperative discrimination between benign and malignant adnexal masses (AMs). Methods: We conducted a retrospective study extracting all consecutive patients with AMs seen at our Institution between January 2015 and December 2020. Accuracy metrics included sensitivity (SE), specificity (SP), and area under the receiver operating characteristic curve (AUC), and their 95% confidence intervals (CI) were calculated for basic discrimination between AMs. Model performance was evaluated in terms of discrimination ability and clinical utility (net benefit, NB). Results: A total of 581 women were included; 481 (82.8%) had a benign ovarian tumor and 100 (17.2%) had a malignant tumor. The SE and SP of CA125, HE4, ROMA score, RMI I, RMI IV, and ADNEX model were 0.60 (0.54–0.66) and 0.80 (0.76–0.83); 0.39 (0.30–0.49) and 0.96 (0.94–0.98); 0.59 (0.50–0.68) and 0.92 (0.88–0.95); 0.56 (0.46–0.65) and 0.98 (0.96–0.99); 0.54 (0.44–0.63) and 0.96 (0.94–0.98); 0.82 (0.73–0.88) and 0.91 (0.89–0.94), respectively. The overall AUC was 0.76 (0.74–0.79) for CA125, 0.81 (0.78–0.83) for HE4, 0.82 (0.80–0.85) for ROMA, 0.86 (0.84–0.88) for RMI I, 0.83 (0.81–0.86) for RMI IV, and 0.92 (0.90–0.94) for ADNEX. The NB for ADNEX was higher than other biomarkers and models across all decision thresholds between 5% and 50%. Conclusions: The ADNEX model showed a better discrimination ability and clinical utility when differentiating malignant from benign Ams, compared to CA125, HE4, ROMA score, RMI I, and RMI IV. Full article

Background: Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder with a growing body of evidence suggesting the central role of lipid metabolism in its pathogenesis. However, the dynamic changes in lipid metabolism across different stages of T2DM remain understudied. Objective: This study aimed to elucidate the temporal alterations in lipid metabolism in T2DM using an integrated lipidomics approach. Method: Serum samples from 155 subjects were analyzed using LC-MS-based lipidomics, including untargeted and targeted approaches. Results: We identified significant alterations in 44 lipid metabolites in newly diagnosed T2DM patients and 29 in high-risk individuals, compared with healthy controls. Key metabolic pathways such as sphingomyelin, phosphatidylcholine, and sterol ester metabolism were disrupted, highlighting the involvement of insulin resistance and oxidative stress in T2DM progression. Moreover, 13 lipid metabolites exhibited diagnostic potential for T2DN, showing consistent trends of increase or decrease as the disease progressed. Conclusion: Our findings underscore the importance of lipid metabolism in T2D development and identify potential lipid biomarkers for early diagnosis and monitoring of disease progression, which contribute to paving the way for novel therapeutic strategies. Full article

Objectives: A common complication in patients with rheumatoid arthritis (RA) is interstitial lung disease (ILD). Antibodies (Abs) to anti-aminoacyl-transfer ribonucleic acid synthetase (ARS) are linked to ILD in patients with idiopathic inflammatory myopathies (IIM). There have been limited studies of anti-ARS Abs in RA. In this study, we examined anti-ARS Abs in ILD in patients with RA. Methods: Anti-ARS Abs in serum from patients with RA were measured. Results: There were higher anti-ARS Ab levels in RA patients with ILD (mean ± SDM, 16.3 ± 32.3 vs. 7.4 ± 7.0 (Index), p = 5.58 × 10⁻¹²), usual interstitial pneumonia (14.4 ± 24.4 vs. 7.4 ± 7.0 [Index], p = 3.14 × 10⁻¹²), and nonspecific interstitial pneumonia (17.9 ± 37.7 vs. 7.4 ± 7.0 (Index), p = 5.07 × 10⁻⁵) compared with patients without chronic lung disease. The area under the curve (AUC) of the receiver operating characteristic curve for anti-ARS Ab was too low to allow for discrimination among RA patients with/without chronic lung disease (0.608, 95% confidence interval (CI) 0.560–0.655, p = 8.69 × 10⁻⁶). Multiple logistic regression analyses of age, smoking status, anti-ARS Abs, as well as Steinbrocker stage generated an ARS-index with a high AUC value (0.707, 95%CI 0.662–0.752, p = 2.20 × 10⁻¹⁹). Conclusions: Anti-ARS Abs are related to ILD pathogenesis in RA and may be a biomarker for ILD. Full article

Acute kidney injury (AKI) constitutes a common complication associated with liver or kidney transplantation, which may significantly impact the graft condition and perioperative mortality. Current AKI diagnostic criteria based on serum creatinine (sCr) and urine output alterations are widely utilized in routine clinical practice. However, the diagnostic value of sCr may be limited by various confounding factors, including age, sex, reduced or increased muscle mass, and pre-existing chronic kidney disease (CKD). Furthermore, sCr is rather a late indicator of AKI, as its concentration tends to increase only when the severity of the injury is enough to decrease the estimated glomerular filtration rate (eGFR). Recent expertise highlights the need for novel biomarkers in post-transplantation AKI diagnosis, prediction of event-associated mortality, or evaluation of indications for renal replacement treatment (RRT). Over the last decade, the diagnostic performance of various AKI biomarkers has been assessed, among which some showed the potential to outperform sCr in AKI diagnosis. Identifying susceptible individuals, early diagnosis, and prompt intervention are crucial for successful transplantation, undisturbed graft function in long-term follow-up, and decreased mortality. However, the research on AKI biomarkers in transplantation still needs to be explored. The field lacks consistent results, rigorous study designs, and external validation. Considering the rapidly growing prevalence of CKD and cirrhosis that are associated with the transplantation at their end-stage, as well as the existing knowledge gap, the aim of this article was to provide the most up-to-date review of the studies on novel biomarkers in the diagnosis of post-transplantation AKI. Full article

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that causes extensive damage to multiple organs and tissues and has no known cure. This study introduces a microfluidic detection platform that combines a microfluidic reaction chip with a micro-spectrometer to accurately detect the anti-cyclic citrullinated peptide antibody (anti-CCP Ab) biomarker, commonly associated with arthritis. The surface of the microfluidic reaction chip is functionalized using streptavidin to enable the subsequent immobilization of biotinylated-labeled cyclic citrullinated peptide (biotin–CCP) molecules through a streptavidin–biotin reaction. The modified chip is then exposed to anti-CCP Ab, second antibody conjugated with horseradish peroxidase (HRP) (2nd Ab-HRP), 3,3′,5,5′-tetramethylbenzidine (TMB), and a stop solution. Finally, the concentration of the anti-CCP Ab biomarker is determined by analyzing the optical density (OD) of the colorimetric reaction product at 450 nm using a micro-spectrometer. The detection platform demonstrated a strong correlation (R² = 0.9966) between OD and anti-CCP Ab concentration. This was based on seven control samples with anti-CCP Ab concentrations ranging from 0.625 to 100 ng/mL. Moreover, for 30 artificial serum samples with unknown anti-CCP Ab concentrations, the biosensor achieves a correlation coefficient of (R² = 0.9650). The proposed microfluidic detection platform offers a fast and effective method for accurately identifying and quantifying the anti-CCP Ab biomarker. Thus, it offers a valuable tool for the early diagnosis and monitoring of RA and its progression in point-of-care settings. Full article

This study focused on evaluating the anti-obesity effects of an extract from Ampelopsis grossedentata (Hand.-Mazz.) W. T. Wang, also known as vine tea, in mature adipocytes and high-fat diet-induced obese mice. Vine tea extract (VTE) effectively decreased lipid accumulation in mature adipocytes without cytotoxicity, as confirmed by the regulation of several factors associated with adipogenesis, lipogenesis, or lipolysis. Subsequently, in a 12-week experiment with obese mice, oral VTE administration significantly reduced body weight gain induced with high-fat diet intake. Au-topsy findings showed reduced fat accumulation in various areas without liver damage. The VTE-administered group showed lower serum LDL levels, while increasing HDL, than the high-fat diet-administered group. Analysis of adipose tissue biomarkers indicated VTE’s ability to inhibit adipogenesis and lipogenesis, promote lipolysis, and regulate energy metabolism, contributing to reduced adiposity induced by the consumption of a high-fat diet. Full article

Background: The gut–lung axis could be a potential therapeutic target for improving post-acute COVID-19 symptoms, and probiotics have been proposed as possible modulators. Aim: We conducted a pilot study to understand alterations in the gut–lung axis and to explore the effects of a probiotic in post-acute COVID-19 disease. Methods: We included patients after severe COVID-19 disease (sCOV, n = 21) in a randomized, placebo-controlled trial to test the effect of a probiotic (Pro-Vi 5, Institute Allergosan, Graz, Austria) in a six-month intervention and used patients after mild disease (mCOV, n = 10) as controls, to compare the intestinal microbiome, metabolome, and patient-reported outcomes and biomarkers along the gut–lung axis at baseline and throughout probiotic intervention. Results: Compared to mCOV patients, sCOV patients showed lower microbial richness, which was significantly improved by probiotic intervention. A reorganization of Ruminococcaceae and Lachnospiraceae taxa was observed in sCOV patients but remained unaffected by the intervention. Serum metabolome showed a dysregulation of lipoproteins in accordance with higher BMI and comorbidities in sCOV patients. HDL and LDL fractions/components were temporarily decreased in the probiotic group. Stool metabolome was altered at baseline in sCOV patients and an increase in L-DOPA after 3 months and butyrate after 6 months of intervention could be observed. Probiotics partially improved reduced quality of life and modulated altered immune responses in sCOV patients. Increased intestinal permeability at baseline remained unaffected. Conclusion: The study provides evidence of long-term alterations of the gut–lung axis after severe COVID-19 infection and suggests that probiotics can modulate the biomarkers of the gut–lung axis. Full article

Background and Objectives: Heart failure (HF) is one of the most common initial presentations of cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM). There are different cardiac biomarkers related to the pathophysiological mechanisms of HF in T2DM. The current research aims to identify additional biomarkers that could improve the diagnosis and prognosis of HFpEF, which is currently assessed using NT pro-BNP levels. NT pro-BNP is a valuable tool for diagnosing heart failure but may not always correlate with clinical symptom severity or can present normal levels in certain cases, such as obesity. Biomarkers like FGF-21 and galectin-3 could provide greater insight into heart failure severity, especially in diabetic patients. The main objective of the current study is to assess the performance of NT-proBNP, FGF21, Galectin-3 and Copeptin to discriminate between advanced and mild HF. Materials and Methods: A total of 117 patients were enrolled in this study and divided into two groups: 67 patients in NYHA functional class I-II (mild HF) and 50 patients in NYHA III-IV (advanced HF). NT-pro BNP, FGF21, Galectin 3 and Copeptin serum levels were determined with the ELISA method. Receiver operating characteristic (ROC) analysis and binomial logistic regression analysis were used to measure the ability of the studied biomarkers to distinguish between advanced and mild HF patients. Results: In patients with T2DM with advanced HF, serum FGF21 level was significantly positively correlated with eGFR (ρ = 0.35, p = 0.0125) and triglycerides (ρ = 0.28, p = 0.0465) and significantly negatively correlated with serum levels of HDL cholesterol (ρ = −0.29, p = 0.0386) and with RV-RA gradient (ρ = −0.30, p = 0.0358). In patients with mild HF, serum FGF21 level was significantly negatively correlated with NT-proBNP levels (ρ = −0.37, p = 0.0022), E/e’ ratio (ρ = −0.29, p = 0.0182), TR velocity (ρ = −0.24, p = 0.0470) and RV-RA gradient (ρ = −0.24, p = 0.0472). FGF21 (AUC = 0.70, 95% CI: 0.60−0.79) and NT-proBNP (AUC = 0.73, 95% CI: 0.63–0.82) demonstrated significant predictive value to discriminate T2DM patients with advanced HF from those with mild HF. Elevated values for FGF21 (≥377.50 ng/mL) or NTproBNP (≥2379 pg/mL) were significantly associated with increased odds of advanced HF after adjusting for demographic and clinical covariates. Conclusions: NTpro-BNP and FGF21 have a similar ability to discriminate T2DM patients with advanced HF from those with mild HF. Univariable and multivariable logistic models showed that, FGF21 and NTproBNP were independent predictors for advanced HF in patients with preserved and mildly reduced ejection fraction and T2DM. Full article

Cardiac troponin serum concentration is a marker of myocardial injury, but NT-pro BNP is a marker of myocardial insufficiency. The purpose of this study was to determine binary logistic regression models to verify the possible association of cardiovascular risk indicators, pre-pandemic history, the number of times participants were infected with SARS-CoV-2, and vaccination against these biomarkers. A total of 281 residents of Trujillo city (Peru) participated between September and December 2023. We found a high prevalence of abdominal obesity of 55.2%; glycemia > 100 m/dL in 53%; hypercholesterolemia in 49.8%; low HDL in 71.9%; and LDL > 100 mg/dL in 78.6%. A total of 97.5% were vaccinated against COVID-19, and 92.2% had three or more doses. Also, 2.5% had cTnI > 0.05 ng/mL, and 3.3% had NT-proBNP > 125 pg/mL. The number of COVID-19 infections versus cTnI > 0.05 ng/mL presented an OR = 3.513 (p = 0.003), while for NT-proBNP > 125 pg/mL, the number of comorbidities presented an OR = 2.185 (p = 0.025) and LDL an OR = 0.209 (p = 0.025). A regression model was obtained in which there is an association between a higher number of COVID-19 infections and elevated cTnI values and a model implying an association of the number of comorbidities and LDL with the NT-proBNP level in a direct and inverse manner, respectively. Both models contribute to the prevention of cardiac damage. Full article

The aim of the present study was the evaluation of the bioaccumulation of cadmium (Cd), Zinc (Zn), Chrome (Cr), Lead (Pb), Iron (Fe) and Copper (Cu), in the blood, serum, tail and mane of horses from the industrialized area of Milazzo (Messina, Sicily), to understand the relationships between haematological parameters: Red Blood Cells (RBCs), White Blood Cells (WBCs), Haemoglobin (Hb), Haematocrit (Hct), Mean Corpuscular Volume (MCV), Mean Corpuscular Haemoglobin (MCH), Mean Corpuscular Haemoglobin Concentration (MCHC), Platelets (PLTs) and the concentrations of trace elements. Blood and hair samples from 20 healthy Italian Saddle horses and water, hay and concentrates samples were obtained to determine the haemogram and mineral concentration using a Thermo Scientific iCAP-Q ICP-MS spectrometer. Descriptive analysis showed a higher concentration of Zn, Cr, Pb, Fe, and Cu in the blood and a higher concentration of Cd in the tail than other substrates. A positive correlation was found for Cr (p < 0.0001) and Zn (p < 0.01) between blood and serum substrates, for Zn (p < 0.001) between mane and tail and for Pb (p < 0.01) between blood and mane, while a negative correlation was observed for Cr (p < 0.01) between blood and tail. Results showed a close relationship between the bioaccumulation of certain trace elements in biological substrates and haematological parameters, which represent useful biomarkers suggesting further studies, given the role of haematological parameters in athletic horses. Full article

Giant cell arteritis (GCA) is an autoimmune/autoinflammatory disease affecting large vessels in patients over 50 years old. The disease presents as an acute inflammatory response with two phenotypes, cranial GCA and large-vessel vasculitis (LV)-GCA, involving the thoracic aorta and its branches. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET-CT) is among the imaging techniques contributing to diagnosing patients with systemic disease. However, its association with soluble inflammatory markers is still elusive. This proof-of-concept study aims to identify novel soluble serum biomarkers in PET/CT-positive patients with LV-GCA and associate them with active (0 months) and inactive disease (6 months following treatment), in sequential samples. The most-diseased-segment target-to-background ratio (TBR_MDS) was calculated for 13 LV-GCA patients, while 14 cranial GCA and 14 Polymyalgia Rheumatica patients with negative initial PET/CT scans served as disease controls. Serum macrophage-related cytokines were evaluated by cytometric bead array (CBA). Finally, previously published NMR/metabolomics data acquired from the same blood sampling were analyzed along with PET/CT findings. TBR_MDS was significantly increased in active versus inactive disease (3.32 vs. 2.65, p = 0.006). The analysis identified nine serum metabolites as more sensitive to change from the active to inactive state. Among them, choline levels were exclusively altered in the LV-GCA group but not in the disease controls. Cytokine levels were not associated with PET/CT activity. Combining CRP, ESR, and TBR_MDS with choline levels, a composite index was generated to distinguish active and inactive LV-GCA (20.4 vs. 11.62, p = 0.001). These preliminary results could pave the way for more extensive studies integrating serum metabolomic parameters with PET/CT imaging data to extract sensitive composite disease indexes useful for everyday clinical practice. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is often asymptomatic and underdiagnosed; consequently, there is a demand for simple, non-invasive diagnostic tools. In this study, we developed a method to quantify liver steatosis based on miRNAs, present in liver and serum, that correlate with liver fat. The miRNAs were analyzed by miRNAseq in liver samples from two cohorts of patients with a precise quantification of liver steatosis. Common miRNAs showing correlation with liver steatosis were validated by RT-qPCR in paired liver and serum samples. Multivariate models were built using partial least squares (PLS) regression to predict the percentage of liver steatosis from serum miRNA levels. Leave-one-out cross validation and external validation were used for model selection and to estimate predictive performance. The miRNAseq results disclosed (a) 144 miRNAs correlating with triglycerides in a set of liver biobank samples (n = 20); and (b) 124 and 102 miRNAs correlating with steatosis by biopsy digital image and MRI analyses, respectively, in liver samples from morbidly obese patients (n = 24). However, only 35 miRNAs were common in both sets of samples. RT-qPCR allowed to validate the correlation of 10 miRNAs in paired liver and serum samples. The development of PLS models to quantitatively predict steatosis demonstrated that the combination of serum miR-145-3p, 122-5p, 143-3p, 500a-5p, and 182-5p provided the lowest root mean square error of cross validation (RMSECV = 1.1, p-value = 0.005). External validation of this model with a cohort of mixed MASLD patients (n = 25) showed a root mean squared error of prediction (RMSEP) of 5.3. In conclusion, it is possible to predict the percentage of hepatic steatosis with a low error rate by quantifying the serum level of five miRNAs using a cost-effective and easy-to-implement RT-qPCR method. Full article

Background/Objectives: Pentraxin 3 (PTX3), a member of the pentraxin superfamily, plays diverse roles in immunity and inflammation. Its dual role in tumorigenesis, exhibiting both protumoral and antitumoral effects, has been the subject of conflicting reports. High PTX3 expression levels in serum and tumor tissues have been associated with poor prognosis in various malignancies, suggesting its potential as a prognostic biomarker. Through this meta-analysis, we aim to comprehensively assess the prognostic significance of PTX3 protein expression in human malignancies and evaluate its potential as a pan-cancer prognostic marker. Methods: A systematic literature search was conducted across the PubMed, Embase, Web of Science, MEDLINE, and Cochrane Library databases. Studies were included if they assessed the association between PTX3 protein expression and overall survival (OS) in cancer patients. Hazard ratios (HRs) were pooled using a random-effects model. Subgroup analyses were performed based on the method of PTX3 assessment, and publication bias was evaluated using Egger’s and Begg’s tests. Results: Nine studies encompassing 1215 patients were included in the analysis. High PTX3 expression was significantly associated with poorer OS (HR = 1.89, 95% CI = 1.55–2.32, p < 0.01) with no significant heterogeneity (I² = 0%). Subgroup analysis revealed consistent results across different assessment methods (immunohistochemistry: HR = 1.93, p < 0.01; immunoassay: HR = 1.86, p < 0.01). However, publication bias was detected (Egger’s test, p = 0.03). Conclusions: High PTX3 protein expression is associated with a poor prognosis in various malignancies, supporting its potential as a prognostic biomarker. Full article