Search Results (931)

Alzheimer’s disease (AD) requires early and accurate identification of affected brain regions, which can be achieved through the detection of specific biomarkers to enable timely intervention. Carbon nanomaterials (CNMs), including graphene derivatives, carbon nanotubes, graphitic carbon nitride, carbon black, fullerenes, and carbon dots, offer high conductivity, large electroactive surface area, and versatile surface chemistry that enhance biosensor performance. While such properties benefit a wide range of transduction principles (e.g., electrochemical, optical, and plasmonic), this review focuses on their role in electrochemical biosensors. This review summarizes CNM-based electrochemical platforms reported from 2020 to mid-2025, employing aptamers, antibodies, and molecularly imprinted polymers for AD biomarker detection. Covered topics include fabrication strategies, transduction formats, analytical performance in complex matrices, and validation. Reported devices achieve limits of detection from the femtomolar to picogram per milliliter range, with linear ranges typically spanning 2–3 orders of magnitude (e.g., from femtomolar to picomolar, or from picogram to nanogram per milliliter levels). They exhibit high selectivity against common interferents such as BSA, glucose, uric acid, ascorbic acid, dopamine, and non-target peptides, along with growing capabilities for multiplexing and portable operation. Remaining challenges include complex fabrication, limited long-term stability and reproducibility data, scarce clinical cohort testing, and sustainability issues. Opportunities for scalable production and integration into point-of-care workflows are outlined. Full article

Purpose: This study sets out to analyze the correlation of ET-1, a vasoactive peptide, along with various cytokines and vascular factors, with clinical parameters and OCT/OCT-A measurements in glaucoma participants. Methods: Eyes of participants with cataract (n = 30) or glaucoma (n = 87) were examined with optical coherence tomography (OCT) and OCT angiography (OCT-A). Aqueous humor (AqH) from the examined eye and plasma were sampled during cataract or glaucoma surgery and analyzed by means of ELISA and Luminex assay to determine their levels of ET-1 and 35 proteins deemed relevant for regulation of the AqH outflow pathway, ocular perfusion (OP), and glucose metabolism. Results: Glaucomatous eyes are characterized by reductions in RNFL thickness and OP, reflected by reduced vessel density. Furthermore, significantly elevated peripheral ET-1 levels were detected in participants with glaucoma. In addition, significantly elevated AqH levels of MMP-2, MMP-3, ET-1, sEMMPRIN, ZAG, sLOX-1, follistatin, cortisol, endostatin, sTIE-2, and PDGF-BB were detected in the glaucomatous eyes, with correlation to reduced VD for APN, C3a, MMP-3, resistin, sTIE-2, and ZAG. Multivariable analysis showed a correlation of AqH APN levels with the reduced VD in glaucomatous eyes. Conclusions: The peripheral ET-1 level and the intraocular levels of APN, C3a, MMP-3, resistin, sTIE-2, and ZAG are associated with impaired OP in glaucoma. Furthermore, elevated intraocular levels of MMP-3, ZAG, and APN were identified as biomarkers for impaired perfusion in glaucoma. Full article

Diabetes mellitus is a chronic metabolic disorder characterised by impaired glucose regulation, leading to severe complications affecting multiple organ systems. Current diagnostic approaches primarily rely on glucose monitoring, which, while being effective, fails to capture the underlying molecular changes associated with disease progression. Emerging biomarkers such as microRNAs (miRNAs) and adipokines offer new insights into diabetes pathophysiology, providing potential diagnostic and prognostic value beyond traditional methods. Given this, precise monitoring of the altered levels of miRNAs and adipokines can forge a path towards early diabetes diagnosis and improved disease management. Biosensors have revolutionised diabetes diagnostics, with glucose biosensors dominating the market for decades. However, recent advancements in nanobiosensors have expanded their scope beyond glucose detection, enabling highly sensitive and selective monitoring of biomolecular markers like miRNAs and adipokines. These nanotechnology-driven platforms offer rapid, inexpensive, and minimally invasive detection strategies, paving the way for improved disease management. This review provides an overview of diabetes, along with its pathogenesis, complications, and demographics, and explores the clinical relevance of miRNAs and adipokines as emerging biomarkers. It further examines the evolution of biosensor technologies, highlights recent developments in nanobiosensors for biomarker detection, and critically analyses the challenges and future directions in this growing field. Full article

The gut microbiome is strongly implicated in the development of obesity and type 2 diabetes mellitus (T2DM). A recent study demonstrated that 6-week oral supplementation of Anaerostipes rhamnosivorans (ARHAM) combined with the prebiotic myo-inositol (MI) reduced fasting glucose levels in mice. In the present study, we investigated the effects of a 13-week ARHAM-MI supplementation in high-fat diet-fed mice and examined the metabolic fate of MI, including its microbial conversion into short-chain fatty acids (SCFAs), using ¹³C-MI and stable isotope tracers in the cecum, portal vein, and peripheral blood. The results showed that the ARHAM-MI group gained less weight than the MI-only and placebo groups. Analysis of intestinal mRNA and stable isotope tracing revealed that MI is primarily absorbed in the upper gastrointestinal tract, whereas microbial conversion to SCFAs predominantly occurs in the cecum and is enhanced by ARHAM. ARHAM-MI mice also showed increased cecal Gpr43 mRNA expression, indicating enhanced SCFA-mediated signaling. Notably, SCFAs derived from MI displayed distinct distribution patterns: ¹³C-butyrate was detected exclusively in the cecum, ¹³C-propionate was present in the cecum and portal vein, whereas ¹³C-acetate was the only SCFA detected in peripheral blood. Collectively, ARHAM-MI co-supplementation confers modest metabolic benefits in high-fat diet-fed mice, underscoring the need to optimize the dosage and administration frequency of ARHAM-MI to enhance its therapeutic efficacy. Full article

Monitoring dopamine (DA) has attracted increasing attention due to alterations in DA levels associated with brain disorders. In addition, the urinary DA concentration plays a significant role in the sympathoadrenal system. A decrease in DA can impair reward-seeking behavior and cognitive flexibility. Therefore, accurate and precise DA detection is necessary. In this study, a poly(3-aminobenzylamine)/functionalized multi-walled carbon nanotube (PABA/f-CNT) composite thin film was fabricated by electrochemical synthesis, or electropolymerization, of 3-aminobenzylamine (3-ABA) monomer and f-CNTs through cyclic voltammetry (CV) on a fluorine-doped tin oxide (FTO)-coated glass substrate, which also served as a working electrode for label-free DA detection in artificial urine. The formation of the film was confirmed by the obtained cyclic voltammogram, electrochemical impedance spectroscopy (EIS) plots, and scanning electron microscope (SEM) and transmission electron microscope (TEM) images. The chemical components of the films were analyzed using attenuated total reflection–Fourier transform infrared (ATR–FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS). For label-free DA detection, various concentrations (50–1000 nM) of DA were determined in buffer solution through differential pulse voltammetry (DPV). The fabricated PABA/f-CNT film presented two linear ranges of 50–400 nM (R² = 0.9915) and 500–1000 nM (R² = 0.9443), with sensitivities of 1.97 and 0.95 µA·cm⁻²·µM⁻¹, respectively. The limit of detection (LOD) and the limit of quantity (LOQ) were 119.54 nM and 398.48 nM, respectively. In addition, the PABA/f-CNT film provided excellent selectivity against common interferents (ascorbic acid, uric acid, and glucose) with high stability, reproducibility, and repeatability. For potential future medical applications, DA detection was further performed in artificial urine, yielding a high percentage of recovery. Full article

Diabetes, a chronic metabolic disease marked by elevated blood glucose levels, affects millions of people globally. A lower quality of life and a markedly higher chance of potentially deadly consequences, such as heart disease, renal failure, and other organ dysfunctions, are closely linked to it. In order to effectively manage diabetes and avoid serious consequences, early detection and ongoing monitoring are essential. Remote health monitoring has emerged as a viable and promising option for proactive healthcare due to the development of contemporary technology, particularly in the areas of wearables and mobile computing. In this work, we suggest a thorough and sophisticated framework for remote monitoring that is intended to automatically predict, identify, and manage diabetes risks. To facilitate real-time data collection analysis and tailored feedback, the system makes use of the integration of smartphones, wearable sensors, and specialized medical equipment. In addition to enhancing patient engagement and lowering the strain on conventional healthcare infrastructures, our suggested model aims to assist patients and healthcare providers in maintaining improved glycemic control. We employed a tenfold stratified cross-validation approach to assess the efficacy of our framework and the results showed remarkable performance metrics. A score of 79.00 percent for clarity (specificity) 87.20 percent for sensitivity, and 83.20 percent for accuracy were all attained by the system. The outcomes show how our framework can be a dependable and scalable remote diabetes management solution, opening the door to more intelligent and easily accessible healthcare systems around the world. Full article

Paper-based electrochemical biosensors have emerged as a revolutionary technology in healthcare diagnostics due to their affordability, portability, ease of use, and environmental sustainability. These biosensors utilize paper as the primary material, capitalizing on its unique properties such as high porosity, flexibility, and capillary action, which make it an ideal candidate for low-cost, functional, and reliable diagnostic devices. The simplicity and cost-effectiveness of paper-based biosensors make them especially suitable for point-of-care (POC) applications, particularly in resource-limited settings where traditional diagnostic tools may be inaccessible. Their lightweight nature and ease of operation allow non-specialized users to perform diagnostic tests without the need for complex laboratory equipment, making them suitable for emergency, field, and remote applications. Technological advancements in paper-based biosensors have significantly enhanced their capabilities. Integration with microfluidic systems has improved fluid handling and reagent storage, resulting in enhanced sensor performance, including greater sensitivity and specificity for target biomarkers. The use of nanomaterials in electrode fabrication, such as reduced graphene oxide and gold nanoparticles, has further elevated their sensitivity, allowing for the precise detection of low-concentration biomarkers. Moreover, the development of multiplexed sensor arrays has enabled the simultaneous detection of multiple biomarkers from a single sample, facilitating comprehensive and rapid diagnostics in clinical settings. These biosensors have found applications in diagnosing a wide range of diseases, including infectious diseases, cancer, and metabolic disorders. They are also effective in genetic analysis and metabolic monitoring, such as tracking glucose, lactate, and uric acid levels, which are crucial for managing chronic conditions like diabetes and kidney diseases. In this review, the latest advancements in paper-based electrochemical biosensors are explored, with a focus on their applications, technological innovations, challenges, and future directions. Full article

Although cardiac metabolic adaptation has been observed in response to the ischemia–reperfusion, the specific temporal and spatial changes occurring in the main regulators of myocardial glucolipid metabolism in the infarcted heart have not been fully characterized. Myocardial infarction (MI) was induced in female swine by transient coronary occlusion. The study design consisted of one control and four MI groups (no reperfusion, 1 min, 1 week, and 1 month after reperfusion). Metabolites obtained from the coronary sinus were determined at baseline, during ischemia, and after coronary reperfusion. mRNA expression of genes related to beta-oxidation and glucose transport were quantified in the five experimental groups and in three myocardial regions (infarcted, adjacent, and remote). In the coronary sinus, reduced glucose and increased lactate levels were detected during ischemia and soon after reperfusion. However, non-esterified fatty acids increased during reperfusion. A general upregulation of genes implicated in glycolysis and beta-oxidation occurred during ischemia and few minutes after reperfusion. Contrarily, heightened mRNA expression of glucose transporters and decay in regulators of beta-oxidation were observed one week after coronary reperfusion. Glycolysis and beta-oxidation are activated during ischemia and few minutes after coronary reopening, while a shift from beta-oxidation to glycolysis is evidenced a few days afterwards. Full article

Background: Insulin resistance (IR) is a central feature in the pathophysiology of type 2 diabetes and a major determinant of cardiovascular morbidity. While sociodemographic and lifestyle factors are established contributors, the role of social isolation as a potential determinant of IR remains underexplored in working populations. Objectives: To assess the association between sociodemographic variables, lifestyle habits, and social isolation with three validated insulin resistance indexes—Triglyceride–Glucose (TyG), Metabolic Score for Insulin Resistance (METS-IR), and Single Point Insulin Sensitivity Estimator (SPISE-IR)—in a large cohort of Spanish workers. Methods: A cross-sectional study was conducted involving 117,298 workers from occupational health centers across Spain. Sociodemographic data, lifestyle factors (Mediterranean diet adherence, physical activity, and smoking), and social support levels (ENRICHD Social Support Instrument) were recorded. Biochemical and anthropometric parameters were obtained through standardized protocols. Logistic regression models estimated the odds ratios (ORs) and 95% confidence intervals (CIs) for high IR risk across the three indexes, adjusting for potential confounders. Results: Male sex, older age, lower social class, smoking, low Mediterranean diet adherence, physical inactivity, and low social support were independently associated with higher odds of IR in all three indexes. The strongest associations were observed for physical inactivity (OR range 6.21–9.95) and low social support (OR range 1.98–3.76). Although effect sizes varied by index, patterns of association were consistent. Conclusions: Sociodemographic, lifestyle, and psychosocial factors, including social isolation, are strongly associated with insulin resistance in working populations. Integrating social support assessment into occupational health strategies may enhance early detection and prevention of IR and related cardiometabolic diseases. Full article

Microbial enzymes, due to their efficiency, specificity, and sustainability, are central to innovative biotechnological strategies aimed at optimizing industrial processes such as winemaking. In this study, the potential of Aureobasidium pullulans m11-2, a native dimorphic fungus from the wine ecosystem, was evaluated as a source of hydrolytic enzymes capable of degrading grape cell wall polysaccharides. The strain was identified at the molecular level and characterised in terms of its morphology. To maximise enzyme production, various culture media were tested. Among the concentrations tested, the optimal levels of glucose and pectin were 1 g L⁻¹ and 10 g L⁻¹, respectively. The partially constitutive and inducible nature of the various polysaccharidase activities (pectinases, cellulases, and xylanases) was confirmed. The effect of grape skins (a winemaking by-product) on microbial growth and enzyme synthesis was evaluated, achieving a pectinase activity of 0.622 U mL⁻¹ when combined with 1 g L⁻¹ of glucose. Maximum enzyme yields were detected during the exponential growth phase in both citrus pectin and grape skin media, suggesting favorable conditions for continuous bioprocessing. These results confirm that A. pullulans m11-2 is an interesting microbial option for producing polysaccharidases that can be adapted to sustainable production systems. Full article

Environmental salinity is a critical factor influencing the physiological and metabolic processes of teleosts. Despite its importance, the molecular mechanisms underlying these responses, particularly those involving specific signaling pathways and gene expression regulation, remain poorly understood. To elucidate the role of lipid metabolism in osmotic regulation, the present study investigated the effects of varying salinity levels (2, 20, 40, and 60 ppt) on growth performance and metabolic status, including the biosynthesis of LC-FAs and VLC-FAs, respectively, in neural tissues (brain and eyes), of the euryhaline fish Fundulus heteroclitus over a 62-day period. The findings revealed multiple physiological adaptations to salinity variation, encompassing both molecular and metabolic responses. Salinity had a significant impact on growth performance, with fish exposed to the highest salinity level (60 ppt) exhibiting reduced growth. At this salinity, plasma levels of lipid-related metabolites, i.e., triglycerides and cholesterol, were decreased, whereas both osmolality and cortisol levels increased. Hepatic glucose and lactate levels increased with rising salinity, while glucose and triglyceride concentrations in muscle tissue declined. Additionally, intestinal lipase activity was significantly higher at 60 ppt. Although no significant differences were observed in the total UFAs content of both tissues, in the brain, significant differences were detected in the levels of 16:1n-7, 18:1n-9, 18:2n-6, 20:3n-3, 20:4n-6, and 20:5n-3, whereas in the eye, differences were observed only for 16:1n-7 and 20:5n-3. Gene expression analysis revealed that salinity exerts a regulatory effect on the expression of fads2b and elovl4a in the eye, with up-regulation observed at 60 ppt. In contrast, no significant changes in the expression of fads or elovl genes were detected in the brain. These findings highlight the contribution of non-osmoregulatory organs, such as the brain and eyes, in the osmotic adaptation of teleosts. Collectively, the results suggest that lipid metabolism plays a key regulatory role in the adaptation of F. heteroclitus to salinity fluctuations. Full article

(1) Background: Gestational diabetes mellitus (GDM) is a glucose metabolism disorder that typically develops in the second half of pregnancy, transforming a normal pregnancy into a high-risk condition, with both short- and long-term complications for the mother and the fetus. Achieving optimal glycaemic control during pregnancy is essential for preventing these outcomes and could be realized using continuous glucose monitoring systems (CGMSs). This systematic review aims to evaluate the role of the CGMS as a potential diagnostic aid and predictor of maternal and fetal outcomes in GDM. (2) Methods: Following the PRISMA guidelines (protocol ID: CRD42024559169), we performed a literature search using the terms “(continuous glucose monitoring system OR CGMS) AND (gestational diabetes mellitus OR GDM)” in the PubMed, Web of Science, and Scopus databases. (3) Results: Twelve studies were included, all reporting data on CGMS use in pregnancies complicated by GDM. The data included in our analysis are heterogeneous, the results suggesting that the CGMS may offer several advantages such as improved glycaemic control (by avoiding hyper- and hypoglycaemia), better gestational weight management, timely initiation of pharmacologic treatment, lower rates of preeclampsia, and improved neonatal outcomes. (4) Conclusions: the CGMS offers a more detailed assessment of both maternal and fetal exposure to high glucose levels, which could lead to earlier detection of those at risk for GDM complications and better guide treatment regimens, especially timely pharmacological intervention. While the current data are heterogeneous, reporting both limited or no benefits and superior benefits compared to the classic monitoring, larger longitudinal studies are mandatory to validate these findings and to better refine the role of CGMS in the monitoring and management of GDM. Full article

One hundred and eighteen years have passed since Alzheimer’s disease (AD) was first diagnosed by Alois Alzheimer as a multifactorial and complex neurodegenerative disorder with psychiatric components. It is inaugurated by a cascade of events initiating from amnesic-type memory impairment leading to the gradual loss of cognitive and executive capacities. Pathologically, there is overwhelming evidence that clumps of misfolded amyloid-β (Aβ) and hyperphosphorylated tau protein aggregate in the brain. These pathological processes lead to neuronal loss, brain atrophy, and gliosis culminating in neurodegeneration and fueling AD. Thus, at a basic level, abnormality in the brain’s protein function is observed, causing disruption in the brain network and loss of neural connectivity. Nevertheless, AD is an aging disorder caused by a combination of age-related changes and genetic and environmental factors that affect the brain over time. Its mysterious pathology seems not to be limited to senile plaques (Aβ) and neurofibrillary tangles (tau), but to a plethora of substantial and biological processes, which have also emerged in its pathogenesis, such as a breakdown of the blood–brain barrier (BBB), patients carrying the gene variant APOE4, and the immuno-senescence of the immune system. Furthermore, type 2 diabetes (T2DM) and metabolic syndrome (MS) have also been observed to be early markers that may provoke pathogenic pathways that lead to or aggravate AD progression and pathology. There are numerous substantial AD features that require more understanding, such as chronic neuroinflammation, decreased glucose utilization and energy metabolism, as well as brain insulin resistance (IR). Herein, we aim to broaden our understanding and to connect the dots of the multiple comorbidities and their cumulative synergistic effects on BBB dysfunction and AD pathology. We shed light on the path-physiological modifications in the cerebral vasculature that may contribute to AD pathology and cognitive decline prior to clinically detectable changes in amyloid-beta (Aβ) and tau pathology, diagnostic biomarkers of AD, neuroimmune involvement, and the role of APOE4 allele and AD–IR pathogenic link—the shared genetics and metabolomic biomarkers between AD and IR disorders. Investment in future research brings us closer to knowing the pathogenesis of AD and paves the way to building prevention and treatment strategies. Full article

Blood glucose monitoring is crucial for the daily management of diabetic patients. In this study, we developed a differential absorbance and photoplethysmography (PPG)-based non-invasive blood glucose measurement system (NIBGMS) using visible–near-infrared (Vis-NIR) light. Three light-emitting diodes (LEDs) (625 nm, 850 nm, and 940 nm) and three photodetectors (PDs) with different source–detector separation distances were used to detect the differential absorbance of tissues at different depths and PPG signals of the index finger. A spatiotemporal multimodal fused long short-term memory (STMF-LSTM) model was developed to improve the prediction accuracy of blood glucose levels by multimodal fusion of optical spatial information (differential absorbance and PPG signals) and glucose temporal information. The validity of the NIBGMS was preliminarily verified using multilayer perceptron (MLP), support vector regression (SVR), random forest regression (RFR), and extreme gradient boosting (XG Boost) models on datasets collected from 15 non-diabetic subjects and 3 type-2 diabetic subjects, with a total of 805 samples. Additionally, a continuous dataset consisting 272 samples from four non-diabetic subjects was used to validate the developed STMF-LSTM model. The results demonstrate that the STMF-LSTM model indicated improved prediction performance with a root mean square error (RMSE) of 0.811 mmol/L and a percentage of 100% for Parkes error grid analysis (EGA) Zone A and B in 8-fold cross validation. Therefore, the developed NIBGMS and STMF-LSTM model show potential in practical non-invasive blood glucose monitoring. Full article

Carbohydrates are a primary nutrient for plant growth, and sugar transporter proteins play a crucial role in sugar allocation. In this study, hexose transporter genes encoding in the genome of colored calla lily ‘Jingcai Yangguang’ (Zantedeschia elliottiana cv. Jingcai Yangguang) were identified, and their expression patterns following infection by Pectobacterium carotovora subsp. Carotovora were investigated. Additionally, the transport characteristics of three hexose transporters, ZeSTP7, ZeSTP15, and ZeSTP17, were determined. The results showed that the sugar transporter protein family in Z. elliottiana comprises 18 members, most of which possess 12 transmembrane domains. Phylogenetic analysis revealed that the ZeSTP gene family was divided into five subgroups. Tandem gene duplication events were identified on the 16 chromosomes of Z. elliottiana, with multiple tandemly duplicated genes detected. Comparative analysis of synteny between species identified ZeSTP8 and OsSTP22 as homologous gene pairs, while OsSTP6 (OsMST6) was identified as a homologous gene pair with both ZeSTP14 and ZeSTP17. Following infection by P. carotovora subsp. carotovora, the transcript levels of ZeSTP7, ZeSTP15, and ZeST17 were all significantly elevated. Yeast mutant hexose complementation tests indicated that ZeSTP7 could transport glucose and galactose, whereas ZeSTP15 and ZeSTP17 exhibited limited transport capacity in this respect. This study provides a systematic identification and analysis of hexose transporter genes at the genome-wide level, highlighting the role of ZeSTP genes in the response of colored calla lily to soft rot and laying a theoretical foundation for further understanding the functions of sugar transporter genes. Full article