Search Results (353)

Background: Uric acid (UA) is linked to gout, renal dysfunction, and cardiovascular disease. Prior studies often assume linear relationships, potentially oversimplifying physiological complexity. Methods: We analyzed data from 5200 healthy Taiwanese men. Demographic, biochemical, lifestyle, and inflammatory variables were assessed using Pearson correlation, multiple linear regression (MLR), and multivariate adaptive regression splines (MARS), an interpretable machine learning method for detecting nonlinear, threshold-based effects. Results: Pearson correlation showed broad linear associations, whereas MARS identified fewer but more physiologically meaningful predictors. Waist-to-hip ratio (WHR) had a strong threshold effect, influencing UA only below 0.969. Creatinine showed a nonlinear impact, becoming substantial above 0.97 mg/dL, suggesting a renal threshold within the “normal” range. Calcium and high-sensitivity C-reactive protein (hs-CRP) each displayed inflection points (9.5 mg/dL and 3.38 mg/L, respectively), indicating range-specific effects. Notably, betel nut exposure, nonsignificant in linear models, emerged in MARS as a predictor with a complex, non-binary association with UA metabolism. Predictive performance was comparable (RMSE: 1.6694 for MARS vs. 1.6666 for MLR), but MARS offered superior interpretability by highlighting localized nonlinear effects. Conclusions: MARS modeling revealed critical nonlinear, threshold-dependent associations between UA and WHR, creatinine, calcium, hs-CRP, and betel nut exposure, which were not captured by conventional methods. These findings underscore the value of interpretable machine learning in metabolic research and suggest precise thresholds for clinical risk stratification. Full article

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

This study reports on the direct electron transfer (DET) ability of the enzyme spermidine dehydrogenase (SpDH) and its use in a DET-type enzymatic sensor for detecting spermine. SpDH was found to exhibit internal electron transfer from its cofactor, flavin adenine dinucleotide (FAD), to heme b. This was confirmed by observing the heme b-derived reduction peak at 560 nm in the presence of spermine, the substrate. SpDH was immobilized on a gold electrode via a dithiobis (succinimidyl hexanoate) self-assembled monolayer. The cyclic voltammetry analysis of the SpDH-immobilized gold electrode revealed an increased oxidation current in the presence of 0.1 mM spermine with an onset potential of −0.14 V vs. Ag/AgCl in the absence of an additional external electron acceptor. This result confirmed that SpDH is capable of DET. Chronoamperometric analyses were conducted using an SpDH-immobilized gold electrode with spermine as the substrate under a 0 V oxidation potential vs. Ag/AgCl using an artificial saliva matrix containing 10 µM ascorbic acid and 100 µM uric acid. The sensor exhibited good linear correlation between the current increase and spermine concentration from 0.2 to 2.0 µM, with a limit of detection of 0.084 µM, which encompasses the physiologically relevant spermine concentration found in the saliva. Primary structure alignments and 3D structure predictions revealed that all SpDH homologs possess two conserved histidine residues in the same location on the surface as the heme b ligand of SpDH. This indicates their potential for DET-ability with an electrode. 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

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

In this study, a novel carbon quantum dots-functionalized UiO-66 composite was successfully prepared via the post-synthetic modification method and further developed into a ratiometric fluorescent probe for detecting uric acid. The composite demonstrates excellent structural and luminescent stability under challenging environmental conditions. As a ratiometric fluorescent probe, its recognition principle relies on the ratio of response signals from two different fluorescent emission centers in the composite. In the presence of uric acid, the fluorescence emission intensity at 430 nm from CDs did not change significantly. However, the fluorescence intensity at 545 nm from Tb³⁺ ions decreased remarkably. This material was evaluated for its capacity to sense urinary components and was shown to specifically recognize uric acid over a wide concentration range (0~5 × 10⁻³ M). Moreover, it exhibited strong resistance to interference and high sensitivity in uric acid detection. The detection limit (LOD) was determined to be 0.102 μM through quantitative analysis. The sensing mechanism was validated through spectral overlap and fluorescence lifetime analysis, which can be attributed to the fluorescence resonance energy transfer (FRET) process. This ratiometric fluorescent probe provides an efficient and reliable strategy for detecting the biomarker uric acid. Full article

Background/Objectives: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder affecting reproductive, metabolic, and inflammatory processes in women of reproductive age. This study explored the diagnostic potential of salivary cytokines, uric acid, and testosterone in distinguishing PCOS patients from healthy controls, as well as to examine their associations with hormonal and metabolic profiles within the PCOS group. Methods: Forty-one adolescent girls with PCOS and thirty healthy controls participated in the study. The PCOS group included both normal-weight and overweight individuals, allowing evaluation of salivary biomarkers across different nutritional statuses. Salivary levels of TNF-α, IL-6, IL-1β, testosterone, and uric acid were measured and compared between the groups. A receiver operating characteristic (ROC) analysis was performed to assess the diagnostic value of each biomarker. Results: Salivary TNF-α, IL-6, and IL-1β showed high diagnostic accuracy (AUC = 0.921, 0.891, and 0.870, respectively), supporting their potential as non-invasive biomarkers. The diagnostic accuracy of salivary cytokines and testosterone remained high even in normal-weight participants, suggesting that low-grade inflammation and hormonal disturbances in PCOS are not limited to excess body weight. Salivary testosterone was strongly associated with hyperandrogenism, while uric acid correlated with the cortisol/DHEA-S ratio, indicating possible links to metabolic stress. Conclusions: In conclusion, salivary assays may offer a valuable, non-invasive tool for the early diagnosis of PCOS in adolescents, including normal-weight girls. This approach could facilitate the timely detection of inflammatory and hormonal imbalances, supporting earlier interventions and more personalized care. Full article

Nickel-based metal–organic frameworks (Ni-MOFs) have received enormous amounts of attention from the scientific community due to their excellent porosity, larger specific surface area, tunable structure, and intrinsic redox properties. In previous years, Ni-MOFs and their hybrid composite materials have been extensively explored for electrochemical sensing applications. As per the reported literature, Ni-MOF-based hybrid materials have been used in the fabrication of electrochemical sensors for the monitoring of ascorbic acid, glucose, L-tryptophan, bisphenol A, carbendazim, catechol, hydroquinone, 4-chlorophenol, uric acid, kaempferol, adenine, _L-cysteine, etc. The presence of synergistic effects in Ni-MOF-based hybrid materials plays a crucial role in the development of highly selective electrochemical sensors. Thus, Ni-MOF-based materials exhibited enhanced sensitivity and selectivity with reasonable real sample recovery, which suggested their potential for practical applications. In addition, Ni-MOF-based hybrid composites were also adopted as electrode modifiers for the development of supercapacitors. The Ni-MOF-based materials demonstrated excellent specific capacitance at low current densities with reasonable cyclic stability. This review article provides an overview of recent advancements in the utilization of Ni-MOF-based electrode modifiers with metal oxides, carbon-based materials, MXenes, polymers, and LDH, etc., for the electrochemical detection of environmental pollutants and biomolecules and for supercapacitor applications. In addition, Ni-based bimetallic and trimetallic catalysts and their composites have been reviewed for electrochemical sensing and supercapacitor applications. The key challenges, limitations, and future perspectives of Ni-MOF-based materials are discussed. We believe that the present review article may be beneficial for the scientific community working on the development of Ni-MOF-based materials for electrochemical sensing and supercapacitor applications. Full article

Uric acid (UA) detection is critical for human health monitoring, necessitating the development of electrochemical sensing electrodes suitable for physiological environments. This study evaluated four 2D conductive metal–organic frameworks (2D c-MOFs), namely Cu-HHTP, Ni-HHTP, Cu-HAB, and Ni-HAB, which share identical graphene-like 2D sheet structures but differ in π-conjugation extent and catalytic active centers [MX₄] (M = Cu or Ni; X = O or NH) as electrosensing electrodes. Electrochemical sensing performance was compared by detecting UA in phosphate-buffered saline (PBS). Herein, the Ni-HHTP electrode demonstrated superior sensitivity (6.79 μA·μM⁻¹·cm⁻²), the lowest oxidation potential (0.272 V), and the lowest detection limit (0.44 μM). Langmuir adsorption isotherm analysis revealed that the Ni-HHTP electrode possesses the highest surface coverage (Γ_A) (5061.16 pmol cm⁻²) and the most favorable Gibbs adsorption free energy (ΔG°) (−18.775 kJ mol⁻¹), indicating its strongest UA adsorption capacity and molecular interaction. This enhanced performance is attributed to the optimal synergy between [NiO₄] catalytic centers and extended ligand π-conjugation, facilitating greater analyte adsorption and electron transfer efficiency. This work establishes clear structure–performance relationships for 2D c-MOF electrodes in UA detection, providing key insights for designing advanced electrosensing materials. Full article

Background/Objectives: The HLA-B*58:01 allele is strongly linked to severe cutaneous adverse reactions (SCARs) during allopurinol treatment, and it has been associated with the A allele of PSORS1C1 rs9263726 (G>A). Paraclinical characteristics of gout are indicative of associated comorbid conditions. This study investigated the genotype frequency of HLA-B*58:01 and its association with paraclinical characteristics and PSORS1C1 rs9263726 in gout patients from Northeast Vietnam. Methods: A total of 133 unrelated gout patients were randomly recruited by the clinician. BioEdit sequence alignment editor version 7.2.5 software (Raleigh, Raleigh, NC, USA) was used for the analysis of nucleotide sequence data of HLA-B gene alleles from the IPD-IMGT/HLA Database, which showed that the HLA-B*58:01 allele can be distinguished from reference and other alleles by specific nucleotide positions: 387C, 379C, 368A, 355A, and 353T (in exon 3); and 319C, 285G, and 209A (in exon 2). HLA-B*58:01 and PSORS1C1 rs9263726 genotypes were identified using Sanger sequencing of PCR products, analyzed with BioEdit software, and verified using the NCBI dbVar database. Statistical analyses were performed using SPSS version 25.0. Results: Our study revealed a significant age difference between male and female gout patients (p < 0.001). Male gout patients had an average age of 51.44 ± 14.59 years, whereas female gout patients were notably older, with an average age of 70.33 ± 10.64 years. Positive correlations were observed between platelet count, serum creatinine, and uric acid levels (r = 0.174, p = 0.045; r = 0.195, p = 0.025) in male gout patients, while only high-density lipoprotein cholesterol showed a statistically significant negative correlation with uric acid levels (r = −0.885, p = 0.002) in female patients. The HLA-B*58:01 allele frequency among study subjects was 6.02%, with 12.03% being heterozygous individuals (*X/HLA-B*58:01, N = 16). The HLA-B*58:01 allele was not detected in female gout patients. White blood cell counts were significantly higher in male gout patients with the *X/HLA-B*58:01 genotype compared to those with the *X/*X genotype (p = 0.018). The A allele frequency of PSORS1C1 rs9263726 was 7.89%, and the heterozygous mutant genotype PSORS1C1 GA had a frequency of 15.79% (N = 21). Among the *X/*58:01 carriers, 4.51% had the GG genotype, and 7.52% had the GA genotype at PSORS1C1 rs9263726. Conclusions: Our study showed that the HLA-B*58:01 allele was not detected in female gout patients. White blood cell counts differed significantly between the *X/HLA-B*58:01 and *X/*X groups in male gout patients. The A allele of PSORS1C1 rs9263726 was not consistently associated with HLA-B*58:01 and was not a reliable marker for its detection in this study population. Full article

Background and Objectives: The uric acid to HDL-cholesterol ratio (UHR) has recently emerged as a promising biomarker reflecting systemic inflammation and metabolic disturbances. Elevated liver transaminases are clinical indicators of hepatic injury and underlying metabolic dysfunction. Many Middle Eastern countries face constrained clinical and laboratory resources, where access to comprehensive diagnostic tools may be limited. In such settings, identifying simple and easily accessible markers could offer significant practical value in detecting and monitoring health disorders. This study investigates the potential association between UHR and elevated liver transaminases levels in the Saudi general population. Materials and Methods: This retrospective cross-sectional study included 9618 subjects, and the association between the UHR and elevated liver transaminases, alanine transaminase (ALT), and aspartate transaminase (AST), was comprehensively analysed. In addition, the study assessed risk indicators including the prevalence ratio (PR) and odds ratio (OR) as well as the diagnostic accuracy of UHR and C-reactive protein (CRP) in detecting liver transaminases abnormalities, with analyses stratified by age and gender. Results: UHR was significantly elevated in subjects with increased ALT and AST activities, and this pattern was consistent across all age and gender categories. High UHR was significantly associated with elevated ALT (OR = 2.32, 95% CI: 2.12–2.53, p < 0.001) and AST (OR = 1.38, 95% CI: 1.25–1.52, p < 0.001), with stronger associations observed in males and for ALT activity. In addition, elevated UHR was more prevalent among individuals with increased liver transaminase activities. Receiver operating characteristic (ROC) analysis showed that UHR outperformed CRP in identifying elevated liver transaminases, with better discriminative ability for ALT than AST activity. Conclusions: These findings highlight a significant association between UHR and liver transaminase abnormalities in the general population, underscoring the potential utility of UHR as a simple and accessible indicator for liver function assessment in clinical settings. Full article

At emergency sites, bacteria in the environment can cause secondary wound infections. Timely treatment of infected wounds can improve the prognosis. In this study, we designed a closed-loop system for real-time wound infection monitoring and electronically controlled drug release, enabling rapid and stable deployment at disaster sites. Multilayer screen-printed electrodes were developed to detect uric acid (UA), pH, and temperature biomarkers. The electrode’s outermost layer was shielded by a zwitterionic conductive hydrogel (Gel) to prevent environmental interference and achieve systematic antibacterial protection through in situ reduction of silver nanoparticles (AgNPs) on its surface. For rapid and efficient drug delivery, amikacin (Ami) loaded cationic liposomes (Lipo) embedded in the zwitterionic conductive hydrogel (Gel-Lipo@Ami) were integrated as the core therapeutic carrier. This closed-loop system provides timely infection detection and enables in situ treatment during emergency rescues. Full article

Ascorbic acid (AA) is a vital biomarker for human metabolic processes, and many diseases are strongly linked to aberrant variations in its content. It is crucial to detect the levels of AA with sensitivity, speed, and accuracy. In this work, three-dimensional honeycomb-like porous carbons derived from discarded walnut (green) husks (DWGH-HCPCs) were synthesized using a process involving hydrothermal treatment, freeze-drying, and carbonization. The DWGH-HCPCs, with a high specific surface area of 419.72 m² g⁻¹, large pore volume of 0.35 cm³ g⁻¹ and high density of defective sites, are used to fabricate the electrochemical sensor for the detection of AA. The electrochemical performance of the DWGH-HCPC-modified glassy carbon electrode (GCE) (DWGH-HCPC/GCE) was investigated through chronoamperometry, differential pulse voltammetry, and cyclic voltammetry. Compared with the GCE, the DWGH-HCPC/GCE exhibits higher sensitivities (34.7 μA mM⁻¹ and 22.7 μA mM⁻¹), a wider linear range (10–1040 μM and 1040–3380 μM), and a lower detection limit (0.26 μM) for AA detection. Specifically, the real sample concentrations of AA in beverages and artificial urine were successfully identified by DWGH-HCPC/GCE. Additionally, the DWGH-HCPC/GCE demonstrated great feasibility in the simultaneous detection of AA, dopamine (DA), and uric acid (UA). Therefore, as a green, eco-friendly, and low-cost electrode modifier, DWGH-HCPCs have broad prospects in the development of electrochemical sensing platforms for food and medical applications. Full article

Urinary tract infections (UTIs) are a common pathology worldwide, frequently associated with kidney stones. We aimed to determine how artificial intelligence (AI) could assist and enhance human medical activities in this field. We performed a search in PubMed using different sets of keywords. When using the keywords “AI, artificial intelligence, urinary tract infections, Escherichia coli (E. coli)”, we identified 16 papers, 12 of which fulfilled our research criteria. When using the keywords “urolithiasis, AI, artificial intelligence”, we identified 72 results, 30 of which were suitable for analysis. We identified that AI/machine learning can be used to detect Gram-negative bacilli involved in UTIs in a fast and accurate way and to detect antibiotic-resistant genes in E. coli. The most frequent AI applications for urolithiasis can be summarized into three categories: The first category relates to patient follow-up, trying to improve physical and medical conditions after specific urologic surgical procedures. The second refers to urinary stone disease (USD), focused on stone evaluation, using different AI and machine learning systems, regarding the stone’s composition in terms of uric acid, its dimensions, its volume, and its speed of detection. The third category comprises the comparison of the ChatGPT-4, Bing AI, Grok, Claude, and Perplexity chatbots in different applications for urolithiasis. ChatGPT-4 has received the most positive evaluations. In conclusion, the impressive number of papers published on different applications of AI in UTIs and urology suggest that machine learning will be exploited effectively in the near future to optimize patient follow-up, diagnosis, and treatment. Full article

Background: Uric acid has been proposed as a diabetogenic factor while its effect on pancreatic β cell function remains elusive. This study aimed to explore the impact of uric acid levels on β cell function and delineate its underlying molecular mechanisms. Methods: Both in vivo hyperuricemia diet-induced mouse models and in vitro pancreatic β cell models were utilized. Results: A progressive decrease in glucose-stimulated insulin secretion and increase in β cell apoptosis were observed in the hyperuricemia diet-induced mouse model, and these could be effectively restored by urate-lowering therapy. The dose- and time-dependent direct effects of uric acid on β cell apoptosis and insulin secretion were further confirmed in both INS-1E cells and primary isolated islets. Mechanistically, the primary role of expression of the endoplasmic reticulum stress marker C/EBP homologous protein (CHOP) was detected by RNA sequencing, and the inflammatory factor NLRP3 and pro-apoptotic genes were significantly upregulated by uric acid treatment. Conclusions: Together, our findings indicate a direct crosstalk between uric acid and β cells via CHOP/NLRP3 pathway, providing a new understanding of the diabetogenic effect of uric acid. Full article