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Metabolites serve as vital biomarkers, reflecting physiological and pathological states and offering insights into disease progression and early detection. This study introduces an advanced analytical technique integrating label-free Surface-Enhanced Raman Spectroscopy (SERS) with deep learning, and leverages SHAP (SHapley Additive exPlanations) to provide a visual interpretative analysis of the predictive rationale of the deep learning model, facilitating simultaneous detection and quantitative analysis of multiple metabolites. Monolayer silver nanoparticle SERS substrates were fabricated via a triple-phase interfacial self-assembly method, which captured complex spectral information of target metabolites in mixed solutions. A custom-built deep neural network model with multi-channel feature extraction was employed to predict the concentrations of uric acid (R 2  = 0.976), xanthine (R 2  = 0.971), hypoxanthine (R 2  = 0.977), and creatinine (R 2  = 0.940). The method's scalability was validated as the performance remained consistent with an increasing number of simultaneous targets. This approach offers a sensitive, cost-effective, and rapid alternative for metabolite analysis, with significant implications for clinical diagnostics and personalized medicine., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Wearable microneedle array (MNA) based electrochemical sensors have gained increasing attention for their capability to analyze biomarkers in the interstitial fluid (ISF), enabling noninvasive, continuous monitoring of health parameters. However, challenges such as nonspecific adsorption of biomolecules on the sensor surfaces and the risk of infection at the microneedle penetration sites hinder their practical application. Herein, a wearable dual-layer microneedle patch was prepared to overcome these issues by integrating an antimicrobial microneedle layer with an antifouling sensing layer. The microneedle layer was prepared from polyvinyl alcohol, carboxylated nanocellulose, quaternary ammonium chitosan and carbon nanotubes, and it possessed antimicrobial and mechanical properties necessary for skin penetration, ISF collection and effective transmission to the sensing layer. The sensing layer was prepared from bacterial cellulose, epoxy propyl dimethyl dodecyl ammonium chloride, carbon nanotubes and gold nanoparticles, and it was capable of preventing biofouling and sensing uric acid (UA) in ISF. The wearable MNA based sensor exhibited a linear range of 0.5 μM - 2.5 μM and 9.6 μM - 2.15 mM for UA detection, with a limit of detection of 0.17 μM. Moreover, it was capable of accurately monitoring UA levels in ISF of mice without significant biofouling, as verified by the ELISA method. This innovative wearable sensor based on the MNA effectively balances the antifouling and antimicrobial functions, offering a reliable strategy for the assay of ISF, and making it a promising tool for personalized and decentralized health monitoring., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier B.V. All rights reserved.)

Accurate determination of dopamine (DA) and uric acid (UA) in biological samples is crucial in diagnosing neurodegenerative disorders and gout, respectively. Here we report a highly sensitive and inexpensive, flexible screen-printed sensor for determining DA and UA in sweat samples. Beta-cyclodextrin-based (βCD) composite gel with reduced graphene oxide (rGO) was synthesized by self-polymerization of βCD at an optimum ratio of "good" and "poor solvent". Multiwall carbon nanotubes (MWCNTs) were incorporated into the composite as a conductive filler. The MWCNTs-βCD-rGO gel provides selective biorecognition of DA and UA at the electrode surface through guest-host interaction. The gels were characterized by XRD, TGA, FTIR, UV-Vis, 1 H NMR, FESEM, XPS and optical microscopy. The flexible printed sensor showed linear DA detection in the range 0.25 to 16 μM with a correlation coefficient (R 2 ) of 0.9890, limit of detection (LoD) of 0.08 μM and sensitivity of 3.63 μA μM -1  cm -2 . Similarly, UA calibration showed linear detection from 50 to 700 μM with a R 2 value of 0.9860, LoD of 0.078 μM and sensitivity of 0.118 μA μM -1  cm -2 . The SPE/MWCNTs-βCD-rGOsensor showed simultaneous determination of DA and UA from exercise induced sweat samples. The proposed sensor demonstrated excellent repeatability and satisfactory recoveries in human sweat., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

A disposable electrochemical sensor is introduced for the selective recognition of uric acid (UA), a crucial biomarker for gout arthritis. The sensor employs synthetic antibodies composed of molecularly imprinted polythiophene (MIP) laden graphitic carbon nitride (GCN) nanocomposites for the selective recognition of UA. Microscopic analysis demonstrates an increase in surface roughness and kurtosis after removing the template, indicating the fabrication and functionalization of the MIP/GCN sensors. These sensors exhibit excellent electrochemical properties, characterized by electrochemical impedance spectroscopy (EIS) and voltammetric (CV, DPV) methods. The sensor displays a wide linear detection range (1-500 µM), encompassing the normal UA levels in human saliva, high sensitivity (5.47 µA/cm 2 .µM), a low limit of detection (0.21 µM), and limit of quantification (0.64 µM). The sensor also exhibits low cross-sensitivity to common salivary interferences, including urea, creatinine, ascorbic acid, glucose, and glutamine. The MIP/GCN sensor accurately identifies UA in human saliva, resulting in a recovery of 93.25 ± 0.33%. Electrochemical studies, utilizing [Fe(CN) 6 ] 4-/3- as a redox probe, also provide insights into the mechanisms of interfacial redox reactions and selective UA recognition. This work demonstrates a significant improvement in POC testing, providing a reliable and non-invasive tool for gout diagnosis., Competing Interests: Declarations. Competing interest: The authors declare no competing interests., (© 2025. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

The development is proposed of a specific non-enzymatic amperometric sensor based on electrodeposited copper nanoparticles (Cu-NPs) for the determination of uric acid (UA) in fermentation samples. Through optimization of the Cu-NPs-containing sensing layer, it was demonstrated that copper(II)-induced oxidation (catalytic effect) in the presence of molecular oxygen is more effective for determining UA than the adsorption of UA on Cu and Cu-oxide surfaces. More importantly, simply changing the sensing layer's surface chemistry by increasing the defect Cu x O y on the surface of Cu-NPs after heating at 70 °C for only 20 min significantly improved the specificity of UA determination in both model and real fermentation samples (viz. supernatants of S. cerevisiae and E. coli). This study can be used as a guideline for the future assembly of functional electrodeposited sensing layers for the specific determination of target electroactive bioanalyte(s)., Competing Interests: Declarations. Conflicts of interest: The authors declare no competing interests., (© 2025. The Author(s).)

Non-invasive continuous detection using tears or sweat as substitutes for blood samples has become an emerging method for real-time monitoring of human health. However, its development is limited by the low sample volume and low level of analytes. The simultaneous determination of multi-analytes with highly sensitive electrochemical sensing platforms has undoubtedly resulted in breakthrough innovations. Furthermore, the determination mode of multi-analyte combinations can accurately characterize the course of certain diseases. In particular, the simultaneous determination of ascorbic acid (AA), uric acid (UA), and acetaminophen (AC) in sweat will provide a one-stop detection system for cardiovascular and degenerative diseases for the entire course analysis. A sacrificial template strategy was adopted in this work using graphene oxide (GO) to guide the growth of two-dimensional Fe-Co composite nanoflakes with large specific surface areas. Defects were introduced via doping carbon through the incomplete pyrolysis of GO. The synthesized C-Fe 1.33 Co 1.67 O 4 exhibited massive redox sites and was highly reactive, which met the requirements for multi-substance analysis. The electrochemical sensor based on C-Fe 1.33 Co 1.67 O 4 accurately and sensitively demonstrated simultaneous detection of AA, UA, and AC in sweat, with a wide detection range for AA (4.0-11500 μM) and high sensitivity for UA and AC (304.5 μA mM -1 and 404.1 μA mM -1 , respectively), along with low detection limit (1.69 μM for AA, 0.23 μM for UA, and 0.07 μM for AC). The sensor also possessed adequate mechanical flexibility, making it suitable for body surface detection, and its performance was maintained above 80% after high-intensity bending 350 times.

The development of biosensing electronics for real-time sweat analysis has attracted increasing research interest due to their promising applications for non-invasive health monitoring. However, one of the critical challenges lies in the sebum interference that largely limits the sensing reliability in practical scenarios. Herein, we report a flexible epidermal secretion-purified biosensing patch with a hydrogel filtering membrane that can effectively eliminate the impact of sebum and sebum-soluble substances. The as-prepared sebum filtering membranes feature a dual-layer sebum-resistant structure based on the poly(hydroxyethyl methacrylate) hydrogel functionalized with nano-brush structured poly(sulfobetaine) to eliminate interferences and provide self-cleaning capability. Furthermore, the unidirectional flow microfluidic channels design based on the Tesla valve was incorporated into the biosensing patch to prevent external sebum contamination and allow effective sweat refreshing for reliable sensing. By seamlessly combining these components, the epidermal secretion-purified biosensing patch enables continuous monitoring of sweat uric acid, pH, and sodium ions with significantly improved accuracy of up to 12 %. The proposed strategy for enhanced sweat sensing reliability without sebum interference shows desirable compatibility for different types of biosensors and would inspire the advances of flexible and wearable devices for non-invasive healthcare., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Elevated levels of uric acid (UA) in the body may not only lead to the formation of stones but also increase the risk of developing chronic kidney disease (CKD). This study presents a biosensor for detecting UA concentration in stones and a deep learning-based artificial neural network (ANN) system for analyzing CKD risk. The biosensor is a screen-printed electrode (SPE) chip, whose surface was modified using oxygen plasma, enabling the detection of UA concentration via cyclic voltammetry. Experimental results show a good linear relationship between UA concentration and anodic peak current within the range of 0.15-5 mM. The surface modification method for this biosensor is simple and cost-effective. The ANN system took age and creatinine values as inputs, utilizing the Chronic_Kidney_Disease dataset and supplementary data from literatures for training. After detecting the UA concentration in stones using the biosensor, the result was converted into serum uric acid concentration, allowing the estimation of creatinine level, which was then used by the ANN to assess the risk of developing CKD. This system can assist urologists in determining whether patients should seek consultation with nephrologists for early diagnosis and treatment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Wearable sweat sensors offering real-time monitoring of biomarker levels suffer from stability and accuracy issues, primarily due to low biomarker concentrations, fluctuating sweat pH, and material detachment from sensor deformation. Here, we developed a wearable sensing system integrated with two advanced electrodes and a flexible microchannel for long-term reliable monitoring of sweat pH and uric acid (UA). By printing the ink doped with nanomaterials (Co 3 O 4 @CuCo 2 O 4 and polyaniline), we achieved highly stable electrodes for the direct analysis of perspiration, without additional surface modification. Additionally, real-time pH analysis provided a means for sensitivity calibration, reducing the effect of individual metabolism and exercise intensity. As a result, the wearable sensing system for effective gout management was validated by accurately tracking the UA fluctuations in serum and sweat of hyperuricemia patients and healthy individuals. These findings offer a reliable method for tracking biomarkers to assess personal health.

Assessing the total antioxidant capacity (TAC) in biological samples, such as saliva, is essential for health monitoring and disease prevention. TAC plays a critical role in protecting cells from damage caused by free radicals and oxidative stress, which are associated with various conditions, including cancer, cardiovascular diseases, and aging. Key antioxidants, including ascorbic acid (AA), cysteine (CYS), glutathione (GSH), and uric acid (UA), significantly contribute to this protective effect, with salivary levels of these antioxidants reflecting their concentrations in the bloodstream. Therefore, there is a strong demand for a robust, non-toxic colorimetric sensor that can effectively monitor these antioxidants using an innovative approach. This study introduces a multi-colorimetric probe capable of generating high-resolution, naked-eye-detectable color readouts for evaluating salivary TAC. The probe utilizes the morphology-dependent properties of plasmonic nanostructures as recently developed colorimetric sensors, enabling precise and efficient analysis of salivary antioxidants. The assessment of antioxidants was conducted using the probe in combination with pattern recognition analysis for accurate identification and regression analysis for quantification. The probe exhibited linear responses to pure antioxidants and TAC over a broad concentration range: 3.1-60.0, 2.6-60.0, 1.2-20.0, 0.8-20.0, and 0.7-14.0 μmol L -1 , with detection limits of 1.1, 0.9, 0.4, 0.3, and 0.2 μmol L -1 for AA, CYS, GSH, UA, and TAC-mixture, respectively. Moreover, performance metrics highlight the robustness and efficacy of the probe in detecting and quantifying antioxidant levels in saliva samples. The efficacy of the developed multi-colorimetric probe was rigorously validated through the analysis of real saliva samples for on-site TAC monitoring. This rapid, cost-effective, user-friendly, non-toxic, and non-invasive method allows for a comprehensive analysis of both individual and total antioxidants, making it highly applicable for health monitoring and disease prevention. Additionally, the probe generates unique response profiles based on varying ratios of endogenous antioxidants, enabling precise TAC quantification in saliva-an essential factor for clinical diagnostics.

A smartphone-based non-invasive method was developed for salivary uric acid detection using Gleditsia Sinensis carbon dots (GS-CDs). The GS-CDs synthesized by the one-pot hydrothermal method emitted blue fluorescence at a maximum excitation wavelength of 350 nm and had good fluorescence stability in the presence of different ions, while showing selectivity to uric acid solution. The ability of uric acid (UA) to quench the fluorescent substances present in the GS-CDs, was confirmed through HPLC-FLD and LC-MS, FTIR and XPS. The results showed that UA reacted with GS-CDs, with a decrease in hydroxyl groups and the formation of carboxyl groups. The fluorescence quenching suggested a possible dynamic quenching mechanism. In addition, a smartphone-based non-invasive detection method was developed for the detection of salivary UA levels, which reflects blood UA levels. This study provides a new perspective on the utilization of GS shells and advances the development of non-invasive testing for UA., Competing Interests: Declarations. Conflict of interest: The authors declare no competing interests., (© 2025. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Using a laser-scribed (direct printing) technique, we have fabricated an enzymeless, mediatorless, and paper-interfaced electrochemical device (P-LSG) for uric acid detection on a flexible polyimide sheet. Various paper substrates were investigated, and it was found that Whatman filter paper-1 is promising to obtain the best electrochemical signals at the small volume of electrolyte, i.e., 20 μL. Furthermore, the Whatman filter paper-1 was modified with gold nanoparticles (AuNPs) to improve the electrocatalytic activity of the P-LSG device. The fabricated AuNP-modified P-LSG biosensor exhibited excellent electrocatalytic activity for the detection of uric acid over a wide range of 10 to 750 μM, with sensitivity of ∼0.214 μA μM -1 cm -2 , and a limit of detection of ∼1.4 μM. The sensor was further validated by using the UHPLC-ESI-MS/MS technique, and the observed percentage recovery was less than 10%. This work opens the window to modified paper substrates with various nanomaterials to improve the sensing parameters. The electrolyte storage capacity and rich chemistry of paper additionally provide an efficient immobilization platform for biorecognition elements to diagnose other metabolites. Furthermore, it has the potential to analyze the volume of small samples (like sweat, tears, urine, etc.) using paper to develop noninvasive wearable biosensors.

Simultaneous monitoring of key metabolites like dopamine, ascorbic acid, and uric acid is essential for early disease diagnosis and evaluating treatment. Electrochemical techniques are increasingly used for precise, point-of-care testing (POCT) of these metabolites. Herein, a sample pretreatment method called effervescent solid-phase extraction (ESPE) was proposed for efficient enrichment of trace analytes for electrochemical detection. In an ESPE process, effervescent tablets made of gold nanoparticle-decorated graphene oxide (Au/GO) were first self-dispersed in a test solution to promote the enrichment of analytes on the Au/GO adsorbents, followed by the addition of flocculant effervescent tablets to cause Au/GO sheets to form self-assembled aggregates, which then can be efficiently collected by the foam electrodes. The entire sample pretreatment process operates without external power and takes only 5 min. With the assistance of the ESPE method, our electrochemical sensors achieve an ultralow detection limit for dopamine, ascorbic acid, and uric acid of 80 pM, 1.8 nM, and 460 pM, respectively, which are two to three orders of magnitude lower than the results obtained by the drop casting technique. The enhancement mechanism of our approach is based on increasing the contact probability with analytes through dynamic dispersion of the Au/GO adsorbents, in contrast to the static diffusion mechanism relied on Brownian motion. We also show that combining the ESPE solution kit with a portable micro-electrochemical workstation can attain the same detection level as HPLC in real urine samples. The proposed ESPE approach holds great promise for POCT applications in 2D material-based biosensors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This study reviews advances in chemical detection methods applied to the metabolic products known as uric acid (UA) and xanthine (XA), which are residues of purine metabolism, with XA being an important intermediate preceding UA. UA and XA play crucial roles in maintaining physiological homeostasis in organisms. Chemical modification of electrodes is a widely used method to address the issues of poor sensitivity and selectivity encountered with bare electrodes. This article reviews various materials commonly used to modify electrode surfaces for the detection of uric acid and xanthine, focusing on properties that enhance electrocatalytic activity. We highlight recent trends in detecting these compounds using electrochemical methods with microfabricated devices and explore cutting-edge modification techniques involving novel nanomaterials, carbon derivatives, metallic nanoparticles, and polymers. The review includes a comparative analysis of these materials, addressing their strengths, limitations, and recent advancements, such as in carbon-based materials and metal-organic frameworks (MOFs). Finally, we critically examine the challenges and future prospects of electrochemical detection of UA and XA in real samples, offering strategies to address these issues. The challenges associated with determination of UA and XA in real samples are also discussed., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Developing sensors with high sensitivity and selectivity for detecting neurotransmitters under near-physiological conditions is a major challenge and is crucial for preventing diseases of the nervous, cardiovascular, and endocrine systems. Most existing systems that meet these requirements involve either complicated synthesis processes, require sulfur groups, or are not functional under aqueous conditions. Herein, we report that the self-organisation of a simple imine ligand L with copper(II) tetrafluoroborate leads to the formation of a [CuL 2 ](BF 4 ) 2 complex (CuL 2 ) with a 2 : 1 ligand-to-metal ratio, as confirmed by high-resolution electrospray ionization mass spectrometry (HR ESI-MS), Fourier-transform infrared (FT-IR) spectroscopy and single-crystal X-ray analysis. Surprisingly, modifying a gold surface with a self-assembled monolayer of the CuL 2 complex created a stable sensor for selective detection of epinephrine (EP) using differential pulse voltammetry (DPV) in phosphate buffer solution (PBS) at pH 7.0. A linear correlation between the current response and the concentration of EP was observed with a detection limit of 0.03 μM, high reproducibility and good stability in the range of 0.0001 to 0.875 mM. These results show that the new sensor (Cu/Au) can serve as a reliable analytical tool to selectively detect EP alone and in a mixture with coexisting uric acid (UA) in tested samples.

Oxidative stress and neuroinflammation are recognized as key factors in the development of neurodegenerative diseases, yet effective interventions and biomarkers to address oxidative stress and neuroinflammation in these conditions are limited. Uric acid (UA), traditionally associated with gout, is now gaining prominence as a potential target in neurodegenerative diseases. Soluble UA stands out as one of the most vital antioxidant compounds produced by the human body, accounting for up to 55% of the extracellular capacity to neutralize free radicals. While there is increasing evidence supporting the neuroprotective properties of UA in Parkinson's disease and Alzheimer's disease, gaps in knowledge still exist regarding the underlying mechanisms and how to effectively translate these benefits into clinical practice. Moreover, the current UA elevation therapy exhibits unstable antioxidant properties, individual variability, and even adverse effects, limiting its potential clinical applications. This review consolidates recent advancements in understanding how UA exerts neuroprotective effects on neurodegenerative diseases and emphasizes the dual roles of UA in managing oxidative stress and neuroinflammation. Additionally, the review elucidates the mechanisms through which UA confers neuroprotection. Based on this, the review underscores the significance of UA as a potential biomarker and aims to provide a comprehensive understanding of its potential as a therapeutic target, while also addressing possible challenges to clinical implementation., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Accurate determination of elemental concentrations in uric acid (UA) stones is crucial for understanding their formation process. However, the lack of matrix-matched calibration standards has limited the application of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) in this field. This study addresses this limitation by preparing a synthetic UA precipitate (UA-1) doped with 17 elements using a recrystallization method. Reference concentrations of these elements were measured using pneumatic nebulization-ICP-MS (PN-ICP-MS) for calibration purposes. The synthetic standard was characterized through 30 random spot analyses, demonstrating a homogeneity of approximately 5%. Using this synthetic standard, a reliable analytical method was developed, achieving limits of detection (LODs) ranging from 0 to 0.42 μg g -1 . The method's accuracy, with relative deviations between -8.33% and 0 and correlation coefficients ( R 2 ) greater than 0.99, confirms its reliability. Additionally, elemental distribution differences observed across various zones in a real UA stone suggest that this method offers a promising approach for the precise analysis of elemental concentrations in UA stones.

Background: The present study aims to determine the relationship between the expression levels of serum and urine biomarkers, and the composition of urinary calculi, in order to provide additional background information on the disease., Methods: A total of 80 patients with urinary calculi, who were admitted to our hospital from January 2022 to June 2023, were selected as the study objects. In addition, 80 healthy subjects, who were admitted to our hospital during the same period, were selected as the control group. Patients with urinary calculi were further divided into two groups: Calcium oxalate calculi group and uric acid carbonate calculi group. The serum and urine biomarker levels of subjects in each group were compared by enzyme-linked immunosorbent assay. The correlation among calculi composition, clinical indicators, and protein biomarker levels was determined by single-factor and multi-factor analyses. The value of protein biomarkers in predicting calculi composition was evaluated using the receiver operating characteristic curve., Results: There were significant differences in the expression levels of Lipocalin-2, matrix metalloproteinase 8, matrix metalloproteinase 9, angiopoietin-like 3, Dickkopf-4, interleukin 10 receptor alpha, interleukin 1 receptor 5, interleukin 2 receptor subunit gamma chain, and interleukin 28 A between the experimental and control groups. Furthermore, serum and urine Dickkopf-4, urine interleukin 10 receptor alpha, and microscopic red blood cell levels in urine were higher in patients with calcium oxalate calculi, when compared to patients with uric acid carbonate calculi ( p < 0.05). The receiver operating characteristic curve analysis revealed that the area under curve for the four indicators was 0.854, with a cut-off value of 0.742. Thus, this can be used to predict the calcium oxalate composition in calculi., Conclusions: Serum and urine protein biomarkers Dickkopf-4 and urine interleukin 10 receptor alpha, and microscopic red blood cells in urine can be used to predict the calculi composition. Patients with calcium oxalate calculi are more likely to have hematuria, when compared to patients with calculi of other compositions., Competing Interests: The authors declare no conflict of interest., (© 2025 The Author(s).)

A sensor for uric acid (UA) based on the urate oxidase enzyme (UOx) immobilized in novel Co-based aerogels with transition metals synthesized by the sol-gel method was developed and evaluated. The Co-based aerogels: Co, Ni-Co and Pd-Co were physicochemically characterized by XRD and HR-TEM. The surface area values of 53, 57 and 66 m 2 g-1 were determined for Co, Ni-Co and Pd-Co, respectively by N 2 adsorption-desorption technique. Co-based aerogels were mixed by cross-linking with UOx enzymes and electrochemically characterized in buffers at pH 7.4 and 5.6 (pH values reported for biological fluids such as blood and sweat) in the presence of different uric acid concentrations. Co-based aerogels with UOx showed improved performance as a uric acid biosensor compared to using the enzyme alone. At a pH of 7.4, a higher sensitivity of 11 μA μM -1 was obtained with Pd-Co/UOx, 1.6 times higher than with UOx. At a pH value of 5.6, the highest sensitivity is achieved with Ni-Co/UOx. Stability and selectivity tests were performed in the presence of biological interferents without significant changes in the sensor. These results indicate a pleasing synergistic activity between Co-based aerogels and the enzyme., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: J. Ledesma-Garcia reports financial support was provided by Mexican Council for Humanities, Sciences and Technologies., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Herein, we report a fast (10 min) and simple surface treatment of pure carbon cloth (CC) only by an air plasma. The structural characterizations indicate that the air plasma process brings out higher rugosity, more defects, and increased oxygen-related groups on CC surfaces than Ar- or N 2 -plasma, which can offer abundant capture sites, large electroactive area, and superhydrophilic interface for analytes. As a result, the air-treated CC (CC-P Air ) electrode achieves a pronounced improvement of electrocatalytic activity for the [Fe(CN) 6 ] 3- /[Fe(CN) 6 ] 4- probe evidenced by increased peak currents, decreased peak-to-peak separation, and the lowered resistance of charge transfer. It is also demonstrated that the self-supported CC-P Air electrode possesses excellent sensing performance toward dopamine (DA) and uric acid (UA). The feasibility of the simultaneous electrochemical detection of DA and UA can be verified by their large peak potential gap (∼112 mV) for differential pulse voltammetry. The chronoamperometric sensor yields wide linear ranges of 0.05-100 μM for DA and 0.5-300 μM for UA. The corresponding detection limits are estimated to be 2.6 and 20.4 nM for DA and UA, respectively. The sensor also displays satisfactory selectivity, stability, and reproducibility. Due to good flexibility, the CC-P Air electrode presents great potential for manufacturing wearable and soft electronics for human health monitoring., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Low-cost transition metal vanadate-based electrochemical sensors have attracted a lot of attention recently. A cobalt vanadate and carboxylated multi-walled carbon nanotube composite (CoV/MWCNTs-COOH) was prepared by an ultrasonic-assisted assembly method. The uniform and dense MWCNTs-COOH attached to the surface of CoV not only combines the large surface area and superior conductivity of MWCNTs-COOH with the excellent electrochemical activity of CoV, but also enhances the redox reaction between CoV/MWCNTs-COOH composite and the analyte through synergistic effect of hydrogen bonding and electrostatic interaction. The electrochemical behaviors of CoV/MWCNTs-COOH composite modified glassy carbon electrode (CoV/MWCNTs-COOH/GCE) were investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV). The simultaneous electrochemical sensing of ascorbic acid (AA), dopamine (DA) and uric acid (UA) on CoV/MWCNTs-COOH/GCE possesses good peak current signals with well-defined peak potentials. The linear ranges of AA, DA, and UA at CoV/MWCNTs-COOH/GCE are 1.0-100.0 μM, and the limits of detection (LODs; S/N = 3) are 0.4 μM, 0.03 μM, and 0.1 μM, respectively. The practicality of the designed sensor was further confirmed by the good recoveries obtained in the simultaneous measurement of actual samples including fetal bovine serum, human serum, urine, and Vitamin C tablets. Overall, the developed electrochemical sensor shows potential therapeutic applications for simultaneous determination of AA, DA and UA in biological fluids., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Renal failure is typical chronic kidney disease that required peritoneal dialysis as the primary treatment, but current catheter devices lack functionality to monitor changes in chemical analytes during peritoneal dialysis. Fabrication of miniatured sensing modules with good electrochemical performance in tiny catheter devices is the key to realize the smart monitoring of peritoneal dialysis. In this work, a vertical graphene-based multiparametric sensing array (VG-MSA) is developed to continuously measure fluctuations of various analyte concentrations for peritoneal dialysis monitoring. Vertical graphene (VG) electrode with good electrochemical properties serves as the core module in VG-MSA, allowing the development of miniatured sensing modules with sufficient electrochemical performance. The VG-MSA enables sensitive and multiplexed measurement of dialysate components like metabolites (reactive oxygen species, uric acid, and glucose) and ions (K + , Ca 2+ , and H + ). The VG-MSA is demonstrated to effectively detect biochemical signals in peritoneal dialysate in vivo on rat models. The VG-MSA catheter can be inserted into abdominal cavity, allowing full contact with dialysate for in situ, real-time, and continuous collection of biochemical information during peritoneal dialysis. The VG-MSA catheter device offers a valuable tool for monitoring dialysis quality and facilitating treatment adjustments, potentially as a promising platform for high-quality therapy of renal failure., (© 2024 Wiley‐VCH GmbH.)

With the deepening understanding of diseases, increasing attention has been paid to personalized healthcare and precise diagnosis, which usually depend on the simultaneous monitoring of multiple metabolites, therefore requiring biological sensing systems to possess high sensitivity, specificity, throughput, and instant monitoring capabilities. In this work, we demonstrated the active-matrix extended-gate field-effect transistor (AMEGFET) array that can perform instant analysis of various metabolites in small amounts of body fluids collected during routine physiological activities. The extended gate electrodes of the AMEGFETs comprise ordered mesoporous carbon fibers loaded with both oxidoreductase enzymes for specific metabolites and platinum nanoparticles. By selecting customized electrode combinations, the AMEGFET array can monitor the concentrations of metabolites closely associated with chronic diseases and lifestyles, such as glucose, uric acid, cholesterol, ethanol, and lactate. The switch function of AMEGFET not only simplifies the readout circuitry for large-scale arrays but also avoids the mutual interferences among sensing units. The high flexibility and scalability make the AMEGFET array widely applicable in establishing high-throughput sensing platforms for biomarkers, providing highly efficient technical support for proactive health and intelligent healthcare., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

As a class of point-of-care (POC) assays with visible distance readout (thermometer style), the electrophoresis titration (ET) biosensor affords high robustness, versatility, and simplicity for point-of-care quantification. However, naked-eye observation of the distance readout is unreliable in POC settings and manual processing of distance readout is time-consuming. Herein, we developed a smartphone-deployable and all-in-one machine vision for four ET biosensors (bovine serum albumin, melamine, uric acid, glutathione) to classify and quantify the samples simultaneously. To ensure accurate and rapid quantification on the smartphone, we customized the decolorization methods and edge detection operators to balance the region of interest (ROI) extraction performance and processing speed. We then established a dataset of 180 distance readout images to endow our machine vision with the ability to classify four sample types. Consequently, our machine vision demonstrated high accuracy in determining the sample type (>97.2%) and concentration (>97.3%). Moreover, expanding its applications to other targets was readily achieved by including distance readout images of other ET biosensors (e.g., hemoglobin A1c) in the dataset. Therefore, our strategy of constructing machine vision is compatible with the versatile ET biosensor technique, suggesting that the same strategy can be used for other thermometer-style POC assays., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Fe single-atom and Fe cluster-coupled N, S co-doped carbon nanomaterials (Fe SA -FeO NC -NSC) were prepared through a two-step high-temperature pyrolysis process using Gelidium corneum enriched with C, Fe, O, N, and S as precursors. The analysis by aberration-corrected scanning transmission electron microscopy and X-ray absorption spectroscopy revealed the presence of single-atom Fe in Fe-N 4 coordination structures, along with small clusters as Fe-O-coordinated Fe 2 O 3 . Single-atom Fe in the form of Fe 2+ /Fe 3+ provides more electrocatalytic active sites, which synergistically accelerates the charge migration process in the assembly of Fe SA -FeO NC -NSC with Fe 2 O 3 clusters. The flexible nonenzymatic sensor, based on Fe SA -FeO NC -NSC and fabricated using a polydimethylsiloxane substrate, exhibited excellent catalytic activity for both uric acid (UA) and tyrosine (Tyr). Low detection limits for UA (0.14 μmol L -1 ) and Tyr (0.03 μmol L -1 ) were observed by using chronoamperometry in artificial sweat. The in situ detection of sweat was performed in combination with an integrated circuit board affixed to human skin, and the results were generally consistent with those of the high-performance liquid chromatography method. Therefore, Fe SA -FeO NC -NSC serves as a good modifier for wearable electrochemical sweat sensor applications.

The growing popularity of electrochemical sensors featuring non-invasive biosensing technologies has generated significant enthusiasm for continuous monitoring of bodily fluid biomarkers, potentially aiding in the early detection of health issues in individuals. However, detection of multiple biomarkers in complex biofluids often necessitates a high-density array which creates a challenge in achieving cost-effective fabrication methods. To overcome this constraint, this work reports the fabrication of an electrochemical sensor utilizing a NiO-Ti 3 C 2 T x MXene-modified flexible laser-induced graphene (LIG) electrode for the separate and concurrent analysis of ascorbic acid (AA), dopamine (DA), and uric acid (UA) in human sweat and also addresses the deficiencies in the existing state of the art by offering a cost-efficient and high-performance sensor that mitigates the degrading constraints of conventional LIG electrodes. Cyclic voltammetry and differential pulse voltammetry measurements reveals that the electrochemical properties of the modified electrode, attain a low detection limit and great sensitivity for the target biomarkers. The NiO-Ti 3 C 2 T x /LIG sensor demonstrated enhanced electrocatalytic activity for the oxidation of ascorbic acid, dopamine, and uric acid, and proved useful for analysing these biomarkers in synthetic sweat samples. Under the optimized conditions, the LOD values were estimated to be 16, 1.97 and 0.78 μM for AA, DA and UA, respectively. The developed high-efficiency sensor holds significant promise for applications in flexible and wearable electronics for health monitoring.

Maintaining normal biomolecular levels in the human body plays a crucial role in controlling various diseases. In this work, we designed a portable microelectrochemical sensor based on laser-induced graphene (LIG) for the simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA). A simple electrode surface modification strategy, potentiostatic polarization in an alkali solution, was applied to functionalize the LIG surface with the aim of enhancing the LIG electrocatalytic activity, conductivity, and wettability. After electrochemical pretreatment, the modified electrode displayed significantly enhanced electrocatalytic activity toward AA, DA, and UA, with well-separated characteristic oxidation peaks for each analyte, thus achieving their simultaneous detection without further modification by nanomaterials. Differential pulse voltammetry (DPV) was applied for determining these three analytes. Under optimal conditions, calibration curves were obtained in the ranges 10-5000 μM, 0.1-6000 μM, and 10-8000 nM for AA, DA, and UA, with the detection limits (S/N = 3) of 1.43 μM, 6.83 nM, and 1.07 nM, respectively. The microelectrochemical sensor achieved reliable and satisfactory results in detecting AA, DA, and UA in actual urine samples, demonstrating significant application prospects in human health monitoring and clinical diagnosis.

To overcome the problems of easy aggregation, poor reproducibility and homogeneity of metal nanosols, a SERS substrate with good sensitivity, homogeneity and reproducibility was designed and prepared for the detection of disease markers in urine. Silver nanocubes (Ag NCs) were firstly prepared and then dispersed in cationic cellulose (C-CNF) to form a homogeneous gel, which was dropped on a filter paper to develop a substrate with good SERS activity. This substrate combines the superior SERS properties of Ag NCs with the stability of C-CNF and has a minimum detection concentration of 10 -9  M for R6G. The homogeneity of this substrate was good and the RSD value was much <20 %. The SERS substrate was employed for the quantification of creatinine and uric acid, with linear ranges were 5 × 10 -3 -5 × 10 -7  M and 10 -2 -10 -6  M. The recoveries of creatinine and uric acid were calculated to be 98.3 % ∼ 103.12 % and 96.72 % ∼ 104.48 %, respectively, in the spike recovery experiments, with the relative standard deviations of <10 %. The experimental results show that the method can provide a scientific and reliable experimental basis for screening, condition monitoring and treatment of kidney and other diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Sweat biomarkers have the potential to offer valuable clinical insights into an individual's health and disease condition. Current sensors predominantly utilize enzymes and antibodies as biometric components to measure biomarkers present in sweat quantitatively. However, enzymes and antibodies are susceptible to interference by environmental factors, which may affect the performance of the sensor. Herein, we present a wearable microfluidic surface-enhanced Raman scattering (SERS) biosensor that enables the non-invasive and label-free detection of biomarkers in sweat. Concretely, we developed a bimetallic self-assembled anti-opal array structure with uniform hot spots, enhanced the Raman scattering effect, and integrated it into a silk fibroin-based sensing patch. Utilizing a silk fibroin substrate in the wearable SERS sensor imparts desirable properties such as softness, breathability, and biocompatibility, which enables the sensor to establish close contact with the skin without causing chemical or physical irritation. In addition, introducing microfluidic channels enables the controlled and high temporal resolution management of sweat, facilitating more efficient sweat collection. The proposed label-free SERS sensor can offer chemical 'fingerprint' information, enabling the identification of sweat analytes. As an illustration of the feasibility, we have effectively monitored the creatinine and uric acid levels in sweat. This study presents a versatile and highly sensitive approach for the simultaneous detection of biomarkers in human sweat, showcasing significant potential for application in point-of-care monitoring., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Simultaneous detection of biomarkers in sweat is crucial for comprehensive health assessment and personalized monitoring. However, the low sweat secretion rate and low metabolite concentrations present challenges for developing non-invasive wearable sensors. This study aims to develop a flexible wearable biosensor for simultaneous detection of low-concentration biomarkers in sweat, enabling comprehensive health assessment. This study synthesized an innovative bimetallic tungstate Ag@Ag 2 WO 4 and evaluated its performance for detecting uric acid (UA, 10-1000 μM), dopamine (DA, 3-500 μM), and tyrosine (Tyr, 5-1000 μM). The detection limits (LODs) for DA, UA, and Tyr sensors were 3.10 μM, 8.47 μM, and 4.17 μM, respectively, with relative standard deviations (RSDs) of 4.76 %, 2.66 %, and 3.51 %, respectively. Additionally, this study designed a hydrophilic microfluidic collection system inspired by bamboo leaf structures to enhance sweat collection efficiency. Validation studies demonstrated that the wearable biosensor effectively detects UA and TA in the sweat of volunteers. We believe this research could contribute to advancing personalized healthcare by improving the convenience and effectiveness of health monitoring technologies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Background: The investigation of biomolecules is essential due to abnormalities in biological metabolism in the human body. Dopamine (DA) and uric acid (UA) are important chemicals that coexist in biological systems and play crucial roles in various physiological processes related to human metabolism. This study explores the application of carbon and SnO 2 nanoparticles for DA and UA sensing, focusing on the preparation of Sn/SnO 2 nanocomposites through electrospinning and plasma treatment. The research aims to measure these concentrations quickly and accurately, offering advantages such as low manufacturing costs and environmental friendliness., Result: This study presents a novel Sn/SnO 2 nanocomposites as an electrocatalyst for the detection of dopamine (DA) and uric acid (UA) levels. Sn/SnO 2 nanocomposites were effectively obtained by argon microwave plasma (ArMP) treatment, a dry and green process, on electrospun fibers containing SnCl 2 within 120 s. The resultant Sn/SnO 2 nanocomposites provide excellent electrochemical catalytic effects to quantify the levels of DA and uric acid UA, which are the two important physiological molecules. To further incorporate graphite into ArMP-Sn/SnO 2 can modulate precise differentiation of the oxidation peaks of DA, UA, and ascorbic acid (AA), solving the problems of overlapped oxidation potential among biomolecules. The as-established nanocomposites revealed excellent applicability to be incorporated onto difference substrates including gold electrode (AuE), screen-printed carbon electrodes (SPCE), and flexible carbon electrodes (FCE), providing great potential for building point-of-care sensing platform., Significance: The 1%g-120s-ArMP-Sn/SnO 2 @AuE resulting the highest sensing performance for DA and UA, which the linear detection range was 0.1-400 μM and 0.1-900 μM, with sensitivity of 473.72 and 169.21 μA/mM.cm 2 , and LOD 0.003 and 0.010 μM, respectively. Additionally, in the areal human fluid matrix the sensor obtains a recovery rate between 95.28 % and 102.72 % with a high selectivity (less than 5 %) upon the presence of common interferences in body fluid., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier B.V. All rights reserved.)

Wearable sweat sensors offer a promising non-invasive approach for real-time physiological monitoring, with significant potential in personalized medicine. In this study, we present an innovative wearable patch designed for highly sensitive and accurate detection of uric acid (UA) in human sweat. The sensor integrates superior platinum-iron dual-atom catalysts (Pt/Fe DACs), developed based on iron single-atom catalysts (Fe SACs), to achieve selective and precise UA detection across a wide concentration range (6.25-1500 μM). To enhance the sensor's performance, a pH electrode based on polyaniline (PANI) is incorporated for reliable pH calibration. Density functional theory (DFT) calculations are used to explore the catalytic mechanism of UA detection and the synergistic interaction between Fe and Pt atoms in the catalyst, which improves sensor sensitivity. Additionally, we developed a microfluidic patch made of polydimethylsiloxane (PDMS) with enhanced hydrophilicity to facilitate efficient sweat collection. This work presents a valuable approach for advancing wearable sweat sensors for UA detection and offers a promising strategy for the application of wearable sensors in personalized health monitoring., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Sensors based on inorganic nanomaterials for the detection of human body fluids show great potential in real-time detection and treatment of human health due to their advantages of small size and easy to wear. Nevertheless, most of the existing sensors have the disadvantage of detecting relatively simple substances and suffer from low sensitivity, which undermines their practical applicability in body fluids detection. In this study, based on the transition metal carbide (Ti 3 C 2 T x , MXene)/αFe 2 O 3 grid composite structure, a highly sensitive flexible sensor is proposed, which can realize accurate and simultaneous detection of glucose and uric acid (UA) concentration. The sensor exhibits outstanding durability, enabling it to withstand prolonged immersion in water and exposure to high flow velocities. More importantly, the sensor has extremely high sensitivity for both glucose (2.14 mA mM -1  cm -2 , 5.5 times the mean value) and UA (2.56 μA μM -1  cm -2 , 3.5 times the mean value). It also has the advantage of low detection limits (0.27 μM for glucose and 0.31 μM for UA) and a wide linear detection range (1 mM-40 mM for glucose and 10 μM-900 μM for UA) compared to existing sensors for body fluids detection. In addition, the sensor has excellent repeatability, long shelf life (over 40 days) and excellent immunity to interference (accurate detection of glucose and UA in the presence of multiple metal ions as well as organics in human body fluids). This study establishes the groundwork for developing a production-ready and highly sensitive blood detection sensor capable of real-time monitoring., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The success of allogeneic hematopoietic cell transplantation (alloHCT) in curing hematologic disorders is limited by its short- and long-term toxicities. One such toxicity is oral mucositis (OM), causing pain, speech/swallowing difficulty, and prolonged hospitalization. Although conditioning chemoradiotherapy is the direct cause of OM, potential host-intrinsic mediators of mucosal injury remain elusive. We hypothesized that the oral microbiota may influence OM severity. We used a validated comprehensive scoring system based on specialized Oral Medicine examinations to longitudinally quantify OM severity in alloHCT recipients. High-throughput multi-site profiling of the oral microbiota was performed in parallel. We identify a sex-dependent commensal bacterium, Oribacterium asaccharolyticum, whose presence in saliva before transplantation is associated with more severe OM 14 days after transplantation. The sex predilection of this species correlated with higher uric acid levels in men. Our findings represent the first sex-dependent microbiota-mediated pathway in OM pathogenesis and introduce novel targets for preventative interventions., Competing Interests: Competing interests: A.R. has received consulting fees from Seres Therapeutics and serves as a member of an Emmes Data and Safety Monitoring Board, both outside of the scope of the present study., (© 2024. The Author(s).)

Background: Chemiluminescence (CL) analysis is a promising analytical method with advantages including easy operation, high sensitivity and simple instrument. However, the single CL mode usually suffered from poor stability and reproducibility as a result of the flash-type nature of luminescent molecules, leading to false positive or negative results in practical applications. Dual-mode detection is an advanced sensing methodology that identifies analytes through independent output signals. This approach has the ability to circumvent the inherent constraints of individual sensing modes while integrating their respective strengths, thereby yielding a synergistic enhancement in the detection system., Results: Herein, a chemiluminescence-fluorescence (FL) dual-mode analysis and imaging system is designed by constructing an atomically Fe(Ⅲ) anchored PCN-224 peroxidase-mimicking nanozyme (PCN-224/Fe(Ⅲ)) and achieve an ultrasensitive detection of Uric Acid (UA). The multifunctional PCN-224/Fe(Ⅲ) serves as a high-efficiency co-reaction promoter in the generation of reactive oxygen species (ROS) in both the CL and FL system, while also demonstrating exceptional capabilities as fluorescent nanoprobes. Ultimately, a smartphone-adopted CL imaging device was developed to achieve a visual CL detection through the design of portable paper-based chips. Besides, with the assistance of the TMB-mediated fluorescence energy resonance transfer, the fluorescent PCN-224/Fe(Ⅲ) nanoprobes exhibited good fluorescence detection performance for UA. The limit of detection was achieved as low as 2.45 × 10 -10  M and 1.99 × 10 -9  M in the CL and FL mode, respectively., Significance: This study engineered an atomically Fe(Ⅲ)- MOF-based multifunctional nanozyme and developed an innovative approach for creating CL-FL dual-mode analysis and imaging detection for UA. The proposed CL-FL dual-mode detection system not only provided a portable and sensitive method for UA detection but also offered valuable insights into the mechanism of the co-reaction promoter enhanced CL and FL analysis., Competing Interests: Declaration of competing interest The authors declare no competing financial interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

We synthesized an unoxidized bis-indolyl methane (BIM) derivative (probe 1) comprising of tetraphenylethylene (TPE) as the signalling moiety. The amphiphilic probe could form self-assembled nanoscopic aggregates in the aqueous medium. The emission of 1 in non-polar solvents originates from the LE state, while in polar solvents, it is dominated by TICT. Moreover, probe 1 exhibited a 'turn-on' fluorescence response for both uric acid (with a blue shift in emission maxima) and phytic acid (with a red shift in emission maxima). Therefore, the present system provides an exceptional opportunity to distinguish between phytic acid and uric acid by considering two different emission channels. Mechanistic investigations revealed that both H-bonding and electrostatic interactions between the probe and analytes could effectively cause restricted intramolecular rotations, leading to a turn-on response. Additionally, in the case of phytic acid, larger aggregates were observed with prominent CT characteristics. The change in the extent of charge transfer interaction in the formed adducts resulted in distinct fluorescence responses with phytic acid and uric acid. Furthermore, we explored the applicability of the present system in the screening of real-life samples, such as uric acid in urine samples and phytic acid in grains. The LOD for phytic acid and uric acid was found to be ∼5.48 nM and 10.4 nM, respectively. The quantitative nature of the system was confirmed, showing promising results in terms of recovery values (between 95.6% and 104.2%) and detection limits. Additionally, we also employed handy paper strips for the on-site monitoring of phytic acid and uric acid, thereby eliminating the need for complex instrumentation or trained technicians.

Objective: To present the most recent data on urinary calculi characteristics in the southern region of China and explore the effects of sociodemographic, clinical and laboratory characteristics on stone composition to fill the research gap., Setting: A retrospective observational study was performed in Shenzhen between December 2019 and August 2022., Participants: A total of 858 calculi samples from patients with urolithiasis were analysed via infrared spectroscopy., Methods: The stone was classified by the European Association of Urology guidelines and the Mayo Clinic stone classification practices. Multivariate logistic regression models were conducted to evaluate the association between different characteristics and urinary stone composition., Results: We found that the majority of these patients with urolithiasis were under 60. Almost half of the stone samples (49.4%) were single constitute, and calcium oxalate stone accounted for the highest proportion (80.0%), followed by infection stone (10.0%) and uric acid stone (4.9%). Of these, 78.0% were collected from males, with a male-to-female ratio of 3.54:1; the majority (95.0%) of calculi localisation was in the upper urinary tract. Multivariate analysis found that age, gender, history of urolithiasis, kidney disease, anatomical location and urinary pH influenced urinary stone composition., Conclusions: The effective prevention of urolithiasis is the key to this working-age population. These findings may supply significant evidence for understanding the underlying aetiology of urolithiasis and offer clues for effectively preventing and treating urinary calculi., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Point-of-care (POC) tests increasingly highlight the importance of portable, cost-effective, and visually quantitative detection of biomarkers. Herein, we developed a power-free and visual signal-readout POC sensor based on the target-triggered ultrafast gelation process. In the gelation process, the target triggered the cascade reaction catalyzed by oxidase and ferrous glycinate to produce carbon radicals that immediately initiated the rapid polymerization and cross-linking of acryloylated chondroitin sulfate and dimethylacrylamide. This highly efficient enzymatic polymerization process contributed to the ultrafast generation of chondroitin hydrogel within 1 min at 25 °C. The increase in viscosity of aqueous solution resulted from hydrogel formation was then visually measured according to the distance of solution migration on a tick-labeled pH test strip, which thus realized the quantification of a target. By utilizing glucose oxidase as an oxidase model during the gelation process, this POC sensor was successfully employed in the rapid quantitative detection of glucose without the need for any auxiliary instruments. Benefiting from the specificity and stability of the enzymatic polymerization reaction, the sensor exhibited excellent performance in the detection of glucose in clinical blood samples. Moreover, the sensor was further extended to uric acid detection and enabled accurate assay in clinical urine samples, which indicated the versatility and practicability of this sensor in the POC test.

Objectives: Urinary stones composed of uric acid can be treated with medicine. Computed tomography (CT) can diagnose urinary stone disease, but it is difficult to predict the type of uric stones. This study aims to develop a method to distinguish pure uric acid (UA) stones from non-uric acid (non-UA) stones by describing quantitative CT parameters of single-energy slices of urinary stones related to chemical stone types., Methods: Clinical data, CT images, and stone composition analysis results of patients with urinary stones clinically diagnosed at The Department of Urology, Affiliated Hospital of Qingdao University between 1 January 2018 and 31 December 2020 were collected and retrospectively analyzed. The above data were preprocessed and fed into a convolutional neural network to perform deep learning (DL) of the model, and the dataset was validated at a ratio of 4:1. The area under the curve (AUC) value of the receiver operating characteristic (ROC) curve and the confusion matrix were utilized to evaluate the predictive effect of the model., Results: A retrospective analysis of 918 non-enhanced thin-slice single-energy CT images of known chemical stone types (124 with UA stones and 794 with non-UA stones) was conducted using a DL model. Compared with the results of ex vivo analysis by infrared spectroscopy, the prediction model obtained an AUC of 0.83 for the dichotomous classification of UA stones and non-UA stones. The accuracy of the model was 97.01%, with an F1 score of 89.04%, sensitivity of 84.62%, and specificity of 82.28%., Conclusions: This DL model constructed based on convolutional neural network analysis of thin-slice single-energy CT images is highly accurate in predicting the composition of pure UA and non-UA stones, providing a simple and rapid diagnosis method., Competing Interests: The authors declare no conflict of interest., (© 2024 The Author(s).)

Background: Urinary stone disease is a prevalent health issue worldwide, with varying incidence influenced by multiple factors. This study aims to provide the first comprehensive analysis of urinary stone composition in Azerbaijan., Methods: A retrospective study was conducted on 1465 patients, aged 1‒83 years, who underwent biochemical urinary stone analysis at the Department of Renal Diseases and Organ Transplantation, Azerbaijan State Security Service Military Hospital, between April 2015 and December 2023. Stone samples were analyzed using Fourier transform infrared (FTIR) spectroscopy. Statistical analyses were performed using the IBM® SPSS software version 29.0., Results: The cohort had a median age of 45 years, with a male-to-female ratio of 1.65:1. Calcium oxalate stones were the most common (56.2%), followed by uric acid (33.7%), struvite (5.3%), cystine (2.5%), calcium phosphate (1.9%), and xanthine (0.1%) stones. Men had a higher prevalence of calcium oxalate and uric acid stones, while women had more struvite stones. Mixed stones were common, particularly among uric acid and struvite stones. Significant differences in stone composition were observed between age groups and genders, with uric acid stones found predominantly in older individuals., Conclusion: This study highlights the predominance of calcium oxalate stones and the elevated prevalence of uric acid stones in Azerbaijan, emphasizing the need for tailored diagnostic and therapeutic approaches. The high prevalence of mixed stones underscores the complexity of urinary stone disease and the need for comprehensive metabolic evaluation and individualized preventive strategies., (© 2024 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)

Purpose: Uric acid stones (UAS) can be treated non-invasively by oral chemolysis. However, it is crucial to identify individuals who are most likely to benefit from this approach, specifically, patients with pure UAS. The aim of this study was to develop a nomogram that can differentiate between pure and mixed UAS., Methods: A retrospective analysis of demographic, clinical and stone composition data of patients with a predominant UAS composition (≥ 50%) treated between 2014 and 2022., Results: A total of 135 patients were included in the analysis, 37.8% had mixed UAS (50-90% UA) and 62.2% had pure UAS (≥ 95% UA). The mean stone density and the percentage of radiopaque stones in the pure UAS group were significantly lower than those in the mixed UAS group (450 Hounsfield Units [HU] vs. 600 HU, and 24% vs. 58%, respectively). A stepwise multivariate logistic regression revealed that lower stone density, bigger size, decreased stone opacity and older age are predictive variables for pure UAS. Accordingly, a nomogram was generated with a receiver operating characteristic (ROC) curve that showed an area under the curve (AUC) of 0.78. A patient with a total score of 156 has a probability of > 95% for pure UAS., Conclusion: Imaging and demographic data can be used to identify patients with pure UAS. The nomogram may be useful for counseling patients regarding oral chemolysis. Future validation of the nomogram with a different data set is required to assess its efficacy., (© 2024. The Author(s).)

A free-standing electrode based on carbon cloth-supported Fe-doped polydopamine-derived carbon (Fe/PDA-C/CC) was developed for the simultaneous detection of dopamine (DA) and uric acid (UA). First, dopamine was self-polymerized on the surface of the carbon cloth to obtain polydopamine coatings. Subsequently, Fe 3+ was introduced through the formation of a coordinate bond with the hydroxyl functional group in the polydopamine layer. After calcination, a flexible and free-standing electrode was obtained. The sensing performance and mechanism of the Fe/PDA-C/CC sensor was investigated and is discussed in detail herein. Experimental results demonstrated that Fe/PDA-C/CC could simultaneously detect DA and UA with a wide detection range of 0.5-300 μM and 0.5-400 μM with low detection limits of 0.041 μM and 0.012 μM, respectively. Meanwhile, Fe/PDA-C/CC possessed excellent anti-interference performance, repeatability, stability, and accuracy in real samples. Overall, this study provides a facile and effective approach for simultaneous detection of UA and DA.

Surface-enhanced Raman spectroscopy (SERS) is a promising technique for the detection of biomarkers, but it can struggle to quantify multiple analytes in complex fluids. This study combines electrochemical SERS (E-SERS) and machine learning for the quantitative multiplexed detection of uric acid (UA) and creatinine (CRN). Using classical polydisperse Ag nanoparticles (NPs) made by scalable synthesis, we achieved quantitative multiplexing with low limits of detection (LoDs) and high prediction accuracy, comparable to those made by sophisticated approaches. The E-SERS LoDs at the optimal applied potentials were 0.127 μM and 0.354 μM for UA and CRN respectively, compared to 0.504 μM and 1.02 μM for conventional SERS (recorded at 0 V). By collecting a multi-dimensional E-SERS dataset and applying a two-step partial least squares regression - multilayer perceptron (PLSR-MLP) machine learning algorithm, we were able to identify the analyte concentrations in unseen spectra with a prediction accuracy of 0.94. This research demonstrates the potential of E-SERS and machine learning for multiplexed detection in clinical settings.

Uric acid is typically measured through blood tests, which can be inconvenient and uncomfortable for patients. Herein, we propose a wearable surface-enhanced Raman scattering (SERS) chip, incorporating a hydrogel membrane with integrated plasmonic trimers, for noninvasive monitoring of uric acid in sweat. The plasmonic trimers feature sub 5 nm nanogaps, generating strong electromagnetic fields to boost the Raman signal of surrounding molecules. Simultaneously, the hydrogel membrane pumps sweat through these gaps, efficiently capturing sweat biomarkers for SERS detection. The chip can achieve saturation adsorption of sweat within 5 min, eliminating variations in individual sweat production rates. Dynamic SERS tracking of uric acid and lactic acid levels during anaerobic exercise reveals a temporary suppression of uric acid metabolism, likely due to metabolic competition with lactic acid. Furthermore, long-term monitoring correlates well with blood test results, confirming that regular exercise helps reduce serum uric acid levels and supporting its potential in managing hyperuricemia.

Wearable sensors enable the noninvasive continuous analysis of biofluid, which is of great importance for healthcare monitoring. In this work, a wearable sensor was seamlessly integrated with a microfluidic chip which was prepared by a three-dimensional printing technology for noninvasive and multiplexed analysis of metabolite and electrolytes in human sweat. The microfluidic chip could enable rapid sampling of sweat, which avoids the sweat evaporation and contamination. Using a Zn metal-organic framework as a sacrificial template, the hexagonal rod-shaped porous carbon nanorod (PCN) with high porosity, a large specific surface area, and excellent conductivity was synthesized and exhibited the robust electrocatalytic ability of uric acid (UA) oxidation. Therefore, the PCN-based sensor showed high sensitivity and good selectivity of UA with a wide linear range of 10-200 μM and a low detection limit of 4.13 μM. Meanwhile, the potentiometry-based ion-selective electrode was constructed for detection of pH and K + , respectively, with good sensitivity, selectivity, reproducibility, and stability. In addition, the testing under different bending states demonstrated that mechanical deformation had little effect on the electrochemical performance of the wearable sensors. Furthermore, we evaluated the utility of the wearable sensor for multiplexed real-time analysis of UA, pH, and K + in sweat during aerobic exercise, and the effect of the amount of consumed purine-rich foods on uric acid metabolite levels in sweat and urine was further investigated. The relationship between urine UA and sweat UA was obtained. Overall, this wearable sensor enables multiple electrolyte and metabolite analysis in different noninvasive biofluids, suggesting its potential application in personalized disease prevention.

Carbon cloth (CC) was electrochemically activated using three electrochemical methods in different electrolytes. The gases released during the activation process etched the surface of the CC, thereby increasing its surface area of the activated CC (FCC). Moreover, functional groups such as oxygen-containing groups and N-doping have been introduced. The quantity and type of functional groups introduced during the activation process were related to the anions in the solution. FCC electrodes were used to construct electrochemical sensors for the simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA). The PFCC electrode activated by advanced cyclic voltammetry in (NH 4 ) 2 HPO 4 showed linear ranges for AA, DA, and UA concentrations of 0.1 to 2.1 mM, 0.5 to 11 µM, and 0.5 to 11 µM, respectively. The detection limits are 72.93, 0.22, and 0.42 µM, respectively. The good flexibility the PFCC electrode made it suitable for the preparation of flexible sensors. The simultaneous determination of AA, DA, and UA in fetal bovine serum showed a reliable recovery ratio. This study provides a simple and green approach for activating carbon cloth and constructing flexible electrochemical sensors with the potential to simultaneously detect AA, DA, and UA., (© 2024. The Author(s).)

In this work, we report a study of a zinc sulfide (ZnS) nanocrystal and reduced graphene oxide (RGO) nanocomposite-based non-enzymatic uric acid biosensor. ZnS nanocrystals with different morphologies were synthesized through a hydrothermal method, and both pure nanocrystals and related ZnS/RGO were characterized with SEM, XRD and an absorption spectrum and resistance test. It was found that compared to ZnS nanoparticles, the ZnS nanoflakes had stronger UV light absorption ability at the wavelength of 280 nm of UV light. The RGO significantly enhanced the electron transfer efficiency of the ZnS nanoflakes, which further led to a better photoelectrochemical property of the ZnS/RGO nanocomposites. The ZnS nanoflake/RGO nanocomposite-based biosensor showed an excellent uric acid detecting sensitivity of 534.5 μA·cm -2 ·mM -1 in the linear range of 0.01 to 2 mM and a detection limit of 0.048 μM. These results will help to improve non-enzymatic biosensor properties for the rapid and accurate clinical detection of uric acid.

This report demonstrates a unique route for translating a non-responsive fluorophore into a responsive one to optically recognize uric acid (UA) in physiological-mimicking conditions. The explicit 'turn ON-turn OFF' fluorescence switching upon sequential disaggregation-reaggregation of the self-aggregated 3,3'-bisindolyl(phenyl)methane molecules materializes a straightforward, trouble-free supramolecular UA sensing platform.

Background/aim: The appropriate sonographic protocol for assessing urate crystal deposits in asymptomatic hyperuricemia (AH) is undefined, as well as how the choice would impact on deposit rates and accompanying sonographic, clinical and laboratory features., Methods: Patients with AH (serum urate ≥7 mg/dL) underwent musculoskeletal ultrasound of 10 locations for OMERACT elementary gout lesions (double contour [DC] signs, tophi, aggregates). Different definitions for AH with deposits were applied, varying according to deposits (any deposits; only DC and/or tophi); gradation (any grade; only grade 2-3 deposits), location (10 locations; 4-joint scheme including knees and 1MTPs; >1 location with deposits), or pre-defined definitions (DC sign in femoral condyles/1MTP and/or tophi in 1MTP). We evaluated crystal deposits rates and compared between other sonographic features, clinical and laboratory variables., Results: Seventy-seven participants with AH showed a median 1 location (IQR 0-2) with tophi, 1 (IQR 1-2) with aggregates, and 0 locations (IQR 0-1) with DC sign. The deposition rate ranged from 23.4% (in >1 location with grade 2-3 DC or tophi) to 87.0% (in any deposit in all 10 locations). Accompanying inflammation - assessed by a positive power-Doppler (PD) signal - and erosions were found in 19.5% and 28.4% of participants, respectively. Positive PD signal was better discriminated by criteria requiring grade 2-3 or >1 location with lesions. Erosions and the different clinical and laboratory variables were similar among protocols., Conclusion: Rates of sonographic deposition in AH varied dramatically among studied protocols, while some could discriminate accompanying inflammation, all highlighting the need for a validated, consensus-based definition., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Mariano Andrés declares speaking fees from Menarini laboratories (below $10,000). The other authors declare they have no conflict of interest in relation to this study. The authors have not received personal compensation for conducting the study nor the patients for their participation., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Acute physiological responses to psychosocial stressors are a potential pathway underlying racial disparities in stress-related illnesses. Uric acid (UA) is a potent antioxidant that has been linked to disparities in stress-related illnesses, and recent research has shown that UA is responsive to acute social stress. However, an examination of the relationships between the purinergic system and other commonly measured stress systems is lacking. Here, we measure and characterize associations of salivary uric acid (sUA) with markers of hypothalamic-pituitary-adrenal (HPA) axis activation, sympathetic-adreno-medullar (SAM) axis activation, and acute inflammation. A community sample of 103 African Americans (33 male, 70 female) completed the Trier Social Stress Test to induce social-evaluative threat. Passive drool collected before, during, and after the stressor task provided salivary reactivity measures of UA (sUA), cortisol, dehydroepiandrosterone sulfate (DHEAS), salivary alpha amylase (sAA - a surrogate marker of SAM activity) and C-reactive protein (sCRP). Multiple regressions revealed that total activation of cortisol, DHEAS, and sCRP were each positively associated with higher total activation of sUA. Additionally, DHEAS reactivity was positively associated with sUA reactivity. Relationships between HPA-axis markers and sUA were especially observed among younger and male participants. Overall, findings suggest potential coordination of stress systems with sUA in response to acute stress, which may further the contributions of biological stress processes to racial health disparities., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Douglas A. Granger reports a relationship with Salimetrics LLC that includes: board membership. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)