Colorimetric array sensor based on bimetallic nitrogen-doped carbon-based nanozyme material to detect multiple antioxidants.

Copper-cobalt bimetallic nitrogen-doped carbon-based nanoenzymatic materials (CuCo@NC) were synthesized using a one-step pyrolysis process. A three-channel colorimetric sensor array was constructed for the detection of seven antioxidants, including cysteine (Cys), uric acid (UA), tea polyphenols (TP), lysine (Lys), ascorbic acid (AA), glutathione (GSH), and dopamine (DA). CuCo@NC with peroxidase activity was used to catalyze the oxidation of TMB by H2O2 at three different ratios of metal sites. The ability of various antioxidants to reduce the oxidation products of TMB (ox TMB) varied, leading to distinct absorbance changes. Linear discriminant analysis (LDA) results showed that the sensor array was capable of detecting seven antioxidants in buffer and serum samples. It could successfully discriminate antioxidants with a minimum concentration of 10 nM. Thus, multifunctional sensor arrays based on CuCo@NC bimetallic nanoenzymes not only offer a promising strategy for identifying various antioxidants but also expand their applications in medical diagnostics and environmental analysis of food.

Kidney stone growth through the lens of Raman mapping.

Bulk composition of kidney stones, often analyzed with infrared spectroscopy, plays an essential role in determining the course of treatment for kidney stone disease. Though bulk analysis of kidney stones can hint at the general causes of stone formation, it is necessary to understand kidney stone microstructure to further advance potential treatments that rely on in vivo dissolution of stones rather than surgery. The utility of Raman microscopy is demonstrated for the purpose of studying kidney stone microstructure with chemical maps at ≤ 1 µm scales collected for calcium oxalate, calcium phosphate, uric acid, and struvite stones. Observed microstructures are discussed with respect to kidney stone growth and dissolution with emphasis placed on < 5 µm features that would be difficult to identify using alternative techniques including micro computed tomography. These features include thin concentric rings of calcium oxalate monohydrate within uric acid stones and increased frequency of calcium oxalate crystals within regions of elongated crystal growth in a brushite stone. We relate these observations to potential concerns of clinical significance including dissolution of uric acid by raising urine pH and the higher rates of brushite stone recurrence compared to other non-infectious kidney stones.

Composition analysis of 1,495 cases of upper urinary tract calculi: the role of age and gender.

OBJECTIVE: This study aimed to quantitatively analyze the calculi components of upper urinary tract calculi and to explore the relationship between calculus components, demographic characteristics, and underlying diseases. PATIENTS AND METHODS: Clinical data of 1,495 patients with upper urinary tract calculi were retrospectively collected. The calculi were divided into simple calcium oxalate, calcium oxalate mixed, calcium phosphate mixed, uric acid, magnesium ammonium phosphate, and other components. Statistical software SPSS 22.0 was used to analyze the differences between the stone compositions and various factors. The influencing factors (p < 0.05) were analyzed using multiple logistic regression analysis. RESULTS: Among 1,495 patients with upper urinary tract calculi, simple calcium oxalate calculi were the most common component (39.7%), followed by calcium oxalate mixed calculi (30.4%), uric acid calculi (13.6%), calcium phosphate mixed calculi (10.4%), magnesium ammonium phosphate calculi (5.8%) and other component calculi (0.1%). Univariate analysis revealed statistically significant differences in stone composition according to gender, age, and hyperuricemia (p < 0.05). Multiple logistic regression analysis showed that compared to men, the odds ratio (OR) values of calcium oxalate mixed stones, calcium phosphate mixed stones, and magnesium ammonium phosphate stones in women were 1.61, 2.50, and 4.17, respectively (p < 0.001). Compared with elderly patients, the OR values of calcium phosphate mixed stones in young and middle-aged patients were 3.14 and 2.70, respectively (p < 0.05). CONCLUSIONS: Patients with different stone components had different demographic characteristics, and stone components were significantly different between gender and age. Calcium oxalate mixed stones were more common in females, and calcium phosphate mixed stones and magnesium ammonium phosphate stones were more common in females, young patients, and middle-aged patients.

Flow injection amperometric uric acid biosensor based on AuNPs-GO-CS porous composite cryogel coated on PB-PEDOT:PSS modified screen-printed carbon electrode.

An enzymatic amperometric uric acid (UA) biosensor was successfully developed by modifying a screen-printed carbon electrode (SPCE) with Prussian blue-poly(3,4-ethylene dioxythiophene) polystyrene sulfonate composite (PB-PEDOT:PSS). The modified SPCE was coated with gold nanoparticles-graphene oxide-chitosan composite cryogel (AuNPs-GO-CS cry). Uricase (UOx) was directly immobilized via chemisorption on AuNPs. The nanocomposite was characterized by scanning electron microscopy, transmission electron microscopy, ultraviolet-visible spectroscopy, and Fourier transform infrared spectroscopy. The electrochemical characterization of the modified electrode was performed by cyclic voltammetry and electrochemical impedance spectroscopy. UA was determined using amperometric detection based on the reduction current of PB which was correlated with the amount of H2O2 produced during the enzymatic reaction. Under optimal conditions, the fabricated UA biosensor in a flow injection analysis (FIA) system produced a linear range from 5.0 to 300 µmol L-1 with a detection limit of 1.88 µmol L-1. The proposed sensor was stable for up to 221 cycles of detection and analysis was rapid (2 min), with good reproducibility (RSDs < 2.90 %, n = 6), negligible interferences, and recoveries from 94.0 ± 3.9 to 101.1 ± 2.6 %. The results of UA detection in blood plasma were in agreement with the enzymatic colorimetric method (P > 0.05).

The key role of major and trace elements in the formation of five common urinary stones.

BACKGROUND: Urolithiasis has emerged as a global affliction, recognized as one of the most excruciating medical issues. The elemental composition of stones provides crucial information, aiding in understanding the causes, mechanisms, and individual variations in stone formation. By understanding the interactions between elements in various types of stones and exploring the key role of elements in stone formation, insights are provided for the prevention and treatment of urinary stone disease. METHODS: This study collected urinary stone samples from 80 patients in Beijing. The chemical compositions of urinary stones were identified using an infrared spectrometer. The concentrations of major and trace elements in the urinary stones were determined using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS), respectively. The data were processed using correlation analysis and Principal Component Analysis (PCA) methods. RESULTS: Urinary stones are categorized into five types: the calcium oxalate (CO) stone, carbonate apatite (CA) stone, uric acid (UA) stone, mixed CO and CA stone, and mixed CO and UA stone. Ca is the predominant element, with an average content ranging from 2.64 to 27.68% across the five stone groups. Based on geochemical analysis, the high-content elements follow this order: Ca > Mg > Na > K > Zn > Sr. Correlation analysis and PCA suggested significant variations in the interactions between elements for different types of urinary stones. Trace elements with charges and ionic structures similar to Ca may substitute for Ca during the process of stone formation, such as Sr and Pb affecting the Ca in most stone types except mixed stone types. Moreover, the Mg, Zn and Ba can substitute for Ca in the mixed stone types, showing element behavior dependents on the stone types. CONCLUSION: This study primarily reveals distinct elemental features associated with five types of urinary stones. Additionally, the analysis of these elements indicates that substitutions of trace elements with charges and ion structures similar to Ca (such as Sr and Pb) impact most stone types. This suggests a dependence of stone composition on elemental behavior. The findings of this study will enhance our ability to address the challenges posed by urinary stones to global health and improve the precision of interventions for individuals with different stone compositions.

Zn-CD@Eu Ratiometric Fluorescent Probe for the Detection of Dipicolinic Acid, Uric Acid, and Ex Vivo Uric Acid Imaging.

Development of reliable methods for the detection of potential biomarkers is of the utmost importance for an early diagnosis of critical diseases and disorders. In this study, a novel lanthanide-functionalized carbon dot-based fluorescent probe Zn-CD@Eu is reported for the ratiometric detection of dipicolinic acid (DPA) and uric acid (UA). The Zn-CD@Eu nanoprobe was obtained from a simple room-temperature reaction of zinc-doped carbon dots (Zn-CD) and the EDTA-Eu lanthanide complex. Under optimal conditions, a good linear response was obtained for DPA in two concentration ranges of 0-55 and 55-100 µM with a limit of detection of 0.53 and 2.2 µM respectively, which is significantly below the infectious dosage of anthrax (∼55 µM). Furthermore, the Zn-CD@Eu/DPA system was employed for the detection of UA with a detection limit of 0.36 µM in the linear range of 0-100 µM. The fluorescent probe was successfully implemented for determining DPA and UA in human blood serum, sweat, and natural water bodies with considerable recovery rates. In addition, the potential of the nanoprobe for ex vivo visualization of UA was demonstrated in fruit fly (Drosophila melanogaster) as a model organism.

The Simultaneous Detection of Dopamine and Uric Acid In Vivo Based on a 3D Reduced Graphene Oxide-MXene Composite Electrode.

Dopamine (DA) and uric acid (UA) are essential for many physiological processes in the human body. Abnormal levels of DA and UA can lead to multiple diseases, such as Parkinson's disease and gout. In this work, a three-dimensional reduced graphene oxide-MXene (3D rGO-Ti3C2) composite electrode was prepared using a simple one-step hydrothermal reduction process, which could separate the oxidation potentials of DA and UA, enabling the simultaneous detection of DA and UA. The 3D rGO-Ti3C2 electrode exhibited excellent electrocatalytic activity towards both DA and UA. In 0.01 M PBS solution, the linear range of DA was 0.5-500 µM with a sensitivity of 0.74 µA·µM-1·cm-2 and a detection limit of 0.056 µM (S/N = 3), while the linear range of UA was 0.5-60 µM and 80-450 µM, with sensitivity of 2.96 and 0.81 µA·µM-1·cm-2, respectively, and a detection limit of 0.086 µM (S/N = 3). In 10% fetal bovine serum (FBS) solution, the linear range of DA was 0.5-500 µM with a sensitivity of 0.41 µA·µM-1·cm-2 and a detection limit of 0.091 µM (S/N = 3). The linear range of UA was 2-500 µM with a sensitivity of 0.11 µA·µM-1·cm-2 and a detection limit of 0.6 µM (S/N = 3). The modified electrode exhibited advantages such as high sensitivity, a strong anti-interference capability, and good repeatability. Furthermore, the modified electrode was successfully used for DA measurement in vivo. This could present a simple reliable route for neurotransmitter detection in neuroscience.

Colorimetric and fluorometric determination of uric acid by a suspension-based assay using enzyme-immobilized micro-sized particles.

Daily monitoring of serum uric acid levels is very important to provide appropriate treatment according to the constitution and lifestyle of individual hyperuricemic patients. We have developed a suspension-based assay to measure uric acid by adding a sample solution to the suspension containing micro-sized particles immobilized on uricase and horseradish peroxidase (HRP). In the proposed method, the mediator reaction of uricase, HRP, and uric acid produces resorufin from Amplex red. This resorufin is adsorbed onto enzyme-immobilized micro-sized particles simultaneously with its production, resulting in the red color of the micro-sized particles. The concentration of resorufin on the small surface area of the microscopic particles achieves a colorimetric analysis of uric acid with superior visibility. In addition, ethanol-induced desorption of resorufin allowed quantitative measurement of uric acid using a 96-well fluorescent microplate reader. The limit of detection (3σ) and RSD (n = 3) were estimated to be 2.2 × 10-2 µg/mL and ≤ 12.1%, respectively. This approach could also be applied to a portable fluorometer.

Nanocubic cobalt-containing Prussian blue analogue-derived carbon-coated CoFe alloy nanoparticles for noninvasive uric acid sensing.

This work describes an electrochemical sensor for the fast noninvasive detection of uric acid (UA) in saliva. The sensing material was based on a cobalt-containing Prussian blue analogue (Na2-xCo[Fe(CN)6]1-y, PCF). By optimizing the ratio of Co and Fe as 1.5 : 1 in PCF (PCF1.5,0), particles with a regular nanocubic morphology were formed. The calcination of PCF1.5,0 produced a carbon-coated CoFe alloy (CCF1.5), which possessed abundant defects and achieved an excellent electrochemical performance. Subsequently, CCF1.5 was modified on a screen-printed carbon electrode (SPCE) to fabricate the electrochemical sensor, CCF1.5/SPCE, which showed a sensitive and selective response toward salivary UA owing to its good conductivity, sufficient surface active sites and efficient catalytic activity. The determination of UA in artificial saliva achieved the wide linear range of 40 nM-30 µM and the low limit of detection (LOD) of 15.3 nM (3σ/s of 3). The performances of the sensor including its reproducibility, stability and selectivity were estimated to be satisfactory. The content of UA in human saliva was determined and the recovery was in the range of 98-107% and the total RSD was 4.14%. The results confirmed the reliability of CCF1.5/SPCE for application in noninvasive detection.

Iron-carbon dots embedded in molybdenum single-atom nanoflowers as multifunctional nanozyme for dual-mode detection of hydrogen peroxide and uric acid.

Single-atom catalysts (SACs) have attracted extensive attention in the field of catalysis due to their excellent catalytic ability and enhanced atomic utilization, but the multi-mode single-atom nanozymes for biosensors remain a challenging issue. In this work, iron-doped carbon dots (Fe CDs) were loaded onto the edges and pores of Mo SACs with nanoflower morphology; accordingly, a composite material Fe CDs/Mo SACs was prepared successfully, which improves the catalytic performance and develops a fluorescence mode without changing the original morphology. The steady-state kinetic data indicates that the material prepared have better affinity for substrates and faster reaction rates under optimized conditions. The specific kinetic parameters Km and Vmax were calculated as 0.39 mM and 7.502×10-7 M·s-1 respectively. The excellent peroxidase-like activity of Fe CDs/Mo SACs allows H2O2 to decompose into •OH, which in turn oxidizes colorless o-phenylenediamine (OPD) to yellow 2,3-diaminophenazine (DAP). At the same time, the fluorescence signal of Fe CDs/Mo SACs quenches obviously by DAP at 460 nm through internal filtration effect (IFE), while the characteristic fluorescence response of DAP gradually increases at 590 nm. Based on this sensing mechanism, a sensitive and accurate dual-mode (colorimetric and ratiometric fluorescent) sensor was constructed to detect H2O2 and uric acid, and the rate of recovery and linearity were acceptable for the detection of UA in human serum and urine samples. This method provides a new strategy for rapid and sensitive detection of UA, and also broadens the development of SACs in the field of biosensors.

Flow-Through Amperometric Biosensor System Based on Functionalized Aryl Derivative of Phenothiazine and PAMAM-Calix-Dendrimers for the Determination of Uric Acid.

A flow-through biosensor system for the determination of uric acid was developed on the platform of flow-through electrochemical cell manufactured by 3D printing from poly(lactic acid) and equipped with a modified screen-printed graphite electrode (SPE). Uricase was immobilized to the inner surface of a replaceable reactor chamber. Its working volume was reduced to 10 µL against a previously reported similar cell. SPE was modified independently of the enzyme reactor with carbon black, pillar[5]arene, poly(amidoamine) dendrimers based on the p-tert-butylthiacalix[4]arene (PAMAM-calix-dendrimers) platform and electropolymerized 3,7-bis(4-aminophenylamino) phenothiazin-5-ium chloride. Introduction of the PAMAM-calix-dendrimers into the electrode coating led to a fivefold increase in the redox currents of the electroactive polymer. It was found that higher generations of the PAMAM-calix-dendrimers led to a greater increase in the currents measured. Coatings consisted of products of the electropolymerization of the phenothiazine with implemented pillar[5]arene and PAMAM-calix-dendrimers showing high efficiency in the electrochemical reduction of hydrogen peroxide that was formed in the enzymatic oxidation of uric acid. The presence of PAMAM-calix-dendrimer G2 in the coating increased the redox signal related to the uric acid assay by more than 1.5 times. The biosensor system was successfully applied for the enzymatic determination of uric acid in chronoamperometric mode. The following optimal parameters for the chronoamperometric determination of uric acid in flow-through conditions were established: pH 8.0, flow rate 0.2 mL·min-1, 5 U of uricase per reactor. Under these conditions, the biosensor system made it possible to determine from 10 nM to 20 µM of uric acid with the limit of detection (LOD) of 4 nM. Glucose (up to 1 mM), dopamine (up to 0.5 mM), and ascorbic acid (up to 50 µM) did not affect the signal of the biosensor toward uric acid. The biosensor was tested on spiked artificial urine samples, and showed 101% recovery for tenfold diluted samples. The ease of assembly of the flow cell and the low cost of the replacement parts make for a promising future application of the biosensor system in routine clinical analyses.

Investigation of the protective effect of chitosan against arsenic-induced nephrotoxicity and oxidative damage in rat kidney tissue.

Arsenic is an important metalloid that can cause poisoning in humans and domestic animals. Exposure to arsenic causes cell damage, increasing the production of reactive oxygen species. Chitosan is a biopolymer obtained by deacetylation of chitin with antioxidant and metal ion chelating properties. In this study, the protective effect of chitosan on arsenic-induced nephrotoxicity and oxidative damage was investigated. 32 male Wistar-albino rats were divided into 4 groups of 8 rats each as control group (C), chitosan group (CS group), arsenic group (AS group), and arsenic+chitosan group (AS+CS group). The C group was given distilled water by oral gavage, the AS group was given 100 ppm/day Na-arsenite ad libitum with drinking water, the CS group was given 200 mg/kg/day chitosan dissolved in saline by oral gavage, the AS+CS group was given 100 ppm/day Na-arsenite ad libitum with drinking water and 200 mg/kg/day chitosan dissolved in saline by oral gavage for 30 days. At the end of the 30-day experimental period, 90 mg/kg ketamine was administered intraperitoneally to all rats, and blood samples and kidney tissues were collected. Urea, uric acid, creatinine, P, Mg, K, Ca, Na, Cystatin C (CYS-C), Neutrophil Gelatinase Associated Lipocalin (NGAL) and Kidney Injury Molecule 1 (KIM-1) levels were measured in serum samples. Malondialdehyde (MDA), Glutathione (GSH), Catalase (CAT) and Superoxide dismutase (SOD) levels in the supernatant obtained from kidney tissue were analyzed by ELISA method. Compared with AS group, uric acid and creatinine levels of the AS+CS group were significantly decreased (p<0.001), urea, KIM-1, CYS-C, NGAL, and MDA levels were numerically decreased and CAT, GSH, and SOD levels were numerically increased (p>0.05). In conclusion, based on both biochemical and histopathological-immunohistochemical- immunofluorescence findings, it can be concluded that chitosan attenuates kidney injury and protects the kidney.

A wearable flexible electrochemical biosensor with CuNi-MOF@rGO modification for simultaneous detection of uric acid and dopamine in sweat.

BACKGROUND: In health assessment and personalized medical services, accurate detection of biological markers such as dopamine (DA) and uric acid (UA) in sweat is crucial for providing valuable physiological information. However, there are challenges in detecting sweat biomarkers due to their low concentrations, variations in sweat yield among individuals, and the need for efficient sweat collection. RESULTS: We synthesized CuNi-MOF@rGO as a high-activity electrocatalyst and investigated its feasibility and electrochemical mechanism for simultaneously detecting low-concentration biomarkers UA and DA. Interaction between the non-coordinating carboxylate group and the sample produces effective separation signals for DA and UA. The wearable biomimetic biosensor has a wide linear range of 1-500 µM, with a detection limit of 9.41 µM and sensitivity of 0.019 µA µM-1 cm-2 for DA, and 10-1000 µM, with a detection limit of 9.09 µM and sensitivity of 0.026 µA µM-1 cm-2 for UA. Thus, our sensor performs excellently in detecting low-concentration biomarkers. To improve sweat collection, we designed a microfluidic-controlled device with hydrophilic modification in the microchannel. Experimental results show optimal ink flow at 2% concentration. Overall, we developed an innovative and highly active electrocatalyst, successfully enabling simultaneous detection of low-concentration biomarkers UA and DA. SIGNIFICANCE: This study provides a strategy for sweat analysis and health monitoring. Moreover, the sensor also showed good performance in detecting real sweat samples. This study has shown great potential in future advances in sweat analysis and health monitoring.

Advancements in Uric Acid Stone Detection: Integrating Deep Learning with CT Imaging and Clinical Assessments in the Upper Urinary Tract.

INTRODUCTION: Among upper urinary tract stones, a significant proportion comprises uric acid stones. The aim of this study was to use machine learning techniques to analyze CT scans and blood and urine test data, with the aim of establishing multiple predictive models that can accurately identify uric acid stones. METHODS: We divided 276 patients with upper urinary tract stones into two groups: 48 with uric acid stones and 228 with other types, identified using Fourier-transform infrared spectroscopy. To distinguish the stone types, we created three types of deep learning models and extensively compared their classification performance. RESULTS: Among the three major types of models, considering accuracy, sensitivity, and recall, CLNC-LR, IMG-support vector machine (SVM), and FUS-SVM perform the best. The accuracy and F1 score for the three models were as follows: CLNC-LR (82.14%, 0.7813), IMG-SVM (89.29%, 0.89), and FUS-SVM (29.29%, 0.8818). The area under the curves for classes CLNC-LR, IMG-SVM, and FUS-SVM were 0.97, 0.96, and 0.99, respectively. CONCLUSION: This study shows the feasibility of utilizing deep learning to assess whether urinary tract stones are uric acid stones through CT scans, blood, and urine tests. It can serve as a supplementary tool for traditional stone composition analysis, offering decision support for urologists and enhancing the effectiveness of diagnosis and treatment.

Heterometallic MIL-125(Ti-Al) frameworks for electrochemical determination of ascorbic acid, dopamine and uric acid.

The detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA) is not only of great significance in the areas of biomedicine and neurochemistry but also helpful in disease diagnosis and pathology research. Due to their diverse structures, designability, and large specific surface areas, metal-organic frameworks (MOFs) have recently caught considerable attention in the electrochemical field. Herein, a family of heterometallic MOFs with amino modification, MIL-125(Ti-Al)-xNH2 (x = 0%, 25%, 50%, 75%, and 100%), were synthesized and employed as electrochemical sensors for the detection of AA, DA, and UA. Among them, MIL-125(Ti-Al)-75%NH2 exhibited the most promising electrochemical behavior with 40% doping of carbon black in 0.1 M PBS (pH = 7.10), which displayed individual detection performance with wide linear detection ranges (1.0-6.5 mM for AA, 5-100 µM for DA and 5-120 µM for UA) and low limits of detection (0.215 mM for AA, 0.086 µM for DA, and 0.876 µM for UA, S/N = 3). Furthermore, the as-prepared MIL-125(Ti-Al)-75%NH2/GCE provided a promising platform for future application in real sample analysis, owing to its excellent anti-interference performance and good stability.

Accurate prediction of pure uric acid urinary stones in clinical context via a combination of radiomics and machine learning.

PURPOSE: Oral chemolysis is an effective and non-invasive treatment for uric acid urinary stones. This study aimed to classify urinary stones into either pure uric acid (pUA) or other composition (Others) using non-contrast-enhanced computed tomography scans (NCCTs). METHODS: Instances managed at our institution from 2019 to 2021 were screened. They were labeled as either pUA or Others based upon composition analyses, and randomly split into training or testing data set. Several instances contained multiple NCCTs which were all collected. In each of NCCTs, individual urinary stone was treated as individual sample. From manually drawn volumes of interest, we extracted original and wavelet radiomics features for each sample. The most important features were then selected via the Least Absolute Shrinkage and Selection Operator for building the final model on a Support Vector Machine. Performance on the testing set was evaluated via accuracy, sensitivity, specificity, and area under the precision-recall curve (AUPRC). RESULTS: There were 302 instances, of which 118 had pUA urinary stones, generating 576 samples in total. From 851 original and wavelet radiomics features extracted for each sample, 10 most important features were ultimately selected. On the testing data set, accuracy, sensitivity, specificity, and AUPRC were 93.9%, 97.9%, 92.2%, and 0.958, respectively, for per-sample prediction, and 90.8%, 100%, 87.5%, and 0.902, respectively, for per-instance prediction. CONCLUSION: The machine learning algorithm trained with radiomics features from NCCTs can accurately predict pUA urinary stones. Our work suggests a potential assisting tool for stone disease treatment selection.

Redox biomarkers in saliva and nuclear abnormalities in jugal epithelial cells of individuals with type 2 diabetes mellitus and periodontitis.

OBJECTIVE: To evaluate salivary redox biomarkers levels in individuals with periodontitis and type 2 diabetes mellitus (T2DM) and correlate with periodontal parameters and nuclear alterations in epithelial cells from jugal mucosa. DESIGN: Sixty individuals were categorized into three groups: T2DM with periodontitis (DM, n = 20), non-T2DM with periodontitis (PE, n = 20), and non-T2DM with periodontal health (HC, n = 20). All participants underwent fasting blood glucose and glycated hemoglobin measurements. After a periodontal examination, samples of epithelial cells from the jugal mucosa and saliva were collected. DNA damage was assessed by counting nuclear abnormalities using cytological analysis. Biomarkers of oxidative stress were determined through biochemical methods. Significant differences among groups were assessed using Kruskal-Wallis, Mann-Whitney, and Chi-square tests at a 5% significance level. Data were analyzed using Spearman's correlation coefficient, linear regression, and logistic regression. RESULTS: Frequencies of nuclear abnormalities, as well as levels of reduced glutathione and uric acid, were significantly higher in the DM group compared to the PE and HC groups (p < 0.05). Fasting glucose, glycated hemoglobin, nuclear abnormalities, reduced glutathione, and uric acid exhibited positive correlations with periodontal parameters (p < 0.05). Furthermore, reduced glutathione was associated with dental biofilm (OR = 1.027 [95% CI, 1.004-1.049]) and condensed chromatin (OR = 0.415 [95% CI, 0.196-0.878]). CONCLUSIONS: Periodontitis and T2DM are correlated with nuclear abnormalities, as well as salivary reduced glutathione and uric acid levels. Moreover, a higher prevalence of teeth with dental biofilm increases the likelihood of elevated levels of reduced glutathione in saliva, while the presence of condensed chromatin decreases that likelihood.

A Wearable Electrochemical Biosensor Utilizing Functionalized Ti3C2Tx MXene for the Real-Time Monitoring of Uric Acid Metabolite.

Wearable, noninvasive sensors enable the continuous monitoring of metabolites in sweat and provide clinical information related to an individual's health and disease states. Uric acid (UA) is a key indicator highly associated with gout, hyperuricaemia, hypertension, kidney disease, and Lesch-Nyhan syndrome. However, the detection of UA levels typically relies on invasive blood tests. Therefore, developing a wearable device for noninvasive monitoring of UA concentrations in sweat could facilitate real-time personalized disease prevention. Here, we introduce 1,3,6,8-pyrene tetrasulfonic acid sodium salt (PyTS) as a bifunctional molecule functionalized with Ti3C2Tx via π-π conjugation to design nonenzymatic wearable sensors for sensitive and selective detection of UA concentration in human sweat. PyTS@Ti3C2Tx provides many oxidation-reduction active groups to enhance the electrocatalytic ability of the UA oxidation reaction. The PyTS@Ti3C2Tx-based electrochemical sensor demonstrates highly sensitive detection of UA in the concentration range of 5 µM-100 µM, exhibiting a lower detection limit of 0.48 µM compared to the uricase-based sensor (0.84 µM). In volunteers, the PyTS@Ti3C2Tx-based wearable sensor is integrated with flexible microfluidic sweat sampling and wireless electronics to enable real-time monitoring of UA levels during aerobic exercise. Simultaneously, it allows for comparison of blood UA levels via a commercial UA analyzer. Herein, this study provides a promising electrocatalyst strategy for nonenzymatic electrochemical UA sensor, enabling noninvasive real-time monitoring of UA levels in human sweat and personalized disease prevention.

New insight into interference-free and highly sensitive dopamine electroanalysis.

Early diagnosis of Parkinson's disease and hyperprolactinemia based on electrochemical dopamine (DA) sensing appears as an efficient and promising practical diagnostic method. However, the coexistence of DA in real samples with ascorbic acid (AA) and uric acid (UA), which oxidize at potentials close to its own, prevents the accurate electrochemical DA sensing and therefore, hinders the effective diagnosis of these diseases. In this work, we successfully combined the electrostatic proprieties of GO, the electron transfer properties of an AuNPs@MWCNTs nanocomposite and the ability of thiol group of the amino acid l-cysteine to react chemically with carbonyl groups of UA, to develop a novel approach that enabled complete suppression of interference from AA and UA and hence, accurate DA electroanalysis in the conditions close to those of human blood serum. The chemical reaction between l-cysteine and UA was evidenced by monitoring the DPV responses of UA under different conditions. XRD, Raman spectroscopy, XPS and FE-SEM revealed the successful synthesis of GO and AuNPs@MWCNTs. The study of the electrode material (GO-AuNPs@MWCNTs) morphology via FE-SEM and HR-TEM showed that AuNPs@MWCNTs are distributed throughout the exfoliated GO layers. The fabricated sensor was calibrated in the concentration range of 0.5-5 µM, in the presence of the highest blood concentrations of AA and UA for healthy individuals. A linear relationship was observed and the LOD was found to be 1.31 nM (S/N = 3). Furthermore, the sensor showed good electron transfer kinetics, good repeatability and reproducibility, satisfactory long-term stability, and recoveries in human blood serum.

Hydrophilic interaction liquid chromatography based method for simultaneous determination of purines and their derivatives in food spices.

This work presents method for separation and quantification of adenine, guanine, xanthine, hypoxanthine, uric acid, and creatinine in food spices using hydrophilic interaction liquid chromatography with UV detection. Optimized conditions allowed separation with mobile phases containing acetonitrile and additives ammonium acetate (90:10, v/v, pH 6.1) or formate (90:10, v/v, pH 3.2). In food spices no uric acid was detected, creatinine (16 ± 2 µg g-1) was found only in instant dried yeast. The highest content of purines was determined in dried yeast (xanthine 110 ± 8 µg g-1, hypoxanthine 441 ± 24 µg g-1, adenine 84 ± 16 µg g-1, guanine 163 ± 12 µg g-1), high in curry, herbal pepper, and chicken seasoning, the lowest concentration was in black pepper (hypoxanthine 12 ± 2 µg g-1, adenine 27 ± 3 µg g-1). To best of our knowledge, no such complementary method and obtained data have been reported so far.