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.

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.

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.

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.

Long-term effects of PM2.5 constituents on metabolic syndrome and mediation effects of serum uric acid.

Exposure to particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) was associated with the risk for metabolic syndrome (MetS) in the general population, but the contributions of individual PM2.5 constituents to this association and the potential pathway between PM2.5 constituents and MetS risk are not well elaborated. This study aimed to investigate associations between PM2.5 constituents and MetS in general populations, relative importance of PM2.5 constituents to and mediation effects of serum uric acid (SUA) on those associations. The 48,148 participants from a provincially representative cohort established in southwest China were included. The 3-year average concentrations of PM2.5 and its constituents (nitrate [NO3-], sulfate [SO42-], ammonium [NH4+], organic matter [OM], and black carbon [BC]) were estimated using a series of machine-learning models. Multivariate logistic regression and weighted quantile sum regression were used to estimate effects of independent PM2.5 constituents on MetS and their contributions to the joint effect. Mediation analysis examined the potential mediation effects of SUA on the associations between PM2.5 constituents and MetS. Each interquartile range (IQR) increase in the concentration of PM2.5 constituents was all positively associated with the increased MetS odds, including SO42- (OR = 1.15 [1.11, 1.19]]), NO3- (OR = 1.12 [1.08, 1.16]), NH4+ (OR = 1.13 [1.09, 1.17]), OM (OR = 1.09 [1.06, 1.13]), and BC (OR = 1.09 [1.06, 1.13]). Their joint associations on MetS were mainly attributed to SO42- (weight=46.1%) and NH4+ (44.0%). The associations of PM2.5 constituents with abnormal MetS components were mainly attributed to NH4+ for elevated BP (51.6%) and reduced HDL-C (97.0%), SO42- for elevated FG (68.9%), NO3- for elevated TG (51.0%), and OM for elevated WC (63.0%). Percentages mediated by SUA for the associations of PM2.5, SO42-, NO3-, and BC with MetS were 13.6%, 13.1%, 10.6%, and 11.1%, respectively. Long-term exposure to PM2.5 constituents, mainly NH4+ and SO42-, was positively associated with MetS odds, partially mediated by SUA.

Enhancing uric acid electrochemical detection with copper ion-activated mini protein mimicking uricase within ZIF-8: response surface methodology (RSM) optimization.

This study aims to investigate the influence of copper(II) ions as a cofactor on the electrochemical performance of a biocomposite consisting of a mini protein mimicking uricase (mp20) and zeolitic immidazolate framework-8 (ZIF-8) for the detection of uric acid. A central composite design (CCD) was utilized to optimize the independent investigation, including pH, deposition potential, and deposition time, while the current response resulting from the electrocatalytic oxidation of uric acid was used as the response. The statistical analysis of variance (ANOVA) showed a good correlation between the experimental and predicted data, with a residual standard error percentage (RSE%) of less than 2% for predicting optimal conditions. The synergistic effect of the nanoporous ZIF-8 host, Cu(II)-activated mp20, and reduced graphene oxide (rGO) layer resulted in a highly sensitive biosensor with a limit of detection (LOD) of 0.21 µM and a reproducibility of the response (RSD = 0.63%). The Cu(II)-activated mp20@ZIF-8/rGO/SPCE was highly selective in the presence of common interferents, and the fabricated layer exhibited remarkable stability with signal changes below 4.15% after 60 days. The biosensor's reliable performance was confirmed through real sample analyses of human serum and urine, with comparable recovery values to conventional HPLC.

Calcium Fluoride/Manganese Dioxide Nanocomposite with Dual Enzyme-like Activities for Uric Acid Sensing: A Comparative Study of Enzyme and Nonenzyme Methods.

The debate over enzyme methods versus nonenzyme methods in the field of nanosensing has lasted for decades despite hundreds of published studies on this topic. In this study, we first present a comparative analysis of these methods using a reaction based on the CaF2/MnO2 nanocomposite (CM Nc) with dual-enzyme activity, presenting oxidase- and peroxidase-like activities. Uric acid (UA) is a byproduct of purine metabolism in the body, and abnormal levels can cause many diseases; hence, tracking the amount of UA in human serum is crucial. The enzyme method was established using uricase and CM Nc: UA produced H2O2 when catalyzed by uricase; H2O2 was then catalyzed into reactive oxygen species (ROS) by the peroxidase activity of the CM Nc; this ROS oxidized 3,3',5,5'-tetramethylbenzidine (TMB), which was oxidized into blue oxidized TMB (oxTMB). The nonenzyme method was built on the scavenging effect of UA on the ROS, which prevented the catalytic capability of CM Nc toward TMB and induced blue oxTMB fading. The results of further tests revealed the good selectivity of the enzyme method compared to the fast response of the nonenzyme method. Additionally, both methods were effective in determining the UA concentration in human serum. The two separate methods can also independently verify each other, increasing the accuracy of the detection results in accordance with the relatively independent detection principles. This research provided theoretical backing for the practical design of multienzyme nanozyme catalysts, which can facilitate the precise detection of UA in biochemical products.

Development of a facile electrochemical sensor based on GCE modified with one-step prepared PNMA-CeO2-fMWCNTs composite for simultaneous detection of UA and 5-FU.

In this study, a poly(N-methyl aniline)-cerium oxide-functionalized MWCNTs (PNMA-CeO2-fMWCNTs) composite was synthesized in a one-step preparation technique. As a highly efficient modifier, the composite was used to modify the glassy carbon electrode surface for simultaneous detection of uric acid (UA) and 5-fluorouracil (5-FU). Morphological characterization of the GCE/PNMA-CeO2-fMWCNTs was studied using scanning electron microscopy. Structural characterization of the composite was performed using X-ray diffraction and Fourier-transformed infrared spectroscopy. Electron transfer properties of the prepared electrodes were carried out with electrochemical impedance spectroscopy and cyclic voltammetry. The linear working range for UA and 5-FU was found to be 0.25-50 µM and 0.5-750 µM, respectively. The limit of detection values for UA and 5-FU were 0.04 µM and 0.19 µM, respectively. The effects of various interfering substances on the electrochemical response of UA and 5-FU were investigated. The GCE/PNMA-CeO2-fMWCNTs sensor has excellent stability, reproducibility, anti-interference ability, and reproducibility. To demonstrate the practical application of the sensing platform, fetal bovine serum was selected and tested in the spiked samples, and satisfactory results were obtained. The prepared composite proved to be a promising platform for simple, rapid, and simultaneous analysis of UA and 5-FU.

Factors influencing the kinetics of MSU crystal depletion measured with dual-energy CT in patients with gout.

OBJECTIVE: To examine factors influencing the kinetics of monosodium urate (MSU) crystal dissolution measured with dual-energy computed tomography (DECT) during follow-up of patients with gout. METHODS: Patients with a diagnosis of gout with baseline knees and feet DECT scans exhibiting MSU crystal volumes ≥0.1 cm3 and at least one follow-up DECT were included. Spearman's correlation coefficient was used to search for association between change from baseline MSU crystal volume at 6, 12, 18 and 24 months and serum urate (SU) level. Associations between percentage change from the baseline volume of MSU crystal deposits and explanatory variables were assessed using linear mixed models. RESULTS: Sixty-two patients (age 67.3±12.8 years; 53 (85%) males) cumulating 104 follow-up DECT scans were included. Overall, SU target levels (<6.0 and <5.0 mg/dL) were achieved by 48 (77%) and 36 (58%) patients, respectively. There was a good correlation (r=0.66; p<0.0001) observed between SU level and percentage change in MSU crystal volume. The median decrease from baseline MSU crystal volume was greater in patients reaching the <5.0 mg/dL SU target than in those reaching ≥5.0 SU <6.0 mg/dL: -85% (95% CI: -94% to -72%) versus -40% (-57% to -22%; p<0.05) at 12 months. In multivariable analysis, time (in days) with a multilevel coefficient of -0.06 (95% CI: -0.08 to -0.03, p<0.001), hypertension (coefficient: 41.87, 95% CI: 16.38 to 67.18, p<0.01) and SU level <5.0 mg/dL (coefficient: -39.46, 95% CI: -70.93 to -8.34, p=0.02) were the only variables significantly associated with MSU crystal volume change. CONCLUSION: In patients with DECT-measured MSU crystal deposition, reaching the <5.0 mg/dL SU target provides more extensive and rapid crystal dissolution than reaching the <6.0 mg/dL SU target.

Possible role of pomegranate fruit in reversing renal damage in rats exposed to Phenylhydrazine.

Background: Pomegranate granatum (molasses and peels) and its constituents showed protective effects against natural toxins such as phenylhydrazine (PHZ) as well as chemical toxicants such as arsenic, diazinon, and carbon tetrachloride. Aim: The current study aimed to assess the effect of pomegranate molasses (PM), white peel extract, and red peel extract on nephrotoxicity induced by PHZ. Methods: 80 male rats were divided into eight equal groups; a control group, PM pure group, white peel pomegranate pure group, red peel pomegranate pure group, PHZ group, PM + PHZ group, white peel pomegranate + PHZ group and red peel pomegranate + PHZ group. Kidney function, inflammation markers, antioxidant activities, and renal tissue histopathology were investigated. Results: The results revealed that PHZ group showed a significant increase in lactate Dehydrogenase (LDH), malondialdehyde (MDA), creatinine, uric acid, BUNBUN, C - reactive protein (CRP), tumor necrosis factor, thiobarbituric acid reactive substances (TBARSs), and total antioxidant capacity (TAC) with a significant decrease of catalase (CAT), glutathione peroxidase (GPx), and superoxide dismutase (SOD) as compared with a control group. Other pomegranate-treated and PHZ co-treated groups with pomegranate showed a significant decrease of LDH, MDA, creatinine, uric acid, BUN, tumor necrosis factor, TBARSs, and TAC with a significant increase of CAT, GPx, and SOD as compared with PHZ group. Conclusion: Collectively, our data suggest that red, white peels, and molasses have anti-toxic and anti-inflammatory effects on renal function and tissues.

Uric acid-based ratios for predicting renal failure in Chinese IgA nephropathy patients.

Objective: The uric acid/albumin ratio (UAR), a novel, simple, and compositive laboratory biomarker, has recently attracted attention for predicting disease prediction and disease prognosis. However, whether uric acid-related biomarkers (especially UAR) could serve as prognostic indicator for IgAN is unclear. Methods: In this retrospective cohort study, biopsy-confirmed IgAN patients from 2009 to 2017 from West China Hospital were evaluated. The optimal cutoff value of UAR for renal outcome was defined using the Youden index by the area under receiver operating characteristic curve (AUC). The patients were then categorized into the high UAR group and the low UAR group. Renal endpoints were defined as progression to ESRD, eGFR decreased ≥50% of the baseline level, or initiation of renal replacement treatment. Kaplan‒Meier survival analysis and Cox regression analysis were used to identify factors influencing IgAN outcomes. Results: A total of 1143 patients with a median age of 33.0 (26.0-42.0) (44.2% men) were included in the study. The best cut-off UAR concerned with renal survival was determined to be 9.94 with a specificity of 77.5% and a sensitivity of 61.5% (J, 0.390; AUC, 0.750). Then, the patients were divided into two groups labelled as low and high UAR ratios (≥ 9.94 and <9.94, respectively). More severe clinical manifestations and pathological lesions were observed in the high UAR group. Multivariate Cox regression analysis after adjusted for important clinicopathological parameters manifested that a high UAR was an independent prognostic biomarker for IgAN. (p = 0.036, HR =2.56, 95% CI: 1.07-6.16). Conclusion: UAR might be a novel predictor for renal progression and contribute to targeted management.

Porous carbon nanosheets derived from two-dimensional Fe-MOF for simultaneous voltammetric sensing of dopamine and uric acid.

It is of great significance for electrochemical sensors to simultaneously detect dopamine (DA) and uric acid (UA) related to biological metabolism. In this work, two-dimensional (2D) porous carbon nanosheets (CNS) was prepared as electrocatalysts to improve the sensitivity, the selectivity, and the detection limit of the simultaneous detection. First, 2D amorphous iron-metal organic frameworks (Fe-MOF) was synthesized with Fe3+and terephthalic acid via a facile wet chemistry method at room temperature. And then, CNS was prepared by pyrolysis and pickling of Fe-MOF. CNS had large specific surface area, good electrical conductivity and lots of carbon defects. The response currents of the CNS modified electrode was larger than those of the control electrodes in the simultaneous determination. The simultaneous determination was measured via differential pulse voltammetry to reduce the effect of capacitive currents on quantitative analysis. The CNS modified electrodes showed high sensitivity and low detection limit for the simultaneous detection of DA and UA. The modified electrodes have been successfully used to detect DA and UA in normal human serum.

Exposure to ambient air pollutants is associated with an increased incidence of hyperuricemia: A longitudinal cohort study among Chinese government employees.

BACKGROUND: It is widely recognized that ambient air pollution can induce various detrimental health outcomes. However, evidence linking ambient air pollutants and hyperuricemia incidence is scarce. OBJECTIVES: To assess the association between long-term air pollution exposure and the risk of hyperuricemia. METHODS: In this study, a total of 5854 government employees without hyperuricemia were recruited and followed up from January 2018 to June 2021 in Hunan Province, China. Hyperuricemia was defined as serum uric acid (SUA) level of >420 µmol/L for men and >360 µmol/L for women or use of SUA-lowering medication or diagnosed as hyperuricemia during follow-up. Data from local air quality monitoring stations were used to calculate individual exposure levels of PM10, PM2.5, SO2 and NO2 by inverse distance weightingn (IDW) method. Cox proportional hazard model was applied to evaluate the causal relationships between air pollutant exposures and the risk of hyperuricemia occurrence after adjustment for potential confounders and meanwhile, restricted cubic spline was used to explore the dose-response relationships. RESULTS: The results indicated that exposures to PM10 (hazard ratio, HR = 1.042, 95% conficence interal, 95% CI: 1.028, 1.057), PM2.5 (HR = 1.204, 95% CI: 1.141, 1.271) and NO2 (HR = 1.178, 95% CI: 1.125,1.233) were associated with an increased HR of hyperuricemia. In addition, a nonlinear dose-response relationship was found between PM10 exposure level and the HR of hyperuricemia (p for nonlinearity = 0.158) with a potential threshold of 50.11 µg/m3. Subgroup analysis demonstrated that participants usually waking up at night and using natural ventilation were more vulnerable to the exposures of PM10, PM2.5, NO2, and SO2. CONCLUSION: Long-term exposures to ambient PM10, PM2.5 and NO2 are associated with an increased incidence of hyperuricemia among Chinese government employees.

Test characteristics of Raman spectroscopy integrated with polarized light microscopy for the diagnosis of acute gouty arthritis.

OBJECTIVES: We studied the performance of Raman spectroscopy integrated with polarized light microscopy (iRPolM) as a next-generation technique for synovial fluid analysis in gout. METHODS: This is a prospective study, including consecutive synovial fluid samples drawn from any peripheral swollen joint. Diagnostic accuracy was compared to the 2015 ACR/EULAR Gout classification criteria as a reference test and to polarized light microscopy (PLM) analysis by a rheumatologist. Synovial fluid was analysed with iRPolM after unblinding the PLM results. RESULTS: Two hundred unselected consecutive patient samples were included in this study. Validation against clinical criteria: 67 patients were classified as gout according to 2015 ACR/EULAR classification criteria. Compared to the 2015 ACR/EULAR gout classification criteria, iRPolM had a sensitivity of 77.6% (95% CI: 65.8-86.9), specificity of 97.7% (95% CI: 93.5-99.5), positive predictive value (PPV) of 94.5% (95% CI: 84.9-98.2), negative predictive value (NPV) of 89.7% (95% CI: 84.7-93.1), an accuracy of 91.0% (95% CI: 86.2-94.6), a positive likelihood ratio of 34.4 (95% CI: 11.16-106.10) and a negative likelihood ratio of 0.23 (95% CI: 0.15-0.36). Validation against PLM: 55 samples were positive for MSU according to PLM. The interrater agreement between PLM and iRPolM was near perfect (к=0.90). The sensitivity of iRPolM to identify MSU in PLM-positive samples was 91.2% (95% CI: 80.7-97.1), the specificity was 97.6% (95% CI: 93.0-99.5), the PPV was 94.6% (95% CI: 85.0-98.2), NPV was 96.0% (95% CI: 91.2-98.2) and the accuracy was 95.6% (95% CI: 91.4-98.2). The positive likelihood ratio was 37.4 (95% CI: 12.20-114.71), and the negative likelihood ratio was 0.09 (95% CI: 0.04-0.21). CONCLUSION: iRPolM is a promising next-generation diagnostic tool for rheumatology by diagnosing gout with high specificity, increased objectivity, and a sensitivity comparable to PLM.

Synovial fluid analysis: Relevance for daily clinical practice.

Synovial fluid analysis can provide a prompt and definite diagnosis of crystal-induced arthritis, the most common acute inflammatory arthritis and a cause of chronic arthritis that may mimic rheumatoid, psoriatic, or peripheral spondyloarthritis. In many patients the diagnosis of gout or calcium pyrophosphate arthritis cannot be made with certainty without synovial fluid analysis. Additional information from fluid analysis can assist the clinician in honing the differential diagnosis of non-crystalline arthritis.