Lactiplantibacillus plantarum 06CC2 Enhanced the Expression of Intestinal Uric Acid Excretion Transporter in Mice.

ATP-binding cassette transporter subfamily G member 2 (ABCG2) is responsible for the excretion of foreign substances, such as uric acid (UA) and indoxyl sulfate (IS), from the body. Given the importance of increased ABCG2 expression in UA excretion, we investigated the enhancement of intestinal ABCG2 expression using Lactiplantibacillus plantarum 06CC2 (LP06CC2). Mice were reared on a potassium oxonate-induced high-purine model at doses of 0.02% or 0.1% LP06CC2 for three weeks. Results showed that LP06CC2 feeding resulted in increased ABCG2 expression in the small intestine. The expression level of large intestinal ABCG2 also showed a tendency to increase, suggesting upregulation of the intestinal excretion transporter ABCG2 by LP06CC2. Overall, LP06CC2 treatment increased fecal UA excretion and showed a trend towards increased fecal excretion of IS, suggesting that LP06CC2 treatment enhanced the expression of intestinal ABCG2, thereby promoting the excretion of UA and other substances from the intestinal tract.

Study of Urinary Electrolytes and Fractional Excretion of Uric Acid in Evaluating Hyponatremia.

INTRODUCTION: Serum sodium levels <135 mmol/L are known as hyponatremia. The syndrome of inappropriate antidiuresis (SIAD), which is described by a drop in the effective arterial blood volume (EABV), is the most common cause of hyponatremia. This study was carried out to categorize hyponatremia based on volume status and on parameters like fractional excretion of uric acid (FE-UA), fractional excretion of sodium (FE-Na), urine uric acid (U-UA), and serum uric acid (SR-UA) values. MATERIALS AND METHODS: Sixty-one patients admitted to the Department of Medicine at Rajendra Institute of Medical Sciences (RIMS), Ranchi, with hyponatremia were included in the study by applying random sampling. Routine urine and blood samples were collected for biochemical tests. Institutional ethical clearance was obtained for this study. Data were analyzed using Statistical Package for the Social Sciences (SPSS) (version 21). Frequency, central tendency, receiver operating characteristic (ROC), and nonparametric Mann-Whitney U test analysis tools were utilized for analysis. RESULTS: Syndrome of inappropriate antidiuretic hormone secretion (SIADH) was found in nearly 50.82% of hyponatremic patients. Approximately, 70% of non-SIADH patients were hypovolemic. When compared to the non-SIADH group, patients in the SIADH group had significantly higher systolic blood pressure (SBP) and diastolic blood pressure (DBP), lower pulse rates, and lower urine creatinine levels and urine creatinine to serum creatinine ratio. The non-SIADH group had significantly higher SR-UA levels (p < 0.0001), but the SIADH group had significantly higher U-UA levels and significantly lower SR-UA levels. Among the studied parameters, FE-UA was the most accurate in diagnosing SIADH. FE-UA (>12%) is a better diagnostic marker for distinguishing SIADH patients from non-SIADH patients. CONCLUSION: FE-uric acid was found to be the most superior in diagnosing SIADH, followed by FE-Na.

Antioxidative effects of molybdenum and its association with reduced prevalence of hyperuricemia in the adult population.

The relationship between molybdenum and kidney-related disease outcomes, including hyperuricemia, is not well investigated. This study aims to determine whether molybdenum and its antioxidative property are associated with systemic inflammation and kidney-related disease parameters including hyperuricemia. Urinary molybdenum's epidemiological relationship to hyperuricemia and kidney-disease related outcomes was evaluated in 15,370 adult participants in the National Health and Nutrition Examination Survey (NHANES) collected between 1999 and 2016. Individuals' urinary molybdenum levels were corrected to their urinary creatinine concentrations. The association between urinary molybdenum-to-creatinine ratio and kidney-disease related outcomes were assessed by multivariable linear and logistic regression analyses, adjusting for covariates including age, sex, ethnicity, diabetes mellitus, hypertension, body mass index, and estimated glomerular filtration rate. Antimony and tungsten were used as control trace metals. Experimentally, HK-2 cell was used to assess molybdenum's antioxidative properties. HK-2 cells were challenged with H2O2-induced oxidative stress. Oxidative stress was measured using a fluorescent microplate assay for reactive oxygen species (ROS) and antioxidation levels were assessed by measuring the expression of manganese superoxide dismutase. In the adult NHANES population, urinary molybdenum-to-creatinine ratio was significantly associated with decreased serum uric acid (ß, -0.119; 95% CI, -0.148 to -0.090) concentrations, and decreased prevalence of hyperuricemia (OR, 0.73; 95% CI, 0.64-0.83) and gout (OR, 0.71; 95% CI, 0.52-0.94). Higher urinary molybdenum levels were associated with lower levels of systemic oxidative stress (gamma-glutamyltransferase levels; ß, -0.052; 95% CI, -0.067 to -0.037) and inflammation (C-reactive protein levels; ß, -0.184; 95% CI, -0.220 to -0.148). In HK-2 cells under H2O2-induced oxidative stress, molybdenum upregulated manganese superoxide dismutase expression and decreased oxidative stress. Urinary molybdenum levels are associated with decreased prevalence of hyperuricemia and gout in adult population. Molybdenum's antioxidative properties might have acted as an important mechanism for the reduction of systemic inflammation, ROS, and uric acid levels.

[First detection of the SLC2A9:p.C188F gene defect in a German Hunting Terrier with ammonium urate urolithiasis]. / Erstmaliger Nachweis des SLC2A9:p.C188F Gendefekts bei einem Deutschen Jagdterrier mit Ammoniumurat-Urolithiasis.

A 1,5-year-old intact male German Hunting Terrier was initially presented 2018 with hematuria. An abdominal ultrasound revealed multiple hyperechogenic structures in the urinary bladder. A urinalysis indicated severe crystalluria (ammonium urate or xanthine). Following cystotomy and urinary calculus analysis, ammonium urate urolithiasis was diagnosed in 2019. The patient was tested homozygous at the SLC2A9:p.C188F variant, which results in severe hyperuricemia and hyperuricosuria. This case report presents the first incidence of the SLC2A9:p.C188F gene variant being detected in a German Hunting Terrier. Veterinary practitioners are encouraged to consider the possibility of this gene defect presenting in breeds beyond the Dalmatian.

Utilizing Raman spectroscopy for urinalysis to diagnose acute kidney injury stages in cardiac surgery patients.

BACKGROUND: The successful treatment and improvement of acute kidney injury (AKI) depend on early-stage diagnosis. However, no study has differentiated between the three stages of AKI and non-AKI patients following heart surgery. This study will fill this gap in the literature and help to improve kidney disease management in the future. METHODS: In this study, we applied Raman spectroscopy (RS) to uncover unique urine biomarkers distinguishing heart surgery patients with and without AKI. Given the amplified risk of renal complications post-cardiac surgery, this approach is of paramount importance. Further, we employed the partial least squares-support vector machine (PLS-SVM) model to distinguish between all three stages of AKI and non-AKI patients. RESULTS: We noted significant metabolic disparities among the groups. Each AKI stage presented a distinct metabolic profile: stage 1 had elevated uric acid and reduced creatinine levels; stage 2 demonstrated increased tryptophan and nitrogenous compounds with diminished uric acid; stage 3 displayed the highest neopterin and the lowest creatinine levels. We utilized the PLS-SVM model for discriminant analysis, achieving over 90% identification rate in distinguishing AKI patients, encompassing all stages, from non-AKI subjects. CONCLUSIONS: This study characterizes the incidence and risk factors for AKI after cardiac surgery. The unique spectral information garnered from this study can also pave the way for developing an in vivo RS method to detect and monitor AKI effectively.

Metal-ligand dual-site single-atom nanozyme mimicking urate oxidase with high substrates specificity.

In nature, coenzyme-independent oxidases have evolved in selective catalysis using isolated substrate-binding pockets. Single-atom nanozymes (SAzymes), an emerging type of non-protein artificial enzymes, are promising to simulate enzyme active centers, but owing to the lack of recognition sites, realizing substrate specificity is a formidable task. Here we report a metal-ligand dual-site SAzyme (Ni-DAB) that exhibited selectivity in uric acid (UA) oxidation. Ni-DAB mimics the dual-site catalytic mechanism of urate oxidase, in which the Ni metal center and the C atom in the ligand serve as the specific UA and O2 binding sites, respectively, characterized by synchrotron soft X-ray absorption spectroscopy, in situ near ambient pressure X-ray photoelectron spectroscopy, and isotope labeling. The theoretical calculations reveal the high catalytic specificity is derived from not only the delicate interaction between UA and the Ni center but also the complementary oxygen reduction at the beta C site in the ligand. As a potential application, a Ni-DAB-based biofuel cell using human urine is constructed. This work unlocks an approach of enzyme-like isolated dual sites in boosting the selectivity of non-protein artificial enzymes.

Association of urinary excretion rates of uric acid with biomarkers of kidney injury in patients with advanced chronic kidney disease.

BACKGROUND: The potential influence of hyperuricemia on the genesis and progression of chronic kidney disease (CKD) remains controversial. In general, the correlation between blood levels of uric acid (UA) and the rate of progression of CKD is considered to be modest, if any, and the results of relevant trials oriented to disclose the effect of urate-lowering therapies on this outcome have been disappointing. Urinary excretion rates of UA could reflect more accurately the potential consequences of urate-related kidney injury. METHOD: Using a cross-sectional design, we investigated the correlation between different estimators of the rates of urinary excretion of UA (total 24-hour excretion, mean urinary concentration, renal clearance and fractional excretion)(main study variables), on one side, and urinary levels of selected biomarkers of kidney injury and CKD progression (DKK3, KIM1, NGAL, interleukin 1b and MCP)(main outcome variables), in 120 patients with advanced CKD (mean glomerular filtration rate 21.5 mL/minute). We took into consideration essential demographic, clinical and analytic variables with a potential confounding effect on the explored correlations (control variables). Spearman's rho correlation and nonlinear generalized additive regression models (GAM) with p-splines smoothers were used for statistical analysis. MAIN RESULTS: Multivariate analysis disclosed independent correlations between urinary UA concentrations, clearances and fractional excretion rates (but not plasma UA or total 24-hour excretion rates of UA), on one side, and the scrutinized markers. These correlations were more consistent for DKK3 and NGAL than for the other biomarkers. Glomerular filtration rate, proteinuria and treatment with statins or RAA axis antagonists were other independent correlates of the main outcome variables. CONCLUSIONS: Our results support the hypothesis that urinary excretion rates of UA may represent a more accurate marker of UA-related kidney injury than plasma levels of this metabolite, in patients with advanced stages of CKD. Further, longitudinal studies will be necessary, to disclose the clinical significance of these findings.

Urinary stone analysis and clinical characteristics of 496 patients in Taiwan.

Evaluate urinary stone components' epidemiological features in urolithiasis individuals and explore potential correlations between stone components and patients' clinical characteristics. A retrospective analysis of urinary stone compositions in 496 patients from a northern Taiwan medical center (February 2006 to October 2021) was conducted. We investigated associations between sex, age, body mass index (BMI), hypertension, diabetes mellitus (DM), hyperlipidemia (HLP), gout, coronary artery disease (CAD), cerebral vascular accident (CVA), chronic kidney disease (CKD), habits, urine pH, and three main stone groups: calcium oxalate (CaOx), calcium phosphate (CaP), and uric acid (UA). Males accounted for 66.5% of cases, with a male-to-female ratio of 1.99:1. Males were negatively associated with CaP stones (OR 0.313, p < 0.001) and positively with UA stones (OR 2.456, p = 0.009). Age showed a negative correlation with CaOx stones (OR 0.987, p = 0.040) and a positive correlation with UA stones (OR 1.023, p < 0.001). DM had a protective effect against CaP stones (OR 0.316, p = 0.004). Gout had a positive association with UA stones (OR 2.085, p = 0.035). Smoking was adversely associated with UA stones (OR 0.350, p = 0.018). Higher urine pH was a risk factor for CaP stones (OR 1.641, p = 0.001) and a protective factor against UA stones (OR 0.296, p < 0.001). These results may provide insights into the pathogenesis of urinary stones and the development of preventative strategies for high-risk populations. Further research is required to confirm and expand upon these findings.

Urine multi-index intelligent detection based on polymer/paper hybrid microfluidic biochip for hyperuricemia monitoring.

Hyperuricemia (HUA) has gradually become a public health burden as an independent risk factor for a variety of chronic diseases. Herein, a user-friendly point-of-care (POC) detection system (namely "Smart-HUA-Monitor") based on smartphone-assisted paper-based microfluidic is proposed for colorimetric quantification of HUA urinary markers, including uric acid (UA), creatinine (CR) and pH. The detection limits of UA and CR were 0.0178 and 0.5983 mM, respectively, and the sensitivity of pH were 0.1. The method was successfully validated in artificial urine samples and 100 clinical samples. Bland-Altman plots showed a high consistency between µPAD and the testing instruments (HITACHI 7600 Automatic Analyzer, URIT-500B Urine Analyzer and AU5800B automatic biochemical analyzer) in hospital. Smart-HUA-Monitor provides an accurate quantitative, rapid, low-cost and reliable tool for the monitoring and early diagnosis of HUA urine indicators.

A Novel Electrochemical Sensor Based on Pd Confined Mesoporous Carbon Hollow Nanospheres for the Sensitive Detection of Ascorbic Acid, Dopamine, and Uric Acid.

In this study, we designed a novel electrochemical sensor by modifying a glass carbon electrode (GCE) with Pd confined mesoporous carbon hollow nanospheres (Pd/MCHS) for the simultaneous detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA). The structure and morphological characteristics of the Pd/MCHS nanocomposite and the Pd/MCHS/GCE sensor are comprehensively examined using SEM, TEM, XRD and EDX. The electrochemical properties of the prepared sensor are investigated through CV and DPV, which reveal three resolved oxidation peaks for AA, DA, and UA, thereby verifying the simultaneous detection of the three analytes. Benefiting from its tailorable properties, the Pd/MCHS nanocomposite provides a large surface area, rapid electron transfer ability, good catalytic activity, and high conductivity with good electrochemical behavior for the determination of AA, DA, and UA. Under optimized conditions, the Pd/MCHS/GCE sensor exhibited a linear response in the concentration ranges of 300-9000, 2-50, and 20-500 µM for AA, DA, and UA, respectively. The corresponding limit of detection (LOD) values were determined to be 51.03, 0.14, and 4.96 µM, respectively. Moreover, the Pd/MCHS/GCE sensor demonstrated outstanding selectivity, reproducibility, and stability. The recovery percentages of AA, DA, and UA in real samples, including a vitamin C tablet, DA injection, and human urine, range from 99.8-110.9%, 99.04-100.45%, and 98.80-100.49%, respectively. Overall, the proposed sensor can serve as a useful reference for the construction of a high-performance electrochemical sensing platform.

Transient paper-based electrochemical biosensor Fabricated by superadditive Cu-TCPP(Fe)/Mxene for Multipathway non-invasive, highly sensitive detection of Bodily metabolites.

Current advances in non-invasive fluid diagnostics highlight unique benefits for monitoring metabolic diseases. However, the low concentrations and complex compositions of biomarkers in fluids such as sweat, urine, and saliva impose stringent demands on the sensitivity and stability of detection technologies. Here, we developed a high-sensitivity, low-cost instantaneous electrochemical sensor based on the superadditive effect mechanism of Cu-TCPP(Fe)/Mxene (MMs Paper-ECL Sensor), which has been successfully applied for the simultaneous real-time detection of glucose and uric acid. Strong interfacial interactions between Mxene and Cu-TCPP(Fe) were revealed through precise simulation calculations and multi-dimensional characterization analysis, significantly enhancing the sensor's electrocatalytic performance and reaction kinetics. Experimentally, this exceptional electrocatalytic activity was demonstrated in its unprecedented high sensitivity and wide linear detection range for glucose and uric acid, with a non-invasive linear range from 0.001 nM to 5 mM, 0.025 nM-5 mM, detection limits as low as 1.88 aM and 5.80 pM, and stability extending up to 100 days. This represents not only a breakthrough in sensitivity and stability but also provides an effective, low-cost solution that overcomes the limitations of existing electronic devices, enabling multi-channel simultaneous detection. The universality of this sensor holds vast potential for application in the field of non-invasive fluid diagnostics.

Association between caffeine metabolites in urine and muscle strength in young and older adults: A cross-sectional study from NHANES 2011-2012.

BACKGROUND: Elevated levels of reactive oxygen species may contribute to the gradual decline in muscle strength over time. Although caffeine and its metabolites have antioxidant properties that can mitigate oxidative stress, the association of caffeine and its metabolites with muscle strength remains unknown. AIM: To investigate whether caffeine metabolites in urine are associated with muscle strength in young and older adults. METHODS: A cross-sectional study was conducted with 1145 individuals aged over 20 years (n = 801 < 60 years and n = 344 ≥ 60 years) from the National Health and Nutrition Examination Survey (NHANES) 2011-2012. Muscle strength was assessed using a handgrip dynamometer, and combined grip strength was determined by summing the highest value from each hand. Caffeine and its metabolites in urine were quantified using ultra-high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (1-methyluric acid, 3-methyluric acid, 7-methyluric acid, 1,3-dimethyluric acid, 1,7-dimethyluric acid, 3,7-dimethyluric acid, 1,3,7-trimethyluric acid, 1-methylxanthine, 3-methylxanthine, 7-methylxanthine, 1,3-dimethylxanthine, 1,7-dimethylxanthine, 3,7-dimethylxanthine, 1,3,7-trimethylxanthine, 5-acetylamino-6-amino-3-methyluracil). Linear regression analyses were performed to determine the association of caffeine and its metabolites with muscle strength in young and older adults, adjusting for confounders. RESULTS: Positive associations between muscle strength and levels of 7-methyluric acid (ß = 0.029; p = 0.021), 1,3-dimethyluric acid (ß = 0.008; p = 0.004), 3,7-dimethyluric acid (ß = 0.645; p = 0.012), 3-methylxanthine (ß = 0.020; p = 0.002), 7-methylxanthine (ß = 0.020; p = 0.006), 1,3-dimethylxanthine (theophylline) (ß = 0.030; p = 0.004) and 3,7-dimethylxanthine (theobromine) (ß = 0.035; p = 0.029) were observed in older adults. In contrast, no such associations were noted in young adults. CONCLUSION: Our study indicates a positive association between certain caffeine metabolites in urine and muscle strength in older adults, but not in younger individuals. These findings indicate that specific caffeine metabolites may contribute to an antioxidant role especially in older adults.

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.

Development of a paper-based transcription aptasensor for convenient urinary uric acid self-testing.

The abnormal uric acid (UA) level in urine can serve as warning signals of many diseases, such as gout and metabolic cardiovascular diseases. The current methods for detecting UA face limitations of instrument dependence and the requirement for non-invasiveness, making it challenging to fulfill the need for home-based application. In this study, we designed an aptasensor that combined UA-specific transcriptional regulation and a fluorescent RNA aptamer for convenient urinary UA testing. The concentration of UA can be translated into the intensity of fluorescent signals. The aptasensor showed higher sensitivity and more robust anti-interference performance. UA levels in the urine of different volunteers could be accurately tested using this method. In addition, a paper-based aptasensor for UA self-testing was manufactured, in which the urinary UA levels could be determined using a smartphone-based colorimetric approach. This work not only demonstrates a new approach for the design of disease-associated aptasensor, but also offers promising ideas for home-based detection of UA.

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.

24-Hour Urinary Chemistries and Kidney Stone Risk.

RATIONALE & OBJECTIVE: Most previous studies of the relationship between urinary factors and kidney stone risk have either assumed a linear effect of urinary parameters on kidney stone risk or implemented arbitrary thresholds suggesting biologically implausible "all-or-nothing" effects. In addition, little is known about the hierarchy of effects of urinary factors on kidney stone risk. This study evaluated the independent associations between urine chemistries and kidney stone formation and examined their magnitude and shape. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: We analyzed 9,045 24-hour urine collections from 6,217 participants of the Health Professionals Follow-Up Study and Nurses' Health Studies I and II. EXPOSURE: Urine volume and pH, and concentrations of calcium, citrate, oxalate, potassium, magnesium, uric acid, phosphorus, and sodium. OUTCOME: Incident symptomatic kidney stones. ANALYTICAL APPROACH: Multivariable logistic regression analysis incorporating restricted cubic splines to explore potentially nonlinear relationships between urinary factors and the risk of forming a kidney stone. Optimal inflection point analysis was implemented for each factor, and dominance analysis was performed to establish the relative importance of each urinary factor. RESULTS: Each urinary factor was significantly associated with stone formation except for urine pH. Higher urinary levels of calcium, oxalate, phosphorus, and sodium were associated with a higher risk of stone formation whereas higher urine volume, uric acid, citrate, potassium, and magnesium were associated with a lower risk. The relationships were substantially linear for urine calcium, uric acid, and sodium. By contrast, the magnitudes of the relationships were modestly attenuated at levels above the inflection points for urine oxalate, citrate, volume, phosphorus, potassium, and magnesium. Dominance analysis identified 3 categories of factors' relative importance: higher (calcium, volume, and citrate), intermediate (oxalate, potassium, and magnesium), and lower (uric acid, phosphorus, and sodium). LIMITATIONS: Predominantly White participants, lack of information on stone composition. CONCLUSIONS: Urine chemistries have complex relationships and differential relative associations with the risk of kidney stone formation. PLAIN-LANGUAGE SUMMARY: Kidney stones are common and likely to recur. Certain urinary factors play a role in the development of stones, but their independent roles, relative importance, and shapes of association with stone formation are not well-characterized. We analyzed 24-hour urine collections from individuals with and without kidney stones. Stones were less likely in those with higher urine volume, citrate, potassium, magnesium, and uric acid and were more likely in those with higher calcium, oxalate, phosphorus, and sodium. The acidity of the urine was not related to stones. The urinary parameters showed different degrees of relative importance, with calcium, volume, and citrate being greatest. All parameters exhibited a linear or close-to-linear shape of association with stone formation.

Machine learning-enhanced drug testing for simultaneous morphine and methadone detection in urinary biofluids.

The simultaneous identification of drugs has considerable difficulties due to the intricate interplay of analytes and the interference present in biological matrices. In this study, we introduce an innovative electrochemical sensor that overcomes these hurdles, enabling the precise and simultaneous determination of morphine (MOR), methadone (MET), and uric acid (UA) in urine samples. The sensor harnesses the strategically adapted carbon nanotubes (CNT) modified with graphitic carbon nitride (g-C3N4) nanosheets to ensure exceptional precision and sensitivity for the targeted analytes. Through systematic optimization of pivotal parameters, we attained accurate and quantitative measurements of the analytes within intricate matrices employing the fast Fourier transform (FFT) voltammetry technique. The sensor's performance was validated using 17 training and 12 test solutions, employing the widely acclaimed machine learning method, partial least squares (PLS), for predictive modeling. The root mean square error of cross-validation (RMSECV) values for morphine, methadone, and uric acid were significantly low, measuring 0.1827 µM, 0.1951 µM, and 0.1584 µM, respectively, with corresponding root mean square error of prediction (RMSEP) values of 0.1925 µM, 0.2035 µM, and 0.1659 µM. These results showcased the robust resiliency and reliability of our predictive model. Our sensor's efficacy in real urine samples was demonstrated by the narrow range of relative standard deviation (RSD) values, ranging from 3.71 to 5.26%, and recovery percentages from 96 to 106%. This performance underscores the potential of the sensor for practical and clinical applications, offering precise measurements even in complex and variable biological matrices. The successful integration of g-C3N4-CNT nanocomposites and the robust PLS method has driven the evolution of sophisticated electrochemical sensors, initiating a transformative era in drug analysis.

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.

Genetic Determinants of Thiazide-Induced Hyperuricemia, Hyperglycemia, and Urinary Electrolyte Disturbances - A Genome-Wide Evaluation of the UK Biobank.

Thiazide diuretics, widely used in hypertension, cause a variety of adverse reactions, including hyperglycemia, hyperuricemia, and electrolyte abnormalities. In this study, we aimed to identify genetic variants that interact with thiazide-use to increase the risk of these adverse reactions. Using UK Biobank data, we first performed genomewide variance quantitative trait locus (vQTL) analysis of ~ 6.2 million SNPs on 95,493 unrelated hypertensive White British participants (24,313 on self-reported bendroflumethiazide treatment at recruitment) for 2 blood (glucose and urate) and 2 urine (potassium and sodium) biomarkers. Second, we conducted direct gene-environment interaction (GEI) tests on the significant (P < 2.5 × 10-9) vQTLs, included a second UK Biobank cohort comprising 13,647 unrelated hypertensive White British participants (3,478 on thiazides other than bendroflumethiazide) and set significance at P = 0.05 divided by the number of vQTL SNPs tested for GEIs. The vQTL analysis identified eight statistically significant SNPs for blood glucose (5 SNPs) and serum urate (3 SNPs), with none being identified for the urinary biomarkers. Two of the SNPs (1 glucose SNP: CDKAL1 intron rs35612982, GEI P = 6.24 × 10-3; and 1 serum urate SNP: SLC2A9 intron rs938564, GEI P = 4.51 × 10-4) demonstrated significant GEI effects in the first, but not the second, cohort. Both genes are biologically plausible candidates, with the SLC2A9-mediated interaction having been previously reported. In conclusion, we used a two-stage approach to detect two biologically plausible genetic loci that can interact with thiazides to increase the risk of thiazide-associated biochemical abnormalities. Understanding how environmental exposures (including medications such as thiazides) and genetics interact, is an important step toward precision medicine and improved patient outcomes.