Relationship between Urine Creatinine and Urine Osmolality in Spot Samples among Men and Women in the Danish Diet Cancer and Health Cohort

Simultaneous Detection of Biomarkers in Urine Using a Multicalibration Potentiometric Sensing Array Combined with a Portable Analyzer

Domestic monitoring devices make real-time and long-term health monitoring possible, allowing people to track their health status regularly. Uric acid (UA), creatinine, and urea in urine are three important biomarkers for various diseases, especially kidney diseases. This work proposed a 10-channel potentiometric sensing array containing a UA electrode group, a creatinine electrode group, a urea electrode group, a pH electrode group, and one pair of reference channels, which could be connected with a portable potentiometric analyzer, realizing the simultaneous detection of UA, creatinine, urea, and pH in urine. The prepared Pt/carbon nanotubes (CNTs)-uricase, creatinine deiminase, Au@urease, and polyaniline were employed as the sensing materials, showing responses to four targets with high sensitivity and selectivity. To improve the accuracy of domestic monitoring, a calibration channel was integrated into each electrode group to calibrate the basic potential of the sensing channels, and the influences of pH and temperature on the responses were investigated through the pH electrode group and an external temperature probe to calibrate the slope and intercept. With the preset of the deduced calibration parameters and computational formula for the four targets in the analyzer in Lab Mode, the concentrations of UA, creatinine, and urea and the pH of the human urine samples were directly displayed on the screen of the analyzer in Practical Mode. The agreement of these results with those obtained from commercial kits and pH meters reveals the high potential of these methods for developing domestic devices to facilitate health monitoring.

Interpretable machine learning for predicting the response duration to Sintilimab plus chemotherapy in patients with advanced gastric or gastroesophageal junction cancer

Background

Sintilimab plus chemotherapy has proven effective as a combination immunotherapy for patients with advanced gastric and gastroesophageal junction adenocarcinoma (GC/GEJC). A multi-center study conducted in China revealed a median progression-free survival (PFS) of 7.1 months. However, the prediction of response duration to this immunotherapy has not been thoroughly investigated. Additionally, the potential of baseline laboratory features in predicting PFS remains largely unexplored. Therefore, we developed an interpretable machine learning (ML) framework, iPFS-SC, aimed at predicting PFS using baseline (pre-treatment) laboratory features and providing interpretations of the predictions.

Materials and methods

A cohort of 146 patients with advanced GC/GEJC, along with their baseline laboratory features, was included in the iPFS-SC framework. Through a forward feature selection process, predictive baseline features were identified, and four ML algorithms were developed to categorize PFS duration based on a threshold of 7.1 months. Furthermore, we employed explainable artificial intelligence (XAI) methodologies to elucidate the relationship between features and model predictions.

Results

The findings demonstrated that LightGBM achieved an accuracy of 0.70 in predicting PFS for advanced GC/GEJC patients. Furthermore, an F1-score of 0.77 was attained for identifying patients with PFS durations shorter than 7.1 months. Through the feature selection process, we identified 11 predictive features. Additionally, our framework facilitated the discovery of relationships between laboratory features and PFS.

Conclusion

A ML-based framework was developed to predict Sintilimab plus chemotherapy response duration with high accuracy. The suggested predictive features are easily accessible through routine laboratory tests. Furthermore, XAI techniques offer comprehensive explanations, both at the global and individual level, regarding PFS predictions. This framework enables patients to better understand their treatment plans, while clinicians can customize therapeutic approaches based on the explanations provided by the model.

An Explorative Study into the Aetiology of Developmental Dysplasia of the Hip Using Targeted Urine Metabolomics

Developmental dysplasia of the hip (DDH) is the most prevalent congenital musculoskeletal disorder, yet its cause remains unknown. Adequate nutrient provision and coordinated electron exchange (redox) processes are critical for foetal growth and tissue development. This novel study sought to explore specific biochemical pathways in skeletal development for potential involvement in the aetiology of DDH. Spot urine samples were collected from infants, aged 13–61 days, with and without DDH. Ion chromatography-mass spectrometry was used to quantify thiosulphate, sulphate, nitrate, and phosphate, whilst nitrite was quantified using high-performance liquid chromato-graphy. Thiobarbituric acid reactive substances (TBARS) were measured as markers of lipid peroxidation. Creatinine and osmolality were determined by a 96-well plate assay and micro-osmometer to potentially normalise values for renal function, lean body mass, and hydration status. Urine samples were analysed from 99 babies: 30 with DDH and 69 age-matched non-DDH controls. Thiosulphate, TBARS, and creatinine concentrations differed between the DDH group and the controls (p = 0.025, 0.015, and 0.004 respectively). Urine osmolality was significantly lower in DDH compared to the controls (p = 0.036), indicative of the production of a more diluted urine in DDH infants. Following adjustment for osmolality, significant differences became apparent in urinary sulphate levels in DDH (p = 0.035) whereas all other parameters were similar between the groups. This is the first study to assess the potential role of these inorganic anions in DDH. The higher levels of sulphate found in infants with DDH suggests either enhanced intake from milk, increased endogenous formation, or impaired renal reabsorption. This investigation demonstrates the power of urine metabolomics and highlights the importance of normalisation for hydration status to disentangle developmental disorders. Our results strongly suggest that DDH is a systemic disease associated with altered uptake, formation, or handling of sulphate. There is potential for new opportunities in the prevention or treatment of DDH via nutritional intervention.

Reference Intervals of Spot Urine Creatinine-to-Osmolality Ratio as a Surrogate of Urinary Creatinine Excretion Rate

A spot urine creatinine-to-osmolality ratio (sUCr/Osm) is proposed as a surrogate of the urinary excretion rate of creatinine (Cr) and convenient for forecasting serum Cr (SCr) trends. The lower the sUCr/Osm, the lower the excreted Cr amount accompanied by per unit of osmoles, the higher the risk of Cr accumulation. For exploring the reference intervals of sUCr/Osm in general adults, a cross-sectional analysis was performed on a subset of data from the National Health and Nutrition Examination Survey (NHANES) 2011–2012. Of the eligible 3,316 adults aged 18.0 to 79.9 years, the age (mean ± SD) was 45.2 ± 17.2 years old, women was 45.02%, body weight (BW) was 76.1 ± 14.5 kg, and African Americans was 23.6%. Blood urea nitrogen (BUN) was 12.6 ± 4.7 mg/dL; SCr was 0.89 ± 0.34 mg/dL. As spot urine Cr and osmolality were 127.1 ± 84.0 mg/dl and 649 ± 266 mOsm/kg, respectively, sUCr/Osm was 0.19 ± 0.08. With adjustment of factors related to personal urinary excretion of Cr and osmoles by multivariable regression analysis, the estimated sUCr/Osm (esUCr/Osm) for an individual was 0.153 × (age in year)^−0.070 × (BW in kg)^0.283 × 1.244 [if African American] × (BUN in mg/dL)^−0.310 × (SCr in mg/dL)^0.681. The index of sUCr/Osm to personalized esUCr/Osm was 1.05 ± 0.39. When only low urinary excretion of Cr is likely to be of clinical concern, further analysis showed 157 individuals (4.7%, outside the 5th percentile) had their original sUCr/Osm < 0.08; 157 had the sUCr/Osm indexed for personalized esUCr/Osm < 0.50.