Background: Clear cell renal cell carcinoma (ccRCC) comprises the majority, approximately 70–80%, of renal cancer cases and often remains asymptomatic until incidentally detected during unrelated abdominal imaging or at advanced stages. Currently, standardized screening tests for renal cancer are lacking, which presents challenges in disease management and improving patient outcomes. This study aimed to identify ccRCC-specific volatile organic compounds (VOCs) in the urine of ccRCC-positive patients and develop a urinary VOC-based diagnostic model. Methods: This study involved 233 pretreatment ccRCC patients and 43 healthy individuals. VOC analysis utilized stir-bar sorptive extraction coupled with thermal desorption gas chromatography/mass spectrometry (SBSE-TD-GC/MS). A ccRCC diagnostic model was established via logistic regression, trained on 163 ccRCC cases versus 31 controls, and validated with 70 ccRCC cases versus 12 controls, resulting in a ccRCC diagnostic model involving 24 VOC markers. Results: The findings demonstrated promising diagnostic efficacy, with an Area Under the Curve (AUC) of 0.94, 86% sensitivity, and 92% specificity. Conclusions: This study highlights the feasibility of using urine as a reliable biospecimen for identifying VOC biomarkers in ccRCC. While further validation in larger cohorts is necessary, this study’s capability to differentiate between ccRCC and control groups, despite sample size limitations, holds significant promise.

Perfluoroalkyl carboxylic acids (PFCAs) are a significant group of per- and polyfluoroalkyl substances (PFASs). They are persistent organic chemicals manufactured for their resistance to heat, water, and stains. PFCAs are ubiquitous in the environment, particularly in surface water and wastewater, because they are widely used in everyday consumer products. This contamination poses a risk to drinking water supplies and human health, necessitating sensitive and effective analytical methods. Traditional liquid chromatography–tandem mass spectrometry (LC-MS/MS) is commonly used but involves complex sample handling and high costs. In this study, we developed an enhanced stir bar sorptive extraction (SBSE) method coupled with thermal desorption–gas chromatography–mass spectrometry (TD-GC-MS) for the analysis of PFCAs in water. This method demonstrates linearity, with R² values from 0.9892 to 0.9988, and low limits of detection (LOD) between 21.17 ng/L and 73.96 ng/L. Recovery rates varied from 47 to 97%, suggesting efficient extraction. Compared to traditional methods, the developed SBSE technique requires only a 1 mL sample volume and minimal amounts of solvents, enhancing eco-friendliness and reducing potential contamination and handling errors. This method also demonstrated good precision and robustness across various water matrices. Overall, the developed method offers a precise, eco-friendly, and reliable approach for analyzing PFCAs in diverse water samples.

Cancer is one of the leading causes of death globally, and is ranked second in the United States. Early detection is crucial for more effective treatment and a higher chance of survival rates, reducing burdens on individuals and societies. Genitourinary cancers, in particular, face significant challenges in early detection. Finding new and cost-effective diagnostic methods is of clinical need. Metabolomic-based approaches, notably volatile organic compound (VOC) analysis, have shown promise in detecting cancer. VOCs are small organic metabolites involved in biological processes and disease development. They can be detected in urine, breath, and blood samples, making them potential candidates for sensitive and non-invasive alternatives for early cancer detection. However, developing robust VOC detection methods remains a hurdle. This review outlines the current landscape of major genitourinary cancers (kidney, prostate, bladder, and testicular), including epidemiology, risk factors, and current diagnostic tools. Furthermore, it explores the applications of using VOCs as cancer biomarkers, various analytical techniques, and comparisons of extraction and detection methods across different biospecimens. The potential use of VOCs in detection, monitoring disease progression, and treatment responses in the field of genitourinary oncology is examined.

Background/objectives: Prostate cancer (PCa) is the most common cancer among males. Approximately 20–40% of patients with clinically localized PCa will present with a biochemical recurrence after a radical prostatectomy (RP), while some will present with recurrent metastasis. Monitoring the disease post-treatment is crucial for detecting a potential cancer recurrence early. Urinary volatile organic compounds (VOCs) have shown potential to detect PCa. However, their application in disease monitoring remains unexplored. Methods: A total of 165 urine samples were collected from male adults with biopsy-designated PCa-positive results before (n = 55) and after a RP (n = 55), and with biopsy-designated PCa-negative diagnosis (n = 55). The post-RP cohort was subdivided into three groups based on their health status after surgery as recovered healthy, biochemical recurrence, and recurrent metastasis. VOCs in the urine samples were extracted by stir bar sorptive extraction and analyzed using gas chromatography and mass spectrometry. We explored the use of metabolomics and a machine learning algorithm tool to investigate the potential of using VOCs for differentiating PCa diagnoses before and after the RP procedure with different outcomes. Results: Over 100 potential VOCs were identified to differentiate PCa patients before and after a RP, and those with biochemical recurrence and recurrent metastasis. Conclusions: Urinary VOCs are promising biomarkers that could be used to differentiate PCa patients pre- and post-RP. The findings from this research provide preliminary insights and could aid future investigations in developing tools for PCa patients after treatment. The absence of a validation cohort limits the reproducibility and translational impact of these findings; therefore, the results should be considered exploratory and require confirmation in larger, independent cohorts.

In this study, eco-friendly and sustainable alginate-activated carbon (Alg-C)-based beads were synthesized and characterized for the adsorption of nonylphenols (NPs) from aqueous environments under various conditions. The surface characterization, functional groups, and adsorption behavior were analyzed using multiple analytical techniques. The effect of key parameters, including dosage, pH, temperature, and reusability, were evaluated. Isotherm and kinetic studies revealed that the adsorption process followed a pseudo-second-order kinetic model and aligned with the Freundlich isotherm, indicating a heterogeneous surface. The beads exhibited a high removal efficiency of 97% over five reuse cycles in a 50 mL solution of 10 mg L⁻¹ NPs under static conditions, demonstrating their recyclability. Thermodynamic analysis suggested potential electrostatic interactions, supported by positive Gibbs free energy values. The highest removal performance was achieved within 90 min, with adsorption capacities from 0.10 to 0.39 mg g⁻¹. Additionally, the performance of Alg-C beads remained stable across different pH levels, highlighting their robustness. When tested with wastewater samples, Alg-C beads maintained high removal efficiency, with no significant matrix effects observed. These results underscore Alg-C beads as a promising and sustainable solution for the elimination of NPs from contaminated water sources.