Search Results (23)

Background: Currently there are no clinically validated biomarkers recommended for prostate cancer (PCa) risk stratification other than prostate-specific antigen (PSA). Objective: This study aimed to identify urine metabolites that are associated with the presence of high-grade PCa at the time of radical prostatectomy. Methods: Urine samples were collected from patients who underwent radical prostatectomy. High-resolution metabolomics were implemented using liquid chromatography mass spectrometry (LC-MS). To enhance metabolic feature identification, sample extracts were analyzed in two modes, C18 chromatography [reverse-phase (RP)] and hydrophilic interaction chromatography (HILIC). Results: This analysis included a total of 22 patients with PCa (10 high-grade and 12 low-grade) and identified 52 differential metabolites, 40 in RP and 12 in HILIC, at the p-value 0.05 level. Among these, methyl alpha-aspartyl phenylalaninate was most significantly differentiated, while 3-methylbutanoicacid had the largest difference (slope −3.488). In the pathway analysis, the histidine metabolism pathway was significantly enriched (p < 0.05) with an enrichment factor of 3.5. Although not statistically significant, alterations were also observed in the vitamin B12, B7 (biotin), B6, and B3 (niacin) pathways. Conclusions: These findings suggest that urinary metabolites may have the potential to differentiate high-grade from low-grade PCa. Our study also highlights the metabolic reprogramming that occurs as PCa becomes more aggressive and potential differences in dietary patterns. Full article

Heavy metal(loid) (HM) contamination in water arises from various anthropogenic activities and natural processes, posing risks to human health through ingestion and dermal absorption. Although numerous studies have assessed health risks associated with HMs in water, inconsistencies in the selection of exposure and toxicity factors limit comparability and reliability across studies. To address this gap, the aim of this review was to provide a comprehensive synthesis of exposure and toxicity factors used in health risk assessment (HRA) of HMs in water. The objectives were to evaluate the variability in ingestion, body weight, exposure duration and frequency, and dermal contact parameters, as well as in reference doses and cancer slope factors and to propose standardized values and statistical distributions for more consistent risk estimation. A systematic search of the Scopus database retrieved 806 studies, from which highly cited articles (≥100 citations) and recent publications (2023–2025) were prioritized for analysis. The findings revealed substantial variability in factors and showed that probabilistic approaches, particularly Monte Carlo simulation, were increasingly applied and provided more reliable estimates than traditional deterministic methods. The highest agreement was observed for exposure frequency for ingestion (365 days/year) and skin surface area (18,000 cm²), each applied in 75.5% of cases. By identifying inconsistencies in current practices and proposing standardized exposure and toxicity values and distributions for water, this review is expected to offer practical recommendations to improve the robustness, reliability, and comparability of HRAs, ultimately informing more effective policy-making and water management practices. Full article

Background/Objectives: Cancer is a major public health burden in Serbia and a factor influencing long-term disaster readiness by straining health system capacity. This study examined spatial and temporal trends in incidence and mortality for eight major cancers among women in Central Serbia (1999–2021) to inform targeted prevention and preparedness strategies. Methods: Standardised rates from national datasets were analysed using the Mann–Kendall trend test and Sen’s slope estimator. Geographic disparities were mapped in ArcGIS Pro 3.2. Mortality trends were assessed only for statistically reliable series. Results: Breast cancer incidence increased in six counties, while cervical cancer declined in several areas, likely reflecting screening success. Colorectal, bladder, pancreatic, and lung and bronchus cancers showed rising incidence; lung and bronchus cancer mortality increased in 16 counties, indicating growing demand for chronic respiratory care. These shifts may reduce surge capacity during disasters by increasing the baseline burden on healthcare infrastructure. Regional disparities highlight uneven system resilience. Conclusions: Aligning cancer control measures—especially for high-burden cancers like lung—with emergency preparedness frameworks is essential to strengthen health system resilience, particularly in resource-limited regions. Full article

Background/Objectives: The clinically validated multiplex Oncuria bladder cancer (BC) assay quickly and noninvasively identifies disease risk and tracks treatment success by simultaneously profiling 10 protein biomarkers in voided urine samples. Oncuria uses paramagnetic bead-based fluorescence multiplex technology (xMAP^®; Luminex, Austin, TX, USA) to simultaneously measure 10 protein analytes in urine [angiogenin, apolipoprotein E, carbonic anhydrase IX (CA9), interleukin-8, matrix metalloproteinase-9 and -10, alpha-1 anti-trypsin, plasminogen activator inhibitor-1, syndecan-1, and vascular endothelial growth factor]. Methods: In a pilot study (N = 36 subjects; 18 with BC), Oncuria performed essentially identically across three different common analyzers (the laser/flow-based FlexMap 3D and 200 systems, and the LED/image-based MagPix system; Luminex). The current study compared Oncuria performance across instrumentation platforms using a larger study population (N = 181 subjects; 51 with BC). Results: All three analyzers assessed all 10 analytes in identical samples with excellent concordance. The percent coefficient of variation (%CV) in protein concentrations across systems was ≤2.3% for 9/10 analytes, with only CA9 having %CVs > 2.3%. In pairwise correlation plot comparisons between instruments for all 10 biomarkers, R² values were 0.999 for 15/30 comparisons and R² ≥ 0.995 for 27/30 comparisons; CA9 showed the greatest variability (R² = 0.948–0.970). Standard curve slopes were statistically indistinguishable for all 10 biomarkers across analyzers. Conclusions: The Oncuria BC assay generates comprehensive urinary protein signatures useful for assisting BC diagnosis, predicting treatment response, and tracking disease progression and recurrence. The equivalent performance of the multiplex BC assay using three popular analyzers rationalizes test adoption by CLIA (Clinical Laboratory Improvement Amendments) clinical and research laboratories. Full article

Camptotheca acuminata Decne. is an endemic and valuable tree species in China that is renowned for its medicinal and economic value due to secondary metabolites like camptothecin, a potent anti-cancer compound. With wild resources dwindling, it is a key protected species. Predicting and analyzing its suitable habitats under different future environmental scenarios is essential for conservation, introduction, development, and planting strategies. This study used 1008 distribution points and 32 environmental factors, applying the MaxEnt v3.4.4 model and ArcGIS v10.7 software to predict C. acuminata’s potential distribution under four greenhouse gas emission scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) for the present, 2050, and 2070. This study identifies the key environmental factors influencing its distribution and analyzes habitat trends under various ecological scenarios. The dominant environmental factors are Bio6 (contribution 23%; importance 59.8%), human activity factor (contribution 18.6%; importance 15.7%), Slope2 (contribution 1%; importance 7%), Slope3 (contribution 5.1%; importance 3.4%), elevation (contribution 0.9%; importance 1.7%), and Bio14 (contribution 41.2%; importance 1%). The total potential suitable habitat area for C. acuminata is 1.5796 × 10⁴ km². Except under RCP8.5, where the habitat area continuously increases, the habitat area shows a trend of first increasing and then decreasing. When human activity is considered, the total potential suitable habitat area is 1.8495 × 10⁴ km², with a consistent decrease under all scenarios except RCP8.5. Centroid migration analysis shows that, driven by global warming, the suitable habitats for C. acuminata are shifting toward higher latitudes. This study provides theoretical support for the conservation, resource management, and germplasm protection of C. acuminata under future ecological and environmental changes. Full article

Probability calibration and decision threshold selection are fundamental aspects of risk prediction and classification, respectively. A strictly proper loss function is used in clinical risk prediction applications to encourage a model to predict calibrated class-posterior probabilities or risks. Recent studies have shown that training with focal loss can improve the discriminatory power of gradient-boosted decision trees (GBDT) for classification tasks with an imbalanced or skewed class distribution. However, the focal loss function is not a strictly proper loss function. Therefore, the output of GBDT trained using focal loss is not an accurate estimate of the true class-posterior probability. This study aims to address the issue of poor calibration of GBDT trained using focal loss in the context of clinical risk prediction applications. The methodology utilizes a closed-form transformation of the confidence scores of GBDT trained with focal loss to estimate calibrated risks. The closed-form transformation relates the focal loss minimizer and the true-class posterior probability. Algorithms based on Bayesian hyperparameter optimization are provided to choose the focal loss parameter that optimizes discriminatory power and calibration, as measured by the Brier score metric. We assess how the calibration of the confidence scores affects the selection of a decision threshold to optimize the balanced accuracy, defined as the arithmetic mean of sensitivity and specificity. The effectiveness of the proposed strategy was evaluated using lung transplant data extracted from the Scientific Registry of Transplant Recipients (SRTR) for predicting post-transplant cancer. The proposed strategy was also evaluated using data from the Behavioral Risk Factor Surveillance System (BRFSS) for predicting diabetes status. Probability calibration plots, calibration slope and intercept, and the Brier score show that the approach improves calibration while maintaining the same discriminatory power according to the area under the receiver operating characteristics curve (AUROC) and the H-measure. The calibrated focal-aware XGBoost achieved an AUROC, Brier score, and calibration slope of 0.700, 0.128, and 0.968 for predicting the 10-year cancer risk, respectively. The miscalibrated focal-aware XGBoost achieved equal AUROC but a worse Brier score and calibration slope (0.140 and 1.579). The proposed method compared favorably to the standard XGBoost trained using cross-entropy loss (AUROC of 0.755 versus 0.736 in predicting the 1-year risk of cancer). Comparable performance was observed with other risk prediction models in the diabetes prediction task. Full article

Background/Objectives: Research on the relationship between small-area-level deprivation and cancer survival, particularly for colorectal cancer (CRC), is lacking. Therefore, we investigated the relationship among small area-level deprivation, individual-level factors, and CRC survival using data from the Busan Regional Cancer Registry. Methods: We analyzed 34,999 patients with CRC from the Busan Regional Cancer Registry from 2003 to 2020. The primary outcome was CRC mortality. The explanatory variables at the individual level included age, gender, cancer stage, and year of diagnosis, whereas the Deprivation Index (DI) was used at the regional level. We conducted a multilevel survival analysis with frailty to assess the impact of individual- and area-level factors on survival probabilities. Results: In the multilevel survival model, each unit increase in the DI at the area level was associated with a 6.6% decrease in survival probability. When applying Model 2 and deriving regional estimates using the empirical Bayesian estimation method, the graph of the DI (x-axis) against survival probability (y-axis) showed that the slope of the regional DI for the 3-year and 5-year survival probabilities increased compared with the 1-year rate across all stages of the disease. Additionally, the slopes were steeper for the distant stage than for the local or regional stages. Conclusions: Small-area level deprivation negatively affects CRC survival, especially in distant-stage patients and those with longer disease duration. Full article

The rapid development of the global chemical industry has led to widespread groundwater contamination, with frequent pollution incidents posing severe threats to water safety. However, there has been insufficient assessment of the health risks posed by chlorinated hydrocarbon contamination in groundwater around chemical industrial parks. This study evaluates the chlorinated hydrocarbon contamination in groundwater at a chemical park and conducts a multi-pathway health risk assessment, identifying the key risk pollutants. In addition, sensitivity analysis of the primary exposure pathways was performed using the Monte Carlo method. The results indicate severe exceedance of pollutant concentrations with widespread diffusion. Carcinogenic risks were mainly driven by vinyl chloride, whose oral cancer slope factor was significantly higher than that of other substances, while non-carcinogenic risks were dominated by trichloro-ethylene, which had the lowest reference dose. Both carcinogenic and non-carcinogenic risks through the drinking water pathway accounted for approximately 90% of the total risk, whereas the risk contribution from dermal contact was negligible. Although boiling water can partially reduce the risks, its effect on high-concentration pollutants is limited. Additionally, sensitivity analysis showed that pollutant concentration was the primary influencing factor for risk values, followed by exposure duration. The findings of this study provide a scientific basis for effectively formulating pollution control measures and ensuring the drinking water safety of nearby residents. Full article

Our previous work demonstrated the presence of lead (Pb) and cadmium (Cd) contamination in cow milk (CM) and soy beverages (SBs) in Portugal. These metals share carcinogenic mechanisms, suggesting at least additive effects. Our goals were to assess carcinogenic risks from Pb and Cd intake detected in various CM and SB brands on the Portuguese market and to determine the relative contributions of Pb and Cd. Furthermore, we modeled different consumption scenarios for various age/body weight groups to estimate cumulative Excess Lifetime Carcinogenic Risk (ELCR). ELCR was computed by multiplying chronic daily intake by a cancer slope factor for each metal, with an ELCR > 1 × 10⁻⁴ indicating carcinogenic risk. Five CM and three SB brands posed cancer risks in children, with the highest values at 1.75 × 10⁻⁴ and 9.12 × 10⁻⁵, respectively; Pb had mean relative contributions of 87.8 ± 3.1% in CM and 54.9 ± 12.1% in SB. Carcinogenic risks were observed for children, adolescents, and adults in several CM or SB consumption scenarios, albeit at levels above typical Portuguese intakes. Strict monitoring of metal levels, such as Pb and Cd, is advised because CM is a component of many foods, including baby food. Full article

This paper reviews the published terminology, mathematical models, and the possible approaches used to characterise the risk of foodborne chemical hazards, particularly pesticides, metals, mycotoxins, acrylamide, and polycyclic aromatic hydrocarbons (PAHs). The results confirmed the wide variability of the nomenclature used, e.g., 28 different ways of referencing exposure, 13 of cancer risk, or 9 of slope factor. On the other hand, a total of 16 equations were identified to formulate all the risk characterisation parameters of interest. Therefore, the present study proposes a terminology and formulation for some risk characterisation parameters based on the guidelines of international organisations and the literature review. The mathematical model used for non-genotoxic hazards is a ratio in all cases. However, the authors used the probability of cancer or different ratios, such as the margin of exposure (MOE) for genotoxic hazards. For each effect studied per hazard, the non-genotoxic effect was mostly studied in pesticides (79.73%), the genotoxic effect was mostly studied in PAHs (71.15%), and both effects were mainly studied in metals (59.4%). The authors of the works reviewed generally opted for a deterministic approach, although most of those who assessed the risk for mycotoxins or the ratio and risk for acrylamide used the probabilistic approach. Full article

Heavy metal(loid)s (HMs) play an important role in economic development since they are used in various branches of industry. However, all industrial activities emit HMs into the environment, where they are no longer useful but potentially toxic. It has been observed that HMs enter the soil and sediment, and potential human health risk may arise due to their excessive accumulation. Having in mind the importance of assessing the risk due to HMs in these media, we analyzed published works in the last decade and created a summary of exposure factors in health risk models for HMs in soil and sediment. This analysis revealed a remarkable increase in the number of publications about health risk assessment of HMs, especially in the last few years. Since many differences in the values of the exposure factors and their distributions were noted, this study focused on elucidating these differences. Non-carcinogenic and carcinogenic health risk assessment models were evaluated through a deterministic approach that is prevalent in use, and a probabilistic one, which is gaining more and more attention in research. In the end, guided by the studied literature, we propose the values and distributions for the exposure factors. Full article

The regions near the Tropic of Cancer are a latitudinal geographical zone with typical climatic, topographic, and human landscape features. It is necessary to explore the region’s net primary productivity (NPP) dynamics as it combines complex topography, various vegetation types, and intense human activities. The study sets the transect near the Tropic of Cancer (TCT) and uses the Carnegie–Ames–Stanford (CASA) model to estimate the NPP from 2000 to 2020. After using the RESTREND method, the paper calculates and compares the relative contributions of climate variability and anthropogenic activities to NPP changes. Finally, the geographical detector (Geodetector) model is applied to evaluate how anthropogenic and natural factors affect spatial distribution patterns and NPP changes. The results indicated that the average annual NPP is 820.39 gC·m⁻²·yr⁻¹ during the 21 years. In addition, when the NPP varies, it increases over the entire study area, with a slope of 4.81 gC·m⁻²·yr⁻¹, particularly in the western region. Across the entire research area, 63.39% and 77.44% of the total pixels positively contribute to climate variability and human activities in NPP, with a contribution of 0.90 and 3.91 gC·m⁻²·yr⁻¹, respectively. Within the western, central, and eastern regions, anthropogenic activities have a stronger impact on NPP than climate variability, particularly pronounced in the eastern region. Furthermore, vegetation cover is the dominant factor in the spatial patterns and NPP trends across the TCT and the three regions. In contrast, climate factors are shown to be less influential in NPP distribution than in the western region. The results also demonstrated that the effect of population density and the GDP on NPP gradually rises. Two-factor interaction is much larger than any individual factor, with the dominant interaction factor being vegetation cover with climatic factors. Lastly, the findings revealed that anthropogenic activities positively promote NPP accumulation across the TCT, thus highlighting the importance of human activity-led ecological restoration and ecological protection measures that contribute to regional carbon sequestration and carbon balance. Full article

Psychoneurological symptoms are commonly reported by newly diagnosed head and neck cancer (HNC) patients, yet there is limited research on the associations of these symptoms with biomarkers of stress and inflammation. In this article, pre-treatment data of a multi-center cohort of HNC patients were analyzed using a network analysis to examine connections between symptoms (poor sleep quality, anxiety, depression, fatigue, and oral pain), biomarkers of stress (diurnal cortisol slope), inflammation markers (c-reactive protein [CRP], interleukin [IL]-6, IL-10, and tumor necrosis factor alpha [TNF-α]), and covariates (age and body mass index [BMI]). Three centrality indices were calculated: degree (number of connections), closeness (proximity of a variable to other variables), and betweenness (based on the number of times a variable is located on the shortest path between any pair of other variables). In a sample of 264 patients, poor sleep quality and fatigue had the highest degree index; fatigue and CRP had the highest closeness index; and IL-6 had the highest betweenness index. The model yielded two clusters: a symptoms—cortisol slope—CRP cluster and a IL-6—IL-10—TNF-α—age—BMI cluster. Both clusters were connected most prominently via IL-6. Our findings provide evidence that poor sleep quality, fatigue, CRP, and IL-6 play an important role in the interconnections between psychoneurological symptoms and biomarkers of stress and inflammation in newly diagnosed HNC patients. Full article

Background: Renal cell carcinoma (RCC) is the most common neoplasm in kidneys, and surgical resection remains the mainstay treatment. Few studies have investigated how the postoperative pain changes over time and what has affected its trajectory. This study aimed to characterize the variations in postoperative pain over time and investigate associated factors after RCC surgery. Methods: This retrospective study was conducted in a single medical center in Taiwan, where maximal pain scores in a numeric rating scale were recorded daily in the first five postoperative days (PODs) after RCC surgery. Latent curve models were developed, using two latent variables, intercept and slope, which represented the baseline pain and rate of pain resolution. These models explain the variations in postoperative pain scores over time. A predictive model for postoperative pain trajectories was also constructed. Results: There were 861 patients with 3850 pain observations included in the analysis. Latent curve analysis identified that female patients and those with advanced cancer (stage III and IV) tended to have increased baseline pain scores (p = 0.028 and 0.012, respectively). Furthermore, patients over 60 years, without PCA use (both p < 0.001), and with more surgical blood loss (p = 0.001) tended to have slower pain resolution. The final predictive model fit the collected data acceptably (RMSEA = 0.06, CFI = 0.95). Conclusion: Latent curve analysis identified influential factors of acute pain trajectories after RCC surgery. This study may also help elucidate the complex relationships between the variations in pain intensity over time and their determinants, and guide personalized pain management after surgery for RCC. Full article

Background: We hypothesized that the Effective radiation Dose to the Immune Cells (EDIC) in circulating blood is a significant factor for the treatment outcome in patients with locally advanced non-small-cell lung cancer (NSCLC). Methods: This is a secondary study of a phase III trial, NRG/RTOG 0617, in patients with stage III NSCLC treated with radiation-based treatment. The EDIC was computed as equivalent uniform dose to the entire blood based on radiation doses to all blood-containing organs, with consideration of blood flow and fractionation effect. The primary endpoint was overall survival (OS), and the secondary endpoints were progression-free survival (PFS) and local progression-free survival (LPFS). The EDIC–survival relationship was analyzed with consideration of clinical significant factors. Results: A total of 456 patients were eligible. The median EDIC values were 5.6 Gy (range, 2.1–12.2 Gy) and 6.3 Gy (2.1–11.6 Gy) for the low- and high-dose groups, respectively. The EDIC was significantly associated with OS (hazard ratio [HR] = 1.12, p = 0.005) and LPFS (HR = 1.09, p = 0.02) but PFS (HR = 1.05, p = 0.17) after adjustment for tumor dose, gross tumor volume and other factors. OS decreased with an increasing EDIC in a non-linear pattern: the two-year OS decreased first with a slope of 8%/Gy when the EDIC < 6 Gy, remained relatively unchanged when the EDIC was 6–8 Gy, and followed by a further reduction with a slope of 12%/Gy when the EDIC > 8 Gy. Conclusions: The EDIC is a significant independent risk factor for poor OS and LPFS in RTOG 0617 patients with stage III NSCLC, suggesting that radiation dose to circulating immune cells is critical for tumor control. Organ at risk for the immune system should be considered during RT plan. Full article