Acute or intense exercise is sometimes related to infections of the urinary tract. It can also lead to incorrect hydration as well as incorrect glomerular filtration due to the presence of high-molecular-weight proteins that cause damage to the kidneys. In this context, our study lays the foundations for the use of a urine test in a team of twelve male basketball players as a means of monitoring numerous biochemical parameters, including pH, specific weight, color, appearance, presence of bacterial cells, presence of squamous cells, leukocytes, erythrocytes, proteins, glucose, ketones, bilirubin, hemoglobin, nitrite, and leukocyte esterase, to prevent and/or treat the onset of pathologies, prescribe personalized treatments for each athlete, and monitor the athletes’ health status.

Intense physical activity can induce metabolic changes that modify specific biochemical biomarkers. In this scenario, the purpose of our study was to evaluate how intense physical activity can affect oxidative metabolism. Following this, fifteen professional basketball players and fifteen sedentary controls were recruited and subjected to two samplings of serum and urine in the pre-season (September) and two months after the start of the competitive season (November). Our results have shown an increase in athletes compared to controls in CK and LDH in September (respectively, p-value 0.003 and p-value < 0.001) and in November (both p-value < 0.001), whereas ALT is increased only in November (p-value 0.09). GGT serum levels were decreased in athletes compared to controls in both months (in September p-value 0.001 and in November p-value < 0.001). A gene expression analysis, carried out using RT-PCR, has revealed that IL-2, IL-6, IL-8, xCT and GCLM are increased in athletes in both months (p-value < 0.0001), while IL-10 and CHAC1 are increased only in September if compared to the controls (respectively, p-value 0.040 and p-value < 0.001). In conclusion, physical activity creates an adaptation of the systems involved in oxidative metabolism but without causing damage to the liver or kidney. This information could be of help to sports doctors for the prevention of injuries and illnesses in professional athletes for the construction of the athlete’s passport.

The management of neuroendocrine neoplasms (NENs) involves the measurement of serum chromogranin A (s-CGA), serum neuro-specific enolase (s-NSE), and urinary 5-hydroxindolacetic acid (5-HIAA). Urinary para-hydroxyphenylacetic acid (u-pHPAA), a metabolite of tyrosine, has been proposed as a potential biomarker for these diseases. This study aims to evaluate the effectiveness of u-pHPAA and tyrosine as biomarkers. We measured the levels of s-CgA, s-NSE, u-5-HIAA, u-pHPAA, and tyrosine in blood or 24 h urine samples collected at baseline (T₀) and after 1 year of follow-up (T₁) from a limited cohort of patients enrolled at Istituto Nazionale Tumori-IRCCS-Fondazione “G. Pascale”. Biomarker values were normalized using the ratios between T₁ and T₀ values (T₁/T₀ parameters). The T₁/T₀ ratios for s-CgA and u-pHPAA were significantly associated with the outcome of death (p = 0.044 and p = 0.022, respectively). An ROC curve analysis demonstrated outstanding performances for these biomarkers (AUC = 0.958 and AUC = 1.00, respectively) and the Kaplan–Meier survival analysis showed significant Log-rank test results (p = 0.001 and p < 0.001, respectively). Additionally, T₀ serum tyrosine correlated with the outcome of death (p = 0.044), with the ROC curve showing good performance (AUC = 0.958) and the Kaplan–Meier analysis yielding significant Log-rank test results (p = 0.007). Our study confirms the role of s-CgA in the management of NEN patients and highlights the potential roles of u-pHPAA and serum tyrosine as biomarkers. Further research is needed to validate our findings in larger populations.

Background: Plant-based diets are recommended in guidelines for the prevention of cancer and cardiometabolic diseases, which remain major causes of death in breast cancer survivors (BCS). Since not all plant foods are healthy, we calculated the plant-based dietary index (PDI), healthy (hPDI) and unhealthy (uPDI), and their associations with cardiometabolic targets in BCS. Methods: Baseline dietary and cardiometabolic data were derived from 492 (median age 51, IQR 46–59) female BCS participating in a multicentric lifestyle trial conducted in Italy. Dietary data were collected with 7-day food records. PDI, hPDI, and uPDI were calculated by assigning positive scores to all plant foods, healthy plant foods or less healthy plant foods, respectively, as defined by the literature (scores ranged from 18 to 90). Using logistic or multinomial regression models, we estimated the odds ratios (OR) and the corresponding 95% confidence intervals (CI) between PDIs and cardiometabolic risk factors. Results: The OR of being obese (BMI ≥ 30 Kg/m²) was 0.47 (95%CI: 0.29–0.77), 0.37 (95%CI: 0.22–0.61) and 1.38 (95%CI: 0.83–2.28) with higher PDI, hPDI and uPDI, respectively. The OR of having a large waist circumference (≥88 cm) was 0.64 (95%CI: 0.42–1.00) with higher hPDI. The OR for hypercholesterolemia (≥200 mg/dL) was 1.80 (95%CI: 1.16–2.78) with higher uPDI. The ORs of hypertriglyceridemia (≥150 mg/dL) and metabolic syndrome were 0.38 (95%CI: 0.20–0.71) and 0.59 (95%CI: 0.35–0.97), respectively, with higher PDI. No other significant association was observed. Conclusions: Maintaining cardiometabolic risk factors within normal ranges is clinically relevant in BCS, and this may be more likely when a plant-based diet is consumed, especially if low in unhealthy plant foods.

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