In this study, we aimed to investigate the frequency of respiratory health symptoms among high school students attending schools at industrial, urban and rural areas in a Turkish city. Three schools located in different zones of the city having different pollution characteristics were chosen based on the pollutant distribution maps using Geographical Information Systems (GIS) software. A cross-sectional survey was performed among 667 high school students in the schools. Outdoor and indoor nitrogen dioxide (NO₂) and ozone (O₃) concentrations were also measured by passive samplers in the same schools to investigate possible routes of exposure. Chronic pulmonary disease (OR = 1.49; 95%CI: 1.11–1.99; p = 0.008), tightness in the chest (OR = 1.57; 95%CI: 1.22–2.02; p = 0.001), morning cough (OR = 1.81 95%CI: 1.19–2.75; p = 0.006) were higher among students in the industrial zone where nitrogen dioxide and ozone levels were also highest. There were no indoor sources of nitrogen dioxide and ozone exists in the schools except for the dining hall. As a conclusion, this study has noticed that air pollution and respiratory health problems among high school students are high in industrial zones and the use of passive samplers combined with GIS is an effective tool that may be used by public health researchers to identify pollutant zones and persons at risk.

Background: The aim of this study is to evaluate the hypothesis test results after categorizing the scale scores with cut-off points and to assess whether similar results would be obtained in that best represent the categories. Methods: This cross-sectional study was conducted between March 15 and 20, 2023 via the Lime Survey. The questionnaire included questions about the sociodemographic and life characteristics of the participants and the Beck Depression Inventory II (BDI-II). Four groups (minimal, mild, moderate, severe depression) were formed using the cutoff points. Data analysis was performed with all participants and referred to as the conventional analysis group. Then, six subanalysis groups were determined to best represent the groups formed according to the BDI-II. In each BDI-II category, six subanalysis groups were created, including those between Q1–Q3 (IQR group), including those within ± 1 std, including those between 5p–95p (90% of the sample), including those between 2.5p–97.5p (95% of the sample). In addition, 100 different samples were randomly selected containing 50% of each group. Results: Of the 1950 participants, 84.7% (n = 1652) were female and 15.3% (n = 298) were male. In terms of depression, it was observed that the significance varied in the analysis groups for sex (p = 0.039), medication use (p = 0.009) and age (p = 0.010) variables. However, these variables were not significant in some of the subanalysis groups. On the other hand, a p < 0.001 value was obtained for income, physical activity, health perception, body shape perception, life satisfaction, and quality of life variables in terms of depression in the conventional analysis group, and it was seen that the significance continued in all subanalysis groups. Conclusions: Our findings showed that variables with p < 0.001 in the conventional analysis group maintained their significance in the other analysis groups. In addition, as the p value got closer to 0.05, we observed that the significance changed according to different cutoff points in the analysis groups. In addition, 50% randomly selected samples support these results. At the end of our study, we reached results that support the necessity of secondary tests in the evaluation of scales. Although further studies are needed, we anticipate that our study will shed light on other studies.

Objectives: Accurate preoperative staging and prediction of extraprostatic extension (EPE) are critical for optimal surgical planning in prostate cancer (PCa). This study evaluated the diagnostic accuracy of ⁶⁸Ga-PSMA PET for EPE assessment, compared it with the standardized multiparametric MRI (mpMRI)-derived EPE-grading system, and examined whether integrating semi-quantitative PSMA PET parameters improves diagnostic performance using hybrid PET/MRI. Methods: This retrospective, single-center study included treatment-naïve, biopsy-proven PCa patients who underwent ⁶⁸Ga-PSMA-11 PET/MRI followed by radical prostatectomy. Diagnostic accuracy was assessed for clinical variables (PSA, ISUP grade), mpMRI features, mpMRI-derived EPE-grading system, visual PET findings, and semi-quantitative PET parameters (SUVmax, SUVmean, PSMA-tumor volume [PSMA-TV]). Optimal cut-offs were determined using the Youden index. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were performed to compare the predictive value of clinical, mpMRI, or PET-derived variables, with histopathology as the reference standard. Results: Forty-five patients were included; EPE was histologically confirmed in 19 (42.2%). Predictors of EPE included capsular irregularity, neurovascular bundle asymmetry, curvilinear contact length ≥ 1.5 cm, seminal vesicle invasion, tumor size ≥ 14.25 mm, EPE grade ≥ 2, ISUP grade ≥ 3, overt EPE on PET, SUVmax ≥ 13.84, SUVmean ≥ 7.20, and PSMA-TV ≥ 1.40 cm³. The highest ROC performance (AUC = 0.890) was achieved by combining overt EPE on PET, SUVmax, and PSMA-TV. Incorporating PET parameters or tumor size into the EPE-grading system improved predictive accuracy. Conclusions: PSMA uptake in the primary tumor is an independent predictor of EPE. Integrating PSMA PET with mpMRI may provide additional information for preoperative EPE assessment.