Objective: To understand current state of physical health levels of first year students in different body mass index (BMI) categories in Ningxia universities, and to explore the correlation between BMI and physical fitness index (PFI), so as to provide a reference for enhancing physical health levels of university students. Methods: In November 2024, physical fitness test data from 16 631 first year students across four universities in Yinchuan City, Ningxia from 2019 to 2023 were collected by adopting convenience and stratified cluster random sampling methods. The PFI was calculated using the Z score of the physical fitness test results, and a nonlinear quadratic model was established via least squares regression to examine the relationship between BMI and PFI among university students. Results: The BMI for males was (21.69±3.53)kg/m 2, while for females was (20.78±2.94)kg/m 2. The composite score for males physical fitness (69.86±9.25) was lower than that for females (72.24± 8.15 ), with a statistically significant difference ( t =-17.54, P <0.01). Moreover, the failure rates of various physical fitness indicators (vital capacity, sit and reach, standing long jump, pull ups/1 minute sit ups, 1 000 m/800 m run) were higher among males than females ( χ 2=103.48, 72.45, 14.38, 5 134.85, 188.89, all P <0.01). Comparisons across BMI categories revealed that among males, the normal weight group outperformed other groups in the 50 m sprint, standing long jump, 1 000 m sprint, composite score, and PFI ( F =89.17, 113.90, 179.02, 573.35, 593.08); among female students, the normal weight group outperformed other groups in the 50 m sprint, sit and reach, 800 m run, composite score, and PFI ( F =10.67, 19.58 , 96.45, 294.05, 183.45) (all P <0.01). The relationship between BMI and PFI among first year students exhibited a parabolic change trend, students with a moderate BMI demonstrated higher PFI, and as BMI increased, PFI decreased (all P <0.01). Conclusions The physical health level of male students in Ningxia universities is lower than that of female students. There is a correlation between BMI classification and PFI. Tailored intervention measures should be implemented according to the physical characteristics of students across different genders and BMI classifications to enhance university students physical health.

BACKGROUNDQuantitative dynamic contrast enhancement MR imaging (DCE-MRI), used to measure properties of tissue microvasculature and tumor angiogenesis, is a promising method for distinguishing benign and malignant tumors and characterizing tumor response to antiangiogenic treatment. The aim of this study was to assess the feasibility of quantitative parameters derived from clinically used DCE-MRI for distinguishing benign from malignant tumors in the sinonasal area, which may be potentially useful for prediction and monitoring of treatment response to chemoradiotherapy of sinonasal tumors.

METHODSOne hundred and forty-three patients with sinonasal tumors, including 78 malignant tumors and 65 benign tumors and tumor-like lesions, underwent clinically used DCE-MRI. Parametric maps were obtained for quantitative parameters including K(trans), kep and ve. Two radiologists reviewed these maps and measured K(trans), kep and ve in the tumor tissue. Data were analyzed using independent T-test or Mann-Whitney U test analysis and receiver operating characteristic curves.

RESULTSK(trans), kep and ve showed significant differences between benign and malignant tumors in the sinonasal area (P = 0.000 1). The accuracy of K(trans), kep and ve in differentiation between benign and malignant sinonasal tumors were 72.0%, 76.2% and 67.1%, respectively. There were significant differences in kep and ve between malignant epithelial sinonasal tumors and lymphomas (P < 0.05). Using a ve value of 0.213 as the threshold value differentiated malignant epithelial tumors from lymphomas with an accuracy of 78.3%, sensitivity of 88.2%, specificity of 68.0%, positive predictive value of 66.7%, and negative predictive value of 90.9%. However, no significant difference in K(trans) and kep was found between malignant epithelial and non-epithelial tumors in the sinonasal area (P > 0.05).

CONCLUSIONSIt is feasible that quantitative parameters of tumors can be derived from clinically used DCE-MRI in the sinonasal region. Preliminary findings suggest an increased value for quantitative DCE-MRI in the evaluation of sinonasal tumors in clinical practice.

Contrast Media ; Female ; Humans ; Image Enhancement ; methods ; Magnetic Resonance Imaging ; methods ; Male ; Middle Aged ; Paranasal Sinus Neoplasms ; diagnosis

Objective To determine whether volume transfer coefficient (Ktrans )can be used to differentiate high-grade glioma (HGG)and metastasis.Methods Thirty-nine patients with brain tumors (12 HGG,27 metastases)underwent dynamic contrast en-hanced MR imaging before surgical resection or stereotactic biopsy.Images were acquired with a three-dimensional (3D)fast gradi-ent echo sequence.Gadolinium-based contrast agent was injected intravenously with dosage of 0.1 mmol/kg bodyweight at a rate of 3.0 mL/s.Ktrans and Ve were calculated from the DCE MRI data.The results of Ktrans and Ve were compared between the 2 types of tumors.Receiver operating characteristic curve analysis was performed for each of the variables in differentiation cerebral metastasis from HGG.Results The Ktrans values in the parenchyma of HGG and metastases were 0.10 (0.11,0.71)min-1 and 0.21 (0.05, 0.77)min-1 ,respectively.The difference was not statistically significant (P>0.05).The Ktrans values in the peritumoral region of the HGG and brain metastasis were 0.04 (0.01,0.10)min-1 and 0.01 (0.00,0.06)min-1 ,respectively.There was a significant difference between the Ktrans values in the peritumoral edema of HGG and cerebral metastases (P<0.05).The optimal cutoff value of Ktrans for differentiating HGG from cerebral metastases was 0.03,with sensitivity of 75% and specificity of 70%.Conclusion Ktrans values in the peritumoral edema may be useful in the differentiating cerebral metastases between HGG.