Objective: To investigate the effects of high intensity interval training (HIIT) on mental health and sleep quality in female college students with normal weight obesity, so as to provide a reference for promoting their physical and mental health. Methods: From September to November 2024, 42 female college students who met the criteria for normal weight obesity were recruited from Anqing Medical College and randomly assigned to an HIIT group ( n =21) or a control group ( n =21) using a random number table. The HIIT group completed an 8 week intervention (3 sessions/week) at 75%-90% of maximum heart rate (HR max ), whereas the control group maintained their usual lifestyle. Before and after the intervention, body composition was measured, and anxiety, depressive symptoms, and sleep quality were assessed using the Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), and Pittsburgh Sleep Quality Index (PSQI), respectively. Statistical analysis included t-test, two way mixed analysis of variance, simple effect analysis, Wilcoxon signed rank test，Mann-Whitney U test, Pearson product moment correlation analysis, and Fisher s Z-transformation test. Results: Before the intervention, there were no statistically significant differences between the HIIT group and the control group in body composition indicators (body weight, body mass index, body fat percentage, visceral fat level, visceral fat area, and waist circumference), psychological indicators (anxiety symptoms and depressive symptoms), and sleep quality problems among female college students (all P >0.05). After the intervention, the above indicators in the HIIT group[（58.53±1.05）kg，（21.93±0.36）kg/m 2，（28.15±0.48）%，（7.31±0.43），（ 78.54± 4.28）cm 2，（75.91± 1.26 ）cm，2(1,3) scores,2(1,4) score,（6.15±1.58）score] all decreased ( F/Z =3.95，12.76，23.65，43.97，19.06，22.04，-3.35， -4.01 ，20.52，all P <0.05), and were all lower than those in the control group ( F/U =4.45， 6.82 ， 52.34 ，28.46，34.25，13.49， 344.0 ，327.0，31.62，all P <0.05).There were no statistically significant differences in the above indicators in the control group before and after the intervention (all P >0.05).Before the intervention, the total score of sleep quality problems in the HIIT group of female college students was positively correlated with the depression symptom score ( r =0.54, P < 0.05 ), while the correlation in the control group was not statistically significant ( r =-0.10, P >0.05). After the intervention, the correlation was strengthened in the HIIT group ( r =0.81, P <0.05), and the strength of the association was greater than that in the control group ( Z =3.50, P <0.05). Conclusion HIIT may improve sleep quality and mental health in female college students with normal weight obesity.

Objective To explore the application value of dual-energy computed tomography(DECT)of the chest combined with enhanced MRI of the brain in predicting anaplastic lymphoma kinase(ALK)gene mutation in patients with brain metastasis of lung adenocarcinoma.Methods The clinical and imaging data of 77 patients with brain metastasis of lung adenocarcinoma were analyzed retrospectively.Clinical data and DECT parameters of chest,enhanced MRI images of brain and ALK gene mutation status were included.And the quantitative parameters of DECT included normalized iodine concentration in arterial phase(NICA),normalized iodine concentration in venous phase(NICV),λ in arterial phase(λA)and λ in venous phase(λV).According to the ALK gene detection results,they were divided into ALK positive group(n=17)and ALK negative group(n=60).The differences of clinical data,DECT parameters,and MRI images between the two groups were compared,and the logistic regression model for predicting ALK gene mutation was constructed.The prediction of the model was evaluated by receiver operating characteristic(ROC)curve and area under the curve(AUC).Results Univariate analysis revealed that ALK positive were found in youngers and non-smokers.λV and NICV in ALK positive group were significantly lower than those in ALK negative group.The peritumoral brain edema index(PBEI)and peritumoral brain edema size(PBES)of ALK positive group were significantly smaller than those of ALK negative group.There was statistically significant in age,smoking history,λV,NICV,PBEI and PBES between the two groups(P＜0.05).Clinical features combined with DECT parameters were used to establish model 1,clinical features combined with DECT parameters and MRI parameters were used to establish model 2.Model 2 was significantly superior to model 1 or univariate analysis,respectively,in predicting ALK gene mutation by DeLong test,the AUC was 0.927.Conclusion ALK mutations are more common in youngers and non-smokers.λV,NICV,PBEI,and PBES are reliable predictors of ALK mutations.Model 2 can improve predictive efficiency significantly.

Objective To explore the application value of dual-energy computed tomography(DECT)of the chest combined with enhanced MRI of the brain in predicting anaplastic lymphoma kinase(ALK)gene mutation in patients with brain metastasis of lung adenocarcinoma.Methods The clinical and imaging data of 77 patients with brain metastasis of lung adenocarcinoma were analyzed retrospectively.Clinical data and DECT parameters of chest,enhanced MRI images of brain and ALK gene mutation status were included.And the quantitative parameters of DECT included normalized iodine concentration in arterial phase(NICA),normalized iodine concentration in venous phase(NICV),λ in arterial phase(λA)and λ in venous phase(λV).According to the ALK gene detection results,they were divided into ALK positive group(n=17)and ALK negative group(n=60).The differences of clinical data,DECT parameters,and MRI images between the two groups were compared,and the logistic regression model for predicting ALK gene mutation was constructed.The prediction of the model was evaluated by receiver operating characteristic(ROC)curve and area under the curve(AUC).Results Univariate analysis revealed that ALK positive were found in youngers and non-smokers.λV and NICV in ALK positive group were significantly lower than those in ALK negative group.The peritumoral brain edema index(PBEI)and peritumoral brain edema size(PBES)of ALK positive group were significantly smaller than those of ALK negative group.There was statistically significant in age,smoking history,λV,NICV,PBEI and PBES between the two groups(P＜0.05).Clinical features combined with DECT parameters were used to establish model 1,clinical features combined with DECT parameters and MRI parameters were used to establish model 2.Model 2 was significantly superior to model 1 or univariate analysis,respectively,in predicting ALK gene mutation by DeLong test,the AUC was 0.927.Conclusion ALK mutations are more common in youngers and non-smokers.λV,NICV,PBEI,and PBES are reliable predictors of ALK mutations.Model 2 can improve predictive efficiency significantly.