Objective To discuss the application of enhanced MRI-based radiomics nomogram in predicting the efficacy of initial transcatheter arterial chemoembolization(TACE)in patients with intermediate to advanced hepatocellular carcinoma(HCC).Methods A total of 195 patients with advanced HCC(CNLC Ⅱ b-Ⅲb),who received initial TACE at the Affiliated Fifth Hospital of Wenzhou Medical University(Center 1)from January 2019 to March 2024,at the Lishui Municipal People's Hospital(Center 2)from July 2021 to June 2023,and at the Rui'an Municipal People's Hospital(Center 3)from January 2022 to January 2024,were enrolled in this study.A total of 134 patients from Center 1 were randomly divided into a training set(n=94)and an internal validation set(n=40)at a 7∶3 ratio;and other 61 patients from Center 2 and Center 3 were selected as the external validation set.Based on the modified Response Evaluation Criteria in Solid Tumors(mRECIST)criteria,the early efficacy of the initial TACE procedure was evaluated.The patients were divided into an effective group and an ineffective group.The tumor contours were delineated on the arterial,portal,and equilibrium phase images of enhanced MRI,and the corresponding radiomics features were extracted.Based on reduced-dimensional features,the Logistic regression,support vector machine,lightweight gradient boosting machine,and multi-layer perceptron models were established.Univariate analysis and multivariate logistic regression analysis were used to screen independent predictive factors,and a nomogram was established in conjunction with the optimal radiomics score.The area under the receiver operating characteristic curve(AUC)was used to evaluate the performance of the model,and decision curve analysis was adopted to calculate the net benefits.Results After screening,9 key radiomics features were obtained.The lightweight gradient boosting machine model showed good prediction performance.The AUCs of the training set,internal validation set,and external validation set were 0.909,0.836 and 0.783 respectively,which was selected as the optimal radiomics model.The nomogram constructed based on AFP level,peritumoral enhancement,and optimal radiomics score could further improve its performance,with AUC values of 0.962,0.890 and 0.821 in the training set,internal validation set,and external validation set respectively.Decision curve analysis showed that this model could bring higher net benefits to patients.Conclusion The nomogram constructed based on the enhanced MRI-based radiomics combined with AFP level and peritumoral enhancement can effectively predict the efficacy of the initial TACE in patients with intermediate to advanced HCC.

Objective:To explore the clinical characteristics and healthcare burden in patients with McCune-Albright syndrome (MAS).Methods:A cross-sectional study was conducted at the Children′s Hospital, Zhejiang University School of Medicine. Clinical and healthcare burden data were systematically collected through structured questionnaires in 164 children with MAS from February 2022 to May 2023. According to the clinical characteristics, patients were categorized into 3 groups: monosymptomatic, bisymptomatic and trisymptomatic groups. Patients were also divided into 3 groups according to the age of <7, 7-<10 and 10-18 years. Comparative analyses of clinical characteristics and healthcare burden were conducted across age, sex, and symptom categories.Results:The cohort comprised 59 males (36.0%) and 105 females (64.0%) with an age of 4.6 (2.0, 7.4) years. Age stratification revealed 117 cases (71.3%) aged 0-<7 years, 29 cases (17.7%) aged 7-<10 years, and 18 cases (11.0%) aged 10-<18 years. Among monosymptomatic (67 cases, 40.9%), the cohort comprised 32 females (47.8%) and 35 males (52.2%), predominantly presenting with fibrous dysplasia (57 cases, 85.1%). This subgroup showed peak prevalence in the 0-<7 years age range (29 cases (50.9%)). The bisymptomatic cohort (56 cases, 34.1%) consisted of 39 females (69.6%) and 17 males (30.4%), predominantly manifesting fibrous dysplasia with skin hyperpigmentation (25 cases, 44.6%). Peak prevalence occurred in the 0-<7 years subgroup(16 cases (64.0%)). The trisymptomatic cohort (41 cases, 25.0%) consisted of 34 females (82.9%) and 7 males (17.1%), with peak prevalence occurring in the 0-<7 years subgroup (36 cases (87.8%)). The diagnostic journey analysis revealed 94 cases (57.3%) required 1-3 referrals, and 34 cases (20.7%) necessitated >3 referrals from symptom onset to definitive diagnosis. Healthcare expenditure analysis revealed 69 families (42.1%) incurred direct medical costs of 10 000-100 000 CNY, with 11 families (6.7%) exceeding >100 000 CNY. Direct non-medical costs reached of 10 000-100 000 CNY for 62 families (37.8%) and >100 000 CNY for 4 families (2.4%). Productivity loss affected 58 families (35.4%) at 10 000-100 000 CNY and 8 families (4.9%) above 100 000 CNY during the study period.Conclusion:MAS requires increased attention to skeletal manifestations, especially in children aged 0-<7 years. Moreover, the significant financial burden on families necessitates a society-wide support system.

Depression poses a severe threat to human health, placing a heavy burden on society and families. Yet, challenges remain in prevention and treatment. Lifestyle medicine aims to use evidence-based lifestyle interventions to prevent, treat, and even reverse chronic progression. Exploring breakthroughs in depression intervention prevention and treatment from the perspective of lifestyle medicine presents an opportunity for interdisciplinary research. Future research should focus on leveraging implementation science, cost-effectiveness analysis, and understanding optimal pathways and mechanisms of action. This article provides a review of this important topic.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective:To explore the clinical characteristics and healthcare burden in patients with McCune-Albright syndrome (MAS).Methods:A cross-sectional study was conducted at the Children′s Hospital, Zhejiang University School of Medicine. Clinical and healthcare burden data were systematically collected through structured questionnaires in 164 children with MAS from February 2022 to May 2023. According to the clinical characteristics, patients were categorized into 3 groups: monosymptomatic, bisymptomatic and trisymptomatic groups. Patients were also divided into 3 groups according to the age of <7, 7-<10 and 10-18 years. Comparative analyses of clinical characteristics and healthcare burden were conducted across age, sex, and symptom categories.Results:The cohort comprised 59 males (36.0%) and 105 females (64.0%) with an age of 4.6 (2.0, 7.4) years. Age stratification revealed 117 cases (71.3%) aged 0-<7 years, 29 cases (17.7%) aged 7-<10 years, and 18 cases (11.0%) aged 10-<18 years. Among monosymptomatic (67 cases, 40.9%), the cohort comprised 32 females (47.8%) and 35 males (52.2%), predominantly presenting with fibrous dysplasia (57 cases, 85.1%). This subgroup showed peak prevalence in the 0-<7 years age range (29 cases (50.9%)). The bisymptomatic cohort (56 cases, 34.1%) consisted of 39 females (69.6%) and 17 males (30.4%), predominantly manifesting fibrous dysplasia with skin hyperpigmentation (25 cases, 44.6%). Peak prevalence occurred in the 0-<7 years subgroup(16 cases (64.0%)). The trisymptomatic cohort (41 cases, 25.0%) consisted of 34 females (82.9%) and 7 males (17.1%), with peak prevalence occurring in the 0-<7 years subgroup (36 cases (87.8%)). The diagnostic journey analysis revealed 94 cases (57.3%) required 1-3 referrals, and 34 cases (20.7%) necessitated >3 referrals from symptom onset to definitive diagnosis. Healthcare expenditure analysis revealed 69 families (42.1%) incurred direct medical costs of 10 000-100 000 CNY, with 11 families (6.7%) exceeding >100 000 CNY. Direct non-medical costs reached of 10 000-100 000 CNY for 62 families (37.8%) and >100 000 CNY for 4 families (2.4%). Productivity loss affected 58 families (35.4%) at 10 000-100 000 CNY and 8 families (4.9%) above 100 000 CNY during the study period.Conclusion:MAS requires increased attention to skeletal manifestations, especially in children aged 0-<7 years. Moreover, the significant financial burden on families necessitates a society-wide support system.

Depression poses a severe threat to human health, placing a heavy burden on society and families. Yet, challenges remain in prevention and treatment. Lifestyle medicine aims to use evidence-based lifestyle interventions to prevent, treat, and even reverse chronic progression. Exploring breakthroughs in depression intervention prevention and treatment from the perspective of lifestyle medicine presents an opportunity for interdisciplinary research. Future research should focus on leveraging implementation science, cost-effectiveness analysis, and understanding optimal pathways and mechanisms of action. This article provides a review of this important topic.

Objective To explore the application value of the nomogram based on dual-energy CT in preoperative evaluation of human epidermal growth factor receptor 2(HER-2)status in patient with breast cancer.Methods A total of 269 patients with pathologically confirmed breast cancer were retrospectively collected and randomly divided into a training cohort(n=189)and a validation cohort(n=80)at a ratio of 7︰3.The dual-energy CT parameters and clinical features of all patients were measured and collected.Varia-bles with significant difference in univariate analysis were included in the multivariate logistic analysis to obtain independent risk fac-tors related to HER-2 status,with establishing a nomogram model.Receiver operating characteristic(ROC)curves were plotted to evaluate the predictive performance of the nomogram.Results There was a significant difference in axillary lymph node enlargement between the two groups(P<0.05).The venous phase iodine concentration(IC)and normalized iodine concentration(NIC)in the HER-2 positive group were significantly higher than those in the HER-2 negative group(P<0.05).Axillary lymph node enlargement,venous phase IC,and venous phase NIC were the independent risk factors for predicting HER-2 status in breast cancer.The nomogram con-structed from the above features exhibited good predictive performance,with area under the curve(AUC)of 0.856 and 0.834 in the training and validation cohorts,respectively.Conclusion The nomogram based on dual-energy CT has a high predictive value for HER-2 status in breast cancer patients.

BACKGROUND:There are increasing scientific and technological ways to promote the recovery of muscle fatigue after sports,such as vibrating foam shaft,fascia gun relaxation,and ultra-low temperature cold therapy.Fascia gun relaxation has been widely used in practice,but there is still relatively little research on fascial guns. OBJECTIVE:To compare the effects of three relaxation methods(fascia gun,stretching,fascia gun+stretching)on muscle status and muscle strength during the recovery of exercise-induced muscle fatigue,and to provide scientific basis for the application of the three methods in practice. METHODS:Forty college students were randomly divided into control group(n=10),stretching group(n=10),fascia gun group(n=10),and fascia gun+stretching group(n=10).All subjects completed leg flexion and extension training at 60%1 RM,15 times per set,for 10 sets in total,to make exercise fatigue models.After modeling,the subjects were intervened with supine rest,static stretching,fascia gun relaxation,fascia gun+stretching relaxation respectively.Muscle status and muscle strength indexes were tested before exercise,immediately after exercise,immediately after relaxation,24 and 48 hours after exercise. RESULTS AND CONCLUSION:The muscle tension and dynamic hardness of the control group and the stretching group immediately after relaxation were significantly higher than those before training(P<0.01).However,there was no significant difference in the fascia gun group and fascia gun+stretching group before and after training(P>0.05).At 24 hours after training,the peak torque of the control group and fascia gun group was significantly lower than that before training(P<0.01),and there was no significant difference in the stretching group and fascia gun+stretching group before and 24 hours after training(P>0.05).To conclude,the fascia gun can immediately and effectively improve the muscle state of sports fatigue and stretching can promote the effective recovery of muscle strength within 24 hours after sports fatigue.Relaxation using fascia gun plus stretching can achieve the superposition of the two effects.

Objective:To investigate the lower limb muscle strength characteristics in amateur runners with patellofemoral pain(PFP). Method:Thirty PFP amateur runners(20 males and 10 females)were recruited as the knee pain group,and 30 matched non-injured amateur runners were recruited as the non-knee pain group.The hip abductor strength,quadriceps strength,hamstring strength,hamstring/quadriceps ratio,and bilateral limb symmetry index were col-lected for all participants.Independent sample t-tests were used to compare the differences between the groups. Result:The hip abductor strength and bilateral limb symmetry index,quadriceps strength and bilateral limb symmetry index of male PFP amateur runners were significantly lower than those of the non-knee pain group,while the hamstring/quadriceps ratio was significantly higher than that of the non-knee pain group.The hip ab-ductor strength and bilateral limb symmetry index of female PFP amateur runners were significantly lower than those of the non-knee pain group. Conclusion:PFP amateur runners exhibit different lower limb muscle strength characteristics compared to non-knee pain runners,and the lower limb strength characteristics of male and female PFP amateur runners are not consistent.Therefore,functional and gender differences should be considered in the clinical treatment and rehabilitation training of PFP.