Objective To investigate the impact of enterovirus 71(EV71)on skeletal muscle injury and explore its mechanism in relation to the caspase-1/interleukin(IL)-1 β signaling pathway in EV71-induced skeletal muscle damage.Methods One-day-old BALB/c suckling mice were divided randomly into three groups:normal control(NC)(n=60),EV71 infection model(n=60),and caspase-1 inhibitor(EV71+VX765)(n=15)groups.The NC and EV71 model groups were further subdivided into four subgroups(5,7,10,and 14 days)(n=5 mice per group).An EV71-infected model was established by intraperitoneal injection of 25 × 103 μL/kg EV71 viral solution for 3 consecutive days.Mice in the caspase-1 inhibitor group received VX765(20 mg/kg)intraperitoneally 6 hours post-viral inoculation,continued daily for 10 days until sample collection.Mice in the NC group received an equivalent volume of saline containing 5％dimethylsulfoxide and 10％PEG300,followed by 2％cell maintenance solution after 6 hours.Post-modeling body weight and clinical disease scores were recorded.Pathological skeletal muscle damage was observed by hematoxylin-eosin(HE)staining,and expression levels of EV71 VP-1(viral capsid protein),pro-caspase-1,cleaved-caspase-1,IL-1 β,α-smooth muscle actin(SMA),and Collagen Ⅰ were detected by Western blot and immunofluorescence.Results Compared with the NC group at the same time points,mice in the EV71 model group exhibited reduced body weight,elevated disease scores,and skeletal muscle pathology characterized by inflammatory cell infiltration,myofiber dissolution,and decreased cross-sectional area(HE staining).Western blot showed significantly increased levels of EV71 VP-1,IL-1β,α-SMA,and Collagen Ⅰ in skeletal muscle homogenate from EV71 mice at 5,7,and 10 days post-infection(P＜0.001).In contrast,mice in the VX765 group showed improved body weight,reduced clinical scores(P＜0.01),and significant downregulation of EV71 VP-1(P＜0.01),pro-caspase-1,cleaved-caspase-1,IL-1β,and Collagen Ⅰ compared with the EV71 model group(P＜0.01).These findings were confirmed by immunofluorescence,indicating that inhibition of caspase-1 alleviated EV71-induced skeletal muscle injury.Conclusions EV71 may induce skeletal muscle injury by activating the caspase-1/IL-1β signaling pathway.

Background and purpose:Approximately 30%of patients with metastatic colorectal cancer(CRC)develops pulmonary metastasis,yet less than 10%are eligible for surgical resection.Radiofrequency ablation(RFA)serves as an alternative therapy for non-surgical candidates,but the relationship between its efficacy and tumor diameter remains controversial.This study aimed to investigate the impact of tumor size on survival outcomes and local progression risk in CRC patients with pulmonary metastasis after RFA,and to validate the clinical utility of a 3 cm threshold for prognosis.Methods:This retrospective study included CRC patients with pulmonary metastasis who underwent RFA at Fudan University Shanghai Cancer Center between January 2016 and December 2024.Patients were stratified into two groups based on maximum lesion diameter:≤3 cm(Small group)and 3-5 cm(Large group).Patient inclusion criteria:⑴ pathologically confirmed lung metastases originating from CRC,with metastases limited to the lungs or extra-pulmonary metastatic lesions having been radically treated;⑵ maximum lesion diameter<5 cm;⑶complete clinical data available;⑷ complete imaging data available,including computed tomography(CT)images during ablation and contrast-enhanced CT images during postoperative follow-up;⑸ follow-up time of at least＞6 months after RFA;⑹ technical complete ablation;⑺ fewer than 3 pulmonary metastatic lesions.Exclusion criteria:⑴ target lesions previously treated with local therapies such as RFA or radiotherapy;⑵ patients unable to tolerate RFA;⑶ patients with follow-up time＜6 months after RFA.Three senior interventional physicians performed percutaneous RFA under guidance of a 64-slice spiral CT scanner.Chest contrast-enhanced CT scans obtained 1 month after RFA were used as the baseline,followed by contrast-enhanced CT scans every 3 months for 1 year,then every 6 months for subsequent follow-up.This study was approved by the medical ethics committee of Fudan University Shanghai Cancer Center(ethical approval number:2108241-11).Primary endpoints included overall survival(OS),progression-free survival(PFS),and local tumor progression(LTP).Kaplan-Meier analysis and multivariate COX regression were employed to evaluate the independent prognostic value of tumor size.Results:A total of 134 patients who met the inclusion criteria were ultimately enrolled,including 77 in the Small group and 57 in the Large group.With a median follow-up of 35 months,the≤3 cm group demonstrated superior 1-,3-,and 5-year OS rates(100.0%,95.1%,74.2%)compared to the 3-5 cm group(94.7%,36.8%,27.0%,P＜0.0001),and the≤3 cm group demonstrated superior 1-,3-,and 5-year PFS rates(90.9%,34.4%,23.3%)compared to the 3-5 cm group(13.8%,0.0%,0.0%,P＜0.000 1).The≤3 cm group also exhibited significantly lower 1-,3-,and 5-year LTP rates(0.0%,19.7%,33.6%)compared to the 3-5 cm group(46.0%,75.5%,75.5%,P＜0.000 1).Multivariable analysis identified tumor diameter＞3 cm as an independent predictor of worse OS[hazard ratio(HR)=6.49,95%CI:3.18-13.24,P＜0.001],while elevated preoperative carcinoembryonic antigen(CEA)(≥5 ng/mL)correlated with shorter OS(HR=1.82,P=0.033).Conclusion:CRC patients with pulmonary metastasis and tumor diameters of 3-5 cm exhibited significantly inferior survival outcomes after RFA compared to the≤3 cm group.A tumor diameter of 3 cm can serve as a critical threshold for selecting RFA indications,and combining preoperative CEA levels can optimize patient stratification.

Objective To explore the efficacy of a model combining clinicopathological characteristics and multiparametric MRI features for predicting BRCA-mutated breast cancer(BC).Methods A total of 256 BC patients were retrospectively selected and divided into BRCA mutation group(116 cases)and BRCA wild group(140 cases)based on the BRCA results.Chi-square tests or independ-ent sample t-tests were used to compare the differences in clinicopathological characteristics and multiparametric MRI features between the BRCA mutation group and the wild group.Risk factors for BRCA-mutated BC were identified through univariate and multivariate logistic regression ananlyses,and a combined predictive model was constructed.Receiver operating characteristic(ROC)curve was used to ana-lyze the diagnostic efficacy of the model.Results There were statistically significant differences in T stage,human epidermal growth factor receptor 2(HER-2),Ki-67,non-mass enhancement,enhancement pattern,time-signal intensity curve(TIC)type,and apparent diffusion coefficient(ADC)values between the BRCA mutation group and the wild group.Univariate logistic regression analysis showed that T stage,HER-2,Ki-67,non-mass enhancement,enhancement pattern,TIC type,and ADC values were risk factors for BRCA-mutated BC(P<0.05).Multivariate logistic regression analysis revealed that T stage,HER-2,Ki-67,enhancement pattern,and TIC type were independent risk factors for BRCA-mutated BC(P<0.05).The combined model incorporating T stage,HER-2,Ki-67,enhancement pattern,and TIC type had the best diagnostic efficacy in predicting BRCA-mutated BC,with an area under the curve(AUC)of 0.751.Conclusion The combined model integrating T stage,HER-2,Ki-67,enhancement pattern,and TIC type has good efficacy in predicting BRCA-mutated BC.

Objective To evaluate the effectiveness of thermal tomography in breast cancer (BC) screening. Methods We conducted a general population-based BC screening in three regions of Hubei Province (Xiantao, Hongan, and Yangxin Districts). Participants underwent a questionnaire-based interview for baseline data collection. They then received a physical examination, thermal tomography, and ultrasound from doctors and technicians. We compared the efficacies, including sensitivity, specificity, and false-positive rates, of ultrasound and thermal tomography in BC screening. Results A total of 59 712 eligible women were included in this screening program. The BI-RADS 1, 2, 3, 4, and 5 accordance rates between the two screening methods were 0.9549, 0.8047, 0.9037, 0.3352, and 0, respectively. The overall accordance rate was 0.933 1. The kappa consistency results showed that the Cicchetti-Allison and Fleiss-Cohen kappa values were 0.7970 and 0.8583, respectively. Although the two methods had equal sensitivities, specificity was higher in thermal tomography than in ultrasound. The false-positive rate was lower in thermal tomography than in ultrasound. The area under the receiver operating characteristic (ROC) curve of thermal tomography was significantly larger than that of ultrasound. Conclusion The general consistency between thermal tomography and ultrasound in BC screening was high. Thermal tomography outperformed ultrasound in terms of specificity and diagnostic efficiency. Therefore, thermal tomography has a high application value for general population-based BC screening.

Purpose To develop an integrate model combining deep learning features from contrast-enhanced lung ultrasonography with clinical characteristics for predicting epidermal growth factor receptor mutation status in peripheral non-small cell lung cancer.Materials and Methods This retrospective study included 117 patients with pathologically confirmed non-small cell lung cancer from the First Affiliated Hospital of Guangxi Medical University(July 2021 to February 2024).Patients were randomly divided into training(n=93)and test(n=24)sets at an 8∶2 ratio.Regions of interest were delineated at the peak enhancement phase of contrast-enhanced lung ultrasonography.Various deep learning convolutional neural networks were pretrained,with ResNet18 selected as optimal for feature extraction.Deep learning,clinical,and integrated models were constructed using naive Bayesian algorithm.Performance was evaluated via receiver operating characteristic and calibration curves,while class activation mapping and Shapley additive explanation values provided model interpretability.Results In the training set,the deep learning,clinical and integrated models achieved area under the curve of 0.93(95%CI 0.88-0.98),0.86(95%CI 0.68-1.00),and 0.91(95%CI 0.85-0.97),respectively.Corresponding test set area under the curve were 0.81(95%CI 0.72-0.90),0.56(95%CI 0.33-0.80),and 0.87(95%CI 0.72-1.00).Both deep learning and integrated models significantly outperformed the clinical model in training(Z=2.380,P=0.017;Z=2.597,P=0.009)and test sets(Z=2.034,P=0.042;Z=2.577,P=0.010).The integrated model demonstrated excellent calibration and predictive performance.Conclusion The integrated model combining deep learning features from contrast-enhanced lung ultrasonography with clinical characteristics effectively predicts epidermal growth factor receptor mutation status in peripheral non-small cell lung cancer.

Objective To explore the efficacy of a model combining clinicopathological characteristics and multiparametric MRI features for predicting BRCA-mutated breast cancer(BC).Methods A total of 256 BC patients were retrospectively selected and divided into BRCA mutation group(116 cases)and BRCA wild group(140 cases)based on the BRCA results.Chi-square tests or independ-ent sample t-tests were used to compare the differences in clinicopathological characteristics and multiparametric MRI features between the BRCA mutation group and the wild group.Risk factors for BRCA-mutated BC were identified through univariate and multivariate logistic regression ananlyses,and a combined predictive model was constructed.Receiver operating characteristic(ROC)curve was used to ana-lyze the diagnostic efficacy of the model.Results There were statistically significant differences in T stage,human epidermal growth factor receptor 2(HER-2),Ki-67,non-mass enhancement,enhancement pattern,time-signal intensity curve(TIC)type,and apparent diffusion coefficient(ADC)values between the BRCA mutation group and the wild group.Univariate logistic regression analysis showed that T stage,HER-2,Ki-67,non-mass enhancement,enhancement pattern,TIC type,and ADC values were risk factors for BRCA-mutated BC(P<0.05).Multivariate logistic regression analysis revealed that T stage,HER-2,Ki-67,enhancement pattern,and TIC type were independent risk factors for BRCA-mutated BC(P<0.05).The combined model incorporating T stage,HER-2,Ki-67,enhancement pattern,and TIC type had the best diagnostic efficacy in predicting BRCA-mutated BC,with an area under the curve(AUC)of 0.751.Conclusion The combined model integrating T stage,HER-2,Ki-67,enhancement pattern,and TIC type has good efficacy in predicting BRCA-mutated BC.

Background and purpose:Approximately 30%of patients with metastatic colorectal cancer(CRC)develops pulmonary metastasis,yet less than 10%are eligible for surgical resection.Radiofrequency ablation(RFA)serves as an alternative therapy for non-surgical candidates,but the relationship between its efficacy and tumor diameter remains controversial.This study aimed to investigate the impact of tumor size on survival outcomes and local progression risk in CRC patients with pulmonary metastasis after RFA,and to validate the clinical utility of a 3 cm threshold for prognosis.Methods:This retrospective study included CRC patients with pulmonary metastasis who underwent RFA at Fudan University Shanghai Cancer Center between January 2016 and December 2024.Patients were stratified into two groups based on maximum lesion diameter:≤3 cm(Small group)and 3-5 cm(Large group).Patient inclusion criteria:⑴ pathologically confirmed lung metastases originating from CRC,with metastases limited to the lungs or extra-pulmonary metastatic lesions having been radically treated;⑵ maximum lesion diameter<5 cm;⑶complete clinical data available;⑷ complete imaging data available,including computed tomography(CT)images during ablation and contrast-enhanced CT images during postoperative follow-up;⑸ follow-up time of at least＞6 months after RFA;⑹ technical complete ablation;⑺ fewer than 3 pulmonary metastatic lesions.Exclusion criteria:⑴ target lesions previously treated with local therapies such as RFA or radiotherapy;⑵ patients unable to tolerate RFA;⑶ patients with follow-up time＜6 months after RFA.Three senior interventional physicians performed percutaneous RFA under guidance of a 64-slice spiral CT scanner.Chest contrast-enhanced CT scans obtained 1 month after RFA were used as the baseline,followed by contrast-enhanced CT scans every 3 months for 1 year,then every 6 months for subsequent follow-up.This study was approved by the medical ethics committee of Fudan University Shanghai Cancer Center(ethical approval number:2108241-11).Primary endpoints included overall survival(OS),progression-free survival(PFS),and local tumor progression(LTP).Kaplan-Meier analysis and multivariate COX regression were employed to evaluate the independent prognostic value of tumor size.Results:A total of 134 patients who met the inclusion criteria were ultimately enrolled,including 77 in the Small group and 57 in the Large group.With a median follow-up of 35 months,the≤3 cm group demonstrated superior 1-,3-,and 5-year OS rates(100.0%,95.1%,74.2%)compared to the 3-5 cm group(94.7%,36.8%,27.0%,P＜0.0001),and the≤3 cm group demonstrated superior 1-,3-,and 5-year PFS rates(90.9%,34.4%,23.3%)compared to the 3-5 cm group(13.8%,0.0%,0.0%,P＜0.000 1).The≤3 cm group also exhibited significantly lower 1-,3-,and 5-year LTP rates(0.0%,19.7%,33.6%)compared to the 3-5 cm group(46.0%,75.5%,75.5%,P＜0.000 1).Multivariable analysis identified tumor diameter＞3 cm as an independent predictor of worse OS[hazard ratio(HR)=6.49,95%CI:3.18-13.24,P＜0.001],while elevated preoperative carcinoembryonic antigen(CEA)(≥5 ng/mL)correlated with shorter OS(HR=1.82,P=0.033).Conclusion:CRC patients with pulmonary metastasis and tumor diameters of 3-5 cm exhibited significantly inferior survival outcomes after RFA compared to the≤3 cm group.A tumor diameter of 3 cm can serve as a critical threshold for selecting RFA indications,and combining preoperative CEA levels can optimize patient stratification.

Purpose To develop an integrate model combining deep learning features from contrast-enhanced lung ultrasonography with clinical characteristics for predicting epidermal growth factor receptor mutation status in peripheral non-small cell lung cancer.Materials and Methods This retrospective study included 117 patients with pathologically confirmed non-small cell lung cancer from the First Affiliated Hospital of Guangxi Medical University(July 2021 to February 2024).Patients were randomly divided into training(n=93)and test(n=24)sets at an 8∶2 ratio.Regions of interest were delineated at the peak enhancement phase of contrast-enhanced lung ultrasonography.Various deep learning convolutional neural networks were pretrained,with ResNet18 selected as optimal for feature extraction.Deep learning,clinical,and integrated models were constructed using naive Bayesian algorithm.Performance was evaluated via receiver operating characteristic and calibration curves,while class activation mapping and Shapley additive explanation values provided model interpretability.Results In the training set,the deep learning,clinical and integrated models achieved area under the curve of 0.93(95%CI 0.88-0.98),0.86(95%CI 0.68-1.00),and 0.91(95%CI 0.85-0.97),respectively.Corresponding test set area under the curve were 0.81(95%CI 0.72-0.90),0.56(95%CI 0.33-0.80),and 0.87(95%CI 0.72-1.00).Both deep learning and integrated models significantly outperformed the clinical model in training(Z=2.380,P=0.017;Z=2.597,P=0.009)and test sets(Z=2.034,P=0.042;Z=2.577,P=0.010).The integrated model demonstrated excellent calibration and predictive performance.Conclusion The integrated model combining deep learning features from contrast-enhanced lung ultrasonography with clinical characteristics effectively predicts epidermal growth factor receptor mutation status in peripheral non-small cell lung cancer.

Objective To investigate the impact of enterovirus 71(EV71)on skeletal muscle injury and explore its mechanism in relation to the caspase-1/interleukin(IL)-1 β signaling pathway in EV71-induced skeletal muscle damage.Methods One-day-old BALB/c suckling mice were divided randomly into three groups:normal control(NC)(n=60),EV71 infection model(n=60),and caspase-1 inhibitor(EV71+VX765)(n=15)groups.The NC and EV71 model groups were further subdivided into four subgroups(5,7,10,and 14 days)(n=5 mice per group).An EV71-infected model was established by intraperitoneal injection of 25 × 103 μL/kg EV71 viral solution for 3 consecutive days.Mice in the caspase-1 inhibitor group received VX765(20 mg/kg)intraperitoneally 6 hours post-viral inoculation,continued daily for 10 days until sample collection.Mice in the NC group received an equivalent volume of saline containing 5％dimethylsulfoxide and 10％PEG300,followed by 2％cell maintenance solution after 6 hours.Post-modeling body weight and clinical disease scores were recorded.Pathological skeletal muscle damage was observed by hematoxylin-eosin(HE)staining,and expression levels of EV71 VP-1(viral capsid protein),pro-caspase-1,cleaved-caspase-1,IL-1 β,α-smooth muscle actin(SMA),and Collagen Ⅰ were detected by Western blot and immunofluorescence.Results Compared with the NC group at the same time points,mice in the EV71 model group exhibited reduced body weight,elevated disease scores,and skeletal muscle pathology characterized by inflammatory cell infiltration,myofiber dissolution,and decreased cross-sectional area(HE staining).Western blot showed significantly increased levels of EV71 VP-1,IL-1β,α-SMA,and Collagen Ⅰ in skeletal muscle homogenate from EV71 mice at 5,7,and 10 days post-infection(P＜0.001).In contrast,mice in the VX765 group showed improved body weight,reduced clinical scores(P＜0.01),and significant downregulation of EV71 VP-1(P＜0.01),pro-caspase-1,cleaved-caspase-1,IL-1β,and Collagen Ⅰ compared with the EV71 model group(P＜0.01).These findings were confirmed by immunofluorescence,indicating that inhibition of caspase-1 alleviated EV71-induced skeletal muscle injury.Conclusions EV71 may induce skeletal muscle injury by activating the caspase-1/IL-1β signaling pathway.

Background and Purpose:The early prediction of local tumor progression-free survival(LTPFS)after radiofrequency ablation(RFA)for colorectal cancer(CRC)lung metastases has significant clinical importance.The application of radiomics in the prediction of tumor prognosis has been explored.This study aimed to construct a radiomics-based nomogram for predicting LTPFS after RFA in CRC patients with lung metastases.Methods:This study retrospectively analyzed 172 CRC patients with 401 lung metastases admitted to Department of Interventional Radiology,Fudan University Shanghai Cancer Center from August 2016 to January 2019.This study was reviewed by the medical ethics committee of Fudan University Shanghai Cancer Center(ethics number:2402291-24).After augmentation of pre-ablation and immediate post-ablation computed tomography(CT)images,the target metastases and ablation regions were segmented manually to extract the radiomic features.Maximum relevance and minimum redundancy algorithm(MRMRA)and least absolute shrinkage and selection operator(LASSO)regression models were applied for feature selection.The clinical model,the radiomics model,and the fusion model were constructed based on the selected radiomic features and clinical variables screened by the multivariate analysis.The Harrell concordance index(C-index)and area under receiver operating characteristic(ROC)curves(AUC)were calculated to evaluate the prediction performance.Finally,the corresponding nomogram of the best model was drawn.Results:Among all the lung metastases,102(25.4%)had final recurrence,and 299(74.6%)had complete response(CR).The median follow-up time was 21 months(95%CI:19.466-22.534),and the LTPFS rates at 1,2,and 3 years after RFA were 76.5%(95%CI:72.0-80.4),72.1%(95%CI:66.6-76.9)and 69.9%(95%CI:64.0-75.1).In both the training and test dataset,the fusion model based on the final 12 radiomic features through the LASSO regression and 4 clinical variables screened by multivariate analysis achieved the highest AUC values for LTPFS,with C-index values of 0.890(95%CI:0.854-0.927)and 0.843(95%CI:0.768-0.916),respectively.Conclusion:The fusion model based on radiomic features and clinical variables is feasible for predicting LTPFS after RFA of CRC patients with lung metastases,whose performance is superior to the single radiomic and clinical model.At the same time,the nomogram of the fusion model can intuitively predict the prognosis of CRC patients with lung metastases after RFA,thus assisting clinicians in developing individualized follow-up review plans for patients and adjusting treatment strategies flexibly.