Objective To establish a reliable prediction model for radiation pneumonitis(RP)based on multi-regional radiomics analysis of localizable CT images.Methods A retrospective analysis was conducted on 185 patients who received radiotherapy from January 2021 to June 2023 in the Department of Radiotherapy,Xuzhou Cancer Hospital.Patients were classified as having RP or not based on imaging combined with clinical diagnosis.Three regions of interest(ROI)were defined in the localizable CT images:Lung,Lung-PTV and PTV,and their radiomics features were extracted.After feature screening using methods such as Mann-Whitney Utest,recursive feature elimination,and Lasso,a prediction model was established using support vector machine classification algorithm.The model performance was validated using 6 evaluation metrics:the area under the receiver operating characteristic curve(AUC),accuracy,specificity,sensitivity,positive predictive value,and negative predictive value.Results The prediction model consisted of 7 radiomics features.The clinical model of target-to-lung ratio,PTV model,Lung model,and Lung-PTV model achieved AUC values of 0.535,0.801,0.672,and 0.706 in the test set,respectively.The AUC value and accuracy of PTV model reached 0.843 and 0.775 in the training set,while 0.801 and 0.750 in the test set.PTV model was superior to Lung model,Lung-PTV model,and clinical model in predictive performance.The AUC values of the combined PTV+(Lung-PTV)model in the training and test sets were 0.867 and 0.806,respectively,higher than those of PTV model and Lung-PTV model.Conclusion The predictive ability of the prediction models constructed from radiomics features in different ROI for symptomatic RP varies.The radiomics prediction model using PTV as ROI exhibits superior predictive performance,and the combined multi-regional radiomics model can further improve the predictive ability for RP.

BACKGROUND:Compensatory changes in sagittal parameters of the cervicothoracic spine after orthopedic surgery in patients with lumbar degenerative scoliosis and their intrinsic relationship,as well as the impact of these changes on quality of life,are still lacking.OBJECTIVE:To evaluate the compensatory alignment of cervical and thoracic vertebrae after correction of lumbar degenerative scoliosis.METHODS:103 patients who underwent surgical correction of lumbar degenerative scoliosis were included in this study.Patients'demographic characteristics and spinal sagittal parameters were assessed,and prediction equations between changes in cervical sagittal parameters and lumbar deformity correction were attempted.Simultaneously,the SRS-22 scale was used to assess the quality of life of patients and to explore the relationship between the compensatory changes of the cervical and thoracic spine after correction and the patients'health-related quality of life.RESULTS AND CONCLUSION:(1)At 3 months and 2 years after surgery,all indicators of the cervical spine and thoracic spine were significantly improved compared with those before surgery(P＜0.05),but there was no significant change at 3 months after surgery compared with 2 years after surgery(P＞0.05).At 3 months and 2 years after surgery,the lumbar spine parameters including lumbar lordosis,C7-S1 sagittal vertical axis,and pelvic incident-lumbar lordosis had significant changes compared with those before surgery(P＜0.05),but the change was not significant at 3 months after surgery compared with 2 years after surgery(P＞0.05).(2)Correlation analysis showed that the lumbar lordosis was highly correlated with the C3-C7 cervical lordosis,C1-C7 cervical lordosis,C2-7 sagittal vertical axis,thoracic inlet angle,and C7-S1 sagittal vertical axis(|r|≥ 0.5,P＜0.000 1).The lumbar lordosis was correlated with the thoracic kyphosis(r=-0.280).(3)Two prediction formulas were established for compensatory changes in cervical spine:cervical lordosis=0.524x,lumbar lordosis=-6.612,C2-7 sagittal vertical axis=-0.263x,and lumbar lordosis=-5.436(P＜0.05,R2＞0.6).(4)When postoperative C2-7 sagittal vertical axis was between 14.4 and 26.8 mm;cervical lordosis was between 9° and 41°,lumbar lordosis was between 42.7° and 68.7°,and sagittal vertical axis was between-40 and 40 mm,patients had better quality of life recovery.(5)It is indicated that significant compensatory changes in the sagittal plane of the cervical spine can be observed after correction of lumbar degenerative scoliosis.We found that each 1° increase in lumbar lordosis was associated with a corresponding increase of about 0.5° in cervical lordosis and a corresponding decrease of about 0.3 mm in the vertical axis of the C2-7 sagittal plane.Patient satisfaction was higher if compensatory changes were closer to normal sagittal plane.

Objective:To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer.Methods:Specimens were collected from 209 breast cancer patients who received NAT at Renmin Hospital of Wuhan University from October 2019 to June 2023. TSR levels in pre-NAT biopsy specimens were automatically computed using a deep learning algorithm and categorized into low stroma (TSR≤30%), intermediate stroma (TSR 30% to ≤60%), and high stroma (TSR>60%) groups. Residual cancer burden (RCB) grading of post-NAT surgical specimens was determined to compare the relationship between TSR expression levels and RCB grades. The correlation of TSR with NAT efficacy was analyzed, and the association between TSR expression and patient prognosis was further investigated.Results:There were 85 cases with low stroma (TSR≤30%), 93 cases with intermediate stroma (TSR 30% to ≤60%), and 31 cases with high stroma (TSR>60%). Different TSR expression levels showed significant differences between various RCB grades ( P<0.05). Logistic univariate and multivariate analyses showed that TSR was a risk factor for obtaining a complete pathological remission from neoadjuvant therapy for breast cancer when it was used as a continuous variable ( P<0.05); COX regression and survival analyses showed that the lower the percentage of tumorigenic mesenchyme was, the better the prognosis of the patient was ( P<0.05). Conclusions:The deep learning-based model enables automatic and accurate quantification of TSR. A lower pre-treatment tumoral stroma is associated with a lower RCB score and a higher rate of pathologic complete response, indicating that TSR can predict the efficacy of neoadjuvant therapy in breast cancer and thus holds prognostic significance. Therefore, TSR may serve as a biomarker for predicting therapeutic outcomes in breast cancer neoadjuvant therapy.

Objective:To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer.Methods:Specimens were collected from 209 breast cancer patients who received NAT at Renmin Hospital of Wuhan University from October 2019 to June 2023. TSR levels in pre-NAT biopsy specimens were automatically computed using a deep learning algorithm and categorized into low stroma (TSR≤30%), intermediate stroma (TSR 30% to ≤60%), and high stroma (TSR>60%) groups. Residual cancer burden (RCB) grading of post-NAT surgical specimens was determined to compare the relationship between TSR expression levels and RCB grades. The correlation of TSR with NAT efficacy was analyzed, and the association between TSR expression and patient prognosis was further investigated.Results:There were 85 cases with low stroma (TSR≤30%), 93 cases with intermediate stroma (TSR 30% to ≤60%), and 31 cases with high stroma (TSR>60%). Different TSR expression levels showed significant differences between various RCB grades ( P<0.05). Logistic univariate and multivariate analyses showed that TSR was a risk factor for obtaining a complete pathological remission from neoadjuvant therapy for breast cancer when it was used as a continuous variable ( P<0.05); COX regression and survival analyses showed that the lower the percentage of tumorigenic mesenchyme was, the better the prognosis of the patient was ( P<0.05). Conclusions:The deep learning-based model enables automatic and accurate quantification of TSR. A lower pre-treatment tumoral stroma is associated with a lower RCB score and a higher rate of pathologic complete response, indicating that TSR can predict the efficacy of neoadjuvant therapy in breast cancer and thus holds prognostic significance. Therefore, TSR may serve as a biomarker for predicting therapeutic outcomes in breast cancer neoadjuvant therapy.

This study aims to investigate the mechanisms underlying the effects of the combined ac-tion of high-fat diet-induced obesity and the aflatoxin B1(AFB1)on hepatic oxidative stress and inflammatory responses.Thirty-six rats of similar weight and 4 weeks old were randomly divided into 4 groups,with 9 rats in each group:the blank control group(basal diet),the AFB1 group(0.4 mg/kg AFB1+basal diet),the HFD group(high-fat diet),and the HFD+AFB1 group(high-fat diet+0.4 mg/kg AFB1).Histological changes and lipid deposition were observed via hematox-ylin-eosin(HE)staining and Oil Red O staining.Levels of oxidative stress and inflammation-relat-ed factors were measured using commercial assay kits.The relative protein expression levels of factors involved in the Nrf2-Keap1 signaling pathway were assessed by Western blot analysis.The HE staining results showed that in the AFB1 group,the liver cells exhibited widespread watery de-generation,with shrunk and ruptured nuclei,inflammatory cells infiltration,and increased fibrosis.In the HFD group,liver cell fatty degeneration was observed,with cytoplasmic lipid droplet infil-tration.In the portal area,liver fibrosis was seen,with liver cell necrosis and inflammatory cell in-filtration in the fibrotic area,accompanied by lipofuscous granules.When HFD was applied to the AFB1 group,the abnormal state of liver interstitial and interstitial spaces was further aggravated,and a large number of lipid droplets appeared.The Oil Red O staining results showed that there were large numbers of dark red lipid droplets in the liver tissue of the HFD group,which were fused in strands.In the AFB1 group,lipid droplets could also be observed in the liver tissue of rats,but the number and degree were significantly less than those in the HFD group.The number and degree of red lipid droplets in the liver tissue of rats in the HFD+AFB1 group were higher than those in the AFB1 group and the HFD group.HFD exacerbated AFB1-induced oxidative stress by elevating ROS,MDA levels,and decreasing the expression of antioxidant stress factors such as CAT,SOD,Nrf2,HO-1,NQO1,and GCLC.Furthermore,the combined effect of HFD and AFB1 further significantly increased the levels of pro-inflammatory cytokines IL-2,IL-6,TNF-α,and IL-1β in the body.In summary,HFD treatment significantly exacerbated liver oxidative stress and in-flammatory responses in rats exposed to AFB1 through the Nrf2-keap1 signaling pathway.

With the rapid advancements in minimally invasive spine surgery and the increasingly sophisti-cated concept of visualization,transforaminal endoscopic lumbar discectomy(TELD)has become a primary treatment for lumbar disc herniation.Among the critical preoperative steps in TELD,foraminalplasty plays a pivotal role,as its quality directly impacts surgical outcomes and postoperative recurrence rates.This article systemati-cally reviews the evolution of foraminalplasty techniques,evaluates the selection and application of plasty sites,examines factors influencing stability after lumbar foraminalplasty,and highlights recent advancements in computer-assisted navigation.The goal is to serve as a comprehensive reference for clinicians.

BACKGROUND:Compensatory changes in sagittal parameters of the cervicothoracic spine after orthopedic surgery in patients with lumbar degenerative scoliosis and their intrinsic relationship,as well as the impact of these changes on quality of life,are still lacking.OBJECTIVE:To evaluate the compensatory alignment of cervical and thoracic vertebrae after correction of lumbar degenerative scoliosis.METHODS:103 patients who underwent surgical correction of lumbar degenerative scoliosis were included in this study.Patients'demographic characteristics and spinal sagittal parameters were assessed,and prediction equations between changes in cervical sagittal parameters and lumbar deformity correction were attempted.Simultaneously,the SRS-22 scale was used to assess the quality of life of patients and to explore the relationship between the compensatory changes of the cervical and thoracic spine after correction and the patients'health-related quality of life.RESULTS AND CONCLUSION:(1)At 3 months and 2 years after surgery,all indicators of the cervical spine and thoracic spine were significantly improved compared with those before surgery(P＜0.05),but there was no significant change at 3 months after surgery compared with 2 years after surgery(P＞0.05).At 3 months and 2 years after surgery,the lumbar spine parameters including lumbar lordosis,C7-S1 sagittal vertical axis,and pelvic incident-lumbar lordosis had significant changes compared with those before surgery(P＜0.05),but the change was not significant at 3 months after surgery compared with 2 years after surgery(P＞0.05).(2)Correlation analysis showed that the lumbar lordosis was highly correlated with the C3-C7 cervical lordosis,C1-C7 cervical lordosis,C2-7 sagittal vertical axis,thoracic inlet angle,and C7-S1 sagittal vertical axis(|r|≥ 0.5,P＜0.000 1).The lumbar lordosis was correlated with the thoracic kyphosis(r=-0.280).(3)Two prediction formulas were established for compensatory changes in cervical spine:cervical lordosis=0.524x,lumbar lordosis=-6.612,C2-7 sagittal vertical axis=-0.263x,and lumbar lordosis=-5.436(P＜0.05,R2＞0.6).(4)When postoperative C2-7 sagittal vertical axis was between 14.4 and 26.8 mm;cervical lordosis was between 9° and 41°,lumbar lordosis was between 42.7° and 68.7°,and sagittal vertical axis was between-40 and 40 mm,patients had better quality of life recovery.(5)It is indicated that significant compensatory changes in the sagittal plane of the cervical spine can be observed after correction of lumbar degenerative scoliosis.We found that each 1° increase in lumbar lordosis was associated with a corresponding increase of about 0.5° in cervical lordosis and a corresponding decrease of about 0.3 mm in the vertical axis of the C2-7 sagittal plane.Patient satisfaction was higher if compensatory changes were closer to normal sagittal plane.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Objective:To analyze the spatiotemporal correlation between the surveillance data of influenza in students reported by medical institutions and school absenteeism due to illness, and evaluate the application of Bayesian Structural Time Series model (BSTS) in the prediction of school influenza epidemic.Methods:A total of 13 schools in Dapeng new district of Shenzhen were selected. The incidence data of influenza in schools in Shenzhen from January 1, 2015 to December 31, 2019 were collected from China Disease Control and Prevention Information System and the illness related school absentence data during this period were collected from Shenzhen Student Health Surveillance System, and the spatiotemporal correlation between the data from two systems was analyzed and compared. BSTS was used to make long-term predictions of the monthly incidence of influenza in students in 2019 and short-term predictions of the weekly incidence of influenza in week 1-8 and week 45-52 of 2019 by using the data from two systems.Results:There was a temporal correlation between the data from China Disease Control and Prevention Information System and the data from Shenzhen Student Health Surveillance System ( r=0.93, P<0.001), and the lag of the former one was 1 day ( r=0.73, P<0.001). Influenza outbreaks were randomly distributed in different schools in Shenzhen, and there was no spatial correlation. The root mean square error ( RMSE) and mean absolute error ( MAE) were 0.35 and 0.28, respectively, in the long-term prediction, and the RMSE was 0.33 and 0.34, and the MAE was 0.26 and 0.28, respectively, in the short-term predictions of week 1-8 and week 45-52 of 2019, respectively, showing good prediction accuracy and fitting effect. Conclusion:By analyzing the data from China Disease Control and Prevention Information System and Shenzhen Student Health Surveillance System with BSTS, the dynamics of the school influenza epidemic can be accurately predicted, and effective technical support can be provided for the early warning and prevention and control of influenza epidemic.

Objective:To understand the changes in the prevelance smoking in people aged ≥15 years in Baoji, and provide evidence for the improvement of tobacco control strategies.Methods:Data were from the sampling survey of chronic diseases and their risk factors conducted in Baoji at an interval of five years from 2013 to 2023. The survey used multi-stage cluster random sampling method to select local people aged ≥15 years, and the information about their tobacco use were collected by face-to-face interview. Descriptive epidemiological methods were used to analyze the prevalence of smoking, and χ2 test was used to analyze the change trend. Results:The smoking rate in people aged ≥15 years in Baoji decreased from 2013 to 2023, and the standardized smoking rate decreased by 13.6% in 2023 compared with 2013. The standardized smoking cessation rate increased by 13.4% in 2018 compared with 2013, and the standardized smoking cessation rate decreased by 7.3% in 2023 compared with 2018. The standardized passive smoking rate decreased by 15.1% in 2018 compared with 2013, and the standardized passive smoking rate increased by 8.8% in 2023 compared with 2018. The average daily smoking amount increased by 3.7 cigarettes in 2018 compared with 2013, and the average daily smoking amount decreased by 3.9 cigarettes in 2023 compared with 2018.Conclusion:Progress has been made in tobacco control in Baoji, but problems still exist in tobacco control, to which close attention needs to be paid.