Objective To introduce an innovative technique, the "balance-shaped sternal elevation device" and its application in the subxiphoid uniportal video-assisted thoracoscopic surgery (VATS) for anterior mediastinal masses resection. Methods Patients who underwent single-port thoracoscopic assisted anterior mediastinal tumor resection through the xiphoid process at the Department of Thoracic Surgery, West China Hospital, Sichuan University from May to June 2024 were included, and their clinical data were analyzed. Results A total of 7 patients were included, with 3 males and 4 females, aged 28-72 years. The diameter of the tumor was 1.9-17.0 cm. The operation time was 62-308 min, intraoperative blood loss was 5-100 mL, postoperative chest drainage tube retention time was 0-9 days, pain score on the 7th day after surgery was 0-2 points, and postoperative hospital stay was 3-12 days. All patients underwent successful and complete resection of the masses and thymus, with favorable postoperative recovery. Conclusion The "balance-shaped sternal elevation device" effectively expands the retrosternal space, providing surgeons with satisfactory surgical views and operating space. This technique significantly enhances the efficacy and safety of minimally invasive surgery for anterior mediastinal masses, reduces trauma and postoperative pain, and accelerates patient recovery, demonstrating important clinical significance and application value.

Objective To analyze the epidemiological distribution characteristics and influencing factors of treat-ment outcome of pulmonary tuberculosis(PTB)patients complicated with diabetes mellitus(DM)in Bijie City from 2017 to 2022,and provide reference for formulating prevention and control measures of PTB-DM.Methods The registered management cases of PTB patients combined with DM from the tuberculosis surveillance report informa-tion management system in Bijie City in 2017-2022 were collected.Changing trends in annual registration rates and successful treatment rates were analyzed with Joint-point regression models.Different characteristics between pa-tients with PTB-DM and PTB alone were conducted comparative analysis;the influencing factors of treatment out-come were analyzed by x2 test and binary logistic regression analysis.Results A total of 679 PTB-DM patients were registered in Bijie City from 2017 to 2022,accounting for 1.53％of total PTB patients,the annual registration rate increased from 1.11/100 000 in 2017 to 3.08/100 000 in 2022,with an increasing trend in the annual percentage change(APC=26.67％,95％CI:5.36％-52.29％,t=3.564,P=0.024).In the analysis on characteristics,the proportion of PTB-DM male patients,age ≥45 years and farmers,the ratio of direct consultation to transfer treat-ment,the pathogenicity positive rate,the proportion re-treatment,and rate of delay in consultation were all higher than those of PTB alone;successful treatment rate and proportion of floating population were all lower than PTB alone,difference were all statistically significant(all P＜0.05).The successful treatment rate of PTB-DM patients in Bijie City from 2017 to 2022 was 87.80％.Age,occupation,pathogenicity diagnosis results were influencing fac-tors for treatment outcome in patients with PTB-DM,with farmers(OR=3.68,95％CI:1.22-11.09),with pathogenicity positivity(OR=2.84,95％CI:1.24-6.50),and without pathogenic detection result+tuberculous pleurisy(OR=11.35,95％CI:2.16-59.74)being risk factors for successful treatment.Conclusion Although the proportion of PTB-DM in the total PTB patients in Bijie City from 2017 to 2022 was not high,it showed an up-ward trend;it is necessary to attach great importance to male,re-treated,farmer,and pathogenicity positivity co-morbid patients in Bijie City,and strengthen the two-way screening of PTB-DM in high-risk populations.

Objective To quantitatively analyze the effect of long-term ultrahigh-altitude and mid-high-altitude expo-sure on fundus microcirculation.Methods In the cross-sectional study,healthy residents from ultrahigh-altitude areas(＞3 500-5 500 m)and those from mid-high-altitude areas(＞1 500-3 500 m)were included as subjects.Meanwhile,healthy residents from plain areas were included as the control group.All subjects underwent optical coherence tomography angiography(OCTA)and spectral domain optical coherence tomography(SD-OCT)scans.Fundus images were quantified using ImageJ,and fundus microcirculation metrics were calculated and compared among these groups.Retinal microcircu-lation metrics included retinal vessel density(RVD),retinal skeleton density(RSD),fractal dimension(FD),foveal avas-cular zone(FAZ)area,and ganglion cell complex(GCC)thickness.Choroidal microcirculation metrics included subfoveal choroidal thickness(SFCT),luminal area(LA),total choroidal area(TCA),and choroidal vascularity index(CVI).Results In the ultra-high altitude group,the RVD was(32.52±3.57)％,the RSD was(15.05±4.24)％,and the FD was 1.68±0.08,all of which were significantly lower compared with the control group(all P＜0.001).The average thick-ness of GCC in the ultrahigh-altitude group was(98.76±10.26)μm,which was significantly thinner than the average thickness of GCC in the control group(P＜0.001).The TCA in the ultrahigh-altitude group was(2.15±0.49)mm2,the LA was(1.17±0.36)mm2,and the SFCT was(318.12±76.50)μm,all of which were significantly higher compared with the control group(all P＜0.001).However,the CVI was significantly decreased in the ultrahigh-altitude group compared with the control group(P＜0.001).There were no significant differences in fundus microcirculation metrics between the mid-high-altitude group and the control group(all P＞0.05).Conclusion Long-term ultrahigh-altitude exposure may induce ischemia and hypoxia in the fundus,primarily characterized by a decrease in the retinal and choroidal blood flow density,whereas long-term mid-high-altitude exposure cannot cause changes in the fundus microcirculation.

Objective:To develop and validate a machine learning (ML) noninvasive model based on routine laboratory parameters to preoperatively predict the microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).Methods:A total of 629 HCC patients who underwent hepatectomy at the First Affiliated Hospital of Fujian Medical University between January 2019 and December 2023 were retrospectively enrolled in this study and were divided chronologically into a training set ( n=464) and internal validation set ( n=165). A cohort with 190 HCC patients from Fujian Provincial Hospital were used as an external validation set. Preoperatively demographic features, tumor size and routine laboratory data were collected. All patients were divided into MVI-positive or MVI-negative group. The Boruta algorithm and LASSO regression algorithm were used to screen out related features in the training set. Eight different ML algorithms including multivariate logistic regression, decision tree (DT), random forest (RF), extreme gradient boosting (XGboost), k-nearest neighbor (KNN), support vector machine (SVM), light gradient boosting machine (LGBM) and Naive Bayes were used to construct the prediction models. The predictive performances of these models on training and internal validation sets were evaluated by the receiver operating characteristic (ROC) curve with the area under the curve (AUC). The ML model with the highest AUC values was defined as the optimal model and its performance was further validated in the external validation set. The calibration curve showed that the probability value curve was close to the actual occurrence probability curve, and the DCA showed that it could be applied within the threshold probability range of 0.3-0.8 to obtain net benefits. Results:After screening, eight parameters including α-fetoprotein (AFP), protein induced by vitamin K absence Ⅱ (PIVKA-Ⅱ), tumor size, eosinophil count, neutrophil count, creatinine, ApoA1 and total bilirubin were finally selected for the construction of the preoperative prediction model for MVI in HCC. Among all the tested eight ML algorithms, XGboost obtained the optimal performance with an AUC of 0.820 in training set, an AUC of 0.803 in internal testing set and an AUC of 0.758 in external testing set. Further stratified analysis showed that the AUC for preoperatively predicting MVI by XGboost was 0.817 for HCC patients with positive hepatitis B surface antigen, 0.779 for male patients and 0.790 for elder patients. The calibration curves showed good agreement between observed and predicted values and the decision curve analysis curve showed relatively higher net benefits.Conclusions:We successfully established and verified a novel XGboost model based on eight routine laboratory parameters with relatively high and reliable predictive accuracy to preoperatively predict MVI in HCC.

Objective To analyze the research status,hotspots,and trends of wearable devices in nursing applications both domestically and internationally.Methods Using China National Knowledge Infrastructure,Wanfang Data Knowledge Service Platform,and Embase core databases as data sources,VOSviewer was used to visualize and analyze the publication time,keywords,and other relevant literature.Results Total of 428 articles were included,including 196 Chinese articles and 232 English articles.The overall publication volume showed an upward trend.Domestic research focuses on chronic diseases,artificial intelligence,and nursing,with the main research subjects being the elderly;Foreign research focuses on smart devices,self-monitoring,and quality of life,with the main research subjects being adults.Conclusion Currently,the number of publications on the application of wearable devices in nursing is relatively small,but the overall research heat is on the rise,mainly used for chronic diseases and self-monitoring.In the future,the application scope of wearable devices should be expanded and their potential value should be explored to promote the innovation and progress of nursing models.

Objective To analyze the research status,hotspots,and trends of wearable devices in nursing applications both domestically and internationally.Methods Using China National Knowledge Infrastructure,Wanfang Data Knowledge Service Platform,and Embase core databases as data sources,VOSviewer was used to visualize and analyze the publication time,keywords,and other relevant literature.Results Total of 428 articles were included,including 196 Chinese articles and 232 English articles.The overall publication volume showed an upward trend.Domestic research focuses on chronic diseases,artificial intelligence,and nursing,with the main research subjects being the elderly;Foreign research focuses on smart devices,self-monitoring,and quality of life,with the main research subjects being adults.Conclusion Currently,the number of publications on the application of wearable devices in nursing is relatively small,but the overall research heat is on the rise,mainly used for chronic diseases and self-monitoring.In the future,the application scope of wearable devices should be expanded and their potential value should be explored to promote the innovation and progress of nursing models.

Objective To analyze the epidemiological distribution characteristics and influencing factors of treat-ment outcome of pulmonary tuberculosis(PTB)patients complicated with diabetes mellitus(DM)in Bijie City from 2017 to 2022,and provide reference for formulating prevention and control measures of PTB-DM.Methods The registered management cases of PTB patients combined with DM from the tuberculosis surveillance report informa-tion management system in Bijie City in 2017-2022 were collected.Changing trends in annual registration rates and successful treatment rates were analyzed with Joint-point regression models.Different characteristics between pa-tients with PTB-DM and PTB alone were conducted comparative analysis;the influencing factors of treatment out-come were analyzed by x2 test and binary logistic regression analysis.Results A total of 679 PTB-DM patients were registered in Bijie City from 2017 to 2022,accounting for 1.53％of total PTB patients,the annual registration rate increased from 1.11/100 000 in 2017 to 3.08/100 000 in 2022,with an increasing trend in the annual percentage change(APC=26.67％,95％CI:5.36％-52.29％,t=3.564,P=0.024).In the analysis on characteristics,the proportion of PTB-DM male patients,age ≥45 years and farmers,the ratio of direct consultation to transfer treat-ment,the pathogenicity positive rate,the proportion re-treatment,and rate of delay in consultation were all higher than those of PTB alone;successful treatment rate and proportion of floating population were all lower than PTB alone,difference were all statistically significant(all P＜0.05).The successful treatment rate of PTB-DM patients in Bijie City from 2017 to 2022 was 87.80％.Age,occupation,pathogenicity diagnosis results were influencing fac-tors for treatment outcome in patients with PTB-DM,with farmers(OR=3.68,95％CI:1.22-11.09),with pathogenicity positivity(OR=2.84,95％CI:1.24-6.50),and without pathogenic detection result+tuberculous pleurisy(OR=11.35,95％CI:2.16-59.74)being risk factors for successful treatment.Conclusion Although the proportion of PTB-DM in the total PTB patients in Bijie City from 2017 to 2022 was not high,it showed an up-ward trend;it is necessary to attach great importance to male,re-treated,farmer,and pathogenicity positivity co-morbid patients in Bijie City,and strengthen the two-way screening of PTB-DM in high-risk populations.

Objective To quantitatively analyze the effect of long-term ultrahigh-altitude and mid-high-altitude expo-sure on fundus microcirculation.Methods In the cross-sectional study,healthy residents from ultrahigh-altitude areas(＞3 500-5 500 m)and those from mid-high-altitude areas(＞1 500-3 500 m)were included as subjects.Meanwhile,healthy residents from plain areas were included as the control group.All subjects underwent optical coherence tomography angiography(OCTA)and spectral domain optical coherence tomography(SD-OCT)scans.Fundus images were quantified using ImageJ,and fundus microcirculation metrics were calculated and compared among these groups.Retinal microcircu-lation metrics included retinal vessel density(RVD),retinal skeleton density(RSD),fractal dimension(FD),foveal avas-cular zone(FAZ)area,and ganglion cell complex(GCC)thickness.Choroidal microcirculation metrics included subfoveal choroidal thickness(SFCT),luminal area(LA),total choroidal area(TCA),and choroidal vascularity index(CVI).Results In the ultra-high altitude group,the RVD was(32.52±3.57)％,the RSD was(15.05±4.24)％,and the FD was 1.68±0.08,all of which were significantly lower compared with the control group(all P＜0.001).The average thick-ness of GCC in the ultrahigh-altitude group was(98.76±10.26)μm,which was significantly thinner than the average thickness of GCC in the control group(P＜0.001).The TCA in the ultrahigh-altitude group was(2.15±0.49)mm2,the LA was(1.17±0.36)mm2,and the SFCT was(318.12±76.50)μm,all of which were significantly higher compared with the control group(all P＜0.001).However,the CVI was significantly decreased in the ultrahigh-altitude group compared with the control group(P＜0.001).There were no significant differences in fundus microcirculation metrics between the mid-high-altitude group and the control group(all P＞0.05).Conclusion Long-term ultrahigh-altitude exposure may induce ischemia and hypoxia in the fundus,primarily characterized by a decrease in the retinal and choroidal blood flow density,whereas long-term mid-high-altitude exposure cannot cause changes in the fundus microcirculation.

Objective:To develop and validate a machine learning (ML) noninvasive model based on routine laboratory parameters to preoperatively predict the microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).Methods:A total of 629 HCC patients who underwent hepatectomy at the First Affiliated Hospital of Fujian Medical University between January 2019 and December 2023 were retrospectively enrolled in this study and were divided chronologically into a training set ( n=464) and internal validation set ( n=165). A cohort with 190 HCC patients from Fujian Provincial Hospital were used as an external validation set. Preoperatively demographic features, tumor size and routine laboratory data were collected. All patients were divided into MVI-positive or MVI-negative group. The Boruta algorithm and LASSO regression algorithm were used to screen out related features in the training set. Eight different ML algorithms including multivariate logistic regression, decision tree (DT), random forest (RF), extreme gradient boosting (XGboost), k-nearest neighbor (KNN), support vector machine (SVM), light gradient boosting machine (LGBM) and Naive Bayes were used to construct the prediction models. The predictive performances of these models on training and internal validation sets were evaluated by the receiver operating characteristic (ROC) curve with the area under the curve (AUC). The ML model with the highest AUC values was defined as the optimal model and its performance was further validated in the external validation set. The calibration curve showed that the probability value curve was close to the actual occurrence probability curve, and the DCA showed that it could be applied within the threshold probability range of 0.3-0.8 to obtain net benefits. Results:After screening, eight parameters including α-fetoprotein (AFP), protein induced by vitamin K absence Ⅱ (PIVKA-Ⅱ), tumor size, eosinophil count, neutrophil count, creatinine, ApoA1 and total bilirubin were finally selected for the construction of the preoperative prediction model for MVI in HCC. Among all the tested eight ML algorithms, XGboost obtained the optimal performance with an AUC of 0.820 in training set, an AUC of 0.803 in internal testing set and an AUC of 0.758 in external testing set. Further stratified analysis showed that the AUC for preoperatively predicting MVI by XGboost was 0.817 for HCC patients with positive hepatitis B surface antigen, 0.779 for male patients and 0.790 for elder patients. The calibration curves showed good agreement between observed and predicted values and the decision curve analysis curve showed relatively higher net benefits.Conclusions:We successfully established and verified a novel XGboost model based on eight routine laboratory parameters with relatively high and reliable predictive accuracy to preoperatively predict MVI in HCC.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, with rapid progression and a poor prognosis. More and more studies have shown that there are small open reading frames (sORFs) on the molecular sequences of a large number of non-coding RNAs (ncRNAs), which can encode conserved peptides that play an important role in controlling the occurrence and development of HCC. This article introduces the discovery, prediction, and validation methods of ncRNA-encoding polypeptides and reviews its research progress, with the aim of providing new targets and ideas for early-stage diagnosis, targeted therapy, and prognosis assessment of HCC.