BACKGROUND:Crosslinked sodium hyaluronate gel has good mechanical property,biocompatibility,and biodegradability,and can be used as an isolated protective material in tumor radiation therapy to protect endangered organs from damage caused by excess radiation dose. OBJECTIVE:To investigate the safety and efficacy of crosslinked sodium hyaluronate gel in reducing the dose of radiation to dangerous organs during brachytherapy. METHODS:A total of 16 specific pathogen-free Kunming mice of the same age and similar body weight were selected as experimental subjects and divided into experimental group and control group by the random number table method,with 8 mice in each group.125I seeds were implanted subcutaneously in the back of mice in the experimental group,and then crosslinked sodium hyaluronate gel was injected around the radioactive particles.Only 125I seeds were implanted subcutaneously in the back of mice in the control group.After injection,the distance between the radioactive particles and the epidermis was measured by spiral CT scan,and the surface radiation dose was measured by radiation dosimeter.Within 10 weeks after injection,the growth state,survival rate,skin radiation damage,and gel retention of mice were observed. RESULTS AND CONCLUSION:(1)Spiral CT scan showed that the implanted gel was relatively concentrated and created an effective distance between the radioactive seeds and the epidermis.The body surface radiation dose of the experimental group was significantly lower than that of the control group(P<0.01).(2)During the experimental observation period,mice in both groups survived;mice in the control group showed obvious irritability and other unstable behavior in the late experimental period,and some mice in the experimental group showed similar behavior.The daily food intake of mice in the two groups had no significant change,and the body mass showed the same increasing trend.After implantation of radioactive seeds,the two groups of mice showed different degrees of radioactive skin injury.From day 23 after injection to the end of the experiment,the skin radiation injury score of the experimental group was lower than that of the control group(P<0.01).At week 10 after implantation,6 mice in the experimental group had no obvious gel residue under their skin,and 2 mice had a very small amount of scattered gel-like samples under their skin.(3)Therefore,the crosslinked sodium hyaluronate injection technique can increase the space between the radioactive target area of 125I seeds and the organ at risk outside the target through physical space occupying,which can effectively reduce the dose of the organ at risk,and play a role in the isolation and protection of the organ at risk.

ObjectiveTo investigate the acute effects of compound air pollution on children’s respiratory function. MethodsUsing panel group study design， 223 students in five classes of grade 4 from two primary schools （a， b） in Xuhui and Hongkou districts of Shanghai were randomly selected to measure pulmonary function and exhaled nitric oxide （FeNO）. The first three tests were carried out from May to June in 2020， and the fourth test was carried out from September to December in 2021. At the same time， the daily and hourly mean values of PM_2.5， PM₁₀， SO₂， NO₂， O₃ and CO was collected from the nearby air quality monitoring points of the two schools during the same period ， as well as meteorological monitoring data （temperature， humidity， wind speed and atmospheric pressure）. The linear mixed effect model was used to analyze the effects of air pollution on pulmonary function and respiratory inflammation in the summer. ResultsThe results of single pollutant model showed that PM_2.5， PM_10， SO₂ and NO₂ were positively correlated with FeNO， and the effect was reflected in lag0， lag1 and lag3 （P<0.05）. PM_2.5， PM₁₀ and NO₂ were negatively correlated with the changes of lung function FEF_25%， FEF_50%， FEF_75%， FeF_25%-75%， PEF， FVC， FEV1 and FEV1/FVC， and the effect was reflected in lag0 to lag3 days （P<0.05）. The results of the dual pollutant model showed that the concentration changes of SO₂ and NO₂ were significantly correlated with the decrease of FEV1 when combined with O₃ or PM_2.5 （P<0.01）， and the concentration changes of PM_2.5 was significantly correlated with the increase of FeNO when O₃， SO₂ and NO₂ were combined respectively （P<0.01）. The effects of the dual pollutant model were greater than the effect of PM_2.5 single pollutant model. ConclusionThe health effects of different air pollutants on children’s respiratory tract function indexes in summer are different. The combined effects of two pollutants on the lung function of children increased to different degrees. Although air pollution is light in summer， it still has an impact on children’s respiratory tract function index and inflammation index， and the combined effect of dual pollutants is more significant than that of single pollutant.

Objective To explore the mechanism and effects of Basonuclin 1(BNC1)on the migration and invasion abilities of lung squamous cell carcinoma.Methods Bioinformatics technology was used to analyze the expression patterns and survival impact of BNC1 in patients with lung squamous cell carcinoma in online databases;Tissue microarrays were stained by immunohistochemistry assay and analyzed for BNC1 protein level.Cell lines for lung squamous cell carcinoma with high and low BNC1 expression were screened in the Cancer Cell Line Encyclopedia(CCLE)database.Wound healing experiment and transwell assay were performed on lung squamous cell carcinoma cell models with knockdown and overexpression of BNC1,and the migration and invasion rates of each cell line were detected;Quantitative reverse transcription PCR(RT-qPCR)was used to validate the migration and invasion of 10 highly related genes derived from literature.Western blotting was used to validate the selected regulatory genes.Results Bioinformatics technology found that BNC1 was highly expressed in lung squamous cell carcinoma tissues and was associated with lower survival rate(P=0.047).The expression of BNC1 in lung squamous cell carcinoma was higher than that in paracancerous tissues(P＜0.05).BNC1 had higher expression in the H226 cells and lower expression in the SK-MES1 cells.BNC1 knockdown inhibited the migration and invasion abilities of lung squamous cell carcinoma cells(P＜0.05),and BNC1 overexpression enhanced the migration and invasion abilities of lung squamous cell carcinoma cells(P＜0.05).Screening of BNC1 downstream regulatory molecules at the mRNA level showed that CDH1 was decreased when BNC1 was overexpressed(P＜0.05),and increased when BNC1 was knocked down(P＜0.05).The results of mRNA level were consistent with the results verified by Western blotting(P＜0.05).Conclusion BNC1 may be a gene predicting poor prognosis for lung squamous cell carcinoma patients,and BNC1 may likely to promote cell migration and invasion of lung squamous cell carcinoma by downregulating CDH1 expression.

Objective:To investigate the incidence of postoperative complications in Chinese patients with gastric or colorectal cancer, and to evaluate the risk factors for postoperative complications.Methods:This was a national, multicenter, prospective, registry-based, cohort study of data obtained from the database of the Prevalence of Abdominal Complications After Gastro- enterological Surgery (PACAGE) study sponsored by the China Gastrointestinal Cancer Surgical Union. The PACAGE database prospectively collected general demographic characteristics, protocols for perioperative treatment, and variables associated with postoperative complications in patients treated for gastric or colorectal cancer in 20 medical centers from December 2018 to December 2020. The patients were grouped according to the presence or absence of postoperative complications. Postoperative complications were categorized and graded in accordance with the expert consensus on postoperative complications in gastrointestinal oncology surgery and Clavien-Dindo grading criteria. The incidence of postoperative complications of different grades are presented as bar charts. Independent risk factors for occurrence of postoperative complications were identified by multifactorial unconditional logistic regression.Results:The study cohort comprised 3926 patients with gastric or colorectal cancer, 657 (16.7%) of whom had a total of 876 postoperative complications. Serious complications (Grade III and above) occurred in 4.0% of patients (156/3926). The rate of Grade V complications was 0.2% (7/3926). The cohort included 2271 patients with gastric cancer with a postoperative complication rate of 18.1% (412/2271) and serious complication rate of 4.7% (106/2271); and 1655 with colorectal cancer, with a postoperative complication rate of 14.8% (245/1655) and serious complication rate of 3.0% (50/1655). The incidences of anastomotic leakage in patients with gastric and colorectal cancer were 3.3% (74/2271) and 3.4% (56/1655), respectively. Abdominal infection was the most frequently occurring complication, accounting for 28.7% (164/572) and 39.5% (120/304) of postoperative complications in patients with gastric and colorectal cancer, respectively. The most frequently occurring grade of postoperative complication was Grade II, accounting for 65.4% (374/572) and 56.6% (172/304) of complications in patients with gastric and colorectal cancers, respectively. Multifactorial analysis identified (1) the following independent risk factors for postoperative complications in patients in the gastric cancer group: preoperative comorbidities (OR=2.54, 95%CI: 1.51-4.28, P<0.001), neoadjuvant therapy (OR=1.42, 95%CI:1.06-1.89, P=0.020), high American Society of Anesthesiologists (ASA) scores (ASA score 2 points:OR=1.60, 95% CI: 1.23-2.07, P<0.001, ASA score ≥3 points:OR=0.43, 95% CI: 0.25-0.73, P=0.002), operative time >180 minutes (OR=1.81, 95% CI: 1.42-2.31, P<0.001), intraoperative bleeding >50 mL (OR=1.29,95%CI: 1.01-1.63, P=0.038), and distal gastrectomy compared with total gastrectomy (OR=0.65,95%CI: 0.51-0.83, P<0.001); and (2) the following independent risk factors for postoperative complications in patients in the colorectal cancer group: female (OR=0.60, 95%CI: 0.44-0.80, P<0.001), preoperative comorbidities (OR=2.73, 95%CI: 1.25-5.99, P=0.030), neoadjuvant therapy (OR=1.83, 95%CI:1.23-2.72, P=0.008), laparoscopic surgery (OR=0.47, 95%CI: 0.30-0.72, P=0.022), and abdominoperineal resection compared with low anterior resection (OR=2.74, 95%CI: 1.71-4.41, P<0.001). Conclusion:Postoperative complications associated with various types of infection were the most frequent complications in patients with gastric or colorectal cancer. Although the risk factors for postoperative complications differed between patients with gastric cancer and those with colorectal cancer, the presence of preoperative comorbidities, administration of neoadjuvant therapy, and extent of surgical resection, were the commonest factors associated with postoperative complications in patients of both categories.

Objective:To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer.Methods:Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5–10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy.Results:The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing.Conclusion:The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.

Objective:To investigate the incidence of postoperative complications in Chinese patients with gastric or colorectal cancer, and to evaluate the risk factors for postoperative complications.Methods:This was a national, multicenter, prospective, registry-based, cohort study of data obtained from the database of the Prevalence of Abdominal Complications After Gastro- enterological Surgery (PACAGE) study sponsored by the China Gastrointestinal Cancer Surgical Union. The PACAGE database prospectively collected general demographic characteristics, protocols for perioperative treatment, and variables associated with postoperative complications in patients treated for gastric or colorectal cancer in 20 medical centers from December 2018 to December 2020. The patients were grouped according to the presence or absence of postoperative complications. Postoperative complications were categorized and graded in accordance with the expert consensus on postoperative complications in gastrointestinal oncology surgery and Clavien-Dindo grading criteria. The incidence of postoperative complications of different grades are presented as bar charts. Independent risk factors for occurrence of postoperative complications were identified by multifactorial unconditional logistic regression.Results:The study cohort comprised 3926 patients with gastric or colorectal cancer, 657 (16.7%) of whom had a total of 876 postoperative complications. Serious complications (Grade III and above) occurred in 4.0% of patients (156/3926). The rate of Grade V complications was 0.2% (7/3926). The cohort included 2271 patients with gastric cancer with a postoperative complication rate of 18.1% (412/2271) and serious complication rate of 4.7% (106/2271); and 1655 with colorectal cancer, with a postoperative complication rate of 14.8% (245/1655) and serious complication rate of 3.0% (50/1655). The incidences of anastomotic leakage in patients with gastric and colorectal cancer were 3.3% (74/2271) and 3.4% (56/1655), respectively. Abdominal infection was the most frequently occurring complication, accounting for 28.7% (164/572) and 39.5% (120/304) of postoperative complications in patients with gastric and colorectal cancer, respectively. The most frequently occurring grade of postoperative complication was Grade II, accounting for 65.4% (374/572) and 56.6% (172/304) of complications in patients with gastric and colorectal cancers, respectively. Multifactorial analysis identified (1) the following independent risk factors for postoperative complications in patients in the gastric cancer group: preoperative comorbidities (OR=2.54, 95%CI: 1.51-4.28, P<0.001), neoadjuvant therapy (OR=1.42, 95%CI:1.06-1.89, P=0.020), high American Society of Anesthesiologists (ASA) scores (ASA score 2 points:OR=1.60, 95% CI: 1.23-2.07, P<0.001, ASA score ≥3 points:OR=0.43, 95% CI: 0.25-0.73, P=0.002), operative time >180 minutes (OR=1.81, 95% CI: 1.42-2.31, P<0.001), intraoperative bleeding >50 mL (OR=1.29,95%CI: 1.01-1.63, P=0.038), and distal gastrectomy compared with total gastrectomy (OR=0.65,95%CI: 0.51-0.83, P<0.001); and (2) the following independent risk factors for postoperative complications in patients in the colorectal cancer group: female (OR=0.60, 95%CI: 0.44-0.80, P<0.001), preoperative comorbidities (OR=2.73, 95%CI: 1.25-5.99, P=0.030), neoadjuvant therapy (OR=1.83, 95%CI:1.23-2.72, P=0.008), laparoscopic surgery (OR=0.47, 95%CI: 0.30-0.72, P=0.022), and abdominoperineal resection compared with low anterior resection (OR=2.74, 95%CI: 1.71-4.41, P<0.001). Conclusion:Postoperative complications associated with various types of infection were the most frequent complications in patients with gastric or colorectal cancer. Although the risk factors for postoperative complications differed between patients with gastric cancer and those with colorectal cancer, the presence of preoperative comorbidities, administration of neoadjuvant therapy, and extent of surgical resection, were the commonest factors associated with postoperative complications in patients of both categories.

Objective:To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer.Methods:Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5–10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy.Results:The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing.Conclusion:The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.

Objective:To screen the main characteristic variables affecting the incidence of cardiovascular and cerebrovascular diseases,and to construct the Bayesian network model of cardiovascular and cerebrovascular disease incidence risk based on the top 10 characteristic variables,and to provide the reference for predicting the risk of cardiovascular and cerebrovascular disease incidence.Methods:From the UK Biobank Database,315 896 participants and related variables were included.The feature selection was performed by categorical boosting(CatBoost)algorithm,and the participants were randomly divided into training set and test set in the ratio of 7∶3.A Bayesian network model was constructed based on the max-min hill-climbing(MMHC)algorithm.Results:The prevalence of cardiovascular and cerebrovascular diseases in this study was 28.8％.The top 10 variables selected by the CatBoost algorithm were age,body mass index(BMI),low-density lipoprotein cholesterol(LDL-C),total cholesterol(TC),the triglyceride-glucose(TyG)index,family history,apolipoprotein A/B ratio,high-density lipoprotein cholesterol(HDL-C),smoking status,and gender.The area under the receiver operating characteristic(ROC)curve(AUC)for the CatBoost training set model was 0.770,and the model accuracy was 0.764;the AUC of validation set model was 0.759 and the model accuracy was 0.763.The clinical efficacy analysis results showed that the threshold range for the training set was 0.06-0.85 and the threshold range for the validation set was 0.09-0.81.The Bayesian network model analysis results indicated that age,gender,smoking status,family history,BMI,and apolipoprotein A/B ratio were directly related to the incidence of cardiovascular and cerebrovascular diseases and they were the significant risk factors.TyG index,HDL-C,LDL-C,and TC indirectly affect the risk of cardiovascular and cerebrovascular diseases through their impact on BMI and apolipoprotein A/B ratio.Conclusion:Controlling BMI,apolipoprotein A/B ratio,and smoking behavior can reduce the incidence risk of cardiovascular and cerebrovascular diseases.The Bayesian network model can be used to predict the risk of cardiovascular and cerebrovascular disease incidence.

Objective:Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease.However,we still don't fully understand how certain immune-related genes contribute to the disease's development and progression.This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis(WGCNA)and machine learning. Methods:This study downloaded the gene chip data from the Gene Expression Omnibus(GEO)database,and used WGCNA to screen out important gene modules related to Parkinson's disease.Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease.Gene ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)were used to analyze the the functions of immune-related genes and signaling pathways involved.Immune cell infiltration analysis was performed using the CIBERSORT package of R language.Using bioinformatics method and 3 machine learning methods[least absolute shrinkage and selection operator(LASSO)regression,random forest(RF),and support vector machine(SVM)],the immune-related genes of Parkinson's disease were further screened.A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes(hub)gene.The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. Results:A total of 218 immune genes related to Parkinson's disease were identified,including 45 upregulated genes and 50 downregulated genes.Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways.The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells,NK cells,CD8+ T cells,and B cells were higher in the samples of Parkinson's disease patients,while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients.ANK1 was screened out as the hub gene.The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction,iron homeostasis regulation,and immune system activation. Conclusion:This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods,suggesting its potential as a candidate therapeutic target for Parkinson's disease.

Objective:To explore the relationships among workplace bullying,resilience and work perform-ance in nurses,employing a moderation and matching analysis perspective.Methods:A total of 3 026 nurses from 4 tertiary hospitals in Shandong Province were recruited.The Negative Acts Questionnaire Revised,Connor-Davidson Resilience Scale-10item,and Work Performance Scale were used to evaluate workplace bullying,psychological re-silience and work performance.Moderation analysis and response surface analysis were used to investigate the rela-tionships among workplace bullying,psychological resilience and work performance in nurses.Results:The results of the moderation effect analysis indicated that psychological resilience could moderate the negative relationship be-tween workplace bullying and work performance(β=0.07,95％CI:0.03-0.10).Response surface analysis re-vealed that compared to nurses with low bullying-low resilience,nurses with high bullying-high resilience showed higher work performance(Z-hat difference=2.06;95％CI=0.48-3.58).Nurses with high bullying-low resili-ence exhibited lower work performance compared to those with low bullying-high resilience(Z-hat difference=-8.31;95％CI=-12.06--5.68).Conclusion:Psychological resilience plays a moderating role in the negative effects of workplace bullying on job performance of nurses,and there are relative differences in work performance between individuals with different levels of workplace bullying and psychological resilience.