Given the lack of annotations for key lung organs and tissues in existing public datasets,this study collected 863 cases of chest CT scan images and constructed the first comprehensive dataset containing annotations of pulmonary vessels,airways,and nodules using a semi-automated method that combines computer vision algorithms with manual corrections by radiologists.On this basis,a lung nodule segmentation model based on multi-task learning is proposed.By incorporating annotations of pulmonary vessels(pulmonary arteries and veins)and the trachea to enhance model's ability to learn lung features,the proposed model reduces the false discovery rate in lung nodule detection,and improves generalization ability.Additionally,the use of larger image patches further optimizes model performance.The trained VAAN_128 model achieves the best performance,with a Dice coefficient of 0.694 and a false discovery rate of 0.210 for lung nodule segmentation.Moreover,it simultaneously provides accurate segmentation results of pulmonary vessels and the trachea,assisting in the formulation of more precise diagnosis and treatment plans.Based on the VAAN_128 model,a software system for navigation and localization in biopsy procedures is developed.In clinical practice,this system can assist physicians in accurately locating lung nodules,distinguishing critical tissues,and improving preoperative planning efficiency.This provides precise and efficient technical support for early diagnosis and disease monitoring of lung diseases,and is of great significance for path planning in clinical navigation system and future lung imaging research.

Objective To observe the value of artificial intelligence ultrasound combined with serum hyaluronic acid synthase 2(HAS2)and trefoil factor-1(TFF1)for early diagnosis of breast cancer.Methods Totally 176 patients with suspected breast cancer were retrospective enrolled and divided into malignant group(n=50)and benign group(n=126)according to pathological results.Artificial intelligence ultrasound and convolutional neural network algorithms were used to automatically label suspicious breast lesions.The lesions were manually graded based on breast imaging reports and data systems,classifying 0-3 grades as benign lesions,4-5 grades as malignant lesions.Clinical data and artificial intelligence ultrasound manifestations were compared between groups.Receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy of HAS2,TFF1,artificial intelligence ultrasound and their combination for diagnosing breast cancer.Results HAS2,TFF1,as well as the proportions of abnormal glandular thickness,low-echo lesions and abnormal blood flow morphology in malignant group were all higher than those in benign group(all P＜0.001).AUC of serum HAS2,TFF1 and artificial intelligence ultrasound for diagnosing breast cancer was 0.772,0.754 and 0.859,respectively.The combined diagnostic efficacy of the above three(AUC=0.925)was higher than single diagnostic efficacy(all P＜0.05).Conclusion Artificial intelligence ultrasound combined with serum HAS2 and TFF1 had good efficacy for early diagnosis of breast cancer.

Objective To observe the value of artificial intelligence ultrasound combined with serum hyaluronic acid synthase 2(HAS2)and trefoil factor-1(TFF1)for early diagnosis of breast cancer.Methods Totally 176 patients with suspected breast cancer were retrospective enrolled and divided into malignant group(n=50)and benign group(n=126)according to pathological results.Artificial intelligence ultrasound and convolutional neural network algorithms were used to automatically label suspicious breast lesions.The lesions were manually graded based on breast imaging reports and data systems,classifying 0-3 grades as benign lesions,4-5 grades as malignant lesions.Clinical data and artificial intelligence ultrasound manifestations were compared between groups.Receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy of HAS2,TFF1,artificial intelligence ultrasound and their combination for diagnosing breast cancer.Results HAS2,TFF1,as well as the proportions of abnormal glandular thickness,low-echo lesions and abnormal blood flow morphology in malignant group were all higher than those in benign group(all P＜0.001).AUC of serum HAS2,TFF1 and artificial intelligence ultrasound for diagnosing breast cancer was 0.772,0.754 and 0.859,respectively.The combined diagnostic efficacy of the above three(AUC=0.925)was higher than single diagnostic efficacy(all P＜0.05).Conclusion Artificial intelligence ultrasound combined with serum HAS2 and TFF1 had good efficacy for early diagnosis of breast cancer.

Given the lack of annotations for key lung organs and tissues in existing public datasets,this study collected 863 cases of chest CT scan images and constructed the first comprehensive dataset containing annotations of pulmonary vessels,airways,and nodules using a semi-automated method that combines computer vision algorithms with manual corrections by radiologists.On this basis,a lung nodule segmentation model based on multi-task learning is proposed.By incorporating annotations of pulmonary vessels(pulmonary arteries and veins)and the trachea to enhance model's ability to learn lung features,the proposed model reduces the false discovery rate in lung nodule detection,and improves generalization ability.Additionally,the use of larger image patches further optimizes model performance.The trained VAAN_128 model achieves the best performance,with a Dice coefficient of 0.694 and a false discovery rate of 0.210 for lung nodule segmentation.Moreover,it simultaneously provides accurate segmentation results of pulmonary vessels and the trachea,assisting in the formulation of more precise diagnosis and treatment plans.Based on the VAAN_128 model,a software system for navigation and localization in biopsy procedures is developed.In clinical practice,this system can assist physicians in accurately locating lung nodules,distinguishing critical tissues,and improving preoperative planning efficiency.This provides precise and efficient technical support for early diagnosis and disease monitoring of lung diseases,and is of great significance for path planning in clinical navigation system and future lung imaging research.

This study aims to understand the biological characteristics of Streptococcus dysgalacti-ae of yak origin.Bacterial isolation and identification,drug susceptibility test,virulence gene test and pathogenicity test were carried out on milk samples of yaks from Naqu City to evaluate the bi-ological characteristics of the isolated strains.Meanwhile,molecular biological information such as virulence factors and drug resistance genes were analyzed by whole genome sequencing,and viru-lence genes were verified by PCR.The results showed that a strain of Streptococcus dysgalactiae was isolated from the milk of yak,and its colony morphology was pinpoint size,smooth edge and milky white.This strain is sensitive to many antibiotics(penicillin G,cephalosporin,ciprofloxacin,tetracycline,erythromycin,etc.).Virulence gene test results showed that the strain carries six key virulence genes(cyl,eno,scpB,bca,bac and napr),which may be closely related to its pathoge-nicity.In the pathogenicity test,the mice were listless and less active after infection,but no death occurred during the observation period.The pathological changes of spleen,kidney,liver and lung tissue were found,suggesting that the strain had certain pathogenic potential but not high lethali-ty.Whole genome sequencing data showed that the gene length of this strain was 4 079 280 bp,the GC content was 39.41％,3 964 coding genes were predicted,604 of which were annotated as viru-lence factors,and another 28 gene mutations may enhance its pathogenic ability.Through annota-tion of CARD database,two Pat A resistance genes and two lmrp resistance genes were found,re-vealing their potential resistance mechanism.Through whole genome sequencing technology and bioinformatics analysis method,this study revealed the genomic characteristics,drug resistance and pathogenicity mechanism of Streptococcus dysgalactiae of yak origin.The findings provide impor-tant scientific evidence for further exploration of the pathogenicity,drug resistance mechanisms,and molecular evolution of yak-derived Streptococcus agalactiae.

Purpose: Erectile dysfunction (ED) is a common male sexual dysfunction. Gut microbiota plays an important role in various diseases. To investigate the effects and mechanisms of intestinal flora dysregulation induced by high-fat diet (HFD) on erectile function. Materials and Methods: Male Sprague–Dawley rats aged 8 weeks were randomly divided into the normal diet (ND) and HFD groups. After 24 weeks, a measurement of erectile function was performed. We performed 16S rRNA sequencing of stool samples. Then, we established fecal microbiota transplantation (FMT) rat models by transplanting fecal microbiota from rats of ND group and HFD group to two new groups of rats respectively. After 24 weeks, erectile function of the rats was evaluated and 16S rRNA sequencing was performed, and serum samples were collected for the untargeted metabolomics detection. Results: The erectile function of rats and the species diversity of intestinal microbiota in the HFD group was significantly lower, and the characteristics of the intestinal microbiota community structure were also significantly different between the two groups. The erectile function of rats in the HFD-FMT group was significantly lower than that of rats in the ND-FMT group. The characteristics of the intestinal microbiota community structure were significantly different. In the HFD-FMT group, 27 metabolites were significantly different and they were mainly involved in the several inflammation-related pathways. Conclusions Intestinal microbiota disorders induced by HFD can damage the intestinal barrier of rats, change the serum metabolic profile, induce low-grade inflammation and apoptosis in the corpus cavernosum of the penis, and lead to ED.

Purpose: Erectile dysfunction (ED) is a common male sexual dysfunction. Gut microbiota plays an important role in various diseases. To investigate the effects and mechanisms of intestinal flora dysregulation induced by high-fat diet (HFD) on erectile function. Materials and Methods: Male Sprague–Dawley rats aged 8 weeks were randomly divided into the normal diet (ND) and HFD groups. After 24 weeks, a measurement of erectile function was performed. We performed 16S rRNA sequencing of stool samples. Then, we established fecal microbiota transplantation (FMT) rat models by transplanting fecal microbiota from rats of ND group and HFD group to two new groups of rats respectively. After 24 weeks, erectile function of the rats was evaluated and 16S rRNA sequencing was performed, and serum samples were collected for the untargeted metabolomics detection. Results: The erectile function of rats and the species diversity of intestinal microbiota in the HFD group was significantly lower, and the characteristics of the intestinal microbiota community structure were also significantly different between the two groups. The erectile function of rats in the HFD-FMT group was significantly lower than that of rats in the ND-FMT group. The characteristics of the intestinal microbiota community structure were significantly different. In the HFD-FMT group, 27 metabolites were significantly different and they were mainly involved in the several inflammation-related pathways. Conclusions Intestinal microbiota disorders induced by HFD can damage the intestinal barrier of rats, change the serum metabolic profile, induce low-grade inflammation and apoptosis in the corpus cavernosum of the penis, and lead to ED.

Purpose: Erectile dysfunction (ED) is a common male sexual dysfunction. Gut microbiota plays an important role in various diseases. To investigate the effects and mechanisms of intestinal flora dysregulation induced by high-fat diet (HFD) on erectile function. Materials and Methods: Male Sprague–Dawley rats aged 8 weeks were randomly divided into the normal diet (ND) and HFD groups. After 24 weeks, a measurement of erectile function was performed. We performed 16S rRNA sequencing of stool samples. Then, we established fecal microbiota transplantation (FMT) rat models by transplanting fecal microbiota from rats of ND group and HFD group to two new groups of rats respectively. After 24 weeks, erectile function of the rats was evaluated and 16S rRNA sequencing was performed, and serum samples were collected for the untargeted metabolomics detection. Results: The erectile function of rats and the species diversity of intestinal microbiota in the HFD group was significantly lower, and the characteristics of the intestinal microbiota community structure were also significantly different between the two groups. The erectile function of rats in the HFD-FMT group was significantly lower than that of rats in the ND-FMT group. The characteristics of the intestinal microbiota community structure were significantly different. In the HFD-FMT group, 27 metabolites were significantly different and they were mainly involved in the several inflammation-related pathways. Conclusions Intestinal microbiota disorders induced by HFD can damage the intestinal barrier of rats, change the serum metabolic profile, induce low-grade inflammation and apoptosis in the corpus cavernosum of the penis, and lead to ED.

Objective To explore the symptom clusters in renal transplant recipients and con-struct a concurrent symptom network to identify core symptoms.Methods A total of 343 patients with followed up after renal transplantation were selected as the study subjects.A general information questionnaire and the Chinese version of the Modified Transplant Symptom Occurrence and Symptom Distress Scale were employed to analyze the occurrence of symptoms in patients.In this study,only symptoms with an incidence rate greater than 20％and Spearman correlation coefficient greater than 0.40 between symptom severity and total score were retained.Exploratory factor analysis was used to extract symptom clusters with a factor loading of ≥0.45 as the criterion.The R language was utilized to construct symptom network,based on which core symptoms and bridge symptoms were identified.Results A total of 5 symptom clusters were extracted in this study:the neuro-gastrointestinal symp-tom cluster,the mood-related symptom cluster,the hormone-related symptom cluster,the energy de-ficiency symptom cluster and the vision-related symptom cluster.The core symptoms were anxiety(rs=1.75),mood swings(rs=1.50)and muscle weakness(rs=1.27).The top three symptoms in terms of bridge strength were muscle weakness(rb=0.87),lack of vitality(rb=0.66)and fa-tigue(rb=0.65).Conclusion Multiple symptoms are presented in patients after renal transplanta-tion.Based on the results of symptom network analysis,clinicians can strengthen the assessment of core symptoms and bridge symptoms to develop precise intervention strategies and improve the effectiveness of symptom management.

Purpose: Erectile dysfunction (ED) is a common male sexual dysfunction. Gut microbiota plays an important role in various diseases. To investigate the effects and mechanisms of intestinal flora dysregulation induced by high-fat diet (HFD) on erectile function. Materials and Methods: Male Sprague–Dawley rats aged 8 weeks were randomly divided into the normal diet (ND) and HFD groups. After 24 weeks, a measurement of erectile function was performed. We performed 16S rRNA sequencing of stool samples. Then, we established fecal microbiota transplantation (FMT) rat models by transplanting fecal microbiota from rats of ND group and HFD group to two new groups of rats respectively. After 24 weeks, erectile function of the rats was evaluated and 16S rRNA sequencing was performed, and serum samples were collected for the untargeted metabolomics detection. Results: The erectile function of rats and the species diversity of intestinal microbiota in the HFD group was significantly lower, and the characteristics of the intestinal microbiota community structure were also significantly different between the two groups. The erectile function of rats in the HFD-FMT group was significantly lower than that of rats in the ND-FMT group. The characteristics of the intestinal microbiota community structure were significantly different. In the HFD-FMT group, 27 metabolites were significantly different and they were mainly involved in the several inflammation-related pathways. Conclusions Intestinal microbiota disorders induced by HFD can damage the intestinal barrier of rats, change the serum metabolic profile, induce low-grade inflammation and apoptosis in the corpus cavernosum of the penis, and lead to ED.