BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some ...BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some unresolved challenges.AIM To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups.METHODS The proposed model represents a two-stage method that combined image classification with object detection.First,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid images.Then,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was marked.We constructed training and testing sets and compared model-assisted reading with physician reading.RESULTS The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single module.The sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’diagnoses.The image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.展开更多
Over-expression of glutathione S-transferase(GST)can promote Cisplatin resistance in hepatocellular carcinoma(HCC)treatment.Hence,inhibiting GST is an attractive strategy to improve Cisplatin sensitivity in HCC therap...Over-expression of glutathione S-transferase(GST)can promote Cisplatin resistance in hepatocellular carcinoma(HCC)treatment.Hence,inhibiting GST is an attractive strategy to improve Cisplatin sensitivity in HCC therapy.Although several synthesized GST inhibitors have been developed,the side effects and narrow spectrum for anticancer seriously limit their clinical application.Considering the abundance of natural compounds with anticancer activity,this study developed a rapid fluorescence technique to screen“green”natural GST inhibitors with high specificity.The fluorescence assay demonstrated that schisanlactone B(hereafter abbreviated as C1)isolated from Xue tong significantly down-regulated GST levels in Cisplatin-resistant HCC cells in vitro and in vivo.Importantly,C1 can selectively kill HCC cells from normal liver cells,effectively improving the therapeutic effect of Cisplatin on HCC mice by downregulating GST expression.Considering the high GST levels in HCC patients,this compound demonstrated the high potential for sensitizing HCC therapy in clinical practice by down-regulating GST levels.展开更多
[Objectives]To observe the clinical efficacy of Sanying capsule combined with Xiaoying Patch in treating thyroid nodule(TN).[Methods]Two groups were treated similarly,with 200 cases in the control group undergoing bas...[Objectives]To observe the clinical efficacy of Sanying capsule combined with Xiaoying Patch in treating thyroid nodule(TN).[Methods]Two groups were treated similarly,with 200 cases in the control group undergoing basic treatment for 12 weeks and 198 cases in the observation group receiving Sanying capsule combined with Xiaoying patches for the same duration.The clinical symptoms,number of nodules,diameter of the largest nodule,and maximum reduction of nodules were observed before and after treatment.A control analysis was performed,and the underlying mechanisms were explored.[Results]The primary symptoms of the observation group exhibited a more favorable improvement than those of the control group.Additionally,the number of nodules decreased,the diameter of the largest nodule decreased,and the maximum reduction of nodules decreased in both groups following treatment.However,the observation group demonstrated a more pronounced improvement than the control group(P<0.05).[Conclusions]The combination of Sanying capsule and Xiaoying patch has been demonstrated to be an effective treatment for TN,with a high degree of reliability in terms of safety.展开更多
Quinoa research aims to deeply understand its nutritional value,develop planting techniques,and explore food applications to promote quinoa industry development and improve human health.Future research directions incl...Quinoa research aims to deeply understand its nutritional value,develop planting techniques,and explore food applications to promote quinoa industry development and improve human health.Future research directions include further exploring nutritional functions,adaptive breeding,cultivation techniques and food processing of quinoa,so as to promote innovation and development in the quinoa industry.Expected outcomes include increased production,improved quality,expanded markets,diversified food sources,reduced environmental impact,and biodiversity protection.There are still challenges such as fluctuating market demand,resource constraints,insufficient nutritional knowledge,and fierce competition.Solutions may include education and publicity,diversified product lines,health certification and brand building,partnerships,new variety cultivation and sustainable farming,and resource sharing.Future research and practice will further promote innovation and development in the quinoa industry,making it one of the most important food and functional ingredients globally.展开更多
基金The Shanxi Provincial Administration of Traditional Chinese Medicine,No.2023ZYYDA2005.
文摘BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some unresolved challenges.AIM To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups.METHODS The proposed model represents a two-stage method that combined image classification with object detection.First,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid images.Then,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was marked.We constructed training and testing sets and compared model-assisted reading with physician reading.RESULTS The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single module.The sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’diagnoses.The image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.
基金supported by the National Natural Science Foundation of China(Grant Nos.:82003931,82204766 and 81374062)the Outstanding Youth Foundation of Hunan Provincial Education Department of China(Grant No.:20B445)+3 种基金the Hunan Youth Science and Technology Innovation Talents Project,China(Grant No.:2021RC3100)the Chinese Postdoctoral Science foundation(Grant No.:2021M690974)Changjiang Scholars Program in Ministry Education,People's Republic of China(Program No.:T2019133)the Scientific Research Project of Hunan Provincial Education Department(Project No.:21B0394).
文摘Over-expression of glutathione S-transferase(GST)can promote Cisplatin resistance in hepatocellular carcinoma(HCC)treatment.Hence,inhibiting GST is an attractive strategy to improve Cisplatin sensitivity in HCC therapy.Although several synthesized GST inhibitors have been developed,the side effects and narrow spectrum for anticancer seriously limit their clinical application.Considering the abundance of natural compounds with anticancer activity,this study developed a rapid fluorescence technique to screen“green”natural GST inhibitors with high specificity.The fluorescence assay demonstrated that schisanlactone B(hereafter abbreviated as C1)isolated from Xue tong significantly down-regulated GST levels in Cisplatin-resistant HCC cells in vitro and in vivo.Importantly,C1 can selectively kill HCC cells from normal liver cells,effectively improving the therapeutic effect of Cisplatin on HCC mice by downregulating GST expression.Considering the high GST levels in HCC patients,this compound demonstrated the high potential for sensitizing HCC therapy in clinical practice by down-regulating GST levels.
基金Supported by"Shaanxi Hu Xiaojuan Famous Chinese Medicine Workshop"Construction Project of Shaanxi Provincial Administration of Traditional Chinese Medicine"Thyroid Specialized Clinic"Construction Project of Shaanxi Provincial Hospital of Traditional Chinese Medicine.
文摘[Objectives]To observe the clinical efficacy of Sanying capsule combined with Xiaoying Patch in treating thyroid nodule(TN).[Methods]Two groups were treated similarly,with 200 cases in the control group undergoing basic treatment for 12 weeks and 198 cases in the observation group receiving Sanying capsule combined with Xiaoying patches for the same duration.The clinical symptoms,number of nodules,diameter of the largest nodule,and maximum reduction of nodules were observed before and after treatment.A control analysis was performed,and the underlying mechanisms were explored.[Results]The primary symptoms of the observation group exhibited a more favorable improvement than those of the control group.Additionally,the number of nodules decreased,the diameter of the largest nodule decreased,and the maximum reduction of nodules decreased in both groups following treatment.However,the observation group demonstrated a more pronounced improvement than the control group(P<0.05).[Conclusions]The combination of Sanying capsule and Xiaoying patch has been demonstrated to be an effective treatment for TN,with a high degree of reliability in terms of safety.
基金Supported by Beijing Science and Technology Program(Z201100008020006).
文摘Quinoa research aims to deeply understand its nutritional value,develop planting techniques,and explore food applications to promote quinoa industry development and improve human health.Future research directions include further exploring nutritional functions,adaptive breeding,cultivation techniques and food processing of quinoa,so as to promote innovation and development in the quinoa industry.Expected outcomes include increased production,improved quality,expanded markets,diversified food sources,reduced environmental impact,and biodiversity protection.There are still challenges such as fluctuating market demand,resource constraints,insufficient nutritional knowledge,and fierce competition.Solutions may include education and publicity,diversified product lines,health certification and brand building,partnerships,new variety cultivation and sustainable farming,and resource sharing.Future research and practice will further promote innovation and development in the quinoa industry,making it one of the most important food and functional ingredients globally.
