Objective:To develop a deep learning-based system for real-time recognition and classification of portal hypertensive gastropathy (PHG) and evaluate its ability to assist junior endoscopists.Methods:A total of 2 848 gastroscopy images from 832 patients with liver cirrhosis were selected from Digestive Endoscopy Center databases of Renmin Hospital of Wuhan University, Wuhan Hospital of Traditional Chinese and Western Medicine, and the Second Hospital of Jingzhou from January 2015 to October 2023. This system referred to 3 endoscopic features of Baveno Ⅱ scoring system. Three models were developed respectively for gastric antral vascular ectasia (GAVE), mosaic-like pattern (MLP), and red marks (RM). The specific classification references were as follows: (1) GAVE model: 0 no, 1 yes; (2) MLP model: 0 no, 1 mild, 2 severe; (3) RM model: 0 no, 1 isolated, 2 fused. The classification results for endoscopic characteristics of PHG of 3 endoscopy experts were taken as the gold standard. The yolov8-m model was used for training. The training dataset, validation dataset, and test dataset were allocated at a ratio of 8∶1∶1. The test dataset was used to evaluate the performance of models and their auxiliary effects on endoscopists. The accuracy, recall, precision, specificity and Kappa coefficient were calculated. Results:The accuracy, recall, specificity of GAVE model were 96.0% (48/50), 87.5% (7/8) and 97.6% (41/42). There was no significant difference between its accuracy and the gold standard ( χ2=316.226, P=1.000). The precision of GAVE1 and GAVE0 were 87.5% (7/8) and 97.6% (41/42) respectively. The accuracy of MLP model was 84.1% (132/157), and there was no significant difference compared with the gold standard ( χ2=3.286, P=0.193). The precision and recall of MLP2 were 88.2% (15/17) and 75.0% (15/20). The precision and recall of MLP1 were 77.9% (60/77) and 88.2% (60/68). The precision and recall of MLP0 were 90.5% (57/63) and 82.6% (57/69). The accuracy of RM model was 87.9% (123/140), and there was no significant difference compared with the gold standard ( χ2=2.891, P=0.409). The precision and recall of RM2 were 94.7% (18/19) and 78.3% (18/23). The precision and recall of RM1 were 72.2% (26/36) and 81.3% (26/32). The precision and recall of RM0 were 92.9% (79/85) and 92.9% (79/85). The mean accuracy of the three junior endoscopists, with and without the assistance of the GAVE model, MLP model, and RM model, respectively increased from 95.3% to 99.3%, from 83.9% to 91.9%, and from 81.9% to 83.1%. The overall consistency analysis of the 3 junior endoscopists with the gold standard indicated that the consistency of the GAVE model before and after assistance was extremely strong (both an overall Kappa of 1.000); the consistency before assistance of the MLP model was moderate (with an overall Kappa of 0.601), which increased to extremely strong after assistance (with an overall Kappa of 0.964); and the consistency of the RM model before and after assistance was also relatively strong (with an overall Kappa of 0.792 before and 0.798 after). Conclusion:The deep learning system accurately identifies and classifies PHG features and significantly enhances diagnostic performance of junior endoscopists.

Objective:To develop a deep learning-based system for real-time recognition and classification of portal hypertensive gastropathy (PHG) and evaluate its ability to assist junior endoscopists.Methods:A total of 2 848 gastroscopy images from 832 patients with liver cirrhosis were selected from Digestive Endoscopy Center databases of Renmin Hospital of Wuhan University, Wuhan Hospital of Traditional Chinese and Western Medicine, and the Second Hospital of Jingzhou from January 2015 to October 2023. This system referred to 3 endoscopic features of Baveno Ⅱ scoring system. Three models were developed respectively for gastric antral vascular ectasia (GAVE), mosaic-like pattern (MLP), and red marks (RM). The specific classification references were as follows: (1) GAVE model: 0 no, 1 yes; (2) MLP model: 0 no, 1 mild, 2 severe; (3) RM model: 0 no, 1 isolated, 2 fused. The classification results for endoscopic characteristics of PHG of 3 endoscopy experts were taken as the gold standard. The yolov8-m model was used for training. The training dataset, validation dataset, and test dataset were allocated at a ratio of 8∶1∶1. The test dataset was used to evaluate the performance of models and their auxiliary effects on endoscopists. The accuracy, recall, precision, specificity and Kappa coefficient were calculated. Results:The accuracy, recall, specificity of GAVE model were 96.0% (48/50), 87.5% (7/8) and 97.6% (41/42). There was no significant difference between its accuracy and the gold standard ( χ2=316.226, P=1.000). The precision of GAVE1 and GAVE0 were 87.5% (7/8) and 97.6% (41/42) respectively. The accuracy of MLP model was 84.1% (132/157), and there was no significant difference compared with the gold standard ( χ2=3.286, P=0.193). The precision and recall of MLP2 were 88.2% (15/17) and 75.0% (15/20). The precision and recall of MLP1 were 77.9% (60/77) and 88.2% (60/68). The precision and recall of MLP0 were 90.5% (57/63) and 82.6% (57/69). The accuracy of RM model was 87.9% (123/140), and there was no significant difference compared with the gold standard ( χ2=2.891, P=0.409). The precision and recall of RM2 were 94.7% (18/19) and 78.3% (18/23). The precision and recall of RM1 were 72.2% (26/36) and 81.3% (26/32). The precision and recall of RM0 were 92.9% (79/85) and 92.9% (79/85). The mean accuracy of the three junior endoscopists, with and without the assistance of the GAVE model, MLP model, and RM model, respectively increased from 95.3% to 99.3%, from 83.9% to 91.9%, and from 81.9% to 83.1%. The overall consistency analysis of the 3 junior endoscopists with the gold standard indicated that the consistency of the GAVE model before and after assistance was extremely strong (both an overall Kappa of 1.000); the consistency before assistance of the MLP model was moderate (with an overall Kappa of 0.601), which increased to extremely strong after assistance (with an overall Kappa of 0.964); and the consistency of the RM model before and after assistance was also relatively strong (with an overall Kappa of 0.792 before and 0.798 after). Conclusion:The deep learning system accurately identifies and classifies PHG features and significantly enhances diagnostic performance of junior endoscopists.

With the performance improvement of the medical electronics and the progress of social development,the utilization rate of implantable medical electronic devices in China shows an increasing trend in recent years,and will maintain a growing trend in the future as population aging is accelerating.Even though implantable medical electronic devices have extremely low failure rates,the explicit clinical accidents caused by their reliability issues deserve sufficient attention in consideration of the large quantity of patients.Compared with other countries,there is lack of domestic researches on application risk of implantable medical electronic devices due to radiation therapy and diagnosis,which is reflected in not only the clinical research,but also the researches on the underlying physical damage mechanism and macro performance of the devices.Therefore,it is crucial and urgent to explore the application risk of implantable medical electronic devices caused by radiation therapy and diagnosis,which has high clinical and scientific significance.The study conducts a literature survey on the risks of medical electronic devices in the radiation environment generated by clinical treatment,summarizes the risks encountered in the aspects of total dose effect,electromagnetic compatibility and instantaneous effect,analyzes the above behaviors from the physical mechanism and perspective,and puts forward some meaningful suggestions for medical electronic engineering and clinical treatment.

With the performance improvement of the medical electronics and the progress of social development,the utilization rate of implantable medical electronic devices in China shows an increasing trend in recent years,and will maintain a growing trend in the future as population aging is accelerating.Even though implantable medical electronic devices have extremely low failure rates,the explicit clinical accidents caused by their reliability issues deserve sufficient attention in consideration of the large quantity of patients.Compared with other countries,there is lack of domestic researches on application risk of implantable medical electronic devices due to radiation therapy and diagnosis,which is reflected in not only the clinical research,but also the researches on the underlying physical damage mechanism and macro performance of the devices.Therefore,it is crucial and urgent to explore the application risk of implantable medical electronic devices caused by radiation therapy and diagnosis,which has high clinical and scientific significance.The study conducts a literature survey on the risks of medical electronic devices in the radiation environment generated by clinical treatment,summarizes the risks encountered in the aspects of total dose effect,electromagnetic compatibility and instantaneous effect,analyzes the above behaviors from the physical mechanism and perspective,and puts forward some meaningful suggestions for medical electronic engineering and clinical treatment.

Metabolic reprogramming, a newly recognized trait of tumor biology, is an intensively studied prospect for oncology medicines. For numerous tumors and cancer cell subpopulations, oxidative phosphorylation (OXPHOS) is essential for their biosynthetic and bioenergetic functions. Cancer cells with mutations in isocitrate dehydrogenase 1 (IDH1) exhibit differentiation arrest, epigenetic and transcriptional reprogramming, and sensitivity to mitochondrial OXPHOS inhibitors. In this study, we report that berberine, which is widely used in China to treat intestinal infections, acted solely at the mitochondrial electron transport chain (ETC) complex I, and that its association with IDH1 mutant inhibitor (IDH1^mi) AG-120 decreased mitochondrial activity and enhanced antileukemic effect in vitro andin vivo. Our study gives a scientific rationale for the therapy of IDH1 mutant acute myeloid leukemia (AML) patients using combinatory mitochondrial targeted medicines, particularly those who are resistant to or relapsing from IDH1^mi.
Humans ; Oxidative Phosphorylation ; Berberine ; Electron Transport ; Mitochondria ; Leukemia, Myeloid, Acute ; Isocitrate Dehydrogenase

Objective:A multi-center and large sample volume study was conducted on the verification and improvement of the early established criteria for intelligent routine urinalysis validation (including the microscopic review rules and manual validation rules, referred to as intelligent criteria for short), in order to improve the clinical application of this intelligent criteria.Methods:A total of 31 456 urine specimens were collected from the inpatients and outpatients in six hospitals in China, from March to September 2019. Firstly, 3105 specimens were analyzed for preliminary verification and improvement of the intelligent criteria based on the results of the microscopic examination and manual validation. Secondly, 28 351 specimens were used to verify the clinical application of the improved intelligent criteria. All samples were manually validated as reference.Results:The approval inconsistency rate of the manual validation rules in the original intelligent criteria was 8.59% (202/2 352), and the interception inconsistency rate was 8.84% (208/2 352). The false negative rate and the microscopic review rate of the microscopic review rules were similar to the previous results. Based on an in-depth analysis of big data and the discussions by senior technicians from eight hospitals, one microscopic review rules and four manual validation rules were added, meanwhile two manual validation rule was deleted. The manual validation standards were unified. Finally, the intelligent criteria was improved. Based on the improved intelligent criteria, for microscopic review rules, the false positive rate, false negative rate (misdiagnosis rate), and microscopic review rate did not change significantly, which were 14.72% (457/3 105), 4.06% (126/3 105), and 24.73% (768/3 105), respectively. The approval inconsistency rate and the interception inconsistency rate of manual validation rules were both reduced to 0; the total manual validation rate of the intelligent criteria was 50.89% (1 580/3 105), and the auto-validation rate was 49.11% (1 525/3 105). The large sample volume verification results were consistent with the preliminary verification results of the improved intelligent criteria.Conclusion:This multi-center and large sample volume study had shown that the improved intelligent criteria had better clinical performance.

Objective:To conduct periodic revalidation of the 15 items and 43 terms autoverification rules of blood analysis after 1 year of application, analyze the application suitability and make the rules improved.Methods:Track the results of 528 010 blood analysis samples of our hospital from August 1, 2019 to January 31, 2020, and analyze the pass rate and interception rate of autoverification; 600 specimens in total were selected randomly for microscope examination, including 300 specimens which touched autoverification rules (1 012 items of autoverification rules) and were intercepted by autoverification and 300 specimens which untouched autoverification rules and were released by autoverification. The abnormal characteristics and unacceptable Delta check of the specimens also need to be concerned at the same time.The false negative rate and false positive rate, true negative rate, true positive rate and pass correct rate of autoverification were verified and compared with the rate of the second phase verification when the autoverification rule was established. The false negative rate, false positive rate, true negative rate and true positive rate of the Delta check rule which 54 716 specimens touched were calculated and compared with the second phase verification rate when the autoverification rule was established.The results of microscopic examination were used as the gold standard for the calculation of the rates, and P<0.05 was considered as a significant difference. The false positive and true positive of 1 012 autoverification rules were analyzed item by item.The false positive and true positive of 108 specimens which touched blast cell autoverification rule were analyzed terms by terms. The mean TAT and median TAT of 528 010 specimens and 193 750 outpatient specimens were calculated respectively, and the report percentages of 528 010 samples that TAT<30, 30-60　and>60 min were calculated respectively. Analyze and evaluate the application suitability of autoverification rules to juge whether they meet the needs of doctors and laboratory. The design process and the rules and application process of autoverification were optimized and improved.Results:The autoverification pass rate was 63.06% (332 971/528 010), the interception rate was 36.94% (195 039/528 010). The false negative rate was 1.00% (1/600), the false positive rate was 12.67% (76/600), the true negative rate was 49% (294/600), the true positive rate was 37.33% (224/600), and the correct rate was 98% (294/300). The pass rate, true negative rate, true positive rate and correct rate of the periodic reverification group were higher than the second phase verification group, the false negative rate and false positive rate were lower than that the second phase verification group. The false negative rate and true positive rate of the Delta check of periodic verification group were lower than that the second phase verification group, the false positive rate and true negative rate were higher than the second phase verification group, there were significant differences in the comparition results. The mean TAT of 528 010 specimens was25 min, and the median TAT was 22 min. The mean TAT of 193 750 outpatient specimens was 23 min, and the median TAT was 20 min. The report percentages of 528 010 samples that TAT<30 min, 30 min-60 min and>60 min were 83.30% (439 819/528 010), 8.00% (42 250/528 010) and 8.70% (45 941/528 010), respectively.Conclusion:The results of periodic revalidation of autoverification after 1 years application show that the 15 items and 43 terms autoverification rules of blood analysis could meet requirements about the accuracy and efficiency of the laboratory, and have a good suitability for application.

Objective To investigate PSP on bone microstructures,Ca,P,OPG and RANKL of osteoporotic rat model.Methods Thirty female rats randomly divided into five groups:Sham,OVX,H-,M-,L-PSP.Sham and OVX were irrigated stomachsaline;PSP solution was gavaged to other groups.After 8-week,bone microstructures of tibial metaphyseal,Ca,P,OPG and RANKL were measured.Results Body weight,Ca,P,RANKL,Tb.Sp of OVX were significantly increased compared to Sham,OPG,BV/TV,Tb.Th,Tb.N decreased.Body weight of H-,M-PSP,Ca and Tb.Sp of PSP,P and RANKL in H-PSP were decreased compared to OVX,OPG in H-,M-PSP,BV/TV,Tb.Th,Tb.N of PSP group increased.The differences were statistically significant (P ＜ 0.05).Conclusion PSP prevents osteoporosis by improving the microstructure of trabecular bone,reducing bone turnover,increasing OPG and reducing RANKL expression.

This study aimed to elucidate the effects of different soil water contents on the yield and quality of R.glutinosa.Different soil water contents were adjusted in different periods of growth of R.glutinosa.The yield,content of water extract,catalpol,verbascoside and polysaccharide were determined and analysed by the grey pattern recognition after harvests.The impacts of soil water content from the most important to the least important were medium moisture content (M2),high moisture content (M3),low moisture content (M1) and blank (M4).In the cultivation of R.glutinosa,the soil water content should be remained in the range of 40％-50％ at seedling stage,while 50％-60％ at the stage of root formation and tuber enlargement,and 20％-30％ during harvesting,which can significantly improve the yield and quality of R.glutinosa.

This article was aimed to study the correlation between iron content inCornus officinalis leaves and its yield as well as quality. The method of microwave digestion atomic absorption spectrophotometer was used to determine the content of iron element inCornus officinalis leaves. HPLC was used to determine the content of loganin and ursolic acid in fruits. Correlation analysis was made among the content of iron element, yield of fruits, loganin and ursolic acid in fruits. The results showed that iron element in leaves of different yield level cornus officinalis was different. It also had some correlation with yield and quality of fruits. It was concluded that the research can improve relations of source-sink inCornus ofifcinalis, adjust source-sink balance, guide farmers to master the period of spraying iron fertilizer, and increase production and quality ofCornus ofifcinalis.