Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To provide a reference for the establishment, development and application of the adverse drug reaction （ADR） automated monitoring system, through verifying and quantifying the research hotspots and advantages of the system by CiteSpace software and systematic review. Methods Literature on ADR automated monitoring up to December 2023 were retrieved and screened from CNKI and web of science databases. CiteSpace 6.4.R1 software was used to conduct co-occurrence, clustering and emergence analysis, and to visualize and comparatively analyze the research hotspots, rules and distribution in the field of automated monitoring of ADR at home and abroad. In compliance with the preferred reporting items for systematic reviews and Meta-analyses （PRISMA）, literature covering publications in English and Chinese including detection rates of ADR collected using Incident Reporting Systems （IRSs） and/or automated monitoring systems were retrieved and screened. The advantages and disadvantages of automated monitoring systems were analyzed by comparing the differences between these two systems in terms of the number of ADR reports and the types of positive signals. Results A total of 56 articles in English and 80 articles in Chinese were indexed by CiteSpace. The research hotspots in recent years included data mining, deep learning, text classification techniques, machine learning and so on. A total of seven studies compiled with the inclusion criteria for the systematic evaluation, all of which were completed between 1991 and 2021 in hospitals in four countries. 150 526 medical records were reviewed from 15 institutions. A total of 194 ADR reports were collected by IRSs. A total of 2 090 ADR reports were collected by the automated monitoring system over the same period, indicating a 977% increase in the number of ADR reports （P=0.0156） compared with the IRSs. Conclusion The ADR automatic monitoring system had significantly improved the level of drug risk identification and reduced costs, but it was necessary to optimize the algorithm, expand the data source and carry out standardization construction to overcome the current limitations.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective: To investigate the characteristics of malignant tumor incidence and mortality in cancer registration areas of Zhejiang Province in 2021. Methods: Based on the 2021 cancer registration data from 22 national cancer registries in Zhejiang Province, the crude incidence, crude mortality, and cumulative rate for 0 to 74 years were calculated. Age standardized was performed using the age composition of the standard population from the Fifth National Population Census in 2000 and Segi's world standard population. The incidence and mortality characteristics of malignant tumor in different genders, urban/rural areas and ages were described. The order of crude incidence and mortality of malignant tumor were analyzed. Results: In 2021, there were 116 639 new malignant tumor cases in Zhejiang Province. The crude, Chinese population standardized, and world population-standardized incidences were 530.93/100 000, 304.83/100 000, and 288.20/100 000, respectively. The cumulative incidence for 0 to 74 years was 31.92%. There were 40 475 death cases. The crude, Chinese population-standardized, and world population-standardized mortalities were 184.24/100 000, 79.40/100 000, and 78.97/100 000, respectively. The cumulative mortality for 0 to 74 years was 8.37%. The Chinese population-standardized incidence for males and females were 286.34/100 000 and 323.45/100 000, respectively, and the Chinese population-standardized mortality were 106.25/100 000 and 54.17/100 000, respectively. The Chinese population-standardized incidence for urban and rural were 316.85/100 000 and 285.11/100 000, respectively, and the Chinese population-standardized mortality were 75.59/100 000 and 85.48/100 000, respectively. The crude incidence and crude mortality of malignant tumor both increased with age, peaking in the groups aged 80-<80 and ≥85 years at 1 845.06/100 000 and 1 656.88/100 000, respectively. The top ten malignant tumors with the highest crude incidence were, in descending order: lung cancer, thyroid cancer, breast cancer, prostate cancer, colorectal cancer, gastric cancer, liver cancer, cervical cancer, lymphoma, and brain tumors. These accounted for 80.34% of all new malignant tumor cases. The top ten malignant tumors with the highest crude mortality were, in descending order: lung cancer, liver cancer, colorectal cancer, gastric cancer, pancreatic cancer, prostate cancer, breast cancer, esophageal cancer, lymphoma, and gallbladder cancer. These accounted for 82.26% of all malignant tumor deaths. Conclusions In 2021, the cancer registration areas of Zhejiang Province were characterized by a relatively high malignant tumor incidence and a comparatively low mortality compared to national data. Males and the elderly emerged as key populations for targeted prevention and control. It is recommended to enhance screening, early diagnosis, and early treatment for lung cancer, thyroid cancer, prostate cancer, breast cancer, and gastric cancer malignancies.

Apurinic/apyrimidinic endonuclease 1(APE 1)is a multifunctional protein that plays important roles in DNA repair and regulation of gene expression.Because APE 1 is overexpressed in various cancers,it can serve as a cancer biomarker for aiding clinical diagnosis,guiding therapy,and monitoring prognosis.On this basis,a label-free fluorescent probe was designed based on the primer exchange reaction(PER)strategy for highly sensitive detection of APE 1 activity.In the absence of APE 1,the structure of catalytic hairpin(HP)was stable and could not form G-quadruplex.Therefore,the background fluorescence of this sensing system was very low due to the dissociation of thioflavin T(ThT).In the presence of APE 1,the apurinic/apyrimidinic(AP)site of HP was cleaved by APE 1 and a short nucleic acid fragment that acted as a primer to initiate PER was generated.After PER reaction,a large number of G-quadruplex were produced,which could specifically bind with ThT and resulted in significant increase of fluorescence signal.The combination of low background design of HP and PER amplification made this biosensor had high sensitivity with a detection limit(3σ)of 0.0008 U/mL.Furthermore,the primer sequence was directly generated by the cleavage of APE 1 without additional addition,which not only increased the specificity of the reaction,but also simplified the experiment procedure.Moreover,the use of label-free fluorescence signal reduced the cost of the experiment,and realized rapid detection of APE 1.Finally,this sensor was used to detect APE 1 in human serum samples with spiked recoveries of 91%-104%,proving great potential in study of biological enzyme.

Objective To explore the teaching effect of a"one-day"training model for basic application of periop-erative echocardiography for refresher anesthesiologists based on AR glasses and simulators.Methods The cardiac ultrasound teaching team of the Department of Anesthesiology at Peking Union Medical College Hospital designed a"one-day"teaching course for 60 trainees with no prior experience,based on AR glasses and simulators,covering basic applications of transthoracic echocardiography(TTE)and transesophageal echocardiography(TEE).We col-lected the scores of theoretical and practical assessments before and after the training and conducted a survey on trainee satisfaction and changes in clinical behavior post-training.Statistical analysis was performed using SPSS 23.0 software.Results The theoretical knowledge scores before and after the training were 52.35±12.33 and 81.20±22.78,respectively(P＜0.05);the practical assessment scores were 30.33±10.65 and 73.96±23.15,respectively(P＜0.05).Overall satisfaction rate was 96.66%(58/60).Conclusions The"one-day"teaching model for basic application of perioperative cardiac ultrasound based on AR glasses and simulators,as an introductory training model,can help beginners quickly master the core content at the entry level and lay a solid foundation for subsequent clinical application.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

OBJECTIVE: To investigate possible associations between physical function assessment scales, such as Short Physical Performance Battery (SPPB) and Berg Balance Scale (BBS), with all-cause mortality in acute decompensated heart failure (ADHF) patients. METHODS: A total of 108 ADHF patients were analyzed from October 2020 to October 2022, and followed up to May 2023. The association between baseline clinical characteristics and all-cause mortality was analyzed by univariate Cox regression analysis, while for SPPB and BBS, univariate Cox regression analysis was followed by receiver operating characteristic curves, in which the area under the curve represented their predictive accuracy for all-cause mortality. Incremental predictive values for both physical function assessments were measured by calculating net reclassification index and integrated discrimination improvement scores. Optimal cut-off value for BBS was then identified using restricted cubic spline plots, and survival differences below and above that cut-off were compared using Kaplan-Meier survival curves and the log-rank test. The clinical utility of BBS was measured using decision curve analysis. RESULTS: For baseline characteristics, age, female, blood urea nitrogen, as well as statins, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, or angiotensin receptor-neprilysin inhibitors, were predictive for all-cause mortality for ADHF patients. With respect to SPPB and BBS, higher scores were associated with lower all-cause mortality rates for both assessments; similar area under the curves were measured for both (0.774 for SPPB and 0.776 for BBS). Furthermore, BBS ≤ 36.5 was associated with significantly higher mortality, which was still applicable even adjusting for confounding factors; BBS was also found to have great clinical utility under decision curve analysis. CONCLUSIONS BBS or SPPB could be used as tools to assess physical function in ageing ADHF patients, as well as prognosticate on all-cause mortality. Moreover, prioritizing the improvement of balance capabilities of ADHF patients in cardiac rehabilitation regimens could aid in lowering mortality risk.

OBJECTIVE: To investigate the mechanism of electroacupuncture (EA) in treating diabetic gastroparesis (DGP) by inhibiting the activation of Nod-like receptor family pyrin domain-containing protein 3 (NLRP3) inflammasome and pyroptosis mediated via NLRP3/cysteinyl aspartate specific proteinase-1 (caspase-1)/gasdermin D (GSDMD) signaling pathway. METHODS: Forty Sprague-Dawley rats were randomly divided into 4 groups including the control, DGP model, EA, and MCC950 groups. The DGP model was established by a one-time high-dose intraperitoneal injection of 2% streptozotocin and a high-glucose and high-fat diet for 8 weeks. EA intervention was conducted at Zusanli (ST 36), Liangmen (ST 21) and Sanyinjiao (SP 6) with sparse-dense wave for 15 min, and was administered for 3 courses of 5 days. After intervention, the blood glucose, urine glucose, gastric emptying, and intestinal propulsive rate were observed. Besides, HE staining was used to observe histopathological changes in gastric antrum tissues, and TUNEL staining was utilized to detect DNA damage. Protein expression levels of NLRP3, apoptosis-associated speck-like protein containing CARD (ASC), pro-caspase-1, caspase-1 and GSDMD were measured by Western blot. Immunofluorescence staining was employed to assess the activity of GSDMD-N. Lactate dehydrogenase (LDH) levels were detected by using a biochemical kit. RESULTS: DGP rats showed persistent hyperglycemia and a significant decrease in gastrointestinal motility (P<0.05 or P<0.01), accompanied by pathological damage in their gastric antrum tissues. Cellular DNA was obviously damaged, and the expressions of NLRP3, ASC, pro-caspase-1, caspase-1 and GSDMD proteins were significantly elevated, along with enhanced fluorescence signals of GSDMD-N and increased LDH release (P<0.01). EA mitigated hyperglycemia, improved gastrointestinal motility in DGP rats and alleviated their pathological injury (P<0.05). Furthermore, EA reduced cellular DNA damage, lowered the protein levels of NLRP3, ASC, pro-caspase-1, caspase-1 and GSDMD, suppressed GSDMD-N activity, and decreased LDH release (P<0.05 or P<0.01), demonstrating effects comparable to MCC950. CONCLUSION EA promotes gastrointestinal motility and repairs the pathological damage in DGP rats, and its mechanism may be related to the inhibition of NLRP3 inflammasome and pyroptosis mediated by NLRP3/caspase-1/GSDMD pathway.
Animals ; Electroacupuncture ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Pyroptosis ; Rats, Sprague-Dawley ; Caspase 1/metabolism* ; Gastroparesis/physiopathology* ; Signal Transduction ; Male ; Diabetes Mellitus, Experimental/physiopathology* ; Phosphate-Binding Proteins/metabolism* ; Gastrointestinal Motility ; Rats ; Intracellular Signaling Peptides and Proteins/metabolism* ; Diabetes Complications/physiopathology* ; Gasdermins