In the context of the modernization of traditional Chinese medicine （TCM）， the inheritance of the experiences of famous doctors faces significant challenges due to its complex nonlinear characteristics and dynamic evolution. There are still issues in the current inheritance system， such as the homogenization of talent cultivation models， lack of standardized mentoring practices， and monotonous evaluation method， which hinder the systematic inheritance and innovative development of famous doctors' experiences. Based on a systematic review of the current state of artificial intelligence （AI）-assisted inheritance of famous doctors' experiences， this study explores innovative pathways for deep integration of modern information technologies with famous doctors' experiences from key dimensions， including data authenticity assurance， interdisciplinary collaboration mechanisms， and the establishment of dynamic inheritance standards. It proposes a paradigm shift in the inheritance of TCM famous doctors' experiences in the AI era， aiming to build a new TCM inheritance system of "digital intelligence empowerment and cross-disciplinary innovation"， providing theoretical support and practical pathways for the inheritance of famous doctors' experiences in TCM.

Objective:We conducted a quality analysis and a survey of current situation of portable blood glucose meters from hospitals and patient sources in Zhejiang Province..Methods:The study is a retrospective cross-sectional study that included 252 portable blood glucose meters, of which 35 portable blood glucose meters (4 in provincial hospitals, 29 in municipal hospitals, and 2 in county-level hospitals) selected for the "Zhejiang Province Portable Blood Glucose Meter Flight Quality Control Inspection" project in April 2023, 126 portable blood glucose meters collected for the "Zhejiang Hospital Portable Blood Glucose Meter Whole Hospital Comparison" project in January 2024, and 91 portable blood glucose meters collected from patients in the "Zhejiang Hospital Home Portable Blood Glucose Meter Convenience Service" project from 2021 to 2023. By comparing the blood glucose results with the reference analyzer, evaluate the qualification rate of portable blood glucose meters between hospitals and patients, imported and domestic brands, and analyze the distribution of blood glucose concentration intervals for unqualified portable blood glucose meters. Conduct a survey questionnaire on the use of portable blood glucose meters by patients to analyze their trust in the results, quality control execution rate, comparison awareness rate, and comparison execution rate.Results:The overall qualification rate of portable blood glucose meters in hospitals (95.7%) was higher than that of portable blood glucose meters use by patients (70.3%), and the difference was statistically significant ( χ 2=31.94 , P<0.001). Among the unqualified blood glucose meters, the unqualified blood glucose concentration is mainly concentrated in the high concentration range (65.9%). Among imported brands, the qualification rate of blood glucose meters from hospitals(99.3%) is higher than that from patients(74.0%), and the difference is statistically significant ( χ 2=36.97, P<0.001). Meanwhile, 75% of patients fully trust the detection results of the blood glucose meter, but its instrument qualification rate is 69%. The awareness rate of patients regarding the comparison of portable blood glucose meters is 73%, but the execution rate of quality control and standard comparison of portable blood glucose meters by patients is 0. Conclusion:The quality of portable blood glucose meters in Zhejiang Province is uneven, with the highest pass rate for portable blood glucose meters from hospitals. Patients have weak awareness of quality control and comparison of portable blood glucose meters.

Objective:To identify the optimal machine learning model for predicting cholecystocardiac syndrome (CCS) in elderly patients and determine key predictive factors.Methods:A total of 150 elderly patients diagnosed as having CCS who presented with chest discomfort as the initial symptom were retrospectively included at Hangzhou First People's Hospital from July 2021 to December 2023, with 150 propensity score-matched controls (1∶1 matching for age, gender, smoking, and drinking history) with chest discomfort but without CCS during the same period. Demographic characteristics, vital signs at admission, laboratory test results, and electrocardiogram (ECG) findings of all patients were collected. The predictive performance of six machine learning models—gradient boosting, logistic regression, random forest (RF), k-nearest neighbor (KNN), multilayer perceptron (MLP), and support vector machine (SVM) for early CCS recognition was compared. The model with the best overall performance was selected according to area under the curve (AUC), and its key predictive factors were identified based on feature importance ranking.Results:Among the six machine learning models, the RF model demonstrated the highest AUC (0.84) and lowest Brier score (0.165) and was therefore identified as the optimal model. In the independent test set, the RF model achieved an AUC of 0.87 (95% CI: 0.735-0.908), with a sensitivity of 86.7% (39/45), specificity of 80.0% (36/45), positive predictive value of 81.3% (39/48) and negative predictive value of 85.7% (36/42). The six most important predictive variables were procalcitonin (PCT), serum amyloid A (SAA), heart rate variability low-frequency to high-frequency ratio (LF/HF), percentage of successive normal RR intervals differing by >50 ms (PMN50), γ-glutamyltransferase/aspartate aminotransferase ratio (GGT/AST), and direct bilirubin (DBIL). Conclusion:The RF model can predict early risk of CCS in elderly patients, with the key predictive factors including PCT, SAA, LF/HF, PMN50, GGT/AST, and DBIL.

Objective: To analyze the trend in burden of rheumatoid arthritis (RA) in China from 1990 to 2021, so as to provide insights into reducing the RA burden in China. Methods: Data of Global Burden of Disease Study 2021 were collected, and the incidence, mortality and disability-adjusted life years (DALY) of RA in China from 1990 to 2021 were analyzed and compared with global and different Socio-demographic Index (SDI) regions. The trend in burden of RA was analyzed using average annual percent change (AAPC). Results: The crude incidence rates of RA in China increased from 10.87/105 in 1990 to 17.38/105 in 2021, the crude mortality rates increased from 0.41/105 to 0.72/105, and the crude DALY rates increased from 34.26/105 to 58.61/105, with the increases of 59.98%, 77.95% and 71.06%, respectively. From 1990 to 2021, the standardized incidence rates of RA in China showed an increasing trend (AAPC=0.545%, P<0.05), the standardized mortality rates showed a decreasing trend (AAPC=-0.783%, P<0.05), and the standardized DALY rates showed no significant trend (AAPC=-0.017%, P>0.05). In 2021, the standardized incidence rate, standardized mortality rate and standardized DALY rate of RA were higher in females than in males; from 1990 to 2021, the standardized DALY rates of RA showed a decreasing trend in females (AAPC=-0.200%, P<0.05) and an increasing trend in males (AAPC=0.316%, P<0.05). The crude incidence rates of RA first increased and then decreased with age in 2021, reaching the highest in the age group of 75-<80 years at 34.36/105. Both the crude mortality rates and the crude DALY rates increased with age, reaching the highest in the age group of 95 years and older at 26.72/105 and 285.67/105, respectively. The standardized incidence rates and standardized DALY rates of RA in China in 2021 were lower than those in high SDI regions, while the standardized mortality rate was lower than that in medium-low SDI regions. Conclusions The burden of RA in China from 1990 to 2021 showed an upward trend, and was at a high level compared to different SDI regions. Higher disease burden of RA was seen in females and the elderly.

Objective:We conducted a quality analysis and a survey of current situation of portable blood glucose meters from hospitals and patient sources in Zhejiang Province..Methods:The study is a retrospective cross-sectional study that included 252 portable blood glucose meters, of which 35 portable blood glucose meters (4 in provincial hospitals, 29 in municipal hospitals, and 2 in county-level hospitals) selected for the "Zhejiang Province Portable Blood Glucose Meter Flight Quality Control Inspection" project in April 2023, 126 portable blood glucose meters collected for the "Zhejiang Hospital Portable Blood Glucose Meter Whole Hospital Comparison" project in January 2024, and 91 portable blood glucose meters collected from patients in the "Zhejiang Hospital Home Portable Blood Glucose Meter Convenience Service" project from 2021 to 2023. By comparing the blood glucose results with the reference analyzer, evaluate the qualification rate of portable blood glucose meters between hospitals and patients, imported and domestic brands, and analyze the distribution of blood glucose concentration intervals for unqualified portable blood glucose meters. Conduct a survey questionnaire on the use of portable blood glucose meters by patients to analyze their trust in the results, quality control execution rate, comparison awareness rate, and comparison execution rate.Results:The overall qualification rate of portable blood glucose meters in hospitals (95.7%) was higher than that of portable blood glucose meters use by patients (70.3%), and the difference was statistically significant ( χ 2=31.94 , P<0.001). Among the unqualified blood glucose meters, the unqualified blood glucose concentration is mainly concentrated in the high concentration range (65.9%). Among imported brands, the qualification rate of blood glucose meters from hospitals(99.3%) is higher than that from patients(74.0%), and the difference is statistically significant ( χ 2=36.97, P<0.001). Meanwhile, 75% of patients fully trust the detection results of the blood glucose meter, but its instrument qualification rate is 69%. The awareness rate of patients regarding the comparison of portable blood glucose meters is 73%, but the execution rate of quality control and standard comparison of portable blood glucose meters by patients is 0. Conclusion:The quality of portable blood glucose meters in Zhejiang Province is uneven, with the highest pass rate for portable blood glucose meters from hospitals. Patients have weak awareness of quality control and comparison of portable blood glucose meters.

Objective:To identify the optimal machine learning model for predicting cholecystocardiac syndrome (CCS) in elderly patients and determine key predictive factors.Methods:A total of 150 elderly patients diagnosed as having CCS who presented with chest discomfort as the initial symptom were retrospectively included at Hangzhou First People's Hospital from July 2021 to December 2023, with 150 propensity score-matched controls (1∶1 matching for age, gender, smoking, and drinking history) with chest discomfort but without CCS during the same period. Demographic characteristics, vital signs at admission, laboratory test results, and electrocardiogram (ECG) findings of all patients were collected. The predictive performance of six machine learning models—gradient boosting, logistic regression, random forest (RF), k-nearest neighbor (KNN), multilayer perceptron (MLP), and support vector machine (SVM) for early CCS recognition was compared. The model with the best overall performance was selected according to area under the curve (AUC), and its key predictive factors were identified based on feature importance ranking.Results:Among the six machine learning models, the RF model demonstrated the highest AUC (0.84) and lowest Brier score (0.165) and was therefore identified as the optimal model. In the independent test set, the RF model achieved an AUC of 0.87 (95% CI: 0.735-0.908), with a sensitivity of 86.7% (39/45), specificity of 80.0% (36/45), positive predictive value of 81.3% (39/48) and negative predictive value of 85.7% (36/42). The six most important predictive variables were procalcitonin (PCT), serum amyloid A (SAA), heart rate variability low-frequency to high-frequency ratio (LF/HF), percentage of successive normal RR intervals differing by >50 ms (PMN50), γ-glutamyltransferase/aspartate aminotransferase ratio (GGT/AST), and direct bilirubin (DBIL). Conclusion:The RF model can predict early risk of CCS in elderly patients, with the key predictive factors including PCT, SAA, LF/HF, PMN50, GGT/AST, and DBIL.

Objective To design a multisensory supported device and evaluate its effectiveness on preterm infants(born before 34 weeks)during NICU hospitalization.Methods The multisensory supported device is composed of a basement,several soft cushions and an adjustable eye mask.The inner layer of the device comprises of the head and tail boundaries,serves as uterine wall-like circular boundaries.The outer skeleton is equipped with multisensory stimulation modules to provide visual,hearing,and tactile sensory stimulations for premature infants.The study was conducted in a NICU of a tertiary A children specialist hospital in Shanghai,China.The convenience sampling method was used and based on the ratio of 1∶2 between the experimental and the control group in this study.The control group was treated by standard nursing care,while the experiment group was treated with the multisensory supported device in addition to NICU conventional care.All infants were assessed during the week of admission and again at corrected gestational age of 36 weeks.The actigraphy watch which was used for 72 hours continuous record of the activities of study infants,allows the researcher to compare the activity scores,wakefulness and sleep indicators of 2 groups of infants.Results 71 preterm infants were enrolled in the study,and 60 preterm infants completed data collection for study data analysis,including 20 in the experimental group and 40 in the control group.There were no statistical differences in demographic characteristics and clinical status regarding wakefulness,sleep and physical development between the 2 groups in baseline(P＞0.05).At 36 weeks of corrected gestational age,the activity score of the experimental group was(46.61±12.14)points,and that of the control group was(57.33±18.36)points,with statistically significant differences in 2 groups(P=0.024).The total waking time of the experimental group was(384.85±169.42)min,and that of the control group was(492.08±220.45)min,with statistically significant differences in 2 groups(P=0.049).There was no statistical difference in other indicators between 2 groups(P＞0.05).Conclusion The multisensory supported device can reduce high-frequency unpleasant activity as well as frequent wakefulness status,which could promote the sleeping quality of preterm infants.Further studies are needed to verify further effects of the device on premature infants'physical development.

Ying and wei qi is derived from the essence of water and grain， and is the basic material to maintain the normal life activities of the body. Ying and wei qi has the difference of nature of yin and yang or the clear and the turbid. When the relationship between ying and wei qi is out of order and in reverse disorder， it will lead to the occurrence of various diseases. Based on the analysis of the theory of "ying-wei disorder" in The Inner Canon of Yellow Emperor （《黄帝内经》）， this paper started from the perspective of the exuberance and debilitation， circulation and function of ying qi and wei qi， focused on the theoretical understanding that the change of deficiency and excess （"fall"） and the change of circulation （"move"）， and refined the core mechanism of "ying-wei disorder"， which is the depletion of ying qi and wei qi， stagnation of ying qi and wei qi， and disharmony of ying qi and wei qi， and finally summarized the syndrome identification and treatment method of supporting ying qi and assisting wei qi， promoting ying qi and moving wei qi， regulating ying qi and wei qi， and constructed the syndrome identification and treatment system for ying-wei disorder of malignant tumor in clinic.

Objective:To explore the normal ranges of perfusion parameters between cerebral hemisphere, cerebellar hemisphere and brain anatomical subregions (56 pairs) in different gender and age groups with multiple post labeling delay time (Multi-PLD) arterial spin labeling (ASL) imaging.Methods:From November 2020 to December 2020, 42 healthy adult volunteers (Male 25, Female 17) were recruited to perform 7 PLD ASL imaging, including 21 young adults (15 males and 6 females, aged 23—35 years) and 21 seniors (10 males and 11 females, aged 36—74 years). The data was processed offline by Cereflow software to obtain arterial arrival time (ATT) and corrected cerebral blood flow (CBF) and cerebral blood volume (CBV) perfusion parameters. SimpleITK standardization function was used to standardize the calculated perfusion image according to the anatomical automatic labeling (AAL) template. Therefore, CBF, ATT, CBV perfusion values of brain subregions were obtained. Paired samples t test, Wilcoxon rank sum test, independent samples t test and Mann-Whitney U test were used to compare the differences of perfusion parameters in the cerebral hemisphere, the cerebellar hemisphere, brain subregions depending on side, gender and age. Pearson correlation analysis was used to compare the correlations of perfusion parameters with age. Results:CBF in 62.5% (35/56) subregions and CBV in 44.6% (25/56) subregions were higher in right side than those in left side. ATT in most brain anatomical subregions (16/56) were higher in left side. The CBF [(35.30±8.31) vs. (34.34±7.53) ml·100g -1·min -1, P=0.021], CBV [(0.47±0.11) vs. (0.45±0.09) ml/100g, P<0.001], ATT [(1.30±0.10) vs. (1.24±0.11) s, P<0.001] in left cerebellar hemisphere were higher than that of right side. The CBF (28/56) of cerebral hemisphere, cerebellar hemisphere and brain subregions was higher in females than that in males, while ATT in 83.9% (47/56) subregions was lower than that in males (all P<0.05). CBV in female subjects was higher only in 5 brain regions (superior occipital gyrus, middle occipital gyrus, inferior occipital gyrus, superior parietal gyrus and cerebelum_7b) (all P<0.05). In young subjects, CBF in 44.6% (25/56) subregions and CBV in 33.9% (19/56) subregions were higher than those in the senior group (all P<0.05). The ATT in most subregions in young group were lower than those in senior group, but the difference was statistically significant only in rectus gyrus ( P=0.026) and paracentral lobule ( P=0.006). The CBF ( r=-0.430, P=0.005) and CBV ( r=-0.327, P=0.035) of cerebral hemisphere were negatively correlated with age. The CBF (24/25, r range:-0.497 —-0.343, all P<0.05) and CBV (16/19, r range:-0.474 —-0.322, all P<0.05) in most subregions were negatively correlated with age, while ATT was positively correlated (gyrus rectus: r=0.311, P=0.045; paracentral lobule: r=0.392, P=0.010). Conclusions:Multi-PLD ASL imaging could be applied for quantitative analysis of brain perfusion. The perfusion parameters of anatomical subregions are different depending on side, gender, and age.