Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

Objective:To investigate the rates of low disease activity and clinical remission in patients with systemic lupus erythematosus(SLE)in a real-world setting,and to analyze the related factors of low disease activity and clinical remission.Methods:One thousand patients with SLE were enrolled from 11 teaching hospitals.Demographic,clinical and laboratory data,as well as treatment regimes were collec-ted by self-completed questionnaire.The rates of low disease activity and remission were calculated based on the lupus low disease activity state(LLDAS)and definitions of remission in SLE(DORIS).Charac-teristics of patients with LLDAS and DORIS were analyzed.Multivariate Logistic regression analysis was used to evaluate the related factors of LLDAS and DORIS remission.Results:20.7％of patients met the criteria of LLDAS,while 10.4％of patients achieved remission defined by DORIS.Patients who met LLDAS or DORIS remission had significantly higher proportion of patients with high income and longer disease duration,compared with non-remission group.Moreover,the rates of anemia,creatinine eleva-tion,increased erythrocyte sedimentation rate(ESR)and hypoalbuminemia was significantly lower in the LLDAS or DORIS group than in the non-remission group.Patients who received hydroxychloroquine for more than 12 months or immunosuppressant therapy for no less than 6 months earned higher rates of LLDAS and DORIS remission.The results of Logistic regression analysis showed that increased ESR,positive anti-dsDNA antibodies,low level of complement(C3 and C4),proteinuria,low household in-come were negatively related with LLDAS and DORIS remission.However,hydroxychloroquine usage for longer than 12 months were positively related with LLDAS and DORIS remission.Conclusion:LLDAS and DORIS remission of SLE patients remain to be improved.Treatment-to-target strategy and standar-dized application of hydroxychloroquine and immunosuppressants in SLE are recommended.

Objective:To investigate the mechanism of extract of ginkgo biloba (EGB) on mitochondrial autophagy in breast cancer cells MCF-7.Methods:Breast cancer MCF-7 cells were divided into four groups. EGB with mass concentrations of 40, 80, 120 mg/L was used to incubate breast cancer MCF-7 cells for 24 h or 48 h, as a low concentration group of EGB, a medium concentration group of EGB, and a high concentration group of EGB. Breast cancer MCF-7 cells without intervention were taken as control group. Cell proliferation was measured using MTT assay; Flow cytometry was used to detect cell apoptosis; Immunofluorescence assay was used to determine the contents of prostacyclin (P62), microtubule-associated protein light chain 3Ⅱ (LC3Ⅱ), and caspase-3; The levels of multidrug resistance-associated protein 1 (MRP1), multidrug resistance gene 1 (MDR1) and breast cancer resistance protein (BCRP) were identified by PCR; Western blotting was used to detect the expression of extracellular signal-regulated kinase (ERK), mitogen-activated protein kinase (MAPK), p-ERK, and p-MAPK proteins in cells.Results:The results of MTT assay for cell proliferation showed that cell proliferation at 24 h in control group, EGB low, medium and high concentration groups were 0.95±0.14, 0.65±0.09, 0.51±0.07, 0.37±0.04, respectively, with a statistically significant difference ( F=43.13, P<0.001), cell proliferation at 48 h were 1.32±0.19, 0.54±0.08, 0.32±0.05, 0.15±0.02, respectively, with a statistically significant difference ( F=141.30, P<0.001). Compared with 24 h, cell proliferation was decreased in EGB low, medium and high concentration groups at 48 h (all P<0.05). Pairwise comparison showed that EGB treatment significantly decreased MCF-7 cell viability and cell proliferation was decreased in turn at 24 and 48 h in control group, low, medium, high EGB groups (all P<0.05). Flow cytometry analysis revealed that the apoptosis rates of MCF-7 cells in control group, EGB low, medium and high concentration groups were 2.12%±0.23%, 9.28%±0.45%, 15.17%±1.28% and 22.21%±2.32%, respectively, with a statistically significant difference ( F=128.80, P<0.001). Pairwise comparison showed that the apoptosis rate of control group, EGB low, medium and high concentration groups were increased in turn (all P<0.05). The results of immunofluorescence assay showed that the protein relative expression levels of P62 protein in MCF-7 cells of control group, EGB low, medium and high concentration groups were 3.34±0.52, 2.85±0.47, 2.02±0.18 and 1.08±0.21, respectively, with a statistically significant difference ( F=41.55, P<0.001). LC3Ⅱ protein relative expression levels were 0.24±0.05, 1.02±0.14, 1.47±0.26, 1.95±0.21, respectively, with a statistically significant difference ( F=94.82, P<0.001). The relative expression levels of caspase-3 protein were 0.25±0.03, 0.68±0.21, 1.12±0.17 and 1.65±0.23, respectively, with a statistically significant difference ( F=68.09, P<0.001). Pairwise comparison showed that LC3Ⅱ and caspase-3 protein expression levels were increased in turn in control group, EGB low, medium and high concentration groups, while P62 protein expression levels were decreased in turn (all P<0.05). The PCR experiment results showed that the MRP1 mRNA level of MCF-7 cells in control group, EGB low, medium and high concentration groups were 1.06±0.14, 0.83±0.18, 0.71±0.11, 0.52±0.08, respectively, with a statistically significant difference ( F=17.41, P<0.001). The mRNA levels of MDR1 were 1.14±0.17, 0.75±0.13, 0.60±0.09, 0.48±0.06, respectively, with a statistically significant difference ( F=34.40, P<0.001). BCRP mRNA levels were 1.09±0.11, 0.88±0.13, 0.69±0.07, 0.57±0.05, respectively, with a statistically significant difference ( F=34.13, P<0.001). Pairwise comparison showed that the levels of MRP1, MDR1 and BCRP mRNA were decreased in turn in control group, EGB low, medium and high concentration groups (all P<0.05). The results of Western blotting showed that the expression of ERK in MCF-7 cells in control group, EGB low, medium and high concentration groups were 2.54±0.38, 1.89±0.25, 1.55±0.21, 1.12±0.16, respectively, with a statistically significant difference ( F=31.18, P<0.001). MAPK expression were 2.47±0.34, 1.96±0.29, 1.63±0.27, 1.20±0.24, respectively, with a statistically significant difference ( F=20.90, P<0.001). p-ERK expression were 2.03±0.29, 1.74±0.21, 1.45±0.11, 1.18±0.24, respectively, with a statistically significant difference ( F=16.31, P<0.001). p-MAPK expression were 2.26±0.47, 1.90±0.41, 1.61±0.33, 1.35±0.16, respectively, with a statistically significant difference ( F=7.01, P=0.002). Pairwise comparison showed that the expressions of ERK, MAPK, p-ERK and p-MAPK in control group, EGB low, medium and high concentration groups were decreased in turn (all P<0.05) . Conclusion:EGB can inhibit the proliferation of breast cancer MCF-7 cells, promote the apoptosis of MCF-7 cells, decrease the expression of P62 protein, increase the expression of LC3Ⅱ and caspase-3 protein, induce mitochondrial autophagy.

Objective To evaluate the effectiveness of a hospital logistics operation and management based on the"one center,four platforms"model.Methods In line with the grading evaluation standards for hospital intelligent management,we used technologies such as big data,Internet of Things,Internet Plus,and artificial intelligence to develop a"one center,four platforms"model.This model consisted of a logistics intelligent operation and maintenance management center,an equipment control information platform,a security prevention information platform,an energy consumption monitoring information platform,and an operation management information platform.Results The equipment fault resolution capability,enhanced by the"smart linkage",showed a significant improvement.In 2022,false alarms decreased by 28.63%compared to 2021,with high-level and ordinary-level alarms decreasing by 69.53%and 33.15%,respectively.The"one-stop"logistics service capability was signifi-cantly improved,as indicated by a 2.92%decrease in maintenance frequency in 2022 compared to 2021.This improvement was further reflected in the quality of maintenance and a decrease in the repeated maintenance occurrences.The energy consumption control capability,based on the"data mining",showed a significant improvement,with an 8.71%year-on-year decrease in en-ergy expenditure of ten thousand yuan in 2022 compared to 2021.Conclusion The"one center,four platforms"model can sig-nificantly enhance the efficiency of logistics operation and maintenance management.

Objective To explore the correlations between serum Mas-related G protein-coupled receptor X2 (MRGPRX2), interleukin (IL)-4, IL-5, IL-6, IL-13, IL-23 and IL-33 levels and chronic spontaneous urticaria (CSU). Methods The clinical characteristics and laboratory data from 55 patients with CSU and 21 healthy controls at Huashan Hospital, Fudan University from February 2021 to September 2023 were collected. The disease activity and severity of CSU patients were assessed. Serum level of MRGPRX2 was tested using enzyme-linked immunosorbent assay (ELISA), and levels of IL-4, IL-5, IL-6, IL-13, IL-23, and IL-33 were measured using Luminex multiplex assay in all subjects. Spearman correlation analysis was used to evaluate the correlations between biomarkers and other parameters in CSU patients, and logistic regression analysis was performed to identify factors influencing CSU. Results CSU patients exhibited significantly higher serum levels of MRGPRX2 (2.41[0, 11.51] ng/mL vs 0[0, 2.86] ng/mL, P＝0.015) and IL-23 (0.09[0.04, 0.56] pg/mL vs 0.05[0.03, 0.08] pg/mL, P＝0.033) than healthy controls. There was no difference in levels of other cytokines between the two groups. There was no difference in levels of MRGPRX2 and cytokines between severe and non-severe CSU patients. Correlation analysis showed that serum MRGPRX2 levels in CSU patients were positively correlated with IL-4 (r＝0.345, P＝0.010) and IL-6 (r＝0.395, P＝0.003) levels. Logistic regression analysis indicated that MRGPRX2≥0.055 ng/mL and IL-23≥0.135 pg/mL were independent risk factors for CSU (P＜0.05). Conclusions Serum levels of MRGPRX2 and IL-23 in CSU patients are elevated, which may be involved in the pathogenesis of CSU.

In the all-media era,online public opinion events are causing more and more trouble to the healthcare industry,and public hospitals in this situation are facing a severe test in terms of online public opinion management,which is generally problematic.It introduces the hospital network public opinion governance strategies and methods based on hazard vulnerability analysis of Peking University People's Hospital and explores a practical and feasible hos-pital online public opinion management model from the aspects of public opinion risk identification,public opinion management system construction,and improvement of departmental management level,to enhance the level of hospital public opinion governance,with a view to reducing and avoiding negative impacts on the hospital caused by online public opinion events,building a harmonious doctor-patient relationship,and improving the work of medical services.The aim is to reduce and avoid the negative impact of online public opinion events on the hospital,to build a harmonious doctor-patient relationship and improve medical services.

【Objective】 To explore the application of machine learning in scientific and rational blood preparation and predictive analysis for surgical blood usage before liver transplantation surgery. 【Methods】 Clinical basic information including gender, age, clinical diagnosis and surgical methods of 356 liver transplantation patients were collected. The duration (Time) and preoperative laboratory test results of hemoglobin (Hb), hematocrit (Hct), platelet count (Plt), prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (Fib), total bilirubin (TBIL), albumin (ALB), creatinine (Crea) and total protein (TP), as well as the amount of intraoperative blood transfusion were collected. A machine learning model capable of predicting the risk of massive blood transfusion during liver transplantation surgery was established by Python, and was evaluated to select the optimal predictive model. 【Results】 Among the 7 machine learning models constructed, the logistic regression model performed the best (AUROC: 0.90, F1 score: 0.82), with an accuracy of 79.44% and precision of 79.69%, followed by the random forest classifier (AUROC: 0.87, F1 score: 0.83), with an accuracy of 79.44% and precision of 77.94%. 【Conclusion】 Establishing a machine learning prediction model by Python is of significant clinical importance for scientific blood preparation, predicting the risk of massive blood transfusion and ensuring the safety of blood use in liver transplantation surgery.

Background Bacteria are the most diverse and widely sourced microorganisms in the indoor air of subway stations, where pathogenic bacteria can spread through the air, leading to increased health risks. Objective To understand the status and distribution characteristics of indoor air bacterial pollution in subway stations and compartments in a city of Central South China, and to provide a scientific basis for formulating intervention measures to address indoor air bacteria pollution in subways. Methods Three subway stations and the compartments of trains parking there in a city in Central South China were selected according to passenger flow for synchronous air sampling and monitoring. Temperature, humidity, wind speed, carbon dioxide (CO₂), fine particulate matter (PM_2.5), and inhalable particulate matter (PM₁₀) were measured by direct reading method. In accordance with the requirements of Examination methods for public places-Part 3: Airborne microorganisms (GB/T 18204.3-2013), air samples were collected at a flow rate of 28.3 L·min⁻¹, and total bacterial count was estimated. Bacterial microbial species were identified with a mass spectrometer and pathogenic bacteria were distinguished from non-pathogenic bacteria according to the Catalogue of pathogenic microorganisms transmitted to human beings issued by National Health Commission. Kruskal-Wallis H test was used to compare the subway hygiene indicators in different regions and time periods, and Bonferroni test was used for pairwise comparison. Spearman correlation test was used to evaluate the correlation between CO₂ concentration and total bacterial count. Results The pass rates were 100.0% for airborne total bacteria count, PM_2.5, and PM₁₀ in the subway stations and train compartments, 94.4% for temperature and wind speed, 98.6% for CO₂, but 0% for humidity. The overall median (P₂₅, P₇₅) total bacteria count was 177 (138,262) CFU·m⁻³. Specifically, the total bacteria count was higher in station halls than in platforms, and higher during morning peak hours than during evening peak hours (P<0.05). A total of 874 strains and 82 species were identified by automatic microbial mass spectrometry. The results of identification were all over 9 points, and the predominant bacteria in the air were Micrococcus luteus (52.2%) and Staphylococcus hominis (9.8%). Three pathogens, Acinetobacter baumannii (0.3%), Corynebacterium striatum (0.1%), and Staphylococcus epidermidis bacilli (2.2%) were detected in 23 samples (2.6%), and the associated locations were mainly distributed in train compartments during evening rush hours. Conclusion The total bacteria count in indoor air varies by monitoring sites of subway stations and time periods, and there is a risk of opportunistic bacterial infection. Attention should be paid to cleaning and disinfection during peak passenger flow hours in all areas.

This paper summarized Professor PENG Peichu's experience in the differentiation and treatment of prostate cancer in three phases and four stages. It is considered that prostatic cancer is categorized into root deficiency and branch excess， with depletion of healthy qi as the root， and the accumulation of cancer toxin as the minifestation. Clinical diagnosis and treatment of prostatic cancer can be divided into three phases and four stages according to the exuberance and decline of pathogenic and healthy qi and the changes of deficiency and excess of yin and yang. In the initial accumulation phase of cancer toxin （yang excess stage）， the key pathogenesis is the accumulation of dampness， heat and static blood， and internal generation of cancer toxin， and the treatment should be resolving toxins， fighting cancer and dispelling yang excess. In the phase of healthy qi deficiency and toxin accumulation （yin deficiency stage）， with the lung and kidney yin deficiency， dampness， heat and static toxin accumulation as the key pathogenesis， the treatment should be centered on mutual generation between metal and water to nourish kidney yin， supplemented with the method of clearing heat and draining dampness， activating blood and resolving toxins， for which self-made Nanbei Formula（南北方）is usually used. In the phase of yang deficiency and cold stagnation （yang deficiency stage and yin excess stage）， with the spleen and kidney yang deficiency， cold dampness stagnation， static heat and toxin accumulation as the key pathogenesis， the treatment should be warming and tonifying spleen and kidney to dissipate cold accumulation； for deficiency of both yin and yang， and excess pathogen obstruction， modified Yanghe Decoction（阳和汤） is recommended， while for yang deficiency， cold congealing and blood stasis， self-made Wenshen Sanjie Formula（温肾散结方） can be used， and for cold dampness binding with cancer toxin， and cold complex with heat， self-made Quanan Formula （泉安方） is advised.

In the all-media era,online public opinion events are causing more and more trouble to the healthcare industry,and public hospitals in this situation are facing a severe test in terms of online public opinion management,which is generally problematic.It introduces the hospital network public opinion governance strategies and methods based on hazard vulnerability analysis of Peking University People's Hospital and explores a practical and feasible hos-pital online public opinion management model from the aspects of public opinion risk identification,public opinion management system construction,and improvement of departmental management level,to enhance the level of hospital public opinion governance,with a view to reducing and avoiding negative impacts on the hospital caused by online public opinion events,building a harmonious doctor-patient relationship,and improving the work of medical services.The aim is to reduce and avoid the negative impact of online public opinion events on the hospital,to build a harmonious doctor-patient relationship and improve medical services.