OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Objective: To address systemic challenges in the blood system, such as supply-demand imbalance, inefficient allocation, and inappropriate clinical use, while bridging gaps in current theories regarding the integration of social mobilization, institutional practice, and policy coordination. It sought to construct a system dynamics model spanning from macro to micro levels to analyze the blood management system holistically. Methods: Key variables were identified by a systematic literature search in both Chinese and English databases. An improved Delphi method was then employed to conduct expert consultations across different fields, leading to the selection and determination of core variable sets for each sub-model. Furthermore, by defining their logical relationships, a system dynamics model was constructed to systematically analyze the operation mechanism of the blood management system. Results: Four core sub-models were developed: 1) A macro "Dynamic Balance" model quantifying regional supply-demand equilibrium and inventory control; 2) a mobilization "Three-Layer Funnel" model analyzing how socio-cultural factors, service channels, and policy incentives influence donation behavior; 3) an institutional "Dual-Cycle Regulation" model revealing hospital blood usage is driven by both disease burden (demand cycle) and management practices (regulation cycle); and 4) an individual "Three-Layer Filter" model standardizing clinical transfusion decisions based on necessity, risk-benefit, and context. These were integrated into a "Multi-Layer Linkage and Feedback" model, elucidating bidirectional interactions among five levels: policy environment, regional supply, blood station mobilization, hospital application, and clinical decision-making. Conclusion: This study constructed a system dynamics model for blood management. By defining key variables and their logical relationships, it systematically analyzes the system′s operational mechanism. The integrated framework connects multiple levels—regional supply, voluntary donation, hospital blood use, and clinical decision-making—revealing their intrinsic linkages. Future efforts should employ systems thinking to synergistically enhance supply-side mobilization, demand-side management, systemic regulation, and decision standardization to build a safe, efficient, and sustainable blood security system.

Objective: To evaluate the comprehensive intervention effect of lunch for primary and secondary school students in Minhang District, so as to provide a theoretical and practical basis for lunch intervention in school. Methods: From October to December 2023, a convenience sampling method was used to select 1 937 students from one primary and secondary school in Minhang District.A comprehensive intervention measure focusing on "reducing oil and salt" for lunch recipe optimization and nutrition education was carried out, and a questionnaire survey was conducted to evaluate the intervention effect three months later. Chi square test and Wilcoxon rank test were used to compare the data before and after the intervention. Results: After intervention, the use of cooking oil and salt, the supply of protein and fat in primary and secondary school lunches were reduced, and had no obvious impact on energy and other major nutrients. After intervention, compared to before intervention, the proportion of primary school students who felt that lunch was greasy decreased (8.9%, 6.2%, χ 2=4.35), and the proportion of primary and secondary school students who felt that lunch were delicious decreased significantly (33.2%, 23.2%; 63.9%, 53.5%, χ 2=26.39, 17.52) ( P < 0.05 ). Secondary school students also felt reduced variety of food ingredients (46.9%, 38.3%, χ 2=16.05, P <0.05). In addition, after intervention, the total surplus rate of primary school students meals decreased (7.4%, 4.4%, χ 2=5.73), mainly reflected in the decrease of the surplus rate of staple foods (7.1%, 2.4%, χ 2=17.39), while the surplus rate of vegetable dishes increased ( 16.0 %, 21.2%, χ 2=6.01) ( P <0.05). Although there was no significant change in the total surplus rate of meals for secondary school students, the surplus rate of staple foods decreased (12.9%, 5.4%, χ 2=33.52), while the surplus rates of meat and vegetable dishes increased (11.2%, 26.9%; 17.5%, 33.2%, χ 2=74.26, 61.88) ( P <0.05). After intervention, there was no statistically significant difference in the overweight and obesity rates of primary school students ( χ 2=0.11,0.43) and secondary school students ( χ 2=0.01,0.00) compared to before intervention( P >0.05). After intervention, the lung capacity of primary school students [1 564 (1 269,1 890) mL] and sitting forward flexion [11.3 (7.6, 15.2) cm] increased compared to before intervention [1 522 (1 259, 1 819 ) mL, 10.5 (6.3, 13.5) cm] ( Z =2.20, 4.68, P <0.01), but there was no statistically significant difference in lung capacity and sitting forward flexion of secondary school students before and after intervention ( Z =-0.46, -0.08, P >0.05). Conclusion The comprehensive intervention of school lunch has promoted a significant decrease in the use of oil and salt in lunch and improved the quality of recipes, and has a positive impact on the situation of leftover lunch and the health of students to a certain extent.

Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Objective: To investigate the objective characteristics of tongue manifestation in different stages of damp-heat syndrome in diabetic kidney disease (DKD). Methods: A cross-sectional study enrolled 134 patients with DKD G3-5 stages who met the diagnostic criteria for damp-heat syndrome in DKD. The patients were treated at Dongzhimen Hospital, Beijing University of Chinese Medicine, from May 2023 to January 2024. The patients were divided into three groups: DKD G3, DKD G4, and DKD G5 stage, with 53, 33, and 48 patients in each group, respectively. Clinical general data (gender, age, and body mass index) and damp-heat syndrome scores were collected from the patients. The YZAI-02 traditional Chinese medicine (TCM) AI Tongue Image Acquisition Device was used to capture tongue images from these patients. The accompanying AI Open Platform for TCM Tongue Diagnosis of the device was used to analyze and extract tongue manifestation features, including objective data on tongue color, tongue quality, coating color, and coating texture. Clinical data and objective tongue manifestation characteristics were compared among patients with DKD G3-5 based on their DKD damp-heat syndrome status. Results: No statistically significant difference in gender or body mass index was observed among the three patient groups. The DKD G3 stage group had the highest age (P<0.05). The DKD G3 stage group had a lower score for symptoms of poor appetite and anorexia(P<0.05) than the DKD G5 group. No statistically significant difference was observed in damp-heat syndrome scores among the three groups. Compared with the DKD G5 stage group, the DKD G3 stage group showed a decreased proportion of pale color at the tip and edges of the tongue (P<0.05). The DKD G4 stage group exhibited an increased proportion of crimson at the root of the tongue, a decreased proportion of thick white tongue coating at the root, a decreased proportion of pale color at the tip and edges of the tongue, an increased hue value (indicating color tone) of the tongue color in the middle, an increased brightness value (indicating color lightness) of the tongue coating color in the middle, and an increased thickness of the tongue coating (P<0.05). No statistically significant difference was observed in other tongue color proportions, color chroma values, body characteristics, coating color proportions, coating color chroma values, and coating texture characteristics among the three groups. Conclusion Tongue features differ in different stages of DKD damp-heat syndrome in multiple dimensions, enabling the inference that during the DKD G5 stage, the degree of qi and blood deficiency in the kidneys, heart, lungs, liver, gallbladder, spleen, and stomach is prominent. Dampness is more likely to accumulate in the lower jiao, particularly in the kidneys, whereas heat evil in the spleen and stomach is the most severe. These insights provide novel ideas for the clinical treatment of DKD.

Objective:To explore the risk factors for primary Sjogren′s syndrome-associated interstitial lung diseases (pSS-ILD) and to evaluate the diagnostic value of NLR and other predictors of pSS-ILD.Methods:A retrospective study of 63 patients with pSS-ILD and 201 patients with pSS visited our hospital from January 2016 to December 2023 was conducted. The general characteristics, clinical symptoms, laboratory indicators and treatment of the patients were collected. Correlation analyses were performed using the point bi-serial correlation test and Spearman′s Rho test, and binary logistic regression analysis was applied to explore the risk factors for the development of pSS-ILD. We assessed the value of diagnostic tools in relation to pSS-ILD by plotting receiver operating characteristic (ROC) curves.Results:①The proportion of males(14.29% vs. 4.48%, χ2=7.26, P=0.007), age at onset [(53±13)years old vs. (47±15)years old, t=2.55, P=0.011], neutrophil-to-lymphocyte ratio (NLR)[3.52(2.28, 6.49) vs. 1.64(1.23, 3.12), Z=-5.94, P<0.001], systemic immune-inflammatory index (SII) [653.34(328.08, 1 393.54) vs. 316.56(185.57, 593.65), Z=-5.26, P<0.001], C-reactive protein (CRP) [3.53(2.95, 9.76)mg/L vs. 2.82(1.67, 5.00)g/L, Z=-2.24, P=0.025], complement C3 [0.93(0.84, 1.02)g/L vs. 0.76(0.66, 0.85)g/L, Z=-5.33, P<0.001], and ESSDAI [4(3, 6) vs. 2(2, 4), Z=-5.70, P<0.001] levels were higher in the pSS-ILD than in non-ILD group, while the proportion of dry eyes (62.7%, χ2=13.37, P<0.001), proportion of anti-SSA/Ro60 antibody positivity (76.1%, χ2=8.77, P=0.012), rheumatoid factor (RF) positiveity [25.90(20.00, 83.30)U/ml, Z=-3.58, P<0.001], immunoglobulin G (IgG)[15.60(12.30, 21.90)g/L, Z=-3.28, P=0.001], immunoglobulin A (IgA)[3.21(2.32, 3.76)g/L, Z=-2.22, P=0.026], and immunoglobulin M (IgM)[1.29(0.93, 1.86)g/L, Z=-4.02, P<0.001) levels were higher in the non-ILD group. ②Correlation analysis showed that age at onset ( r=0.16, P<0.011), NLR ( r=0.43, P<0.001), SII ( r=0.41, P<0.001), and C3 ( r=0.27, P<0.001) were positively correlated with pSS-ILD, whereas IgG ( r=-0.18, P=0.005), IgM ( r=-0.19, P=0.002) were negatively correlated with pSS-ILD. Meanwhile, age at onset ( r=0.27, P<0.001), NLR ( r=0.30, P<0.001), and SII ( r=0.27, P<0.001) were positively correlated with ESSDAI score. ③Regression analysis showed that high levels of NLR[ OR(95% CI)=2.559(1.650, 3.969), P<0.001], C3[ OR(95% CI)=35.228(5.685, 218.309), P<0.001] might be risk factors for pSS-ILD. ④The area under the curve (AUC) for the diagnosis of pSS-ILD by NLR was 0.748, with a diagnostic sensitivity and specificity of 97.01% and 39.68%, respectively; the AUC for C3 was 0.727, with a diagnostic sensitivity and specificity of 66.67% and 79.03%, respectively; and the AUC for the joint predictive probability (Pre_1) of NLR and C3 was 0.812, with a sensitivity and specificity of 93.33% and 54.84%, respectively. Conclusion:High levels of NLR, C3 may be risk factors for pSS-ILD. NLR and C3 are adjunctive tools for the diagnosis of pSS-ILD, and the combination of the two increases the predictive value.

Type 2 diabetes mellitus (T2DM) is a highly prevalent chronic metabolic disease with an increasing incidence worldwide, that poses a significant risk to public health. In many current clinical practices for diabetes management, conventional Western treatments, including oral or injectable hypoglycemic agents, have serious side effects. Given that traditional Chinese medicine (TCM) is characterized by a multi-component, multi-target and multi-pathway approach, its combination with Western medicine could enhance efficacy and reduce adverse effects. Consequently, the use of TCM as a potential auxiliary or alternative treatment for the prevention and/or management of T2DM has emerged as a research hotspot. This article reviews existing reports on TCM in the treatment of T2DM and provides a detailed discussion of its applications. By integrating relevant clinical evidence, this review summarizes the clinical data on 23 TCM formulas and Chinese patent medicines, comprehensively describing their efficacy and potential pharmacological mechanisms in the treatment of T2DM. This includes an exploration of the impacts of TCM-based therapeutic interventions on T2DM-related microRNAs and their target genes. We hope this review not only offers new insights for future research directions but also enhances the understanding of the scientific value of TCM. Please cite this article as: Ni HX, Cao LH, Gong XX, Zang ZY, Chang H. Traditional Chinese medicine for treatment of type 2 diabetes mellitus: Clinical evidence and pharmacological mechanisms. J Integr Med. 2025; 23(6):605-622.
Humans ; Diabetes Mellitus, Type 2/drug therapy* ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/pharmacology* ; Hypoglycemic Agents/pharmacology*

OBJECTIVE: miR-34c-3p is down-regulated in nasopharyngeal carcinoma (NPC). The biological role of miR-34c-3p in NPC and its underlying mechanisms are unknown and were explored in this study. METHODS: Flow cytometry and immunohistochemical staining were employed to detect cluster of differentiation 86 (CD86) and cluster of differentiation 206 (CD206) expression; quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were employed to examine mRNA expression and protein levels; cell counting kit-8 (CCK8) and transwell assays were employed to assess cell proliferation, migration, and invasion; and hematoxylin-eosin (HE) staining was employed to assess pathological changes in tumor tissues. RESULTS: Our results revealed that the miR-34c-3p mimic markedly inhibited M2 polarization of macrophages by targeting SLC7A11, and M2 macrophages transfected with the miR-34c-3p mimic inhibited the proliferation, migration, and invasion of NPC cells. The in vivo experiments further confirmed that miR-34c-3p mimics blocked tumor growth and reduced inflammatory infiltration in tumor tissues. CONCLUSION This study provides novel insights into the pathogenesis of NPC and a new treatment strategy.
MicroRNAs/metabolism* ; Nasopharyngeal Carcinoma/genetics* ; Humans ; Animals ; Nasopharyngeal Neoplasms/genetics* ; Macrophages/physiology* ; Cell Line, Tumor ; Mice ; Cell Proliferation ; Mice, Inbred BALB C ; Cell Movement ; Male ; Gene Expression Regulation, Neoplastic ; Mice, Nude ; Female

Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.