ObjectiveTo investigate the mechanism by which Shaoyaotang regulates the miRNA-155-mediated suppressor of cytokine signaling 1 （SOCS1）/Janus kinase 1 （JAK1）/signal transducer and activator of transcription 1 （STAT1） signaling pathway and thereby affects macrophage polarization. MethodsThe cell-counting kit-8 （CCK-8） assay was used to detect the effect of drug-containing serum of Shaoyaotang at different concentrations on the viability of RAW 264.7 cells. A cell model of inflammation was established by stimulating RAW264.7 cells with lipopolysaccharide （LPS） at a concentration of 10 mg·L^-1 The modeled cells were assigned by the random number table method into seven groups： LPS-induced M1 polarization （model）， M1+miRNA-155 mimics， M1+miRNA-155 inhibitor， M1+Shaoyaotang-containing serum， M1+miRNA-155 mimics+Shaoyaotang-containing serum， M1+miRNA-155 inhibitor+Shaoyaotang-containing serum， and M1+blank serum. Enzyme-linked immunosorbent assay was employed to measure the levels of inflammatory factors ［tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and interleukin-1β （IL-1β）］. Immunofluorescence assay was used to detect the expression of macrophage polarization markers ［inducible nitric oxide synthase （iNOS） and macrophage mannose receptor 1 （CD206）］. Real-time PCR was employed to measure the expression of miRNA-155 in cells. Western blot was performed to determine the protein levels of SOCS1， STAT1， and JAK1. ResultsCompared with the LPS-induced M1 polarization （model） group， the M1+miRNA-155 mimics group showed up-regulated expression of miRNA-155， JAK1， STAT1， TNF-α， IL-6， IL-1β， and iNOS （P<0.05） and down-regulated expression of CD206 （P<0.05）. In both the M1+miRNA-155 inhibitor group and the M1+Shaoyaotang-containing serum group， the expression levels of miRNA-155， JAK1， STAT1， TNF-α， IL-6， IL-1β， and iNOS were down-regulated （P<0.05）， while those of SOCS1 and CD206 were up-regulated （P<0.05）. Compared with the M1+miRNA-155 mimics group， the M1+miRNA-155 mimics+Shaoyaotang-containing serum group showed down-regulated expression of miRNA-155， JAK1， STAT1， TNF-α， IL-6， IL-1β， and iNOS （P<0.05） and up-regulated expression of SOCS1 and CD206 （P<0.05）. Compared with the M1+miRNA-155 inhibitor group， the M1+miRNA-155 inhibitor+Shaoyaotang-containing serum group showed down-regulated expression of miRNA-155， JAK1， STAT1， TNF-α， IL-6， IL-1β， and iNOS （P<0.05） and up-regulated expression of SOCS1 and CD206 （P<0.05）. ConclusionShaoyaotang regulates macrophage polarization by modulating miRNA-155 expression and interfering with the SOCS1/JAK1/STAT1 signaling pathway. The findings provide new experimental evidence for the treatment of ulcerative colitis with Shaoyaotang.

ObjectiveTo investigate the potential role and underlying mechanisms of Shaoyaotang in intervening macrophage glycolytic reprogramming in ulcerative colitis （UC）. MethodsForty-eight C57BL/6 mice were randomly divided into six groups： Normal control group， model group， mesalazine group （0.39 g·kg^-1）， Shaoyaotang group （15.54 g·kg^-1）， 2-deoxy-D-glucose （2-DG） group （glycolysis inhibitor， 100 mg·kg^-1）， and 2-DG + Shaoyaotang combined group （100 mg·kg^-1+15.54 g·kg^-1）. Except for the normal control group， mice in the other five groups were induced to establish UC models using dextran sulfate sodium （DSS）. The normal control group was administered pure water via intragastric gavage， while the other groups received intragastric gavage of mesalazine solution， intragastric gavage of Shaoyaotang， and the 2-DG group was treated with 2-DG via intraperitoneal injection. After 7 consecutive days of treatment， colonic tissues were extracted. Hematoxylin and eosin （HE） staining was performed to evaluate histopathological changes and tissue injury in the colon. Enzyme-linked immunosorbent assay （ELISA） was used to detect the expression of interleukin-10 （IL-10） and tumor necrosis factor-α （TNF-α） in colonic tissues. Western blot analysis was employed to determine the expression levels of hypoxia-inducible factor-1α （HIF-1α）， glucose transporter （GLUT1）， lactate dehydrogenase A （LDHA）， pyruvate kinase M2 （PKM2）， and 6-phosphofructo-2-kinase/fructose-2，6-biphosphatase 3 （PFKFB3） in colonic tissues. Immunofluorescence was conducted to detect the expression of CD206 and inducible nitric oxide synthase （iNOS） in colonic tissues. Liquid chromatography-mass spectrometry （LC-MS） was utilized to measure lactate and citrate levels in colonic tissues. ResultsCompared with the normal control group， mice in the model group exhibited a significant increase in disease activity index （DAI） scores， accompanied by colonic mucosal congestion， edema， and inflammatory cell infiltration， significantly elevated expression of the inflammatory cytokine TNF-α （P<0.05）， significantly decreased IL-10 expression （P<0.05）， significantly increased levels of HIF-1α， GLUT1， LDHA， PKM2， and PFKFB3 in colonic tissues （P<0.05）， markedly elevated iNOS expression （P<0.05）， significantly decreased CD206 expression （P<0.05）， and significantly elevated lactate and citrate levels in colonic tissues （P<0.05）. In contrast to the model group， the Shaoyaotang group， inhibitor group， and Shaoyaotang combined with inhibitor group demonstrated amelioration of mucosal injury in colonic tissues， markely decreased expression levels of the inflammatory cytokine TNF-α （P<0.05）， elevated IL-10 expression levels， significantly decreased expression of HIF-1α， GLUT1， LDHA， PKM2， and PFKFB3 （P<0.05）， markedly reduced iNOS expression levels （P<0.05）， significantly increased CD206 expression （P<0.05） and significantly decreased lactate and citrate levels （P<0.05）. ConclusionShaoyaotang ameliorates symptoms of DSS-induced UC in mice， and its therapeutic mechanism may be associated with regulating macrophage glycolytic reprogramming via modulation of the HIF-1α signaling pathway.

ObjectiveTo investigate the role of microRNA-155-5p （miR-155-5p） in ulcerative colitis （UC） and study the molecular mechanism of Shaoyaotang in the treatment of UC by regulating miR-155-5p. MethodsForty-eight SPF-grade male C57BL/6 mice were selected and assigned via the random number table method into 6 groups （n=8）： A blank control group， a model group， a mesalazine （0.39 g·kg^-1） group， a Shaoyaotang （31.08 g·kg^-1） group， a Janus kinase 1 （JAK1） inhibitor （baricitinib， 10 mg·kg^-1） group， and a Shaoyaotang combined with inhibitor （baricitinib 10 mg·kg^-1 + Shaoyaotang 31.08 g·kg^-1） group. After successful modeling of UC by gavage of 3% dextran sulphate sodium solution， each group received corresponding drug intervention for 7 days. Shaoyaotang and mesalazine were administered by gavage， and baricitinib by intraperitoneal injection. Twenty-four hours after the last administration， mice were anesthetized by intraperitoneal injection of pentobarbital sodium， and blood was collected for determination of white blood cell count and erythrocyte sedimentation rate （ESR）. Mice were then sacrificed for measurement of colon length. Hematoxylin-eosin staining was used to observe colonic pathological changes and perform pathological scoring. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was employed to determine the relative expression of miR-155-5p in the colonic tissue， and Western blot was used to determine the protein levels of JAK1， phosphorylated JAK1 （p-JAK1）， suppressor of cytokine signaling 1 （SOCS1）， signal transducer and activator of transcription 1 （STAT1）， and phosphorylated STAT1 （p-STAT1）. ResultsCompared with the blank control group， the model group showed increased disease activity index （DAI） score and pathological score， shortened colon， upregulated relative expression of miR-155-5p and protein levels of p-JAK1 and p-STAT1， downregulated protein level of SOCS1 in the colonic tissue， prolonged time of erythrocyte sedimentation， and increased white blood cell count （P<0.01）. Compared with the model group， all drug-treated groups exhibited improvements in the above indicators （P<0.01）. Moreover， the Shaoyaotang group showed better therapeutic effects than the mesalazine group in regulating miR-155-5p expression， related protein levels， DAI score， and colonic pathological score （P<0.01）. ConclusionShaoyaotang may downregulate miR-155-5p to relieve its inhibition on SOCS1， thereby suppressing the excessive activation of the JAK1/STAT1 signaling pathway and ultimately alleviating intestinal inflammatory damage.

ObjectiveTo investigate the role of the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-κB （NF-κB） signaling pathway in intestinal mucosal barrier damage in ulcerative colitis， as well as the intervention mechanism of Shaoyaotang. MethodsSixty SD rats were allocated into a blank group， a model group， a mesalazine （0.42 g·kg^-1） group， and low-， medium-， and high-dose （11.1， 22.2， 44.4 g·kg^-1， respectively） Shaoyaotang groups. A model of ulcerative colitis was induced by 2，4，6-trinitrobenzenesulfonic acid （TNBS）. After successful modeling， rats were administrated with corresponding agents via gavage for 7 days. Changes in colon length and colon weight were observed. Hematoxylin-eosin staining was performed to examine the pathological changes of the colon， and immunohistochemistry was employed to detect the expression of the inflammatory cytokine interleukin-8 （IL-8）， cyclooxygenase-2 （COX-2）， junction adhesion molecule-1 （JAM-1）， and claudin-1 in the colon. Western blot analysis was performed to determine the protein levels of TLR4， MyD88， and NF-κB in the colon. ResultsCompared with the blank group， the model group showed elevated DAI score （P<0.01）， reduced colon length and colon weight （P<0.01）， down-regulated protein levels of JAM-1 and claudin-1 （P<0.01）， and up-regulated protein levels of IL-8， COX-2， TLR4， MyD88， and NF-κB p65 （P<0.01） in the colon tissue. Compared with the model group， each treatment group showed decreased DAI score （P<0.05， P<0.01）， increased colon length and colon weight （P<0.05， P<0.01）， up-regulated protein levels of JAM-1 and claudin-1 （P<0.01）， and down-regulated protein levels of IL-8， COX-2， TLR4， MyD88， and NF-κB p65 （P<0.01） in the colon tissue. ConclusionShaoyaotang alleviates intestinal inflammation and intestinal mucosal damage to protect intestinal barrier integrity by regulating the TLR4/MyD88/NF-κB signaling pathway.

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*

Protrusive facial deformities, characterized by the forward displacement of the teeth and/or jaws beyond the normal range, affect a considerable portion of the population. The manifestations and morphological mechanisms of protrusive facial deformities are complex and diverse, requiring orthodontists to possess a high level of theoretical knowledge and practical experience in the relevant orthodontic field. To further optimize the correction of protrusive facial deformities, this consensus proposes that the morphological mechanisms and diagnosis of protrusive facial deformities should be analyzed and judged from multiple dimensions and factors to accurately formulate treatment plans. It emphasizes the use of orthodontic strategies, including jaw growth modification, tooth extraction or non-extraction for anterior teeth retraction, and maxillofacial vertical control. These strategies aim to reduce anterior teeth and lip protrusion, increase chin prominence, harmonize nasolabial and chin-lip relationships, and improve the facial profile of patients with protrusive facial deformities. For severe skeletal protrusive facial deformities, orthodontic-orthognathic combined treatment may be suggested. This consensus summarizes the theoretical knowledge and clinical experience of numerous renowned oral experts nationwide, offering reference strategies for the correction of protrusive facial deformities.
Humans ; Orthodontics, Corrective/methods* ; Consensus ; Malocclusion/therapy* ; Patient Care Planning ; Cephalometry

Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases. Accurately predicting microbe-disease interactions (MDIs) offers critical insights for disease intervention and pharmaceutical research. Current advanced AI-based technologies automatically generate robust representations of microbes and diseases, enabling effective MDI predictions. However, these models continue to face significant challenges. A major issue is their reliance on complex feature extractors and classifiers, which substantially diminishes the models' generalizability. To address this, we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer potential MDIs. Initially, we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation. Secondly, we employ decoupled representation learning technology, compelling the graph neural network (GNN) to independently learn the weights for each feature subspace, thus enhancing its expressive power. Finally, we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN, reducing information loss due to occlusion. Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models. This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research. Code and data are accessible at: https://github.com/shmildsj/MDI-IFDRL.

The National Essential Medicines System could protect public health and ensure access to essential medications.Although the current selection methods for China's National Essential Medicines Lists(NEMLs)are becoming more scientific and standardized,there are still problems such as much emphasis on expert experience and the lack of transparency of decision-making basis.To address these issues,it proposes an evidence-based decision-making pathway for NEMLs selection guided by clinical value.This approach ensures a strong integration of evidence and decision-making,offering valuable insights for improving the adjustment procedures and selection criteria of the NEMLs in China.

Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases.Accurately predicting microbe-disease interactions(MDIs)offers critical insights for disease intervention and pharmaceutical research.Current advanced AI-based technologies automatically generate robust representations of microbes and diseases,enabling effec-tive MDI predictions.However,these models continue to face significant challenges.A major issue is their reliance on complex feature extractors and classifiers,which substantially diminishes the models' generalizability.To address this,we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer po-tential MDIs.Initially,we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation.Secondly,we employ decoupled representation learning technology,compelling the graph neural network(GNN)to independently learn the weights for each feature subspace,thus enhancing its expressive power.Finally,we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN,reducing information loss due to occlusion.Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models.This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research.Code and data are accessible at:https://github.com/shmildsj/MDI-IFDRL.

The National Essential Medicines System could protect public health and ensure access to essential medications.Although the current selection methods for China's National Essential Medicines Lists(NEMLs)are becoming more scientific and standardized,there are still problems such as much emphasis on expert experience and the lack of transparency of decision-making basis.To address these issues,it proposes an evidence-based decision-making pathway for NEMLs selection guided by clinical value.This approach ensures a strong integration of evidence and decision-making,offering valuable insights for improving the adjustment procedures and selection criteria of the NEMLs in China.