As a complex autoimmune disease， rheumatoid arthritis （RA） involves immune microenvironment dysregulation resulting from excessive activation of pyroptosis， which is a crucial factor in disease progression. Based on the theory of ying-wei in traditional Chinese medicine， "ying decline and wei attack" is considered the fundamental pathogenesis of RA. Pyroptosis serves as a microscopic manifestation of this concept， suggesting a potential correlation between "ying decline and wei attack" and pyroptosis nd immune microenvironment dysregulation in RA. Accordingly， treatment principles based on this theory are proposed： in the early stage of the disease， boosting wei to consolidate the exterior， and regulating ying to dispel pathogens； in the middle and late stages， harmonizing ying to remove stagnation， and nourishing its transformational source.

ObjectiveA qualitative analysis method was established for the composition of Astragali Radix（AR） before and after rice stir-frying. On the basis of systematic characterization of the chemical compositions in AR and stir-fried AR with rice（ARR）， the structures of their major compounds were deduced and identified， and the differential compositions between them were analyzed. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect the samples of AR and ARR in positive and negative ion modes， respectively. The compounds were analyzed and identified through self-constructed databases， literature， and reference standards， etc. And the data were analyzed by chemometrics， in order to screen for the differential components between AR and ARR. ResultsA total of 123 compounds were identified in AR and ARR， including 41 flavonoids， 19 terpenoids， 26 organic acids， 8 amino acids， 5 nucleotides， 5 carbohydrates and 19 other compounds. Among them， there were 95 common components in both， 18 unique components in AR， and 10 unique components in ARR. Principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） results both showed that there were significant differences in the chemical constituents of AR before and after rice stir-frying， and a total of 26 constituents with differences in the content were screened out， including L-canavanine， L-pyroglutamic acid， L-phenylalanine， cis-caffeic acid， and malonylastragaloside Ⅰ. Among them， 19 constituents of ARR were down-regulated and 7 constituents were up-regulated by comparing with AR. ConclusionThis study clarifies that the chemical composition of AR and ARR is mainly composed of flavonoids， terpenoids， and organic acids， and analyzes the components with significant differences in content between the two in combination with chemometrics， and the differential components are dominated by amino acids， organic acids and terpenoids， which can provide reference for the subsequent quality control and material basis research.

ObjectiveTo explore the potential mechanism of action of the combination of Sanguisorbae Radix-Sophorae Flos （DH） in the treatment of ulcerative colitis （UC） using network pharmacology methods and molecular docking technology. MethodsNetwork pharmacology analysis was utilized to predict the potential targets of DH for the treatment of UC. The therapeutic effects were experimentally validated by inducing a UC model in mice with 3% dextran sulfate sodium （DSS）. The experimental groups were the normal group， the model group， the salazosulfapyridine group （100 mg·kg^-1）， and the low， medium， and high dose groups of DH （1.2， 2.4， and 4.8 g·kg^-1）. The efficacy of the treatment was assessed through the general condition of the mice， histopathological examination， and the expression levels of inflammatory markers in the colon. The effect of DH on angiogenesis was explored by messenger RNA （mRNA） detection of colonic angiogenesis-related mediators， vascular endothelial growth factor （VEGF） immunohistochemistry， microvessel density （MVD） detection， and transmission electron microscopy. The phosphatidylinositol-3-kinase （PI3K）-protein kinase B （Akt） signaling pathway proteins were quantitatively analyzed through Western blot to assess whether the suppression of pathological angiogenesis by DH is associated with this pathway. ResultsNetwork pharmacological analysis yielded 112 potential core therapeutic targets for the treatment of UC with DH， of which the core targets were tumor protein 53 （TP53）， JUN， interleukin （IL）-6， Akt1， and tumor necrosis factor （TNF）. Compared with the normal group， mice in the model group showed significant weight loss， colon shortening， and high DAI score， increased expression of inflammatory factors IL-6， IL-1β， and TNF-α， as well as increased mRNA expression levels of angiogenesis-related mediators VEGF， vascular cell adhesion molecule 1 （VCAM1）， angiotensin 1 （Ang1）， matrix metalloproteinase （MMP）-1， MMP-2， and MMP-9. The positive expression of CD31 and VEGF in colonic tissue increased， and the protein expression of the PI3K/Akt pathway was increased （P<0.05）. The endothelial cells of the colonic mucosa and the colonic vasculature were severely damaged. Compared with the model group， mice in the DH groups had significantly reduced weight loss and colon shortening， lower DAI scores， and a significant decrease in mRNA expression of inflammatory factors and angiogenesis-related mediators. In addition， there was decreased positive expression of CD31 and VEGF in colonic tissue and decreased protein expression of the PI3K/Akt pathway （P<0.05）. ConclusionNetwork pharmacology， molecular docking， and experimental validation are applied to explore the mechanism of action of DH in the treatment of UC， and it is found that DH is able to improve the symptoms of colitis and inhibit the pathological angiogenesis in UC mice. Its action might be related to affecting the PI3K/Akt pathway.

ObjectiveTo evaluate the effectiveness of stone needle thermocompression and massage compared to flurbiprofen gel patch in relieving chronic musculoskeletal pain in the shoulder and back， and to explore the potential mediating mechanism through muscle elasticity. MethodsA total of 120 patients with chronic musculoskeletal pain in the shoulder and back were randomly assigned to either stone needle group or flurbiprofen group， with 60 patients in each. The stone needle group received stone needle thermocompression and massage for 30 minutes， three times per week； the flurbiprofen group received flurbiprofen gel patch twice daily. Both groups were treated for 2 weeks. Pain improvement， as the primary outcome， was assessed using the Global Pain Scale （GPS） at baseline， after 2 weeks of treatment， and again 2 weeks post-treatment. To explore potential mechanisms， a mediator analysis was conducted by measuring changes in superficial and deep muscle elasticity using musculoskeletal ultrasound at baseline and after the 2-week treatment period. ResultsThe stone needle group showed significantly greater pain relief than the flurbiprofen group 2 weeks post-treatment. After adjusting for confounders related to pain duration， the between-group mean difference was -8.8 ［95% CI （-18.2， -0.7）， P＜0.05］. Part of the therapeutic effect was mediated by changes in deep muscle elasticity， with a mediation effect size of -1.5 ［95% CI （-2.0， -0.9）， P = 0.024］， accounting for 17.9% of the total effect. ConclusionStone needle thermocompression and massage can effectively relieve chronic musculoskeletal pain in the shoulder and back， partly through a mediating effect of improved deep muscle elasticity.

ObjectiveTo explore the potential mechanism of action of the combination of Sanguisorbae Radix-Sophorae Flos （DH） in the treatment of ulcerative colitis （UC） using network pharmacology methods and molecular docking technology. MethodsNetwork pharmacology analysis was utilized to predict the potential targets of DH for the treatment of UC. The therapeutic effects were experimentally validated by inducing a UC model in mice with 3% dextran sulfate sodium （DSS）. The experimental groups were the normal group， the model group， the salazosulfapyridine group （100 mg·kg^-1）， and the low， medium， and high dose groups of DH （1.2， 2.4， and 4.8 g·kg^-1）. The efficacy of the treatment was assessed through the general condition of the mice， histopathological examination， and the expression levels of inflammatory markers in the colon. The effect of DH on angiogenesis was explored by messenger RNA （mRNA） detection of colonic angiogenesis-related mediators， vascular endothelial growth factor （VEGF） immunohistochemistry， microvessel density （MVD） detection， and transmission electron microscopy. The phosphatidylinositol-3-kinase （PI3K）-protein kinase B （Akt） signaling pathway proteins were quantitatively analyzed through Western blot to assess whether the suppression of pathological angiogenesis by DH is associated with this pathway. ResultsNetwork pharmacological analysis yielded 112 potential core therapeutic targets for the treatment of UC with DH， of which the core targets were tumor protein 53 （TP53）， JUN， interleukin （IL）-6， Akt1， and tumor necrosis factor （TNF）. Compared with the normal group， mice in the model group showed significant weight loss， colon shortening， and high DAI score， increased expression of inflammatory factors IL-6， IL-1β， and TNF-α， as well as increased mRNA expression levels of angiogenesis-related mediators VEGF， vascular cell adhesion molecule 1 （VCAM1）， angiotensin 1 （Ang1）， matrix metalloproteinase （MMP）-1， MMP-2， and MMP-9. The positive expression of CD31 and VEGF in colonic tissue increased， and the protein expression of the PI3K/Akt pathway was increased （P<0.05）. The endothelial cells of the colonic mucosa and the colonic vasculature were severely damaged. Compared with the model group， mice in the DH groups had significantly reduced weight loss and colon shortening， lower DAI scores， and a significant decrease in mRNA expression of inflammatory factors and angiogenesis-related mediators. In addition， there was decreased positive expression of CD31 and VEGF in colonic tissue and decreased protein expression of the PI3K/Akt pathway （P<0.05）. ConclusionNetwork pharmacology， molecular docking， and experimental validation are applied to explore the mechanism of action of DH in the treatment of UC， and it is found that DH is able to improve the symptoms of colitis and inhibit the pathological angiogenesis in UC mice. Its action might be related to affecting the PI3K/Akt pathway.

OBJECTIVE To explore the effects of CD20 coding gene （MS4A1） polymorphism on the blood concentration and efficacy of rituximab in patients with non-Hodgkin’s lymphoma. METHODS A prospective observational study was conducted on 160 newly diagnosed non-Hodgkin’s lymphoma patients who received the R-CHOP regimen at the Sun Yat Sen University Cancer Center from January 2016 to December 2020， with a minimum follow-up period of approximately 5 years. The blood concentration of rituximab was detected by enzyme-linked immunosorbent assay. MS4A1 tagSNPs were selected by Haploview4.2 software， including rs1051461， rs17155034， rs4939364， and rs10501385. The genotype of MS4A1 was detected by Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Univariate linear regression analysis was employed to examine the correlation between various factors（demographic， clinical， and genotypic variables） in patients and the steady-state trough concentration of rituximab during the first course of treatment， followed by multivariate linear regression analysis. Kaplan-Meier curves were drawn to evaluate progression-free survival （PFS） and overall survival （OS）. Using MS4A1 genotype and tumor stage as independent variables， Cox regression model was employed to evaluate the factors influencing patient prognosis. RESULTS The blood concentration of rituximab in MS4A1 rs10501385 CC carriers was 15.20 μg/mL，which was significantly lower than 21.95 μg/mL in AA+AC carriers （P＜0.05）. The multivariate linear regression model incorporating tumor stage and MS4A1 rs10501385 polymorphism explained 7.3% of the interindividual variability in rituximab concentrations. Compared with MS4A1 rs1051461 CC carriers， CT+TT carriers had significantly prolonged PFS and OS （P＜0.05）. The Cox proportional hazards regression model showed that the MS4A1 rs1051461 CC genotype （HR＝4.406， 95%CI：1.743-11.137， P＜0.05） and tumor Ⅲ&Ⅳ （HR＝3.233， 95%CI： 1.413-7.399， P＜0.05） were independent risk factors for PFS. CONCLUSIONS The tumor staging and MS4A1 rs10501385 polymorphism are key influencing factors for blood concentration of rituximab， and MS4A1 rs1051461 polymorphism significantly affects PFS in non-Hodgkin’s lymphoma patients.

Intravitreal injection of anti-vascular endothelial growth factor(VEGF)agents has become the primary treatment for macular edema associated with retinal vascular disease such as diabetic retinopathy and retinal vein occlusion, but there are limitations such as variable treatment efficacy and insufficient durability of therapeutic effects. As the first bispecific antibody applied in ophthalmic treatment, Faricimab achieves favorable outcomes by simultaneously targeting both VEGF-A and angiopoietin-2(Ang-2)pathways. Based on evidence from recent clinical trials and real-world studies, this article reviews the research progress on Faricimab for the treatment of diabetic macular edema(DME), retinal vein occlusion-associated macular edema(RVO-ME)and refractory macular edema compared to the therapeutic effects of other agents. Additionally, based on Faricimab's safety characteristics and future potential, its therapeutic prospects for macular edema associated with retinal vascular diseases are discussed. This review aims to provide evidence-based references for optimizing clinical treatment strategies, thereby contributing to mitigating the risk of vision loss due to macular edema.

Perceptual decision making refers to the process by which individuals make choices and judgments based on sensory information, serving as a fundamental ability for human adaptation to complex environments. While traditional research has focused on perceptual decision making in isolated contexts, growing evidence highlights the profound influence of social contexts prevalent in real-world scenarios. As a crucial factor supporting individual survival and development, social context not only provides rich information sources but also shapes perceptual decision making through top-down processing mechanisms, prompting researchers to recognize the inherently social nature of human decisions. Empirical studies have demonstrated that social information, such as others’ choices or group norms, can systematically bias individuals’ perceptual decisions, often manifesting as conformity behaviors. Social influence can also facilitate performance under certain conditions, particularly when individuals can accurately identify and adopt high-quality social information. The impact of social context on perceptual decisions is modulated by a variety of external and internal factors, including group characteristics(e.g., group size, response consistency), attributes of peers (e.g., familiarity, social status, distinctions between human and artificial agents), as well as individual differences such as confidence, personality traits, and developmental stage. The motivations driving social influence encompass three primary mechanisms: improving decision accuracy through informational influence, gaining social acceptance through normative influence, and maintaining positive self-concept. Recent computational approaches have employed diverse theoretical frameworks to provide valuable insights into the cognitive mechanisms underlying social influence in perceptual decision making. Reinforcement learning models demonstrate how social feedback shapes future choices through reward-based updating. Bayesian inference frameworks describe how individuals integrate personal beliefs with social information based on their respective reliabilities, dynamically updating beliefs to optimize decisions under uncertainty. Drift diffusion models offer powerful tools to decompose social influence into distinct cognitive components, allowing researchers to differentiate between changes in perceptual processing and shifts in decision criteria. Collectively, these models establish a comprehensive methodological foundation for disentangling the multiple pathways by which social context shapes perceptual decisions. Neuroimaging and electrophysiological studies provide converging evidence that social context influences perceptual decision making through multi-level neural mechanisms. At early perceptual processing stages, social influence modulates sensory evidence accumulation in parietal cortex and directly alters primary visual cortex activity, while guiding selective attention to stimulus features consistent with social norms through attentional alignment mechanisms. At higher cognitive levels, the reward system (ventral striatum, ventromedial prefrontal cortex) is activated during group-consistent decisions; emotion-processing networks (anterior cingulate cortex, insula, amygdala) regulate experiences of social acceptance and rejection; and mentalizing-related brain regions (dorsomedial prefrontal cortex, temporoparietal junction) support inference of others’ mental states and social information integration. These neural circuits work synergistically to achieve top-down multi-level modulation of perceptual decision making. Understanding the mechanisms by which social context shapes perceptual decision making has broad theoretical and practical implications. These insights inform the optimization of collective decision-making, the design of socially adaptive human-computer interaction systems, and interventions for cognitive disorders such as autism spectrum disorder and anorexia nervosa. Future studies should combine computational modeling and neuroimaging approaches to systematically investigate the multi-level and dynamic nature of social influences on perceptual decision making.

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control