OBJECTIVE To establish a Chinese drug-related problem （DRP） classification system applicable to pharmacist-led pharmaceutical care in China， providing pharmacists with an effective and practical tool for pharmaceutical care. METHODS A multi-stage process was employed to construct the DRP classification system， including literature review and analysis， comparison of existing classification systems， refinement of classification items and framework development， two rounds of standard case validation， expert discussion， and system revision. The Fleiss′ kappa test was used to calculate the consistency coefficient κ， assessing the reliability of pharmacists participating in evaluating the classification system. An electronic questionnaire comprising six items was employed to evaluate the system’s applicability. RESULTS The constructed Chinese DRP classification system comprised six sections [problem（including potential problems）， DRP evaluation， cause （including possible causes of potential problems）， intervention， acceptance of intervention and DRP status]， with 24 primary codes and 96 secondary codes. In the first round of case validation， κ values exceeded 0.4 for all sections except “intervention” and “DRP status”. In the second round， κ values exceeded 0.4 for all sections. In the applicability evaluation of the classification system， positive ratings （“strongly agree” or “agree”） exceeded 85% for all items. Specifically， positive ratings for“the classification system can provide appropriate category selection”，“ the classification system is comprehensive”，“ the classification system is convenient to use” and “the classification system is highly satisfactory” exceeded 92%. CONCLUSIONS The Chinese DRP classification system developed demonstrates both high reliability and applicability， providing an effective and practical classification tool for pharmacists in China to conduct pharmaceutical care.

ObjectiveTo explore the vascular endothelial injury in male mice caused by exposure to polystyrene microplastics （PS-MPs） and the intervention effect of luteolin on vascular remodeling. Additionally， to investigate the mechanism through the oxidative system and metabolomics. MethodsThirty-two C57BL/6 mice （6-8 weeks old） were randomly divided into the saline group （saline group）， the 0.1 mg/kg PS-MPs exposure group （0.1PS-MPs group）， the 1 mg/kg PS-MPs exposure group （1PS-MPs group）， and the 1 mg/kg PS-MPs + luteolin treatment group （1PS-MPs + Lut group）， with 8 mice in each group. After 8 weeks of intervention， the body weight， blood pressure， aortic organ coefficient， and aortic histopathological changes of mice in each group were detected； the total cholesterol （TC）， triglyceride （TG）， and high-density lipoprotein cholesterol （HDL-C） lipid metabolism-related indicators in the aorta of mice were detected； the reactive oxygen species （ROS）， glutathione （GSH）， and malondialdehyde （MDA） oxidative stress-related indicators were detected； the endothelin （ET-1）， nitric oxide （NO）， vascular endothelial growth factor A （VEGF-A）， vascular cell adhesion molecule-1 （VCAM-1/CD106）， and intercellular adhesion molecule-1 （ICAM-1/CD54） endothelial function-related indicators and serum metabolomics were detected. ResultsCompared to the saline group， exposure to PS-MPs resulted in pathological thickening of the mouse aorta， increased aortic organ coefficient， and elevated blood pressure. Lipid metabolism-related indicators， including TC and TG， were elevated， while HDL-C was reduced， indicating lipid metabolism disorder in mice. Oxidative stress markers such as ROS and MDA increased， whereas GSH decreased， demonstrating oxidative damage. Vascular endothelial inflammation and injury markers， including ET-1， VEGF-A， VCAM-1， and ICAM-1， were upregulated， while the vasodilatory substance NO was downregulated， confirming endothelial injury. Furthermore， serum metabolomics results revealed that PS-MPs exposure induced endothelial damage by disrupting metabolic pathways such as the citrate cycle. Compared to the PS-MPs group， luteolin significantly reversed these effects， attenuating oxidative stress and lipid metabolism disorders， and effectively repairing endothelial injury. ConclusionPS-MPs induce vascular toxicity through oxidative stress and lipid metabolism. Luteolin effectively alleviates endothelial damage and vascular remodeling.

Endoscopic full-thickness resection (EFTR) is a minimally invasive technique that is increasingly used for gastrointestinal stromal tumors (GISTs) originating from the muscularis propria. Despite its advantages over conventional surgery, such as complete tumor resection and faster recovery, EFTR faces challenges related to its efficacy, safety, and feasibility, particularly in gastric GISTs. By summarizing the literature published over the past decade, this review provides a comprehensive overview of the clinical outcomes of EFTR and the evolution of defect closure devices.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

ObjectiveTo construct a risk prediction model for chronic atrophic gastritis （CAG） that combines disease and syndrome by integrating spleen deficiency and blood stasis syndrome scores， gastric stem cell marker analysis， and network pharmacology and to elucidate the mechanism link between spleen deficiency， blood stasis， and gastric stem cell dysregulation. MethodsA total of 60 patients were stratified into high-risk CAG， low-risk CAG， and non-atrophic groups based on the operative link for gastritis assessment （OLGA）/operative link for gastric intestinal metaplasia assessment （OLGIM） stages. General data and syndrome scores of the patients were collected. Immunohistochemistry was employed to measure the protein levels of leucine-rich repeat-containing G protein-coupled receptor 5 （LGR5）， trefoil factor 2 （TFF2）， and β-catenin in gastric mucosa across groups. Transcriptomic data （GSE130823） from the Gene Expression Omnibus （GEO） database were analyzed to validate the expression of these molecular markers at the gene level. A Firth penalized maximum likelihood logistic regression model was employed to integrate clinical， molecular， and TCM syndrome data to develop a CAG risk prediction model. Finally， network pharmacology analysis was conducted on spleen-invigorating herbs （Astragali Radix， Atractylodis Macrocephalae Rhizoma， and Dioscorea Rhizoma） and blood-activating herbs （Hedyotis diffusa， Salviae Miltiorrhizae Radix et Rhizoma， and Curcumae Rhizoma） to identify overlapping targets between these herbs and differentially expressed genes between low-grade intraepithelial neoplasia （LGIN） and gastritis， thereby clarifying the role of spleen deficiency and blood stasis in CAG progression from a pharmacological perspective. ResultsHigh-risk CAG patients exhibited higher blood stasis scores （4.60±1.50，2.62±1.32， P<0.01）， progressive nuclear accumulation of β-catenin （A 0.28-0.53， P<0.01）， and an increased LGR5⁺/TFF2⁺ ratio （A 1.02-1.92， P<0.01）. Blood stasis scores were correlated with LGR5/TFF2 imbalance （P=0.03） and activation of the Wnt/β-catenin signaling pathway （CTNNB1 increase， log₂=0.78）. The integrated prediction model （blood stasis score≥5 + β-catenin>0.38 + LGR5/TFF2>1.5） outperformed a pure biomarker approach ［Area Under the Curve （AUC） 0.92，0.89， ΔAUC=0.03， P=0.02］. Moreover， network pharmacology revealed 66 overlapping targets between spleen-invigorating/blood-activating herbs and LGIN， which were functionally enriched in mucosal repair and anti-oxidative stress， and negatively correlated with the Wnt/β-catenin signaling pathway （P<0.01）. ConclusionThis study developed an integrated risk prediction model for CAG by combining TCM spleen deficiency and blood stasis syndromes with gastric stem cell molecular markers. Furthermore， it proposed for the first time the "blood stasis-Wnt/β-catenin-stem cell axis" hypothesis， preliminarily elucidating that spleen deficiency and blood stasis may exacerbate gastric stem cell dysregulation and promote malignant transformation of CAG through hypoxia-induced Wnt activation. This provides a theoretical foundation and a translational tool for risk stratification and multi-target TCM intervention in CAG.

ObjectiveTo construct a risk prediction model for chronic atrophic gastritis （CAG） that combines disease and syndrome by integrating spleen deficiency and blood stasis syndrome scores， gastric stem cell marker analysis， and network pharmacology and to elucidate the mechanism link between spleen deficiency， blood stasis， and gastric stem cell dysregulation. MethodsA total of 60 patients were stratified into high-risk CAG， low-risk CAG， and non-atrophic groups based on the operative link for gastritis assessment （OLGA）/operative link for gastric intestinal metaplasia assessment （OLGIM） stages. General data and syndrome scores of the patients were collected. Immunohistochemistry was employed to measure the protein levels of leucine-rich repeat-containing G protein-coupled receptor 5 （LGR5）， trefoil factor 2 （TFF2）， and β-catenin in gastric mucosa across groups. Transcriptomic data （GSE130823） from the Gene Expression Omnibus （GEO） database were analyzed to validate the expression of these molecular markers at the gene level. A Firth penalized maximum likelihood logistic regression model was employed to integrate clinical， molecular， and TCM syndrome data to develop a CAG risk prediction model. Finally， network pharmacology analysis was conducted on spleen-invigorating herbs （Astragali Radix， Atractylodis Macrocephalae Rhizoma， and Dioscorea Rhizoma） and blood-activating herbs （Hedyotis diffusa， Salviae Miltiorrhizae Radix et Rhizoma， and Curcumae Rhizoma） to identify overlapping targets between these herbs and differentially expressed genes between low-grade intraepithelial neoplasia （LGIN） and gastritis， thereby clarifying the role of spleen deficiency and blood stasis in CAG progression from a pharmacological perspective. ResultsHigh-risk CAG patients exhibited higher blood stasis scores （4.60±1.50，2.62±1.32， P<0.01）， progressive nuclear accumulation of β-catenin （A 0.28-0.53， P<0.01）， and an increased LGR5⁺/TFF2⁺ ratio （A 1.02-1.92， P<0.01）. Blood stasis scores were correlated with LGR5/TFF2 imbalance （P=0.03） and activation of the Wnt/β-catenin signaling pathway （CTNNB1 increase， log₂=0.78）. The integrated prediction model （blood stasis score≥5 + β-catenin>0.38 + LGR5/TFF2>1.5） outperformed a pure biomarker approach ［Area Under the Curve （AUC） 0.92，0.89， ΔAUC=0.03， P=0.02］. Moreover， network pharmacology revealed 66 overlapping targets between spleen-invigorating/blood-activating herbs and LGIN， which were functionally enriched in mucosal repair and anti-oxidative stress， and negatively correlated with the Wnt/β-catenin signaling pathway （P<0.01）. ConclusionThis study developed an integrated risk prediction model for CAG by combining TCM spleen deficiency and blood stasis syndromes with gastric stem cell molecular markers. Furthermore， it proposed for the first time the "blood stasis-Wnt/β-catenin-stem cell axis" hypothesis， preliminarily elucidating that spleen deficiency and blood stasis may exacerbate gastric stem cell dysregulation and promote malignant transformation of CAG through hypoxia-induced Wnt activation. This provides a theoretical foundation and a translational tool for risk stratification and multi-target TCM intervention in CAG.

Objective To analyze the correlation between tongue image features and the risk levels of disease in patients with idiopathic membranous nephropathy(IMN).Methods Based on IMN clinical research electronic data acquisition system,a cross-sectional study method was used to analyze the clinical diagnosis and treatment data of 135 IMN patients from Guangdong Provincial Hospital of Chinese Medicine.The patients were grouped according to the risk levels of disease,and then the correlation between the risk levels of disease and tongue image features was analyzed.During the description of tongue image features,TB is for tongue body,TC is for tongue coating,L is for luminance,a is for red-green axis,G is for the value of green,B is for the value of blue,and AUT is for the value of autocorrelation.Results The comparison of tongue image feature indicators of patients with different risk levels of IMN showed that:(1)the higher the level of disease risk of IMN patients,the greater the values of TB-L,TB-G and TB-B(P<0.05 or P<0.01).The values of tongue image indicator TB-a and TC-a of the patients with different risk levels of IMN were shown in decreasing sequence:low-risk group>high-risk group>middle-risk group>extremely-high-risk group(P<0.05).(2)Linear regression analysis showed that TB-L,TB-G,and TB-B were significantly increased in the high-risk group compared with those in the middle-and low-risk groups(P<0.05 or P<0.01),whereas there were no significant differences between the middle-risk group and low-risk group(P>0.05).(3)The results of correlation analysis showed that there was a positive correlation among most of the tongue image feature indicators(including TB-L,TB-G,TB-B,TB-AUT,TC-L,TC-G,and TC-B,etc.)and the risk level of disease,while TB-a was negatively correlated with the risk level of disease,and the differences were all statistically significant(P<0.05 or P<0.01).(4)All patients were treated with Chinese medicine and/or Chinese patent medicine,and 46.7%of patients were given hormones and immunosuppressants,and there was no statistically significant difference in the the use of hormones and immunosuppressants among various groups(P=0.637).Conclusion There is a correlation between the tongue image features of IMN patients and the risk level of disease,and the results will provide an objective reference for the assessment of illness state and traditional Chinese medicine(TCM)syndrome differentiation of IMN patients.With reference to the changes in the tongue image features,the illness state can be precisely identified,which is more accurate than the inspection of four diagnostic methods of TCM.

Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.

Objective To explore the mechanism by which the sanguis draconis flavones(SDF)regulates the reactive oxygen species(ROS)/thioredoxin-interacting protein(TXNIP)pathway to mediate cell pyroptosis and improve cerebral ischemia-reperfusion injury(CIRI)in rats.Methods The experimental rats were randomly divided into the control group(Ctrl),the CIRI group,the low-dose SDF group(SDF-L),the high-dose SDF group(SDF-H),and the SDF-H+ROS/TXNIP pathway activator,trimethylamine oxide(TMAO)group(SDF-H+TMAO).Among them,except for the control group,the remaining rats all needed to establish the CIRI rat model by the modified suture method.Zea Longa scoring was performed on rats from each group.ELISA was used to detect the levels of serum inflammatory factors interleukin(IL)-1β,IL-18 and oxidative stress-related factors superoxide dismutase(SOD),malondialdehyde(MDA),glutathione peroxidase(GSH-Px).Flow cytometry was used to measure the ROS levels.Cerebral edema was detected.Cerebral infarction was detected by 2,3,5-triphenyl tetrazolium chloride(TTC)staining.HE staining was used to detect the pathological changes of brain tissue.Immunohistochemistry was used to detect the expression of pyrolytic effector protein dermolin D(GSDMD).Western blotting was used to detect the expression of proteins related to the ROS/TXNIP pathway.Results Compared with the control group,a large area of cerebral infarctions were observed in the brain tissue of the CIRI group,accompanied by mild hemorrhage and obvious infiltration of inflammatory cells.Neuronal cells underwent degeneration and necrosis,with sparse and disordered arrangement.The phenomena of nuclear condensation and nucleolus lysis were obvious.The Zea Longa score,cerebral infarction volume,brain tissue water content,levels of IL-1β,IL-18,ROS,MDA,and the expressions of GSDMD,TXNIP,nucleotide-binding oligomerization domain-like receptor protein 3(NLRP3),apoptosis-related punctate protein(ASC),and Caspase-1 increased,while the activities of SOD and GSH-Px decreased(P＜0.05).Compared with the CIRI group,the pathological damage of brain tissues in the SDF-L group and the SDF-H group was significantly improved.The Zea Longa score,cerebral infarction volume,brain tissue water content,levels of IL-1β,IL-18,ROS,MDA,and the expressions of GSDMD,TXNIP,NLRP3,ASC,and Caspase-1 decreased.The activities of SOD and GSH-Px increased(P＜0.05);TMAO treatment partially reversed the improvement effect of SDF on CIRI in rats.Conclusion SDF ameliorates cerebral CIRI in rats by inhibiting ROS/TXNIP pathway-mediated pyroptosis.

BACKGROUND: The sirtuin family is well recognized for its crucial involvement in various cellular processes. Nevertheless, studies on its role in the human endometrium are limited. This study aimed to explore the expression and localization of the sirtuin family in the human endometrium, focusing on sirtuin 3 (SIRT3) and its potential role in the oxidative imbalance of the endometrium in polycystic ovary syndrome (PCOS). METHODS: Endometrial specimens were collected from both patients with PCOS and controls undergoing hysteroscopy at the Center for Reproductive Medicine, Peking University Third Hospital, from July to August 2015 and used for cell culture. The protective effects of SIRT3 were investigated, and the mechanism of SIRT3 in improving endometrial receptivity of patients with PCOS was determined using various techniques, including cellular bioenergetic analysis, small interfering ribonucleic acid (siRNA) silencing, real-time quantitative polymerase chain reaction, Western blot, immunofluorescence, immunohistochemistry, and flow cytometry analysis. RESULTS: The sirtuin family was widely expressed in the human endometrium, with SIRT3 showing a significant increase in expression in patients with PCOS compared with controls ( P <0.05), as confirmed by protein and gene assays. Concurrently, endometrial antioxidant levels were elevated, while mitochondrial respiratory capacity was reduced, in patients with PCOS ( P <0.05). An endometrial oxidative stress (OS) model revealed that the downregulation of SIRT3 impaired the growth and proliferation status of endometrial cells and reduced their receptivity to day 4 mouse embryos. The results suggested that SIRT3 might be crucial in maintaining normal cellular state by regulating antioxidants, cell proliferation, and apoptosis, thereby contributing to enhanced endometrial receptivity. CONCLUSIONS Our findings proposed a significant role of SIRT3 in improving endometrial receptivity in patients with PCOS by alleviating OS and regulating the balance between cell proliferation and apoptosis. Therefore, SIRT3 could be a promising target for predicting and improving endometrial receptivity in this patient population.
Humans ; Female ; Polycystic Ovary Syndrome/metabolism* ; Endometrium/metabolism* ; Sirtuin 3/genetics* ; Oxidative Stress/genetics* ; Adult ; Animals ; Mice ; Apoptosis/physiology* ; Immunohistochemistry ; Cell Proliferation/physiology*