OBJECTIVE To investigate the effects and mechanisms of Lycium ruthenicum Murr. in improving sleep. METHODS Network pharmacology was employed to identify the active components of L. ruthenicum and their associated disease targets， followed by enrichment analysis. A caffeine‑induced zebrafish model of sleep deprivation was established ， and the zebrafish were treated with L. ruthenicum Murr. extract （LRME） at concentrations of 0.1， 0.2 and 0.4 mg/mL， respectively； 24 h later， behavioral changes of zebrafish and pathological alterations in brain neurons were subsequently observed. The levels of inflammatory factors [interleukin-6 （IL-6）， IL-1β， IL-10， tumor necrosis factor-α （TNF-α）]， oxidative stress markers [superoxide dismutase （SOD）， malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， catalase （CAT）]， and neurotransmitters [5- hydroxytryptamine （5-HT）， γ-aminobutyric acid （GABA）， glutamic acid （Glu）， dopamine （DA）， and norepinephrine （NE）] were measured. The protein expression levels of protein kinase B1 （AKT1）， phosphorylated AKT1 （p-AKT1）， epidermal growth factor receptor （EGFR）， B-cell lymphoma 2 （Bcl-2）， sarcoma proto-oncogene，non-receptor tyrosine kinase （SRC）， and heat shock protein 90α family class A member 1 （HSP90AA1） in the zebrafish were also determined. RESULTS A total of 12 active components and 176 intersecting disease targets were identified through network pharmacology analysis. Among these， apigenin， naringenin and others were recognized as core active compounds， while AKT1， EGFR and others served as key targets； EGFR tyrosine kinase inhibitor resistance signaling pathway was identified as the critical pathway. The sleep improvement rates in zebrafish of LRME low-， medium-， and high-dose groups were 54.60%， 69.03% and 77.97%， 开发。E-mail：hjp_yft@163.com respectively， while the inhibition ratios of locomotor distance were 0.57， 0.83 and 0.95， respectively. Compared with the model group， the number of resting counts， resting time and resting distance were significantly increased/extended in LRME medium- and high-dose groups （P＜0.05）. Neuronal damage in the brain was alleviated. Additionally， the levels of IL-6， IL-1β， TNF-α， MDA， Glu， DA and NE， as well as the protein expression levels of AKT1， p-AKT1， EGFR， SRC and HSP90AA1， were markedly reduced （P＜0.05）， while the levels of IL-10， SOD， GSH-Px， CAT， 5-HT and GABA， as well as Bcl-2 protein expression， were significantly elevated （P＜0.05）. CONCLUSIONS L. ruthenicum Murr. demonstrates sleep-improving effects， and its specific mechanism may be related to the regulation of inflammatory responses， oxidative stress， neurotransmitter balance， and the EGFR tyrosine kinase inhibitor resistance signaling pathway.

ObjectiveThis study aims to systematically analyze the blood-absorbed components and metabolic profiles of Xiebaisan（XBS） in normal and chronic bronchitis （CB） mice using ultra performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS）， while comparing differences between the two states. MethodsThirty female BABL/c mice were randomly divided into the normal group， the normal drug administration group， the CB group， the CB drug administration group and the dexamethasone group， with 6 mice in each group. The CB mouse model was established by inducing with ovalbumin （OVA）. The mice in the normal drug administration group and the CB drug administration group started to be gavaged with XBS（13.2 g·kg^-1） from the 21^st day， and the dexamethasone group mice were simultaneously gavaged with dexamethasone （0.5 mg·kg^-1） until the end of the 35^th day of the experiment. Subsequently， serum samples were collected and evaluated for their efficacy， based on the pharmacological evaluation indicators， to determine the efficacy of XBS in treating CB. Then the UPLC-Q-Exactive Orbitrap MS was employed to identify and analyze the chemical constituents， blood-absorbed components， and metabolites of XBS. Chemometric analysis was conducted to reveal metabolic profile differences under "dual states". Concurrently， Real-time PCR technology was utilized to detect the expression levels of key liver metabolic enzymes CYP2E1， CYP3A1， UGT1A1， and UGT1A6. ResultsA total of 28 prototype components and 158 metabolites （including 48 phase Ⅰ metabolites and 110 phase Ⅱ metabolites） of XBS were unambiguously identified in the serum of normal mice. Additionally， a comprehensive characterization was performed on a total of 32 prototype components and 178 metabolites （including 50 phase Ⅰ metabolites and 128 phase Ⅱ metabolites） of XBS in the serum of CB mice. Among them， 27 prototype components were detected in both states， including 12 flavonoids， 2 alkaloids， 3 triterpenes， 4 organic acids， 3 amides， 1 stilbene and 2 other compounds. The chemometrics analysis revealed no significant difference in the prototype components and metabolites of XBS between normal and CB mice； however， there was a significant increase in the in-vivo exposure of XBS in CB mice. Compared to normal mice， the levels of phase Ⅰ metabolites such as oxidation， reduction and methylation of blood components of XBS as well as phase Ⅱ metabolites of glucuronidation showed significant changes in CB mice. Real-time PCR further confirmed that these alterations were attributed to the upregulation of CYP2E1 （P<0.05）， CYP3A1 （P>0.05）， UGT1A1 （P<0.01） and UGT1A6 （P<0.01） enzymes expression in the liver of CB mice. ConclusionThis study elucidated the disparities in the levels of the blood-absorbed components and metabolic profiles of XBS in normal and CB mice， especially in oxidation， reduction， methylation in phase Ⅰ metabolism and glucoaldehyde acidification in phase Ⅱ metabolism. And there are related to the differences in the expression levels of phase Ⅰ and phase Ⅱ metabolic enzymes CYP2E1， CYP3A1， UGT1A1 and UGT1A6 in the liver.

Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Objective: To investigate the prevalence of overweight and obesity among children and adolescents in Yangzhou City, and its association with screen behaviors, so as to provide scientific evidence for weight management among students. Methods: In May 2025, an electronic questionnaire survey was conducted among children and adolescents in Yangzhou City. A total of 3 722 participants were selected from grades 4 to 12 in 18 primary and secondary schools (108 classes) by using stratified cluster random sampling. The Chi square test was used to compare the differences in the detection rates of overweight and obesity among children and adolescents with 5 types of screen behaviors (watching TV, playing electronic games, scrolling short videos, screen based learning, electronic socializing) in different time groups each day (never, >0~<2 h, ≥2 h). Multivariate Logistic regression analysis was performed to examine the associations of five types of screen behaviors, presence of electronic devices in the bedroom, and screen use during meals on the weight status of children and adolescents. Results: The prevalence of overweight and obesity among children and adolescents was 37.3%. For all five types of screen behaviors, the differences in the distribution of overweight and obesity detection rates among children and adolescents across the three time spent categories were statistically significant ( χ 2=30.76- 70.78 , all P <0.01). After adjusting for confounding factors, multivariate Logistic regression analysis revealed that frequent or always using screens during meals( OR =1.63, 95％ CI =1.14~2.31), playing video games ( OR =1.28, 95% CI =1.11-1.48), browsing short videos ( OR =1.29, 95％ CI=1.09-1.54), and screen based learning ( OR =1.26, 95％ CI =1.10-1.44) were significantly associated with overweight and obesity among children and adolescents (all P <0.05). Conclusions Excessive screen use is positively correlated with the incidence of overweight and obesity in children and adolescents. Targeted interventions on screen behaviors among children and adolescents are therefore warranted.

OBJECTIVE To evaluate the anticoagulant efficacy and safety of nafamostat mesylate （NM） in the treatment of uremic patients at high risk of bleeding undergoing continuous veno-venous hemofiltration （CVVH） with different methods （pre- dilution and post-dilution）. METHODS A total of 130 uremic patients at high risk of bleeding who underwent CVVH treatment in the nephrology department of Chongqing University Three Gorges Hospital from July 2023 to September 2024 were selected. They were divided into pre-dilution group and post-dilution group according to the random number table method， with 65 cases in each group. Both groups of patients received CVVH treatment under NM anticoagulation. The pre-dilution group adopted the pre-dilution replacement method， while the post-dilution group adopted the post-dilution replacement method. The coagulation， pressure， and usage duration of the filter and dialysis circuit venous reservoirs were compared between the two groups. The changes in prothrombin time （PT）， prothrombin time-international normalized ratio （PT-INR）， activated partial thromboplastin time （APTT）， and fibrinogen （FIB） in the peripheral venous blood before the heparin pump and after the filter at 1， 4 and 7 h of CVVH treatment， as well as 20 min after the end of treatment， were compared between the two groups. The single-compartment urea clearance rate （spKt/V）， β2-microglobulin （β2-MG） clearance rate and the incidence of adverse reactions were duni2007@foxmail.com compared between the two groups. RESULTS Both the pre-dilution and post-dilution groups had 60 patients who completed the study. The incidence of grade Ⅱ-Ⅲ coagulation of the filter and venous reservoirs， as well as the number of patients with transmembrane and venous pressure alarm intervention in the post- dilution group were significantly higher or more than those in the pre-dilution group （P＜0.05）， while usage time of the filter and the pipeline in the post-dilution group was significantly shorter than that in the pre-dilution group （P＜0.05）. The APTT values before the heparin pump as well as PT and APTT values after the filter at 1 h， 4 h， and 7 h of CVVH treatment in the post-dilution group were significantly higher than those in the pre-dilution group （P＜0.001）. There were no significant differences in PT， PT- INR， APTT and FIB between the two groups of patients 20 min after the end of treatment （P＞0.05）. The spKt/v and β2-MG clearance rates in the post-dilution group were significantly higher than those in the pre-dilution group （P＜0.001）. There was no significant difference in the incidence of adverse reactions between the two groups （P＞0.05）. CONCLUSIONS When NM is used as an anticoagulant in the CVVH treatment of uremic patients at high risk of bleeding， compared with the pre-dilution treatment method， the post-dilution treatment method has a higher incidence of filter and dialysis tubing venous reservoir， a shorter usage time of the filter and pipeline， and a greater impact on extracorporeal coagulation， but has a higher solute clearance rate. Clinically， different dilution methods can be selected according to the different treatment needs of patients.

Objective To study the seasonal distribution characteristics of polycyclic aromatic hydrocarbons (PAHs) in PM_2.5 in Lianyungang City, and analyze the sources of PAHs pollution, and to evaluate the health risks of PAHs in different seasons. Methods PM2.5 samples were collected regularly from January 2019 to December 2023, and 16 types of PAHs were determined by HPLC. Kruskal-Wallis H test was used to compare the concentrations of PM2.5 and PAHs in different years and seasons. The source of PAHs was analyzed by characteristic ratio and principal component analysis (PCA). Health risks were assessed using the BaP equivalent method and the incremental lifetime cancer risk (ILCR) model. Results The annual exceedance rates of PM_2.5 and BaP in Lianyungang showed a decreasing trend from 2019 to 2023. PM_2.5, total PAHs and PAHs monomers (except Ace, Flu and Acy) all showed significant seasonal differences, with the highest concentration in winter (P<0.001). The average proportion of 4-ring PAHs was the highest and the average proportion of 2-ring PAHs was the lowest. The proportion of 5-6 ring PAHs was relatively high in winter and spring. PM2.5and PAHs were negatively correlated with temperature, relative humidity and precipitation, and were positively correlated with atmospheric pressure. PM_2.5 was negatively correlated with wind speed, while some PAHs monomers were positively correlated with wind speed. The characteristic ratio and PCA results showed that the main sources of PAHs in Lianyungang City were mixed sources of road dust and vehicle emissions, oil pollution sources and biomass combustion sources. The results of ILCR showed that the highest risk was found in adults, with males slightly higher than females. In Lianyungang, the maximum value of ILCR in winter was more than 10-6 in people over 9 years old. Conclusion The main sources of PAHs in PM_2.5 in Lianyungang City are mixed sources of road dust and vehicle emissions, oil pollution sources, and biomass combustion sources. Under the current exposure level of PAHs in PM_2.5, residents have a certain potential carcinogenic risk.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

To introduce and analyze guideline terminology related to clinical question formulation, evidence retrieval and appraisal, and recommendation development.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

As the brain's resident immune cells, microglia perform crucial functions such as phagocytosis, neuronal network maintenance, and injury restoration by adopting various phenotypes. Dynamic imaging of these phenotypes is essential for accessing brain diseases and therapeutic responses. Although numerous probes are available for imaging pro-inflammatory microglia, no PET tracers have been developed specifically to visualize anti-inflammatory microglia. In this study, we present an ¹⁸F-labeled PET tracer (QTFT) that targets the P2Y₁₂, a receptor highly expressed on anti-inflammatory microglia. [¹⁸F]QTFT exhibited high binding affinity to the P2Y₁₂ (14.43 nmol/L) and superior blood-brain barrier permeability compared to other candidates. Micro-PET imaging in IL-4-induced neuroinflammation models showed higher [¹⁸F]QTFT uptake in lesions compared to the contralateral normal brain tissues. Importantly, this specific uptake could be blocked by QTFT or a P2Y₁₂ antagonist. Furthermore, [¹⁸F]QTFT visualized brain lesions in mouse models of epilepsy, glioma, and aging by targeting the aberrantly expressed P2Y₁₂ in anti-inflammatory microglia. In a pilot clinical study, [¹⁸F]QTFT successfully located epileptic foci, showing enhanced radioactive signals in a patient with epilepsy. Collectively, these studies suggest that [¹⁸F]QTFT could serve as a valuable diagnostic tool for imaging various brain disorders by targeting P2Y₁₂ overexpressed in anti-inflammatory microglia.