ObjectiveTo investigate the effects of Simiaowan on intestinal barrier function and adenosine triphosphate （ATP） binding cassette transporter G2 （ABCG2） expression in hyperuricemic （HUA） rats， and elucidate its therapeutic mechanisms. MethodsForty male Sprague Dawley （SD） rats were randomized into a normal group， a model group， low-dose （282.6 mg·kg^-1） and high-dose （565.2 mg·kg^-1） Simiaowan groups， and a Benzbromarone （4.7 mg·kg^-1） group. The HUA model was established via intraperitoneal injection of potassium oxonate （ip） combined with oral gavage of hypoxanthine （ig） for 14 days. Following modeling， treatments were administered for 14 days. Samples were collected and weighed 4 h after final dosing. Blood uric acid and hepatic function were analyzed. Histopathological changes were evaluated by hematoxylin-eosin （HE） staining， and Chiu's scoring was conducted. Enzyme-linked immunosorbent assay （ELISA） quantified tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， interleukin-1β （IL-1β）， lipopolysaccharide （LPS）， diamine oxidase （DAO）， and D-lactic acid （D-LA） levels. Real-time polymerase chain reaction （Real-time PCR）， Western blot， and immunohistochemistry assessed the expression of Claudin-1， Occludin， occludens-1 （ZO-1）， and ABCG2 mRNAs and proteins. 16S rDNA amplicon sequencing characterized ileal microbiota. ResultsCompared with the normal group， the model group exhibited epithelial shedding in the ileal villus， structural disruption， infiltration of extensive inflammatory cells， and significantly elevated Chiu's scores （P<0.01）. The DAO， TNF-α， IL-6， IL-1β， LPS， and D-LA levels in the ileum were markedly increased （P<0.01）， while mRNA and protein expressions of Claudin 1， Occludin， ZO-1， and ABCG2， as well as positive staining area and proportion， were significantly reduced （P<0.01）. Compared with the model group， the Simiaowan groups at all doses showed improved epithelial damage in the ileal villus， significantly lowered Chiu's scores （P<0.01）， significantly reduced DAO， TNF-α， IL-6， IL-1β， LPS， and D-LA levels in the ileum （P<0.01）， and upregulated mRNA and protein expressions of Claudin 1， Occludin， ZO-1， and ABCG2， as well as positive staining area and proportion （P<0.01）. The 16S rDNA results showed that in the model group， the α-diversity index of the ileal microbiota was increased， and species diversity and richness were enhanced， with microbiota dysfunction observed. The community structure of the gut microbiota was significantly different from that of the normal microbiota. The abundance of probiotics was decreased， and the abundance of pathogenic bacteria was increased， with butyrate-producing bacteria showing a low abundance. In contrast， Simiaowan at all doses reduced species diversity and richness， regulated microbiota dysfunction， and promoted the shift of the structure of the gut microbiota community towards a normal one. This increased the abundance of beneficial bacteria， decreased the abundance of harmful bacteria， and restored the abundance of butyrate-producing bacteria. ConclusionSimiaowan enhances ileal uric acid excretion and further alleviates HUA by modulating the gut microbiota composition to improve the intestinal barrier and upregulate the expression of the urate transporter ABCG2 in HUA rats.

OBJECTIVE To investigate the efficacy and safety of Wuling capsules combined with fluoxetine in the treatment of adolescents with first-episode moderate-to-severe depressive disorder accompanied by insomnia. METHODS The clinical data of 476 adolescents with first-episode moderate-to-severe depression accompanied by insomnia admitted to our hospital from June 2022 to May 2025， were retrospectively collected. According to the initial treatment regimen， patients were divided into a control group （241 cases， treated with fluoxetine alone） and an observation group （235 cases， treated with Wuling capsules combined with fluoxetine）. The depression severity （Hamilton Depression Rating Scale-17 Item and the Self-Rating Depression Scale scores）， sleep quality （Pittsburgh Sleep Quality Index score， sleep latency， wake after sleep onset， total sleep time， sleep efficiency）， serum neuroendocrine indicator （cortisol） and inflammatory markers （C-reactive protein， interleukin-6） were compared between the two groups before treatment and at 4th and 8th weeks of treatment. The effective rate at 8th weeks and the occurrence of adverse drug reactions （ADRs） were also compared between the two groups. RESULTS Before treatment， there were no significant differences in depression severity， sleep quality， serum neuroendocrine indicator， and inflammatory markers between the two groups （ P ＞0.05）. At 4th and 8th weeks， both groups showed significant improvement in these indicators compared to those before treatment， with the observation group demonstrating significantly greater improvement than the control group at the corresponding time points （ P ＜0.05）. At 8th week， the eff ective rate of the observation group was 90.21%， significantly higher than 80.50% in the control group （ P ＜0.05）. The incidence of nausea， headache， fatigue， dry mouth， and palpitations， as well as the total incidence of ADRs， did not differ significantly between the two groups （ P ＞0.05）. CONCLUSIONS Wuling capsules combined with fluoxetine can significantly improve the effective rate in adolescents with first-episode moderate-to-severe depression accompanied by insomnia， accelerate the relief of depressive symptoms， improve sleep quality， and reduce serum neuroendocrine indicator and inflammatory markers， with a favorable safety profile.

Both cathartic colon （CC） and cathartic-dependent constipation （CDC） are caused by the abuse of stimulant laxatives， while their concepts are not completely the same.Starting from the disease name of CC， this article traced the origin and evolution of the concept of CC， summarizes and compared the similarities and differences between CC， CDC， and slow transit constipation （STC）， and called for strict differentiation among the three.Furthermore， this article explored the specific contents of Western medicine clinical subtypes and traditional Chinese medicine （TCM） syndrome differentiation of CDC and delved into the TCM pathogenesis of CDC according to both literature and clinical practice.The relationship between clinical subtypes and TCM syndromes was established， and the syndrome characteristics of CDC of different clinical subtypes and TCM syndromes were summarized.The recommended prescriptions for corresponding syndromes were listed.A systematic CDC diagnosis and treatment approach of "clinical subtypes-syndrome differentiation-syndrome characteristics-recommended prescriptions" was thus formed.Additionally， the paper provides an overview of current research on CDC in both Western medicine and TCM contexts， identifies future research directions， and suggests research pathways for refining and advancing CDC studies.

ObjectiveTo observe the clinical efficacy of the Yiqi Yangyin Huoxue prescription （YYHP） in the treatment of cathartic colon （CC） and its effects on fecal short-chain fatty acids （SCFAs）， and to explore the correlations among CC severity indicators and between these indicators and patient history. MethodsAccording to the inclusion and exclusion criteria， 98 patients meeting the diagnostic criteria of both traditional Chinese and Western medicine for CC with the syndrome of Qi-Yin deficiency complicated by blood stasis were randomly assigned to an observation group and a control group. The observation group received YYHP granules， while the control group received lactulose. Both medications were administered twice daily， one sachet each time， half an hour after breakfast and dinner， with a treatment course of 8 weeks. The primary constipation symptom score， Patient Assessment of Constipation Quality of Life （PAC-QOL） score， and TCM syndrome score were assessed before and after treatment and at the 8^th week after the end of treatment. The overall clinical effective rate， as well as the efficacy attenuation index and degree， were evaluated. Fecal SCFA levels were measured using gas chromatography-mass spectrometry （GC-MS）. Spearman correlation analysis was performed to explore the correlations among CC severity indicators and between these indicators and patient history. ResultsThe overall clinical effective rate in the observation group （95.83%） was higher than that in the control group （78.72%） （P<0.05）. After treatment， the total scores for primary constipation symptoms， PAC-QOL， and TCM syndromes decreased in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. The severity of all primary constipation symptoms was alleviated in both groups （P<0.05）. In terms of "excessive straining and difficult defecation"， "anal heaviness， incomplete evacuation， and bloating sensation"， "abdominal distension"， and "defecation frequency"， the observation group showed better efficacy than the control group （P<0.05）. Scores of the four PAC-QOL dimensions and the scores and severity of primary and secondary TCM symptoms were reduced in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. After treatment， acetic acid， propionic acid， butyric acid， and total SCFAs in the observation group increased significantly （P<0.05）. The efficacy attenuation index and degree in the observation group were lower than those in the control group （P<0.05）. No severe adverse reactions occurred in either group， and there was no statistically significant difference in the incidence of adverse reactions between the two groups. Positive correlations of varying degrees were observed among the total scores of primary constipation symptoms， PAC-QOL， and TCM syndromes， as well as between these scores and the history of stimulant laxative use， disease duration， and age. ConclusionYYHP can effectively alleviate the primary constipation symptoms in CC patients， improve quality of life， and ameliorate TCM syndromes， with good safety. It also has the advantage of a lower rebound degree after drug withdrawal， and its mechanism may be related to increasing fecal SCFA levels. Long-term abuse of stimulant laxatives may aggravate the severity of CC and prolong the disease course.

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.

Although teniposide(VM26)is widely used in the treatment of lymphoma,its poor water sol-ubility,low bioavailability and systemic toxicities still limit its clinical application.Nano-delivery systems are effective in increasing the bioavailability and reducing the toxicity of VM26,but there is an urgent need to overcome the problem of its non-specific targeting.Therefore,in this paper,we designed and constructed a hyaluronic acid-modified teniposide-targeted nano-delivery system(VM26-TNDS),and characterised its drug encapsulation rate,particle size and zeta potential.We also investigated the effects of VM26-TNDS on B-cell lymphoma cells with different expression of CD44 receptor,in terms of cellular targeting,inhibitory effect of proliferation,and induction of apoptosis and necrosis.The results showed that the drug encapsulation efficiency of VM26-TNDS exceeded 85％,and its liquid formulation could be stably stored at 4 ℃ for more than 6 months without precipitation.Based on CD44 receptor expression,Granta-519(high expression),Raji(medium-low expression)and SU-DHL-4(almost no expression)were screened for cellular experiments.Compared with VM26-NDS,the targeted modification could effec-tively reduce the uptake of VM26-TNDS by RAW264.7 and increase the uptake of VM26-TNDS by CD44 receptor-expressing lymphoma cells.The inhibitory proliferative effect and apoptotic necrosis-inducing a-bility of VM26-TNDS were stronger than those of VM26-NDS for Granta-519 and Raji cells,whereas there was no significant difference in the inhibitory effect on proliferation and ability to induce apoptosis and necrosis between VM26-NDS and VM26-TNDS in SU-DHL-4 cells,reflecting the targeting advantage for VM26-TNDS,as expected.However,its toxic effect on B-cell lymphoma cells only reflected the targeting advantage at some concentrations(0.25 μmol/L and 0.5 μmol/L),which met the expectation.The a-bove results indicate that a teniposide-targeted nano-delivery system,VM26-TNDS,has been successfully prepared in this study.VM26-TNDS improves the delivery efficiency of VM26 by targeting human B-cell lymphoma cells expressing the CD44 receptor,thus killing human B-cell lymphoma cells more effectively and overcoming the problem of non-specific targeting in drug delivery to improve the therapeutic effect.Its biological therapeutic effects and mechanisms still need to be proved by more in vitro and in vivo ex-perimental evidence.

Objective To investigate whether successful percutaneous coronary intervention(PCI)could improve symptoms and quality of life(QOL)in left main disease and/or 3-vessel disease patients with diabetes.Methods Patients with left main disease and/or 3-vessel disease who underwent PCI in the First Affiliated Hospital of Air Force Medical University from April 2018 to May 2021 were consecutively enrolled and subdivided into 2 groups:diabetes and no diabetes.Detailed baseline characteristics,symptoms,including dyspnea and angina,assessed with the Rose dyspnea scale(RDS),Seattle angina questionnaire(SAQ),the European quality of life-5 dimensions(EQ-5D)and 12-item short-form health survey(SF-12)questionnaire respectively,procedural details,and 1 month and 1 year follow-up data were collected.Results Among 440 left main disease and/or 3-vessel disease patients,disease was present in 176(40.00％),who had more hypertension,peripheral artery disease,and LCX lesion(all P＜0.05).The incidence of major adverse cardiovascular events(MACE)and all-cause mortality were similar between the two groups(both P＞0.05)at 1 month follow-up,while all-cause mortality in diabetes patients was significantly higher than those without diabetes at 1 year follow-up(P=0.013).Low left ventricular ejection fraction was an independent risk factor for MACE and all-cause mortality at 1 month and 1 year follow-up after successful revascularization(all P＜0.05).Most importantly,symptoms,including dyspnea and angina,and QOL were markedly improved regardless of diabetes both at 1 month and 1 year follow-up(all P＜0.05).Diabetes patients showed improved dyspnea and QOL at similar degree to the non-diabetes patients(all P＞0.05)and a more significantly relieved angina(P=0.013).Additionally,the number of chronic total occlusion(CTO)per patient was identified as an independent risk factor of dyspnea(OR 0.723,95％CI 0.525～0.997,P=0.048)and angina relief(OR 0.686,95％CI 0.473～0.995,P=0.047),and the contrast volume(OR 0.995,95％CI 0.992～0.999,P=0.008)as an independent risk factor of QOL improvement in diabetic patients.Conclusions Successful PCI is beneficial for relieving symptoms and improving quality of life in patients with diabetes who have left main disease and/or 3-vessel disease.

Objective:To analyze the epidemiological characteristics and trends of preterm births in China using medical institution survey data, thereby providing epidemiological data support for perinatal care.Methods:Based on a nationwide sampling survey on healthcare quality data from 2017 to 2022, this study included 3 547, 4 436, 4 513, 4 535, 5 068, and 5 790 medical institutions, with 7 039 107, 8 926 441, 9 006 420, 7 051 984, 7 311 862, and 7 354 062 parturient women, respectively. The overall rates of preterm birth (live births at 28 to 36 +6 weeks of gestation/overall live births) and early preterm birth (live births at 28 to <34 weeks of gestation/overall live births) were calculated at the national level, across diverse provinces, autonomous regions, municipalities and Xinjiang Production and Construction Corps, and for various levels of medical institutions. Generalized estimating equations were used to analyze the influence of maternal characteristics and medical institution characteristics on the rates of preterm birth and early preterm birth. Results:From 2017 to 2022, both the preterm birth rate and the early preterm birth rate in China showed a continuous increase. The preterm birth rate rose from 5.13% (363 036/7 079 454) in 2017 to 6.56% (487 150/7 424 734) in 2022, and the early preterm birth rate increased from 1.32% (118 021/8 971 870) in 2018 to 1.43% (106 157/7 424 734) in 2022. These rates showed an overall increasing trend in private, secondary public specialty, and general hospitals. In tertiary public specialty hospitals, these rates fluctuated around 8.0% and 2.0% from the year 2018, respectively, while in tertiary public general hospitals, these rates peaked in 2020 at 8.63% (205 570/2 381 523) and 2.19% (52 197/2 381 523), respectively. Compared with 2017, by 2022, the preterm birth rate had increased to varying degrees in all provinces, autonomous regions, municipalities and Xinjiang Production and Construction Corps, except for Henan Province [preterm birth rate in 2017 was 6.22% (27 173/437 187); preterm birth rate in 2022 was 5.83% (37 604/645 104)]. As for the early preterm birth rate, it showed a decline in Fujian, Guangdong, Guangxi, Hainan, Henan, Jiangsu, Shanghai, Xinjiang, Yunnan, and Zhejiang, but had increased to varying degrees in all other provinces , autonomous regions, municipalities and Xinjiang Production and Construction Corps across the country. The grade and location of medical institutions both had a significant impact on the preterm birth rate and early preterm birth rate (both P<0.05). For every 1% increase in the proportions of multiparous women, women of advanced maternal age, or twin pregnancies, the preterm birth rate increased by 0.014%, 0.042%, and 0.763%, and the early preterm birth rate increased by 0.004%, 0.013%, and 0.239%, respectively (all P<0.05). Conclusion:From 2017 to 2022, the preterm birth rate and early preterm birth rate in China have continued to rise, reflecting the dual challenges of changing characteristics in the childbearing population and the uneven distribution of medical and health resources faced by maternal and child healthcare in China.

The immune microenvironment plays a pivotal role in maintaining ovarian homeostasis. Polycystic ovary syndrome (PCOS), a common endocrine and metabolic disorder, is closely associated with immune microenvironment imbalance. This review systematically describes the dysregulation of innate immune cells (e.g., macrophages, natural killer cells and dendritic cells) and adaptive immune cells (e.g., Th1, Th2, Treg and Th17) in PCOS, highlighting their impacts on ovarian function, insulin resistance, and hyperandrogenemia. These findings underscore the central role of immune microenvironment disturbances in PCOS pathogenesis. Additionally, the association between gut microbiota dysbiosis and PCOS is explored, emphasizing how gut microbiota influences metabolic byproducts and hormonal levels to contribute to PCOS development. Furthermore, therapeutic strategies targeting immune microenvironment imbalance such as modulating macrophage polarization, restoring Th1/Th2 and Th17/Treg balance, and ameliorating gut microbiota dysbiosis are discussed, offering novel insights for PCOS immunotherapy. In conclusion, this review comprehensively analyzes the pathogenesis of PCOS from the perspective of the immune microenvironment, aiming to provide a theoretical foundation and reference for future research and clinical practice.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.