Depression is a common mental disorder that falls under the category of "stagnation syndrome" in traditional Chinese medicine （TCM）. Its complex pathogenesis poses challenges for the development of novel therapeutic agents. Currently， clinically used antidepressants are often accompanied by significant side effects， and statistics show that about one-third of patients do not respond to these medications. TCM demonstrates advantages in the treatment of depression through multi-target， multi-pathway and multi-mechanistic approaches. Pinelliae Rhizoma， a phlegm-resolving herb， exhibits effects such as drying dampness and resolving phlegm， as well as eliminating stuffiness and reducing masses. The characteristics of harmonizing Yin and Yang and resolving stagnation in the middle energizer align precisely with the pathogenesis of depression syndrome， demonstrating therapeutic efficacy in affected patients. Literature studies have found that the active ingredients of Pinelliae Rhizoma， such as cavidine， baicalein， β-sitosterol， as well as Pinelliae Rhizoma herb pairs， such as Pinelliae Rhizoma-Magnoliae Officinalis Cortex， Pinelliae Rhizoma-husked sorghum， Pinelliae Rhizoma-Prunellae Spica， exhibit significant antidepressant effects. Furthermore， TCM formulas containing Pinelliae Rhizoma as the principal therapeutic agent， such as Banxia Xiexin Tang， Banxia Houpo Tang， and Wendan Tang， as well as formulas incorporating Pinelliae Rhizoma like compound Xiaochaihu Tang， Chaihu Jia Longgu Muli Tang， and Erchen Tang， have also demonstrated favorable antidepressant efficacy. The antidepressant mechanism of these agents may involve modulation of 5-hydroxytryptamine （5-HT） and dopamine （DA） levels， up-regulation of brain-derived neurotrophic factor （BDNF） expression， regulation of the hypothalamus-pituitary-adrenal （HPA） axis， reduction of oxidative stress， modulation of nuclear transcription factor-κB （NF-κB） signaling pathway， and inhibition of microglia-mediated inflammatory responses. This review summarized the antidepressant mechanisms and clinical applications of the active components， herb pairs， and TCM formulas containing Pinelliae Rhizoma， aiming to provide a reference for modern research on the use of Pinelliae Rhizoma in antidepressant therapy.

Aim To examine the pathogenesis of disul-fide death gene in vascular dementia(VD)by bioin-formatics analysis of disulfide death differentially ex-pressed genes(DEGs)combined with experimental verification.Methods The death DEGs of disulfide were screened and their correlation was analyzed.The VD patients data in the data set were analyzed by clus-tering and typing and gene set variation.The clustering risk of DEGs was tested with a nomogram model,and the optimal learning model was predicted.After the es-tablishment of VD rat model,water maze test,HE stai-ning and RT-qPCR detection were performed to verify the results of health information.Results Four DEGs including SLC7A11 were obtained,which had antago-nistic or synergistic interaction with each other.The genetic data could be divided into two subtypes with significant differences.After typing,VD disulfide DEGs were mainly concentrated in GnRH signaling pathways.The accuracy of the nomogram prediction model was high.Generalized linear was the best ma-chine learning model.Compared with the sham opera-tion group,the escape latency of rats in the model group was prolonged,the number of crossing platforms decreased,the relative mRNA expression levels of Slc3a2 and Slc7a11 decreased,and LRPPRC in-creased.Conclusions SLC7A11 and other disulfide death DEGs and its related GnRH signaling pathway may be an important part of the pathogenesis of VD di-sulfide death.SLC3A2,LRPPRC and SLC7A11 can be used as characteristic genes in the regulation of VD by disulfide death,which may affect VD progression through the regulation of disulfide death.

Isoflavones which mainly distributed in leguminous plants have plenty of health benefits.Isoflavone synthase(IFS)is a membrane-associated cytochrome P450 enzyme(CYP450)which carries out the unique aryl-ring migration and hydroxylation.So far,few crystal structures of plant P450s have been obtained.We determined the crystal structure of IFS from Medicago truncatula at 1.9 ? by MAD method using a selenomethionine substituted crystal and conducted molecular docking and mutagenesis study.The structure of IFS complexed with imidazole exhibits the helix Ⅰa-loop-helix Ⅰβ motif which cor-responds to helix Ⅰ of other P450s.Compared with structures of common P450s,IFS/imidazole structure contains an extra domain,i.e.,the γ-domain.The structure reveals a homodimer in which the γ-domain of one molecule interacts with the β-domain of another.The plane of heme group makes an angle of ap-proximately 40° with the helix Ⅰa-loop-helix Ⅰβ motif.Molecular docking combined with mutagenesis study suggested that Trp-128 and Asp-300 might play important roles in substrate binding and recogni-tion.Phe-301,Ser-303 and Gly-305 from the helix Ⅰa-loop-helix Ⅰβ motif may play important roles in the aryl-ring migration.These novel structural features reveal insights into the unique reaction mechanism of IFS and provide a basis for engineering IFS in leguminous crops for health purpose.

AIM To study the chemical constituents from Inula japonica Thunb.and their anti-asthmatic activity.METHODS Separation and purification were performed using silica gel and Sephadex LH-20,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The effect of compounds on the release rate of β-Hex was evaluated by substrate coloration method.RESULTS Twenty-three compounds were isolated and identified as dehydrodontic acid(1),vitexin(2),alternariol(3),globuxanthone(4),1,3,6,7-tetrahydroxyxanthone(5),hydroxyhydrolapachol(6),isoscopoletin(7),elephanmollen(8),benzoylcholine(9),hoconobiflavone(10),clovandiol(11),hydroxydihydrobovolide(12),5,7-dihydroxycoumarin(13),scopoletin(14),orlichenol glucoside(15),urolignoside(16),9-angeloyloxythymol(17),6,3′,4′-trihydroxyaurone(18),flufuran(19),sweroside(20),guajadial(21),5,7,4′-trimethoxy-4-phenylcoumarin(22),dibutylphthalate(23).After intervention with compounds 9 and 16,the release rates of β-Hex were(56.64±2.37)％and(58.07±2.29)％,respectively.CONCLUSION Compounds 1-23 are isolated from Ⅰ.japonica for the first time.Compounds 9 and 16 have anti-asthmatic activity.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

OBJECTIVE: To develop and validate a nomogram model for predicting 30-day mortality among elderly patients with sepsis-associated liver dysfunction (SALD), to identify high-risk patients and improve prognosis. METHODS: A retrospective cohort study was conducted using data extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database for elderly patients with SALD who were first admitted to the intensive care unit (ICU) of Beth Israel Deaconess Medical Center between 2008 and 2019, including basic characteristics, severity scores, underlying diseases, infection foci, 24-hour vital signs, initial laboratory indicators, 24-hour complications, and prognosis related indicators. Patients were randomly assigned to training group and validation group in a ratio of 7 : 3. The training group used the LASSO regression analysis, as well as multivariate Logistic regression analysis to screen for independent risk factors for 30-day mortality. A nomogram prediction model was constructed, and receiver operator characteristic curve (ROC curve), calibration curves, and decision curve analysis (DCA) were used to evaluate the model, and validate the model using the validation cohort. RESULTS: A total of 630 elderly patients with SLAD were included in the study, including 441 in the training group and 189 in the validation group. Oxford acute severity of illness score (OASIS) for training group [odds ratio (OR) = 1.060, 95% confidence interval (95%CI) was 1.034-1.086], 24-hour pulse oxygen saturation (SpO₂; OR = 0.876, 95%CI was 0.797-0.962), initial mean corpuscular volume (MCV; OR = 1.043, 95%CI was 1.009-1.077), initial red blood cell distribution width (RDW; OR = 1.237, 95%CI was 1.123-1.362), initial blood glucose (OR = 1.008, 95%CI was 1.004-1.013), and initial aspartate aminotransferase (AST; OR = 1.000, 95%CI was 1.000-1.001) were independent risk factors for 30-day mortality in patients (all P < 0.05). Based on the above variables, a nomogram model was constructed, and the ROC curve showed that the area under the curve (AUC) of the model in the training group was 0.757 (95%CI was 0.712-0.803), with a sensitivity of 65.05% and a specificity of 74.90%; the AUC of the model in the validation group was 0.712 (95%CI was 0.631-0.792), with a sensitivity of 58.67% and a specificity of 81.58%. The calibration curves of the training and validation groups show that both the fitted curves were close to the standard curves. The Hosmer-Lemeshow test: the training group (χ ² = 6.729, P = 0.566), the validation group (χ ² = 13.889, P = 0.085), indicating that the model can fit the observed data well. The DCA curve shows that when the threshold probability of the training group was 16% to 94% and the threshold probability of the validation group was 27% to 99%, the net benefit of the model was good. CONCLUSIONS OASIS, 24-hour SpO₂, initial MCV, initial RDW, initial blood glucose and initial AST are independent risk factors for 30-day mortality in elderly patients with SALD. The nomogram based on these six variables demonstrates good predictive performance.
Humans ; Sepsis/complications* ; Retrospective Studies ; Nomograms ; Aged ; Prognosis ; Risk Factors ; Liver Diseases/mortality* ; Intensive Care Units ; ROC Curve ; Male ; Female ; Logistic Models

Based on the pharmacokinetics theory, this study investigated the pharmacokinetic characteristics of albiflorin, paeoniflorin, wogonoside, and wogonin in normal and febrile rats and summarized absorption and elimination rules of Dayuanyin in them to provide reference for further development and clinical application of Dayuanyin. Blood samples were taken from the fundus venous plexus of normal and model rats after intragastric administration of Dayuanyin at different time points. The concentration of each substance in blood was determined by ultra performance liquid chromatography-triple quadrupole mass spectrometry(UPLC-MS/MS) technique at different time points. DAS 2.0, a piece of pharmacokinetics software, was used to calculate the pharmacokinetic parameters of each component. The results show that the 4 components had good linear relationship in their respective ranges, and the results of methodological investigation met the requirements. The pharmacokinetic parameters of C_(max), T_(max), t_(1/2), AUC_(0-t), AUC_(0-∞), and MRT_(0-t) were calculated by the DAS 2.0 non-compartmental model. Compared with those in the normal group, C_(max) and AUC_(0-t) of the 4 components in the model group were significantly increased. There were significant differences in the pharmacokinetic characteristics between the normal and model groups, suggesting that the absorption and elimination of Dayuanyin may be affected by the changes of internal environment of the body in different physiological states.
Animals ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Fever/metabolism* ; Tandem Mass Spectrometry ; Chromatography, High Pressure Liquid ; Glucosides/pharmacokinetics* ; Monoterpenes

Based on the ultra performance liquid chromatography-quadrupole Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology, combined with related literature, databases, and reference material information, this study qualitatively analyzed the components of Dayuanyin in the tissue of rats after gavage and employed molecular docking technology to predict the rationality of the mechanism behind the antipyretic effect of the in vivo components in Dayuanyin. A total of 21, 26, 20, 21, 14, and 31 prototype components and 3, 16, 3, 7, 5, and 24 metabolites were identified from the heart, liver, spleen, lung, kidney, and hypothalamus of the rats, respectively, and the binding ability of key components and targets was further verified by molecular docking. The results showed that all components had good binding ability with targets. The established UPLC-Q-Exactive Orbitrap-MS could effectively and quickly identify the Dayuanyin components distributed in tissue and preliminarily identify their metabolites. Many components were identified in the hypothalamus, which suggested that the components delivered to the brain should be focused on in the study on Dayuanyin in the treatment of febrile diseases. The molecular docking technology was used to predict the rationality of the mechanism behind its antipyretic effect, which lays the foundation for the clarification of the material basis and action mechanism of Dayuanyin, the development of new preparations, and the prediction of quality markers.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Molecular Docking Simulation ; Male ; Antipyretics/metabolism* ; Rats, Sprague-Dawley ; Tissue Distribution ; Mass Spectrometry ; Chromatography, High Pressure Liquid ; Hypothalamus/metabolism*

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.