Depression is a common psychiatric disorder characterized by persistent low mood or mental disorders. Current treatments primarily focus on regulating neurotransmitter levels， but their effectiveness is limited. The mechanisms underlying its onset are complex， and there is no unified consensus. Abnormal signaling pathway transmission plays a crucial role in the development of depression， involving multiple pathways， including Toll-like receptor 4/nucleotide-binding oligomerization domain-like receptor protein 3 （TLR4/NLRP3）， nuclear factor-κB （NF-κB）， Janus kinase/signal transducer and activator of transcription （JAK/STAT）， mitogen-activated protein kinase/extracellular signal-regulated kinase （MAPK/ERK）， brain-derived neurotrophic factor/tyrosine kinase receptor B （BDNF/TrkB）， cyclic AMP/protein kinase A/cAMP response element-binding protein （cAMP/PKA/CREB）， and others. Traditional Chinese medicine（TCM） is based on a holistic approach and the principle of treatment based on the differentiation of syndromes， regulating the balance of multiple systems and organ functions from a macroscopic perspective. This approach has shown unique advantages in the treatment of depression. TCM attributes the onset of depression to dysfunction of the organ systems， involving liver Qi stagnation， heart spirit deficiency， kidney essence depletion， and spleen dysfunction. TCM compound treatments focus on soothing the liver， strengthening the spleen， calming the heart， and replenishing essence， with formulas such as Xiaoyaosan， Zishui Qinggan Yin， and Chahu Jia Guizhi Longgu Muli Tang. The active components of Chinese herbs mainly aim to tonify and regulate Qi， such as salidroside， ginsenoside Rb₁， astragaloside， and muscone. External TCM treatments， primarily acupuncture， aim to open the orifices and invigorate the spirit. Acupoints such as Baihui， Shenting， and Yintang are commonly used. Additionally， massage and moxibustion therapy can intervene in depression by regulating signaling pathways. This article reviews the core role of signaling pathways in the development of depression and the mechanism of TCM regulation of signaling pathways to intervene in depression， aiming to discover new therapeutic approaches that can improve the symptoms of depressed patients.

As an important protein synthesized by the liver， albumin is one of the most important markers for liver function， and its structure and function change with the progression of liver injury. Latest studies have shown that albumin in the disease state is not only reduced in quantity， but also damaged in quality， and thus the concept of “effective albumin” was proposed. This article elaborates on the research advances in the physiological structure and function of albumin， the changes of physiological function in the disease state， and the research advances in effective albumin， so as to explore precise strategies for the clinical application of albumin.

OBJECTIVE To explore the pharmacokinetic characteristics of 3 blood-absorbed components of Xiangshao sanjie oral liquid in rats with hyperplasia of mammary gland （HMG）. METHODS Female SD rats were divided into control group and HMG group according to body weight， with 6 rats in each group. The HMG group was given estrogen+progesterone to construct HMG model. After modeling， two groups were given 1.485 g/kg of Xiangshao sanjie oral liquid （calculated by crude drug） intragastrically， once a day， for 7 consecutive days. Blood samples were collected before the first administration （0 h）， and at 5， 15， 30 minutes and 1， 2， 4， 8， 12， 24 hours after the last administration， respectively. Using chlorzoxazone as the internal standard， the plasma concentrations of ferulic acid， paeoniflorin and rosmarinic acid in rats were detected by UPLC-Q/TOF-MS. The pharmacokinetic parameters [area under the drug time curve （AUC0－24 h， AUC0－∞）， mean residence time （MRT0－∞）， half-life （t1/2）， peak time （tmax）， peak concentration （cmax）] were calculated by the non-atrioventricular model using Phoenix WinNonlin 8.1 software. RESULTS Compared with the control group， the AUC0－24 h， AUC0－∞ and cmax of ferulic acid in the HMG group were significantly increased （P＜0.05）； the AUC0－24 h， AUC0－∞ ， MRT0－∞ ， t1/2 and cmax of paeoniflorin increased， but there was no significant difference between 2 groups （P＞0.05）； the AUC0－24 h and MRT0-∞ of rosmarinic acid were significantly increased or prolonged （P＜0.05）. C ONCLUSIONS In HMG model rats， the exposure of ferulic acid， paeoniflorin and rosmarinic acid in Xiangshao sanjie oral liquid all increase， and the retention time of rosmarinic acid is significantly prolonged.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Objective To explore the nephrotoxic effects of exposure to perfluorobutanoic acid (PFBA) and its mechanism in mice, with a particular focus on analyzing the changes in kidney metabolism and their potential implications. Methods The specific pathogen free C57BL/6 mice were randomly divided into control group, low-dose group, and high-dose group, with 10 mice in each group. Mice in the three groups received intragastric administration of PFBA solution at doses of 0, 35 and 350 mg/kg body weight, once per day for seven consecutive days. The histopathological changes of kidneys of mice in these three groups were evaluated. Metabolomic profiling of mouse kidneys was performed using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Differentially accumulated metabolites (DAMs) were identified based on the Human Metabolome Database, and related metabolic pathways were analyzed through MetaboAnalyst 6.0 and Kyoto Encyclopedia of Genes and Genomes (KEGG). Results Histopathological analysis of kidneys showed that the renal pelvis mucosa of mice in the low-dose group presented focal mild inflammatory changes without marked structural damage, whereas mice in the high-dose group showed severe inflammation and partial destruction of renal structure. The kidney coefficient of mice in both low-dose group and the high-dose group decreased (both P<0.05), and the Paller scores of renal tissues increased (both P<0.05) compared with that in the control group. The Paller score of mouse renal tissue in the high-dose group was higher than that in the low-dose group (P<0.05). Metabolomic profiling identified 46 DAMs (26 upregulated, 20 downregulated) in the low-dose group and 104 DAMs (54 upregulated, 50 downregulated) in the high-dose group, with 26 shared DAMs between the two dose groups. KEGG pathway analysis revealed that DAMs were mainly involved in metabolic pathways such as glycerophospholipid metabolism, glycerolipid metabolism, sphingolipid and steroid hormone synthesis. Conclusion Acute exposure to PFBA can cause kidney injury in mice. Lipid metabolism pathways such as glycerophospholipid and sphingolipid metabolism is involved in the development of acute renal toxicity of PFBA.

Objective To construct a nomogram model for predicting lower extremity deep vein throm-bosis(DVT)during hospitalization in the patients undergoing mechanical thrombectomy due to acute ische-mic stroke.Methods A total of 901 patients with acute anterior circulation large vessel occlusion undergoing mechanical thrombectomy in the hospital from January 1,2017 to January 1,2024 were selected as the study subjects and divided into the lower extremity DVT group(n=112)and non-DVT group(n=789)according to whether DVT occurred after surgery.The observation indicators included the clinically relevant data,perio-perative related indicators and related laboratory indicators.The multivariate logistic regression was used to analyze the relevant influencing factors,and then the nomogram model was established.The receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to analyze the predictive efficiency of the model.The clinical benefit of the predictive model was assessed by the clinical decision curve analysis(DCA)curve.Results There were statistically significant differences in the age,NIHSS score at admission,history of diabetes mellitus,history of smoking and history of DVT between the two groups(P<0.05).There were statistically significant differences in the time from onset to femoral artery puncture,time from onset to admission,time from femoral artery puncture to revascularization and postoperative complicating pul-monary infection between the two groups(P<0.05).There were statistically significant differences in D-di-mer,venous blood glucose and PLT at admission between the two groups(P<0.05).The multivariate logis-tic regression analysis results showed that the NIHSS score at admission,diabetes history,age,D-dimer,time from onset to femoral artery puncture and postoperative complicating pulmonary infection were the independ-ent influencing factors for lower extremity DVT during hospitalization in the patients with acute ischemic stroke treated with mechanical thrombectomy(P<0.05).The ROC curve and Bootstrap method verification results all showed that the nomogram predictive ability was strong.The DCA curve showed that when the threshold value was 0.12-0.96,the clinical benefit and applicability of the model were the best.Conclusion The constructed nomogram model can better predict the clinical outcome of the patients,and has a wide range of clinical applicability.

Dent disease is a rare X-linked recessive renal tubular disease characterized by low molecular weight proteinuria，hypercalcemia and nephrocalcinosis. It is also a major cause of tubular proteinuria in children. According to different causative genes，Dent disease can be divided into three types：type 1 is caused by mutations in the CLCN5 gene，accounting for about 60%-70%；type 2 is caused by mutations in the OCRL gene，accounting for about 15%-20%；type 3 has a similar clinical phenotype but no known pathogenic gene mutations. CLCN5 encodes the voltage-dependent 2Cl -/1H +exchange channel CIC-5，which is involved in proximal renal tubule endocytosis. Its mutations can cause a variety of proximal tubular dysfunction symptoms，mainly including low molecular weight proteinuria. The use of gene detection technology has resulted in an increase in reports on Dent disease year after year. At present，the specific mechanism underlying Dent disease remains unknown. This article reviews the research progress of CLCN5，hoping to provide new insight for the mechanism research of CLCN5 and the specific treatment of Dent disease type 1.

Objective To investigate the effects of dienogest on pain relief and inflammation in endometriosis(EMs),as well as its impact on the brain-derived neurotrophic factor(BDNF)/tropo-myosin receptor kinase B(TrkB)and nuclear factor kappa-B(NF-κB)/NOD-like receptor protein 3(NLRP3)inflammatory pathways.Methods An allograft method was used to establish an EMs rat model.The rats were randomly divided into sham-operated group(n=16),model group(n=16),low-dose dienogest group(n=16),medium-dose dienogest group(n=16)and high-dose dienogest group(n=16).After 7 days of treatment,the implantation volume and writhing response frequency were recorded.Enzyme-linked immunosorbent assay(ELISA),reverse transcription-polymerase chain reaction and Western blotting were employed to measure the expression levels of vascular endothelial growth factor(VEGF),inducible nitric oxide synthase(iNOS),interleukin(IL)-6,IL-1β and tumor necrosis factor(TNF)-α in the EMs rat models.Serum levels of BDNF,TrkB,NF-κB and NLRP3 were detected.Results Compared with model group,dinorgestrel significantly reduced ectopic endo-metrial volume and torsion response of EMs(P＜0.05).Compared with model group,dinorgestrel significantly decreased the expression of VEGF,iNOS,IL6,IL-1 β and TNF-α in EMs model(P＜0.05).In addition,compared with model group,dienogest significantly decreased the expressions of BDNF,TrkB,NF-κB and NLRP3 in ectopic endometrium(P＜0.05).Conclusion Dinorgestrel can relieve EMS-related dysmenorrhea and inflammation,and its mechanism of action may be partly mediated by BDNF/TrkB pathway and NF-κB/NLRP3 pathway.

OBJECTIVE To analyze the metabolites of Zhideke granules and speculate its metabolic pathway in rats in vivo. METHODS Male SD rats were randomly divided into blank group and administration group （Zhideke granules， 9.45 g/kg）； they were given ultrapure water or relevant medicine， twice a day， every 6-8 h， for 3 consecutive days. Serum， urine and feces samples of rats were collected， and their metabolites were identified by UPLC-Q-Exactive-MS technique after intragastric administration of Zhideke granules； their metabolic pathways were speculated. RESULTS After intragastric administration of Zhideke granules， 16 prototype components （i.g. irisflorentin， baicalin， chlorogenic acid） and 11 metabolites （i.g. hydration products of kaempferol or luteolin， methylation products of chlorogenic acid， and hydroxylation products of baicalin） were identified in serum， urine and feces of rats. Among them， 8 prototype components and 4 metabolites were identified in serum samples； 10 prototype components and 7 metabolites were identified in urine samples； 8 prototype components and 5 metabolites were identified in the fecal samples. CONCLUSIONS The metabolites of Zhideke granules in rats mainly include baicalin， irisflorentin，chlorogenic acid， and the main metabolic pathways included methylation， hydroxylation， glucuronidation.

OBJECTIVE To provide reference for basic analysis of the pharmacodynamic substance in Stahlianthus involucratus. METHODS Overall 24 SD male rats were randomly divided into blank group （purified water）， and administration group （ethanol extract of S. involucratus， 15.75 g/kg， calculated by crude drug）， with 12 rats in each group. They were given drug liquid/purified water intragastrically， twice a day， every 6-8 h， for consecutive 3 days. After medication， the blood， urine and fecal samples were collected from two groups of rats. UPLC-Q-Exactive-MS technology was used to identify the chemical constituents in the ethanol extract of S. involucratus， and metabolites in the blood， urine and fecal of rats after intragastrical administration of the ethanol extract of S. involucratus. Multivariate statistical analysis was employed to screen various serum metabolites. Metabolic pathways were analyzed by MetaboAnalyst 5.0 platform. RESULTS A total of 38 chemical constituents were identified from the ethanol extract of S. involucratus， including fourteen prototype components and three metabolites identified from 5 urine samples， nine prototype components identified from fecal samples， and ten prototype components and one metabolite identified from serum samples. A total of 71 differential metabolites were screened from two groups of rat serum samples， of which 44 differential metabolites， such as ferulic acid， glycyrrhizin， were up-regulated and 27 differential metabolites， such as arachidonic acid， phenylacetylglutamine， were down-regulated. The 71 differential metabolites were mainly enriched in 11 metabolic pathways， including phenylalanine metabolism， linoleic acid metabolism， arachidonic acid metabolism， and tryptophan metabolism. CONCLUSIONS Ferulic acid， liquiritigenin， isofraxidin and formononetin may be the material basis that directly exert pharmacological effects of S. involucratus. S. involucratus may exert anti-inflammatory effects by affecting metabolic pathways， including arachidonic acid metabolism and tryptophan metabolism.