BACKGROUND:Stress-induced damage to hippocampal neurons may underlie abnormalities in neuronal structure and function,ultimately leading to mood disorders.G protein-coupled receptors in brain tissue play an important role in mood regulation.OBJECTIVE:To analyze the mechanism of depression-like behavior in chronic social defeat stress mice based on high-throughput sequencing and bioinformatics analysis.METHODS:C57BL/6J mice were randomly divided into control group and model group.There was no special treatment in the control group,while a mouse model of chronic social defeat stress was established in the model group.Depression-like behavior was assessed through the sucrose preference test,tail suspension test,and forced swim test.Anxiety behavior was evaluated using the elevated plus-maze,while social behavior was measured through the social interaction test.Cognitive function was assessed with the Y-maze spontaneous alternation test.Immunofluorescence staining was performed to quantify microglia markers in the mouse hippocampus,and Nissl staining was used to examine neuronal damage in mice.High-throughput sequencing was used to identify differentially expressed genes and gene enrichment in the mouse hippocampus,and qPCR was used to measure the expression of G protein-coupled receptors in the mouse hippocampus.RESULTS AND CONCLUSION:(1)Compared with the control group,chronic social defeat stress mice showed significant behavioral impairments,including increased anxiety,depression,and cognitive deficits.(2)Additionally,the Nissl body light density in hippocampal neurons was significantly reduced in chronic social defeat stress mice.(3)Sequencing results revealed synaptic damage in the neurons after chronic social defeat stress.Microglia activation was also markedly increased in the hippocampus of CSDS mice.Furthermore,the expression of G protein-coupled receptors in the hippocampus was significantly higher in chronic social defeat stress mice compared with the control group.These findings suggest that chronic social defeat stress induces anxiety,depression,and cognitive deficits in mice,accompanied by neuropathological changes in the hippocampus,and that altered G protein-coupled receptors expression may play a key role in these behavioral and neuropathological changes.

Breast cancer has become the malignant tumor with the highest incidence rate among women， seriously threatening the life and health of women all over the world. The pathogenic factors and development mechanisms of breast cancer are complex and diverse. The development of breast cells from ordinary hyperplasia to atypical hyperplasia， and from pre-cancerous lesions to cancerous lesions， is a long-term progressive process. Therefore， early screening and prevention of breast cancer is particularly important. Western medicine has a relatively mature treatment program for breast cancer， which is mainly based on surgery and systemic treatment， whereas the ensuing complications and adverse reactions often bring a heavy burden to patients. For the precancerous lesions of breast cancer， surgery is also the mainstay of treatment. In recent years， traditional Chinese medicine （TCM） has increasingly highlighted its advantages in the prevention and treatment of breast cancer. Increasing studies have shown that in the prevention and treatment of breast cancer and pre-cancerous lesions， TCM compound prescriptions， single herbs or herb pairs， and active components are able to regulate a variety of intracellular signaling pathways through multi-targets to inhibit the proliferation and invasion， promote the apoptosis and autophagy of tumor cells， and regulate the cell cycle and the immune microenvironment， thus exerting anti-tumor effects. At the same time， they can significantly attenuate the toxic side effects of radiotherapy and drug resistance of patients. However， the specific mechanisms of TCM in the prevention and treatment of breast cancer and precancerous lesions have not been fully clarified. The available studies are tanglesome regarding the TCM inhibition of tumor development through the regulation of classical signaling pathways such as phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR）， Wnt/β-catenin， and Notch， which still need to be verified by a large number of clinical and experimental studies. Therefore， this paper reviews the research progress in the prevention and treatment of breast cancer and precancerous lesions by TCM through interfering with the relevant signaling pathways in recent years， aiming to summarize the possible mechanisms of TCM in the prevention and treatment of breast cancer and provide references for subsequent studies.

BACKGROUND:Stress-induced damage to hippocampal neurons may underlie abnormalities in neuronal structure and function,ultimately leading to mood disorders.G protein-coupled receptors in brain tissue play an important role in mood regulation.OBJECTIVE:To analyze the mechanism of depression-like behavior in chronic social defeat stress mice based on high-throughput sequencing and bioinformatics analysis.METHODS:C57BL/6J mice were randomly divided into control group and model group.There was no special treatment in the control group,while a mouse model of chronic social defeat stress was established in the model group.Depression-like behavior was assessed through the sucrose preference test,tail suspension test,and forced swim test.Anxiety behavior was evaluated using the elevated plus-maze,while social behavior was measured through the social interaction test.Cognitive function was assessed with the Y-maze spontaneous alternation test.Immunofluorescence staining was performed to quantify microglia markers in the mouse hippocampus,and Nissl staining was used to examine neuronal damage in mice.High-throughput sequencing was used to identify differentially expressed genes and gene enrichment in the mouse hippocampus,and qPCR was used to measure the expression of G protein-coupled receptors in the mouse hippocampus.RESULTS AND CONCLUSION:(1)Compared with the control group,chronic social defeat stress mice showed significant behavioral impairments,including increased anxiety,depression,and cognitive deficits.(2)Additionally,the Nissl body light density in hippocampal neurons was significantly reduced in chronic social defeat stress mice.(3)Sequencing results revealed synaptic damage in the neurons after chronic social defeat stress.Microglia activation was also markedly increased in the hippocampus of CSDS mice.Furthermore,the expression of G protein-coupled receptors in the hippocampus was significantly higher in chronic social defeat stress mice compared with the control group.These findings suggest that chronic social defeat stress induces anxiety,depression,and cognitive deficits in mice,accompanied by neuropathological changes in the hippocampus,and that altered G protein-coupled receptors expression may play a key role in these behavioral and neuropathological changes.

Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72％by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.

Background:Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials.Microbial agents,as environmentally friendly and efficient plant growth promoters and soil conditioners,have increasingly attracted attention in eco-agriculture research.Objective:Our understanding remains limited regarding how the application of microbial agents,alone or in combination,affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials.Methods:In this study,Epimedium pubescens Maxim.was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis)applied individually and in combination on plant growth and the accumulation of bioactive components.Additionally,this study explored the relationship between the rhizosphere microbiome and plant development.Results:The application of microbial agents increased the yield of E.pubescens leaves by 20.30％to 33.66％and enhanced the total flavonol glycosides content by 11.40％to 29.94％.Meanwhile,microbial treatments reshaped the rhizosphere microbiome,promoted the enrichment of beneficial microorganisms(e.g.,Frankia and Paenibacillus),suppressed phytopathogenic fungi such as Didymella and Scytalidium,and enhanced the stability of the soil microbial co-occurrence network.The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumula-tion of bioactive components by modulating the soil microbiome.Conclusion:These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere micro-biomes as mediated by microbial agents.They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Objective To explore the value of combined ultrasound parameters, including the hepatorenal index (HRI) and renal resistance index (RRI), with cystatin C (CysC) in monitoring early acute kidney injury (AKI) after liver transplantation. Methods Perioperative data from 121 liver transplant recipients who received organs from donation after brain death were collected. The HRI and RRI of the recipients were measured on postoperative days 1-7 and at 1 month, and the CysC levels were measured on postoperative day 1. The recipients were divided into the AKI group (n=53) and the non-AKI group (n=68) based on whether AKI occurred within 7 days after operation. The data of the two groups were compared, and the ultrasound parameters before and after recovery in the AKI group were analyzed. The value of combined HRI, RRI and CysC in monitoring AKI was also analyzed. Results AKI occurred in 53 recipients, with an incidence rate of 43.8%, including 30 cases of stage 1, 18 cases of stage 2, and 5 cases of stage 3. Among them, 49 cases occurred on postoperative day 1, and 4 cases occurred on postoperative day 2. Of these, 43 cases recovered within 7 days after surgery, 8 cases recovered within 2 months after surgery, 1 case was lost to follow-up, and 1 case received renal replacement therapy. The body mass index and preoperative CysC levels were higher in the AKI group than in the non-AKI group, and the operative time was longer in the AKI group than in the non-AKI group (all P < 0.05). The HRI on postoperative day 1 was lower in the AKI group than in the non-AKI group, while the RRI and CysC levels were higher (all P < 0.05). When AKI occurred, the HRI was lower than the baseline level, and the RRI was higher than the baseline level. As AKI recovered, the HRI gradually increased, and the RRI gradually decreased. The receiver operating characteristic curve analysis showed that the sensitivity and specificity of HRI ≤ 1.12 for predicting AKI were 0.623 and 0.878, respectively, with an area under the curve (AUC) of 0.801. The sensitivity and specificity of RRI ≥ 0.65 for predicting AKI were 0.878 and 0.676, respectively, with an AUC of 0.825. The sensitivity and specificity of CysC ≥ 1.38 mg/L for predicting AKI were 0.736 and 0.882, respectively, with an AUC of 0.851 (all P<0.01). The combination of HRI and CysC (AUC=0.897, P<0.01), RRI and CysC (AUC=0.910, P<0.01), and all three parameters combined (AUC=0.934, P<0.01) were more effective than using each parameter alone. Conclusions HRI and RRI may be used to monitor the occurrence and recovery of early AKI after liver transplantation. The combination of these two parameters with CysC has a high application value in monitoring early AKI after liver transplantation.

AIM: To assess the effectiveness of selective laser trabeculoplasty(SLT)in the treatment of primary open angle glaucoma(POAG).METHODS:Totally 24 patients(33 eyes)with POAG who had poor control of intraocular pressure(IOP)from June 2022 to December 2023 were included in this retrospective study, and all of them were treated with SLT. Furthermore, the IOP, mean deviation(MD), mean sensitivity(MS), and the thickness and vascular density(VD)of optic disc nerve layer were compared after treatment. RESULTS: There were significant reducion in IOP at 1, 3, 6, 12 mo after treatment(all P<0.001). There were no statistically significant differences in MD and MS before treatment and at 6 and 12 mo after treatment(all P>0.05), and there were no statistical significant differences in the thickness and VD of optic disc(all P>0.05).CONCLUSION: SLT can significantly reduce IOP in POAG patients in the short term, without damaging the visual field and optic disc nerves, while the effectiveness of SLT decreases over time.

This article systematically analyzes the historical evolution of the name， origin， quality evaluation， harvesting， processing and other aspects of Picrorhizae Rhizoma by referring to the medical books， prescription books， and other documents of the past dynasties， combined with relevant modern research materials， in order to provide a basis for the development and utilization of famous classical formulas containing this medicinal herb. The research results indicate that Picrorhizae Rhizoma was first recorded in New Revised Materia Medica from the Tang dynasty. Throughout history， Huhuanglian has been used as its official name， and there are also aliases such as Gehu Luze， Jiahuanglian and Hulian. The main source of past dynasties is the the rhizomes of Picrorhiza kurrooa and P. scrophulariiflora. In ancient times， Picrorhizae Rhizoma was mainly imported by foreign traders via Guangzhou and other regions， and also produced in China， mainly in Xizang. In ancient times， it was harvested and dried in early August of the lunar calendar， while in modern times， it is mostly harvested from July to September， with the best quality being those with thick and crispy rhizomes without impurities， and bitter taste. Throughout history， Picrorhizae Rhizoma was collected， washed， sliced， and dried before being used as a raw material for medicine， it has a bitter and cold taste， mainly used to treat bone steaming， hot flashes， infantile chancre fever， and dysentery. There is no significant difference in taste and efficacy between ancient and modern times. Based on the research results， it is recommended that the rhizomes of P. scrophulariiflora in the 2020 edition of Chinese Pharmacopoeia， or the rhizomes of P. kurrooa， can be used in famous classical formulas containing this medicinal herb， which can be processed according to the processing requirements marked by the original formula. For those without clear processing requirements， the dried raw products are used as medicine.

Stroke ranks as the third leading cause of death and the fourth leading cause of disability worldwide. Its high disability rate and prolonged recovery period not only severely impact patients' quality of life but also impose a significant burden on families and society. Primary prevention is the cornerstone of stroke control, as early intervention on risk factors can effectively reduce its incidence. Therefore, the development of predictive models for first-ever stroke risk holds substantial clinical value. In recent years, advancements in big data and artificial intelligence technologies have opened new avenues for stroke risk prediction. This article reviews the current research status of traditional methods and machine learning models in predicting first-ever stroke risk and outlines future development trends from three perspectives: First, emphasis should be placed on technological innovation by incorporating advanced algorithms such as deep learning and large models to further enhance the accuracy of predictive models. Second, there is a need to diversify data types and optimize model architectures to construct more comprehensive and precise predictive models. Lastly, particular attention should be given to the clinical validation of models in real-world settings. This not only enhances the robustness and generalizability of the models but also promotes physicians' understanding of predictive models, which is crucial for their application and dissemination.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.