The interactions between microorganisms and medicinal plants are crucial to the quality improvement of medicinal plants. Medicinal plants attract microorganisms to colonize by secreting specific compounds and provide niche and nutrient support for these microorganisms, with a symbiotic network formed. These microorganisms grow in the rhizosphere, phyllosphere, and endophytic tissues of plants and significantly improve the growth performance and medicinal component accumulation of medicinal plants by promoting nutrient uptake, enhancing disease resistance, and regulating the synthesis of secondary metabolites. Microorganisms are also widely used in the ecological planting of medicinal plants, and the growth conditions of medicinal plants are optimized by simulating the microbial effects in the natural environment. The interactions between microorganisms and medicinal plants not only significantly improve the yield and quality of medicinal plants but also enhance their geoherbalism, which is in line with the concept of green agriculture and eco-friendly development. This study reviewed the research results on the interactions between medicinal plants and microorganisms in recent years and focused on the analysis of the great potential of microorganisms in optimizing the growth environment of medicinal plants, regulating the accumulation of secondary metabolites, inducing systemic resistance, and promoting the ecological planting of medicinal plants. It provides a scientific basis for the research on the interactions between medicinal plants and microorganisms, the research and development of microbial agents, and the application of microorganisms in the ecological planting of medicinal plants and is of great significance for the quality improvement of medicinal plants and the green and sustainable development of TCM resources.
Plants, Medicinal/metabolism* ; Bacteria/genetics* ; Symbiosis

Following the core outcome set standards for development(COS-STAD), this study aims to construct core outcome set(COS) for clinical research on traditional Chinese medicine(TCM) treatment of simple obesity. Firstly, a comprehensive review was conducted on the randomized controlled trial(RCT) and systematic review(SR) about TCM treatment of simple obesity that were published in Chinese and English databases to collect reported outcomes. Additional outcomes were obtained through semi-structured interviews with patients and open-ended questionnaire surveys for clinicians. All the collected outcomes were then merged and organized as an initial outcome pool, and then a preliminary list of outcomes was formed after discussion by the working group. Subsequently, two rounds of Delphi surveys were conducted with clinicians, methodology experts, and patients to score the importance of outcomes in the list. Finally, a consensus meeting was held to establish the COS for clinical research on TCM treatment of simple obesity. A total of 221 RCTs and 12 SRs were included, and after integration of supplementary outcomes, an initial outcome pool of 141 outcomes were formed. Following discussions in the steering advisory group meeting, a preliminary list of 33 outcomes was finalized, encompassing 9 domains. Through two rounds of Delphi surveys and a consensus meeting, the final COS for clinical research on TCM treatment of simple obesity was determined to include 8 outcomes: TCM symptom scores, body mass index(BMI), waist-hip ratio, waist circumference, visceral fat index, body fat rate, quality of life, and safety, which were classified into 4 domains: TCM-related outcomes, anthropometric measurements, quality of life, and safety. This study has preliminarily established a COS for clinical research on TCM treatment of simple obesity. It helps reduce the heterogeneity in the selection and reporting of outcomes in similar clinical studies, thereby improving the comparability of research results and the feasibility of meta-analysis and providing higher-level evidence support for clinical practice.
Humans ; Obesity/therapy* ; Medicine, Chinese Traditional ; Randomized Controlled Trials as Topic ; Treatment Outcome ; Drugs, Chinese Herbal/therapeutic use*

Climate and land use changes may significantly impact the habitat distribution of Gastrodia elata, an endangered traditional medicinal plant. Accurately predicting its future potential suitable habitats is crucial for its conservation and sustainable development. This study integrates current distribution data of G. elata with 56 environmental variables and uses the MaxEnt model to predict changes in its suitable habitats under current climate conditions and four future climate scenarios(SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The results show that October precipitation and December minimum temperature are key environmental factors influencing its distribution. Under the current climate, optimal habitats for G. elata are concentrated in montane forest areas in Sichuan, Yunnan, Guizhou, and Hubei, which meet the species' requirements for understory growth. Across all future scenarios, the suitable habitat of G. elata consistently shows a stable northward shift, with a steady increase in suitable areas, extending to the middle and lower reaches of the Yangtze River and the Huang-Huai region, and even expanding into Liaoning, Jilin, and southern Heilongjiang. Land use analysis, taking into account the protection of arable land and the utilization of forest resources, indicates that by 2100, under future climate conditions, arable land in medium-to high-suitability areas is expected to increase by 30%-124%. While the conversion of non-suitable forest land into suitable habitats is projected to increase by 5%-52%, the growth of medium-to high-suitability areas within forests is relatively modest, ranging from 1% to 24%. These findings highlight the need to balance agricultural expansion with forest resource conservation to ensure the long-term sustainability of G. elata and provide scientific guidance for future suitable habitat management.
Ecosystem ; China ; Climate Change ; Gastrodia/growth & development* ; Conservation of Natural Resources ; Plants, Medicinal/growth & development*

Hepatocellular carcinoma(HCC), the third leading cause of cancer-related death worldwide, is characterized by high mortality and recurrence rates. Common treatments include hepatectomy, liver transplantation, ablation therapy, interventional therapy, radiotherapy, systemic therapy, and traditional Chinese medicine(TCM). While exhibiting specific advantages, these approaches are associated with varying degrees of adverse effects. To alleviate patients' suffering and burdens, it is crucial to explore additional treatments and elucidate the pathogenesis of HCC, laying a foundation for the development of new TCM-based drugs. With emerging research on gut microbiota, it has been revealed that microbiota plays a vital role in the development of HCC by influencing intestinal barrier function, microbial metabolites, and immune regulation. TCM, with its multi-component, multi-target, and multi-pathway characteristics, has been increasingly recognized as a vital therapeutic treatment for HCC, particularly in patients at intermediate or advanced stages, by prolonging survival and improving quality of life. Recent global studies demonstrate that TCM exerts anti-HCC effects by modulating gut microbiota, restoring intestinal barrier function, regulating microbial composition and its metabolites, suppressing inflammation, and enhancing immune responses, thereby inhibiting the malignant phenotype of HCC. This review aims to elucidate the mechanisms by which gut microbiota contributes to the development and progression of HCC and highlight the regulatory effects of TCM, addressing the current gap in systematic understanding of the "TCM-gut microbiota-HCC" axis. The findings provide theoretical support for integrating TCM with western medicine in HCC treatment and promote the transition from basic research to precision clinical therapy through microbiota-targeted drug development and TCM-based interventions.
Humans ; Gastrointestinal Microbiome/drug effects* ; Carcinoma, Hepatocellular/microbiology* ; Liver Neoplasms/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Medicine, Chinese Traditional

Cardiac troponin I (cTnI), a widely used biomarker for assessing cardiovascular risk, can provide a window for the evaluation of drug-induced myocardial injury. Label-free biosensors are promising candidates for detecting cell secretomes, since they do not require labor-intensive processes. In this work, a label-free electrochemical aptasensor is developed for in situ monitoring of cardiac cell secretomes in cell culture media based on target-induced strand displacement. The aptasensing system contains an aptamer-functionalized signal nanoprobe facing trimetallic metal-organic framework nanosheets and a gold nanoparticle-based detection working electrode modified with DNA nanotetrahedron-based complementary DNA for indirect target detection. The signal nanoprobes (termed CAHA) consisted of copper-based metal-organic frameworks, AuPt nanoparticles, horseradish peroxidase, and an aptamer. When the aptasensor is exposed to cardiac cell secretomes, cTnI competitively binds to the aptamer, resulting in the release of signal nanoprobes from the biorecognition interface and electrochemical signal changes. The aptasensor exhibited rapid response times, a low detection limit of 0.31 pg/mL, and a wide linear range of 0.001-100 ng/mL. We successfully used this aptasensor to measure cTnI concentrations among secreted cardiac markers during antitumor drug treatment. In general, aptasensors can be used to monitor a variety of cardiac biomarkers in the evaluation of cardiotoxicity.

Objective To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Methods Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People’s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients’radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients’radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. Results The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = −5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. Conclusions The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.

The COVID-19 epidemic has spread to the whole world for three years and has had a serious impact on human life, health and economic activities. China's epidemic prevention and control has gone through the following stages: emergency unconventional stage, emergency normalization stage, and the transitional stage from the emergency normalization to the "Category B infectious disease treated as Category B" normalization, and achieved a major and decisive victory. The designated hospitals for prevention and control of COVID-19 epidemic in Tianjin has successfully completed its tasks in all stages of epidemic prevention and control, and has accumulated valuable experience. This article summarizes the experience of constructing a hospital infection prevention and control system during the "Category B infectious disease treated as Category A" period in designated hospital. The experience is summarized as the "Cluster" hospital infection prevention and control system, namely "three rings" outside, middle and inside, "three districts" of green, orange and red, "three things" before, during and after the event, "two-day pre-purification" and "two-director system", and "one zone" management. In emergency situations, we adopt a simplified version of the cluster hospital infection prevention and control system. In emergency situations, a simplified version of the "Cluster" hospital infection prevention and control system can be adopted. This system has the following characteristics: firstly, the system emphasizes the characteristics of "cluster" and the overall management of key measures to avoid any shortcomings. The second, it emphasizes the transformation of infection control concepts to maximize the safety of medical services through infection control. The third, it emphasizes the optimization of the process. The prevention and control measures should be comprehensive and focused, while also preventing excessive use. The measures emphasize the use of the least resources to achieve the best infection control effect. The fourth, it emphasizes the quality control work of infection control, pays attention to the importance of the process, and advocates the concept of "system slimming, process fattening". Fifthly, it emphasizes that the future development depends on artificial intelligence, in order to improve the quality and efficiency of prevention and control to the greatest extent. Sixth, hospitals need to strengthen continuous training and retraining. We utilize diverse training methods, including artificial intelligence, to ensure that infection control policies and procedures are simple. We have established an evaluation and feedback mechanism to ensure that medical personnel are in an emergency state at all times.

ObjectiveTo investigate the effect of total alkaloids of Corydalis saxicola on a rat model of lipopolysaccharide（LPS）-induced depression， as well as the pharmacokinetic characteristics of 8 of its major components. MethodTwenty-four male SD rats were randomly divided into normal group， model group， fluoxetine group（10 mg·kg^-1） and total alkaloids of C. saxicola group（210 mg·kg^-1）， with 6 rats in each group. In addition to the normal group， the rats were injected intraperitoneally with LPS to establish the inflammation model of depression， and the drug administration was started 1 week after modeling， and the administration groups were gavaged according to the corresponding dose， and the normal and model groups were intragastric administration with equal volume of distilled water， and the administration was performed along with the modeling. After two weeks of continuous administration， the effect of total alkaloids of C. saxicola on the behavior of depressed rats were tested by sucrose preference， forced swimming and open field experiments， the levels of tumor necrosis factor-α（TNF-α）， interleukin（IL）-1β and IL-6 in serum of rats were determined by enzyme-linked immunosorbent assay（ELISA）， the histopathological changes of rat hippocampus were observed by hematoxylin-eosin（HE） staining. After the last administration， blood was collected from orbit according to the set time， and ultra-high performance liquid chromatography-triple quadrupole tandem mass spectrometry（UPLC-QqQ-MS） was established to simultaneously detect the concentrations of dehydrocavidine， tetrahydropalmatine， coptisine， palmatine， jatrorrhizine， berberine， berberrubine and epiberberine in plasma， and drug-time curves were drawn. The pharmacokinetic parameters were analyzed by DAS 2.0 software. ResultCompared with the normal group， the model group exhibited a decrease in sucrose preference rate， total distance traveled in the open field， as well as an increase in swimming immobility time and serum inflammatory factor expression（P<0.01）. In contrast， compared with the model group， rats in each administration group showed an increase in sucrose preference rate and total distance traveled in the open field， a decrease in swimming immobility time， and a reduction in serum inflammatory factor expression（P<0.05， P<0.01）. Additionally， HE staining results revealed that neurons in the hippocampus of rats from the model group were characterized by loss， disorganization and residual vacuoles， whereas those from the total alkaloids of C.saxicola group displayed an increase in number with orderly arrangement and clear cytoplasm. Pharmacokinetic results showed that the time to peak（t_max） and half-life（t_1/2） of the 8 active ingredients were 0.19-2.06 h and 3.71-8.70 h after continuous administration of total alkaloids of C. saxicola. Among them， the area under the curve（AUC_0-∞） of tetrahydropalmatine was the highest and the t_1/2 was the shortest， and the AUC_0-∞ of coptisine， palmatine， jatrorrhizine， berberine， berberrubine and epiberberine were low. The curves of dehydrocavidine， coptisine， palmatine， berberine and epiberberine showed obvious double peak phenomenon. ConclusionTotal alkaloids of C. saxicola can improve the depression-like behavior of rats， inhibit the expression of inflammatory factors in serum， improve the pathological injury of hippocampus， and has the antidepressant effect. Meanwhile， the effective site is absorbed quickly and eliminated slowly in the depressed model rats， and the efficacy is maintained for a long time.

Background The respiratory toxicity of inhaled polyhexamethylene guanidine (PHMG) has been extensively studied since the humidifier disinfectant incident. However, the impacts of inhalation of PHMG on the immune system are not comprehensively studied yet. Objective To explore the effects of inhalation of PHMG disinfectant aerosol on major immune organs and immune cells in mice. Methods Thirty male C57BL/6J mice (6-8 weeks old) were randomly divided into three groups: control, low-dose (0.1 mg·m⁻³ PHMG), and high-dose (1.0 mg·m⁻³ PHMG), with ten mice in each group. The mice were administered by oral-nasal inhalation of PHMG aerosol for 4 h per day, 5 d per week for 4 weeks consecutively. After designed treatment, venous blood was collected from the inner canthus of the eyes of mice and peripheral hematological indicators were measured with a blood analyzer. Then the mice were sacrificed by cervical dislocation and the lung, thymus, spleen, and femur were isolated. Lung, thymus, and spleen were weighed and organ coefficients were calculated, and single cell suspensions of thymus, spleen, and bone marrow were prepared to analyze lymphocytes phenotypes and proportions by flow cytometry. Results The body weight of mice in the high-dose group was lower than that of mice in the control group (P<0.01) from the 7th day of inhalation, and decreased by 15.74% compared with that of mice in the control group at the end of inhalation (P<0.01). The lung coefficients of both the low-dose and high-dose groups were higher than that of the control group (P<0.01), the thymus coefficient of mice in the high-dose group was lower than that of the control group (P<0.05), but the spleen coefficient did not change significantly (P>0.05). Leukocyte count [(1.49±0.22)×10⁹·L⁻¹], lymphocyte count [(0.96±0.36)×10⁹·L⁻¹] and its proportion [(63.13±14.96)%] in the peripheral blood of mice in the high-dose group were lower than those in the control group [(2.69±0.25)×10⁹·L⁻¹, (2.33±0.28)×10⁹·L⁻¹, and (86.23±3.40)%, respectively] (P<0.01), whereas red blood cell count [(12.32±0.46)×10¹²·L⁻¹], hemoglobin count [(175.25±4.65) g·L⁻¹], and hematocrit [(53.55±0.70)%] in the peripheral blood of mice in the high-dose group were higher than those in the control group [(11.11±0.37)×10¹²·L⁻¹, (160.67±4.04) g·L⁻¹, and (45.10±9.75)%, respectively] (P<0.05). Compared with the control group, the proportion of CD4+ CD8+ double-positive T cells decreased (P<0.05), the proportions of CD4+ T cells and CD8+ T cells increased (P<0.05), and the amounts of CD8+, CD4+ CD8+, CD4+, and CD4- CD8- cells decreased (P<0.05) in the thymus of mice of the high-dose group, the proportion of CD4+ T cells in the spleen of the high-dose group increased (P<0.05), the proportions and amounts of T cells, CD4+ T cells, and CD8+ T cells in the bone marrow of the high-dose group increased (P<0.05). Conclusion Inhalation of PHMG may cause thymic atrophy, disrupt T-lymphocyte development, and lead to an imbalance in the number of immune cells in the bone marrow, peripheral blood, and spleen, suggesting that inhalation of PHMG induces immune dysfunction.

Rare diseases still lack effective treatments, and the development of drugs for rare diseases (known as orphan drugs) is an urgent medical problem. As natural active ingredients in living organisms, some biomacromolecule drugs have good biocompatibility, low immunogenicity, and high targeting. They have become one of the most promising fields in drug research and development in the 21st century. However, there are still many obstacles in terms of in vivo delivery. In view of the unique advantages of nanocarriers prepared from polymers, lipids, organic biomimetic and inorganic materials in drug delivery, researchers are committed to building an efficient delivery system with versatility and synergy to solve the bottleneck issues in treating rare diseases with biomacromolecule drugs. Therefore, this article reviews the research progress of nanocarrier delivering proteins, peptides and nucleic acids in the field of rare disease treatment in the past ten years, which provides ideas for researches on biomacromolecule drug nanosystems in the field of treatment of rare diseases.