Objective: To investigate the role and mechanism of the heat-clearing and detoxifying drug Laggerae Herba in regulating the nuclear factor-erythroid 2-related factor-2(Nrf2)/solute carrier family 7 member 11 (SLC7A11)/glutathione peroxidase 4 (GPX4) signaling pathway to inhibit ferroptosis and improve chronic heart failure induced by transverse aortic arch constriction in mice. Methods: Twenty-four male ICR mice were divided into the sham (n=6) and transverse aortic arch constriction groups (n=18) according to the random number table method. The transverse aortic arch constriction group underwent transverse aortic constriction surgery to establish models. After modeling, the transverse aortic arch constriction group was further divided into the model, captopril, and Laggerae Herba groups according to the random number table method, with six mice per group. The captopril (15 mg/kg) and Laggerae Herba groups (1.95 g/kg) received the corresponding drugs by gavage, whereas the sham operation and model groups were administered the same volume of ultrapure water by gavage once a day for four consecutive weeks. After treatment, the cardiac function indexes of mice in each group were detected using ultrasound. The heart mass and tibia length were measured to calculate the ratio of heart weight to tibia length. Hematoxylin and eosin staining were used to observe the pathological changes in myocardial tissue. Masson staining was used to observe the degree of myocardial fibrosis. Wheat germ agglutinin staining was used to observe the degree of myocardial cell hypertrophy. Prussian blue staining was used to observe the iron deposition in myocardial tissue. An enzyme-linked immunosorbent assay was used to detect the amino-terminal pro-brain natriuretic peptide (NT-proBNP) and glutathione (GSH) contents in mice serum. Colorimetry was used to detect the malondialdehyde (MDA) content in mice serum. Western blotting was used to detect the Nrf2, GPX4, SLC7A11, and ferritin heavy chain 1 (FTH1) protein expressions in mice cardiac tissue. Results: Compared with the sham group, in the model group, the ejection fraction (EF) and fractional shortening (FS) of mice decreased, the left ventricular end-systolic volume (LVESV) and left ventricular end-systolic diameter (LVESD) increased, the left ventricular anterior wall end-systolic thickness (LVAWs) and left ventricular posterior wall end-systolic thickness (LVPWs) decreased, the ratio of heart weight to tibia length increased, the myocardial tissue morphology changed, myocardial fibrosis increased, the cross-sectional area of myocardial cells increased, iron deposition appeared in myocardial tissue, the serum NT-proBNP and MDA levels increased, the GSH level decreased, and Nrf2, GPX4, SLC7A11, and FTH1 protein expressions in cardiac tissue decreased (P<0.05). Compared with the model group, in the captopril and Laggerae Herba groups, the EF, FS, and LVAWs increased, the LVESV and LVESD decreased, the ratio of heart weight to tibia length decreased, the myocardial cells were arranged neatly, the degree of myocardial fibrosis decreased, the cross-sectional area of myocardial cells decreased, the serum NT-proBNP level decreased, and the GSH level increased. Compared with the model group, the LVPWs increased, the iron deposition in myocardial tissue decreased, the serum MDA level decreased, and Nrf2, GPX4, SLC7A11, and FTH1 protein expressions in cardiac tissue increased (P<0.05) in the Laggerae Herba group. Conclusion Laggerae Herba improves the cardiac function of mice with chronic heart failure caused by transverse aortic arch constriction, reduces the pathological remodeling of the heart, and reduces fibrosis. Its mechanism may be related to Nrf2/SLC7A11/GPX4 pathway-mediated ferroptosis.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Objective: To analyze the epidemiological characteristics and changing trends of non suicidal self injury (NSSI) behaviors among middle school students in Jiading District of Shanghai, from 2015 to 2023, so as to provide a basis for the development of NSSI prevention and control measures among students. Methods: Using a stratified cluster random sampling method, a total of five times for Shanghai Adolescent Health Risk Behavior Surveys were conducted for every two years in Jiading District of Shanghai from 2015 to 2023. A total of 5 231 middle school students from junior high schools and senior high schools were selected for questionnaire surveys. Intergroup comparisons were performed using the x 2 test or the χ 2 trend test, and the JointPoint 5.0 software was used to analyze the changing trends, with the annual percent change (APC) used for evaluation. A binary Logistic regression model was employed to analyze the related factors of NSSI behavior among middle school students. Results: In 2023, the reported NSSI rate among middle school students in Jiading District was 14.2%. The rate was significantly higher among junior high school students (17.1%) than that among senior high school students (11.1%), and higher among females (19.2%) than that among males (10.0%) ( χ 2=10.04, 23.21, both P <0.01). From 2015 to 2023, the overall reported NSSI rate showed an increasing trend, rising from 8.6% in 2015 to 14.2% in 2023 ( χ 2 trend =22.25), with an APC of 6.64% ( t =3.49), and the APC for girls was 9.79 % ( t =3.20) (all P <0.05). Among students reporting NSSI, the proportion experiencing ≥6 episodes increased from 10.8% in 2015 to 19.2% in 2023 ( χ 2 trend =6.57, P <0.05). Multivariate Logistic regression analysis indicated that girls, junior high school students, those with insomnia, depressive emotion and drinkers had higher risks of NSSI, compared to boys, senior high school students, those without insomnia, non depressive emotion students and non drinkers ( OR =1.71, 1.96, 3.44, 4.76, 1.77, all P < 0.05 ). Conclusions The reported rate of NSSI among middle school students in Jiading District of Shanghai, increased annually from 2015 to 2023, and the proportion of repeated NSSI also showed an upward trend. Early intervention measures targeting middle school students, especially junior high school students and females, should be implemented to prevent and control its occurrence and development.

AIM To establish a quantitative analysis of multi-components by single-marker(QAMS)method for the simultaneous content determination of gastrodin,parishin E,syringin,parishin B,parishin C,ferulic acid,parishin A,buddleoside,harpagoside and cinnamic acid in Tianma Toufengling Capsules.METHODS The analysis was performed on a 30℃thermostatic GL Science InertsilTM ODS-3 column(150 mm×4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.1%phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelengths were set at 220,280 nm.Syringin was used as an internal standard to calculate the relative correction factors of the other nine constituents,after which the content determination was made.RESULTS Ten constituents showed good linear relationships within their own ranges(r≥0.999 7),whose average recoveries were 98.53%-102.22%with the RSDs of 1.26%-2.68%.The result obtained by QAMS approximated those obtained by external standard method.CONCLUSION This accurate and specific method can be used for the quality control of Tianma Toufengling Capsules.

Objective:To construct a scientific and technological evaluation system based on the needs of the pilot program for building a national high-quality hospital and establishing a national medical center.Methods:Xiangya Hospital of Central South University gradually improved its academic evaluation system by following the guidelines outlined in national authorities′ documents regarding "abolishing the five only" and "setting new standards", adhering to the guiding principles of "quality, contribution, efficiency, and impact" and employing the principles of "high-standard evaluation, quantitative evaluation, representative work evaluation, and third-party evaluation" .Results:The hospital established a comprehensive, scientific, and quantifiable indicator pool. These indicators were applied to various aspects of medical innovation evaluation, including awarding incentives, discipline assessment, professional promotion, personnel assessment, mentor selection for graduates, and excellence evaluation. Simultaneously, the hospital developed an intelligent platform for medical innovation evaluation and assessment in university-affiliated hospitals based on performance management theory.Conclusions:Through the construction and practice of the Xiangya technology evaluation system, the hospital further improved and optimized its academic evaluation work, guiding researchers to high-quality innovation and efficient translational research, ultimately promoting the high-quality development of the hospital.

Objective The aim of this study was to assess the impact of bisphenol A (BPA) and its substitute, bisphenol F (BPF), on the colonic fecal community structure and function of mice.Methods We exposed 6-8-week-old male C57BL/6 mice to 5 mg/(kg·day) and 50 μg/(kg·day) of BPA or BPF for 14 days. Fecal samples from the colon were analyzed using 16S rRNA sequencing. Results Gut microbiome community richness and diversity, species composition, and function were significantly altered in mice exposed to BPA or BPF. This change was characterized by elevated levels of Ruminococcaceae UCG-010 and Oscillibacter and decreased levels of Prevotella 9 and Streptococcus. Additionally, pathways related to carbohydrate and amino acid metabolism showed substantial enrichment. Conclusion Mice exposed to different BP analogs exhibited distinct gut bacterial community richness, composition, and related metabolic pathways. Considering the essential role of gut bacteria in maintaining intestinal homeostasis, our study highlights the intestinal toxicity of BPs in vertebrates.

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.

Objective To design and implement a high-precision ear pulse wave physiological signal detection device for human centrifuge training to solve the problems in measurement and calibration of pilot ear pulse wave signal during human centrifuge training.Methods The high-precision ear pulse wave physiological signal detection device was composed of an ear pulse wave acquisition sensor,a signal acquisition and control unit and a host signal processing module.The ear pulse wave acquisition sensor had an ear-clip-like shape and consisted of an outer shell,an inner shell and an elastic steel plate;the signal acquisition and control unit was made up of an power supply module,a constant voltage module for the light source,a signal acquisition module,a master control module and a data transmission module,which had its software developed with an embedded system;the host signal processing module divided the signal processing into 2 phases of signal pre-processing and pulse wave signal monitoring and display.The detection performance of the device was verified by using a physiological electrical signal calibrator to test the ear pulse wave signals detected with the device;the effectiveness and stability of the device were validated by implementing human centrifuge training experiments with different loads.Results The voltage measurement error,amplitude-frequency characteristics and common mode rejection ratio detected by this device were all within the permitted ranges of JJG 760-2003 Verification Regulation for Electro Cardiac Monitor and JJG 954-2019 Verification Regulation of Digital Electroencephalographs;the device was capable of detecting the ear pulse wave signals of pilot during human centrifuge training in real time with little interference from motion and stable signal quality.Conclusion The device can accurately clarify the changes in the amplitude of the pilot's ear pulse wave during human centrifuge training and effectively reflect the changes in the pilot's cerebral blood flow under positive acceleration.[Chinese Medical Equipment Journal,2024,45(9):35-40]

Objective:To enhance the understanding of the diagnosis and individualized treatment of myelodysplastic syndrome/myeloproliferative neoplasms with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T).Methods:A retrospective case series study was conducted. The clinical data, diagnosis and treatment process and prognosis of 4 patients with MDS/MPN-RS-T admitted to Affiliated Hospital of Hebei University from September 2015 to May 2021 were retrospectively analyzed, and the related literature was reviewed.Results:All the 4 patients were male, aged 63 to 75 years. Patients 1 and 2 were classified as revised international prognostic scoring system (IPSS-R) high-risk group, combined with ASXL1 mutation and high risk cytogenetic abnormality. The therapeutic effect of various treatment regimens was poor, and they were converted to acute myeloid leukemia (AML) and then died due to disease progression. Patient 3 was classified as IPSS-R medium-risk group. His main manifestation was myelodysplastic syndrome (MDS) combined with ring sideroblasts in the early stage and was transformed into MDS/MPN-RS-T during the treatment, and JAK2 mutation occurred in the subsequent treatment. After lenalidomide treatment, the patient was removed from blood transfusion and the condition was stable at present. Patient 4 was classified as IPSS-R medium-risk group, and lenalidomide showed significant therapeutic effects and he was in stable condition.Conclusions:Lenalidomide can significantly improve transfusion dependence in patients with MDS/MPN-RS-T, and ASXL1 mutation and high-risk cytogenetic abnormality may be associated with AML transformation.

The efficient clinical treatment of oral squamous cell carcinoma(OSCC)is still a challenge that demands the development of effective new drugs.Phenformin has been shown to produce more potent anti-tumor activities than metformin on different tumors,however,not much is known about the influence of phenformin on OSCC cells.We found that phenformin suppresses OSCC cell proliferation,and promotes OSCC cell autophagy and apoptosis to significantly inhibit OSCC cell growth both in vivo and in vitro.RNA-seq analysis revealed that autophagy pathways were the main targets of phenformin and identified two new targets DDIT4(DNA damage inducible transcript 4)and NIBAN1(niban apoptosis regulator 1).We found that phenformin significantly induces the expression of both DDIT4 and NIBAN1 to promote OSCC autophagy.Further,the enhanced expression of DDIT4 and NIBAN1 elicited by phenformin was not blocked by the knockdown of AMPK but was suppressed by the knockdown of transcription factor ATF4(activation transcription factor 4),which was induced by phenformin treatment in OSCC cells.Mechanistically,these results revealed that phenformin triggers endoplasmic reticulum(ER)stress to activate PERK(protein kinase R-like ER kinase),which phosphorylates the transitional initial factor eIF2,and the increased phosphorylation of eIF2 leads to the increased translation of ATF4.In summary,we discovered that phenformin induces its new targets DDIT4 and especially NIBAN1 to promote autophagic and apoptotic cell death to suppress OSCC cell growth.Our study supports the potential clinical utility of phenformin for OSCC treatment in the future.