The influenza A virus (IAV), renowned for its high contagiousness and potential to catalyze global pandemics, poses significant challenges due to the emergence of drug-resistant strains. Given the critical role of RNA polymerase in IAV replication, it stands out as a promising target for anti-IAV therapies. In this study, we identified a novel C-3-substituted oleanolic acid benzyl amide derivative, A5, as a potent inhibitor of the PA_C-PB1_N polymerase subunit interaction, with an IC₅₀ value of 0.96 ± 0.21 μmol/L. A5 specifically targets the highly conserved PA_C domain and demonstrates remarkable efficacy against both laboratory-adapted and clinically isolated IAV strains, including multidrug-resistant strains, with EC₅₀ values ranging from 0.60 to 1.83 μmol/L. Notably, when combined with oseltamivir, A5 exhibits synergistic effects both in vitro and in vivo. In a murine model, dose-dependent administration of A5 leads to a significant reduction in IAV titers, resulting in a high survival rate among treated mice. Additionally, A5 treatment inhibits virus-induced Toll-like receptor 4 activation, attenuates cytokine responses, and protects against IAV-induced inflammatory responses in macrophages. In summary, A5 emerges as a novel inhibitor with high efficiency and broad-spectrum anti-influenza activity.

Objective To investigate the biological functions of the ERG3 gene in Candida albicans and its potential value in antifungal therapy. Methods The ERG3 null mutant was constructed by the CRISPR/Cas9 technology. Gas chromatography-mass spectrometry, microbroth dilution method, hyphal induction and mouse systemic infection models were carried out to evaluate sterol metabolism, drug susceptibility, hyphal formation ability and pathogenicity in C. albicans. Results The disruption of the ERG3 gene led to disordered sterol metabolism in C. albicans with a significant increased level of episterol, 14α-methylfecosterol and ergosta-7,22-dienol. The ERG3 null mutant exhibited significantly reduced susceptibility to antifungal azole and polyene drugs, which suggested that ERG3 involve in regulating drug resistance. Although the disruption of ERG3 inhibited hyphal growth and biofilm formation, it did not significantly alter the pathogenicity of the strain in a mouse model of systemic fungal infection. Conclusion The ERG3 gene was a key regulator in the ergosterol synthesis pathway in C. albicans. Its deletion induced multi-drug resistance by reshaping sterol metabolism, while pathogenicity maintenance depended on compensatory mechanisms. This study provided critical insights for developing antifungal drugs targeting sterol metabolism and overcoming drug resistance.

OBJECTIVE To establish a combined pharmacokinetic(PK)-pharmacodynamic(PD)model for knee osteoarthritis(KOA)of crossbow drug microemulsion multi-components(benzoylmesaconine,benzoylhypacoitine,mesaconitine,periplocin,neo-chlorogenic acid,vanillic acid,chlorogenic acid),and elucidate the dynamic changes in the KOA rats and the interrelation with the e-lapsed efficacy of the drug.METHODS A KOA rat model was induced by 4%papain;the PK process of crossbow medicine microe-mulsion components in rat synovial fluid was analyzed by UPLC to establish a PK model;the contents of MMP-3,MMP-13,TNF-α and IL-1β in KOA rats at different time points after administration were determined by ELISA analysis to establish a PD model;Phoe-nix WinNonlin software was used to fit the PK and PD data to obtain a PK-PD model.RESULTS PK results showed that the multi-components of the microemulsion were slowly absorbed in the joint cavity and gradually reached the peak value within 3-5 h.The Cmax of benzoylmesaconine,benzoylhypacoitine mesaconitine,periplocoside,neochlorogenic acid,vanillic acid and chlorogenic acid were 1.23,1.48,1.62,4.67,0.93,1.25 and 2.35 μg·mL-1,respectively;the area under the drug-time curve(AUC0-11)was 2.58,4.04,3.54,12.15,2.51,2.41 and 4.11 h·μg·mL-1,respectively.PD results showed that at different time points after adminis-tration,the contents of MMP-3,IL-1β,TNF-α,and MMP-13 decreased to varying degrees,among which MMP-3 decreased insig-nificantly,with significant differences only at 6 h;the contents of the remaining IL-1β,TNF-α,and MMP-13 decreased significantly(P<0.05,P<0.01),and showed the phenomenon of lagged efficacy;the PK-PD binding model showed that the drug concentration of the multi-component drug in the crossbow medicine microemulsion could be well fitted with its drug efficacy data.CONCLUSION The established PK-PD binding model can predict the drug efficacy changes after administration,and provides a corresponding refer-ence for the crossbow medicine microemulsion treatment of KOA.

OBJECTIVE To establish a combined pharmacokinetic(PK)-pharmacodynamic(PD)model for knee osteoarthritis(KOA)of crossbow drug microemulsion multi-components(benzoylmesaconine,benzoylhypacoitine,mesaconitine,periplocin,neo-chlorogenic acid,vanillic acid,chlorogenic acid),and elucidate the dynamic changes in the KOA rats and the interrelation with the e-lapsed efficacy of the drug.METHODS A KOA rat model was induced by 4%papain;the PK process of crossbow medicine microe-mulsion components in rat synovial fluid was analyzed by UPLC to establish a PK model;the contents of MMP-3,MMP-13,TNF-α and IL-1β in KOA rats at different time points after administration were determined by ELISA analysis to establish a PD model;Phoe-nix WinNonlin software was used to fit the PK and PD data to obtain a PK-PD model.RESULTS PK results showed that the multi-components of the microemulsion were slowly absorbed in the joint cavity and gradually reached the peak value within 3-5 h.The Cmax of benzoylmesaconine,benzoylhypacoitine mesaconitine,periplocoside,neochlorogenic acid,vanillic acid and chlorogenic acid were 1.23,1.48,1.62,4.67,0.93,1.25 and 2.35 μg·mL-1,respectively;the area under the drug-time curve(AUC0-11)was 2.58,4.04,3.54,12.15,2.51,2.41 and 4.11 h·μg·mL-1,respectively.PD results showed that at different time points after adminis-tration,the contents of MMP-3,IL-1β,TNF-α,and MMP-13 decreased to varying degrees,among which MMP-3 decreased insig-nificantly,with significant differences only at 6 h;the contents of the remaining IL-1β,TNF-α,and MMP-13 decreased significantly(P<0.05,P<0.01),and showed the phenomenon of lagged efficacy;the PK-PD binding model showed that the drug concentration of the multi-component drug in the crossbow medicine microemulsion could be well fitted with its drug efficacy data.CONCLUSION The established PK-PD binding model can predict the drug efficacy changes after administration,and provides a corresponding refer-ence for the crossbow medicine microemulsion treatment of KOA.

Purpose To investigate the feasibility of a deep learning framework to automatically analyze echocardiographic color Doppler videos in detecting valvular regurgitation.Materials and Methods This study retrospectively collected echocardiographic images of 1 109 patients with valvular regurgitation in the Fourth Medical Center of PLA General Hospital,from June 2015 to September 2019 as the training and validation sets.A prospective continuous collection of 1 562 echocardiography images was used as the test set in the Fourth Medical Center of PLA General Hospital from May 13 to June 13,2023,including 378 cases of mitral regurgitation and 223 cases of aortic regurgitation.This study developed deep learning networks to establish view classification model and valvular regurgitation recognition model,including the efficiency of section classification of deep learning models.Results The deep learning view classification model in this study could automatically identify two views for diagnosing mitral regurgitation and aortic regurgitation.The recognition accuracy for the parasternal long axis color Doppler view and the apical four chamber mitral color Doppler view was 1.00 and 0.93,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model for diagnosing mitral regurgitation were 0.847,0.852,0.849 and 0.930,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model in diagnosing aortic regurgitation were 0.857,0.861,0.859 and 0.940,respectively.Conclusion Deep learning algorithms can automatically identify valvular regurgitation and have the potential to become a screening tool for valvular heart disease.

Purpose To investigate the feasibility of a deep learning framework to automatically analyze echocardiographic color Doppler videos in detecting valvular regurgitation.Materials and Methods This study retrospectively collected echocardiographic images of 1 109 patients with valvular regurgitation in the Fourth Medical Center of PLA General Hospital,from June 2015 to September 2019 as the training and validation sets.A prospective continuous collection of 1 562 echocardiography images was used as the test set in the Fourth Medical Center of PLA General Hospital from May 13 to June 13,2023,including 378 cases of mitral regurgitation and 223 cases of aortic regurgitation.This study developed deep learning networks to establish view classification model and valvular regurgitation recognition model,including the efficiency of section classification of deep learning models.Results The deep learning view classification model in this study could automatically identify two views for diagnosing mitral regurgitation and aortic regurgitation.The recognition accuracy for the parasternal long axis color Doppler view and the apical four chamber mitral color Doppler view was 1.00 and 0.93,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model for diagnosing mitral regurgitation were 0.847,0.852,0.849 and 0.930,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model in diagnosing aortic regurgitation were 0.857,0.861,0.859 and 0.940,respectively.Conclusion Deep learning algorithms can automatically identify valvular regurgitation and have the potential to become a screening tool for valvular heart disease.

ObjectiveMolecular docking plays a critical role in predicting binding modes and affinity between molecules, serving as a pivotal method in structural biology and computer-aided drug design research. Our research team has recently developed a novel template-based docking method called FitDock, which outperforms commonly used molecular docking methods in terms of accuracy and speed, particularly when approximate protein-ligand templates are available. To enhance the accessibility of the FitDock method and promote its broader application in the field of molecular simulation, the development of a graphical software tool is imperative. MethodsUtilizing Python-based graphical programming, we have created FitDockApp, a plugin software for the molecular visualization software PyMOL. ResultsFitDockApp enables template-based molecular docking and ligand structure alignment through an interactive graphical interface, providing real-time visualization of predicted three-dimensional structures. It also offers the convenience of uploading docking files to a laboratory server to obtain the optimal template. Additionally, FitDockApp includes batch docking functionality. ConclusionFitDockApp simplifies the docking process through its user-friendly interface and provides robust functionality to assist researchers in obtaining precise docking results. FitDockApp is a free software compatible with both Windows and Linux systems and can be downloaded from http://cao.labshare.cn/fitdock/.

Objective To discuss the perioperative care and wound protection of xenotransplantation from genetically edited pigs to monkeys, with the goal of improving the success rate of such experimental procedures. Methods From October 2022 to October 2023, perioperative care and wound protection were performed on 7 recipient rhesus monkeys undergoing xenotransplantation of genetically edited pig tissues and organs. Customized wound protective garments were designed based on monkeys' size and surgical area to protect the wounds, alongside meticulous perioperative care. This included preoperative preparation and medication, intraoperative monitoring of physiological indicators and anesthesia management, and postoperative care comprising wound protection, observation and monitoring, and nutritional support. Results All seven monkeys successfully underwent xenotransplantation. With the aid of protective garments and detailed care, all surgical wounds healed by first intention, and postoperative recovery was satisfactory. Conclusion Proper care and wound protection during xenotransplantation from genetically edited pigs to monkeys not only promote wound healing, but also alleviate pain and harm to animals. This has significant implications for advancing experimental research in pig-monkey xenotransplantation and enhancing animal welfare.

The traditional commodity specifications of Chinese medicinal materials are mainly divided into different grades based on macroscopic characteristics. As the basis for high quality and good price, there is still a lack of systematic evaluation on whether they are consistent with the current standards and whether they can reflect the internal quality of medicinal material. Panax notoginseng is a commonly used, large consumption of Chinese medicinal material. At present, it is divided into 8 grades in the market based on "Tou" (the number of crude drug /500 g), but it is not related to the standard of total saponins of Panax notoginseng (the sum of three saponins) in Chinese Pharmacopoeia. In this study, ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF-MS/MS) coupled with mass spectrometry molecular network were used for the rapid identification of saponins of Panax notoginseng with different "Tou" and a total of 64 saponins were identified. Seventeen saponins related to "Tou" were screened by orthogonal partial least squares discriminant analysis (OPLS-DA). The content of five saponins R₁, Rb₁, Rg₁, Rd, and Re in Panax notoginseng with different "Tou" was determined by high performance liquid chromatography (HPLC). The results of correlation analysis showed that Rd and R₁ with the largest VIP values among the differential saponins, which significantly negatively correlated with "Tou" (P < 0.05). Based on the determination results of 36 batches of samples, using Rd/Total Panax notoginseng saponins (TPNS) ratio ( > 0.08) as the index, Panax notoginseng can be divided into two grades: 20-60 "Tou" (superior) and 80-200 "Tou" (qualified). Based on the concept of "macroscopic characteristics and chemical profiling", this study integrates the non-targeted analysis and quantitative determination methods to provide a new strategy for quality evaluation of Panax notoginseng.