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.

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.

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.

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.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

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 evaluate the efficacy of SedLine Brain Function Monitor-guided total intravenous anesthesia for children undergoing hypospadias surgery.Methods:This was a randomized controlled trial. A total of 161 children, aged 1-10 yr, with American Society of Anesthesiologists Physical Status classification ⅠorⅡ, scheduled for elective hypospadias surgery, were divided into SedLine group (S group, n=83) and control group (C group, n=78) using a random number table method. In group S, 95% spectral edge frequency (SEF 95) was maintained at 14-18 Hz, and the patient state index (PSI) was maintained at 25-50 during surgery. In group C, mean arterial pressure was maintained at 60-80 mmHg, and heart rate was maintained at 80-110 beats/min during surgery. PSI and SEF 95 were recorded before induction (T 1), at 0, 5 and 10 min after intubation (T 2-4), at the beginning of surgery (T 5), at 30 min and 1 h after surgery (T 6, 7), and at the end of surgery (T 8). The anesthetic duration, operation time, time from withdrawal to extubation, postanesthesia care unit duration, consumption of propofol and remifentanil, intraoperative adverse events, 5-point Likert scale scores, and emergence delirium scores were recorded. Results:Compared to C group, the total anesthesia time, time from withdrawal to extubation and postanesthesia care unit duration were significantly shortened, the consumption of propofol for both induction and maintenance was reduced, the PSI at T 5-8, SEFL 95 at T 2-6, and SEFR 95 at T 2-8 were increased, and the incidence of intraoperative body movement and incidence of emergence agitation were decreased in S group ( P<0.05). Conclusions:SedLine Brain Function Monitor-guided total intravenous anesthesia provides better efficacy when used for the children undergoing hypospadias surgery.