ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Pre-admission is a critical initiative to optimize medical service processes and alleviate the challenge of "difficult access to healthcare. "However, there is currently a lack of standardized protocols for pre-admission procedures. This study aims to systematically analyze key nodes and risk factors in pre-admission process design and propose optimization strategies, providing a foundation for policy formulation and hospital practices. By constructing a "forward-reverse" dual-process model of pre-admission and identifying risk points based on stakeholder theory (patients, hospitals, healthcare administration, and insurance), the study reveals that while pre-admission can reduce the average length of stay, improve bed turnover rates, and enhance patient satisfaction, it also presents risks such as cross-period financial settlement, challenges in insurance policy adaptability, demands for information system integration, and the need for defining medical safety boundaries. To optimize the pre-admission process and mitigate these risks, this study explores framework improvements in areas including eligibility criteria, mode selection, cost settlement, transition between pre-admission and inpatient status, and cancellation of pre-admission, offering practical guidance for public hospitals. The authors argue that pre-admission requires tripartite collaboration among hospitals, insurers, and healthcare administrations: hospitals should establish top-level design, continuously refine processes, and implement dynamic risk assessment mechanisms; insurance providers should support cross-period settlement policies; and healthcare administrations should issue guiding policies or standardized protocols. Through multi-department coordination and collaborative efforts, the optimization and innovation of pre-admission processes can be advanced, ultimately delivering more efficient and convenient healthcare experiences for patients.

Immunotherapy is an important breakthrough in canc-er treatment.Unfortunately,low drug concentration in tumor sites almost ineffectively initiates immune responses and thereby severely limits immune therapy applications in clinics.Nanoma-terials are well-recognized drug delivery system in cancer thera-py.Nanographene oxide(NGO)have shown immense perti-nence for anti-cancer drug delivery owing to their ultra-high sur-face area,chemical stability,good biocompatibility and excel-lent photosensitivity.In addition,functionalized modifications on the surface of NGO increase tumor targeting and minimize cy-totoxicity.This study focuses on reviewing the literature and up-dates on NGO in drug delivery and discussing the possibilities and challenges of NGO in cancer synergetic therapy.

Objective To evaluate the in vitro effect of combinations of 5 β-lactam antibiotics with different β-lac-tamase inhibitors on the activity of multidrug-resistant Mycobacterium tuberculosis(MDR-TB),and identify the most effective combination of β-lactam antibiotics and β-lactamase inhibitors against MDR-TB.Methods MDR-TB strains collected in Henan Province Antimicrobial Resistance Surveillance Project in 2021 were selected.The mini-mum inhibitory concentrations(MIC)of 5 β-lactam antibiotics or combinations with different β-lactamase inhibitors on clinically isolated MDR-TB strains were measured by MIC detection method,and the blaC mutation of the strains was analyzed by polymerase chain reaction(PCR)and DNA sequencing.Results A total of 105 strains of MDR-TB were included in the analysis.MIC detection results showed that doripenem had the highest antibacterial activity against MDR-TB,with a MIC50 of 16 μg/mL.MIC values of most β-lactam antibiotics decreased significantly after combined with β-lactamase inhibitors.A total of 13.33％(n=14)strains had mutations in blaC gene,mainly 3 nu-cleotide substitution mutations,namely AGT333AGG,AAC638ACC and ATC786ATT.BlaC proteins Ser111 Arg and Asn213Thr enhanced the synergistic effect of clavulanic acid/sulbactam and meropenem on MDR-TB compared with synonymous single-nucleotide mutation.Conclusion The combination of doripenem and sulbactam has the strongest antibacterial activity against MDR-TB.Substitution mutations of BlaC protein Ser111 Arg and Asn213Thr enhances the sensitivity of MDR-TB to meropenem through the synergy with clavulanic acid/sulbactam.

Chinese materia medica and its compound formulas have the characteristics of multi-component,multi-target,and multi pathway effects,and have unique advantages in preventing and treating complex diseases.Network pharmacology explains disease patterns and drug mechanisms from the perspective of complex biological networks,and explores the pharmacological substance basis and target of Chinese medicine.This article summarized the application of network pharmacology from the aspects of biological basis of TCM syndrome,the substance basis and pharmacological mechanism of TCM,compatibility theory of TCM compound formulas,etc.,with the purpose to provide a reference for the research and application of network pharmacology in TCM.

Objective:To investigate the value of nomogram based on radiomics features of CT enterography (CTE) combined with clinical characteristics to predict secondary loss of response (SLOR) after infliximab (IFX) treatment in patients with Crohn′s disease (CD).Methods:This study was a case-control study. Clinical and imaging data of 155 patients with CD diagnosed at the First Affiliated Hospital of Anhui Medical University from March 2015 to July 2022 were retrospectively collected. The patients were divided into a training set ( n=108) and a testing set ( n=47) in the ratio of 7∶3 by stratified sampling method. All patients were treated according to the standardized protocol and were classified as SLOR (43 in the training set and 18 in the testing set) and non-SLOR (65 in the training set and 29 in the testing set) according to treatment outcome. Based on the data from the training group, independent clinical predictors of SLOR after IFX treatment were screened in the clinical data using univariate and multivariate logistic regression analysis to establish a clinical model. Intestinal phase images were selected to be outlined layer by layer along the margin of the lesion to obtain the volume of the region of interest to extract the radiomics features. The radiomics features were screened using univariate analysis and the minimum absolute shrinkage and selection operator to establish the radiomics model. Multivariate logistic regression analysis was used to build a combined clinical-radiomics model based on the screened clinical independent predictors and radiomics characters, then a nomogram was drawn. The predictive efficacy of the 3 models for SLOR after IFX treatment was assessed by receiver operating characteristic curves, and the area under the curve (AUC) was calculated. The decision curve analysis was applied to evaluate the clinical utility of the models. Results:Disease duration ( OR=1.983, 95% CI 1.966-2.000, P=0.046) and intestinal stenosis ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as the independent predictors of SLOR in the clinical data, and a clinical model was established. Totally 9 radiomics features were included in the radiomics model. The AUCs of clinical, radiomics, and combined models for predicting SLOR after IFX treatment in CD patients were 0.691 (95% CI 0.591-0.792), 0.896 (95% CI 0.836-0.955), and 0.910 (95% CI 0.855-0.965) in the training set, and 0.722 (95% CI 0.574-0.871), 0.866 (95% CI 0.764-0.968), and 0.889 (95% CI 0.796-0.982) in the testing set. Decision curve analysis in the testing set showed higher net clinical benefits for both the radiomics model and combined model than the clinical model, and combined model had higher net clinical benefits than the radiomics model over most threshold probability intervals. Conclusions:CTE-based radiomics model can effectively predict SLOR after IFX treatment in patients with CD, and a combined model by incorporating clinical characteristics of disease duration and intestinal stenosis can further improve the predictive efficacy.

Objective To evaluate the predictive value of a dose-surface histogram (DSH) for radiation cystitis (RC) in patients with cervical cancer. Methods We retrospectively included 190 patients with cervical cancer who underwent image-guided radiotherapy (IGRT) from the HIS system of The First Affiliated Hospital of Hebei North University from May 2013 to May 2023. The patients were divided into test group (n = 100) and control group (n = 90). The dose distribution in the bladder was evaluated by using a DSH for the test group and using a dose-volume histogram (DVH) for the control group. Receiver operating characteristic curves were used to evaluate the predictive value of DSH for RC in comparison with DVH. Results There were no significant differences in baseline data and RC incidence between the two groups (all P＞0.05). All evaluation indicators were significantly different between DSH and DVH (all P＜0.05). The predictive value of S₄₅ and V₄₅ for the incidence of grade-I, -II, and -III RC was low (all P＜0.05). The predictive value of S₅₀ and V₅₀ for the incidence of grade-I, -II, and -III RC was moderate (all P＜0.05). S₅₅−S₅₇ and V₅₅−V₅₇ showed high value for predicting the incidence of grade-I, -II, and -III RC (all P＜0.05). Conclusion DSH shows basically the same predictive value for the incidence of RC caused by IGRT in cervical cancer as DVH, which is expected to become a new tool for evaluating radiotherapy plans.

Objective To identify the latent profile of physical and psychological symptoms in postpartum women and examine the associations of the latent class membership with individual characteristics,based on a latent profile analysis.Methods A cross-sectional survey study was conducted.With convenience sampling,157 postpartum women who had delivered at the Obstetrics and Gynecology Hospital,Fudan University from Dec 2023 to Mar 2024 were selected.The participants were surveyed with patient-reported outcomes measurement information system(PROMIS)Anxiety,Depression,Fatigue,Sleep Disturbance,and Pain interference short forms.LPA and multinomial Logistic regression model were performed to identify subgroups based on physical and psychological symptoms in postpartum women and population heterogeneity.Results LPA results suggested that there existed three distinct classes of postpartum physical and psychological symptoms:severe symptoms distress class(10.2%),moderate symptoms distress class(50.3%),and mild symptoms distress class(39.5%).Postpartum women's age,living arrangements,newborn's birthweight,newborn's feeding method,newborn's medical background,prenatal pregnancy risk assessment,mode of delivery,and postpartum complications had significant associations with the latent class membership(P<0.05).Conclusion There are 3 latent profiles of postpartum physical and psychological symptoms.Healthcare providers could provide targeted intervention to postpartum women according to the characteristics of different subgroup population characteristics,so as to improve the postpartum experience of women.

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Mice ; Animals ; Tandem Mass Spectrometry ; Alpha-Amanitin ; Chromatography, Liquid ; Metabolomics ; Chromatography, High Pressure Liquid/methods*