Objective To analyze the clinical and epidemiological characteristics of influenza A(H3N2) in Tangshan City, Hebei Province, from 2023 to 2025, and to provide a scientific basis for precise prevention and control of local influenza. Methods The influenza-like cases and influenza outbreak cases in the influenza surveillance sentinel hospitals in Tangshan City from January 2023 to December 2025 were included in this study. The clinical characteristics and epidemic characteristics of H3N2 influenza patients were analyzed by descriptive epidemiological methods and chi-square test. Results A total of 11 567 influenza case samples were tested in the study, with a positive rate of 9.34% (1 080/11 567). Influenza A (H3N2) remained the predominant circulating subtype throughout the study period. January 2023 to February 2023 marked the tailing end of the previous season’s H3N2. Then, a minor peak dominated by H1N1 occurred from March to June, and H3N2 circulated again from October to December, peaking in December. From September 2024 to December 2024, H1N1 and H3N2 circulated concurrently, with H3N2 as the dominant strain, peaking in January of the following year. From March 2025 to September 2025, influenza activity remained at low level, and activity began to rise in October, with H1N1 peaking in November before declining, and H3N2 becoming the dominant strain in December. H3N2 mainly occurred in the 5-14 years old group. Cases in the 0–4-year-old group were primarily characterized by gastrointestinal symptoms, with high fever being common. Cases in the 5–59-year-old group were primarily characterized by systemic and respiratory symptoms, with better clinical outcomes. Cases aged 60 and older exhibited the highest rates of hospitalization, severe illness, and incidence of complications. Conclusion From 2023 to 2025, the influenza virus in Tangshan City, Hebei Province is dominated by influenza A (H3N2). The epidemic is characterized by a peak incidence during autumn and winter, co-circulation with H1N1, and fluctuations during the peak period. It is necessary to pay attention to the clinical management and prevention and control of influenza A (H3N2) in infants and the elderly.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To evaluate the accuracy and feasibility of an automated scanning and uptake system to assist pathologists with hu-man epidermal growth factor receptor 2(HER2)FISH interpretation.Methods:HER2 gene amplification is detected using FISH,and"result interpretation by independent pathologists"is regarded as the"gold standard."The consistency of"human-machine dialogue results"(use of a CytoVision* system combined with manual interpretation)and"CytoVision*-based automated interpretation"with the"gold standard"was assessed.Results:Consistency between"human-machine dialogue results"and the"gold standard"can surpass 91%,with the former method saving up to 50%of the manual operation time.The tendency of each cell nucleus's HER2 copy number to be"underestimated"is the main reason for the low sensitivity observed in cases with low copy number amplification and HER2 heterogeneous expression cases in"human-machine dialogue interpretation."Conclusions:Automatic FISH image analysis and uptake systems simulate the process of manu-ally interpreted cell selection,ensure random cell selection,and improve work efficiency.With its accurate selection of the hybridization re-gion and"human-computer dialogue,"the system is expected to"replace"interpretation by independent pathologists.

ObjectiveTo explore the application value of probe-based confocal laser endomicroscopy (pCLE) in rapidly detecting and evaluating the morphological characteristics of digestive tract tissues in mice. MethodsTwelve male SPF Kunming mice aged 6 weeks were randomly divided into two groups. Six mice were subjected to gastric gavage with 52% Red Star Erguotou to establish the model, and six were given saline by gastric gavage as a control. After 28 days of modeling, 3 mice were randomly selected from each group. After deep anesthesia induced by inhalation of 3% isoflurane, the mice were sacrificed by cervical dislocation. The stomach, duodenum, jejunum, and rectum tissues were excised and immersed in 1% fluorescein sodium solution for staining. The microstructure of the mucosal surface of each tissue was observed using pCLE. The remaining mice in the model group and the control group were deeply anesthetized by inhaling 3% isoflurane, then cardiac perfusion was performed successively with saline and 4% paraformaldehyde. The stomach, duodenum, jejunum, and rectum tissues were excised for dehydration, section and hematoxylin-eosin (HE) staining, and the morphological changes of the tissues were observed under a microscope. ResultsUnder pCLE imaging, fluorescence staining on the surface of the gastrointestinal mucosa was uniform in the control group; the morphology of gastric pits, intestinal villi, and intestinal crypts was intact, arranged compactly, and had distinct boundaries. In the model group, the gastrointestinal mucosa exhibited mucosal swelling and deformation, with uneven fluorescence staining and fluorescein leakage. Furthermore, some tissues showed defects or cell shedding, and the boundaries between adjacent characteristic structures (e.g., gastric pits, intestinal crypts) were blurred. HE staining showed that the gastrointestinal tissue structure of the control group mice was normal and well-organized, with no structural defects. Moreover, submucosal glands were uniform in size, with no hyperplasia observed, and no obvious inflammatory cell infiltration. In the model group, some gastrointestinal mucosal structures were defective and sparsely arranged; submucosal glands showed atrophy, accompanied by obvious inflammatory cell infiltration. The histological characteristics detected by pCLE were consistent with those of HE staining. ConclusionpCLE can be used to obtain rapid, real-time, large-scale, and high-resolution microscopic imaging of the gastrointestinal mucosa, realistically and comprehensively displaying its physiological and microstructural characteristics. It shows promising prospects and practical utility in the histological evaluation of digestive system injuries in small animals.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Antibody-drug conjugates (ADCs) represent a promising class of targeted cancer therapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic payloads. Despite their therapeutic potential, the use of ADCs faces significant challenges, including off/on-target toxicity and resistance development. This review examines the current landscape of ADC development, focusing on the critical aspects of target selection and antibody engineering. We discuss strategies to increase ADC efficacy and safety, including multitarget approaches, pH-dependent antibodies, and masked peptide technologies. The importance of comprehensive antigen expression profiling in both tumor and normal tissues is emphasized, highlighting the role of advanced technologies, such as single-cell sequencing and artificial intelligence, in optimizing target selection. Furthermore, we explore combination therapies and innovations in linker‒payload chemistry, which may provide approaches for expanding the therapeutic window of ADCs. These advances pave the way for the development of more precise and effective cancer treatments, potentially extending ADC applications beyond oncology.
Humans ; Immunoconjugates/adverse effects* ; Neoplasms/immunology* ; Animals ; Antibodies, Monoclonal/therapeutic use* ; Antineoplastic Agents/therapeutic use*

[Objective] To compare next generation sequencing (NGS) library construction technology between probe hybridization capture and amplicon methods, and analyze the influencing factors of HLA genotyping resolution level and its prospects in clinical applications. [Methods] A total of 207 clinical samples with known typing results and samples from the proficiency testing plan were selected. The conformity rate of HLA genotyping results, allele coverage and typing data analysis indicators were confirmed, and the effects of two library construction methods on the level of HLA genotyping discrimination were compared. [Results] The concordance rate of 207 samples with the feedback results of PT or prior well-characterized HLA genotypes was 100%. Among them, 91 samples were captured using hybridization probe capture method. Compared with the original amplicon method, the hybridization probe capture method can distinguish the alleles of DRB1 and DPB1 that cannot be determined in 13 samples. The allelic imbalance of DRB1, DPA1, and DQB1 loci in 6 samples was resolved. Three samples were found to have missed detection of alleles at the DQA1 and DQB1 loci. [Conclusion] The performance indicators of hybridization probe capture and amplicon performance confirmation meet the requirements of clinical detection of HLA genotyping, which provides an experimental method and basis for clinical application.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Post-translational modification of protein is a key mechanism for regulating cancer development and immune re-sponses,and has become an important target for cancer diagnosis and treatment.Among them,lactylation modification provides a new perspective for the precise prevention and control of tumors by affecting metabolism and epigenetics.Lactylation modification precisely regulates the functions of histone and non-histone,affecting tumor cell characteristics,microenvironment acidification,and immune cell functions,becoming a key hub connecting metabolic reprogramming and malignant phenotypes.This article reviews the regulatory roles of lactylation modification in tumor development,immune escape,clinical translation,and explores the potential of targeted inhi-bition of lactylation modification and its related pathways,as well as the inhibition of key enzyme activity.