Chronic obstructive pulmonary disease (COPD) is the most common chronic respiratory disease around the world, and pharmacotherapy is the foremost treatment method currently. In recent decades, with the rapid development of bronchoscopic interventional therapy, endoscopic physical ablation technology presents a therapeutic effect in treating COPD, with few treatment-related side effects, showing excellent application prospects in treating COPD. Since ablation techniques in this field are emerging technologies with low patient acceptance, they are not widely used in the clinical treatment of COPD. This article reviews the development process of physical ablation techniques. Moreover, their current application status and the prospects in the field of COPD treatment are also summarized and analyzed. We hope to promote the application of physical ablation in the clinical treatment of COPD and provide practical references and a theoretical basis for the clinical treatment of COPD.

In recent years,the market share of food and medicine homology substances has continued to grow,and various types of contamination issues have become the focus of attention both inside and outside the industry.The contamination not only affects the original medicinal quality,but also leads to the accumulation of toxic substances in the human body,causing acute and chronic severe hazards such as vomiting,poisoning and cancer.Therefore,the development of biosensors that can conveniently,accurately and sensitively detect various pollutants in food and medicine homology substances has become a research hotspot.Aptasensors based on metal-organic frameworks(MOFs)with advantages such as strong specificity,rapid response and simple operation,have been widely used in detection of various pollutants.This review focused on the research progress of aptasensors based on MOFs for detection of food and medicine homology contamination in the past few years,and provided a detailed comparison and analysis for detection of chemical pollutants(such as pesticide residues,heavy metal residues,mycotoxins,etc.)and microbial contamination in food and medicine homology substances.Besides,the development trend and possible challenges of MOFs aptasensors in detection of food and medicine homology substances in the future were discussed,which was anticipated to provide a reference for the development of new MOFs aptasensors.

B and T lymphocyte attenuator (BTLA) is an inhibitory immune checkpoint, which typically interacts with herpesvirus entry mediator (HVEM) and plays a crucial role in regulating immune balance. BTLA interacts with its ligand HVEM in a cis manner on the surface of the same immune cell to maintain immune tolerance, while trans interactions on the surface of different immune cells mediate immunosuppressive effects. Dysregulation of the BTLA/HVEM axis can impair the functions of immune cells, particularly T lymphocytes, promoting immune escape of tumor cells and ultimately leading to tumor progression. Researchers have found that BTLA and HVEM are abnormally expressed in various tumors and are associated with prognosis, suggesting that they may be potential targets for tumor immunotherapy. This review summarizes the molecular structures of BTLA and HVEM, immunomodulatory mechanisms, recent advances in hematologic malignancies, potential inhibitors of BTLA/HVEM interaction, and their applications in immunotherapy for hematologic malignancies.
Humans ; Receptors, Tumor Necrosis Factor, Member 14/chemistry* ; Receptors, Immunologic/immunology* ; Hematologic Neoplasms/genetics* ; Immunotherapy/methods* ; Animals

Objective To explore the prognostic value of glycolysis-related genes in colorectal cancer (CRC) patients and formulate a novel glycolysis-related prognostic risk model. Methods Single-cell and bulk transcriptomic data of CRC patients, along with clinical information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Glycolysis scores for each sample were calculated using single-sample Gene Set Enrichment Analysis (ssGSEA). Kaplan-Meier survival curves were generated to analyze the relationship between glycolysis scores and overall survival. Novel glycolysis-related subgroups were defined among the cell type with the highest glycolysis scores. Gene enrichment analysis, metabolic activity assessment, and univariate Cox regression were performed to explore the biological functions and prognostic impact of these subgroups. A prognostic risk model was built and validated based on genes significantly affecting the prognosis. Gene Set Enrichment Analysis (GSEA) was conducted to explore differences in biological processes between high- and low-risk groups. Differences in immune microenvironment and drug sensitivity between these groups were assessed using R packages. Potential targeted agents for prognostic risk genes were predicted using the Enrichr database. Results Tumor tissues showed significantly higher glycolysis scores than normal tissues, which was associated with a poor prognosis in CRC patients. The highest glycolysis score was observed in epithelial cells, within which we defined eight novel glycolysis-related cell subpopulations. Specifically, the P4HA1⁺ epithelial cell subpopulation was associated with a poor prognosis. Based on signature genes of this subpopulation, a six-gene prognostic risk model was formulated. GSEA revealed significant biological differences between high- and low-risk groups. Immune microenvironment analysis demonstrated that the high-risk group had increased infiltration of macrophages and tumor-associated fibroblasts, along with evident immune exclusion and suppression, while the low-risk group exhibited higher levels of B cell and T cell infiltration. Drug sensitivity analysis indicated that high-risk patients were more sensitive to Abiraterone, while low-risk patients responded to Cisplatin. Additionally, Valproic acid was predicted as a potential targeted agent. Conclusion High glycolytic activity is associated with a poor prognosis in CRC patients. The novel glycolysis-related prognostic risk model formulated in this study offers significant potential for enhancing the diagnosis and treatment of CRC.
Humans ; Colorectal Neoplasms/pathology* ; Glycolysis/genetics* ; Prognosis ; Transcriptome ; Tumor Microenvironment/genetics* ; Gene Expression Profiling ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Male ; Female ; Kaplan-Meier Estimate

Allergic rhinitis (AR) is a chronic non-specific inflammatory disease of the nasal mucosa caused by abnormal activation of the immune system, with alterations in macrophage polarization playing a crucial role in its occurrence and development. Non-coding RNA has been found to play a key role in the polarization of macrophages. This study aims to explore the latest developments in research on the role of non-coding RNA-regulated macrophage polarization in the pathogenesis of AR, with the goal of identifying new approaches and potential targets for the diagnosis and treatment of AR.
Humans ; Rhinitis, Allergic/immunology* ; Macrophages/metabolism* ; RNA, Untranslated/genetics* ; Animals ; Macrophage Activation/genetics* ; Cell Polarity/genetics*

Hepatocellular carcinoma (HCC) is one of the fastest growing cancers in the world, ranking fourth among the causes of cancer-induced death in the world. At present, the field of HCC treatment is developing rapidly, and immunotherapy has been recognized as a promising treatment method, in which T cells play a key role in HCC immunotherapy. However, in the case of virus infection or in tumor microenvironment (TME), T cells will be continuously stimulated by antigens and then fall into the state of T cell exhaustion (Tex). This state will not only reduce the immunity of patients but also lead to poor efficacy of immunotherapy. Therefore, to deeply analyze the mechanism of Tex and to explore effective strategies to reverse Tex is the key point in the immunotherapy for HCC. This review aims to summarize the mechanism of Tex in HCC patients, and the current situation and shortcomings of drug research and development to reverse Tex at this stage, in order to provide theoretical basis for the optimization of immunotherapy regimen for HCC patients.
Humans ; Carcinoma, Hepatocellular/therapy* ; Liver Neoplasms/therapy* ; Immunotherapy/methods* ; T-Lymphocytes/immunology* ; Tumor Microenvironment/immunology* ; Animals ; T-Cell Exhaustion

Objective To explore the effect of Evodiamine (Evo) on the immune function of allergic rhinitis (AR) rats and the regulatory mechanism on C-C motif chemokine ligand 2 (CCL2)/ C-C motif chemokine receptor 2 (CCR2) pathway. Methods The related targets of Evo-AR-immune function were screened by network pharmacology, and the protein interaction network diagram of intersecting targets was constructed. The AR rat model was established by ovalbumin (OVA) combined with aluminium hydroxide, and the rats were divided into six groups: a normal control (NC) group, a model group, a Loratadine (LOR) group, an Evodiamine low dose (Evo-L) group, a Evodiamine high dose (Evo-H) groups, and an Evo-H combined with CCL2 group. After the last administration, the symptoms of rats in each group were scored; ELISA was applied to detect the levels of histamine, immunoglobulin E (IgE), interleukin 4 (IL-4), IL-13 and interferon γ (IFN-γ); Diff-Quick staining solution was applied to detecte the number of cells in the nasal lavage fluid (NALF); hematoxylin eosin (HE) staining was applied to observe the pathological changes of nasal mucosa tissue; real-time quantitative PCR was applied to detect the levels of CCL2 and CCR2 mRNA in tissue; Western blot was applied to detect the expression levels of CCL2, CCR2 and CXC motif chemokine ligand 8 (CXCL8) proteins in nasal mucosa. Results There were eight intersection targets of EVo-AR-immune function, and protein interaction network diagram showed that CXCL8 was the core target. Compared with the NC group, the score of nasal symptoms, the levels of histamine, IgE, IL-4 and IL-13, the numbers of eosinophil, macrophages, neutrophils, lymphocytes and total cells, the mRNA and protein expression levels of CCL2 and CCR2, and the expression of CXCL8 protein in the model group were increased, while the level of IFN-γ was decreased. Compared with the model group, the score of nasal symptoms, the levels of histamine, IgE, IL-4 and IL-13, the numbers of eosinophil, macrophages, neutrophils, lymphocytes and total cells, the mRNA and protein expression levels of CCL2 and CCR2, and the expression of CXCL8 protein in LOR and Evo groups were decreased, while the level of IFN-γ was increased. Further use of CCL2 recombinant protein for compensatory experiments revealed that the improvement effect of Evo on immune function in AR rats was reversed by CCL2. Conclusion Evo can improve the immune function of AR rats, and its mechanism may be related to the inhibition of the CCL2/CCR2 pathway.
Animals ; Receptors, CCR2/immunology* ; Signal Transduction/drug effects* ; Chemokine CCL2/immunology* ; Rats ; Rhinitis, Allergic/metabolism* ; Immunoglobulin E/blood* ; Quinazolines/pharmacology* ; Male ; Interferon-gamma ; Rats, Sprague-Dawley ; Interleukin-13 ; Histamine ; Interleukin-4/immunology* ; Disease Models, Animal

Objective To mine and analyze the routine blood test data of children with allergic rhinitis (AR), identify routine blood parameters related to childhood allergic rhinitis, establish an effective diagnostic model, and evaluate the performance of the model. Methods This study was a retrospective study of clinical cases. The experimental group comprised a total of 1110 children diagnosed with AR at the First Affiliated Hospital of Air Force Medical University during the period from December 12, 2020 to December 12, 2021, while the control group included 1109 children without a history of allergic rhinitis or other allergic diseases who underwent routine physical examinations during the same period. Information such as age, sex and routine blood test results was collected for all subjects. The levels of routine blood test indicators were compared between AR children and healthy children using comprehensive intelligent baseline analysis, with indicators of P≥0.05 excluded; variables were screened by Lasso regression. Binary Logistic regression was used to further evaluate the influence of multiple routine blood indexes on the results. Five kinds of machine model algorithms were used, namely extreme value gradient lift (XGBoost), logistic regression (LR), gradient lift decision tree (LGBMC), Random forest (RF) and adaptive lift algorithm (AdaBoost), to establish the diagnostic models. The receiver operating characteristic (ROC) curve was used to screen the optimal model. The best LightGBM algorithm was used to build an online patient risk assessment tool for clinical application. Results Statistically significant differences were observed between the AR group and the control group in the following routine blood test indicators: mean cellular hemoglobin concentration (MCHC), hemoglobin (HGB), absolute value of basophils (BASO), absolute value of eosinophils (EOS), large platelet ratio (P-LCR), mean platelet volume (MPV), platelet distribution width (PDW), platelet count (PLT), absolute values of leukocyte neutrophil (W-LCC), leukocyte monocyte (W-MCC), leukocyte lymphocyte (W-SCC), and age. Lasso regression identified these variables as important predictors, and binary Logistic regression further analyzed the significant influence of these variables on the results. The optimal machine learning algorithm LightGBM was used to establish a multi-index joint detection model. The model showed robust prediction performance in the training set, with AUC values of 0.8512 and 0.8103 in the internal validation set. Conclusion The identified routine blood parameters can be used as potential biomarkers for early diagnosis and risk assessment of AR, which can improve the accuracy and efficiency of diagnosis. The established model provides scientific basis for more accurate diagnostic tools and personalized prevention strategies. Future studies should prospectively validate these findings and explore their applicability in other related diseases.
Humans ; Male ; Female ; Rhinitis, Allergic/blood* ; Child ; Biomarkers/blood* ; Retrospective Studies ; Early Diagnosis ; Child, Preschool ; ROC Curve ; Logistic Models ; Hematologic Tests ; Algorithms ; Adolescent ; Machine Learning