Background: Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear. Methods: We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP). Results: We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin. Conclusions PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.

Neutrophil extracellular traps (NETs), intricate reticular structures released by activated neutrophils, play a pivotal regulatory role in the pathogenesis of malignant tumors. Lung cancer is one of the most prevalent malignancies globally, with persistently high incidence and mortality rates. Recent studies have revealed that NETs dynamically modulate the tumor microenvironment through unique pathological mechanisms, exhibiting complex immunoregulatory characteristics during the progression of lung cancer, and this discovery has increasingly become a focal point in tumor immunology research. This paper provides a comprehensive review of the latest advancements in NETs research related to lung cancer, offering an in-depth analysis of their impact on lung cancer progression, their potential diagnostic value, and the current state of research on targeting NETs for lung cancer prevention and treatment. The aim is to propose novel strategies to enhance therapeutic outcomes and improve the prognosis for lung cancer patients.
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Extracellular Traps/immunology* ; Humans ; Lung Neoplasms/metabolism* ; Neutrophils/metabolism* ; Animals ; Tumor Microenvironment

Background: Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear. Methods: We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP). Results: We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin. Conclusions PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.

Background: Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear. Methods: We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP). Results: We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin. Conclusions PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.

OBJECTIVES: To study the clinical effect of the L-shape technique combined with concentrated growth factor on the horizontal bone defects of maxillary anterior teeth. METHODS: Twenty-five implants from 25 patients who underwent single maxillary anterior tooth implantation with simultaneous bone grafting were selected as the study subjects. Based on the bone grafting techniques, the patients were divided into a test group (L-shaped technique with guided bone regeneration combined with concentrated growth factor, 11 cases) and a control group (traditional guided bone regeneration combined with concentrated growth factor, 14 cases). The early discomfort and wound healing conditions in the two groups at two weeks after surgery were compared. The horizontal bone thickness, vertical bone thickness, and grayscale values in the augmentation area were measured immediately postsurgery and six months after surgery. Implant stability, hard tissue resorption within six months, and grayscale values were compared between the two groups. RESULTS: Differences in early discomfort, wound healing, implant stability, and grayscale values between the two groups were not statistically significant (P>0.05). Vertical bone thickness in the test group was significantly better than that in the control group at six months after surgery (P<0.05). The variation in horizontal bone thickness in the test group was significantly higher than that in the control group (P<0.05). CONCLUSIONS The application of the L-shape technique with concentrated growth factor for horizontal bone defects in the anterior maxillary area yielded satisfactory short-term results in terms of bone augmentation, early discomfort, wound healing, and implant stability at six months after surgery.
Humans ; Maxilla/diagnostic imaging* ; Intercellular Signaling Peptides and Proteins/therapeutic use* ; Wound Healing ; Bone Transplantation/methods* ; Dental Implantation, Endosseous/methods* ; Bone Regeneration ; Male ; Female ; Adult ; Dental Implants, Single-Tooth ; Middle Aged

Objective:To develop and validate a diagnostic model for pancreatic benign and malignant tumors using radiomics technology.Methods:A retrospective analysis was conducted on the clinical data of 113 patients with pancreatic tumors who underwent surgical treatment at the Hepatobiliary and Pancreatic Surgery Departments of the Second Hospital and the First Hospital of Hebei Medical University from January 2020 to December 2022. There were 59 male and 54 female patients, aged (55.3±16.8) years. Preoperative enhanced thin-slice computed tomography (CT) data and postoperative pathological diagnosis results were collected. Data from 74 patients at the Second Hospital were selected, and according to the random classification principle of 7∶3, the data of 52 patients were determined as the training set for model construction, while the remaining 22 patients' data served as the internal validation set. Data from 39 patients at the First Hospital of Hebei Medical University were used as the external validation set to assess the generali-zability of the established model. The region of interest in the lesions on CT images was analyzed using three-dimensional radiomics feature extraction, and the top 5 features were selected using feature selection methods. Radiomics models were established for the selected features using 17 classifiers. The performance of the models was evaluated using the area under curve (AUC) of the receiver operating characteristic (ROC).Results:Two hundred and fifty-five models were established with 15 feature selection methods and 17 classifiers. 7 models with the AUC greater than 0.7 were selected, among which the best one was LASSO-K neighbors classifier model, constructed using the LASSO feature selection method and the k-nearest neighbors algorithm, achieving AUC values of 0.933 (95% CI: 0.859-0.984) in the training set, 0.973 (95% CI: 0.896-1.000) in the validation set, and 0.774 (95% CI: 0.624-0.908) in the external validation set, with satisfactoryclassification and generalization ability. Conclusion:The radiomics-based diagnostic model for pancreatic benign and malignant tumors can effectively distinguish the benignancy and malignancy of tumors. The LASSO-K neighbors classifier model demonstrated high accuracy and reliability in this study.

Estrogen, through binding to its receptors in the female endometrium, promotes the proliferation, differentiation, and angiogenesis of endometrial stromal cells, thereby playing a critical role in endometrial injury repair, regeneration, and the prevention and treatment of intrauterine adhesions. Currently, various estrogen-based pharmaceutical formulations are applied in clinical practice, and the development of related products is progressively advancing. This review systematically outlines the etiology of endometrial injury and the mechanisms by which estrogen facilitates endometrial repair and regeneration. Furthermore, it highlights recent research progress and clinical applications of estrogen-based therapies in endometrial regeneration, aiming to provide a valuable reference for relevant scientific research and clinical practice.

Estrogen, through binding to its receptors in the female endometrium, promotes the proliferation, differentiation, and angiogenesis of endometrial stromal cells, thereby playing a critical role in endometrial injury repair, regeneration, and the prevention and treatment of intrauterine adhesions. Currently, various estrogen-based pharmaceutical formulations are applied in clinical practice, and the development of related products is progressively advancing. This review systematically outlines the etiology of endometrial injury and the mechanisms by which estrogen facilitates endometrial repair and regeneration. Furthermore, it highlights recent research progress and clinical applications of estrogen-based therapies in endometrial regeneration, aiming to provide a valuable reference for relevant scientific research and clinical practice.

Objective:To develop and validate a diagnostic model for pancreatic benign and malignant tumors using radiomics technology.Methods:A retrospective analysis was conducted on the clinical data of 113 patients with pancreatic tumors who underwent surgical treatment at the Hepatobiliary and Pancreatic Surgery Departments of the Second Hospital and the First Hospital of Hebei Medical University from January 2020 to December 2022. There were 59 male and 54 female patients, aged (55.3±16.8) years. Preoperative enhanced thin-slice computed tomography (CT) data and postoperative pathological diagnosis results were collected. Data from 74 patients at the Second Hospital were selected, and according to the random classification principle of 7∶3, the data of 52 patients were determined as the training set for model construction, while the remaining 22 patients' data served as the internal validation set. Data from 39 patients at the First Hospital of Hebei Medical University were used as the external validation set to assess the generali-zability of the established model. The region of interest in the lesions on CT images was analyzed using three-dimensional radiomics feature extraction, and the top 5 features were selected using feature selection methods. Radiomics models were established for the selected features using 17 classifiers. The performance of the models was evaluated using the area under curve (AUC) of the receiver operating characteristic (ROC).Results:Two hundred and fifty-five models were established with 15 feature selection methods and 17 classifiers. 7 models with the AUC greater than 0.7 were selected, among which the best one was LASSO-K neighbors classifier model, constructed using the LASSO feature selection method and the k-nearest neighbors algorithm, achieving AUC values of 0.933 (95% CI: 0.859-0.984) in the training set, 0.973 (95% CI: 0.896-1.000) in the validation set, and 0.774 (95% CI: 0.624-0.908) in the external validation set, with satisfactoryclassification and generalization ability. Conclusion:The radiomics-based diagnostic model for pancreatic benign and malignant tumors can effectively distinguish the benignancy and malignancy of tumors. The LASSO-K neighbors classifier model demonstrated high accuracy and reliability in this study.

ObjectiveTo explore the molecular mechanism of Sanhuang Xiexintang （SHXXT） in protecting stress gastric ulcer （SGU） in rats through network pharmacology， molecular docking， and animal experiments. MethodThe active ingredients and corresponding targets in SHXXT were collected and screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， Traditional Chinese Medicine Information Database （TCMID）， Bioinformation Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine （BATMAN-TCM）， and Swiss Target Prediction database. SGU-related targets were screened from the Online Mendelian Inheritance in Man （OMIM）， Therapeutic Target Database （TTD）， GeneCards database， and PharmGKB database. Herbal-ingredient-target （H-C-T） network was constructed by using Cytoscape 3.9.1 software. Protein-protein interaction （PPI） of drug and disease intersection targets was analyzed by using the Protein Interaction Platform （STRING） database. Gene ontology （GO） enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway analysis were conducted through the Database for Annotation Visualization and Integrated Discovery （DAVID）. The active ingredients and key targets were validated using AutodockVina 1.2.2 molecular docking software， and the experimental results were further validated through animal experiments. ResultThe 55 active ingredients were screened， and 255 potential target genes for SHXXT treatment of SGU were predicted. The PPI analysis showed that protein kinase B （Akt）， phosphatase and tensin homolog deleted on chromosome ten （PTEN）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and cyclooxygenase-2 （COX-2） are the core targets of SHXXT for protecting SGU. GO and KEGG analyses showed that SHXXT may affect the development of SGU by regulating various biological processes such as the phosphoinositide 3-kinase （PI3K）/Akt signaling pathway and inflammatory processes. The molecular docking results showed that both the active ingredients and key targets had good binding ability. Animal experiments showed that compared with the blank group， the ulcer index （UI） of the model group was significantly increased （P<0.01）， and the serum levels of TNF-α and IL-1β significantly increased （P<0.01）. The phosphorylation level of PTEN in gastric mucosal tissue was significantly down-regulated （P<0.05）. The phosphorylation levels of PI3K， Akt， and nuclear factor kappa-B （NF-κB） were significantly up-regulated （P<0.05）. Compared with the model group， the UI of the treatment group was significantly reduced （P<0.01）， and the serum levels of TNF-α and IL-1β were significantly reduced （P<0.01）. The phosphorylation level of PTEN in gastric mucosal tissue was significantly up-regulated （P<0.01）， and the phosphorylation levels of PI3K， Akt， and NF-κB were significantly downregulated （P<0.01）. ConclusionThe application of network pharmacology prediction， molecular docking simulation， and animal experimental validation confirms that SHXXT regulates the PI3K/Akt/NF-κB signaling pathway to regulate the inflammatory response of rats and thus protects the gastric mucosa of SGU rats.