BACKGROUND: This study aimed to investigate programmed death-ligand 1 tumor proportion score in predicting the safety and efficacy of PD-1/PD-L1 antibody-based therapy in treating patients with advanced non-small cell lung cancer (NSCLC) in a real-world setting. METHODS: This retrospective, multicenter, observational study enrolled adult patients who received PD-1/PD-L1 antibody-based therapy in China and met the following criteria: (1) had pathologically confirmed, unresectable stage III-IV NSCLC; (2) had a baseline PD-L1 tumor proportion score (TPS); and (3) had confirmed efficacy evaluation results after PD-1/PD-L1 treatment. Logistic regression, Kaplan-Meier analysis, and Cox regression were used to assess the progression-free survival (PFS), overall survival (OS), and immune-related adverse events (irAEs) as appropriate. RESULTS: A total of 409 patients, 65.0% ( n = 266) with a positive PD-L1 TPS (≥1%) and 32.8% ( n = 134) with PD-L1 TPS ≥50%, were included in this study. Cox regression confirmed that patients with a PD-L1 TPS ≥1% had significantly improved PFS (hazard ratio [HR] 0.747, 95% confidence interval [CI] 0.573-0.975, P = 0.032). A total of 160 (39.1%) patients experienced 206 irAEs, and 27 (6.6%) patients experienced 31 grade 3-5 irAEs. The organs most frequently associated with irAEs were the skin (52/409, 12.7%), thyroid (40/409, 9.8%), and lung (34/409, 8.3%). Multivariate logistic regression revealed that a PD-L1 TPS ≥1% (odds ratio [OR] 1.713, 95% CI 1.054-2.784, P = 0.030) was an independent risk factor for irAEs. Other risk factors for irAEs included pretreatment absolute lymphocyte count >2.5 × 10 9 /L (OR 3.772, 95% CI 1.377-10.329, P = 0.010) and pretreatment absolute eosinophil count >0.2 × 10 9 /L (OR 2.006, 95% CI 1.219-3.302, P = 0.006). Moreover, patients who developed irAEs demonstrated improved PFS (13.7 months vs. 8.4 months, P <0.001) and OS (28.0 months vs. 18.0 months, P = 0.007) compared with patients without irAEs. CONCLUSIONS A positive PD-L1 TPS (≥1%) was associated with improved PFS and an increased risk of irAEs in a real-world setting. The onset of irAEs was associated with improved PFS and OS in patients with advanced NSCLC receiving PD-1/PD-L1-based therapy.
Humans ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Lung Neoplasms/metabolism* ; Aged ; B7-H1 Antigen/metabolism* ; Programmed Cell Death 1 Receptor/metabolism* ; Adult ; Aged, 80 and over ; Immune Checkpoint Inhibitors/therapeutic use*

The Baihe Dihuang Decoction(BDD) is a representative traditional Chinese medicine formula that has been used to treat depression. This study employed metabolomics and network pharmacology to investigate the mechanism of BDD in the treatment of depression. Fifty male Sprague-Dawley(SD) rats were randomly assigned to the normal control group, model group, fluoxetine group, and high-and low-dose BDD groups. A rat model of depression was established through chronic unpredictable mild stress(CUMS), and the behavioral changes were detected by forced swimming test and open field test. Metabolomics technology was used to analyze the metabolic profiles of serum and hippocampal tissue to screen differential metabolites and related metabolic pathways. Additionally, network pharmacology and molecular docking techniques were used to investigate the key targets and core active ingredients of BDD in improving metabolic abnormalities of depression. A "component-target-metabolite-pathway" regulatory network was constructed. BDD could significantly improve depressive-like behavior in CUMS rats and regulate 12 differential metabolites in serum and 27 differential metabolites in the hippocampus, involving tryptophan metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, alanine, aspartate, and glutamate metabolism, tyrosine metabolism, and purine metabolism. Verbascoside, isorbascoside, and regaloside B were the key active ingredients for improving metabolic abnormalities in depression. Epidermal growth factor receptor(EGFR), protooncogene tyrosine-protein kinase(SRC), glycogen synthase kinase 3β(GSK3β), and androgen receptor(AR) were the key core targets for improving metabolic abnormalities of depression. This study offered a preliminary insight into the mechanism of BDD in alleviating metabolic abnormalities of depression through network regulation, providing valuable guidance for its clinical use and subsequent research.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Rats ; Metabolomics ; Depression/genetics* ; Antidepressive Agents/chemistry* ; Network Pharmacology ; Hippocampus/drug effects* ; Humans ; Molecular Docking Simulation ; Behavior, Animal/drug effects* ; Disease Models, Animal

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

OBJECTIVE: Peritoneal fibrosis (PF) is an adverse event that occurs during long-term peritoneal dialysis, significantly impairing treatment efficiency and adversely affecting patient outcomes. Astragaloside IV (AS-IV), a principal active component derived from Astragalus membranaceus (Fisch.) Bunge, has exhibited anti-inflammatory and antifibrotic effects in various settings. This study aims to investigate the potential therapeutic efficacy and mechanism of AS-IV in the treatment of PF. METHODS: The PF mouse model was established by intraperitoneal injection of 4.25% peritoneal dialysis fluid (100 mL/kg). The epithelial-mesenchymal transition (EMT) of HMrSV5 cells was induced by the addition of 10 ng/mL transforming growth factor β (TGF-β). The differentially expressed genes in HMrSV5 cells treated with AS-IV were screened using transcriptome sequencing analysis. The potential targets of AS-IV were screened using network pharmacology and analyzed using molecular docking and molecular dynamics simulations. RESULTS: Administration of AS-IV at doses of 20, 40, or 80 mg/kg effectively mitigated the increase in peritoneal thickness and the development of fibrosis in mice with PF. The expression of the fibrosis marker α-smooth muscle actin in the peritoneum was significantly decreased in AS-IV-treated mice. The treatment of AS-IV (10, 20, and 40 μmol/L) significantly delayed the EMT of HMrSV5 cells induced by TGF-β, as demonstrated by the decreased number of 5-ethynyl-2'-deoxyuridine-positive cells, reduced migrated area, and decreased expression of fibrosis markers. A total of 460 differentially expressed genes were detected in AS-IV-treated HMrSV5 cells through transcriptome sequencing, with notable enrichment in the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-AKT serine/threonine kinase 1 (AKT) signaling pathway. The reduced levels of phosphorylated PI3K (p-PI3K) and p-AKT were detected in HMrSV5 cells with AS-IV treatment. Epidermal growth factor receptor (EGFR) was predicted as a direct target of AS-IV, exhibiting strong hydrogen bond interactions. The activation of the PI3K-AKT pathway by the compound 740Y-P, and the activation of the EGFR pathway by NSC 228155 each partially counteracted the inhibitory effect of AS-IV on the EMT of HMrSV5 cells. CONCLUSION AS-IV delayed the EMT process in peritoneal mesothelial cells and slowed the progression of PF, potentially serving as a therapeutic agent for the early prevention and treatment of PF. Please cite this article as: Huang Y, Chu CL, Qiu WH, Chen JY, Cao LX, Ji SY, Zhu B, Wang GK, Shen QQ. Astragaloside IV delayed the epithelial-mesenchymal transition in peritoneal fibrosis by inhibiting the activation of EGFR and PI3K-AKT pathways. J Integr Med. 2025; 23(6):694-705.
Epithelial-Mesenchymal Transition/drug effects* ; Animals ; Saponins/pharmacology* ; Triterpenes/pharmacology* ; Mice ; Peritoneal Fibrosis/pathology* ; Proto-Oncogene Proteins c-akt/metabolism* ; ErbB Receptors/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Signal Transduction/drug effects* ; Male ; Humans ; Molecular Docking Simulation ; Cell Line ; Mice, Inbred C57BL

OBJECTIVE: Emerging evidence suggests that exposure to ultrafine particulate matter (UPM, aerodynamic diameter < 0.1 µm) is associated with adverse cardiovascular events. Previous studies have found that Shenlian (SL) extract possesses anti-inflammatory and antiapoptotic properties and has a promising protective effect at all stages of the atherosclerotic disease process. In this study, we aimed to investigated whether SL improves UPM-aggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis. METHODS: We established a mouse model of MI+UPM. Echocardiographic measurement, measurement of myocardialinfarct size, biochemical analysis, enzyme-linked immunosorbent assay (ELISA), histopathological analysis, Transferase dUTP Nick End Labeling (TUNEL), Western blotting (WB), Polymerase Chain Reaction (PCR) and so on were used to explore the anti-inflammatory and anti-apoptotic effects of SL in vivo and in vitro. RESULTS: SL treatment can attenuate UPM-induced cardiac dysfunction by improving left ventricular ejection fraction, fractional shortening, and decreasing cardiac infarction area. SL significantly reduced the levels of myocardial enzymes and attenuated UPM-induced morphological alterations. Moreover, SL significantly reduced expression levels of the inflammatory cytokines IL-6, TNF-α, and MCP-1. UPM further increased the infiltration of macrophages in myocardial tissue, whereas SL intervention reversed this phenomenon. UPM also triggered myocardial apoptosis, which was markedly attenuated by SL treatment. The results of in vitro experiments revealed that SL prevented cell damage caused by exposure to UPM combined with hypoxia by reducing the expression of the inflammatory factor NF-κB and inhibiting apoptosis in H9c2 cells. CONCLUSION Overall, both in vivo and in vitro experiments demonstrated that SL attenuated UPM-aggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis. The mechanisms were related to the downregulation of macrophages infiltrating heart tissues.
Animals ; Apoptosis/drug effects* ; Particulate Matter/adverse effects* ; Mice ; Male ; Inflammation/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Mice, Inbred C57BL ; Myocardial Ischemia/drug therapy* ; Cell Line

OBJECTIVE: Poxviruses are zoonotic pathogens that infect humans, mammals, vertebrates, and arthropods. However, the specific role of ticks in transmission and evolution of these viruses remains unclear. METHODS: Transcriptomic and metatranscriptomic raw data from 329 sampling pools of seven tick species across five continents were mined to assess the diversity and abundance of poxviruses. Chordopoxviral sequences were assembled and subjected to phylogenetic analysis to trace the origins of the unblasted fragments within these sequences. RESULTS: Fifty-eight poxvirus species, representing two subfamilies and 20 genera, were identified, with 212 poxviral sequences assembled. A substantial proportion of AT-rich fragments were detected in the assembled poxviral genomes. These genomic sequences contained fragments originating from rodents, archaea, and arthropods. CONCLUSION Our findings indicate that ticks play a significant role in the transmission and evolution of poxviruses. These viruses demonstrate the capacity to modulate virulence and adaptability through horizontal gene transfer, gene recombination, and gene mutations, thereby promoting co-existence and co-evolution with their hosts. This study advances understanding of the ecological dynamics of poxvirus transmission and evolution and highlights the potential role of ticks as vectors and vessels in these processes.
Animals ; Poxviridae/physiology* ; Ticks/virology* ; Phylogeny ; Transcriptome ; Evolution, Molecular ; Poxviridae Infections/virology* ; Genome, Viral

Occlusal rehabilitation is an effective means of treating tooth wear, edentulous jaws and other oral diseases. Among them, full-mouth fixed occlusal reconstruction can effectively restore aesthetics and function, but the complexity of the clinical process, the high sensitivity of the technique, and the high incidence of various complications have always drawn much attention. With the application and development of digital technology in occlusal rehabilitation, the treatment outcome has been improved compared with traditional treatment. However, there are many kinds of digital technology with different efficacy, how to build an efficiently standardized digital clinical technical solution is a current difficulty. Therefore, combined with the long-term work of the department of prosthodontics in our hospital, in this paper, the minimum (occlusal perception of thickness) and maximum (centric relation) geometric quantities which should be paid attention to during reconstruction are put forward. We systematically organized the clinical procedure of digital full-mouth fixed occlusal rehabilitation used in our department for a long time. In conclusion, a 5-stage 19-step or n-step solution (5-19N for short) characterized by "from large to small" restorative space splitting logic is proposed. It has a certain reference value for the future use of digital technology to deal with complex occlusal rehabilitation cases.
Humans ; Dental Occlusion ; Computer-Aided Design ; Mouth, Edentulous/rehabilitation*

The inflammatory effect of dietary is strongly related to the development of cancer,therefore,the diet-related inflammatory index was developed as a methodological tool to investigate the relationship between dietary,inflammation and tumors.In this paper,we summarized the results on diet-related inflammatory indices and common cancers of the digestive system based on relevant cancer epidemiological studies.The available epidemiological evidence suggests that pro-inflammatory diet is associated with an increased risk of gastrointestinal malignancies,with the strongest association with colorectal cancer,followed by esophageal and gastric cancers,and then pancreatic cancer,and the least evidence of studies with liver cancer.Among these studies,the level of evidence for esophageal cancer is lower than colorectal cancer,the study of gastric cancer has gender differences and problems in adjusting for confounders,and the study of pancreatic cancer has heterogeneous results.In view of the current research progress and deficiencies,prospective studies or population-based cohort studies,as well as strengthening nutritional epidemiological studies related to common tumors such as liver cancer could be considered in the future.This review is expecting to provide basic information and scientific basis for strengthening the related healthy eating behavior promotion in the prevention and control of digestive system tumors.

Anterior diastema is a common esthetic defect in China.The general treatment for a patient with diastema-ta,including orthodontics and direct and indirect restorations,is a multidisciplinary clinical procedure covering the ortho-dontics,operative dentistry,general dentistry,and prosthodontics department.Given the diversity of departments and the complex etiology of this defect,decision-making regarding the closing methods and time selection is undefined and unin-tegrated,which makes the long-term stability of closure unpredictable.This article proposed an etiology-based decision tree with actual measurement of diastemata width for diastemata closure.The decisional steps include classifying the eti-ological factors based on patients'medical history and clinical manifestation to evaluate the stability of diastemata.After maintaining the stability of diastemata,contemporary and multidisciplinary treatment plans were selected in accordance with the measured width of diastemata and patients'cosmetic psychology,economics,and available time.These decision trees focus on the challenges of collaboration among dental departments,propose an objective and efficient ways for con-nections,and promote efficient and effective diastemata closure.

Near infrared spectroscopy(NIRS)has emerged as an indispensable analytical technology for quality monitoring in industrial and agricultural production.It is widely used in quantitative analysis in areas such as food,agriculture and medicine.To meet the requirements of industrial and agricultural production,it is particularly important to develop a NIRS quantitative analysis model that can predict the multicomponent of different samples.In this study,the multicomponent quantitative analysis model of NIRS based on convolution neural network(MulCoSpecNet)was proposed.MulCoSpecNet was composed of an encoding and decoding module,an expert module,a gate module,a multicomponent quantitative prediction module,and a hyperparameter optimizer.The spectral noise and random errors were mitigated,and the signal-to-noise ratio was enhanced through up-sampling and down-sampling in the encoding and decoding module.Diverse weightings were employed by the expert module and gate module to construct distinct sub-spectra.The model prediction accuracy and generalization ability were enhanced by the multicomponent quantitative prediction module,which employed convolutional and pooling operations.The hyperparameters in the hyperparameter space were synchronously optimized by the hyperparameter optimizer.By taking public NIRS datasets of grain and corn as examples,the prediction results of MulCoSpecNet were compared with partial least squares(PLS),extreme learning machine(ELM),support vector regression(SVM)and back propagation neural network(BP).The results showed that compared to PLS,the prediction accuracy of MulCoSpecNet to grain and corn were increased by 25.5%?45.2%and 10.0%?35.7%,respectively.Compared to ELM,the prediction accuracy of MulCoSpecNet were increased by 17.8%?38.6%and 18.2%?37.2%,respectively.Compared to SVM,the prediction accuracy of MulCoSpecNet were increased by 33.6%?47.0%and 31.3%?50.7%,respectively.Compared to BP,the prediction accuracy of MulCoSpecNet were increased by 2.0%?58.5%and 29.6%?48.6%,respectively.The issues of low prediction accuracy and poor generalization ability were effectively solved by the MulCoSpecNet,which was a NIRS multicomponent prediction model based on convolutional neural network.It provided a theoretical foundation for establishing non-destructive and high-precision NIRS multicomponent quantitative analysis model.