Objective To analyze the differences in distribution of traditional Chinese medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without, and to explore the potential correlation between the distribution of TCM syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of TCM syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between TCM syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary TCM syndrome elements related to disease location were the lung and liver, and the primary TCM syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary TCM syndrome elements related to disease location were the lung and spleen, and the primary TCM syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of TCM syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there was significant difference in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, the results showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of TCM syndrome elements and the species abundance and composition of salivary microbiota between the patients with pulmonary nodules and the healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

To investigate effects of α-asarone and β-asarone on induced PC12 cell injury and related mechanisms. Aβ toxic injury cell model was induced by Aβ in PC12 cells. PC12 cells were divided into blank control group, model control group, α-asarone group (0.5, 1.0, β-asarone group (6.3, 12.5, vasoactive intestinal peptide (VIP) group, and VIP antagonist control group. Cell survival rate was detected by CCK-8 kit; cell apoptosis rate was detected by flow cytometry. The levels of inflammatory cytokines interleukin (IL)-1, , tumor necrosis factor (TNF)-α, oxidation-related inducible nitric oxide synthase (iNOS), nitric oxide (NO), apoptosis factors caspase-3 and p53 were detected by ELISA method. The expressions of C-Jun N-terminal kinase (JNK) and p38 mitogen-activated protein kinase (p38MAPK) were detected by Western blotting. Compared with model control group, cell survival rates of group, β-asarone group and VIP group increased; the cell apoptosis rate decreased; levels of apoptosis-related factors caspase-3, p53, inflammatory factors IL-1, TNF-α decreased; IL-10 level increased; levels of oxidization-related factors iNOS and NO decreased; the expression of JNK and p38MAPK protein decreased (all <0.05). After VIP antagonist intervention, the survival rate of β-asarone group decreased; apoptosis rate increased; apoptosis related factors caspase-3, p53, inflammatory factors IL-1, TNF-α increased; IL-10 decreased; oxidation related factors iNOS and NO increased; the expression of JNK and p38MAPK protein increased (all <0.05); while there were no significant changes in these indicators of α-asarone group (all >0.05). α-asarone and β-asarone have protective effects on PC12 cell injury induced by Aβ. β-asarone may inhibit inflammatory factors and oxidation-related factors through promoting VIP secretion, regulating JNK/MAPK pathway, and reducing PC12 cell apoptosis; however, the effect of α-asarone may be not related to VIP secretion.
Allylbenzene Derivatives ; Animals ; Anisoles/pharmacology* ; Apoptosis ; PC12 Cells ; Rats

Objective:To identify new prognostic markers and therapeutic targets for gastric adenocarcinoma.Methods:The public datasets of gastric adenocarcinoma collected from GEO database (GSE33335 and GSE63089) were downloaded for analysis. There were 70 GC tissues and paired normal tissues in the two profile datasets. Differentially expressed genes (DEGs) between GC tissues and normal stomach tissues were selected by the R software. Protein-protein interaction (PPI) of these DEGs were visualized by the Search Tool for the Retrieval of Interacting Genes (STRING). The key gene sets were analyzed by Cytoscape and Molecular Complex Detection (MCODE). The mRNA and protein expression levels of prognosis related genes identified by public database were confirmed by using GC tissues and paired normal tissues collected from July 2019 to September 2019 in Affiliated Hospital of Nantong University.Results:DEGs were identified in the two datasets by using R software. A total of 128 DEGs were detected, including 85 up-regulated genes ( log2FC>1.2 and FDR<0.01) and 43 down-regulated genes ( log2FC<-1.2 and FDR<0.01) in the GC tissues. PPI network model and MCODE model were established by using the Online String tool and Cytoscape software, and 27 key genes were obtained, including 25 genes related with prognosis of GC patients ( P<0.05). We identified 14 significant DEGs in GC tissues, including cyclin B1 (CCNB1), polo-like kinase 1 (PLK1) and pituitary-tumor transforming gene (PTTG1), which were significantly enriched in the cell cycle pathway through KEGG pathway enrichment analysis. The positive expression rate of PTTG1 in GC tissues was 68.8% (22/32), significantly higher than 18.8% (6/32) in normal gastric tissues ( P<0.05). Conclusions:The expression of PTTG1 is different in GC and gastric tissues, implicates it is the key gene in gastric carcinogenesis. The prognoses of GC patients with higher PTTG1 expression are worse. PTTG1 might participate in the development of gastric adenocarcinoma by regulating cell cycle.

Objective:To investigate the clinical features and prognosis of extranodal nasal-type NK/T-cell lymphoma of the extra-upper aerodigestive tract (extra-UADT NKTCL).Methods:The clinical data of 159 patients with extra-UADT NKTCL from the China Lymphoma Collaborative Group (CLCG) database between November 2001 and December 2015 were retrospectively analyzed. Kaplan-Meier survival analysis and Log-rank test were used to evaluate the prognosis. The Cox regression model is used for multi-factor analysis.Results:Extra-UADT NKTCL commonly occurs in skin and soft tissues (106/159, 66.7%) and gastrointestinal tract (31/159, 19.5%). The incidences of elevated lactate dehydrogenase (LDH) and Ann Arbor Ⅲ~Ⅳ stage were 47.8% (76/159) and 64.2% (102/159), respectively. The 3-year overall survival (OS) and progression-free survival (PFS) rates were 43.6% and 27.9%, respectively. The corresponding OS rates of primary skin/soft tissue site and gastrointestinal tract site were 41.0% and 59.4% ( P=0.281), while the PFS rates were 24.8% and 48.3%, respectively ( P=0.109). Combined modality treatment improved the 3-year OS of all the patients (58.4% vs 33.9%, P=0.001) and 3-year PFS (40.7% vs 20.7%, P=0.008) when compared with chemotherapy alone. LDH elevation, Ann Arbor synthesising and ≥2 junction external bits were intrusive as independent risk factors for total survival ( P<0.05), LDH elevation and ≥2 junction outer bits were intrusive as independent risk factors for progressionless survival( P<0.05). The distant extranodal dissemination was the primary failure patterns. Conclusions:Extra-UADT NKTCL appears to have distinct clinical characteristics and poor outcome. Compared with chemotherapy alone, combined modality treatment may improve the prognosis of patients with extra-UADT NKTCL.

Objective:To evaluate the prognosis and determine the failure patterns after radiotherapy for low-risk early-stage patients with extranodal NK/T-cell lymphoma, nasal-type (ENKTCL).Methods:A total of 557 patients from 2000—2015 with low-risk early-stage ENKTCL who received radiotherapy (RT) with or without chemotherapy (CT) from China Lymphoma Collaborative Group were retrospectively reviewed. Among them, 427 patients received combined modality therapy, whereas 130 patients received RT alone. Survivals were calculated by Kaplan-Meier method and compared with Log-rank test. Overall survival (OS) was compared with age and sex-matched general Chinese population using expected survival and standardized mortality ratio (SMR). Cox stepwise regression model was used for multivariate analysis.Results:The 5-year OS and progression-free survival (PFS) were 87.2% and 77.2%. The SMR was 3.59 ( P<0.001) at 1 year after treatment, whereas it was 1.50 at 4 years after treatment, without significant difference between ENKTCL group and country-matched general population ( P=0.146). Compared with RT alone, CMT did not result in significantly superior 5-year OS (87.0% vs 87.4%, P=0.961) or PFS (76.1% vs 80.7%, P=0.129). Local failure (11.5%, 64/557) and distant failure (10.8%, 60/557) were the main failure modes, while regional failure was rare (2.9%, 16/557). The 5-year locoregional control rate (LRC) was 87.2% for the whole group, with 89.5% for ≥50 Gy versus 73.7% for <50 Gy ( P<0.001). Radiotherapy dose was an independent factor affecting LRC( P<0.05). Conclusions:Radiotherapy achieves a favorable prognosis in patients with low-risk early-stage ENKTCL. The incidence of either locoregional or distant failure is low. Radiation dose still is an important prognostic factor for LRC.

Objective:To identify new prognostic markers and therapeutic targets for gastric adenocarcinoma.Methods:The public datasets of gastric adenocarcinoma collected from GEO database (GSE33335 and GSE63089) were downloaded for analysis. There were 70 GC tissues and paired normal tissues in the two profile datasets. Differentially expressed genes (DEGs) between GC tissues and normal stomach tissues were selected by the R software. Protein-protein interaction (PPI) of these DEGs were visualized by the Search Tool for the Retrieval of Interacting Genes (STRING). The key gene sets were analyzed by Cytoscape and Molecular Complex Detection (MCODE). The mRNA and protein expression levels of prognosis related genes identified by public database were confirmed by using GC tissues and paired normal tissues collected from July 2019 to September 2019 in Affiliated Hospital of Nantong University.Results:DEGs were identified in the two datasets by using R software. A total of 128 DEGs were detected, including 85 up-regulated genes ( log2FC>1.2 and FDR<0.01) and 43 down-regulated genes ( log2FC<-1.2 and FDR<0.01) in the GC tissues. PPI network model and MCODE model were established by using the Online String tool and Cytoscape software, and 27 key genes were obtained, including 25 genes related with prognosis of GC patients ( P<0.05). We identified 14 significant DEGs in GC tissues, including cyclin B1 (CCNB1), polo-like kinase 1 (PLK1) and pituitary-tumor transforming gene (PTTG1), which were significantly enriched in the cell cycle pathway through KEGG pathway enrichment analysis. The positive expression rate of PTTG1 in GC tissues was 68.8% (22/32), significantly higher than 18.8% (6/32) in normal gastric tissues ( P<0.05). Conclusions:The expression of PTTG1 is different in GC and gastric tissues, implicates it is the key gene in gastric carcinogenesis. The prognoses of GC patients with higher PTTG1 expression are worse. PTTG1 might participate in the development of gastric adenocarcinoma by regulating cell cycle.

Objective:To investigate the clinical features and prognosis of extranodal nasal-type NK/T-cell lymphoma of the extra-upper aerodigestive tract (extra-UADT NKTCL).Methods:The clinical data of 159 patients with extra-UADT NKTCL from the China Lymphoma Collaborative Group (CLCG) database between November 2001 and December 2015 were retrospectively analyzed. Kaplan-Meier survival analysis and Log-rank test were used to evaluate the prognosis. The Cox regression model is used for multi-factor analysis.Results:Extra-UADT NKTCL commonly occurs in skin and soft tissues (106/159, 66.7%) and gastrointestinal tract (31/159, 19.5%). The incidences of elevated lactate dehydrogenase (LDH) and Ann Arbor Ⅲ~Ⅳ stage were 47.8% (76/159) and 64.2% (102/159), respectively. The 3-year overall survival (OS) and progression-free survival (PFS) rates were 43.6% and 27.9%, respectively. The corresponding OS rates of primary skin/soft tissue site and gastrointestinal tract site were 41.0% and 59.4% ( P=0.281), while the PFS rates were 24.8% and 48.3%, respectively ( P=0.109). Combined modality treatment improved the 3-year OS of all the patients (58.4% vs 33.9%, P=0.001) and 3-year PFS (40.7% vs 20.7%, P=0.008) when compared with chemotherapy alone. LDH elevation, Ann Arbor synthesising and ≥2 junction external bits were intrusive as independent risk factors for total survival ( P<0.05), LDH elevation and ≥2 junction outer bits were intrusive as independent risk factors for progressionless survival( P<0.05). The distant extranodal dissemination was the primary failure patterns. Conclusions:Extra-UADT NKTCL appears to have distinct clinical characteristics and poor outcome. Compared with chemotherapy alone, combined modality treatment may improve the prognosis of patients with extra-UADT NKTCL.

Objective:To evaluate the prognosis and determine the failure patterns after radiotherapy for low-risk early-stage patients with extranodal NK/T-cell lymphoma, nasal-type (ENKTCL).Methods:A total of 557 patients from 2000—2015 with low-risk early-stage ENKTCL who received radiotherapy (RT) with or without chemotherapy (CT) from China Lymphoma Collaborative Group were retrospectively reviewed. Among them, 427 patients received combined modality therapy, whereas 130 patients received RT alone. Survivals were calculated by Kaplan-Meier method and compared with Log-rank test. Overall survival (OS) was compared with age and sex-matched general Chinese population using expected survival and standardized mortality ratio (SMR). Cox stepwise regression model was used for multivariate analysis.Results:The 5-year OS and progression-free survival (PFS) were 87.2% and 77.2%. The SMR was 3.59 ( P<0.001) at 1 year after treatment, whereas it was 1.50 at 4 years after treatment, without significant difference between ENKTCL group and country-matched general population ( P=0.146). Compared with RT alone, CMT did not result in significantly superior 5-year OS (87.0% vs 87.4%, P=0.961) or PFS (76.1% vs 80.7%, P=0.129). Local failure (11.5%, 64/557) and distant failure (10.8%, 60/557) were the main failure modes, while regional failure was rare (2.9%, 16/557). The 5-year locoregional control rate (LRC) was 87.2% for the whole group, with 89.5% for ≥50 Gy versus 73.7% for <50 Gy ( P<0.001). Radiotherapy dose was an independent factor affecting LRC( P<0.05). Conclusions:Radiotherapy achieves a favorable prognosis in patients with low-risk early-stage ENKTCL. The incidence of either locoregional or distant failure is low. Radiation dose still is an important prognostic factor for LRC.

Objective: In order to investigate the clinical features and influence factors for incidence in patients with radiation-induced external auditory canal carcinoma (RIEACC). Methods: The nasopharyngeal carcinoma (NPC) 16 patients who were diagnosised RIEACC after radiotherapy in the Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University from January 1990 to December 2017 were retrospectively analysis. The influence factors analysis were used Logistic regression analysis. Results: Univariate analysis showed that age, somking history, family history of cancer and NPC stage were the influencing factors. Multi-factor logistic regression analysis showed that age, family history of cancer and NPC stage were independent risk factors. Conclusions RIEACC is rare complication of NPC patients received radiotherapy, which is also a multifactorial outcome. Age, family history of cancer and NPC stage is preliminary the main influencing factor. Although RIEACC has a low incidence, its malignancy should be highly vigilant.