ObjectiveTo elucidate the potential mechanisms by which the classic prescription Anmeidan alleviates cognitive impairment in insomnia model rats through metabolic profiling. MethodsA total of 60 SD rats were randomly divided into six groups： blank group， model group， low-， medium-， and high-dose Anmeidan groups， and the Suvorexant group， with 10 rats in each group. Except for the blank group， the insomnia model was established in all other groups via intraperitoneal injection of para-chlorophenylalanine. The Suvorexant group was administered Suvorexant solution （30 mg·kg^-1·d^-1） by gavage， while the low-， medium-， and high-dose Anmeidan groups received Anmeidan decoction （4.55， 9.09， 18.18 g·kg^-1·d^-1） by gavage. The blank group received an equivalent volume of normal saline. The open field test was used to assess spatial exploration and anxiety/depressive-like behaviors in rats. Serum levels of epidermal growth factor （EGF）， brain-derived neurotrophic factor （BDNF）， and vasoactive intestinal peptide （VIP） were measured using enzyme-linked immunosorbent assay （ELISA）. Untargeted metabolomics was employed to identify differential metabolites in rat serum， and systematic biological methods were applied to analyze the potential targets and pathways of Anmeidan. ResultsCompared to the blank group， the model group exhibited significant reductions in total distance traveled， average speed， number of entries into the central area， time spent in the central area， and frequency of upright events （P<0.01）， along with significant decreases in VIP， EGF， and BDNF levels （P<0.05，P<0.01）. A total of 100 differential metabolites were identified between the model and blank groups. Compared to the model group， the low-， medium-， and high-dose Anmeidan groups showed significant increases in total distance traveled， average speed， number of entries into the central area， time spent in the central area， and frequency of upright events （P<0.05，P<0.01）， as well as a significant increase in VIP levels （P<0.05，P<0.01）. Anmeidan significantly reversed abnormal changes in 67 metabolites compared to the model group. A combined analysis identified 134 potential targets of Anmeidan， with network topology analysis suggesting that Caspase-3， B-cell lymphoma 2 （Bcl-2）， nuclear transcription factor-κB （NF-κB）， interleukin-1β （IL-1β）， interleukin-2 （IL-2）， matrix metalloproteinase-9 （MMP-9）， and Toll-like receptor 4 （TLR4）， among others， may serve as key targets of Anmeidan. Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway analysis revealed major enriched pathways， including the cyclic adenosine monophosphate （cAMP） signaling pathway， hypoxia inducible factor-1 （HIF-1） signaling pathway， and IL-17 signaling pathway. ConclusionThis study demonstrates that Anmeidan can recalibrate abnormal metabolic profiles in insomnia model rats to mitigate cognitive impairment， with its mechanisms of action potentially involving the regulation of immune-inflammatory responses， energy metabolism， and apoptosis-related pathways.

Background/Aims: The long noncoding RNA DUXAP8 is a pivotal regulator in cancer pathogenesis, but the molecular mechanism underlying the role of DUXAP8 in colon cancer progression is underexplored. Methods: In addition to bioinformatic analyses, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to assess DUXAP8, microRNA-378a-3p, FOXQ1 expression in colon cancer tissues, and clinical data were analyzed to determine the correlation between DUXAP8 expression and colon cancer patient outcomes. Nuclear/cytoplasmic RNA fractionation was utilized to analyze the subcellular distribution of DUXAP8. Dual-luciferase and RNA immunoprecipitation assays were performed to confirm the binding of DUXAP8/FOXQ1 and microRNA-378a-3p. After cell transfection, qRT-PCR was performed to evaluate the modulatory relationship of DUXAP8/microRNA-378a-3p/FOXQ1. Cell Counting Kit-8, MTT, scratch healing, and Transwell assays were performed to evaluate the impact of DUXAP8/microRNA-378a-3p/ FOXQ1 expression on colon cancer cell functions. Results: The results revealed that the expression of DUXAP8 and FOXQ1 was upregulated in colon cancer tissues, while the expression of microRNA-378a-3p was down-regulated. The increased DUXAP8 expression was positively correlated with lymph node metastasis and TNM stage. Dual-luciferase and RNA immunoprecipitation assays demonstrated that DUXAP8 was a sponge for microRNA-378a-3p and targeted the ability of microRNA-378a-3p to regulate FOXQ1.In addition, functional experiment results revealed that overexpressed DUXAP8 facilitated the growth and migratory ability of colon cancer cells. DUXAP8 also reversed the tumor-suppressive effect of microRNA-378a-3p. However, silencing FOXQ1 could reverse the cancer-promoting effects of high DUXAP8 expression. Conclusions DUXAP8 expression was significantly increased in colon cancer, which was associated with lymph node metastasis and unfavorable outcomes in colon cancer patients. DUXAP8may hasten malignant progression of colon cancer cells through its effects on microRNA-378a-3p/FOXQ1.

Background/Aims: The long noncoding RNA DUXAP8 is a pivotal regulator in cancer pathogenesis, but the molecular mechanism underlying the role of DUXAP8 in colon cancer progression is underexplored. Methods: In addition to bioinformatic analyses, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to assess DUXAP8, microRNA-378a-3p, FOXQ1 expression in colon cancer tissues, and clinical data were analyzed to determine the correlation between DUXAP8 expression and colon cancer patient outcomes. Nuclear/cytoplasmic RNA fractionation was utilized to analyze the subcellular distribution of DUXAP8. Dual-luciferase and RNA immunoprecipitation assays were performed to confirm the binding of DUXAP8/FOXQ1 and microRNA-378a-3p. After cell transfection, qRT-PCR was performed to evaluate the modulatory relationship of DUXAP8/microRNA-378a-3p/FOXQ1. Cell Counting Kit-8, MTT, scratch healing, and Transwell assays were performed to evaluate the impact of DUXAP8/microRNA-378a-3p/ FOXQ1 expression on colon cancer cell functions. Results: The results revealed that the expression of DUXAP8 and FOXQ1 was upregulated in colon cancer tissues, while the expression of microRNA-378a-3p was down-regulated. The increased DUXAP8 expression was positively correlated with lymph node metastasis and TNM stage. Dual-luciferase and RNA immunoprecipitation assays demonstrated that DUXAP8 was a sponge for microRNA-378a-3p and targeted the ability of microRNA-378a-3p to regulate FOXQ1.In addition, functional experiment results revealed that overexpressed DUXAP8 facilitated the growth and migratory ability of colon cancer cells. DUXAP8 also reversed the tumor-suppressive effect of microRNA-378a-3p. However, silencing FOXQ1 could reverse the cancer-promoting effects of high DUXAP8 expression. Conclusions DUXAP8 expression was significantly increased in colon cancer, which was associated with lymph node metastasis and unfavorable outcomes in colon cancer patients. DUXAP8may hasten malignant progression of colon cancer cells through its effects on microRNA-378a-3p/FOXQ1.

Background/Aims: The long noncoding RNA DUXAP8 is a pivotal regulator in cancer pathogenesis, but the molecular mechanism underlying the role of DUXAP8 in colon cancer progression is underexplored. Methods: In addition to bioinformatic analyses, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to assess DUXAP8, microRNA-378a-3p, FOXQ1 expression in colon cancer tissues, and clinical data were analyzed to determine the correlation between DUXAP8 expression and colon cancer patient outcomes. Nuclear/cytoplasmic RNA fractionation was utilized to analyze the subcellular distribution of DUXAP8. Dual-luciferase and RNA immunoprecipitation assays were performed to confirm the binding of DUXAP8/FOXQ1 and microRNA-378a-3p. After cell transfection, qRT-PCR was performed to evaluate the modulatory relationship of DUXAP8/microRNA-378a-3p/FOXQ1. Cell Counting Kit-8, MTT, scratch healing, and Transwell assays were performed to evaluate the impact of DUXAP8/microRNA-378a-3p/ FOXQ1 expression on colon cancer cell functions. Results: The results revealed that the expression of DUXAP8 and FOXQ1 was upregulated in colon cancer tissues, while the expression of microRNA-378a-3p was down-regulated. The increased DUXAP8 expression was positively correlated with lymph node metastasis and TNM stage. Dual-luciferase and RNA immunoprecipitation assays demonstrated that DUXAP8 was a sponge for microRNA-378a-3p and targeted the ability of microRNA-378a-3p to regulate FOXQ1.In addition, functional experiment results revealed that overexpressed DUXAP8 facilitated the growth and migratory ability of colon cancer cells. DUXAP8 also reversed the tumor-suppressive effect of microRNA-378a-3p. However, silencing FOXQ1 could reverse the cancer-promoting effects of high DUXAP8 expression. Conclusions DUXAP8 expression was significantly increased in colon cancer, which was associated with lymph node metastasis and unfavorable outcomes in colon cancer patients. DUXAP8may hasten malignant progression of colon cancer cells through its effects on microRNA-378a-3p/FOXQ1.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

Background/Aims: The long noncoding RNA DUXAP8 is a pivotal regulator in cancer pathogenesis, but the molecular mechanism underlying the role of DUXAP8 in colon cancer progression is underexplored. Methods: In addition to bioinformatic analyses, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to assess DUXAP8, microRNA-378a-3p, FOXQ1 expression in colon cancer tissues, and clinical data were analyzed to determine the correlation between DUXAP8 expression and colon cancer patient outcomes. Nuclear/cytoplasmic RNA fractionation was utilized to analyze the subcellular distribution of DUXAP8. Dual-luciferase and RNA immunoprecipitation assays were performed to confirm the binding of DUXAP8/FOXQ1 and microRNA-378a-3p. After cell transfection, qRT-PCR was performed to evaluate the modulatory relationship of DUXAP8/microRNA-378a-3p/FOXQ1. Cell Counting Kit-8, MTT, scratch healing, and Transwell assays were performed to evaluate the impact of DUXAP8/microRNA-378a-3p/ FOXQ1 expression on colon cancer cell functions. Results: The results revealed that the expression of DUXAP8 and FOXQ1 was upregulated in colon cancer tissues, while the expression of microRNA-378a-3p was down-regulated. The increased DUXAP8 expression was positively correlated with lymph node metastasis and TNM stage. Dual-luciferase and RNA immunoprecipitation assays demonstrated that DUXAP8 was a sponge for microRNA-378a-3p and targeted the ability of microRNA-378a-3p to regulate FOXQ1.In addition, functional experiment results revealed that overexpressed DUXAP8 facilitated the growth and migratory ability of colon cancer cells. DUXAP8 also reversed the tumor-suppressive effect of microRNA-378a-3p. However, silencing FOXQ1 could reverse the cancer-promoting effects of high DUXAP8 expression. Conclusions DUXAP8 expression was significantly increased in colon cancer, which was associated with lymph node metastasis and unfavorable outcomes in colon cancer patients. DUXAP8may hasten malignant progression of colon cancer cells through its effects on microRNA-378a-3p/FOXQ1.

Objective To understand the epidemic characteristics and trends of gonorrhea in Shiyan City in recent years, and to provide a scientific basis for the formulation of prevention and control strategies and measures. Methods The network data of gonorrhea reported in Shiyan City from 2012 to 2023 were collected, and the epidemiological characteristics of reported gonorrhea cases in Shiyan City from 2012 to 2023 were analyzed by descriptive epidemiological statistical analysis methods. Results A total of 2 224 cases of gonorrhea were reported in Shiyan City from 2012 to 2023, with an average annual incidence of 5.55/100 000. The annual incidence ranged from 3.46/100 000 to 7.58/100 000, with statistical significance (χ² trend =95.193, df=1, P<0.001). The incidence of gonorrhea was generally on the rise. The cases of gonorrhea were mainly concentrated in the two main urban areas of Maojian District and Zhangwan District, with the incidence rates of 13.64/100 000 and 7.01/100 000, respectively. The average incidence rate of gonorrhea in the main urban area was higher than that in other counties and urban areas (χ²=634.017, df=1, P<0.001). The incidence in males was much higher than that in females (χ²=1171.064, df=1, P<0.001), with a male to female ratio of 7.46:1. The age of the cases was mainly concentrated in the age group of 20-49 years, accounting for 82.01%. In terms of occupational distribution, the number of cases reported by household and unemployed, unknown and farmers ranked the top three, accounting for 41.55%, 22.98%, and 18.12%, respectively. Conclusion The incidence of gonorrhea in Shiyan City from 2012 to 2023 is generally on the rise. It is necessary to carry out timely intervention measures according to the epidemic characteristics of gonorrhea, monitor and educate key groups, and strengthen the diagnosis, treatment and prevention of venereal diseases in order to effectively prevent the transmission of gonorrhea.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

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.

BackgroundPrevious studies have found that patients with generalized anxiety disorder （GAD） have impaired performance in executive function， and group cognitive behavioral therapy （CBT） has been shown to be effective in alleviating negative affect in patients with GAD， while its efficacy on executive function remains unclear. ObjectiveTo explore the efficacy of group CBT on anxiety symptom and executive function in GAD patients， so as to provide references for the rehabilitation program for GAD. MethodsA total of 80 consecutive patients with GAD who were hospitalized in Sleep and Psychosomatic Medical Center of Shiyan Taihe Hospital from March 2021 to August 2022 and met the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） diagnostic criteria for GAD were enrolled， and they were assigned into study group （n=40） and control group （n=40） using random number table methods. All patients were subjected to routine medication treatment and regular health education， based on this， study group received group CBT once a week （6 weeks， 60 to 90 minutes per session）. At the enrollment and after 6 weeks of treatment， patients were assessed using Hamilton Anxiety Scale （HAMA） and Frontal Assessment Battery （FAB）. ResultsANOVA with repeated measures on HAMA score revealed a significant time effect （F=1 870.320， P<0.01）， no significant group effect and no significant time×group interaction effect （F=1.254， 0.293， P>0.05）. Significant time effect， group effect and time×group interaction effect were reported on FAB scores （F=311.190， 4.399， 7.021， P<0.05 or 0.01）. Further analysis indicated that FAB scores of both groups after treatment were higher than those at baseline （t=200.569， 115.401， P<0.01）.And the FAB score of study group was higher than that of control group after treatment （t=-3.211， P<0.01）. ConclusionGroup CBT combined with medication treatment for GAD may alleviate the anxiety symptoms and improve executive function in GAD patients. ［Funded by Shiyan Science and Technology Bureau Pilot Scientific Research Project （number， 21Y21）］