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.

Objective To analyze the causal relationship between immune cell phenotype and gastric cancer. Methods Bidirectional two-sample Mendelian randomization (MR) analysis was used to select 731 genetic variants involving immune cell phenotypes from the GWAS dataset as instrumental variables. Inverse-variance weighting method (IVW), weighted median method (WM), and MR-Egger regression were used for sensitivity analysis. Cochran Q test, MR-Egger regression, MR-PRESSO method, and remain-one method were also conducted. Results Changes in the absolute count of IgD+ B cells and CD14-CD16- cells were significantly associated with the risk of gastric cancer. A lower proportion of IgD+ B cells was associated with a lower risk of gastric cancer (OR=0.86, 95%CI: 0.79-0.94), while an increased number of CD4-CD8-T cells was associated with an increased risk of gastric cancer (OR=1.2, 95%CI: 1.1-1.3). Conclusion A causal relationship exists between immune cell phenotype and the risk of gastric cancer. Changes in specific immune markers may regulate the development of gastric cancer by affecting the tumor microenvironment.

ObjectiveBased on the conjoint analysis of transcriptome and metabolome， the key genes in the phenylpropanoid biosynthesis pathway of Lonicera macranthoides were explored， which provided a basis for further exploring the synthesis and regulation mechanism of phenylpropanoid compounds in "Xianglei" L. macranthoides. MethodsThe stem， leaves， and three flowering flowers of "Xianglei" L. macranthoides were selected as experimental materials to construct transcriptome and metabolome. The transcriptome and metabolomics were conjointly analyzed by the Kyoto Encyclopedia of Genes and Genomes （KEGG） database and weighted correlation network analysis （WGCNA）， and the key genes in the phenylpropanoid biosynthesis pathway of L. macranthoides were explored. ResultsIn this study， 77 differential phenylpropanoids and 315 differential genes were found. Through the joint analysis of transcription and metabolism， nine key differential metabolites and four key genes related to them were finally discovered. Among them， cinnamic acid， 5-O-caffeoylshikimic acid，sinapyl alcohol， and chlorogenic acid were higher in flowers， and the content of the iconic effective component， namely chlorogenic acid，decreased sharply during the withering period. Caffeic acid，ferulic acid， 5-hydroxyconiferaldehyde，p-coumaryl alcohol， and syringin were higher in leaves. These four key genes belong to the cinnamic alcohol dehydrogenase （CAD） family， 4-coumaric acid： Coenzyme A （4CL） family， hydroxycinnamyl transferase （HCT） family， and L-phenylalanine ammonlyase （PAL） family genes. ConclusionAmong the four key genes excavated from L. macranthoides， TRINITY_DN42767_c0_g6 is related to the synthesis of p-coumaryl alcohol and sinapyl alcohol. TRINITY_DN43525_c4_g1 uses caffeic acid，ferulic acid，and cinnamic acid as substrates to catalyze the next reaction. TRINITY_DN47958_c3_g4 correlates with the synthesis of 3-p-coumaroyl quinic acid and caffeoyl-CoA， and TRINITY_DN52595_c1_g2 correlates with cinnamic acid synthesis. These findings provide a basis for further exploring the synthesis and regulation mechanism of phenylpropanoids in "Xianglei" L. macranthoides.

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.

Gastrointestinal motility disorder is an important cause of digestive system diseases. Patients often suffer from nausea， vomiting， gastric retention， gastroparesis， constipation， and many other symptoms， and their quality of life is seriously reduced. Prokinetic agents are routinely used in clinical practice， but their long-term use is prone to problems such as reduced efficacy and increased adverse reactions. Since the incidence of gastrointestinal diseases has continued to rise globally in recent years， there is an urgent need for clinical development of safe and effective treatment strategies. Aurantii Fructus， a traditional Chinese medicine， has the effect of smoothing Qi and eliminating distention， and it has been used to treat gastrointestinal diseases for thousands of years. In modern clinical practice， it is mainly used for the treatment and auxiliary treatment of various gastrointestinal diseases such as functional dyspepsia， functional constipation， and irritable bowel syndrome. The efficacy is remarkable， and no adverse reactions have been reported at conventional doses. Therefore， it can greatly improve the symptoms of patients with gastrointestinal diseases and improve their quality of life. Modern research has revealed that there are many active components in Aurantii Fructus， among which flavonoids have the highest content and the most types. Flavonoids are the main active components in Aurantii Fructus to regulate gastrointestinal motility. Aurantii Fructus and its active components can affect gastrointestinal hormones， neural pathways， Cajal mesenchymal cells， and other multiple mechanisms. They can adjust gastrointestinal motility and correct gastrointestinal motility disorders， showing potential application value in the treatment of gastrointestinal motility disorders. However， a comprehensive analysis of Aurantii Fructus in this aspect is still lacking. This study summarized the pharmacological activities of active components of Aurantii Fructus extract and its flavonoids， volatile oils， alkaloids， and coumarin on the regulation of gastrointestinal motility and explored the latest research progress on its mechanism. Finally， the adverse reactions of Aurantii Fructus were summarized. It aims to provide a scientific basis for the research and clinical application of Aurantii Fructus and its active components in the regulation of gastrointestinal motility.

BackgroundChronic insomnia is characterized by a prolonged and recurrent course. The efficacy of repeated transcranial magnetic stimulation （rTMS） as a physical therapy method to improve sleep quality remains inadequately supported by evidence， particularly regarding its relationship with personality traits. ObjectiveTo explore the efficacy and influencing factors of rTMS in the treatment of chronic insomnia， and to provide insights into its therapeutic potential. MethodA total of 46 patients who met the diagnostic criteria for chronic insomnia according to the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）， and were treated at the Third Hospital of Mianyang from September 2022 to September 2023 were selected. Prior to treatment， participants underwent assessments using the Eysenck Personality Questionnaire （EPQ）， Hamilton Depression Scale-17 item （HAMD-17） and Hamilton Anxiety Scale （HAMA）. The Pittsburgh Sleep Quality Index （PSQI） was used to assess sleep quality before treatment， at the end of the second week of treatment and one week post-treatment. ResultsAt the end of the second week of treatment， patients exhibited significantly improved total PSQI score and subscale scores related to subjective sleep quality， sleep latency， sleep duration， sleep efficiency， sleep disturbance and daytime dysfunction （t=4.755~13.361， P<0.01）， with 24 cases （54.35%） showing effective treatment outcomes. Multiple linear regression analysis showed that introverted and extroverted personality traits contributed significantly to the regression equation （B=0.317， P<0.01）， explaining 29.90% of the total variation （R²=0.299）. ConclusionrTMS treatment may effectively improve the sleep quality of patients with chronic insomnia， with its therapeutic effect appearing to associated with introverted and extroverted personality traits. ［Funded by National Natural Science Project of China （number， 82372080）］

OBJECTIVE To systematically evaluate the efficacy and safety of intrawound vancomycin powder for preventing surgical site infections in total knee and total hip arthroplasty. METHODS Computer retrieval of PubMed, Embase, Web of Science, the Cochrane Library, CNKI, Wanfang Database, Chinese Biomedical Literature Database, The clinical research about intrawound vancomycin in total knee arthroplasty(TKA) and total hip arthroplasty(THA) for the prevention of surgical site infections were screened. The quality of included studies was assessed using the Cochrane risk bias assessment tool and the Newcastle-Ottawa Scale. Meta-analysis was performed using RevMan 5.4 software. RESULTS Finally, 20 literature were included, including 1 prospective randomized controlled trial, 2 prospective cohort study, and 17 retrospective cohort study, with a total of 34900 patients. Meta-analysis showed that interventional group had a decreased tolal rate of prosthetic joint infection(PJI)[OR=0.44, 95%CI(0.35−0.56), P<0.000 01] and superficial infection[OR=0.27, 95%CI(0.19−0.41), P<0.000 01]compared with control group. Subgroup analysis showed that TKA and THA, primary and revision patients who received intrawound vancomycin had lower rates of PJI, the differences were statistical significance(P<0.05). Meta-analysis of 11 studies reported adverse reaction suggested that the total rate of adverse reactions in the intervention group(7.68%) was higher than that in the control group(5.68%) with significant differences[OR=1.47, 95%CI(1.14−1.89), P=0.003)]. CONCLUSION The current literature suggests that intrawound vancomycin can decrease the rate of PJI and superficial infection in primary and revision TKA and THA , however, it may increase risk of aseptic wound complications and other adverse reaction.

BackgroundVestibular neuritis is a common clinical acute peripheral vertigo disorder. Some patients may experience negative emotions states， leading to chronic exacerbation of vestibular neuritis and a poorer prognosis. Further research is needed to understand the psychological state of patients with vestibular neuritis and its influencing factors. ObjectiveTo explore the relationship between depressive symptoms and vestibular symptoms in patients with vestibular neuritis and its influencing factors， so as to provide references for clinical intervention. MethodsA total of 86 patients with vestibular neuritis， hospitalized in the Department of Neurology of the Third Hospital of Mianyang from June 2021 to June 2023， were included in the study. Assessments were conducted using the Hamilton Depression Scale-17 item （HAMD-17）， Dizziness Assessment Rating Scale （DARS） and Dizziness Handicap Inventory （DHI）. Patients were divided into depression group（n=46） and non-depression group（n=40） based on HAMD-17 score. Pearson correlation analysis was used to examine the correlation among each scale score. Binary Logistic regression was used to identify influencing factors for depressive symptoms. ResultsAmong the 86 patients， 46 （53.49%） exhibited depressive symptoms. Statistically significant differences were observed between depression group and non-depression group in terms of age， disease duration， years of education， DARS score and DHI score （t=4.512， 4.921， 2.712， 3.529， 5.471， P<0.01 ）. In depression group， HAMD-17 score was positively correlated with DARS score and DHI score （r=0.345， 0.335， P<0.01）. Binary Logistic regression analysis showed that age （OR=4.352， 95% CI： 1.520~12.462）， disease duration（OR=3.772， 95% CI： 1.339~10.630）， years of education （OR=0.074， 95% CI： 0.235~0.923）， DARS score （OR=1.213， 95% CI： 0.405~3.628） and DHI score （OR=3.619， 95% CI： 1.246~10.514） were the influencing factors of depressive symptoms among patients with vestibular neuritis. ConclusionDepressive symptoms in patients with vestibular neuritis are positively correlated with vestibular symptoms. Risk factors for depressive symptoms in patients with vestibular neuritis include age， disease duration， DARS score and DHI score， while years of education serve as a protective factor.

Robotic surgery is known as the"third technological revolution"in the field of surgery,and is an important milestone in the development of modern surgery.However,our country's innovative surgical robot industry is still in its early stages,and it is only being utilized in certain surgical fields.To explore the effectiveness of the application of do-mestic surgical robot in oral and maxillofacial surgery,the author successfully completed a case of benign parotid tumor resection with the assistance of a domestic autonomous robot.The operation was successful,facial nerve function was preserved,and postoperative wound healing was good.

Objective : To investigate the correlation between the expression level of YTHDF1 in oral squamous cell carcinoma ( OSCC) and clinicopathologic features and its potential prognostic value． Methods : The expression of YTHDF1 in 132 OSCC tissues and 66 paracancerous tissues was detected by immunohistochemistry (IHC) ，and the expression of YTHDF1 protein in OSCC cell lines was detected by Western blot．The correlation between YTHDF1 and clinicopathological features was analyzed by chi-square test．Kaplan-Meier and Cox factors were used to analyze the factors affecting the survival time of the patients and draw the survival curves of the YTHDF1 gene to evaluate its potential clinical significance. Results : The expression of YTHDF1 in OSCC tissues was higher than that in para- cancerous tissues (P＜0. 001) ，and the expression of YTHDF1 protein increased in OSCC cell lines compared with normal oral epithelial keratinocytes (P ＜0. 001) ．The expression of YTHDF1 was correlated with the TNM stage and T stage of patients with OSCC (P＜0. 05) ，and the patients with high expression of YTHDF1 had a shorter sur- vival time compared with those with low expression (P ＜0. 001) ． Conclusion High expression of YTHDF1 may be associated with poor patient prognosis and YTHDF1 may be able to serve as a target for OSCC treatment.