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.

This study investigated the role of the nuclear factor of activated T cells c3 (NFATc3) in vascular smooth muscle cells (VSMCs) during aortic aneurysm and dissection (AAD) progression and the underlying molecular mechanisms. Cytoplasmic and nuclear NFATc3 levels were elevated in human and mouse AAD. VSMC-NFATc3 deletion reduced thoracic AAD (TAAD) and abdominal aortic aneurysm (AAA) progression in mice, contrary to VSMC-NFATc3 overexpression. VSMC-NFATc3 deletion reduced extracellular matrix (ECM) degradation and maintained the VSMC contractile phenotype. Nuclear NFATc3 targeted and transcriptionally upregulated matrix metalloproteinase 9 (MMP9) and MMP2, promoting ECM degradation and AAD development. NFATc3 promoted VSMC phenotypic switching by binding to eukaryotic elongation factor 2 (eEF2) and inhibiting its phosphorylation in the VSMC cytoplasm. Restoring eEF2 reversed the beneficial effects in VSMC-specific NFATc3-knockout mice. Cabamiquine-targets eEF2 and inhibits protein synthesis-inhibited AAD development and progression in VSMC-NFATc3-overexpressing mice. VSMC-NFATc3 promoted VSMC switch and ECM degradation while exacerbating AAD development, making it a novel potential therapeutic target for preventing and treating AAD.

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.

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.

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.

Although significant progress has been made in the development of novel targeted drugs for the treatment of acute myeloid leukemia(AML)in recent years,chemotherapy still remains the mainstay of treatment and the overall survival is poor in most patients.Here,we demonstrated the antileukemia activity of a novel small molecular compound NL101,which is formed through the modification on bendamustine with a suberanilohydroxamic acid(SAHA)radical.NL101 suppresses the proliferation of myeloid malignancy cells and primary AML cells.It induces DNA damage and caspase 3-mediated apoptosis.A genome-wide clustered regularly interspaced short palindromic repeats(CRISPR)library screen revealed that phosphatase and tensin homologous(PTEN)gene is critical for the regulation of cell survival upon NL101 treatment.The knockout or inhibition of PTEN significantly reduced NL101-induced apoptosis in AML and myelodysplastic syndrome(MDS)cells,accompanied by the activation of protein kinase B(AKT)signaling pathway.The inhibition of mammalian target of rapamycin(mTOR)by rapamycin enhanced the sensitivity of AML cells to NL101-induced cell death.These findings uncover PTEN protein expression as a major determinant of chemosensitivity to NL101 and provide a novel strategy to treat AML with the combination of NL101 and rapamycin.

Oxalate is an organic dicarboxylic acid that is a common component of plant foods.The kidneys are essential organs for oxalate excretion,but excessive oxalates may induce kidney stones.Jupiter micro-tubule associated homolog 2(JPT2)is a critical molecule in Ca2+mobilization,and its intrinsic mecha-nism in oxalate exposure and kidney stones remains unclear.This study aimed to reveal the mechanism of JPT2 in oxalate exposure and kidney stones.Genetic approaches were used to control JPT2 expression in cells and mice,and theJPT2 mechanism of action was analyzed using transcriptomics and untargeted metabolomics.The results showed that oxalate exposure triggered the upregulation of JPT2,which is involved in nicotinic acid adenine dinucleotide phosphate(NAADP)-mediated Ca2+mobilization.Tran-scriptomic analysis revealed that cell adhesion and macrophage inflammatory polarization were inhibited by JPT2 knockdown,and these were dominated by phosphatidylinositol 3-kinase(PI3K)/AKT signaling,respectively.Untargeted metabolomics indicated that JPT2 knockdown inhibited the produc-tion of succinic acid semialdehyde(SSA)in macrophages.Furthermore,JPT2 deficiency in mice inhibited kidney stones mineralization.In conclusion,this study demonstrates that oxalate exposure facilitates kidney stones by promoting crystal-cell adhesion,and modulating macrophage metabolism and in-flammatory polarization via JPT2/PI3K/AKT signaling.