OBJECTIVE To investigate the efficacy and safety of omadacycline in the treatment of macrolide-unresponsive Mycoplasma pneumoniae pneumonia （MUMPP） in children. METHODS A retrospective study was conducted on children aged 1-18 years old with MUMPP who were hospitalized in the Department of Pediatrics， the First Affiliated Hospital of Xinjiang Medical University from January 2022 to June 2025. According to the selection of secondary antibiotics after 72 h of initial treatment with macrolides， they were divided into the omadacycline group and the doxycycline group. Based on conventional treatment， children in the omadacycline group were given intravenous infusion of 2.4 mg/kg （once daily） of omadacycline tosylate， while children in the doxycycline group were given oral doxycycline hydrochloride tablets at 2 mg/kg （twice daily）. The efficacy and safety were compared between the two groups of pediatric patients. Univariate analysis and multivariate Logistic regression analysis were performed on clinical efficacy， and subgroup analysis along with multiple sensitivity analyses were conducted to verify the robustness of the conclusions. RESULTS A total of 284 children with MUMPP were included in this study， with 142 in the omadacycline group and 142 in the doxycycline group. In terms of efficacy， although the hospitalization time of children in the omadacycline group was longer than that in the doxycycline group （ P ＜0.05）， the lung lesion absorption rate and clinical efficacy were significantly higher or better than those in the doxycycline group （ P ＜0.05）. The results of multivariate Logistic regression analysis showed that medication （OR＝5.300， 95%CI： 2.526-11.123）， length of hospital stay （OR＝1.348， 95%CI： 1.167-1.556）， and medication duration （OR＝1.422， 95%CI： 1.169-1.729） were influencing factors of clinical efficacy （ P ＜0.05）. The subgroup analysis results showed that the clinical efficacy of omadacycline was significantly better than that of doxycycline in all subgroups （ P ＜0.05）. The results of multiple sensitivity analysis showed that the regression coefficients B of the four models （gradually adjust variables） before and after inverse probability of treatment weighting were significantly greater than 1 （ P ＜0.05）. In terms of safety， there was no statistically significant difference in the inci dence of adverse drug reactions between the two groups of patients （ χ 2 ＝0.447， P ＝0.504）. CONCLUSIONS In the case of hospitalization and prolonged medication， the efficacy of omadacycline in treating childhood MUMPP is superior to that of doxycycline， and its safety is good.

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.

To address the challenges of complex digital model management and difficulties in model interoperability during the development of sophisticated products,this paper proposes an intelligent cloud architecture-based method for MBSE(model-based systems engineering)model microservice aggregation and adaptive integration.By introducing ontology semantic annotation and hash encoding mechanisms,we achieve unified encapsulation and service-oriented management of heterogeneous modeling tool resources.Combined with model virtual execution modes and dynamic resource orchestration technology,we design a task-oriented of Model-Based Microservice Deployment Framework,significantly improving model service scheduling efficiency and resource utilization.Leveraging a service-cluster-based model aggregation approach,we employ Hamming distance to calculate model capability compatibility,optimizing model discovery and orchestration processes.The prototype implementation and multi-phase experimental validation conducted in a domestic private cloud environment demonstrate that the proposed method effectively supports digital development across the entire lifecycle of aerospace products,enhancing model resource sharing and system integration efficiency.

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.