To study the characteristics of periostin， tenascin-C （TNC）， and soluble human matrix metalloproteinase-2 （sST2） levels in asthmatic children infected with Mycoplasma pneumoniae and their impact on acute asthma exacerbations.
Methods
A total of 187 asthmatic children with mycoplasma pneumoniae infection who were hospitalized and treated in our hospital from May 2020 to October 2022 were selected， including 104 males and 83 females， with ages ranging from 10 to 14 years and a mean age of（12.07±1.25） years. The children were categorized into two groups： a remission group （n=134） and an acute exacerbation group （n=53）， based on the presence of acute asthma exacerbation. A comparison was made between the two groups in terms of general clinical characteristics， as well as serum levels of periostin， TNC，and sST2. Univariate and multivariate logistic regression analyses were conducted to ascertain whether serum periostin， TNC， and sST2 levels could independently predict the risk of acute exacerbations in children with asthma infected by Mycoplasma pneumoniae. Through the use of receiver operating characteristic （ROC）curves， cutoff values for serum periostin， TNC， and sST2 were identified. Based on the results of multivariate logistic regression analysis， a risk prediction nomogram model incorporating serum periostin， TNC， and sST2 was constructed. The model degree of fitting was evaluated using Hosmer-Lemeshow test and calibration curves， the predictive performance was assessed through ROC curve analysis， and the clinical application value was evaluated using decision curve analysis （DCA）.
Results
Compared to the remission group， the acute exacerbation group had a lower proportion of regular use of inhaled corticosteroids （ICS）， a lower forced expiratory volume in one second/forced vital capacity ratio （FEV1/FVC），and forced expiratory volume in 1 second as a percentage of predicted value （FEV1/pred）， and higher levels of serum periostin， TNC， and sST2（P＜0.05）. ROC analysis indicated that the AUC values for serum periostin， TNC， and sST2 in predicting acute exacerbations in children with asthma infected by Mycoplasma pneumoniae were 0.673， 0.737， and 0.720， respectively. Multivariate logistic regression analysis indicated that high periostin ［OR （95%CI）=1.031 （1.014～1.049）］， high TNC ［OR （95%CI）=1.099 （1.055～1.144）］， and high sST2 ［OR （95%CI）=1.171（1.080～1.271）］ were all independent risk factors for acute exacerbations in children with asthma infected by Mycoplasma pneumoniae （P＜0.05）. The nomogram model constructed based on the aforementioned three indicators demonstrated favorable degree of fitting （Hosmer-Lemeshow test： χ2=7.356， df=8， P=0.499）. ROC analysis revealed that the AUC value of this nomogram model for predicting acute exacerbations in pediatric patients was 0.838 （95% CI： 0.779～0.898， P＜0.001）. DCA analysis indicated that this nomogram prediction model exhibited satisfactory clinical net benefit across a threshold probability range of 0～0.95.
Conclusion
The levels of serum periostin， TNC， and sST2 in children with asthma complicated by Mycoplasma pneumoniae infection are strongly correlated with the likelihood of experiencing acute asthma exacerbations.Utilizing a model that incorporates these serum biomarkers can greatly assist healthcare providers in assessing the risk of acute asthma exacerbations in this specific group of children， thereby demonstrating significant clinical utility.
To analyze the related factors of the pause duration caused by the manualmechanical conversion of cardiopulmonary resuscitation （CPR） in out-of-hospital cardiac arrest （OHCA）patients.
Methods
A retrospective cohort study was conducted to analyze the OHCA patients treated by the direct-affiliated emergency stations of Yixing Emergency Medical Center from June 2023 to January 2024， all of whom received mechanical chest compression outside the hospital. A total of 160 OHCA patients were enrolled， including 120 males （75.0%） and 40 females （25.0%）， aged 34 to 89 years， with an average age of （62.75±15.48） years. Basic patient information， rescue data， and data related to the pause duration caused by the conversion to mechanical compression were collected.
Results
The patient's weight （r=0.238， P=0.002）， body mass index （r=0.238， P=0.002）， and the duration of mechanical compression initiation（r=0.912， P＜0.001） were positively linearly correlated with the pause duration. Multiple linear regression analysis revealed that the patient's height （P=0.01）， body mass index （BMI） （P=0.046）， and the duration of mechanical compression initiation （P＜0.001） were independent risk factors for the pause duration.
Conclusion
The patient's height， BMI， and the duration of mechanical compression initiation are correlated with the duration of chest compression interruption.
To explore the roles and immune regulatory mechanisms of key genes in mitophagy and ferroptosis in sepsis-induced acute respiratory distress syndrome （ARDS） using an integrative analysis of machine learning and transcriptomics.
Methods
The DEGs from the GSE32707 dataset in the GEO database were obtained and the differential genes screened. The core genes were identified and validated by secondary screening of DEGs with LASSO regression and the SVM-RFE algorithm， and their diagnostic performance with ROC curves was evaluated. DEGs-related biological pathways and immune cell interactions were investigated via GSEA and immune infiltration analysis. The hub genes by intersecting mitophagy-related genes， ferroptosis markers， and core DEGs were determined. A multi-dimensional regulatory network was established by predicting miRNA targets （using miRWalk， etc.） and ubiquitination interactions （using UbiBrowser）， and then potential regulatory mechanisms of hub genes were explored.
Results
Initially， 576 DEGs were screened. Then， 12 core genes were identified via machine learning algorithms. GSEA and immune infiltration analysis showed these core genes were significantly enriched in immune-related pathways. By integrating mitophagy and ferroptosis-related genes with core DEGs， FTH1 was identified as a hub gene， whose expression positively correlated with neutrophil levels and CCR. Mechanistic exploration suggested FTH1 expression might be regulated by miR-224-5p and interact with the E3 ubiquitin ligase SMURF1， implying its potential involvement in disease progression via ubiquitination modification.
Conclusion
This study， combining machine learning and multi-omics integration， first identifies FTH1 as a key regulator of mitophagy and ferroptosis in sepsis-related ARDS. It reveals a regulatory network where FTH1 might be targeted by miR-224-5p and interact with SMURF1， offering new directions and a theoretical basis for developing early immunointervention targets for this disease.
