Background Per- and poly-fluoroalkyl substances (PFAS) can influence gestational diabetes mellitus (GDM); however, current studies on their association are limited and have yielded inconsistent findings. Objective To investigate the association between maternal exposure to PFAS, as measured by urinary concentrations in early pregnancy, and the risk of developing GDM. Methods Based on the Wuhu Birth Cohort in Anhui Province conducted between 2020 and 2023, this study included 1910 pregnant women. Urine samples were collected during the first trimester, and a 75 g oral glucose tolerance test (OGTT) was completed at 24–28 gestational weeks. The concentrations of six PFAS in urine were measured using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Participants were categorized into low, medium, and high exposure groups according to tertiles of individual PFAS concentrations. Logistic regression analysis was employed to assess the potential impact of early-pregnancy PFAS exposure levels on the risk of GDM, with stratified analyses by maternal age and fetal sex. A generalized weighted quantile sum regression (gWQS) model was applied to evaluate the relative weight distribution of the six PFAS in their mixture effect. Results The logistic regression results revealed that both medium exposure to perfluorohexane sulfonate (PFHxS) (OR=1.475, 95%CI: 1.040, 2.093) and high exposure to perfluorononanoic acid (PFNA) (OR=1.430, 95%CI: 1.013, 2.018) were positively associated with diagnosed GDM. This association was more pronounced among women older than 28 years. Among pregnant women carrying male fetuses, high-level exposures to per fluorohexanoic acid (PFHxA) (OR=1.708, 95%CI: 1.006, 2.899) and PFHxS (OR=2.116, 95%CI: 1.247, 3.584) showed positive associations with diagnosed GDM. In contrast, among those carrying female fetuses, moderate perfluorooctanesulfonic acid (PFOS) exposure was associated with a lower risk of GDM (OR=0.542, 95%CI: 0.311, 0.946). The gWQS results demonstrated that PFOS (0.48) and perfluorobutane sulfonate (PFBS) (0.34) contributed the most to the mixture effect. Conclusion Early-pregnancy exposure to PFAS (particularly PFHxS and PFNA) may be an etiological factor for GDM, with maternal age and fetal sex potentially acting as effect modifiers in this association.

ObjectiveTo investigate the role of DEAD-box helicase 3 X-linked （DDX3X） in immune-mediated liver injury （ILI）， and to clarify its mechanism by regulating endoplasmic reticulum stress （ERS）-dependent apoptotic pathway and its association with the clinical progression of hepatitis B. MethodsMice were given injection of concanavalin A （ConA） via the caudal vein to establish a model of ILI， PBS （control group） and different concentrations of ConA were injected into the tail vein of hepatocyte-specific DDX3X-knockout mice （DDX3X^ΔHep and DDX3X-flox mice （DDX3X^fl/fl）， respectively.. The log-rank survival analysis， measurement of the serum levels of aspartate aminotransferase （AST） and alanine aminotransferase （ALT）， and HE staining of liver tissue were performed to assess liver injury， and qRT-PCR and Western Blot were used to measure the mRNA and protein expression levels of glucose-regulated protein 78 （GRP78）， CCAAT/enhancer-binding protein homologous protein （CHOP）， and DDX3X in liver tissue. Intraperitoneal injection of 4-phenylbutyric acid （4-PBA， 100 mg/kg） was performed to inhibit ERS. Serum samples （n=30） and liver tissue samples （n=6） were collected from healthy controls， chronic hepatitis B （CHB） patients， and hepatitis B virus-associated liver failure （HBV-LF） patients； ELISA was used to measure the serum level of DDX3X， and qRT-PCR/Western Blot was used to analyze the expression of targets in liver tissue. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the control group of mice， the expression of DDX3X in the liver of mice induced by ConA was significantly increased after liver injury （P<0.05）， and hepatocyte-specific DDX3X knockout increased the 72-hour survival rate of mice by 55% （compared with 20% in the DDX3X^fl/fl group）， with significant reductions in the serum levels of ALT and AST （P<0.000 1） and the expression levels of the ERS markers GRP78 and CHOP （P<0.05）. After ERS was inhibited by 4-PBA， there was alleviation of liver injury （with reductions in ALT and AST， P <0.001） and a reduction in DDX3X expression （P<0.01）. The analysis of clinical samples showed that the mRNA and protein expression levels of liver DDX3X in CHB patients and HBV-LF patients were significantly higher than those in healthy controls （all P<0.01）， and there was a significant increase in the serum level of DDX3X in HBV-LF patients （P<0.000 1）. ConclusionDDX3X exacerbates ILI by regulating the ERS-dependent apoptotic pathway （GRP78/CHOP）， and its expression is associated with the progression of hepatitis B. Therefore， it can be used as a potential therapeutic target.

Lung transplantation is a definitive treatment for end-stage lung disease and can significantly improve patient prognosis. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury and chronic lung allograft dysfunction intertwine to form a complex pathological network, posing persistent challenges to long-term patient survival. In 2025, research teams worldwide have made systematic progress in the field of basic lung transplantation research. By integrating cutting-edge technologies including single-cell multi-omics, spatial transcriptomics and novel animal models, significant breakthroughs have been achieved in the evolutionary dynamics of drug-resistant infections, molecular mechanisms of immune regulation, programmed cell death, optimization of donor lung protection strategies and early warning of chronic lung allograft dysfunction. This article systematically reviews the representative advances in basic lung transplantation research worldwide in 2025, and deeply analyzes the implications of mechanistic breakthroughs for optimizing diagnosis and treatment strategies, aiming to anchor the direction for innovative breakthroughs and clinical translation in basic lung transplantation research.

Early correction of childhood malocclusion is timely managing morphological, structural, and functional abnormalities at different dentomaxillofacial developmental stages. The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion. This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence, aiming to provide general guidance on appropriate imaging examination selection, comprehensive and accurate imaging assessment for early orthodontic treatment patients.
Humans ; Malocclusion/diagnostic imaging* ; Child ; Consensus

Ankylosing spondylitis (AS) is linked to an increased prevalence of myocardial infarction (MI). However, research dedicated to elucidating the pathogenesis of AS-MI is lacking. In this study, we explored the biomarkers for enhancing the diagnostic and therapeutic efficiency of AS-MI. Datasets were obtained from the Gene Expression Omnibus database. We employed weighted gene co-expression network analysis and machine learning models to screen hub genes. A receiver operating characteristic curve and a nomogram were designed to assess diagnostic accuracy. Gene set enrichment analysis was conducted to reveal the potential function of hub genes. Immune infiltration analysis indicated the correlation between hub genes and the immune landscape. Subsequently, we performed single-cell analysis to identify the expression and subcellular localization of hub genes. We further constructed a transcription factor (TF)-microRNA (miRNA) regulatory network. Finally, drug prediction and molecular docking were performed. S100A12 and MCEMP1 were identified as hub genes, which were correlated with immune-related biological processes. They exhibited high diagnostic value and were predominantly expressed in myeloid cells. Furthermore, 24 TFs and 9 miRNA were associated with these hub genes. Enzastaurin, meglitinide, and nifedipine were predicted as potential therapeutic agents. Our study indicates that S100A12 and MCEMP1 exhibit significant potential as biomarkers and therapeutic targets for AS-MI, offering novel insights into the underlying etiology of this condition.
Humans ; Spondylitis, Ankylosing/complications* ; Systems Biology/methods* ; Myocardial Infarction/diagnosis* ; Biomarkers/metabolism* ; MicroRNAs/genetics* ; Gene Regulatory Networks ; Gene Expression Profiling ; Machine Learning

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Lung transplantation is currently the only recognized effective treatment for end-stage lung disease and has improved the quality of life for patients. However, lung transplantation still faces many challenges, including rejection, infection, post-transplant acute kidney injury, post-transplant diabetes mellitus, ischemia-reperfusion injury and donor shortage, etc. Chinese lung transplantation scholars made a series of important progress in the field of clinical research in 2024, focusing on the study and solution of the above problems, and providing new ideas for lung transplantation surgery. This article systematically reviews the clinical research and technological innovation in the field of lung transplantation in 2024, summarizes the achievements of clinical research in the field of lung transplantation in China in 2024, and aims to providing new directions and strategies for future research.

Lung transplantation is the optimal treatment for end-stage lung diseases and can significantly improve prognosis of the patients. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury, and other challenges (like shortage of donor lungs) , limit the practical application of lung transplantation in clinical practice. Chinese research teams have been making continuous efforts and have achieved breakthroughs in basic research on lung transplantation by integrating emerging technologies and cutting-edge achievements from interdisciplinary fields, which has strongly propelled the development of this field. This article will comprehensively review the academic progress made by Chinese research teams in the field of lung transplantation in 2024, with a focus on the achievements of Chinese teams in basic research on lung transplantation. It aims to provide innovative ideas and strategies for key issues in the basic field of lung transplantation and to help China's lung transplantation cause reach a higher level.

Objective:Investigate key genes influencing vascular calcification through bioinformatics analysis and experimental validation.Methods:Three vascular calcification datasets (GSE159832, GSE229679 and GSE37558) were obtained from the Gene Expression Omnibus database. Subsequently, gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and conventional gene set enrichment analysis (GSEA) were performed on the common differential expressed genes(DEGs). For in vitro validation, a vascular smooth muscle cell calcification model was established by stimulating mouse primary vascular smooth muscle cells with high phosphate and calcium chloride (Pi+CaCl 2). Cells were divided into a control group and a Pi+CaCl 2 group. To investigate the role of TK1, cells were transfected with TK1-targeting siRNA (siTK1) or control siRNA (siControl) prior to Pi+CaCl 2 stimulation, creating siControl+Pi+CaCl 2 and siTK1+Pi+CaCl 2 groups. The association between key DEGs and vascular calcification was assessed at the protein and mRNA levels using Western blot and quantitative real-time PCR, respectively. Changes in the phosphorylation of the downstream effector, AKT (p-AKT/AKT), were also measured. Results:A total of 2275, 449, and 381 DEGs were identified from the three vascular calcification datasets (GSE159832, GSE229679, and GSE37558), respectively. Two common DEGs-phosphoserine aminotransferase 1 and thymidine kinase 1 (TK1)-were identified across all datasets. GO enrichment analysis revealed that TK1 was significantly enriched in pathways related to ribosome biogenesis, assembly, and rRNA processing and maturation. GSEA-KEGG analysis indicated significant enrichment in the PI3K-AKT signaling pathway, pathways in cancer, neurodegenerative diseases, cytoskeleton, and smooth muscle contraction. Conventional GSEA of TK1 further confirmed significant enrichment in pathways including dynein, epithelial tight junctions, axon guidance, and vascular smooth muscle contraction pathways. At the experimental level, both protein and mRNA expression of TK1, along with the p-AKT/AKT ratio, were significantly lower in the Pi+CaCl 2 group compared to the control group (all P<0.05). Furthermore, compared to the siControl+Pi+CaCl 2 group, the siTK1+Pi+CaCl 2 group exhibited decreased expression of differentiation markers, increased expression of calcification markers, and a further reduced p-AKT/AKT ratio (all P<0.05). Conclusion:Integrated bioinformatics and cellular validation demonstrate a correlation between TK1 expression and vascular calcification, suggesting a potential protective role for TK1 in this pathological process.