ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

Electrical impedance tomography (EIT) is a technique that uses an array of electrodes to deliver safe stimulating currents and measures the boundary voltages between adjacent electrode pairs in the array in sequence. Subsequently, it reconstructs the impedance distribution in all or part of the tissue using reconstruction algorithms to achieve structural and functional imaging. Lung EIT technology features continuity, being radiation-free and non-invasive, and it can be used for real-time dynamic monitoring of the lungs in critically ill patients. This paper introduces the basic principles of lung EIT, analyzes the research progress and existing problems of the technology from the perspectives of hardware systems, imaging algorithms, and clinical applications (such as lung ventilation, lung perfusion, and lung function assessment), and discusses the development direction to provide ideas for expanding the clinical application of lung EIT.
Electric Impedance ; Humans ; Tomography/methods* ; Lung Diseases/therapy* ; Algorithms

The catalytic activity of 3-mercaptopyruvate (3MP) sulfurtransferase (MPST) converts 3MP to hydrogen sulfide (H₂S). However, the regulatory mechanisms governing MPST and its impact on the brain remain largely unexplored. Our study reveals the neuroprotective role of endothelial MPST-generated H₂S, regulated by protein phosphatase 2A (PP2A). Bioinformatics analysis and RNA sequencing demonstrated that endothelial PP2A is associated with neurodegenerative disease pathways. Cerebral ischemic mice exhibited significant inactivation of endothelial PP2A, evidenced by the reduction of PP2Acα in the brain endothelium. Mice with endothelium-specific null PP2A (PP2A^EC-cKO) exhibited neuronal loss, cognitive dysfunction, and long-term potentiation deficits. Postnatal inactivation of endothelial PP2A also contributes to cognitive dysfunction and neuronal loss. However, regaining endothelial PP2A activity by overexpressing Ppp2ca rescued neuronal dysfunction. Mechanistically, PP2A deficiency is intricately linked to the MPST-H₂S signaling pathway. A robust reduction in endothelial MPST-dependent H₂S production followed PP2A deficiency. Exogenous H₂S treatment and AAV-mediated overexpression of MPST in brain endothelial cells significantly mitigated neuronal dysfunction in PP2A^EC-cKO mice. Furthermore, PP2A deficiency promotes an increase in calcium influx and calpain2 phosphorylation, subsequently leading to MPST degradation. The PP2A activator (FTY720) and MPST activator (3MP sodium) both remarkably restored endothelial MPST-dependent H₂S production, subsequently rescuing ischemia-induced neurological deficits. In conclusion, our study demonstrates that endothelial PP2A deficiency leads to MPST degradation by activating calpain2, thus damaging neuronal function.

Abdominal aortic aneurysm (AAA) is a deadly condition of the aorta, carrying a significant risk of death upon rupture. Currently, there is a dearth of efficacious pharmaceutical interventions to impede the advancement of AAA and avert it from rupturing. Here, we investigated dihydromyricetin (DHM), one of the predominant bioactive flavonoids in Ampelopsis grossedentata (A. grossedentata), as a potential agent for inhibiting AAA. DHM effectively blocked the formation of AAA in angiotensin II-infused apolipoprotein E-deficient (ApoE^-/-) mice. A combination of network pharmacology and whole transcriptome sequencing analysis revealed that DHM's anti-AAA action is linked to heme oxygenase (HO)-1 (Hmox-1 for the rodent gene) and hypoxia-inducible factor (HIF)-1α in vascular smooth muscle cells (VSMCs). Remarkably, DHM caused a robust rise (∼10-fold) of HO-1 protein expression in VSMCs, thereby suppressing VSMC inflammation and oxidative stress and preserving the VSMC contractile phenotype. Intriguingly, the therapeutic effect of DHM on AAA was largely abrogated by VSMC-specific Hmox1 knockdown in mice. Mechanistically, on one hand, DHM increased the transcription of Hmox-1 by triggering the nuclear translocation and activation of HIF-1α, but not nuclear factor erythroid 2-related factor 2 (NRF2). On the other hand, molecular docking, combined with cellular thermal shift assay (CETSA), isothermal titration calorimetry (ITC), drug affinity responsive target stability (DARTS), co-immunoprecipitation (Co-IP), and site mutant experiments revealed that DHM bonded to HO-1 at Lys243 and prevented its degradation, thereby resulting in considerable HO-1 buildup. In summary, our findings suggest that naturally derived DHM has the capacity to markedly enhance HO-1 expression in VSMCs, which may hold promise as a therapeutic strategy for AAA.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease lacking effective therapy. Metformin, an antidiabetic medication, has shown promising therapeutic properties in preclinical fibrosis models; however, its precise cellular targets and associated mechanisms in fibrosis resolution remain incompletely defined. Most research on metformin's effects has focused on mesenchymal and inflammatory responses with limited attention to epithelial cells. In this study, we utilized Sftpc lineage-traced and Fgfr2b conditional knockout mice, along with BMP2/PPARγ and AMPK inhibitors, to explore metformin's impact on alveolar epithelial cells in a bleomycin-induced pulmonary fibrosis model and cell culture. We found that metformin increased the proliferation and differentiation of alveolar type 2 (AT2) cells, particularly the recently identified injury-activated alveolar progenitors (IAAPs)-a subpopulation characterized by low SFTPC expression but enriched for PD-L1. Single-cell RNA sequencing revealed a reduction in apoptosis among mature AT2 cells. Interestingly, metformin's therapeutic effects were not significantly affected by BMP2 or PPARγ inhibition, which blocked the lipogenic differentiation of myofibroblasts. However, Fgfr2b deletion in Sftpc lineage cells significantly impaired metformin's ability to promote fibrosis resolution, a process linked to AMPK signaling. In conclusion, metformin alleviates fibrosis by directly activating AT2 cells, especially the IAAPs, through a mechanism that involves AMPK and FGFR2b signaling, but is largely independent of BMP2/PPARγ pathways.

Acute lung injury (ALI) has been a kind of acute and severe disease that is mainly characterized by systemic uncontrolled inflammatory response to the production of huge amounts of reactive oxygen species (ROS) in the lung tissue. Given the critical role of ROS in ALI, a Fe₃O₄ loaded bovine serum albumin (BSA) nanocluster (BF) was developed to act as a nanomedicine for the treatment of ALI. Combining with NIR irradiation, it exhibited excellent ROS scavenging capacity. Significantly, it also displayed the excellent antioxidant and anti-inflammatory functions for lipopolysaccharides (LPS) induced macrophages (RAW264.7), and Sprague Dawley rats via lowering intracellular ROS levels, reducing inflammatory factors expression levels, inducing macrophage M2 polarization, inhibiting NF-κB signaling pathway, increasing CD4⁺/CD8⁺ T cell ratios, as well as upregulating HSP70 and CD31 expression levels to reprogram redox homeostasis, reduce systemic inflammation, activate immunoregulation, and accelerate lung tissue repair, finally achieving the synergistic enhancement of ALI immunotherapy. It finally provides an effective therapeutic strategy of BF + NIR for the management of inflammation related diseases.

The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans ; Malocclusion, Angle Class III/classification* ; Orthodontics, Corrective/methods* ; Consensus ; Child

Stem cells play a crucial role in maintaining tissue regenerative capacity and homeostasis. However, mechanisms associated with stem cell senescence require further investigation. In this study, we conducted a proteomic analysis of human dental pulp stem cells (HDPSCs) obtained from individuals of various ages. Our findings showed that the expression of NUP62 was decreased in aged HDPSCs. We discovered that NUP62 alleviated senescence-associated phenotypes and enhanced differentiation potential both in vitro and in vivo. Conversely, the knocking down of NUP62 expression aggravated the senescence-associated phenotypes and impaired the proliferation and migration capacity of HDPSCs. Through RNA-sequence and decoding the epigenomic landscapes remodeled induced by NUP62 overexpression, we found that NUP62 helps alleviate senescence in HDPSCs by enhancing the nuclear transport of the transcription factor E2F1. This, in turn, stimulates the transcription of the epigenetic enzyme NSD2. Finally, the overexpression of NUP62 influences the H3K36me2 and H3K36me3 modifications of anti-aging genes (HMGA1, HMGA2, and SIRT6). Our results demonstrated that NUP62 regulates the fate of HDPSCs via NSD2-dependent epigenetic reprogramming.
Humans ; Dental Pulp/cytology* ; Nuclear Pore Complex Proteins/genetics* ; Cellular Senescence/genetics* ; Stem Cells/metabolism* ; Epigenesis, Genetic ; Cell Proliferation ; Cell Differentiation ; Histone-Lysine N-Methyltransferase/metabolism* ; Cells, Cultured ; Cellular Reprogramming ; Cell Movement ; Proteomics

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene