ObjectiveTo elucidate the effects of autonomic neuromodulators [calcium chloride (CaCl₂)-acetylcholine (ACh)] on atrial electrical remodeling and histopathological changes in rats, thereby providing evidence for further investigation into the pathological mechanisms by which autonomic imbalance induces atrial fibrillation (AF). MethodsTen 8-week-old male Sprague-Dawley (SD) rats were randomly divided into experimental and control groups, with 5 rats in each group. The experimental group received daily tail vein injections of a CaCl₂-ACh mixed solution for 28 days, while the control group received an equal volume of saline. Surface electrocardiograms were recorded before and after daily administration. On day 28 of administration, under isoflurane inhalation anesthesia, echocardiography was performed, and then the rats were euthanized by exsanguination under isoflurane anesthesia for tissue collection. Body weight and heart weight of rats were measured, and electrophysiological parameters including AF inducibility, conduction velocity, and conduction dispersion in isolated rat hearts were monitored using the MappingLab multichannel electrophysiological mapping system. HE staining was performed to evaluate atrial tissue architecture and inflammatory cell infiltration. The expression levels of matrix metalloproteinase 9 (MMP-9) and interleukin-1 beta (IL-1β) were analyzed by Western blotting. Masson staining was used to quantitatively analyze the proportional distribution of collagen fibers and myocardial fibers, and to calculate the area of collagen deposition, thereby evaluating the degree of myocardial fibrosis. Wheat germ agglutinin (WGA) staining was used to evaluate morphological changes of cardiomyocytes. Dihydroethidium (DHE) staining was used to detect the level of oxidative stress in atrial myocytes. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining was used to detect atrial cell apoptosis. ResultsCompared with the control group, the experimental group showed obvious arrhythmias on electrocardiograms. Echocardiography after 28 days of administration revealed significant structural remodeling in the experimental group, with a marked increase in left atrial anteroposterior diameter (P < 0.05), and also showed cardiac dysfunction, with significant decreases in left ventricular ejection fraction and left ventricular fractional shortening (P < 0.01). Compared with the control group, the experimental group showed a significantly increased heart weight-to-body weight ratio (P < 0.05), a markedly higher AF inducibility (P < 0.001), a significantly slowed atrial conduction velocity (P < 0.05), an uneven isochronal map with irregular directions, and a significantly increased conduction dispersion (P < 0.01). HE staining showed that atrial myocytes in the experimental group were disorganized, with slight inflammatory cell infiltration. Western blotting showed that the expression levels of MMP-9 and IL-1β in the atrial tissue of the experimental group were significantly upregulated (P < 0.05). Masson staining showed a significant increase in collagen deposition and a significant increase in fibrosis area in the atrial tissue of the experimental group (P < 0.001). WGA staining showed that cardiomyocytes in the experimental group were significantly hypertrophied compared with the control group (P < 0.05). DHE staining and TUNEL staining revealed that the level of oxidative stress in atrial myocytes (P < 0.001) and the apoptotic rate (P < 0.01) were both significantly increased. Conclusion Daily tail vein injections of the autonomic neuromodulator CaCl₂-ACh mixed solution for 28 days can successfully induce AF in rats, accompanied by significant atrial structural remodeling, electrical remodeling, and oxidative stress.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

Objective:To explore the differences in early clinical features between Kawasaki disease shock syndrome (KDSS) and septic shock (SS).Methods:A retrospective case-control study was conducted. Clinical data was collected from 64 children who were diagnosed with KDSS or SS and admitted to the Department of Critical Care Medicine of Capital Center for Children′s Health, Capital Medical University from January 2018 to February 2025. Mann-Whitney U test, χ2 test, or Fisher′s exact test were used to compare the differences in clinical features, treatment, and outcomes between children with KDSS and SS. Lasso regression was applied to screen predictive variables, and multivariable logistic regression analysis was performed to identify factors associated with KDSS. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of parameters for KDSS. Results:Among the 64 children (30 males and 34 females), the age was 3.6 (1.2, 6.5) years. There were 51 cases in the SS group and 13 cases in the KDSS group. Compared to children with SS, children with KDSS had a longer pre-shock fever duration, lower lactate levels and serum albumin levels, and higher soluble interleukin-2 receptor (sIL-2R) levels (all P<0.05). Additionally, they exhibited a higher incidence of coronary involvement, pericardial effusion, and ascites, a higher utilization rate of intravenous immunoglobulin, and a lower utilization rate of invasive mechanical ventilation (all P<0.05). There was no significant difference in in-hospital mortality between KDSS and SS ( P=0.574). Multivariate logistic regression analysis identified pre-shock fever duration and sIL-2R as independent factors associated with KDSS ( OR=1.52 and 1.54 per 1 000 U increase, 95% CI 1.12-2.05 and 1.06-2.24, respectively; both P<0.05). ROC curve analysis showed that the areas under the curve for pre-shock fever duration and sIL-2R in identifying KDSS were 0.83 (95% CI 0.73-0.94, P=0.001) and 0.70 (95% CI 0.53-0.87, P=0.042), respectively. The optimal cutoff values were 3.5 d and 3.8×10 6 U/L, with sensitivities of 0.91 and 0.82, and specificities of 0.71 and 0.62, respectively. Conclusions:Children with KDSS have higher incidences of coronary involvement, pericardial effusion, and ascites compared to those with SS. Pre-shock fever duration and sIL-2R may serve as potential early indicators for distinguishing KDSS from SS.

Objective:To analyze and summarize clinical phenotypic characteristics and genetic variations in patients with intellectual disability and pathogenic variations of the DYNC1H1 gene across 4 generations within a single family. Methods:Retrospective case analysis.Clinical data of a child with epilepsy and intellectual disability and her family members were collected from the Children′s Medical Center, Peking University First Hospital on December 2019.The child was followed up regularly.DNA was extracted from the peripheral blood of the child′s family members.Then whole-exome sequencing and Sanger sequencing were performed to identify the genetic variation type in the proband and her family members.The relationship between genotype and phenotype was further analyzed.Results:A total of 13 patients across 4 generations in the family had intellectual disability, and the proband also had drug-resistant epilepsy.The variation c. 13556C> A (p.A4519E) of the DYNC1H1 gene was confirmed by gene testing in 8 patients (no blood samples were obtained from the remaining patients). Conclusions:DYNC1H1 gene-related intellectual disability in most previously reported cases are caused by novel variations of this gene.In this study, a large family of 13 intellectual disability patients across 4 generations caused by a pathogenic mutation in the DYNC1H1 gene was summarized.The findings make precise genetic counseling possible for this family and provide a basis for further studies on the relationship between the genotype and phenotype of the DYNC1H1 gene.

Aim To investigate the effects of circ_0071653 targeting miR-197-3p on the proliferation and metastasis of esophageal squamous cell carcinoma(ES-CC)cells.Methods The circular structure of circ_0071653 was confirmed by Sanger sequencing and ribo-nuclease R tolerance experiments.Real-time quantita-tive polymerase chain reaction(RT-qPCR)and tissue fluorescence in situ hybridization assay were performed to detect the circ_0071653 expression levels and ana-lyze its clinical relevance.Cell fluorescence in situ hy-bridization and nuclear cytoplasmic separation assays were used to verify the subcellular localization of circ_0071653 and miR-197-3p.Bioinformatics analysis,dual luciferase reporter gene and RT-qPCR assays were conducted to validate the interactions between circ_0071653 and miR-197-3p.Moreover,the cell counting Kit-8(CCK-8),colony formation,scratch,Transwell invasion and subcutaneous tumor formation in nude mice assays were used to evaluate the effects of circ_0071653 and miR-197-3p on cell viability,prolifera-tion,migration,and invasion and in vivo tumorigenesi-sability.Results Circ_0071653 was a circular RNA,which showed high expression in ESCC cell lines and tissues.The expression of circ_0071653 was signifi-cantly correlated with lymph node metastasis and clini-cal stage of ESCC patients.Circ_0071653 and miR-197-3p were mainly localized in the cytoplasm.The databases predict that circ_0071653 had complementa-ry binding sites with miR-197-3p,and their binding were confirmed by dual luciferase reporter geneand RT-qPCR assays.Moreover,the activity,proliferation,migration,invasion and in vivo tumorigenesis abilities of ESCC cells were significantly reduced after knocking down circ_0071653,and this effect could be reversed by downregulating the expression of miR-197-3p.Con-clusions Circ_0071653 promotes the malignant pro-gression of ESCC through targeted regulation of miR-197-3p.

Abstract Neurodegenerative diseases include Alzheimer′s disease, Parkinson′s disease, Huntington′s disease, amyotrophic lateral sclerosis, and other disease. There are many causes of neurodegenerative diseases, and the pathogenesis is not entirely clear. Currently, most scholars believe that the occurrence of diseases is closely related to mitochondria. Mitochondrial quality control includes the production, fusion, division, and clearance of mitochondria. Abnormal mitochondrial quality control affects the function of neurons and nerve fibers, leading to the occurrence of neurodegenerative diseases. The author elaborates on the relationship between mitochondria and the pathogenesis of neurodegenerative diseases, providing a basis for the treatment of neurodegenerative diseases.

Objective:To discuss the influencing factors of angina pectoris in the patients with diabetes mellitus(DM),to construct a Bayesian network model to explore the network relationships among the influencing factors,and to predict the risk of angina pectoris in the patients with DM.Methods:Based on the UK Biobank(UKB)database,the Logistic regression aralysis model was used to screen the influencing factors of angina pectoris in the patients with DM.The taboo search algorithm was used for structure learning,and the Bayesian parameter estimation method was used for parameter learning to construct the Bayesian network model.Results:A total of 22 712 DM patients were included.The influencing factors of angina pectoris in the patients with DM included 14 variables:gender,age,body mass index(BMI),triglycerides(TG),total cholesterol(TC),glycated hemoglobin(HbA1c),hypertension,maternal smoking around delivery,smoking status,alcohol consumption,regular exercise,insomnia,sleep duration,and childhood relative body size(P<0.05).A Bayesian network model was constructed with 15 nodes and 22 directed edges.Among them,age,HbA1c,hypertension,regular exercise,BMI,and sleep duration were directly associated with the occurrence of angina pectoris in the patients with DM,while gender,smoking status,alcohol consumption,TC,TG,insomnia,childhood relative body size,and maternal smoking around delivery were indirectly associated with the occurrence of angina pectoris in the patients with DM.Conclusion:Age,HbA1c,hypertension,regular exercise,BMI,and sleep duration are direct influencing factors of angina pectoris in the patients with DM.Controlling HbA1c,blood pressure,and BMI levels,engaging in regular exercise,and maintaining appropriate sleep duration are beneficial for reducing the risk of angina pectoris in the patients with DM.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

Intentional tooth replantation (ITR) is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions. ITR is defined as the deliberate extraction of a tooth; evaluation of the root surface, endodontic manipulation, and repair; and placement of the tooth back into its original socket. Case reports, case series, cohort studies, and randomized controlled trials have demonstrated the efficacy of ITR in the retention of natural teeth that are untreatable or difficult to manage with root canal treatment or endodontic microsurgery. However, variations in clinical protocols for ITR exist due to the empirical nature of the original protocols and rapid advancements in the field of oral biology and dental materials. This heterogeneity in protocols may cause confusion among dental practitioners; therefore, guidelines and considerations for ITR should be explicated. This expert consensus discusses the biological foundation of ITR, the available clinical protocols and current status of ITR in treating teeth with refractory apical periodontitis or anatomical aberration, and the main complications of this treatment, aiming to refine the clinical management of ITR in accordance with the progress of basic research and clinical studies; the findings suggest that ITR may become a more consistent evidence-based option in dental treatment.
Humans ; Tooth Replantation/methods* ; Consensus ; Periapical Periodontitis/surgery*

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology