OBJECTIVE: To investigate the effects of low-dose irradiated autologous peripheral blood reinfusion (LDIAPBR) on a rat model of radiation-induced leukopenia. METHODS: The rats were randomly divided into four groups. In the LDIAPBR group, LDIAPBR was performed 1 day before modeling (10% of the total circulating blood volume was withdrawn, irradiated with 100 mGy ex vivo, and completely reinfused). Meanwhile, the normal group and model group only underwent blood withdrawal and reinfusion of the same proportion without blood irradiation. Except for the normal group, all groups were subjected to 1 Gy X-ray whole-body irradiation to establish a radiation-induced leukopenia rat model. The positive drug group received subcutaneous injection of rhG-CSF after modeling. It was monitored that the general condition of the rats, peripheral blood cell counts, immune organ indices, bone marrow nucleated cell counts and viability, and the pathological analysis of bone marrow sections was conducted. RESULTS: The LDIAPBR group exhibited significant improvements in overall condition compared to the model group. Notably, compared with the model group, peripheral blood leukocyte and lymphocyte counts were markedly higher in the LDIAPBR group. Furthermore, there was a significant increase in both the number and viability of nucleated cells in the bone marrow. Pathological examination of bone marrow sections revealed increased nucleated cell density and reduced cavity area in the LDIAPBR group. CONCLUSION LDIAPBR can effectively improve hematological parameters and bone marrow hematopoietic function in a rat model of radiation-induced leukopenia, providing a new approach for the prevention and treatment of radiation-related injuries.
Animals ; Leukopenia/prevention & control* ; Rats ; Blood Transfusion, Autologous ; Whole-Body Irradiation ; Radiation Injuries, Experimental/therapy*

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

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

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.

【Objective】 To measure and analyze foot development indicators of children under 3 years old, in order to provide basis for the correct clinical assessment of children foot development. 【Methods】 A total of 5 894 children under 3 years old who took physical examination in the Child Health Care Department of Xi′an People′s Hospital from August 2022 to March 2023 were randomly selected. Foot length, foot width, the ratio of foot width to length and arch index were measured by image processing system, and were compared among different age groups and sex groups. 【Results】 1) Foot length, foot width and arch index of children under 3 years old increased significantly with age, while the ratio of foot width to length decreased significantly with age(F=1 345.23, 396.21,184.65, 287.03, P<0.05). 2) There was no statistical significance in foot length, foot width and arch index between left and right foot of children under 3 years old(P>0.05). 3) Foot length and foot width of boys were greater than those of girls in all age groups, and the difference was statistically significant(tfoot length:3.45 - 10.19, tfoot width: 3.77 - 9.21, P<0.05). There was no significant difference in arch index between boys and girls in all age groups(P>0.05). 【Conclusion】 Foot shape of children under 3 years old changes with age, there are differences in foot length and width between boys and girls.

Objective:To investigate the value of radiomics nomogram based on standardized pre-treatment chest enhanced CT in predicting the mutation status of epidermal growth factor receptor (EGFR) for patients with lung adenocarcinoma.Methods:A retrospective analysis was conducted on pre-treatment chest enhanced CT images and clinical data of 262 patients from the affiliated hospital of Jining Medical University with pathologically proven primary lung adenocarcinoma who received EGFR gene testing, including EGFR wild type ( n=122) and mutant type ( n=140). The patients were divided into training group ( n=183) and testing group ( n=79) according to a ratio of 7∶3 by stratified sampling method. Standardized pre-processed the images, delineated the ROI and extracted the radiomics features. Least absolute shrinkage and selection operator (LASSO) algorithm was used to reduce the dimension and select key features. The standardized radiomics model, clinical model and the combined model were established by Logistic Regression (LR) machine learning method. Calculated the Rad-score and drew the nomogram. ROC curve and Delong were used to evaluate and compare the predictive performance of different models. Results:23 standardized enhanced CT radiomics features and 4 clinical features were selected. The predictive performance of standardized radiomics model was better than that of non-standardized radiomics model [area under curve (AUC): 0.863 vs. 0.805, t=2.19, P<0.05]. The AUCs of the combined model and standardized radiomics model were higher than that of the clinical model (training group: 0.885, 0.863 vs. 0.774, t=3.57, 2.17, P<0.05; testing group: 0.873, 0.829 vs. 0.763, t=2.19, 2.02, P<0.05). The radiomics nomogram was built based on Rad-score, age, sex, smoking history and BMI. Conclusions:The combined model and standardized radiomics model could effectively predict the mutation status of EGFR gene in lung adenocarcinoma patients before treatment, providing valuable clinical insights.

Objective: To determine the active components of Eupolyphaga sinensis Walker (Tu Bie Chong) and explore the mechanisms underlying its fracture-healing ability. Methods: A modified Einhorn method was used to develop a rat tibial fracture model. Progression of bone healing was assessed using radiological methods. Safranin O/fast green and CD31 immunohistochemical staining were performed to evaluate the growth of bone cells and angiogenesis at the fracture site. Methylthiazoletetrazolium blue and wound healing assays were used to analyze cell viability and migration. The Transwell assay was used to explore the invasion capacity of the cells. Tubule formation assays were used to assess the angiogenesis capacity of human vascular endothelial cells (HUVECs). qRT-PCR was used to evaluate the changes in gene transcription levels. Results: Tu Bie Chong fraction 3 (TF3) significantly shortened the fracture healing time in model rats. X-ray results showed that on day 14, fracture healing in the TF3 treatment group was significantly better than that in the control group (P = .0086). Tissue staining showed that cartilage growth and the number of H-shaped blood vessels at the fracture site of the TF3 treatment group were better than those of the control group. In vitro, TF3 significantly promoted the proliferation and wound healing of MC3T3-E1s and HUVECs (all P < .01). Transwell assays showed that TF3 promoted the migration of HUVECs, but inhibited the migration of MC3T3-E1 cells. Tubule formation experiments confirmed that TF3 markedly promoted the ability of vascular endothelial cells to form microtubules. Gene expression analysis revealed that TF3 significantly promoted the expression of VEGFA, SPOCD1, NGF, and NGFR in HUVECs. In MC3T3-E1 cells, the transcript levels of RUNX2 and COL2A1 were significantly elevated following TF3 treatment. Conclusion TF3 promotes fracture healing by promoting bone regeneration associated with the RUNX2 pathway and angiogenesis associated with the VEGFA pathway.