Saliva is an important body fluid in the oral cavity containing lots of biomarkers, whose inherent micro-ecosystem holds significant value for early diagnosis and monitoring of oral diseases. Simultaneously, saliva has particular advantages, such as ease of sampling, painless and non-invasive collection, and suitability for repeated sampling, making it highly appropriate for surveillance and follow-up of diseases. In a series of studies conducted by the research group for preventive dentistry in Peking University School and Hospital of Stomatology, we compared different segments of saliva and those samples collected via different sampling methods using proteomic/peptidomic and microbiomic technologies to explore the stability of saliva samples. Besides, the significance of applying representative salivary biomarkers in early prevention and control of representative oral diseases (e.g. dental caries, periodontal diseases) and systemic conditions (e.g. type 2 diabetes mellitus, chronic kidney disease) was confirmed as well.
Humans ; Saliva/chemistry* ; Dental Caries/diagnosis* ; Biomarkers/analysis* ; Periodontal Diseases/diagnosis* ; Mouth Diseases/diagnosis* ; Proteomics/methods* ; Diabetes Mellitus, Type 2/diagnosis* ; Microbiota ; Renal Insufficiency, Chronic/prevention & control*

OBJECTIVE: To explore the mechanism of Dihuang Yinzi (DHYZ) in the treatment of Alzheimer's disease (AD) by integrating metabolomics and experimental verification. METHODS: Forty-eight male APP/PS1 mice were divided into model, high- (DHYZ-H), medium- (DHYZ-M), and low-dose DHYZ (DHYZ-L) groups (12 mice per group) according to a random number table. Mice in DHYZ groups were gavaged with DHYZ 6.34, 12.68, and 25.35 g/(kg·d), respectively. Twelve C57BL/6 mice were gavaged with distilled water as the blank group. Metabolomics was used to analyze differential metabolites in the brains of mice. Morris water maze test was used to detect the memory abilities of mice. The hematoxylin-eosin staining and transmission electron microscopy were used to observe the general morphology and ultrastructure of neurons. The enzyme-linked immunosorbent assay was used to detect the levels of superoxide dismutase (SOD), reactive oxygen species (ROS), and amyloid β -protein 1-42 (A β_1-42). The real-time quantitative polymerase chain reaction was used to detect the mRNA expressions of density-regulated protein 1 (DRP1), fission 1 (FIS1), mitofusin-1 (MFN1), and optic atrophy protein 1 (OPA1). Western blot was used to detect the protein expressions of cyclic adenosine monophosphate (cAMP), protein kinase A (PKA), cAMP response binding protein (CREB), brain-derived neurotrophic factor (BDNF), synapsin 1 (SYN1), synaptophysin (SYP), and postsynaptic density protein 95 (PSD95). RESULTS: A total of 82 differential metabolites were identified in the brains of APP/PS1 mice, among which 7 differential metabolites could be regulated by DHYZ. After DHYZ intervention, the memory abilities of mice significantly increased (P<0.05 or P<0.01), the number of synapses and neurons in the hippocampus increased, and the mitochondrial morphology and structure were relatively intact. The DHYZ groups exhibited a significant reduction in hippocampal ROS and A β_1-42 levels, along with a significant elevation in SOD level (P<0.05 or P<0.01). The mRNA expressions of DRP1 and FIS1 were reduced, while the mRNA expressions of MFN1 and OPA1 were increased after DHYZ treatment (P<0.05 or P<0.01). The cAMP/PKA/CREB-BDNF pathway was activated, and the expressions of SYN1, SYP and PSD95 proteins were significantly increased in the DHYZ-H group (P<0.05 or P<0.01). CONCLUSIONS DHYZ could improve mitochondrial dynamics and synaptic plasticity in APP/PS1 mice, inhibit oxidative stress, and thereby enhancing learning and memory abilities in APP/PS1 mice. Its mechanism might be related to activation of the cAMP/PKA/CREB-BDNF signaling pathway.
Animals ; Brain-Derived Neurotrophic Factor/metabolism* ; Male ; Cyclic AMP Response Element-Binding Protein/metabolism* ; Brain/drug effects* ; Metabolomics ; Mice, Inbred C57BL ; Neuronal Plasticity/drug effects* ; Drugs, Chinese Herbal/therapeutic use* ; Cyclic AMP-Dependent Protein Kinases/metabolism* ; Cyclic AMP/metabolism* ; Reactive Oxygen Species/metabolism* ; Amyloid beta-Protein Precursor/metabolism* ; Mice, Transgenic ; Mice ; Amyloid beta-Peptides/metabolism* ; Signal Transduction/drug effects* ; Alzheimer Disease/drug therapy* ; Superoxide Dismutase/metabolism*

OBJECTIVES: Hepatocellular carcinoma is one of the most common primary malignant tumors with the third highest mortality rate worldwide. This study aims to identify key genes associated with hepatocellular carcinoma prognosis using the Gene Expression Omnibus (GEO) database and provide a theoretical basis for discovering novel prognostic biomarkers for hepatocellular carcinoma. METHODS: Hepatocellular carcinoma-related datasets were retrieved from the GEO database. Differentially expressed genes (DEGs) were identified using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and key genes were identified using Cytoscape software. The University of Alabama at Birmingham Cancer Data Analysis Resource (UALCAN) was used to analyze the expression levels of key genes in normal and hepatocellular carcinoma tissues, as well as their associations with pathological grade, clinical stage, and patient survival. The Human Protein Atlas (THPA) was used to further validate the impact of key genes on overall survival. Expression levels of key genes in the blood of hepatocellular carcinoma patients were evaluated using the expression atlas of blood-based biomarkers in the early diagnosis of cancers (BBCancer). RESULTS: A total of 78 DEGs were identified from the GEO database. GO and KEGG analyses indicated that these genes may contribute to hepatocellular carcinoma progression by promoting cell division and regulating protein kinase activity. Sixteen key genes were screened via Cytoscape and validated using UALCAN and THPA. These genes were overexpressed in hepatocellular carcinoma tissues and were associated with disease progression and poor prognosis. Finally, BBCancer analysis showed that ASPM and NCAPG were also elevated in the blood of hepatocellular carcinoma patients. CONCLUSIONS This study identified 16 key genes as potential prognostic biomarkers for hepatocellular carcinoma, among which ASPM and NCAPG may serve as promising blood-based markers for hepatocellular carcinoma.
Humans ; Carcinoma, Hepatocellular/mortality* ; Liver Neoplasms/pathology* ; Prognosis ; Computational Biology/methods* ; Protein Interaction Maps/genetics* ; Biomarkers, Tumor/genetics* ; Gene Expression Regulation, Neoplastic ; Gene Expression Profiling ; Gene Ontology ; Databases, Genetic

OBJECTIVES: Osteoarthritis (OA) and sarcopenia are significant health concerns in the elderly, substantially impacting their daily activities and quality of life. However, the relationship between them remains poorly understood. This study aims to uncover common biomarkers and pathways associated with both OA and sarcopenia. METHODS: Gene expression profiles related to OA and sarcopenia were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between disease and control groups were identified using R software. Common DEGs were extracted via Venn diagram analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to identify biological processes and pathways associated with shared DEGs. Protein-protein interaction (PPI) networks were constructed, and candidate hub genes were ranked using the maximal clique centrality (MCC) algorithm. Further validation of hub gene expression was performed using 2 independent datasets. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of key genes for OA and sarcopenia. Mouse models of OA and sarcopenia were established. Hematoxylin-eosin and Safranin O/Fast Green staining were used to validate the OA model. The sarcopenia model was validated via rotarod testing and quadriceps muscle mass measurement. Real-time reverse transcription PCR (real-time RT-PCR) was employed to assess the mRNA expression levels of candidate key genes in both models. Gene set enrichment analysis (GSEA) was conducted to identify pathways associated with the selected shared key genes in both diseases. RESULTS: A total of 89 common DEGs were identified in the gene expression profiles of OA and sarcopenia, including 76 upregulated and 13 downregulated genes. These 89 DEGs were significantly enriched in protein digestion and absorption, the PI3K-Akt signaling pathway, and extracellular matrix-receptor interaction. PPI network analysis and MCC algorithm analysis of the 89 common DEGs identified the top 17 candidate hub genes. Based on the differential expression analysis of these 17 candidate hub genes in the validation datasets, AEBP1 and COL8A2 were ultimately selected as the common key genes for both diseases, both of which showed a significant upregulation trend in the disease groups (all P<0.05). The value of area under the curve (AUC) for AEBP1 and COL8A2 in the OA and sarcopenia datasets were all greater than 0.7, indicating that both genes have potential value in predicting OA and sarcopenia. Real-time RT-PCR results showed that the mRNA expression levels of AEBP1 and COL8A2 were significantly upregulated in the disease groups (all P<0.05), consistent with the results observed in the bioinformatics analysis. GSEA revealed that AEBP1 and COL8A2 were closely related to extracellular matrix-receptor interaction, ribosome, and oxidative phosphorylation in OA and sarcopenia. CONCLUSIONS AEBP1 and COL8A2 have the potential to serve as common biomarkers for OA and sarcopenia. The extracellular matrix-receptor interaction pathway may represent a potential target for the prevention and treatment of both OA and sarcopenia.
Sarcopenia/genetics* ; Osteoarthritis/genetics* ; Computational Biology/methods* ; Humans ; Protein Interaction Maps/genetics* ; Animals ; Mice ; Gene Expression Profiling ; Gene Ontology ; Transcriptome ; Male ; Signal Transduction/genetics* ; Gene Regulatory Networks

OBJECTIVES: Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects women's health. This study aims to investigate gene and transcription factor (TF) expression differences between PCOS patients and healthy individuals using bioinformatics approaches, and to verify the function of key transcription factors, with the goal of providing new insights into the pathogenesis of PCOS. METHODS: Differentially expressed genes (DEGs) and differentially expressed transcription factors (DETFs) between PCOS patients and controls were identified from the RNA sequencing dataset GSE168404 using bioinformatics methods. Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The expression and function of core transcription factors were further validated in ovarian tissues of PCOS model mice and control mice using Western blotting and reverse transcription quantitative polymerase chain reaction (RT-qPCR). RESULTS: A total of 332 DEGs were identified between PCOS patients and controls, including 259 upregulated and 73 downregulated genes in the PCOS group. 19 DETFs were further screened, of which 16 were upregulated and 3 were downregulated in PCOS. The upregulated DETFs (including TFCP2L1, DACH1, ESR2, AFF3, SMAD9, ZNF331, HOPX,ATOH8, HIF3α, DPF3, HOXC4, HES1, ID1, JDP2, SOX4, and ID3) were primarily associated with lipid metabolism, development, and cell adhesion. Protein and mRNA expression analysis in PCOS model mice revealed significantly decreased levels of hypoxia-inducible factor (HIF) 1α and HIF2α, and significantly increased expression of HIF3α compared to control mice (all P<0.001). CONCLUSIONS Significant differences in gene and TF expression exist between PCOS patients and healthy individuals. HIF-3α may play a crucial role in PCOS and could serve as a novel biomarker for diagnosis and a potential therapeutic target.
Polycystic Ovary Syndrome/metabolism* ; Female ; Humans ; Animals ; Mice ; Transcription Factors/metabolism* ; Computational Biology ; Gene Expression Profiling ; Adult

OBJECTIVES: Multiple myeloma (MM) is a hematologic malignancy characterized by clonal proliferation of plasma cells and remains incurable. Patients with primary refractory multiple myeloma (PRMM) show poor response to initial induction therapy. This study aims to develop a machine learning-based model to predict treatment response in newly diagnosed multiple myeloma (NDMM) patients, in order to optimize therapeutic strategies. METHODS: NDMM and post-treatment MM patients hospitalized in the Department of Hematology, Third Xiangya Hospital, Central South University, between August 2022 and July 2023 were enrolled. Post-treatment MM patients were categorized into PRMM patients and treatment-responsive MM (TRMM) patients based on therapeutic efficacy. Serum metabolites were detected and analyzed via metabolomics. Based on the metabolomics analysis results and combined with transcriptomic sequencing data of NDMM patients from databases, differentially expressed amino acid metabolism-related genes (AAMGs) among post-treatment NDMM patients with varying therapeutic outcomes were screened. Using bioinformatics analyses and machine learning algorithms, a predictive model for treatment response in NDMM was constructed and used to identify patients at risk for PRMM. RESULTS: A total of 61 patients were included: 22 NDMM, 23 TRMM, and 16 PRMM patients. Significant differences in metabolite levels were observed among the 3 groups, with differential metabolites mainly enriched in amino acid metabolism pathways. Follow-up data were available for 16 of the 22 NDMM patients, including 12 treatment responders (ND_TR group) and 4 with PRMM (ND_PR group). A total of 23 differential metabolites were identified between these 2 groups: 6 metabolites (e.g., tryptophan) were upregulated and 17 (e.g., citric acid) were downregulated in the ND_TR group. Transcriptomic data from 108 TRMM and 77 PRMM patients were analyzed to identify differentially expressed AAMGs, which were then used to construct a prediction model. The area under the receiver operating characteristic curve (AUC) for the model exceeded 0.8, and AUC values in 3 external validation cohorts were all above 0.7. CONCLUSIONS This study delineated the metabolic alterations in MM patients with different treatment response, suggesting that dysregulated amino acid metabolism may be associated with poor treatment response in PRMM. By integrating metabolomics and transcriptomics, a machine learning-based predictive model was successfully established to forecast treatment response in NDMM patients.
Humans ; Multiple Myeloma/drug therapy* ; Machine Learning ; Male ; Female ; Metabolomics/methods* ; Middle Aged ; Aged ; Treatment Outcome ; Transcriptome ; Computational Biology ; Adult ; Multiomics

Dent disease is a rare X-linked recessive inherited renal tubular disorder characterized by low molecular weight proteinuria (LMWP), hypercalciuria, nephrocalcinosis, and other clinical features, and can lead to progressive renal failure. It is primarily caused by mutations in the CLCN5 gene. This article reports the case of a 10-year-old male patient of Chinese descent who was incidentally found to have asymptomatic proteinuria during a routine health examination. Comprehensive biochemical testing and clinical evaluation revealed significant LMWP and hypercalciuria, while renal biopsy showed mesangial cell and matrix proliferation. Whole exome sequencing identified a novel deletion mutation in the CLCN5 gene (NM_001127899.4, c.1158delC, p.F387Lfs*42) causing a frameshift and premature termination, which is likely to disrupt its role in chloride/hydrogen ion exchange and endosomal acidification. Bioinformatic analysis indicated the variant is pathogenic. Genetic testing plays an important role in diagnosing rare kidney diseases. Early identification of pathogenic mutations is essential for facilitating timely intervention and appropriate management, potentially enhancing patient outcomes. This report expands the CLCN5 mutation spectrum and contributes to understanding the genetic and molecular mechanisms of Dent disease.
Humans ; Chloride Channels/genetics* ; Dent Disease/genetics* ; Male ; Child ; Computational Biology ; Mutation ; Proteinuria/genetics* ; Hypercalciuria/genetics*

Neuropsychiatric disorders arise from complex interactions between genetic and environmental factors. DNA methylation, a reversible and environmentally responsive epigenetic regulatory mechanism, serves as a crucial bridge linking environmental exposure, gene expression regulation, and neurobehavioral outcomes. During long-duration deep-space missions, astronauts face multiple stressors-including microgravity, cosmic radiation, circadian rhythm disruption, and social isolation, which can induce alterations in DNA methylation and increase the risk of neuropsychiatric disorders. Genome-wide DNA methylation research can be divided into 3 major methodological stages: Study design, sample preparation and detection, and data analysis, each of which can be applied to astronaut neuropsychiatric health monitoring. Systematic comparison of the Illumina MethylationEPIC array and whole-genome bisulfite sequencing reveals their complementary strengths in terms of genomic coverage, resolution, cost, and application scenarios: the array method is cost-effective and suitable for large-scale population studies and longitudinal monitoring, whereas sequencing provides higher resolution and coverage and is more suitable for constructing detailed methylation maps and characterizing individual variation. Furthermore, emerging technologies such as single-cell methylation sequencing, nanopore long-read sequencing, and machine-learning-based multi-omics integration are expected to greatly enhance the precision and interpretability of epigenetic studies. These methodological advances provide key support for establishing DNA-methylation-based monitoring systems for neuropsychiatric risk in astronauts and lay an epigenetic foundation for safeguarding neuropsychiatric health during future long-term deep-space missions.
DNA Methylation ; Humans ; Space Flight ; Mental Disorders/genetics* ; Epigenesis, Genetic ; Astronauts/psychology* ; Weightlessness/adverse effects* ; Epigenomics

BACKGROUND: PANoptosis has the features of pyroptosis, apoptosis, and necroptosis. Numerous studies have confirmed the diverse roles of various types of cell death in acute liver failure (ALF), but limited attention has been given to the crosstalk among them. In this study, we aimed to explore the role of PANoptosis in ALF and uncover new targets for its prevention or treatment. METHODS: Three ALF-related datasets (GSE14668, GSE62029, and GSE74000) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Hub genes were identified through intersecting DEGs, genes obtained from weighted gene co-expression network analysis (WGCNA), and genes related to PANoptosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein‍‒‍protein interaction (PPI) analyses and gene set enrichment analysis (GSEA) were performed to determine functional roles. Verification was performed using an ALF mouse model. RESULTS: Our results showed that expression of seven hub genes (B-cell lymphoma-2-modifying factor (BMF), B-cell lymphoma-2-interacting protein 3-like (BNIP3L), Caspase-1 (CASP1), receptor-interacting protein kinase 3 (RIPK3), uveal autoantigen with coiled-coil domains and ankyrin repeats protein (UACA), uncoordinated-5 homolog B receptor (UNC5B), and Z-DNA-binding protein 1 (ZBP1)) was up-regulated in liver samples of patients. However, in the ALF mouse model, the expression of BNIP3L, RIPK3, phosphorylated RIPK3 (P-RIPK3), UACA, and cleaved caspase-1 was up-regulated, while the expression of CASP1 and UNC5B was down-regulated. The expression of ZBP1 and BMF increased only during the development of ALF, and there was no significant change in the end stage. Immunofluorescence of mouse liver tissue showed that macrophages expressed all seven markers. Western blot results showed that pyroptosis, apoptosis, and necroptosis were always involved in lipopolysaccharide (LPS)/ d-galactosamine (d-gal)‍-induced ALF mice. The ALF cell model showed that bone marrow-derived macrophages (BMDMs) form PANoptosomes after LPS stimulation. CONCLUSIONS: Our results suggest that PANoptosis of macrophages promotes the development of ALF. The seven new ALF biomarkers identified and validated in this study may contribute to further investigation of diagnostic markers or novel therapeutic targets of ALF.
Animals ; Liver Failure, Acute/genetics* ; Computational Biology ; Mice ; Pyroptosis/genetics* ; Humans ; Protein Interaction Maps ; Apoptosis/genetics* ; Necroptosis/genetics* ; Gene Regulatory Networks ; Gene Ontology ; Gene Expression Profiling ; Disease Models, Animal

Objective:To explore the effect, postoperative mucosal pathological changes and molecular biological changes of reboot operation for type 2 inflammation chronic rhinosinusitis with nasal polyps（CRSwNP） patients, and to provide theoretical basis for the clinical application of this kind of operation. Methods:We collected 29 patients who were diagnosed with CRSwNP with type 2 inflammatino response and underwent Reboot surgery from June 2022 to August 2023, and 27 patients who were diagnosed with deviated septum and underwent simple submucosal resection of the septum as the control group. We conducted nasal symptom scoring, endoscopic sinusitis scoring, and CT scanning of the sinuses before and after surgery, as well as HE staining, immunohistochemical staining, and detection of inflammatory factors using Elisa kits at the time of surgery, 1, 3, and 6 months postoperatively. We also observed the ultrastructural changes using transmission electron microscopy and scanning electron microscopy, and performed proteomic analysis of the mucosa in the ethmoid sinus area of the sinusitis patients at the time of surgery and 6 months postoperatively. Results:After 6 months of postoperative follow-up, CT scores of the nasal cavity and sinuses had gradually decreased compared with the preoperative period. The VAS score of main symptoms, SNOT-22 score and Lund-Kennedy endoscopic score were decreased after 12 months follow-up. The histological morphology of the mucosa in the area of the screen was significantly improved compared with the preoperative period, with a reduction in the number of eosinophils. The levels of inflammatory factors such as IL-4 and IL-5 et al. in the mucosa of the area of the screen were gradually reduced compared with the preoperative period. The histological morphology, ultrastructure, and cilia structure of the mucosa in the area of the screen were gradually improved compared with the preoperative period, though not recovered completely. The number of CD4⁺T and CD8⁺T cells not changed significantly before and after the surgery yet. By conducting proteomic analysis of the ethmoidal sinus mucosa before and after surgery, differential proteins were selected, and bioinformatics analysis was conducted on the differentially expressed proteins. By using cytoHubba to identify hub genes and intersecting them with the genes related to chronic sinusitis, we found that MMP9 expression increased in non-type 2 CRS and type 2 CRS in sequence, while ACTC1 expression decreased in non-tpye 2 CRS and type 2 CRS in sequence. Conclusion:Reboot surgery can improve the postoperative symptoms and signs of patients, improve the pathological morphology of the mucosa, and influence the expression of protein after surgery. However, the surgery may not have a significant impact on the distribution of T cell subpopulations and inflammation signal pathway in the nasal mucosa.
Humans ; Sinusitis/metabolism* ; Nasal Polyps/metabolism* ; Nasal Mucosa/ultrastructure* ; Chronic Disease ; Rhinitis/complications* ; Inflammation ; Male ; Female ; Postoperative Period ; Adult ; Interleukin-5/metabolism* ; Interleukin-4/metabolism* ; Middle Aged ; Proteomics ; Rhinosinusitis