BACKGROUND: Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and its dysregulation can lead to glycometabolic disorders. This study aimed to identify hub biomarkers of these disorders to provide a theoretical foundation for enhancing diagnosis and treatment. METHODS: Gene expression profiles from liver tissues of three well-characterized gluconeogenesis mouse models were analyzed to identify commonly differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA), machine learning techniques, and diagnostic tests on transcriptome data from publicly available datasets of type 2 diabetes mellitus (T2DM) patients were employed to assess the clinical relevance of these DEGs. Subsequently, we identified hub biomarkers associated with gluconeogenesis-related glycometabolic disorders, investigated potential correlations with immune cell types, and validated expression using quantitative polymerase chain reaction in the mouse models. RESULTS: Only a few common DEGs were observed in gluconeogenesis-related glycometabolic disorders across different contributing factors. However, these DEGs were consistently associated with cytokine regulation and oxidative stress (OS). Enrichment analysis highlighted significant alterations in terms related to cytokines and OS. Importantly, osteomodulin ( OMD ), apolipoprotein A4 ( APOA4 ), and insulin like growth factor binding protein 6 ( IGFBP6 ) were identified with potential clinical significance in T2DM patients. These genes demonstrated robust diagnostic performance in T2DM cohorts and were positively correlated with resting dendritic cells. CONCLUSIONS Gluconeogenesis-related glycometabolic disorders exhibit considerable heterogeneity, yet changes in cytokine regulation and OS are universally present. OMD , APOA4 , and IGFBP6  may serve as hub biomarkers for gluconeogenesis-related glycometabolic disorders.
Machine Learning ; Humans ; Computational Biology/methods* ; Biomarkers/metabolism* ; Diabetes Mellitus, Type 2/genetics* ; Animals ; Mice ; Gluconeogenesis/physiology* ; Gene Expression Profiling ; Transcriptome/genetics* ; Gene Regulatory Networks/genetics* ; Clinical Relevance

With the rapid development of artificial intelligence, computational pathology has been seamlessly integrated into the entire clinical workflow, which encompasses diagnosis, treatment, prognosis, and biomarker discovery. This integration has significantly enhanced clinical accuracy and efficiency while reducing the workload for clinicians. Traditionally, research in this field has depended on the collection and labeling of large datasets for specific tasks, followed by the development of task-specific computational pathology models. However, this approach is labor intensive and does not scale efficiently for open-set identification or rare diseases. Given the diversity of clinical tasks, training individual models from scratch to address the whole spectrum of clinical tasks in the pathology workflow is impractical, which highlights the urgent need to transition from task-specific models to foundation models (FMs). In recent years, pathological FMs have proliferated. These FMs can be classified into three categories, namely, pathology image FMs, pathology image-text FMs, and pathology image-gene FMs, each of which results in distinct functionalities and application scenarios. This review provides an overview of the latest research advancements in pathological FMs, with a particular emphasis on their applications in oncology. The key challenges and opportunities presented by pathological FMs in precision oncology are also explored.
Humans ; Precision Medicine/methods* ; Medical Oncology/methods* ; Artificial Intelligence ; Neoplasms/pathology* ; Computational Biology/methods*

This study aims to investigate the therapeutic effect and mechanism of Daotan Xixin Decoction on APP/PS1 mice. Twelve APP/PS1 male mice were randomized into four groups: APP/PS1 and low-, medium-, and high-dose Daotan Xixin Decoction. Three C57BL/6 wild-type mice were used as the control group. The learning and memory abilities of mice in each group were examined by the Morris water maze test. The pathological changes of hippocampal nerve cells were observed by hematoxylin-eosin staining and Nissl staining. Immunohistochemistry was employed to detect the expression of β-amyloid(Aβ)_(1-42) in the hippocampal tissue. The high-dose Daotan Xixin Decoction group with significant therapeutic effects and the model group were selected for high-throughput sequencing. The differentially expressed gene(DEG) analysis, Gene Ontology(GO) analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and Gene Set Variation Analysis(GSVA) were performed on the sequencing results. RT-qPCR and Western blot were conducted to determine the mRNA and protein levels, respectively, of some DEGs. Compared with the APP/PS1 group, Daotan Xixin Decoction at different doses significantly improved the learning and memory abilities of APP/PS1 mice, ameliorated the neuropathological damage in the CA1 region of the hippocampus, increased the number of neurons, and decreased the deposition of Aβ_(1-42) in the brain. A total of 1 240 DEGs were screened out, including 634 genes with up-regulated expression and 606 genes with down-regulated expression. The GO analysis predicted the biological processes including RNA splicing and protein folding, the cellular components including spliceosome complexes and nuclear spots, and the molecular functions including unfolded protein binding and heat shock protein binding. The KEGG pathway enrichment analysis revealed the involvement of neurodegenerative disease pathways, amyotrophic lateral sclerosis, and splicing complexes. Further GSVA pathway enrichment analysis showed that the down-regulated pathways involved nuclear factor-κB(NF-κB)-mediated tumor necrosis factor-α(TNF-α) signaling pathway, UV response, and unfolded protein response, while the up-regulated pathways involved the Wnt/β-catenin signaling pathway. The results of RT-qPCR and Western blot showed that compared with the APP/PS1 group, Daotan Xixin Decoction at different doses down-regulated the mRNA and protein levels of signal transducer and activator of transcription 3(STAT3), NF-κB, and interleukin-6(IL-6) in the hippocampus. In conclusion, Daotan Xixin Decoction can improve the learning and memory abilities of APP/PS1 mice by regulating the STAT3/NF-κB/IL-6 signaling pathway.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Male ; Alzheimer Disease/metabolism* ; Computational Biology ; Mice, Inbred C57BL ; High-Throughput Nucleotide Sequencing ; Amyloid beta-Protein Precursor/metabolism* ; Hippocampus/metabolism* ; Mice, Transgenic ; Presenilin-1/metabolism* ; Humans ; Memory/drug effects* ; Maze Learning/drug effects* ; Amyloid beta-Peptides/genetics* ; Disease Models, Animal

This study explored the action mechanism of Jiawei Xionggui Decoction in the treatment of Alzheimer's disease(AD) by integrating mouse brain tissue metabolomics and network pharmacology. Six-month-old amyloid precursor protein/presenilin 1(APP/PS1) mice were selected and divided into the APP/PS1 group and Jiawei Xionggui Decoction intervention group, with age-matched C57BL/6 mice serving as controls. Cognitive abilities and pathological damage in the mice were observed. Gas chromatography-mass spectrometry/mass spectrometry(GC-MS/MS) technology was utilized to analyze the metabolic profiles of mice brain tissue. Differential metabolites were screened, and relevant metabolic pathways were enriched. Network pharmacology was adopted to screen the active components of Jiawei Xionggui Decoction, so as to construct a protein-protein interaction network of its core targets for AD treatment and conduct Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis of potential targets for Jiawei Xionggui Decoction in treating AD. Finally, a "metabolite-reaction-enzyme-gene" network was constructed for combined analysis of metabolomics and network pharmacology. The results showed that Jiawei Xionggui Decoction significantly reversed the trends of 18 differential metabolites involved in 15 metabolic pathways such as glyoxylate and dicarboxylate metabolism, glycine, serine, and threonine metabolism, pyruvate metabolism, alanine, aspartate, and glutamate metabolism, and tricarboxylic acid cycle(TCA) in mouse brain tissue. Furthermore, 383 core targets of Jiawei Xionggui Decoction were implicated in pathways like the phosphoinositide 3-kinase(PI3K)/protein kinase B(Akt) signaling pathway and calcium signaling pathway. Overall analysis indicated that energy metabolism, amino acid metabolism, and fatty acid metabolism were crucial metabolic pathways for Jiawei Xionggui Decoction in treating AD. The findings suggest that Jiawei Xionggui Decoction can protect neuronal cells in mouse brain tissue, thus improving cognitive impairment.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Network Pharmacology ; Metabolomics ; Cognitive Dysfunction/genetics* ; Alzheimer Disease/genetics* ; Mice, Inbred C57BL ; Amyloid beta-Protein Precursor/metabolism* ; Male ; Brain/drug effects* ; Humans ; Presenilin-1/metabolism* ; Protein Interaction Maps/drug effects* ; Mice, Transgenic ; Disease Models, Animal

This study aimed to explore the pharmacological mechanism of Yourenji Capsules(YRJ) in improving osteoporosis by combining network pharmacology and proteomics technologies. The SD rats were randomly divided into a blank control group and a 700 mg·kg~(-1) YRJ group. The rats were subjected to gavage administration with the corresponding drugs, and the blank serum, drug-containing serum, and YRJ samples were compared using ultra performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) to analyze the main components absorbed into blood. Network pharmacology analysis was conducted based on the YRJ components absorbed into blood to obtain related targets of the components and target genes involved in osteoporosis, and Venn diagrams were used to identify the intersection of drug action targets and disease targets. The STRING database was used for protein-protein interaction(PPI) network analysis of potential target proteins to construct a PPI network. Gene Ontology(GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment were performed using Enrichr to investigate the potential mechanism of action of YRJ. Ovariectomy(OVX) was performed to establish a rat model of osteoporosis, and the rats were divided into a sham group, a model group, and a 700 mg·kg~(-1) YRJ group. The rats were given the corresponding drugs by gavage. The femurs of the rats were subjected to label-free proteomics analysis to detect differentially expressed proteins, and GO functional enrichment and KEGG pathway enrichment analyses were performed on the differentially expressed proteins. With the help of network pharmacology and proteomics results, the mechanism by which YRJ improves osteoporosis was predicted. The analysis of the YRJ components absorbed into blood revealed 23 bioactive components of YRJ, and network pharmacology results indicated that key targets involved include tumor necrosis factor(TNF), tumor protein p53(TP53), protein kinase(AKT1), and matrix metalloproteinase 9(MMP9). These targets are mainly involved in osteoclast differentiation, estrogen signaling pathways, and nuclear factor-kappa B(NF-κB) signaling pathways. Additionally, the proteomics analysis highlighted important pathways such as peroxisome proliferator-activated receptor(PPAR) signaling pathways, mitogen-activated protein kinase(MAPK) signaling pathways, and β-alanine metabolism. The combined approaches of network pharmacology and proteomics have revealed that the mechanism by which YRJ improves osteoporosis may be closely related to the regulation of inflammation, osteoblast, and osteoclast metabolic pathways. The main pathways involved include the NF-κB signaling pathways, MAPK signaling pathways, and PPAR signaling pathways, among others.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Osteoporosis/metabolism* ; Proteomics ; Rats ; Rats, Sprague-Dawley ; Network Pharmacology ; Female ; Protein Interaction Maps/drug effects* ; Capsules ; Humans ; Signal Transduction/drug effects*

The Baihe Dihuang Decoction(BDD) is a representative traditional Chinese medicine formula that has been used to treat depression. This study employed metabolomics and network pharmacology to investigate the mechanism of BDD in the treatment of depression. Fifty male Sprague-Dawley(SD) rats were randomly assigned to the normal control group, model group, fluoxetine group, and high-and low-dose BDD groups. A rat model of depression was established through chronic unpredictable mild stress(CUMS), and the behavioral changes were detected by forced swimming test and open field test. Metabolomics technology was used to analyze the metabolic profiles of serum and hippocampal tissue to screen differential metabolites and related metabolic pathways. Additionally, network pharmacology and molecular docking techniques were used to investigate the key targets and core active ingredients of BDD in improving metabolic abnormalities of depression. A "component-target-metabolite-pathway" regulatory network was constructed. BDD could significantly improve depressive-like behavior in CUMS rats and regulate 12 differential metabolites in serum and 27 differential metabolites in the hippocampus, involving tryptophan metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, alanine, aspartate, and glutamate metabolism, tyrosine metabolism, and purine metabolism. Verbascoside, isorbascoside, and regaloside B were the key active ingredients for improving metabolic abnormalities in depression. Epidermal growth factor receptor(EGFR), protooncogene tyrosine-protein kinase(SRC), glycogen synthase kinase 3β(GSK3β), and androgen receptor(AR) were the key core targets for improving metabolic abnormalities of depression. This study offered a preliminary insight into the mechanism of BDD in alleviating metabolic abnormalities of depression through network regulation, providing valuable guidance for its clinical use and subsequent research.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Rats ; Metabolomics ; Depression/genetics* ; Antidepressive Agents/chemistry* ; Network Pharmacology ; Hippocampus/drug effects* ; Humans ; Molecular Docking Simulation ; Behavior, Animal/drug effects* ; Disease Models, Animal

To explore the anti-depression effect of Suanzaoren Decoction(SZRD), the regulatory effects on endogenous metabolites in the liver of rats with depression induced by chronic unpredictable mild stress(CUMS) were analyzed by using LC-MS metabolomics. The rats were randomly divided into normal control group, model group, low-dose SZRD group, high-dose SZRD group, and positive drug group. The CUMS depression model was replicated by applying a variety of stimuli, such as fasting and water deprivation, ice water swimming, hot water swimming, day and night reversal, tail clamping, and restraint for rats. Modeling and treatment were conducted for 56 days. The behavioral indexes of rats in each group, including body weight, open field test, sucrose preference test, and tail suspension test, were observed. Plasma samples and liver tissue samples were collected, and the contents of 5-hydroxytryptamine(5-HT), dopamine(DA), and norepinephrine(NE) in plasma were measured using enzyme-linked immunosorbent assay(ELISA). Meanwhile, the regulatory effects of SZRD on the liver metabolic profile of CUMS model rats were analyzed by the LC-MS metabolomics method. The results show that SZRD can significantly improve the depression-like behavior of CUMS model rats and increase the neurotransmitter levels of 5-HT, DA, and NE in plasma. A total of 24 different metabolites in the rats' liver are identified using the LC-MS metabolomics method, and SZRD can reverse 13 of these metabolites. Metabolic pathway analysis indicates that nine metabolic pathways are found to be significantly associated with depression, and in the low-dose SZRD group, four pathways can be regulated, including pentose phosphate pathway, purine metabolism, inositol phosphate metabolism, and sphingolipid metabolism. In the high-dose SZRD group, two metabolic pathways can be regulated, including sphingolipid metabolism and glycerol glycerophospholipid metabolism. Sphingolipid metabolism is a metabolic pathway that can be regulated by SZRD at different doses, so it is speculated that it may be the primary pathway through which SZRD can alleviate metabolic disturbances in the liver of CUMS model rats.
Animals ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Metabolomics ; Depression/metabolism* ; Male ; Liver/drug effects* ; Rats, Sprague-Dawley ; Antidepressive Agents/administration & dosage* ; Serotonin/blood* ; Humans ; Disease Models, Animal ; Behavior, Animal/drug effects*

With the advancement in big data and artificial intelligence technologies, the extensive application of omics technologies in traditional Chinese medicine(TCM) research has generated large experimental datasets, enabling the exploration of cross-scale correlations among massive data and thereby resulting in the shift toward a data-intensive research paradigm. The emerging approach of multi-omics data fusion analysis, emphasizing technical and computational tools, presents a potential breakthrough in this field. The holistic perspective of TCM aligns with the concept of multi-omics data fusion, yet the data types encountered exhibit high dimensionality with small sample sizes, necessitating data processing techniques such as dimensionality reduction. The current challenge lies in selecting suitable analytical methods for these data to enhance the systematic understanding of physiological functions and disease diagnosis/treatment processes. This paper explores the theories and frameworks of multi-omics data fusion, analyzes methods for fusing high-dimensional, small-sample multi-omics data in TCM, and aims to provide insights for advancing TCM research.
Medicine, Chinese Traditional/methods* ; Humans ; Computational Biology/methods* ; Genomics/methods* ; Sample Size ; Artificial Intelligence ; Multiomics

A serum metabolomics analysis method based on gas chromatography-mass spectrometry(GC-MS) was used to investigate the metabolic regulation mechanism of Hericium erinaceus(H. erinaceus) polysaccharides on radiation injury. A mouse model of radiation injury was established by ~(60)Co-γ irradiation. High and low dose groups of H. erinaceus polysaccharide injection were designed, and Rubiae Radix et Rhizoma extract was set as the positive control group to investigate the therapeutic effects and metabolic reaction pathways of H. erinaceus polysaccharides on radiation injury. The metabolites of serum samples were collected by GC-MS, and principal component analysis(PCA) was conducted to establish the metabolic profiles of each group of mice. Partial least squares discriminant analysis(PLS-DA), t-test(P<0.05), and variable importance in the projection(VIP>1) were used to screen out the differential metabolite. Metabolite identification and construction of related metabolic pathways and metabolic networks were achieved by using online databases such as HMDB and METLIN. The results showed that 12 differential metabolites in the serum of mice irradiated at 6.5 Gy that were associated with the radiation injury model, including lactic acid, alanine, urea, serine, threonine, glycerol, L-5-oxoproline, L-lysine, stearic acid, stearic acid, oleic acid, and 1-monopalmitoylglucoside. Two metabolic pathways were enriched: glycerolipid metabolism and metabolism of glycine, serine, and threonine. 18 differential metabolites in the serum of mice irradiated at 8.5 Gy were associated with the radiation injury model, including lactic acid, alanine, urea, L-leucine, glycerol, nonanoic acid, serine, threonine, L-5-oxoproline, phenylalanine, L-ornithine, 1,5-dehydroorbital, L-lysine, L-tyrosine, pectic, oleic, stearic, and cholesterol. Four metabolic pathways were enriched: phenylalanine, tyrosine, and tryptophan synthesis, phenylalanine metabolism, glyceride metabolism, and glycine, serine, and threonine metabolism. It was suggested that H. erinaceus polysaccharides could intervene in radiation injury by altering amino acid and fatty acid synthesis in mice. It was assumed that H. erinaceus polysaccharides regulated the level of metabolic pathways through lipid metabolism and amino acid metabolism, thus affecting energy metabolism and amino acid metabolism and exerting its therapeutic effect on radiation damage.
Animals ; Mice ; Metabolomics/methods* ; Gas Chromatography-Mass Spectrometry/methods* ; Polysaccharides/pharmacology* ; Male ; Hericium/chemistry* ; Drugs, Chinese Herbal/administration & dosage* ; Metabolome/drug effects* ; Gamma Rays/adverse effects*

This study investigates the reproductive protective effect and potential mechanism of Cistanches Herba extract(CHE) on a rat model of kidney-Yang deficiency induced by adenine. Rats were randomly divided into five groups: normal, model, low-dose CHE(0.6 g·kg~(-1)·d~(-1)), high-dose CHE(1.2 g·kg~(-1)·d~(-1)), and L-carnitine(100 mg·kg~(-1)·d~(-1)). The rats were administered adenine(200 mg·kg~(-1)·d~(-1)) by gavage for the first 14 days to induce kidney-Yang deficiency, while simultaneously receiving drug treatment. After 14 days, the modeling was discontinued, but drug treatment continued to 49 days. The content of components in CHE was analyzed by high-performance liquid chromatography. The adenine-induced kidney-Yang deficiency model was assessed through symptom characterization and measurement of testosterone(T) levels using an enzyme-linked immunosorbent assay kit. Pathological damage to the testis and epididymis was evaluated based on the wet weight and performing hematoxylin-eosin staining. Sperm density and motility were measured using computer-aided sperm analysis, and sperm viability was assessed using live/dead sperm staining kits, and sperm morphology was evaluated using eosin staining, thereby determining rat sperm quality. Metabolomics was used to analyze changes in serum metabolites, enrich related metabolic pathways, and explore the mechanism of CHE in improving reproductive function damage in rats with kidney-Yang deficiency syndrome. Compared to the normal group, the model group exhibited significant kidney-Yang deficiency symptoms, reduced T levels, decreased testicular and epididymal wet weights, and significant pathological damage to the testis and epididymis. The sperm density, motility, and viability decreased, with an increased rate of sperm abnormalities. In contrast, rats treated with CHE showed marked improvements in kidney-Yang deficiency symptoms, restored T levels, alleviated pathological damage to the testis and epididymis, and improved various sperm parameters. Metabolomics results revealed 286 differential metabolites between the normal and model groups(191 upregulated and 95 downregulated). Seventy-five differential metabolites were identified between the model and low-dose CHE groups(21 upregulated and 54 downregulated). A total of 24 common differential metabolites were identified across the three groups, with 22 of these metabolites exhibiting opposite regulation trends between the two comparison groups. These metabolites were primarily involved in linoleic acid metabolism, ether lipid metabolism, and pantothenic acid and coenzyme A biosynthesis, as well as metabolites including 13-hydroperoxylinoleic acid, lysophosphatidylcholine, and pantethine. CHE can improve kidney-Yang deficiency symptoms in rats, alleviate reproductive organ damage, and enhance sperm quality. The regulation of lipid metabolism may be a potential mechanism through which CHE improves reproductive function in rats with kidney-Yang deficiency. The potential bioactive compounds of CHE include echinacoside, verbascoside, salidroside, betaine, and cistanoside A.
Animals ; Male ; Rats ; Yang Deficiency/physiopathology* ; Metabolomics ; Kidney/physiopathology* ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/administration & dosage* ; Cistanche/chemistry* ; Kidney Diseases/metabolism* ; Testis/metabolism* ; Humans ; Reproduction/drug effects* ; Testosterone/blood*