Methods: CHB patients and healthy volunteers were enrolled from Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine between August 21, 2018 and December 31, 2020. They were divided into three groups: healthy group, LGDHS group, and latent syndrome (LP) group. Proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) was performed to identify differentially expressed proteins (DEPs). Metabolomic profiling via ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was applied to serum samples to detect differentially regulated metabolites (DMs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment were employed to explore dysregulated pathways. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to visualize group separation and identify key metabolites and proteins contributing to LGDHS differentiation. Receiver operating characteristic (ROC) curve analysis evaluated the diagnostic performance of key biomarkers, while logistic regression models assessed their predictive accuracy. P values were corrected for multiple tests using the Benjamini-Hochberg method to control the false discovery rate (FDR). Validation of potential biomarkers was conducted using independent microarray data and real-time quantitative polymerase chain reaction (RT-qPCR). Results: A total of 150 participants were enrolled, including healthy group (n = 45), LGDHS group (n = 60), and LP group (n = 45). 254 DEPs from proteomics data and 72 DMs from metabolomic profiling were identified by PCA and OPLS-DA. DEPs were mainly enriched in immune and complement pathways, while DMs involved in amino acid and energy metabolism. The integrated analysis identified seven key biomarkers: α1-acid glycoprotein (ORM1), asparagine synthetase (ASNS), solute carrier family 27 member 5 (SLC27A5), glucosidase II alpha subunit (GANAB), hexokinase 2 (HK2), 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), and maltase-glucoamylase (MGAM). Microarray validation confirmed the diagnostic potential of these genes, with area under the curve (AUC) values for ROC analysis ranging from 0.536 to 0.759. Among these, ORM1, ASNS, and SLC27A5 showed significant differential ability in differentiating LGDHS patients (P = 0.016, P = 0.035, and P < 0.001, respectively), with corresponding AUC of 0.749, 0.743, and 0.759, respectively. A logistic regression model incorporating these three genes demonstrated an AUC of 0.939, indicating a high discriminatory power for LGDHS. RT-qPCR further validated the differential expression of ORM1 and SLC27A5 between LGDHS and LP groups (P = 0.011 and P = 0.034, respectively), with ASNS showing a consistent trend in expression (P = 0.928). Conclusion This study integrates multi-omics approaches to uncover the molecular mechanisms underlying LGDHS in CHB. The identification of biomarkers ORM1, ASNS, and SLC27A5 offers a solid basis for the objective diagnosis of LGDHS, contributing to the standardization and modernization of TCM diagnostic practices.

ObjectiveTo explore the metabolic changes during the development of Tupaia belangeri breast tumors, to investigate the close relationship between the changes of serum metabolic substances and the occurrence and progression of tumors, and to screen for biomarkers reflecting the progression of breast tumors. MethodsBreast tumors in Tupaia belangeri were induced by orally administering 7,12-dimethylbenzoanthracene (DMBA) three times, with a 15-day interval between each administration, along with a high-fat and high-sugar diet. The DMBA-induced breast cancer group and the DMBA-inducedwithout breast cancer group were compared with the control group. Untargeted determination of serum metabolites was performed using gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) in DMBA-induced Tupaia belangeri with breast cancer, DMBA-induced without breast cancer and the control group. Multidimensional statistical analysis including unsupervised principal component analysis (PCA), and orthogonal partial least squares analysis (OPLS-DA) were conducted. Furthermore, t-test was used for intergroup differential comparison. Differential metabolites were screened under VIP>1 and P<0.05 conditions, and significantly changing differential metabolites were identified using the HMDB online database. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was utilized to enrich metabolic-related gene regulatory pathways. ResultsThe incidence of breast tumors was 40% in DMBA-induced Tupaia belangeri. Compared with the control group, 30 metabolic differential products were detected in the serum of the group with breast cancer, with 18 down-regulated and 12 up-regulated (VIP>1, P<0.05). KEGG pathway analysis revealed significant changes in four metabolic pathways: glutamate metabolism, glyceride metabolism, citric acid cycle, and alanine metabolism. Compared with the group without breast cancer, 18 metabolic differential products were detected, with 7 down-regulated and 11 up-regulated (VIP>1, P<0.05). KEGG pathway analysis revealed significant changes in the citric acid cycle and glutamate metabolism. Compared with the control group, 31 metabolic differential products were detected in the serum of the groups without breast cancer, with 14 down-regulated and 17 up-regulated (VIP>1, P<0.05). KEGG pathway analysis revealed significant changes in three metabolic pathways: glutamate metabolism, glyceride metabolism, and citric acid cycle. ConclusionMetabolomics analysis can reveal the characteristics of changes in metabolites in the serum of breast tumors. The results suggest that glutamate metabolism, glyceride metabolism, citric acid cycle, and alanine metabolism pathways are associated with the occurrence and development of DMBA-induced breast tumors in Tupaia belangeri. It provides a foundation for further research into the biological mechanism of breast cancer.

Stem cell is critical to regeneration of tissue or organ of human. How to promote repair or regeneration in the tissues/organ using its pluripotency is always an important issue. Lgr5-possitive cell is one type of the stem cell-like cells capable of pluripotent differentiation in various tissues/organs of both humans and mice. Current study showed that single or small amount Lgr5-possitive stem cells can grow and form a plurality of organs in 3D culture system, and some organs can present similar biological and physiological properties with the progenitor they were derived. These studies provided new insight into future orientation, for example, Lgr5-possitive inner ear cells were confirmed as inner ear pluripotent cells population, the experiences obtained from organoid studies of Lgr5-possitive cells have certainly showed potential in the future study of inner ear stem cells. This review will focus on the recent progress associated with Lgr 5-positive stem cells forming organoids in the 3D culture.