Functional dyspepsia （FD） is a prioritized disease category where traditional Chinese medicine （TCM） demonstrates distinct therapeutic advantages. The current western medicine treatment for FD is mainly based on proton pump inhibitors and prokinetic agents， with digestive enzymes， probiotics and antidepressants serving as adjuvant medication， yet such therapies still have certain limitations. TCM treatment for FD includes oral administration of Chinese herbal formulas and Chinese patent medicines， as well as external TCM therapies such as acupuncture and moxibustion， acupoint application， hot medicinal compress therapy， rubbing with ointment， medicinal iontophoresis， auricular acupoint therapy and tui na （Chinese medical massage）. The combined treatment of FD with integrated TCM and western medicine can significantly improve clinical effectiveness and reduce adverse reactions. The common mechanisms underlying the therapeutic effects of both TCM and western medicine revolve around the core pathological processes of FD， mainly focusing on restoring gastrointestinal motility， regulating the levels of brain-gut peptides， modulating intestinal microecology， and ameliorating inflammatory status. The differential mechanisms lie in the precise targeting feature of western medicine versus the holistic-regulating and multi-target characteristics of TCM， and the two approaches exert a synergistic effect to enhance efficacy. This paper proposes to leverage the advantages of TCM in holistic regulation and the strengths of western medicine in targeted treatment， so as to provide personalized and comprehensive treatment regimens for FD patients.

Objective To explore the potential molecular mechanism of Sangma Xingbei Tang （SMXBT） in the treatment of acute exacerbation of chronic obstructive pulmonary disease （AECOPD）. Methods TCMSP and TCMID databases were searched for the active ingredients of SMXBT, the targets of the active ingredients were predicted by SwissTargetPrediction database, and the AECOPD-related targets were searched by GeneCards and OMIM databases; the drug-active ingredient-target network and protein interaction network were constructed, and the GO enrichment and KEGG pathway enrichment were analyzed by the DAVID database. The drug-active ingredient-target network and protein interaction network were constructed, and the GO enrichment and KEGG pathway enrichment were analyzed by DAVID database, and molecular docking was performed by AutoDock Tools software. Animal experiments were conducted for validation. Results 192 active ingredients were obtained and 1066 targets were predicted in SMXBT. Network analysis showed that the top 3 active ingredients in SMXBT were quercetin, kaempferol, and glycyrrhizin, and the top 3 therapeutic targets were TNF, ALB, and IL-1β, etc. The GO analysis and KEGG showed that the main pathways were the cancer pathway, the MAPK signaling pathway, and the PI3K-Akt signaling pathway. Molecular docking showed that the binding energies of glycyrrhizin and AKT1, IL-1β, GFR, SRC, and quercetin and kaempferol and IL-1β were all <−5 kcal·mol. Animal experiments showed that Sangma Xingbei Decoction could treat AECOPD by anti-inflammatory effects and reduce changes in lung tissue structure. Additionally, it could lower the serum inflammatory levels of TNF-α, IL-6, and IL-8. Conclusion SMXBT may act on the targets of AKT1, IL-1β, EGFR, SRC, etc., reduce the serum inflammation levels of TNF-α, IL-6, IL-8, and improve the lung tissue structure and inflammatory response to achieve the therapeutic effect on AECOPD through the modulation of the PI3K/Akt signaling pathway, the MAPK signaling pathway, the cancer pathway, and other pathways of action.

ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

BACKGROUND:A large number of studies have demonstrated that stem cell exosomes play an important role in the repair of bone defects,either directly as carriers for loading other small molecules or surface modifications,or by binding to biomaterials to promote the repair and regeneration of bone tissue.OBJECTIVE:To summarize the osteogenic mechanisms of stem cell exosomes from different sources and their research progress in bone defect repair.METHODS:Chinese search terms"stem cell,exosome,bone,biomaterial,carrier,bioceramic,polymer,metal,hydrogel,engineered exosome"were used to search CNKI.English search terms"stem cell,exosome,bone defect,biomaterial,carrier,bioceramic,ploymer,metal material,hydrogel,engineering exosome"were used to search PubMed database.According to the inclusion and exclusion criteria,77 relevant articles were finally included for summary.RESULTS AND CONCLUSION:Exosomes from stem cells of different origins can promote osteoblast proliferation and differentiation,promote angiogenesis,and regulate osteoclast activity and macrophage phenotype to promote bone formation and bone mineralization.In addition,many achievements of exosomes in the field of bone defect repair were described from two aspects:biomaterial-assisted exosomes and engineered exosomes.However,the current research on stem cell exosomes in bone tissue engineering is still insufficient,and most of these studies are limited to small animal models,while the treatment of bone defects in large animals,including humans,will be more complex,which will also become a major challenge for the treatment of bone defects.This will also be a great challenge in the dissemination of exosome therapy.

BACKGROUND:A large number of studies have demonstrated that stem cell exosomes play an important role in the repair of bone defects,either directly as carriers for loading other small molecules or surface modifications,or by binding to biomaterials to promote the repair and regeneration of bone tissue.OBJECTIVE:To summarize the osteogenic mechanisms of stem cell exosomes from different sources and their research progress in bone defect repair.METHODS:Chinese search terms"stem cell,exosome,bone,biomaterial,carrier,bioceramic,polymer,metal,hydrogel,engineered exosome"were used to search CNKI.English search terms"stem cell,exosome,bone defect,biomaterial,carrier,bioceramic,ploymer,metal material,hydrogel,engineering exosome"were used to search PubMed database.According to the inclusion and exclusion criteria,77 relevant articles were finally included for summary.RESULTS AND CONCLUSION:Exosomes from stem cells of different origins can promote osteoblast proliferation and differentiation,promote angiogenesis,and regulate osteoclast activity and macrophage phenotype to promote bone formation and bone mineralization.In addition,many achievements of exosomes in the field of bone defect repair were described from two aspects:biomaterial-assisted exosomes and engineered exosomes.However,the current research on stem cell exosomes in bone tissue engineering is still insufficient,and most of these studies are limited to small animal models,while the treatment of bone defects in large animals,including humans,will be more complex,which will also become a major challenge for the treatment of bone defects.This will also be a great challenge in the dissemination of exosome therapy.

Objective To investigate the epidemiological characteristics and changing trend of typhus in Shaanxi Province from 2005 to 2023 to provide a scientific basis for its prevention and control. Methods Excel 2007, SPSS 25.0, Joinpoint 4.9.1.0, and Geoda 1.6 were used for data collection and statistical analysis. Super Map was used for data visualization to describe the changing characteristics of the disease. Results A total of 394 typhus cases were reported in Shaanxi Province from 2005 to 2023. The average annual incidence of typhus was 0.054/100 000, showing a dynamic fluctuation trend(AAPC=-3.3, t=-0.3, P>0.05). The cases were mainly concentrated in Baoji, Hanzhong and Xi′an, accounting for 78.68%. The incidence peak was from May to October, accounting for 64.21% of annual incidence. The epidemic season was from May to October and December. The incidence of the disease was concentrated in the 40-69 age group, accounting for 58.88%, and the sex was 1.07:1. The main occupation was farmers, accounting for 72.08%. The median time from onset to diagnosis was 7 days. Global spatial autocorrelation analysis showed that there were significant spatial autocorrelations in 11 years from 2005 to 2023(P<0.05). Local spatial autocorrelation analysis detected a total of 43“high-high”clustering areas, mainly concentrated in Baoji City. Conclusions The overall incidence of typhus in Shaanxi Province showed a dynamic fluctuation trend, with notable seasonal and regional aggregation. The incidence of typhus was higher in middle-aged and elderly people in rural areas. Surveillance should be strengthened in typhus endemic areas in summer and autumn, and health education should be conducted for key population to form good health habits and reduce the incidence of typhus.

Objective To establish a standardized quality criterion for the formula of the Liuwei Runfu oil recipe. Methods The qualitative identification of the components, such as Cannabis sativa, Ligusticum chuanxiong, Angelica sinensis, Coix lacryma-jobi, and Glycyrrhiza uralensis, was conducted by thin layer chromatography （TLC）. The concentration of Senkyunolide A, ligustilide, and linoleic acid was determined by high-performance liquid chromatography （HPLC）. Results The TLC identification results demonstrated excellent differentiation and high selectivity, without any disruption from the negative samples. The reference standard for Senkyunolide A exhibited excellent linearity in the range of 25 to 300 µg （r=0.9999）, with an average recovery rate of 102.3% and a relative standard deviation （RSD） of 2.3%. The ligustilide reference standard exhibited strong linearity between the concentrations of 0.6875 and 8.25 µg （r=0.9993）, with an average recovery rate of 100.1% and a relative standard deviation （RSD） of 2.8%. The linoleic acid reference standard demonstrated strong linear correlation within the range of 2.8125 to 33.75 µg （r=0.9990）, with an average spiking recovery rate of 102.7% and a relative standard deviation （RSD） of 1.7%. Conclusion The established method with strong specificity was simple，accurate，reliable，which coulod provide a reference for the quality control of the Liuwei Runfu oil recipe.

ObjectiveTo develop and validate a diagnostic prediction model for differentiating pulmonary tuberculosis from community-acquired pneumonia based on routine blood parameters. MethodsA total of 642 patients with pulmonary tuberculosis and 503 patients with community-acquired pneumonia were retrospectively enrolled from the Seventh Hospital of Tangshan. They were randomly divided into a training set and an internal validation set at a 7∶3 ratio. Additionally， 218 patients from the 981st Hospital were independently included as an external validation set. The Boruta algorithm and recursive feature elimination were employed to select predictors from 82 blood parameters， sex， and age. A multivariate Logistic regression model was established and evaluated using receiver operating characteristic （ROC） curves， calibration curves， and decision curve analysis. ResultsThe final model incorporated eight predictors， namely uric acid， urea nitrogen， alkaline phosphatase， monoamine oxidase， alanine aminotransferase， glutathione， neutrophil percentage， and age. The model achieved areas under the curve （AUCs） of 0.800 （95%CI： 0.769-0.830）， 0.787 （95%CI： 0.738-0.836）， and 0.736 （95%CI： 0.667-0.835） in the training， internal validation， and external validation sets， respectively. The model demonstrated good calibration， and decision curve analysis showed clinical net benefit within the threshold probability range of 10%-80%. ConclusionThe developed model exhibits good discriminative ability and clinical utility， serving as an effective early screening tool for primary healthcare institutions.

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