Biomedical subjects

Guoping Liu

Publications and source records attributed to Guoping Liu.

4 recordsLinked to original sources

PubMed2026

Genomic Structural Equation Modeling Identifies a Shared Inflammatory Genetic Dimension Across Inflammatory Arthritis Phenotypes and Biomarkers.

BACKGROUND: Inflammatory arthritis (IA), including rheumatoid arthritis (RA), psoriatic arthritis (PsA) and gout, shares systemic inflammatory features indexed by C-reactive protein (CRP) and interleukin-6 (IL-6), yet the extent of their common genetic basis remains unclear. AIMS: We aimed to delineate the shared genetic architecture across IA phenotypes and inflammatory biomarkers. MATERIALS AND METHODS: We applied genomic structural equation modelling (Genomic SEM) to GWAS summary statistics for RA, PsA, gout, CRP and IL-6, fitted a single common factor, and performed multivariate GWAS followed by fine-mapping, transcriptome-wide association, gene-based analysis, pathway enrichment, and cell-type and spatial mapping. RESULTS: A single common factor was fitted (CFI = 0.990, SRMR = 0.045). The multivariate GWAS identified 56 genome-wide significant SNPs across 10 independent lead loci, including one novel signal. Fine-mapping prioritized high-confidence variants near PTPN22, the CRP gene cluster and a urate-associated locus. Gene-level analyses converged on DCLRE1B, PTPN22, IL6R, NLRP3 and HNF1A, with pathway enrichment implicating inflammasome assembly and metabolic-inflammatory overlap. Cell-type enrichment highlighted myeloid populations, and spatial mapping localized signals to lung, kidney, mucosal epithelium and gastrointestinal tissues. DISCUSSION: These results delineate a shared inflammatory genetic dimension across IA phenotypes and biomarkers, anchored in immune, inflammasome, cytokine-receptor and metabolic pathways. CONCLUSION: Together, these findings provide a valuable framework for prioritizing candidate genes and cellular contexts for future investigation.

TWAS↗

PubMed2006

Ultrasonographic evaluation of osteosarcomas.

The ultrasonographic appearances of osteosarcomas and the roles of ultrasonography in the diagnosis and surgical staging of osteosarcomas were investigated. A comparative study was performed on 45 cases of osteosarcomas by ultrasonography and radiography. Bony changes, periosteal reaction and soft tissue mass were evaluated for each lesion. The results showed that ultrasonography revealed a solid mass around bone in 42 patients, bone destruction in 24 patients and periosteal reaction in 16 patients. Plain radiographs showed bony changes in 44 patients and no bony change in remaining one patient, shadowing of soft tissue swelling in 30 patients, and pulmonary metastases in 3 patients. Surgical biopsy and pathological examination confirmed osteosarcoma in all 45 patients. Soft tissue mass was confirmed in 42 patients surgically. The diagnostic accuracy of soft tissue masses by ultrasonography and radiography was 100 % (42/42) and 71.4 % (30/42), respectively. The positive rate of ultrasonography and radiography in displaying bony changes was 53.3 % (24/45) and 97.8 % (44/45), respectively. In conclusion, in the detection of soft tissue mass of osteosarcoma, ultrasonography is superior to radiography, and in displaying bony changes of osteosarcomas, radiography is superior to ultrasonography. So it may come to a conclusion that plain radiography combined with ultrasonography can completely display the bony and soft tissue lesion of osteosarcomas.

Adolescent↗

PubMed2006

[A new method for visual SARS DNA sequences analysis].

Traditional DNA sequence analysis is based on sequence alignment, while a new DNA visual sequence analysis is proposed in this paper. Based on S. Wolfram's cellular automation theory, the method transfers one-dimensional DNA sequence into two-demensional visual image. Applying this method to SARS DNA sequence analysis, a characteristic of SARS-CoV differing from non-SARS is discovered. Compared with all known coronaviruses' images, It is found that this is a unique characteristic of SARS virus, and it is helpful to clinical identification of SARS.

Algorithms↗

PubMed2005

Labeling conditions, in vitro properties and biodistributions of various Sn-labeled complexes.

Conditions for preparing Sn-EDTMP, Sn-DTPMP, Sn-TTHMP, Sn-HEDTMP and Sn-DTPA in aqueous solution in open air environments, and their in vitro properties including adsorption on hydroxyapatite (HA) and collagen (I) and binding to bovine serum albumin (BSA) were studied using (117m)Sn and 113Sn as tracers. Biodistributions of SnO2.xH2O.yEDTMP, SnO2.xH2O.yDTPMP, SnO2.xH2O.yTTHMP, SnO2.xH2O.yHEDTMP, SnO2.xH2O.yDTPA in normal mice were also tested. Based on the above experiments, the relationship between in vitro biochemical properties and biodistributions of these SnO2.xH2O.yLigands was investigated. The results show that Sn(IV)-Ligands are prone to hydrolysis into SnO2.xH2O.yLigands in aqueous solutions in open air environments, especially when the ligand is DTPA, when the molar ratio of metal to ligand is higher than 1:200, or when the pH of the solution is higher than 10. The in vitro experiments show that all of the SnO2.xH2O.yLigands bind strongly to BSA, and the binding percentages of SnO2.xH2O.yLigands to BSA are much higher than those of the corresponding Sn(IV)-Ligands. The biodistribution data indicate that all of the SnO2.xH2O.yLigands locate mainly in bone with little uptake in liver. When the binding percentages of SnO2.xH2O.yLigands to BSA are similar, those SnO2.xH2O.yLigands with higher adsorption on HA and collagen (I) undergo lower liver uptake.

Animals↗