Biomedical subjects

Tao You

Publications and source records attributed to Tao You.

3 recordsLinked to original sources

PubMed2025

Association of MTHFD1 G1958A (rs2236225) gene polymorphism with the risk of congenital heart disease: a systematic review and meta-analysis.

BACKGROUND: We did this study to better clarify the correlations of methylenetetrahydrofolate dehydrogenase 1 (MTHFD1)-G1958A (rs2236225) gene polymorphism with the risk of congenital heart diseases (CHD) and its subgroups. METHODS: Relevant articles were searched in PubMed, Web of Science, Cochrane Library, Embase, CNKI, VIP database and Wanfang DATA until October 2023. We will use odds ratios (ORs) and 95% confidence intervals (CIs) to examine the potential associations of MTHFD1- G1958A gene polymorphism with CHD and its subgroups. RESULTS: We included a total of 9 eligible studies, encompassing 1917 children with CHD, 1863 healthy children, 1717 mothers of the children with CHD and 1666 mothers of healthy children. In our study, the meta-analysis of fetal group revealed no significant association between any of the five genetic models for the MTHFD1-G1958A polymorphism and the risk of CHD. Subgroup analysis showed that associations between the MTHFD1-G1958A polymorphism and Tetralogy of Fallot (TOF) risk in the homozygote model (AA vs. GG, OR = 2.82, 95%CI [1.16, 6.86], P = 0.02) and recessive model (AA vs. GG + GA, OR = 3.09, 95%CI [1.36, 7.03], P = 0.007). In addition, the MTHFD1-G1958A polymorphism was associated with the risk of CHD in racial subgroup, increasing the risk of CHD in Caucasians. In maternal analysis, 2 genetic models of MTHFD1-G1958A polymorphism increased the risk of CHD: the heterozygote model (GA vs. GG, OR = 1.22, 95%CI [1.04, 1.42], P = 0.01), and the dominance model (GA + AA vs. GG, OR = 1.17, 95%CI [1.01, 1.34], P = 0.03). CONCLUSIONS: The fetal MTHFD1-G1958A (rs2236225) gene polymorphism increase their risk of TOF. The maternal MTHFD1-G1958A polymorphism has a strong correlation with the risk of CHD, and there are racial differences in this correlation. Compared with GG genotype, the GA genotype increases the risk of CHD.

Humans↗

PubMed2006

Proteomic analysis of colorectal cancer reveals alterations in metabolic pathways: mechanism of tumorigenesis.

Colorectal cancer is the second leading killer cancer worldwide and presently the most common cancer among males in Singapore. The study aimed to detect changes of protein profiles associated with the process of colorectal tumorigenesis to identify specific protein markers for early colorectal cancer detection and diagnosis or as potential therapeutic targets. Seven pairs of colorectal cancer tissues and adjacent normal mucosa were examined by two-dimensional gel electrophoresis at basic pH range (pH 7-10). Intensity changes of 34 spots were detected with statistical significance. 16 of the 34 spots were identified by MALDI-TOF/TOF tandem mass spectrometry. Changes in protein expression levels revealed a significantly enhanced glycolytic pathway (Warburg effect), a decreased gluconeogenesis, a suppressed glucuronic acid pathway, and an impaired tricarboxylic acid cycle. Observed changes in protein abundance were verified by two-dimensional DIGE. These changes reveal an underlying mechanism of colorectal tumorigenesis in which the roles of impaired tricarboxylic acid cycle and the Warburg effect may be critical.

Case-Control Studies↗

PubMed2006

SPLASH: systematic proteomics laboratory analysis and storage hub.

In the field of proteomics, the increasing difficulty to unify the data format, due to the different platforms/instrumentation and laboratory documentation systems, greatly hinders experimental data verification, exchange, and comparison. Therefore, it is essential to establish standard formats for every necessary aspect of proteomics data. One of the recently published data models is the proteomics experiment data repository [Taylor, C. F., Paton, N. W., Garwood, K. L., Kirby, P. D. et al., Nat. Biotechnol. 2003, 21, 247-254]. Compliant with this format, we developed the systematic proteomics laboratory analysis and storage hub (SPLASH) database system as an informatics infrastructure to support proteomics studies. It consists of three modules and provides proteomics researchers a common platform to store, manage, search, analyze, and exchange their data. (i) Data maintenance includes experimental data entry and update, uploading of experimental results in batch mode, and data exchange in the original PEDRo format. (ii) The data search module provides several means to search the database, to view either the protein information or the differential expression display by clicking on a gel image. (iii) The data mining module contains tools that perform biochemical pathway, statistics-associated gene ontology, and other comparative analyses for all the sample sets to interpret its biological meaning. These features make SPLASH a practical and powerful tool for the proteomics community.

Database Management Systems↗