Project description:Transcriptomic signature of human embryonic thyroid is not described so far. The goal of this project was to evaluate what enables the transition from differentiation to functional maturation of the human developing thyroid, by performing transcriptomic analysis of human thyroids covering the period of gestation weeks 7-11 and comparing it to adult human thyroids. We defined a non TSH (thyroid stimulating hormone) dependent transition from differentiation to maturation of thyroid. The study also sought to shed light on possible factors that could replace TSH, which is absent in this window of gestational age, to trigger transition to the emergence of thyroid function.
Project description:Re-uploaded from the integrated proteome resources (iProX) with the dataset identifier IPX0004220000. https://doi.org/10.3390/diagnostics12092184
"In this study, a comprehensive analysis approach based on 1D-LC-MS/MS and 2D-LC-MS/MS was applied to profile normal human urine metabolites from 348 children and 315 adults."
Project description:Affimetrix Human Gene 1.1 ST Array profiling of 13 normal human cerebellum samples. Total RNA from 8 fetal brains and 5 adult brains was obtained from the Biochain company.
Project description:The interaction between cancer and stroma plays a key role in tumor progression. Inactivation of p53 is often observed in stromal cells surrounding in cancer, suggesting that p53 in fibroblasts is involved in tumor progression. To elucidate the mechanism by which p53 loss in fibroblasts effect on proliferation and invasiveness of cancer cells, we performed comprehensive expression profiling analyses between p53 knockdown and control fibroblasts using GeneChip Human Genome U133 plus 2.0 arrays. Intact human fetal lung normal diploid fibroblasts TIG-7 cells and TIG-7 cells infected with lentiviruses for the expression of shRNA against p53 were used for RNA extraction and hybridization on Affymetrix microarrays.
Project description:Healthy adults with serum insulin like growth factor -1 (IGF-I) levels at the lowest quartile of normal ranges have increased fat metabolism and reduced glucose utlisation compared with those in the highest quartile during fasting We used gene expression in skeletal muscle to explore metabolism during fasting