RESUMO
Material stocks have created alternative perspectives in many environmental and climate studies. Their significance nonetheless may be under-explored, partially due to scarcity of more precise, timely and higher-resolution information. To address this limitation, our present study developed a gridded material stocks dataset for China in Year 2000 and 2020, by examining the geographical distribution and geometric configurations of the human-made stock-containing environment. The stocks of twelve materials embodied in five end-use sectors and 104 products and constructions were assessed at a resolution of 1 × 1 km grid. Material intensity in each product or construction component was carefully evaluated and tagged with its geometric conformation. The gridded stocks aggregately are consistent with the stock estimation across 337 prefectures and municipalities. The reliability of our assessment was also validated by previous studies from national, regional, to grid levels. This gridded mapping of material stocks may offer insights for urban-rural disparities, urban mining opportunity, and climate and natural disaster resilience.
RESUMO
Background: Numerous studies, ranging from the alleviation of tissue ischemia to the assessment of cancer prognosis, have demonstrated the fundamental biological differences between human umbilical cord blood-derived endothelial progenitor cells (CB-EPCs) and adult peripheral blood-derived endothelial progenitor cells (PB-EPCs). However, the underlying molecular mechanisms that produce these differences are not clear.The purpose of this study was to identify potential hub genes, key protein interactive networks, and correlated signal pathways unique to CB-EPC biology via bioinformatic methods. Materials and Methods: We selected the microarray dataset GSE39763 and identified the differentially expressed genes (DEGs) using the "limma" package in the RStudio software. These DEGs were annotated by gene ontology enrichment analyses and signal pathway analyses. A protein-protein interaction (PPI) analysis was then performed to construct PPI networks and identify a hub protein module. We further validated candidate DEGs from the selected module in the gene expression profiling interactive analysis (GEPIA) database because the DEGs were enriched in cancer pathways. Results: Setting an adjusted p-value <0.01 and |Log2 fold change (FC)| ≥ 2 as cutoff criteria, a total of 346 DEGs, including 314 upregulated genes and 32 downregulated genes in CB-EPCs, were identified. Expression of the genes encoding the AT-Hook Containing Transcription Factor 1 (AHCTF1), the Cancer Susceptibility Candidate 5 (CASC5), the Centromere Protein C (CENPC), the Centromere Protein E (CENPE), the Centromere Protein F (CENPF), the NUF2 Component of NDC80 Kinetochore Complex (NUF2), the RAN-Binding Protein 2 (RANBP2), the Shugoshin-like 2 (SGOL2), the Structural Maintenance of Chromosomes 3 (SMC3), and the Spindle Apparatus Coiled-Coil Protein 1 (SPDL1) proteins were specifically associated with CB-EPCs. Except for CENPC, the other nine genes' expression are all associated with a poorer overall survival rate in cancers. The expression levels of the CENPF and NUF2 genes in tumor patients were significantly higher than those in the controls. Conclusion: The CB-EPCs express genes with greater potential for proliferation and increased migration compared to PB-EPCs; in this regard they are similar to cancer cells.
