Single-minded homolog 2 as a potential prognostic signature and assessment of its correlation with immune cell infiltration in pancreatic cancer.

Single-minded homolog 2 (SIM2) has been identified as a potential contributor to the development of solid tumors. Despite this, there is a lack of comprehensive research regarding its biological role and underlying mechanism within pancreatic cancer (PC), as well as its prognostic impact. This study systematically evaluated the expression level and clinical significance of SIM2 in patients with PC using various databases, including The Cancer Genome Atlas, KM Plotter, and gene expression profiling interactive analysis. To investigate the relationship between SIM2 expression and immune cell infiltration, we conducted ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) analyses. Single-minded homolog 2 was up-regulated in patients with PC. Pancreatic cancer patients with higher SIM2 expression had poorer overall survival rates. Gene set enrichment analysis results suggested that SIM2 may have a significant impact on the progression of PC and the regulation of immune responses. According to the ssGSEA algorithm, SIM2 has a negative correlation with the levels of infiltrating TFH, mast cells, and pDC. Our study demonstrated that SIM2 serves as a biomarker, and is associated with both prognosis and immune infiltration in PC. This provides a solid foundation for future investigations into the precise role of SIM2 in the carcinogenesis and progression of PC.

Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration.

Resolving regional carbon budgets is critical for informing land-based mitigation policy. For nine regions covering nearly the whole globe, we collected inventory estimates of carbon-stock changes complemented by satellite estimates of biomass changes where inventory data are missing. The net land-atmospheric carbon exchange (NEE) was calculated by taking the sum of the carbon-stock change and lateral carbon fluxes from crop and wood trade, and riverine-carbon export to the ocean. Summing up NEE from all regions, we obtained a global 'bottom-up' NEE for net land anthropogenic CO2 uptake of -2.2 ± 0.6 PgC yr-1 consistent with the independent top-down NEE from the global atmospheric carbon budget during 2000-2009. This estimate is so far the most comprehensive global bottom-up carbon budget accounting, which set up an important milestone for global carbon-cycle studies. By decomposing NEE into component fluxes, we found that global soil heterotrophic respiration amounts to a source of CO2 of 39 PgC yr-1 with an interquartile of 33-46 PgC yr-1-a much smaller portion of net primary productivity than previously reported.

Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction.

In this study, we use simulations from seven global vegetation models to provide the first multi-model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001-2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire-induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state-of-the-art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.

The local projection in the density functional theory plus U approach: A critical assessment.

Density-functional theory plus the Hubbard U correction (DFT + U) method is widely used in first-principles studies of strongly correlated systems, as it can give qualitatively (and sometimes, semi-quantitatively) correct description of energetic and structural properties of many strongly correlated systems with similar computational cost as local density approximation or generalized gradient approximation. On the other hand, the DFT + U approach is limited both theoretically and practically in several important aspects. In particular, the results of DFT + U often depend on the choice of local orbitals (the local projection) defining the subspace in which the Hubbard U correction is applied. In this work we have systematically investigated the issue of the local projection by considering typical transition metal oxides, ß-MnO2 and MnO, and comparing the results obtained from different implementations of DFT + U. We found that the choice of the local projection has significant effects on the DFT + U results, which are more significant for systems with stronger covalent bonding (e.g., MnO2) than those with more ionic bonding (e.g., MnO). These findings can help to clarify some confusion arising from the practical use of DFT + U and may also provide insights for the development of new first-principles approaches beyond DFT + U.