Synergies quantification and evolution on air pollutant and CO2 emissions driven by different socio-economic effects.

Realizing a synergistic reduction of air pollutant and CO2 emissions (APCE) is an important approach to promote a green socio-economic transformation in China, and it can provide a solid foundation for the achievement of clean energy production and climate action under a sustainable development goal framework. The objective of this study is to explore the quantitative relationship and evolution of synergies between APCE in industrial sectors driven by different socio-economic effects from 2007 to 2020 in China. The results indicated that the main sectors of pollutant emissions had consistency, however, large differences in the reduction efficiency of emissions exist among pollutants. The efficiency in reducing CO2 emissions was about 48% lower when compared with reductions of SO2 (95%), NOx (86%), and smoke and dust (83%) emissions from 2007 to 2020. The effects of improved technology were the main contributor to a reduction in pollutant emissions, but the synergies between APCE driving by it were not achieved. While the synergies between APCE driven by structure and final demand effects were significant. The synergies between NOx and CO2 emissions were stronger driven by final demand structure and type effects, with correlation coefficients of 1.06 and 1.13, respectively. Besides, the degree of synergistic reduction between APCE in most industrial sectors was around zero. Therefore, the efficiency of synergistic pollution reduction should be improved with the development of a synergistic governance system for industrial sectors. The structural decomposition analysis based on input-output model combined with the cross-elasticity analysis method to quantitively synergies between APCE from the consumption (demand) perspective, considering the connections between industrial sectors with socio-economic developing, which would contribute to the industrial synergistic reduction and green transformation as the consumption driven gradually increasing.

Spatial multiomics reveals a subpopulation of fibroblasts associated with cancer stemness in human hepatocellular carcinoma.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are the prominent cell type in the tumor microenvironment (TME), and CAF subsets have been identified in various tumors. However, how CAFs spatially coordinate other cell populations within the liver TME to promote cancer progression remains unclear. METHODS: We combined multi-region proteomics (6 patients, 24 samples), 10X Genomics Visium spatial transcriptomics (11 patients, 25 samples), and multiplexed imaging (92 patients, 264 samples) technologies to decipher the expression heterogeneity, functional diversity, spatial distribution, colocalization, and interaction of fibroblasts. The newly identified CAF subpopulation was validated by cells isolated from 5 liver cancer patients and in vitro functional assays. RESULTS: We identified a liver CAF subpopulation, marked by the expression of COL1A2, COL4A1, COL4A2, CTGF, and FSTL1, and named F5-CAF. F5-CAF is preferentially located within and around tumor nests and colocalizes with cancer cells with higher stemness in hepatocellular carcinoma (HCC). Multiplexed staining of 92 patients and the bulk transcriptome of 371 patients demonstrated that the abundance of F5-CAFs in HCC was associated with a worse prognosis. Further in vitro experiments showed that F5-CAFs isolated from liver cancer patients can promote the proliferation and stemness of HCC cells. CONCLUSIONS: We identified a CAF subpopulation F5-CAF in liver cancer, which is associated with cancer stemness and unfavorable prognosis. Our results provide potential mechanisms by which the CAF subset in the TME promotes the development of liver cancer by supporting the survival of cancer stem cells.

Single-cell and spatially resolved transcriptomics for liver biology.

Single-cell transcriptomics enables the identification of rare cell types and the inference of state transitions, whereas spatially resolved transcriptomics allows the quantification of cells and genes in the context of tissues. The recent progress in these new technologies is improving our understanding of the cell landscape and its roles in diseases. Here, we review key biological insights into liver homeostasis, development, regeneration, chronic liver disease, and cancer obtained from single-cell and spatially resolved transcriptomics. We highlight recent progress in the liver cell atlas that characterizes the comprehensive cellular composition; diversity and function; the spatial architecture such as liver zonation, cell communication, and proximity; the cell identity conversion and cell-specific alterations that are associated with liver pathology; and new therapeutic targets. We further discuss outstanding challenges, advanced experimental technologies, and computational methods that help to address these challenges.

Localization, purification, and characterization of a novel ß-glucosidase from Hanseniaspora uvarum Yun268.

ß-Glucosidase is a key enzyme that hydrolyzes nonvolatile glycosylated precursors of aroma compounds and enhances the organoleptic quality of wines. In this study, a novel ß-glucosidase from Hanseniaspora uvarum Yun268 was localized, purified, and characterized. Results indicated that ß-glucosidase activity was mainly distributed within the cells. After purification via ammonium sulfate precipitation combined with chromatography, ß-glucosidase specific activity increased 8.36 times, and the activity recovery was 56.90%. The enzyme had a molecular mass of 74.22 kDa. It has a Michaelis constant (Km ) of 0.65 mmol/L, and a maximum velocity (Vmax ) of 5.1 nmol/min under optimum conditions; and Km of 0.94 mmol/L, and Vmax of 2.8 nmol/min under typical winemaking conditions. It exhibited the highest activity at 50°C and pH 5.0 and was stable at a temperature range of 20-80°C and pH range of 3.0-8.0. The enzyme has good tolerance to Fe3+ , especially maintaining 93.68% of its activity with 10 mmol/L of Fe3+ . Ethanol (<20%) and glucose (<150 g/L) inhibited its activity only slightly. Therefore, ß-glucosidase from H. uvarum Yun268 has excellent biochemical properties and a good application potential in winemaking. PRACTICAL APPLICATION: Winemaking is a biotechnological process in which exogenous ß-glucosidase is used to overcome the deficiency of endogenous ß-glucosidase activity in grapes. By localizing, purifying, and characterizing of ß-glucosidase from Hanseniaspora uvarum Yun268, it is expected to reveal its physical and chemical characteristics to evaluate its oenological properties in winemaking. The results may provide the basis for promoting the release of varietal aroma and improving wine sensory quality in the wine industry.