MicroRNA-181a Functions as an Oncogene in Gastric Cancer by Targeting Caprin-1

MicroRNA-181a (miRNA-181a) is a multifaceted miRNA implicated in various cellular processes, particularly in cell fate determination and cellular invasion. It is frequently expressed aberrantly in human tumors and shows opposing functions in different types of cancers. In this study, we found that miRNA-181a is overexpressed in Gastric cancer (GC) tissues. Clinical and pathological analyses revealed that the expression of miRNA-181a is correlated with tumor size, lymph node metastasis, distant metastasis, and TNM stage. Kaplan-Meier analysis indicated that overexpression of miRNA-181a is associated with poor overall survival of patients with GC. Moreover, miRNA-181a is overexpressed in GC cells, and downregulation of miRNA-181a induced cell apoptosis and suppressed the proliferation, invasion, and metastasis of GC cells both in vitro and in vivo. Target prediction and luciferase reporter assay showed that caprin-1 was a direct target of miRNA-181a. Downregulation of caprin-1 expression resulted in a converse change with miRNA-181a in GC. Spearman’s correlation test confirmed that the expression of miRNA-181a expression was inversely correlated with that of caprin-1 in GC cells. Furthermore, the expression of caprin-1 increased after downregulation of miRNA-181a in the GC cells. Caprin-1 siRNA can rescue the oncogenic effect of miRNA-181a on GC cell proliferation, apoptosis, migration, and invasion. These findings suggest that miRNA-181a directly inhibits caprin-1 and promotes GC development. miRNA-181a could be a target for anticancer drug development

Carbon Neutrality in Shanxi Province: Scenario Simulation Based on LEAP and CA-Markov Models

In the context of global climate governance and China’s carbon neutrality target, Shanxi Province, one of China’s major energy exporting regions, is under high pressure to achieve carbon neutrality. This paper sets up three carbon source scenarios and three carbon sink scenarios based on the Long-range Energy Alternatives Planning System (LEAP) and CA-Markov models to simulate the future change in carbon source and carbon sink of Shanxi from 2020 to 2060; it analyzes the achievement of the carbon peaking and carbon neutrality targets for each source–sink scenario. The results show that: (1) The total energy consumption and CO2 emissions have increased significantly, from 2000 to 2020, especially in heavy industry; (2) The CO2 emissions are predicted to peak at 381.6 Mt, 294.1 Mt and 282.7 Mt in 2040 (baseline scenario), 2030 (policy scenario), and 2025 (carbon neutrality scenario), respectively. The achievement of the carbon neutrality mainly depends on the reduction in CO2 emissions; (3) If Shanxi Province strives to reach the energy intensity of developed countries by 2060, with 80% of non-fossil energy generation, it has the potential to achieve the carbon neutrality target; (4) The popularization of carbon capture, utilization and storage (CCUS) technology will significantly accelerate the achievement of Shanxi Province’s carbon neutrality target

Balancing Water Ecosystem Services: Assessing Water Yield and Purification in Shanxi

Water yield and purification are important aspects of water ecosystem services, and achieving a balanced development of the two is necessary for the development of aquatic ecosystems. Using the InVEST model, the spatiotemporal variations of regional water yield and purification services in Shanxi, China, from 2000 to 2020 were analyzed. Three future scenarios (natural development, urban development, and ecological protection) were assessed for 2030 using the PLUS model. The results showed that in 2000–2020, the water yield of Shanxi Province in terms of space was generally low in the middle and northwest and high in the southeast, and it was affected by land-use change and climatic change. From 2000 to 2020, the water yield of Shanxi Province changed by 78.8 mm. In 2030, water yield will be highest under the urban development scenario (380.53 mm) and lowest in the ecological protection scenario (368.22 mm). Moreover, the water quality purification capacity improved, with nitrogen loading high in the center and low in the east and west. Due to the implementation of environmental protection policies and the improvement of the technical level, the nitrogen load was the highest in 2000 (0.97 kg/hm2) and lowest in 2015 (0.94 kg/hm2). By 2030, because of the high nitrogen loadings of cultivation and construction land and low nitrogen loadings of forests and grasslands, the nitrogen load was lowest under the scenario of urban development (0.94 kg/hm2) and highest under ecological protection (0.85 kg/hm2)

Analysis and prediction of crop water footprints in the Fen River Basin of Shanxi Province, China

In China, the major water user is agriculture. Under the background of climate change and with the pressure of scarce water resources, the study of crop water footprints serves as a theoretical basis for regional optimization of water resource management, fine-tuning crop planting structures and actively addressing the negative impacts of climate change on agricultural production, among other critical issues. Leveraging meteorological and agricultural data, we employed Taiyuan which is situated in Fen River Basin as our focal research subject and calculated and analyzed the water footprint variations concerning six major food crops—wheat, corn, grain, sorghum, soybean, and potato—from 2000 to 2020. Through meticulous examination, we identified the predominant contribution of blue water (45 %) to the total water footprint, followed by green water (39 %), with grey water playing the smallest role (16 %), indicating that the use of water for crops in the Fen River Basin mainly consumes surface water and groundwater. Our investigation reveals a complementary association between blue water and green water, while both blue water and grey water exhibit an overall declining tendency from 2000 to 2020. Moreover, our predictive modeling of food crop water footprints, considering various SSPs-RCPs scenarios refered from IPCC, points towards a peak within the coming 10–20 years, with a growth rate of 16.2 % to 33.0 %, followed by a subsequent decline. Particularly, in SSP3-7.0 scenario, the water footprint of food crops presents the highest, with a growth rate of up to 33.0 % because of the continuous growth of population and the increase of crop sowing area, while in SSP1-2.6 scenario, the water footprint of food crops shows the lowest, with a growth rate of 16.2 % because of the decrease in population and crop sowing area, before the middle of the current century

Predicting the impact of climate change on crop water footprint using CMIP6 in the Shule River Basin, China

Abstract Quantitatively predicting the impacts of climate change on water demands of various crops is essential for developing measures to ensure food security, sustainable agriculture, and water resources management, especially in arid regions. This study explored the water footprints (WFs) of nine major crops in the middle and downstream areas of Shule River Basin, Northwest China, from 1989 to 2020 using the WF theory and CROPWAT model and predicted the future WFs of these crops under four emission and socio-economic pathway (SSPs-RCPs) scenarios, which provides scientific support for actively responding to the negative impacts of climate change in arid regions. Results indicated: (1) an increasing trend of the overall crop WF, with blue WF accounting for 80.31–99.33% of the total WF in the last 30 years. Owing to differences of planting structure, water-conservation technologies, and other factors, the multi-year average WF per unit area of crops was 0.75 × 104 m3 hm−2 in downstream area, which was higher than that in midstream area (0.57 × 104 m3 hm−2) in the last 30 years; therefore agricultural water use efficiency in the downstream area was lower than that in the midstream area, implying that the midstream area has more efficient agricultural water utilization. (2) an initial increase and then decrease of crop WFs in the study area under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios by the end of the century, reaching their peak in 2030s which was higher than that from 1989 to 2020; with the maximum growth rates in the midstream area ranging from −0.85% in SSP5-8.5 to 5.33% in SSP2-4.5 and 29.74% in SSP5-8.5 to 34.71% in SSP2-4.5 in the downstream area. The local agricultural water demand would continue to increase and water scarcity issues would be more severe in the next 10–20 years, affecting downstream areas more. Under the SSP3-7.0 scenario, crop WF values of the midstream and downstream regions will be 2.63 × 108 m3 and 4.22 × 108 m3 in 2030, respectively, which is significantly higher than those of other scenarios and show a long-term growth trend. The growth rate of the midstream and downstream regions will reach 44.71% and 81.12%, respectively, by the end of this century, so the local agricultural water use would be facing more strain if this scenario materializes in the future. Therefore, the Shule River Basin should encourage development of water-saving irrigation technologies, adjust the planting ratio of high water consuming crops, and identify other measures to improve water resource utilization efficiency to cope with future water resource pressures

The Oral Microbiome Impacts the Link between Sugar Consumption and Caries: A Preliminary Study

Background: The excessive and frequent intake of refined sugar leads to caries. However, the relationship between the amount of sugar intake and the risk of caries is not always consistent. Oral microbial profile and function may impact the link between them. This study aims to identify the plaque microbiota characteristics of caries subjects with low (CL) and high (CH) sugar consumption, and of caries-free subjects with low (FL) and high sugar (FH) consumption. Methods: A total of 40 adolescents were enrolled in the study, and supragingival plaque samples were collected and subjected to metagenomic analyses. The caries status, sugar consumption, and oral-health behaviors of the subjects were recorded. Results: The results indicate that the CL group showed a higher abundance of several cariogenic microorganisms Lactobacillus, A. gerencseriae, A. dentails, S. mutans, C. albicans, S. wiggsiae and P. acidifaciens. C. gingivalis, and P. gingivalis, which were enriched in the FH group. In terms of gene function, the phosphotransferase sugar uptake system, phosphotransferase system, and several two-component responses–regulator pairs were enriched in the CL group. Conclusion: Overall, our data suggest the existence of an increased cariogenic microbial community and sugar catabolism potential in the CL group, and a healthy microbial community in the FH group, which had self-stabilizing functional potential

Spatio-Temporal Variation of Precipitation in the Qinling Mountains from 1970 to 2100 Based on CMIP6 Data

Estimating future precipitation changes in the Qinling Mountains has significance, for understanding how to reveal the basic characteristics of the atmospheric water cycle in mountainous areas under the action of monsoons and the temporal- and spatial-variation mechanism of water resources in the ‘central water tower’, under the background of climate change. Based on four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) of the CMIP6 model, the Taylor diagram method was used to select the best regional simulation model, according to historical observation data (1970–2014). On this basis, the precipitation change and circulation background of the Qinling Mountains over the next 86 years (2015–2100) were analyzed. The results show that the simulation effect of the optimal mode is better than that of the single mode. Under the four scenarios, the variation trends of the annual precipitation in the Qinling Mountains from 2015 to 2100 were 4.4 mm/10a, 18.5 mm/10a, 18.1 mm/10a, and 19.1 mm/10a, respectively. By the middle of this century (2041–2060), compared with the reference period of 1995–2014, the average annual precipitation in the Qinling Mountains under the four scenarios will increase by 64.1 mm, 7 mm, 28.8 mm, and −51 mm, respectively. By the end of this century (2081–2100), the average annual precipitation under the four scenarios will increase by 29.5 mm, 77.2 mm, 82.9 mm, and 21.2 mm, respectively. The abnormal increase (decrease) of water vapor, transported northward from the western Pacific and the Bay of Bengal, is the main reason for the abnormal increase (decrease) of precipitation in the flood season in the Qinling Mountains. With the increase in emission scenarios, the influence of the South Asian summer monsoon on precipitation in the Qinling Mountains becomes more significant

Spatio-Temporal Variation of Precipitation in the Qinling Mountains from 1970 to 2100 Based on CMIP6 Data

Estimating future precipitation changes in the Qinling Mountains has significance, for understanding how to reveal the basic characteristics of the atmospheric water cycle in mountainous areas under the action of monsoons and the temporal- and spatial-variation mechanism of water resources in the ‘central water tower’, under the background of climate change. Based on four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) of the CMIP6 model, the Taylor diagram method was used to select the best regional simulation model, according to historical observation data (1970–2014). On this basis, the precipitation change and circulation background of the Qinling Mountains over the next 86 years (2015–2100) were analyzed. The results show that the simulation effect of the optimal mode is better than that of the single mode. Under the four scenarios, the variation trends of the annual precipitation in the Qinling Mountains from 2015 to 2100 were 4.4 mm/10a, 18.5 mm/10a, 18.1 mm/10a, and 19.1 mm/10a, respectively. By the middle of this century (2041–2060), compared with the reference period of 1995–2014, the average annual precipitation in the Qinling Mountains under the four scenarios will increase by 64.1 mm, 7 mm, 28.8 mm, and −51 mm, respectively. By the end of this century (2081–2100), the average annual precipitation under the four scenarios will increase by 29.5 mm, 77.2 mm, 82.9 mm, and 21.2 mm, respectively. The abnormal increase (decrease) of water vapor, transported northward from the western Pacific and the Bay of Bengal, is the main reason for the abnormal increase (decrease) of precipitation in the flood season in the Qinling Mountains. With the increase in emission scenarios, the influence of the South Asian summer monsoon on precipitation in the Qinling Mountains becomes more significant