Predicting Quercus gilva distribution dynamics and its response to climate change induced by GHGs emission through MaxEnt modeling.

Quercus gilva, an evergreen tree species in Quercus section Cyclobalanopsis, is an ecologically and economically valuable species in subtropical regions of East Asia. Predicting the impact of climate change on potential distribution of Q. gilva can provide a scientific basis for the conservation and utilization of its genetic resources, as well as for afforestation. In this study, 74 distribution records of Q. gilva and nine climate variables were obtained after data collection and processing. Current climate data downloaded from WorldClim and future climate data predicted by four future climate scenarios (2040s SSP1-2.6, 2040s SSP5-8.5, 2060s SSP1-2.6, and 2060s SSP5-8.5) mainly based on greenhouse gases emissions of distribution sites were used in MaxEnt model with optimized parameters to predict distribution dynamics of Q. gilva and its response to climate change. The results showed that the predicted current distribution was consistent with natural distribution of Q. gilva, which was mainly located in Hunan, Jiangxi, Zhejiang, Fujian, Guizhou, and Taiwan provinces of China, as well as Japan and Jeju Island of South Korea. Under current climate conditions, precipitation factors played a more significant role than temperature factors on distribution of Q. gilva, and precipitation of driest quarter (BIO17) is the most important restriction factor for its current distribution (contribution rate of 57.35%). Under future climate conditions, mean temperature of driest quarter (BIO9) was the essential climate factor affecting future change in potential distribution of Q. gilva. As the degree of climatic anomaly increased in the future, the total area of predicted distribution of Q. gilva showed a shrinking trend (decreased by 12.24%-45.21%) and Q. gilva would migrate to high altitudes and latitudes. The research results illustrated potential distribution range and suitable climate conditions of Q. gilva, which can provide essential theoretical references for the conservation, development, and utilization of Q. gilva and other related species.

Intermediate irrigation with low fertilization promotes soil nutrient cycling and reduces CO2 and CH4 emissions via regulating fungal communities in arid agroecosystems.

The field practices, including irrigation and fertilization, strongly affect greenhouse gas emissions and soil nutrient cycling from agriculture. Understanding the underlying mechanism of greenhouse gas emissions, soil nutrient cycling, and their impact factors (fungal diversity, network characteristics, soil pH, salt, and moisture) is essential for efficiently managing global greenhouse gas mitigation and agricultural production. By considering abundant and rare taxa, we determine the identities and relative importance of ecological processes that modulate the fungal communities and identify whether they are crucial contributors to soil nutrient cycling and greenhouse gas emissions. The research is based on a 4-year field fertigation experiment with low (300 kg/ha P2O5 with 150 kg/ha urea) and high (600 kg/ha P2O5 with 300 kg/ha urea) fertilization level and three irrigation levels, that is, low (200 mm), medium (300 mm), and high (400 mm). The α-diversity (richness and Shannon index) of fungal subcommunities was significantly higher under medium irrigation (300 mm) and low fertilization (300 kg/ha P2O5 with 150 kg/ha urea) than under other treatments. Intermediate irrigation with low fertilization treatment yielded the most significant higher multinutrient cycling index and the lowest CO2 and CH4 emissions. The null model indicated that abundant taxa are mainly regulated by stochastic processes (dispersal limitation), and rare taxa are mainly regulated by environmental selection, especially by soil salinity. The co-occurrence network of rare taxa explained the changes in the entire fungal network stability. The abundant taxa played vital roles in regulating soil nutrient status, owing to the stronger association between their network and multinutrient cycling index. Furthermore, we have confirmed that soil moisture and fungal network stability are crucial factors affecting greenhouse gas emissions. Together, these results provide a deep understanding of the mechanisms that reveal fungal community assembly and soil fungal-driven variations in nutrient status and network stability, link fungal network characteristics to ecosystem functions, and reveal the factors that influence greenhouse gas emissions.

Arecoline induces epithelial-mesenchymal transformation and promotes metastasis of oral cancer by SAA1 expression.

Arecoline, the main alkaloid of areca nut, is well known for its role in inducing submucosal fibrosis and oral squamous cell carcinoma (OSCC), however the mechanism remains unclear. The aim of this study was to establish an arecoline-induced epithelial-mesenchymal transformation (EMT) model of OSCC cells and to investigate the underlying mechanisms. CAL33 and UM2 cells were induced with arecoline to establish an EMT cell model and perform RNA-sequence screening. Luminex multiplex cytokine assays, western blot, and RT-qPCR were used to investigate the EMT mechanism. Arecoline at a concentration of 160 µg/ml was used to induce EMT in OSCC cells, which was confirmed using morphological analysis, transwell assays, and EMT marker detection. RNA-sequence screening and Luminex multiplex cytokine assays showed that many inflammatory cytokines (such as serum amyloid A1 [SAA1], interleukin [IL]-6, IL-36G, chemokine [CCL]2, and CCL20) were significantly altered during arecoline-induced EMT. Of these cytokines, SAA1 was the most highly upregulated. SAA1 overexpression induced EMT and promoted the migration and invasion of CAL33 cells, while SAA1 knockdown attenuated arecoline-induced EMT. Moreover, arecoline enhanced cervical lymph node metastasis in an orthotopic xenograft model of the tongue established using BALB/c nude mice. Our findings revealed that arecoline induced EMT and enhanced the metastatic capability of OSCC by the regulation of inflammatory cytokine secretion, especially that of SAA1. Our study provides a basis for understanding the mechanism of OSCC metastasis and suggests possible therapeutic targets to prevent the occurrence and development of OSCC associated with areca nut chewing.