Detecting Sulfuric and Nitric Acid Rain Stresses on Quercus glauca through Hyperspectral Responses

Acid rain, which has become one of the most severe global environmental issues, is detrimental to plant growth. However, effective methods for monitoring plant responses to acid rain stress are currently lacking. The hyperspectral technique provides a cost-effective and nondestructive way to diagnose acid rain stresses. Taking a widely distributed species (Quercus glauca) in Southern China as an example, this study aims to monitor the hyperspectral responses of Q. glauca to simulated sulfuric acid rain (SAR) and nitric acid rain (NAR). A total of 15 periods of leaf hyperspectral data under four pH levels of SAR and NAR were obtained during the experiment. The results showed that hyperspectral information could be used to distinguish plant responses under acid rain stress. An index (green peak area index, GPAI) was proposed to indicate acid rain stresses, based on the significantly variations in the region of 500–660 nm. Light acid rain (pH 4.5 SAR and NAR) promoted Q. glauca growth relative to the control groups (pH 5.6 SAR and NAR); moderate acid rain (pH 3.0 SAR) firstly promoted and then inhibited plant growth, while pH 3.0 NAR showed mild inhibitory effects during the experiment; and heavy acid rain (pH 2.0) significantly inhibited plant growth. Compared with NAR, SAR induced more serious damages to Q. glauca. These results could help monitor acid rain stress on plants on a regional scale using remote sensing techniques

(−)-Epigallocatechin gallate alleviates chronic unpredictable mild stress-induced depressive symptoms in mice by regulating the mTOR autophagy pathway and inhibiting NLRP3 inflammasome activation

Depression is a global public health issue that is widely studied due to the large number of people it affects and its serious consequences. Clinical studies have shown that regular tea consumption may reduce depression risk. (−)-Epigallocatechin gallate (EGCG), the main tea polyphenol, was observed to alleviate depression, but the underlying mechanism has not been elucidated. In this study, chronic unpredictable mild stress (CUMS) was used to induce depression-like behavior in mice, and behavioral tests, such as sucrose preference test and forced swim test, were performed. Then, ELISA, western blot and QT-PCR tests were used to assess the expression of the key components of the NLRP3 inflammasome and its downstream inflammatory effectors (e.g., IL-1β, IL-18), autophagy markers (Beclin-1, LC3, P62) and apoptosis markers (Bax, Bcl-2) in mouse brain tissues. Changes in serum lipid levels were also assessed. EGCG alleviated CUMS-induced depression-like behavioral changes in mice, reduced activation of the NLRP3 inflammasome, inhibited the mTOR signaling pathway, restored autophagy levels, reduced apoptosis marker expression and attenuated abnormal changes in blood lipid levels. Our study demonstrates that EGCG exerts antidepressive effects through multiple mechanisms, providing new insight into the pathological mechanism of depression and laying the foundation for the development of new therapeutic measures

Addendum: Using Satellite Data for the Characterization of Local Animal Reservoir Populations of Hantaan Virus on the Weihe Plain, China. Remote Sens. 2017, 9, 1076

After publication of the research paper[...

Using Satellite Data for the Characterization of Local Animal Reservoir Populations of Hantaan Virus on the Weihe Plain, China

Striped field mice (Apodemus agrarius) are the main host for the Hantaan virus (HTNV), the cause of hemorrhagic fever with renal syndrome (HFRS) in central China. It has been shown that host population density is associated with pathogen dynamics and disease risk. Thus, a higher population density of A. agrarius in an area might indicate a higher risk for an HFRS outbreak. Here, we surveyed the A. agrarius population density between 2005 and 2012 on the Weihe Plain, Shaanxi Province, China, and used this monitoring data to examine the relationships between the dynamics of A. agrarius populations and environmental conditions of crop-land, represented by remote sensing based indicators. These included the normalized difference vegetation index, leaf area index, fraction of photosynthetically active radiation absorbed by vegetation, net photosynthesis (PsnNet), gross primary productivity, and land surface temperature. Structural equation modeling (SEM) was applied to detect the possible causal relationship between PsnNet, A. agrarius population density and HFRS risk. The results showed that A. agrarius was the most frequently captured species with a capture rate of 0.9 individuals per hundred trap-nights, during 96 months of trapping in the study area. The risk of HFRS was highly associated with the abundance of A. agrarius, with a 1–5-month lag. The breeding season of A. agrarius was also found to coincide with agricultural activity and seasons with high PsnNet. The SEM indicated that PsnNet had an indirect positive effect on HFRS incidence via rodents. In conclusion, the remote sensing-based environmental indicator, PsnNet, was highly correlated with HTNV reservoir population dynamics with a 3-month lag (r = 0.46, p < 0.01), and may serve as a predictor of potential HFRS outbreaks