Identification of agricultural surface source pollution in plain river network areas based on 3D-EEMs and convolutional neural networks.

Agricultural non-point sources, as major sources of organic pollution, continue to flow into the river network area of the Jiangnan Plain, posing a serious threat to the quality of water bodies, the ecological environment, and human health. Therefore, there is an urgent need for a method that can accurately identify various types of agricultural organic pollution to prevent the water ecosystems in the region from significant organic pollution. In this study, a network model called RA-GoogLeNet is proposed for accurately identifying agricultural organic pollution in the river network area of the Jiangnan Plain. RA-GoogLeNet uses fluorescence spectral data of agricultural non-point source water quality in Changzhou Changdang Lake Basin, based on GoogLeNet architecture, and adds an efficient channel attention (ECA) mechanism to its A-Inception module, which enables the model to automatically learn the importance of independent channel features. ResNet are used to connect each A-Reception module. The experimental results show that RA-GoogLeNet performs well in fluorescence spectral classification of water quality, with an accuracy of 96.3%, which is 1.2% higher than the baseline model, and has good recall and F1 score. This study provides powerful technical support for the traceability of agricultural organic pollution.

Model evaluation of total phosphorus prediction based on model accuracy and interpretability for the surface water in the river network of the Jiangnan Plain, China.

Due to climatic and hydrological changes and human activities, eutrophication and frequent outbreaks of cyanobacteria are prominent in the Jiangnan Plain basin of China. Therefore, building a suitable model to accurately predict the phosphorus concentration in surface water is of practical significance to prevent the above problems. This study built 10 models to predict the phosphorus element in the surface water of the river network in the Jiangnan Plain. The main water types in the basin include the Yangtze River, the Beijing-Hangzhou Canal, and the Gehu Lake. The 10 models in different datasets have been comprehensively evaluated by the prediction accuracy and interpretability of the model, and the calculation of the partial dependence diagram (PDP) and SHAP has proved that there is a transparent response relationship between phosphorus and different factors. The results show that the Yangtze River, Beijing-Hangzhou Canal, and Gehu Lake are suitable for random forest, linear regression, and random forest models, respectively, under the comprehensive evaluation of the prediction accuracy and interpretability of the model. Models with low prediction accuracy often show strong interpretability. In different water body types, turbidity, water temperature, and chlorophyll-a are the three factors that affect the model in predicting phosphorus.

[Study on GLI values of Polygonatum odoratum base on multi-temporal of unmanned aerial vehicle remote sensing].

Unmanned aerial vehicle(UAV) remote sensing and vegetation index have great potential in the field of Chinese herbal medicine planting. In this study, the visible light image of Polygonatum odoratum planting area in Changyi district of Jilin province were acquired by UAV, and the real-time monitoring of P. odoratum planting area was realized. The green leaf index(GLI) was established, and GLI values of P. odoratum were collected used the spatial sampling points. To compare the GLI values in different periods, it was found that the GLI values of P. odoratum have three stages changing rule of rising-gentle-falling related to the germination, vigorous growth and withered of P. odoratum growth. Meanwhile, the GLI values were compared with four biomass data of P. odoratum, including plant height, leaf area, chlorophyll a and chlorophyll b content in leaves, and it was found that the GLI value was related to the growth potential of P. odoratum. The GLI value with a rapid increase in rising stage or at a high level in the gentle stage means the P. odoratum was in a better growth potential. GLI value has a same change trend with plant height, and has certain correlation with plant height and leaf area. However, there is no obvious relationship between chlorophyll a and chlorophyll b contents in leaves and GLI value. The study clarified the change rule of GLI value of P. odoratum, explained the reason for the change of GLI value, and expanded the application range of GLI. The research shows that UAV and vegetation index can be applied to monitoring the Chinese herbal medicines planting, and provides a new idea for exploring more effective information extraction methods of Chinese herbal medicines.

Abscisic acid ameliorates d-galactose -induced aging in mice by modulating AMPK-SIRT1-p53 pathway and intestinal flora.

Abscisic acid (ABA) is a plant hormone with various biological activities. Aging is a natural process accompanied by cognitive and physiological decline, and aging and its associated diseases pose a serious threat to public health, but its mechanisms remain insufficient. Therefore, the purpose of this study was to investigate the ameliorative effects of ABA on d-galactose (D-Gal)-induced aging in mice and to delve into its molecular mechanisms. Aging model was es-tablished by theintraperitoneal injection of D-Gal. We evaluated the oxidative stress by measuring superoxide dismutase (SOD), malondialdehyde (MDA), catalase (CAT) levels in serum. Proteins content in brain were determined by Western blot. D-Gal-induced brain damage was monitored by measuring the levels of acetylcholinesterase (AChE) content and hematoxylin-eosin staining (H&E). To evaluate the effects of ABA on aging, we measured the gut microbiota. The results demonstrated that ABA increased SOD, CAT and AChE, decreased MDA level. H&E staining showed that ABA could improve D-Gal-induced damage. In addition, ABA regulated the B-cell-lymphoma-2 (BCL-2) family and Phosphatidylinositol 3-kinase/Protein kinase B (PI3K/AKT) signaling pathway, while further regulating the acetylation of p53 protein by modulating the AMPK pathway and activating SIRT1 protein, thereby inhibiting the apoptosis of brain neurons and thus regulating the aging process. Interestingly, ABA improved the ratio of intestinal bacteria involved in regulating multiple metabolic pathways in the aging process, such as Bacteroides, Firmicutes, Lactobacillus and Ak-kermansia. In conclusion, the present study suggests that ABA may be responsible for improving and delaying the aging process by enhancing antioxidant activity, anti-apoptosis and regulating intestinal flora.

Dihydroquercetin composite nanofibrous membrane prevents UVA radiation-mediated inflammation, apoptosis and oxidative stress by modulating MAPKs/Nrf2 signaling in human epidermal keratinocytes.

Exposure to ultraviolet (UV) radiation is a key cause of skin inflammation and photodamage in the environment. Dihydroquercetin composite nanofiber membrane (CPD) is a nano-scale membrane cloth prepared by electrospinning technology. The results in this study showed that CPD could enhance the activities of endogenous antioxidant enzymes such as SOD and GSH-Px induced by UVA radiation, and reduce the overexpression of ROS. MAPKs/Nrf2 signaling is associated with inflammation, apoptosis and oxidative stress. Compared with control HaCaT cells, we found that CPD pretreatment prevents MAPK (p-ERK, p-JNK, and p-P38)/Nrf2-induced inflammation, apoptosis, and oxidative stress signaling during UVA exposure pathway overexpression. Immunofluorescence experiments also showed that CPD could reduce the fluorescence intensity of Caspase-3 and TNF-α. These results suggest that CPD may be a successful healing agent that provides reinforcement against UVA-induced oxidative and irritating skin compensation.

Research on rat's pulmonary acute injury induced by lunar soil simulant.

BACKGROUND: The steps to the moon never stopped after the Apollo Project. Lessons from manned landings on the moon have shown that lunar dust has great influence on the health of astronauts. In this paper, comparative studies between the lunar soil simulant (LSS) and PM2.5 were performed to discover their harm to human biological systems and explore the methods of prevention and treatment of dust poisoning for future lunar manned landings. METHODS: Rats were randomly divided into the control group, two CAS-1 lunar soil simulant groups (tracheal perfusion with 7 mg and 0.7 mg, respectively, in a 1-mL volume) and the PM2.5 group (tracheal perfusion with 0.7 mg in a 1-mL volume). The biochemical indicators in the bronchoalveolar lavage fluid (BALF), MPO activity in the lung tissue, pathologic changes, and inflammatory cells in the BALF were measured after 4 h and 24 h. RESULTS: The LSS group showed cytotoxicity that was closely related to the concentration. The figures of the two LSS groups (4 and 24 h) show that the alveolar septa were thickened. Additionally, it was observed that neutrophils had infiltrated, and various levels of inflammation occurred around the vascular and bronchial structures. CONCLUSION: The overall results of the acute effects of the lungs caused by dust showed that the lung toxicity of LSS was greater than that of PM2.5. LSS could induce lung damage and inflammatory lesions. The biomarkers in BALF caused by acute injury were consistent with histopathologic observations.