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.

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.