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Conventional supervised and unsupervised machine learning models used for landslide susceptibility prediction (LSP) have many drawbacks, such as an insufficient number of recorded landslide samples, and the subjective and random selection of non-landslide samples. To overcome these drawbacks, a semi-supervised multiple-layer perceptron (SSMLP) is innovatively proposed with several processes: (1) an initial landslide susceptibility map (LSM) is produced using the multiple-layer perceptron (MLP) based on the original recorded landslide samples and related environmental factors; (2) the initial LSM is respectively classified into five areas with very high, high, moderate, low and very low susceptible levels; (3) some reasonable grid units from the areas with very high susceptible level are selected as new landslide samples to expand the original landslide samples; (4) reasonable non-landslide samples are selected from the areas with very low susceptible level; and (5) the expanded landslide samples, reasonable selected non-landslide samples and related environmental factors are put into the MLP once again to predict the final LSM. The Xunwu County of Jiangxi Province in China is selected as the study area. Conventional supervised machine learning (i.e. MLP) and unsupervised machine learning (i.e. K-means clustering model) are selected for comparisons. The comparative results indicate that the SSMLP model has a considerably higher LSP performance than the MLP and K-means clustering in Xunwu County. The SSMLP model successfully addresses the drawbacks existed in the conventional machine learning for LSP.

Landslides are one type of serious geological hazard which cause immense losses of local life and property. Landslide susceptibility prediction (LSP) can be used to determine the spatial probability of landslide occurrence in a certain area. It is important to implement LSP for landslide hazard prevention and reduction. This study developed a particle-swarm-optimized multilayer perceptron (PSO-MLP) model for LSP implementation to overcome the drawbacks of the conventional gradient descent algorithm and to determine the optimal structural parameters of MLP. Shicheng County in Jiangxi Province of China was used as the study area. In total, 369 landslides, randomly selected non-landslides, and 14 landslide-related predisposing factors were used to train and test the present PSO-MLP model and three other comparative models (an MLP-only model with the gradient descent algorithm, a back-propagation neural network (BPNN), and an information value (IV) model). The results showed that the PSO-MLP model had the most accurate prediction performance (area under the receiver operating characteristic curve (AUC) of 0.822 and frequency ratio (FR) accuracy of 0.856) compared with the MLP-only (0.791 and 0.829), BPNN (0.800 and 0.840), and IV (0.788 and 0.824) models. It can be concluded that the proposed PSO-MLP model addresses the drawbacks of the MLP-only model well and performs better than conventional artificial neural networks (ANNs) and statistical models. The spatial probability distribution law of landslide occurrence in Shicheng County was well revealed by the landslide susceptibility map produced using the PSO-MLP model. Furthermore, the present PSO-MLP model may have higher prediction and classification performances in some other fields compared with conventional ANNs and statistical models.

Poyang Lake is the largest freshwater lake in China, with a wide area and abundant species resources. It is a serious issue to protect and monitor the water quality of Poyang lake. This paper proposes to use principal component analysis (PCA) to evaluate the water pollution index of Poyang Lake. The input variables of PCA are the weekly monitoring water pollution factors including dissolved oxygen (DO), chemical oxygen demand (CODMn) and NH4+-N. The water quality monitoring station is in Hukou County of China from 2004 to 2014. Finally, a series of new water pollution indexes are generated by PCA to reflect the change characteristics of lake water pollution. The results can provide support for the comprehensive evaluation of lake water quality. Meanwhile, the results also discuss the variation in water pollution, which is practical and innovative.

In order to accurately quantify the terrain complexity, a simple and accurate terrain complexity assessment (TCA) model is proposed. Taking Ningdu county in Jiangxi Province of China as an example, firstly, six terrain factors (named slope, topographic relief degree, surface cutting depth, surface roughness, elevation variation coefficient and topographic factors) of Ningdu county are extracted based on the Digital Elevation Model (DEM) with 30 m resolution and ARCGIS 10.2 software. Secondly, terrain complexity indexes of Ningdu County are obtained using k-means clustering. Results show that a current and effective spatial distribution characteristic of topographic complexity in Ningdu county is produced, and the very low and low terrain complexity indexes account for 33.28%, 28.35% respectively. The terrain complexity can be evaluated effectively by k-means clustering model. The terrain complexity can be provided for environmental protection and land use planning.

The landslide susceptibility prediction(LSP) is of great importance to the prevention and control of regional landslide geology disasters. Taking Ningdu County of Jiangxi province as an case, this study obtains a total of 297 landslide locations in the study area and selects ten conditioning factors (elevation, slope aspect, slope, profile curvature, plan curvature, topographic relief, distance to rivers, lithology, NDVI, NDBI). The information value model(IVM) is used to predict the landslide susceptibility and the receiver operating characteristic curve (ROC) is adopted to evaluate the prediction accuracy of IVM. The result shows that the area under ROC (AUC) value of IVM is 0.838. It can be seen that IVM has a good prediction accuracy and also obtains a reasonable distribution characteristics of landslide susceptibility.

Summary Grain weight is the most important component of rice yield and is mainly determined by grain size, which is generally controlled by quantitative trait loci (QTLs). Although numerous QTLs that regulate grain weight have been identified, the genetic network that controls grain size remains unclear. Herein, we report the cloning and functional analysis of a dominant QTL, grain length and width 2 (GLW2), which positively regulates grain weight by simultaneously increasing grain length and width. The GLW2 locus encodes OsGRF4 (growth‐regulating factor 4) and is regulated by the microRNA miR396c in vivo. The mutation in OsGRF4 perturbs the OsmiR396 target regulation of OsGRF4, generating a larger grain size and enhanced grain yield. We also demonstrate that OsGIF1 (GRF‐interacting factors 1) directly interacts with OsGRF4, and increasing its expression improves grain size. Our results suggest that the miR396c‐OsGRF4‐OsGIF1 regulatory module plays an important role in grain size determination and holds implications for rice yield improvement.

Background Recently, the use of traditional Chinese medicine (TCM) has become more generally accepted, including by the Food and Drug Administration. To expand the use of TCM worldwide, it is important to study the molecular mechanisms by which TCM and its active ingredients produce effects. Gastrodin is an active ingredient from Gastrodia elata Blume . It is reported that gastrodin has neuroprotective function in Parkinson’s disease. But its mechanisms of neuroprotection remain not clear in PD. Here, we build two C. elegans PD model using 6-OHDA and transgenic animal to observe the changes of PD worms treated with or without gastrodin to confirm the function of gastrodin, then utilize mutant worms to investigate DAF-2/DAF-16 signaling pathway, and finally verify the mechanism of gastrodin in PD. Results Gastrodin attenuates the accumulation of α-synuclein and the injury of dopaminergic neurons, improves chemotaxis behavior in Parkinson’s disease models, then recovers chemotaxis behavior by insulin-like pathway. DAF-2/DAF-16 is required for neuroprotective effect of dopamine neuron in PD. Conclusions Our study demonstrated that gastrodin rescued dopaminergic neurons and reduced accumulation of α-synuclein protein, and the activity of gastrodin against Parkinson’s disease depended on the insulin-like DAF-2/DAF-16 signaling pathway. Our findings revealed that this insulin-like pathway mediates neuroprotection of gastrodin in a Parkinson’s disease model.

Chinese bayberry ( Morella rubra ), the most economically important fruit tree in the Myricaceae family, is a rich source of natural flavonoids. Recently the Chinese bayberry genome has been sequenced, and this provides an opportunity to investigate the organization and evolutionary characteristics of MrMYB genes from a whole genome view. In the present study, we performed the genome-wide analysis of MYB genes in Chinese bayberry and identified 174 MrMYB transcription factors (TFs), including 122 R2R3-MYBs, 43 1R-MYBs, two 3R-MYBs, one 4R-MYB, and six atypical MYBs. Collinearity analysis indicated that both syntenic and tandem duplications contributed to expansion of the MrMYB gene family. Analysis of transcript levels revealed the distinct expression patterns of different MrMYB genes, and those which may play important roles in leaf and flower development. Through phylogenetic analysis and correlation analyses, nine MrMYB TFs were selected as candidates regulating flavonoid biosynthesis. By using dual-luciferase assays, MrMYB12 was shown to trans-activate the MrFLS1 promoter, and MrMYB39 and MrMYB58a trans-activated the MrLAR1 promoter. In addition, overexpression of 35S:MrMYB12 caused a significant increase in flavonol contents and induced the expression of NtCHS , NtF3H , and NtFLS in transgenic tobacco leaves and flowers and significantly reduced anthocyanin accumulation, resulting in pale-pink or pure white flowers. This indicates that MrMYB12 redirected the flux away from anthocyanin biosynthesis resulting in higher flavonol content. The present study provides valuable information for understanding the classification, gene and motif structure, evolution and predicted functions of the MrMYB gene family and identifies MYBs regulating different aspects of flavonoid biosynthesis in Chinese bayberry.

Neurodegenerative diseases (NDs) are characterized by progressive degeneration and necrosis of neurons, including Alzheimer's disease, Parkinson's disease, Huntington's disease and others. There are no existing therapies that correct the progression of these diseases, and current therapies provide merely symptomatic relief. The use of polysaccharides has received significant attention due to extensive biological activities and application prospects. Previous studies suggest that the polysaccharides as a candidate participate in neuronal protection and protect against NDs. In this review, we demonstrate that various polysaccharides mediate NDs, and share several common mechanisms characterized by autophagy, apoptosis, neuroinflammation, oxidative stress, mitochondrial dysfunction in PD and AD. Furthermore, this review reveals potential role of polysaccharides in vitro and in vivo models of NDs, and highlights the contributions of polysaccharides and prospects of their mechanism studies for the treatment of NDs. Finally, we suggest some remaining questions for the field and areas for new development.

The use of fatty livers in liver transplantation has emerged as a crucial strategy to expand the pool of donor livers; however, fatty livers are more sensitive to ischemia‒reperfusion injury (IRI). Excessive congenital inflammatory responses are crucial in IRI. Hypothermic oxygenated perfusion (HOPE) is a novel organ preservation technique that may improve marginal donor liver quality by reducing the inflammatory response. Tissue factor pathway inhibitor-2 (TFPI2) and CAP-Gly domain-containing linker protein 1 (CLIP1) exhibit modulatory effects on the inflammatory response. However, the underlying mechanisms of HOPE in fatty liver and the effects of TFPI2 and CLIP1 in fatty liver IRI remain unclear. Here, we aimed to explore the impact of HOPE on the inflammatory response in a rat model of fatty liver IRI and the mechanisms of action of TFPI2 and CLIP1. HOPE significantly reduces liver injury, especially the inflammatory response, and alleviates damage to hepatocytes and endothelial cells. Mechanistically, HOPE exerts its effects by inhibiting TFPI2, and CLIP1 can rescue the damaging effects of TFPI2. Moreover, HOPE promoted the ubiquitination and subsequent degradation of Toll/interleukin-1 receptor domain-containing adapter protein (TIRAP) by regulating the binding of R24 of the KD1 domain of TFPI2 with CLIP1, thereby negatively regulating the TLR4/NF-κB-mediated inflammatory response and reducing IRI. Furthermore, TFPI2 expression increased and CLIP1 expression decreased following cold ischemia in human fatty livers. Overall, our results suggest that targeting the inflammatory response by modulating the TFPI2/CLIP1/TIRAP signaling pathway via HOPE represents a potential therapeutic approach to ameliorate IRI during fatty liver transplantation. Targeting Inflammation Enhances Fatty Liver Transplant Outcomes Liver transplantation is the only effective treatment for end-stage liver disease, but donor organ shortages limit its progress. Researchers found that fatty livers, which make up 15-30% of donations, are more prone to damage during transplantation. In this study, the researchers used a rat model to explore how hypothermic oxygenated perfusion (HOPE) affects fatty liver transplants. HOPE is a technique where the liver is preserved at low temperatures with oxygenated fluid. They divided rats into three groups: sham, cold storage (CS), and HOPE. Results showed that HOPE significantly reduces liver injury, especially the inflammatory response, and alleviates oxidative stress to improve liver function. The researchers concluded that HOPE can protect fatty livers during transplantation by inhibiting inflammation. Future studies could explore HOPE’s potential in human liver transplants. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.