Semantic uncertainty Guided Cross-Transformer for enhanced macular edema segmentation in OCT images.

Macular edema, a prevalent ocular complication observed in various retinal diseases, can lead to significant vision loss or blindness, necessitating accurate and timely diagnosis. Despite the potential of deep learning for segmentation of macular edema, challenges persist in accurately identifying lesion boundaries, especially in low-contrast and noisy regions, and in distinguishing between Inner Retinal Fluid (IRF), Sub-Retinal Fluid (SRF), and Pigment Epithelial Detachment (PED) lesions. To address these challenges, we present a novel approach, termed Semantic Uncertainty Guided Cross-Transformer Network (SuGCTNet), for the simultaneous segmentation of multi-class macular edema. Our proposed method comprises two key components, the semantic uncertainty guided attention module (SuGAM) and the Cross-Transformer module (CTM). The SuGAM module utilizes semantic uncertainty to allocate additional attention to regions with semantic ambiguity, improves the segmentation performance of these challenging areas. On the other hand, the CTM module capitalizes on both uncertainty information and multi-scale image features to enhance the overall continuity of the segmentation process, effectively minimizing feature confusion among different lesion types. Rigorous evaluation on public datasets and various OCT imaging device data demonstrates the superior performance of our proposed method compared to state-of-the-art approaches, highlighting its potential as a valuable tool for improving the accuracy and reproducibility of macular edema segmentation in clinical settings, and ultimately aiding in the early detection and diagnosis of macular edema-related diseases and associated retinal conditions.

4-Ethylphenol, A Volatile Organic Compound Produced by Disease-Resistant Soybean, Is a Potential Botanical Agrochemical Against Oomycetes.

Oomycetes, represented by Phytophthora, are seriously harmful to agricultural production, resulting in a decline in grain quality and agricultural products and causing great economic losses. Integrated management of oomycete diseases is becoming more challenging, and plant derivatives represent effective alternatives to synthetic chemicals as novel crop protection solutions. Biologically active secondary metabolites are rapidly synthesized and released by plants in response to biotic stress caused by herbivores or insects, as well as pathogens. In this study, we identified groups of volatile organic compounds (VOCs) from soybean plants inoculated with Phytophthora sojae, the causal agent of soybean root rot. 4-Ethylphenol was present among the identified VOCs and was induced in the incompatible interaction between the plants and the pathogen. 4-Ethylphenol inhibited the growth of P. sojae and Phytophthora nicotianae and had toxicity to sporangia formation and zoospore germination by destroying the pathogen cell membrane; it had a good control effect on soybean root rot and tobacco black shank in the safe concentration range. Furthermore, 4-Ethylphenol had a potent antifungal activity against three soil-borne phytopathogenic fungi, Rhizoctonia solani, Fusarium graminearum, and Gaeumannomyces graminis var tritici, and four forma specialis of Fusarium oxysporum, which suggest a potential to be an eco-friendly biological control agent.

Lauric Acid Is a Potent Biological Control Agent That Damages the Cell Membrane of Phytophthora sojae.

Sustainable management of plant pathogens is becoming more challenging, and novel solutions are needed. Plant biologically active secondary metabolites are important sources of novel crop protection chemistry. Effective individual compounds of these natural products have the potential to be successful new agrochemicals. In this study, we identified lauric acid (LA) from soybean defense leaf volatiles. LA inhibited the growth of Phytophthora sojae, the causal agent of soybean root rot. It influenced mycelial development, sporangium formation, and zoospore generation and germination by damaging the P. sojae cell membrane. Additionally, we showed that LA and several of its derivatives, such as glycerol monolaurate (GML), had similar biological activities. Both LA and GML were safe to soybean plants when used at less than 0.3 g a.i./plant and could promote soybean growth, implying their potential as eco-friendly biological control agents.