Exploring the Dynamic Invasion Pattern of the Black-Headed Fall Webworm in China: Susceptibility to Topography, Vegetation, and Human Activities.

The fall webworm (FWW), H. cunea (Drury) (Lepidoptera: Erebidae: Arctiidae), is an extremely high-risk globally invasive pest. Understanding the invasion dynamics of invasive pests and identifying the critical factors that promote their spread is essential for devising practical and efficient strategies for their control and management. The invasion dynamics of the FWW and its influencing factors were analyzed using standard deviation ellipse and spatial autocorrelation methods. The analysis was based on statistical data on the occurrence of the FWW in China. The dissemination pattern of the FWW between 1979 and 2022 followed a sequence of "invasion-occurrence-transmission-outbreak", spreading progressively from coastal to inland regions. Furthermore, areas with high nighttime light values, abundant ports, and non-forested areas with low vegetation cover at altitudes below 500 m were more likely to be inhabited by the black-headed FWW. The dynamic invasion pattern and the driving factors associated with the fall webworm (FWW) provide critical insights for future FWW management strategies. These strategies serve not only to regulate the dissemination of insects and diminish migratory tendencies but also to guarantee the implementation of efficient early detection systems and prompt response measures.

Exploring the Close-Range Detection of UAV-Based Images on Pine Wilt Disease by an Improved Deep Learning Method.

Pine wilt disease (PWD) is a significantly destructive forest disease. To control the spread of PWD, an urgent need exists for a real-time and efficient method to detect infected trees. However, existing object detection models have often faced challenges in balancing lightweight design and accuracy, particularly in complex mixed forests. To address this, an improvement was made to the YOLOv5s (You Only Look Once version 5s) algorithm, resulting in a real-time and efficient model named PWD-YOLO. First, a lightweight backbone was constructed, composed of multiple connected RepVGG Blocks, significantly enhancing the model's inference speed. Second, a C2fCA module was designed to incorporate rich gradient information flow and concentrate on key features, thereby preserving more detailed characteristics of PWD-infected trees. In addition, the GSConv network was utilized instead of conventional convolutions to reduce network complexity. Last, the Bidirectional Feature Pyramid Network strategy was used to enhance the propagation and sharing of multiscale features. The results demonstrate that on a self-built dataset, PWD-YOLO surpasses existing object detection models with respective measurements of model size (2.7 MB), computational complexity (3.5 GFLOPs), parameter volume (1.09 MB), and speed (98.0 frames/s). The Precision, Recall, and F1-score on the test set are 92.5%, 95.3%, and 93.9%, respectively, which confirms the effectiveness of the proposed method. It provides reliable technical support for daily monitoring and clearing of infected trees by forestry management departments.

Vaccination with DNA encoding ES 43-kDa /45-kDa antigens significantly reduces Trichinella spiralis infection in mice.

Trichinella spiralis is an intestinal nematode parasite that can cause trichinellosis in humans and animals worldwide. The most important known hosts of T. spiralis are pigs, horses, dogs and cats. Pork and its products are the main sources of infection in human trichinellosis. Vaccines against these infections are urgently needed. In this study, the genes encoding the 43-kDa or 45-kDa glycoprotein present in the excretory-secretory (ES) products from T. spiralis muscle larvae (ML) were cloned into the eukaryotic expression vector pVAX1, resulting plasmids pVAX1-Ts43 and pVAX1-Ts45, respectively. Then BALB/c mice were intramuscularly immunized with the DNA vaccine pVAX1-Ts43, pVAX1-Ts45, or both to evaluate their immunogenicity and host protective potential. After the third immunization, mice of each group were challenged with 300 T. spiralis ML. The results showed that the mice immunized with the DNA vaccine pVAX1-Ts43 or pVAX1-Ts45 developed significant numbers of FAS+PNA+ B220+ B cells indicating the formation of the germinal centers (GCs), IFN-γ-secreting (mesenteric lymph nodes, MLN) cells, and IL-4-, and IL-10-secreting splenocytes. Mice immunized with the pVAX1-Ts43 or pVAX1-Ts45 vaccine elicited partial protective immunity against challenge infections with T. spiralis as shown by significant reduction in ML. Most notably, the combined immunity of pVAX1-Ts43 and pVAX1-Ts45 induced better immune responses than either of the DNA vaccines given alone and provided as high as 75.9% reductions in muscle larval burden. These results suggest that the plasmid DNA encoding the 43-kDa or 45-kDa glycoprotein could be considered as a potential vaccine candidate against T. Spiraling infection.