Accurate information concerning the spatial distribution of invasive alien species’ habitats is essential for invasive species prevention and management, and ecological sustainability. Currently, nationwide identification of suitable habitats for the highly destructive and potentially invasive weed, Solanum rostratum Dunal (S. rostratum), poses a series of challenges. Simultaneously, research on potential future invasion areas and likely directions of spread has not received adequate attention. This study, based on species occurrence data and multi-dimensional environmental variables constructed from multi-source remote sensing data, utilized Principal Component Analysis (PCA) in combination with the Maxent model to effectively model the current and future potential habitat distribution of S. rostratum in China, while quantitatively assessing the various factors influencing its distribution. Research findings indicate that the current suitable habitat area of S. rostratum covers 1.3952 million km², all of which is located in northern China. As the trend of climate warming persists, the potential habitat suitability range of S. rostratum is projected to shift southward and expand in the future; while still predominantly located in northern China, it will have varying degrees of expansion at different time frames. Notably, during the period from 2040 to 2061, under the SSP1-2.6 scenario, the habitat area exhibits the most significant increase, surpassing the current scenario by 19.23%. Furthermore, attribution analysis based on PCA inverse transformation reveals that a combination of soil, climate, spatial, humanistic, and topographic variables collectively influence the suitability of S. rostratum habitats, with soil factors, in particular, playing a dominant role and contributing up to 75.85%. This study identifies target areas for the management and control of S. rostratum, providing valuable insights into factor selection and variable screening methods in species distribution modeling (SDM).

Pine wilt disease (PWD) is regarded as one of the most serious conifer diseases affecting pines worldwide. To date, an in-depth study of the driving mechanisms behind short-distance PWD spread is lacking. In this study, we collected PWD forest subcompartment data in Fushun, China, and analysed the effects of factors on the short-distance transmission of PWD; the analysed factors included the number of neighbouring PWD-infected forest subcompartments, the canopy density, the slope direction, and different traffic corridor types. The results suggested that the spatial spill-over effect of nearby PWD-infected subcompartments contributed the most to short-distance PWD transmission, with an impact of up to 78% on its propagation. The impact of the traffic corridor was 20%. With the help of a beetle vector, PWD can spread to nearby forest subcompartments, and this spatial PWD spill-over effect showed a linearly decaying trend as the distance to neighbouring subcompartments increased. Different traffic corridor types exhibited significant PWD transmission impact differences. County roadways and highways had great impacts, while others had relatively small impacts. For each additional 100 m of distance from a county roadway, highway, national, or provincial roadway, the PWD infection risks in forest subcompartments were reduced by 18%, 11%, 5%, and 3%, respectively. In this study, we quantified the influence of driving factors on the short-distance spread of PWD and provided a theoretical basis for the control of PWD transmission; the results obtained herein are critical for maintaining the ecological security of forests, promoting ecological forest management and stabilising forest carbon sinks.

Multispectral object detection is a fundamental task with an extensive range of practical implications. In particular, combining visible (RGB) and infrared (IR) images can offer complementary information that enhances detection performance in different weather scenarios. However, the existing methods generally involve aligning features across modalities and require proposals for the two-stage detectors, which are often slow and unsuitable for large-scale applications. To overcome this challenge, we introduce a novel one-stage oriented detector for RGB-infrared object detection called the Layer-wise Cross-Modality calibration and Aggregation (LCMA) detector. LCMA employs a layer-wise strategy to achieve cross-modality alignment by using the proposed inter-modality spatial-reduction attention. Moreover, we design Gated Coupled Filter in each layer to capture semantically meaningful features while ensuring that well-aligned and foreground object information is obtained before forwarding them to the detection head. This relieves the need for a region proposal step for the alignment, enabling direct category and bounding box predictions in a unified one-stage oriented detector. Extensive experiments on two challenging datasets demonstrate that the proposed LCMA outperforms state-of-the-art methods in terms of both accuracy and computational efficiency, which implies the efficacy of our approach in exploiting multi-modality information for robust and efficient multispectral object detection.

The Hetao Irrigation District is an important arid-oasis agricultural system in the Yellow River Basin, where water scarcity has become a major constraint on high-quality regional development and irrigation water use dominates the district’s water-use structure. Irrigation water resources carrying capacity represents the application of the broader concept of water resources carrying capacity to irrigation systems. Existing studies have largely overlooked long-term assessments of irrigation water resources carrying capacity and the identification of its dominant patterns of variation at the irrigation-district scale. This study aimed to evaluate irrigation water resources carrying capacity in the Hetao Irrigation District from 2001 to 2023 and identify its dominant patterns of variation. An evaluation indicator system was developed, and a TOPSIS model incorporating combined subjective–objective weighting was used to assess long-term changes in carrying status, while principal component analysis was applied to identify the dominant patterns of variation. The results showed that improvement in the irrigation water-use efficiency subsystem partially offset the adverse effects of the decline in the water availability subsystem, resulting in an overall improvement in carrying status. Linhe District ranked highest among the county-level units, whereas Dengkou County ranked lowest. The variation in carrying capacity was summarized into three dimensions: joint variation in water availability and water-use scale; a mixed pattern linking irrigation water-use intensity, the degree of water resource utilization, and groundwater conditions; and variation in effective irrigation coverage. By integrating long-term carrying-status assessment with the identification of dominant patterns of variation, this study reveals a compensatory relationship between improved irrigation water-use efficiency and declining water availability, thereby providing a new perspective on carrying-status evolution at the irrigation-district scale.

Background: Gastric cancer (GC) ranks the fifth most common cancer and the fourth most frequent cause of cancer-related deaths. Genomically stable gastric cancers (GSGCs) represent 20% of all GCs and GSGC patients have the worst prognosis among all GC subtypes. Although two HER2-targeted antibody-drug conjugates (ADCs), RC48 and DS8201, have shown promising clinical efficacies, most GSGC patients do not benefit from these ADCs due to the infrequent and heterogeneous HER2 expression. Therefore, there remains a significant and unmet medical need for developing novel ADCs targeting GSGC tumors. Methods: In this presented study, a quantitative and unbiased approach was first used to identify potential targets for GSGC in a panel of human GSGC cell lines in reference with two normal human gastric epithelial cells. Cell membrane localizations of potential targets on GSGC cell lines were determined by immunofluorescent (IF) staining. To correlate it with clinically-relevant GSGC tumor samples, immunohistochemical (IHC) staining of potential targets were performed in human diffuse GC tumor tissues along with normal gastric tissues. Next, GSGC cellular internalization capability of antibodies against potential targets was evaluated. Then, an optimized target was selected for developing GSGC-targeted ADCs. A series of ADC formulations with different linkers and payloads were constructed and characterized. Their anti-tumor activities against GSGC cell lines were subsequently screened in order to identify the optimized ADC formulation. Eventually, the anti-tumor activity and biosafety profile of the optimized ADC formulation were determined in suppressing tumor growth, progression and metastasis by using established orthotopic and peritoneal metastasis models of GSGC. Results: We first identified CD54 as a potential molecular target for human GSGCs using comparative flow cytometric analysis. We next evaluated its potential as an ADC target for GSGC-targeted therapy by determining its overexpression levels, cell membrane localizations, and cell internalization activity in GSGC cells. Furthermore, we constructed and characterized a panel of CD54-targeted ADCs and identified an optimized ADC formulation by quantitatively determining their half maximum inhibitory concentrations (IC50s) and validated its anti-tumor efficacy against GSGC tumors. Meanwhile, there was no evidence to indicate histopathological damages to normal organs in the optimized ADC treated group. Conclusions: In this study, we identified a molecular target for GSGC using an unbiased and quantitative screening assay and explored its potential application in developing GSGC-targeted ADCs. In order to maximize its efficacy, we optimized the ADC formulations against GSGC cells using different ADC linkers and payloads. Our study provides a promising targeted therapeutic candidate for the clinical treatment of GSGC. Citation Format: Rui Xu, Li Yuan, Xiao-Qing Guan, Shi-Li Yao, Bing Zhu, Tong Yang, Chun Liu, Peng Guo, Jiang-Jiang Qin, Xiang-Dong Cheng. Rationally developing antibody drug conjugates targeting genomically stable gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5293.