Dynamic spatial network simulation accounting for multiple ecological factors provides practical recommendations for biosecurity early detection and rapid response (EDRR) strategies.

Background: Globally the spread of invasive pests is being facilitated by increased human mobility and climate change. Simulation modelling can help assess biosecurity strategies for early detection and rapid response (EDRR), but has struggled to account for important factors in the invasion process, such as spatial and temporal variability in habitat suitability and connectivity; population dynamics; and multiple dispersal pathways. We developed a novel dynamic spatial network simulation approach based on spatial network theory that enables integration of a wider range of spatio-temporal factors than previous studies, calibrated it against extensive historical trapping data, and applied it to comprehensively analyse the EDRR strategy for Oriental fruit fly (Bactrocera dorsalis; OFF) in northern Australia.

Multiparametric MRI radiomics for predicting disease-free survival and high-risk histopathological features for tumor recurrence in endometrial cancer.

Background: Current preoperative imaging is insufficient to predict survival and tumor recurrence in endometrial cancer (EC), necessitating invasive procedures for risk stratification.

Purpose: To establish a multiparametric MRI radiomics model for predicting disease-free survival (DFS) and high-risk histopathologic features in EC.

Methods: This retrospective study included 71 patients with histopathology-proven EC and preoperative MRI over a 10-year period.

The role of protein kinase D (PKD) in obesity: Lessons from the heart and other tissues.

Obesity causes a range of tissue dysfunctions that increases the risk for morbidity and mortality. Protein kinase D (PKD) represents a family of stress-activated intracellular signalling proteins that regulate essential processes such as cell proliferation and differentiation, cell survival, and exocytosis. Evidence suggests that PKD regulates the cellular adaptations to the obese environment in metabolically important tissues and drives the development of a variety of diseases.

Simulated herbicide mixtures delay both specialist monogenic and generalist polygenic resistance evolution in weeds.

Background: Evolution of herbicide-resistant weed populations is a major challenge to world food production. Using different herbicides in rotation and/or using different herbicides together as mixtures are strategies that may delay the selection of resistance. This study used simulation modelling to investigate whether mixtures and rotations can delay the selection of both generalist polygenic and specialist monogenic herbicide resistance, and whether these strategies are more likely to lead to the selection of generalist resistance in weed types with varying biological characteristics.